diff --git a/docs/latest/containers/alerts.html b/docs/latest/containers/alerts.html index 9a79b3f84e..451e579be7 100644 --- a/docs/latest/containers/alerts.html +++ b/docs/latest/containers/alerts.html @@ -2179,7 +2179,7 @@ 55.627 l 55.6165,55.627 -231.245496,231.24803 c -127.185,127.1864 -231.5279,231.248 -231.873,231.248 -0.3451,0 -104.688, -104.0616 -231.873,-231.248 z - " fill="currentColor">

PHDI Alerts Service (1.2.6)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

PHDI Alerts Container

This Docker container provides a simple API for sending alerts via SMS, Slack, or Microsoft Teams. It can be run as a local service or deployed as part of a full pipeline using PHDI Building Blocks as in CDCgov/phdi-azure.

+ " fill="currentColor">

PHDI Alerts Service (1.2.7)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

PHDI Alerts Container

This Docker container provides a simple API for sending alerts via SMS, Slack, or Microsoft Teams. It can be run as a local service or deployed as part of a full pipeline using PHDI Building Blocks as in CDCgov/phdi-azure.

Usage

Some manual steps need to be taken to enable alerts in your particular environment.

SMS

In order to send text messages, you'll need to create an Azure Communication Service. Follow this quickstart guide to set up the resource. Once created, you'll need to provide the name of your resource as an environment variable (COMMUNICATION_SERVICE_NAME) to the container.

@@ -2241,7 +2241,7 @@

Sample request

Request samples

Content type
application/json
{
  • "message": "string"
}

Response samples

Content type
application/json
null
+ + + + + +
API docs by Redocly

TEFCA Viewer (1.1.11)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Use Case Query

path Parameters
use_case
required
string (Use Case)
Enum: "social-determinants" "newborn-screening" "syphilis" "cancer"
Request Body schema: application/json
fhir_server
required
string (Fhir Server)
Enum: "meld" "ehealthexchange"
first_name
required
string (First Name)
last_name
required
string (Last Name)
dob
required
string (Dob)
mrn
string (Mrn)
phone
string (Phone)
street
string (Street)
city
string (City)
state
string (State)
zip
string (Zip)

Responses

Request samples

Content type
application/json
{
  • "fhir_server": "meld",
  • "first_name": "string",
  • "last_name": "string",
  • "dob": "string",
  • "mrn": "string",
  • "phone": "string",
  • "street": "string",
  • "city": "string",
  • "state": "string",
  • "zip": "string"
}

Response samples

Content type
application/json
null

Root

Responses

Response samples

Content type
application/json
null

Health Check

Check service status. If an HTTP 200 status code is returned along with +'{"status": "OK"}' then the FHIR conversion service is available and running +properly.

+

Responses

Response samples

Content type
application/json
null
+ + + + \ No newline at end of file diff --git a/docs/latest/containers/validation.html b/docs/latest/containers/validation.html index ebbc472c6a..6b33e4de52 100644 --- a/docs/latest/containers/validation.html +++ b/docs/latest/containers/validation.html @@ -2186,7 +2186,7 @@ 55.627 l 55.6165,55.627 -231.245496,231.24803 c -127.185,127.1864 -231.5279,231.248 -231.873,231.248 -0.3451,0 -104.688, -104.0616 -231.873,-231.248 z - " fill="currentColor">

PHDI Validation Service (1.2.6)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Getting Started with the PHDI Validation Service

Introduction

+ " fill="currentColor">

PHDI Validation Service (1.2.7)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Getting Started with the PHDI Validation Service

Introduction

The PHDI validation service offers a REST API for validating health care messages (e.g., whether health care messages are in the proper format and contain user-defined fields of interest).

Running the Validation Service

The validation service can be run using Docker (or any other OCI container runtime e.g., Podman), or directly from the Python source code.

@@ -2235,7 +2235,7 @@

The API

Request samples

Content type
application/json
{
  • "message_type": "ecr",
  • "include_error_types": "string",
  • "message": "string",
  • "rr_data": "string"
}

Response samples

Content type
application/json
Example
{
  • "message_valid": "True",
  • "validation_results": {
    }
}
+ + + + + +
API docs by Redocly

PHDI Alerts Service (1.2.7)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

PHDI Alerts Container

This Docker container provides a simple API for sending alerts via SMS, Slack, or Microsoft Teams. It can be run as a local service or deployed as part of a full pipeline using PHDI Building Blocks as in CDCgov/phdi-azure.

+

Usage

Some manual steps need to be taken to enable alerts in your particular environment.

+

SMS

+

In order to send text messages, you'll need to create an Azure Communication Service. Follow this quickstart guide to set up the resource. Once created, you'll need to provide the name of your resource as an environment variable (COMMUNICATION_SERVICE_NAME) to the container.

+

The first time you make a call to /sms-alert, the container will purchase a phone number to use for sending text messages. This will charge your Azure account $2/month to reserve the phone number.

+

Support for other SMS providers besides Azure are coming soon!

+

Sample request

+

POST /sms-alert

+
{
+    "phone_number": "+19168675309",
+    "message": "Hi this is a test"
+}
+
+

Slack

+

To send alerts to your Slack workspace, you'll need to create a Slack application. Follow this guide to create the Slack app, giving it a name you'll recognize, such as PHDI Alerts. The OAuth access token must be provided to the container as an environment variable (SLACK_BOT_TOKEN). You must also invite the application to any channel you wish to alert (type /invite in the channel and choose "Add apps to channel"). To get the ID of a channel, right click the channel name and choose "View channel details". The ID is at the bottom of the modal that appears.

+

Sample request

+

POST /slack-alert

+
{
+    "channel_id": "C04GKBFMGRM",
+    "message": "Hi this is a test"
+}
+
+

Microsoft Teams

+

To send alerts to Microsoft Teams, you'll need to create a webhook in the channel you wish to alert. To add an incoming webhook to a Teams channel:

+
    +
  1. Navigate to the channel where you want to add the webhook and select (•••) Connectors from the top navigation bar.
    2. +
  2. Search for Incoming Webhook, and add it.
    3. +
  3. Click Configure and provide a name for your webhook.
    4. +
  4. Copy the URL which appears and click "OK".
    5. +
+

Provide this URL as an environment variable (TEAMS_WEBHOOK_URL) to the container.

+

Sample request

+

POST /teams-alert

+
{
+    "message": "Hi this is a test"
+}
+
+

Health Check

Check service status. If an HTTP 200 status code is returned along with +'{"status": "OK"}' then the service is available and running properly.

+

Responses

Response samples

Content type
application/json
{
  • "status": "OK"
}

Sms Alert

Send an SMS alert to a phone number. +:param input: A JSON formated request body with schema specified by the + SmsAlertInput model.

+
Request Body schema: application/json
phone_number
required
string (Phone Number)

The phone number to send the alert to.

+
message
required
string (Message)

The message to send to the phone number.

+

Responses

Request samples

Content type
application/json
{
  • "phone_number": "string",
  • "message": "string"
}

Response samples

Content type
application/json
null

Slack Alert

Send a Slack alert to a channel. +:param input: A JSON formated request body with schema specified by the + SlackAlertInput model.

+
Request Body schema: application/json
channel_id
required
string (Channel Id)

The Slack channel ID to send the alert to.

+
message
required
string (Message)

The message to send to the Slack channel.

+

Responses

Request samples

Content type
application/json
{
  • "channel_id": "string",
  • "message": "string"
}

Response samples

Content type
application/json
null

Teams Alert

Send a Teams alert to a channel. +:param input: A JSON formated request body with schema specified by the + TeamsAlertInput model.

+
Request Body schema: application/json
message
required
string (Message)

The message to send to the Teams channel.

+

Responses

Request samples

Content type
application/json
{
  • "message": "string"
}

Response samples

Content type
application/json
null
+ + + + \ No newline at end of file diff --git a/docs/v1.2.7/containers/fhir-converter.html b/docs/v1.2.7/containers/fhir-converter.html new file mode 100644 index 0000000000..2439a7c5d2 --- /dev/null +++ b/docs/v1.2.7/containers/fhir-converter.html @@ -0,0 +1,2355 @@ + + + + + + PHDI FHIR Converter Service + + + + + + + + + +
API docs by Redocly

PHDI FHIR Converter Service (0.0.1)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Getting started with the PHDI FHIR Conversion Service

This service relies on Microsoft's FHIR converter to convert messages.

+

If you plan to run the service via Docker, you can skip to Running with Docker. This container will automatically use the Microsoft FHIR converter without need for additional installation.

+

If you plan to run the service locally via Python, you'll need to install both the Microsoft FHIR Converter CLI and run the PHDI FHIR Converter service. Read on for installation instructions for both.

+

Microsoft FHIR Converter CLI Installation Guide

This document provides a guide for installing the Microsoft FHIR Converter as a Command Line Interface (CLI) tool on Windows, MacOS, and Linux systems, as well as a brief introduction to using the converter.

+

Using the .NET Framework

+

We will use the .NET SDK to build the FHIR Converter from source code. If you have already installed a .NET SDK, skip to Download and Build the FHIR Converter, otherwise follow the steps below to install it on your system.

+

To check if a .NET SDK is installed, try running dotnet --list-sdks. You should see an output message that lists the .NET SDK version you have installed, as well as where it's located. It should look something like the following, but note that the version number and filepath will differ depending on which operating system you use and when you installed the .NET SDK.

+
6.0.40 [C:\Program Files\dotnet\sdk]
+
+

If you see a message like Command 'dotnet' not found (MacOS and Linux) or The term 'dotnet' is not recognized as the name of a cmdlet, function, script file, or operable program (Windows), then .NET has not been installed. Additionally, if running dotnet --list-sdks does not produce any output, then you likely have the .NET runtime installed, but not the SDK. In either event, you should follow the instructions below to install the SDK.

+

Install the .NET SDK

+

The instructions for installing the .NET SDK will differ depending on whether you're using Windows, MacOS, or Linux. MacOS and Linux users will utilize the command line to install the software, while Windows users should use the installer. Instructions for both approaches are below.

+

MacOS and Linux

+
Download the .NET Install Script
+

Run wget https://dotnet.microsoft.com/download/dotnet/scripts/v1/dotnet-install.sh to download the .NET installation script from Microsoft. +From the directory containing the dotnet-install.sh file, run sh ./dotnet-install.sh to execute the script and install .NET. By default, this script installs the .NET SDK, which is perfect for our needs.

+

Note: Bash is required to run the script. If you are using a different shell, such as zsh, it is recommend to switch to using Bash.

+
Add .NET to the PATH Environment Variable
+

Finally, permanently add .NET to you PATH variable by running echo 'export PATH="$PATH:$HOME/.dotnet"' >> ~/.bashrc.

+
Confirm the Installation
+

Restart your shell with exec $SHELL and then run dotnet. If you get a response that looks like what is shown below, then .NET was installed successfully.

+
Usage: dotnet [options]
+Usage: dotnet [path-to-application]
+
+Options:  
+  -h|--help         Display help.  
+  --info            Display .NET Core information.  
+  --list-sdks       Display the installed SDKs.  
+  --list-runtimes   Display the installed runtimes.  
+
+path-to-application:  
+  The path to an application .dll file to execute.  
+
+

Windows

+
Install the .NET SDK
+

Navigate to https://dotnet.microsoft.com/en-us/download and click on the "Download .NET SDK x64" button. Note that the label may read slightly differently if you're using a 32-bit operating system. Clicking this button will download a file with a name similar to dotnet-sdk-6.0.400-win-x64.exe, but note that the name of your file may differ if a new version of the SDK has been released. The most important thing is to ensure that the file is for the dotnet-sdk and for Windows.

+

Open this file and follow the instructions that are presented to you. If you're asked if you should allow this program to make changes to your machine, select yes. Once the installer is finished, you'll be presented with a screen that summarizes what was installed and where it was saved. The default location should be "C:\Program Files\dotnet". Open File Explorer, navigate to the installation location (C:\Program Files\dotnet), open the "sdk" folder, and confirm that a folder exists with the .NET SDK version as its name.

+
Add .NET to the PATH Environment Variable
+

Open your Start Menu and type "Environment Variables" into the search bar. Select "Edit environment variables for your account" from the list of options that appear. In the top section labeled "User variables", click the variable called "Path" and then click the "Edit..." button. A new screen will pop up, and you should click the "New" button on the right-hand side. In the text box that is highlighted, enter "C:\Program Files\dotnet" (without the quotes). Hit enter, click "OK" to close the Path screen, and then click "OK" to close the Environment Variables screen.

+
Confirm the Installation
+

Open Powershell and run dotnet. If you get a response that looks like when is shown below, then .Net was installed successfully.

+
Usage: dotnet [options]
+Usage: dotnet [path-to-application]
+
+Options:  
+  -h|--help         Display help.  
+  --info            Display .NET Core information.  
+  --list-sdks       Display the installed SDKs.  
+  --list-runtimes   Display the installed runtimes.  
+
+path-to-application:  
+  The path to an application .dll file to execute.  
+
+

Download and Build the FHIR Converter

+

Get Microsoft FHIR Converter

+

Using whichever command line tool you are comfortable with (Powershell on Windows, or Terminal on Linux and MacOS), download the FHIR Converter source code from Github with the following command.

+
git clone https://github.com/microsoft/FHIR-Converter
+
+

This will install the most recent version of the tool. However, if you'd like to use a specific version, you can use a command like this one that specifically downloads the 5.0.4 release (most recent at the time of writing). +git clone https://github.com/microsoft/FHIR-Converter.git --branch v5.0.4 --single-branch

+

Build the FHIR Converter Tool

+

Navigate to the directory that was just created with the git clone command, which should be a directory named "FHIR-Converter" inside of your current directory, and run dotnet build.

+

Note: If you're using Windows, it's important to perform this action using Powershell instead of a tool like Git Bash. Due to Windows' use of the \ as its filepath seperator, other terminals can misinterpret the instructions and fail when trying to access directories.

+

Using the Microsoft FHIR Converter

+

Two examples have been provided below of using the FHIR Converter via the dotnet run function. Please note that -- is used to deliminate between arguments that should be passed to dotnet as opposed arguments that dotnet should be pass to the application, in this case the FHIR Converter, that it is being used to run. Additionaly, the -p option is only required when not calling dotnet run from the FHIR-Converter/src/Health.Fhir.Liquid.Converter.Tool/ directory. For additional information on dotnet run please refer to this documentation from Microsoft.

+

Message in File to FHIR

+

The following command can be used to convert a message from a file to FHIR. +dotnet run convert -p path-to-Microsoft.Health.Fhir.Liquid.Converter.Tool/ -- -d path-to-template subdirectory-for-message-type -r root-template -n path-to-file-to-be-converted -f path-to-output

+

Covert Message Content Directory to FHIR

+

The following command can be used to convert the contents of a message provided directly as a string to FHIR. +dotnet run convert -p path-to-Microsoft.Health.Fhir.Liquid.Converter.Tool/ -- -d path-to-template subdirectory-for-message-type -r root-template -c message-content -f path-to-output

+

Note: The use of -- in the command is to separate the command line parameters that are passed to .NET vs those that are passed to the FHIR Converter

+

Using an Alias

+

To avoid the need for typing dotnet run convert -p path-to-Microsoft.Health.Fhir.Liquid.Converter.Tool/ -- every time you'd like to convert HL7, it is recommended that you create an alias. Instructions for creating an alias on Windows, MacOS, and Linux can be found here, here, and here, respectively.

+

Running the PHDI FHIR Conversion Service

Once the Microsoft FHIR converter is installed, the FHIR conversion service can be run using Docker (or any other OCI container runtime e.g., Podman), or directly from the Python source code.

+ +

To run the FHIR conversion service with Docker follow these steps.

+
    +
  1. Confirm that you have Docker installed by running docker -v. If you do not see a response similar to what is shown below, follow these instructions to install Docker.
    ❯ docker -v
+Docker version 20.10.21, build baeda1f
+
    +
    2. +
  2. Download a copy of the Docker image from the PHDI repository by running docker pull ghcr.io/cdcgov/phdi/fhir-converter:latest.
    3. +
  3. Run the service with docker run -p 8080:8080 ghcr.io/cdcgov/phdi/fhir-converter:latest.
    4. +
+

Congratulations, the ingestion service should now be running on localhost:8080!

+

Running from Python Source Code

+

For local development, it may be preferred to run the service directly from Python. To do so, follow the steps below.

+
    +
  1. Ensure that both Git and Python 3.10 or higher are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/fhir-converter/.
    4. +
  4. Make a fresh virtual environment with python -m venv .venv.
    5. +
  5. Activate the virtual environment with source .venv/bin/activate (MacOS and Linux), venv\Scripts\activate (Windows Command Prompt), or .venv\Scripts\Activate.ps1 (Windows PowerShell).
    6. +
  6. Install all of the Python dependencies for the ingestion service with pip install -r requirements.txt into your virtual environment.
    7. +
  7. Run the FHIR Converter on localhost:8080 with python -m uvicorn app.main:app --host 0.0.0.0 --port 8080.
    8. +
+

Building the Docker Image

+

To build the Docker image for the FHIR conversion service from source code instead of downloading it from the PHDI repository, follow these steps.

+
    +
  1. Ensure that both Git and Docker are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/fhir-converter/.
    4. +
  4. Run docker build -t fhir-converter ..
    5. +
  5. Run the service with docker run -p 8080:8080 fhir-converter.
    6. +
+

Updating RCTC document

+

RCTC spreadsheet gets updated approximately every 6 months. The latest RCTC spreadsheet can be found on the eRDS Aims Platform, an account is required to download. Two output files are created, in which json_output_loc holds the Grouping List, and json_output_loc2 holds the Expansion List. +The script can be run by using the following command python3 rctc-to-json.py spreadsheet_input_loc json_output_loc json_output_loc2

+

License (for Microsoft FHIR Converter)

MIT License

+

Copyright (c) Microsoft Corporation. All rights reserved.

+

Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions:

+

The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software.

+

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE

+

Health Check

Check service status. If an HTTP 200 status code is returned along with +'{"status": "OK"}' then the FHIR conversion service is available and running +properly.

+

Responses

Response samples

Content type
application/json
null

Health Check

Check service status. If an HTTP 200 status code is returned along with +'{"status": "OK"}' then the FHIR conversion service is available and running +properly.

+

Responses

Response samples

Content type
application/json
null

Convert

Converts an HL7v2 or C-CDA message to FHIR format using the Microsoft FHIR +Converter CLI tool. When conversion is successful, a dictionary containing the +response from the FHIR Converter is returned.

+

In order to successfully call this function, the Microsoft FHIR Converter tool +must be installed. For information on how to do this, please refer to the +description.md file. The source code for the converter can be found at +https://github.com/microsoft/FHIR-Converter.

+
Request Body schema: application/json
input_data
required
string (Input Data)

The message to be converted as a string.

+
input_type
required
string (InputType)
Enum: "elr" "vxu" "ecr"

The type of message to be converted.

+
root_template
required
string (RootTemplate)
Enum: "ADT_A01" "ADT_A02" "ADT_A03" "ADT_A04" "ADT_A05" "ADT_A06" "ADT_A07" "ADT_A08" "ADT_A09" "ADT_A10" "ADT_A11" "ADT_A13" "ADT_A14" "ADT_A15" "ADT_A16" "ADT_A25" "ADT_A26" "ADT_A27" "ADT_A28" "ADT_A29" "ADT_A31" "ADT_A40" "ADT_A41" "ADT_A45" "ADT_A47" "ADT_A60" "BAR_P01" "BAR_P02" "BAR_P12" "DFT_P03" "DFT_P11" "MDM_T01" "MDM_T02" "MDM_T05" "MDM_T06" "MDM_T09" "MDM_T10" "OMG_O19" "OML_O21" "ORM_O01" "ORU_R01" "OUL_R22" "OUL_R23" "OUL_R24" "RDE_O11" "RDE_O25" "RDS_O13" "REF_I12" "REF_I14" "SIU_S12" "SIU_S13" "SIU_S14" "SIU_S15" "SIU_S16" "SIU_S17" "SIU_S26" "VXU_V04" "CCD" "EICR" "ELR" "ConsultationNote" "DischargeSummary" "Header" "HistoryandPhysical" "OperativeNote" "ProcedureNote" "ProgressNote" "ReferralNote" "TransferSummary"

Name of the liquid template within to be used for conversion.

+
rr_data
string (Rr Data)

If an eICR message, the accompanying Reportability Response data.

+

Responses

Request samples

Content type
application/json
{
  • "input_data": "string",
  • "input_type": "vxu",
  • "root_template": "ADT_A01",
  • "rr_data": "string"
}

Response samples

Content type
application/json
{
  • "response": {
    }
}

Convert

Converts an HL7v2 or C-CDA message to FHIR format using the Microsoft FHIR +Converter CLI tool. When conversion is successful, a dictionary containing the +response from the FHIR Converter is returned.

+

In order to successfully call this function, the Microsoft FHIR Converter tool +must be installed. For information on how to do this, please refer to the +description.md file. The source code for the converter can be found at +https://github.com/microsoft/FHIR-Converter.

+
Request Body schema: application/json
input_data
required
string (Input Data)

The message to be converted as a string.

+
input_type
required
string (InputType)
Enum: "elr" "vxu" "ecr"

The type of message to be converted.

+
root_template
required
string (RootTemplate)
Enum: "ADT_A01" "ADT_A02" "ADT_A03" "ADT_A04" "ADT_A05" "ADT_A06" "ADT_A07" "ADT_A08" "ADT_A09" "ADT_A10" "ADT_A11" "ADT_A13" "ADT_A14" "ADT_A15" "ADT_A16" "ADT_A25" "ADT_A26" "ADT_A27" "ADT_A28" "ADT_A29" "ADT_A31" "ADT_A40" "ADT_A41" "ADT_A45" "ADT_A47" "ADT_A60" "BAR_P01" "BAR_P02" "BAR_P12" "DFT_P03" "DFT_P11" "MDM_T01" "MDM_T02" "MDM_T05" "MDM_T06" "MDM_T09" "MDM_T10" "OMG_O19" "OML_O21" "ORM_O01" "ORU_R01" "OUL_R22" "OUL_R23" "OUL_R24" "RDE_O11" "RDE_O25" "RDS_O13" "REF_I12" "REF_I14" "SIU_S12" "SIU_S13" "SIU_S14" "SIU_S15" "SIU_S16" "SIU_S17" "SIU_S26" "VXU_V04" "CCD" "EICR" "ELR" "ConsultationNote" "DischargeSummary" "Header" "HistoryandPhysical" "OperativeNote" "ProcedureNote" "ProgressNote" "ReferralNote" "TransferSummary"

Name of the liquid template within to be used for conversion.

+
rr_data
string (Rr Data)

If an eICR message, the accompanying Reportability Response data.

+

Responses

Request samples

Content type
application/json
{
  • "input_data": "string",
  • "input_type": "vxu",
  • "root_template": "ADT_A01",
  • "rr_data": "string"
}

Response samples

Content type
application/json
{
  • "response": {
    }
}
+ + + + \ No newline at end of file diff --git a/docs/v1.2.7/containers/ingestion.html b/docs/v1.2.7/containers/ingestion.html new file mode 100644 index 0000000000..67fc1d4c6d --- /dev/null +++ b/docs/v1.2.7/containers/ingestion.html @@ -0,0 +1,2319 @@ + + + + + + PHDI Ingestion Service + + + + + + + + + +
API docs by Redocly

PHDI Ingestion Service (1.2.7)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Getting Started with the PHDI Ingestion Service

Introduction

+

The PHDI ingestion service offers a REST API with endpoints for standardization and harmonization of FHIR messages. It offers name standardization, date of birth standardization, phone number standardization, geocoding, and several utilities for working with FHIR servers.

+

Running the Ingestion Service

+

The ingestion service can be run using Docker (or any other OCI container runtime e.g., Podman), or directly from the Python source code.

+ +

To run the ingestion service with Docker follow these steps.

+
    +
  1. Confirm that you have Docker installed by running docker -v. If you do not see a response similar to what is shown below, follow these instructions to install Docker.
    ❯ docker -v
+Docker version 20.10.21, build baeda1f
+
    +
    2. +
  2. Download a copy of the Docker image from the PHDI repository by running docker pull ghcr.io/cdcgov/phdi/ingestion:latest.
    3. +
  3. Run the service with docker run -p 8080:8080 ghcr.io/cdcgov/phdi/ingestion:latest.
    4. +
+

Congratulations, the ingestion service should now be running on localhost:8080!

+

Running from Python Source Code

+

We recommend running the ingestion service from a container, but if that is not feasible for a given use case, it may also be run directly from Python using the steps below.

+
    +
  1. Ensure that both Git and Python 3.10 or higher are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/ingestion/.
    4. +
  4. Make a fresh virtual environment with python -m venv .venv.
    5. +
  5. Activate the virtual environment with source .venv/bin/activate (MacOS and Linux), venv\Scripts\activate (Windows Command Prompt), or .venv\Scripts\Activate.ps1 (Windows PowerShell).
    6. +
  6. Install all of the Python dependencies for the ingestion service with pip install -r requirements.txt into your virtual environment.
    7. +
  7. Run the FHIR Converter on localhost:8080 with python -m uvicorn app.main:app --host 0.0.0.0 --port 8080.
    8. +
+

Building the Docker Image

+

To build the Docker image for the ingestion service from source code instead of downloading it from the PHDI repository, follow these steps.

+
    +
  1. Ensure that both Git and Docker are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/ingestion/.
    4. +
  4. Run docker build -t ingestion ..
    5. +
+

The API

+

When viewing these docs from the /redoc endpoint on a running instance of the ingestion service or the PHDI website, detailed documentation on the API will be available below.

+

Health Check

Check service status. If an HTTP 200 status code is returned along with +'{"status": "OK"}' then the service is available and running properly.

+

Responses

Response samples

Content type
application/json
{
  • "status": "OK"
}

fhir/harmonization

Standardize Names Endpoint

Standardize the names in the provided FHIR bundle or resource.

+

:param input: A dictionary with the schema specified by the StandardizeNamesInput + model.

+

:return: A FHIR bundle or resource with standardized names.

+
Request Body schema: application/json
data
required
object (Data)

A FHIR resource or bundle in JSON format.

+
trim
boolean (Trim)
Default: true

When true, leading and trailing spaces are removed.

+
overwrite
boolean (Overwrite)
Default: true

If true, data is modified in-place; if false, a copy of data is modified and returned.

+
case
string (Case)
Default: "upper"
Enum: "upper" "lower" "title"
remove_numbers
boolean (Remove Numbers)
Default: true

If true, delete numeric characters; if false leave numbers in place.

+

Responses

Request samples

Content type
application/json
{
  • "data": {
    },
  • "trim": true,
  • "overwrite": true,
  • "case": "upper",
  • "remove_numbers": true
}

Response samples

Content type
application/json
{
  • "status_code": "200",
  • "bundle": {
    }
}

Standardize Phones Endpoint

Standardize the phone numbers in the provided FHIR bundle or resource.

+

Requires an address so that country code can be generated.

+

:param input: A dictionary with the schema specified by the StandardizePhonesInput + model.

+

:return: A FHIR bundle with standardized phone numbers.

+
Request Body schema: application/json
data
required
object (Data)

A FHIR resource or bundle in JSON format.

+
overwrite
boolean (Overwrite)
Default: true

If true, data is modified in-place; if false, a copy of data is modified and returned.

+

Responses

Request samples

Content type
application/json
{
  • "data": {
    },
  • "overwrite": true
}

Response samples

Content type
application/json
{
  • "status_code": "200",
  • "bundle": {
    }
}

Standardize Dob Endpoint

Standardize the patient date of birth in the provided FHIR bundle or resource.

+

Dates are changed to the FHIR standard of YYYY-MM-DD.

+

Returns a FHIR bundle with standardized birth dates.

+
Request Body schema: application/json
data
required
object (Data)

A FHIR resource or bundle in JSON format.

+
overwrite
boolean (Overwrite)
Default: true

If true, data is modified in-place; if false, a copy of data is modified and returned.

+
format
string (Format)
Default: "Y%-m%-d%"

Responses

Request samples

Content type
application/json
{
  • "data": {
    },
  • "overwrite": true,
  • "format": "%m/%d/%Y"
}

Response samples

Content type
application/json
{
  • "status_code": "200",
  • "bundle": {
    }
}

fhir/geospatial

Geocode Bundle Endpoint

Given a FHIR bundle and a specified geocode method, geocode all patient addresses +across all patient resources in the bundle.

+

Two geocode methods are currently supported - Smarty and the U.S. Census.

+

If using the Smarty provider, an smarty_auth_id, smarty_auth_token and license_type +must be provided. If they are not provided as request parameters, then the service +will attempt to obtain them through environment variables. If they cannot be found +in either the request parameters or environment variables, an HTTP 400 status will +be returned.

+
Request Body schema: application/json
bundle
required
object (Bundle)

A FHIR resource or bundle in JSON format.

+
geocode_method
required
string (Geocode Method)
Enum: "smarty" "census"

The geocoding service to be used.

+
smarty_auth_id
string (Smarty Auth Id)
Default: ""

Authentication ID for the geocoding service. Must be provided in the request body or set as an environment variable of the service if geocode_method is smarty.

+
smarty_auth_token
string (Smarty Auth Token)
Default: ""

Authentication Token for the geocoding service. Must be provided in the request body or set as an environment variable of the service if geocode_method is smarty.

+
license_type
string (License Type)
Default: "us-rooftop-geocoding-enterprise-cloud"
Enum: "us-standard-cloud" "us-core-cloud" "us-rooftop-geocoding-cloud" "us-rooftop-geocoding-enterprise-cloud" "us-autocomplete-pro-cloud" "international-global-plus-cloud"

License type for the geocoding service. Must be provided in the request body or set as an environment variable of the service if geocode_method is smarty.

+
overwrite
boolean (Overwrite)
Default: true

If true, data is modified in-place; if false, a copy of data modified and returned.

+

Responses

Request samples

Content type
application/json
{
  • "bundle": { },
  • "geocode_method": "smarty",
  • "smarty_auth_id": "",
  • "smarty_auth_token": "",
  • "license_type": "us-standard-cloud",
  • "overwrite": true
}

Response samples

Content type
application/json
Example
{
  • "status_code": "200",
  • "bundle": {
    }
}

fhir/linkage

Add Patient Identifier In Bundle Endpoint

Add a salted hash identifier to every patient resource in a FHIR bundle using. If +a salt is not provided in the request the value of the 'SALT_STR' environment +variable will be used. In the case where a salt is not provided and 'SALT_STR' is +not defined an HTTP 500 status code is returned.

+

:param input: A JSON formated request body with schema specified by the + AddPatientIdentifierInBundleInput model. +:return: A FHIR bundle where every patient resource contains a hashed identifier.

+
Request Body schema: application/json
bundle
required
object (Bundle)

A FHIR bundle

+
salt_str
string (Salt Str)
Default: ""

The salt to use with the hash. This is intended to prevent reverse engineering of the PII used to create the hash.

+
overwrite
boolean (Overwrite)
Default: true

If true, data is modified in-place; if false, a copy of data modified and returned.

+

Responses

Request samples

Content type
application/json
{
  • "bundle": { },
  • "salt_str": "",
  • "overwrite": true
}

Response samples

Content type
application/json
{
  • "status_code": "string",
  • "message": "string",
  • "bundle": { }
}

fhir/transport

Upload Bundle To Fhir Server Endpoint

Upload all of the resources in a FHIR bundle to a FHIR server.

+

:param input: A JSON formated request body with schema specified by the + UploadBundleToFhirServerInput model. +:return: A dictionary containing the status code and body of the response received + from the FHIR server.

+
Request Body schema: application/json
bundle
required
object (Bundle)

A FHIR bundle (type 'batch' or 'transaction') to post. Each entry in the bundle must contain a request element in addition to a resource. The FHIR API provides additional details on creating FHIR-conformant batch/transaction bundles.

+
cred_manager
string (Cred Manager)
Enum: "azure" "gcp"

The credential manager used to authenticate to the FHIR server.

+
fhir_url
string (Fhir Url)

The url of the FHIR server to upload to.

+

Responses

Request samples

Content type
application/json
{
  • "bundle": { },
  • "cred_manager": "azure",
  • "fhir_url": "string"
}

Response samples

Content type
application/json
{
  • "status_code": "string",
  • "message": "string",
  • "bundle": { }
}

cloud/storage

Write Blob To Cloud Storage Endpoint

Upload the information from a blob into a specified cloud providers storage +organizing it by a bucket name as well as a file name.

+

:param input: A JSON formated request body (blob) with schema specified by the + WriteBlobToStorageInput model. +:return: A dictionary containing the status code and body of the response received + from the cloud provider.

+
Request Body schema: application/json
blob
required
object (Blob)

Contents of a blob to be written to cloud storage.

+
cloud_provider
string (Cloud Provider)
Enum: "azure" "gcp"

The cloud provider hosting the storage resource that the blob will be uploaded to. Must be provided in the request body or set as an environment variable of the service.

+
bucket_name
string (Bucket Name)

Name of the cloud storage bucket that the blob should be uploaded to. Must be provided in the request body or set as an environment variable of the service.

+
file_name
required
string (File Name)

Name of the blob

+
storage_account_url
string (Storage Account Url)
Default: ""

The URL of an Azure storage account. Must be provided in the request body or set as an environment variable of the service is 'cloud_provider' is 'azure'.

+

Responses

Request samples

Content type
application/json
{
  • "blob": { },
  • "cloud_provider": "azure",
  • "bucket_name": "string",
  • "file_name": "string",
  • "storage_account_url": ""
}

Response samples

Content type
application/json
{
  • "status_code": "string",
  • "message": "string",
  • "bundle": { }
}
+ + + + \ No newline at end of file diff --git a/docs/v1.2.7/containers/message-parser.html b/docs/v1.2.7/containers/message-parser.html new file mode 100644 index 0000000000..066c7ef2cd --- /dev/null +++ b/docs/v1.2.7/containers/message-parser.html @@ -0,0 +1,2360 @@ + + + + + + PHDI Message Parser + + + + + + + + + +
API docs by Redocly

PHDI Message Parser (1.2.7)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Getting Started with the DIBBs Message Parser

Introduction

+

The PHDI message parser offers a REST API for extracting desired fields from a given message. The service natively supports extracting values from FHIR bundles, but it can support parsing Hl7v2 (eLR, VXU, ADT, etc.) and CDA(eCR) messages by first using the DIBBs FHIR converter to convert them to FHIR. Fields are extracted using a "parsing schema" which is simply a mapping in key:value format between desired field names (keys) and the FHIRPaths within the bundle to the values. In addition the data type of value (string, integer, float, boolean, date, timestamp) as well as whether the value can be null (true, false) must be specified. A simple example of a schema for extracting a patient's first and last name from messages is shown below.

+
{
+  "first_name": {
+    "fhir_path": "Bundle.entry.resource.where(resourceType = 'Patient').name.first().given.first()",
+    "data_type": "string",
+    "nullable": true
+  },
+  "last_name": {
+    "fhir_path": "Bundle.entry.resource.where(resourceType = 'Patient').name.first().family",
+    "data_type": "string",
+    "nullable": true
+  }
+}
+
+

Using this schema on a message about a patient named John Doe yield a result like this.

+
{
+  "first_name": "John",
+  "last_name": "Doe"
+}
+
+

Nested Data

+

Sometimes healthcare messages can be large and complex. A single message might contain several lab results that all must be extracted. We could do this by mapping each lab to its own column, "lab_result_1", "lab_result_2", "lab_result_3" and so on. However, this is cumbersome and often a poor solution if the possible number of labs is unknown or very large. To address this the message parser can return multiple values found in equivalent locations in a FHIR bundle as an array. To do this we can add the "secondary_schema" key to the field of a parsing schema that should contain multiple values. The schema below demonstrates extracting a patient's first name, last name, as well as all of their labs.

+
{
+  "first_name": {
+    "fhir_path": "Bundle.entry.resource.where(resourceType = 'Patient').name.first().given.first()",
+    "data_type": "string",
+    "nullable": true
+  },
+  "last_name": {
+    "fhir_path": "Bundle.entry.resource.where(resourceType = 'Patient').name.first().family",
+    "data_type": "string",
+    "nullable": true
+  },
+  "labs": {
+        "fhir_path": "Bundle.entry.resource.where(resourceType='Observation').where(category.coding.code='laboratory')",
+        "data_type": "array",
+        "nullable": true,
+        "secondary_schema": {
+          "test_type": {
+              "fhir_path": "Observation.code.coding.display",
+              "data_type": "string",
+              "nullable": true
+          },
+          "test_type_code": {
+              "fhir_path": "Observation.code.coding.code",
+              "data_type": "string",
+              "nullable": true
+          },
+          "test_result": {
+              "fhir_path": "Observation.valueString",
+              "data_type": "string",
+              "nullable": true
+          },
+          "specimen_collection_date": {
+              "fhir_path": "Observation.extension.where(url='http://hl7.org/fhir/R4/specimen.html').extension.where(url='specimen collection time').valueDateTime",
+              "data_type": "datetime",
+              "nullable": true
+          }
+        }
+    }
+}
+
+

If this parsing schema is used on a message about a patient named Jane Doe with two labs the service would a return a result like this.

+
{
+  "first_name": "Jane",
+  "last_name": "Doe",
+  "labs": [
+    {
+      "test_type": "Campylobacter, NAAT",
+      "test_type_code": "82196-7",
+      "test_result": "Not Detected",
+      "specimen_collection_date": "2023-01-31T18:52:00Z"
+    },
+    {
+      "test_type": "C. Diff Toxin A/B, NAAT",
+      "test_type_code": "82197-5",
+      "test_result": "Not Detected",
+      "specimen_collection_date": "2023-01-31T18:52:00Z"
+    }
+  ]
+}
+
+

Running the Message Parser

+

The message parser can be run using Docker (or any other OCI container runtime e.g., Podman), or directly from the Python source code.

+ +

To run the message parser with Docker, follow these steps.

+
    +
  1. Confirm that you have Docker installed by running docker -v. If you do not see a response similar to what is shown below, follow these instructions to install Docker.
    ❯ docker -v
+Docker version 20.10.21, build baeda1f
+
    +
    2. +
  2. Download a copy of the Docker image from the PHDI repository by running docker pull ghcr.io/cdcgov/phdi/message-parser:latest.
    3. +
  3. Run the service with docker run -p 8080:8080 message-parser:latest.
    4. +
+

Congratulations, the message parser should now be running on localhost:8080!

+

Running from Python Source Code

+

We recommend running the message parser from a container, but if that is not feasible for a given use-case, it may also be run directly from Python using the steps below.

+
    +
  1. Ensure that both Git and Python 3.10 or higher are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/message-parser/.
    4. +
  4. Make a fresh virtual environment with python -m venv .venv.
    5. +
  5. Activate the virtual environment with source .venv/bin/activate (MacOS and Linux), venv\Scripts\activate (Windows Command Prompt), or .venv\Scripts\Activate.ps1 (Windows Power Shell).
    6. +
  6. Install all of the Python dependencies for the message parser with pip install -r requirements.txt into your virtual environment.
    7. +
  7. Run the FHIR Converter on localhost:8080 with python -m uvicorn app.main:app --host 0.0.0.0 --port 8080.
    8. +
+

Building the Docker Image

+

To build the Docker image for the message parser from source instead of downloading it from the PHDI repository follow these steps.

+
    +
  1. Ensure that both Git and Docker are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/message-parser/.
    4. +
  4. Run docker build -t message-parser ..
    5. +
+

The API

+

When viewing these docs from the /redoc endpoint on a running instance of the message parser or the PHDI website, detailed documentation on the API will be available below.

+

Health Check

Check service status. If an HTTP 200 status code is returned along with +'{"status": "OK"}' then the FHIR conversion service is available and running +properly.

+

Responses

Response samples

Content type
application/json
null

Parse Message Endpoint

Extract the desired values from a message. If the message is not already in +FHIR format, convert it to FHIR first. You can either provide a parsing schema +or the name of a previously loaded parsing schema.

+
Request Body schema: application/json
message_format
required
string (Message Format)
Enum: "fhir" "hl7v2" "ecr"

The format of the message.

+
message_type
string (Message Type)
Enum: "ecr" "elr" "vxu"

The type of message that values will be extracted from. Required when 'message_format is not FHIR.

+
parsing_schema
object (Parsing Schema)
Default: {}

A schema describing which fields to extract from the message. This must be a JSON object with key:value pairs of the form :.

+
parsing_schema_name
string (Parsing Schema Name)
Default: ""

The name of a schema that was previously loaded in the service to use to extract fields from the message.

+
fhir_converter_url
string (Fhir Converter Url)
Default: ""

The URL of an instance of the PHDI FHIR converter. Required when the message is not already in FHIR format.

+
credential_manager
string (Credential Manager)
Enum: "azure" "gcp"

The type of credential manager to use for authentication with a FHIR converter when conversion to FHIR is required.

+
include_metadata
string (Include Metadata)
Enum: "true" "false"

Boolean to include metadata in the response.

+
required
Message (string) or Message (object) (Message)

The message to be parsed.

+

Responses

Request samples

Content type
application/json
{
  • "message_format": "fhir",
  • "message_type": "ecr",
  • "parsing_schema": { },
  • "parsing_schema_name": "",
  • "fhir_converter_url": "",
  • "credential_manager": "azure",
  • "include_metadata": "true",
  • "message": "string"
}

Response samples

Content type
application/json
Example
{
  • "message": "Parsing succeeded!",
  • "parsed_values": {
    }
}

Fhir To Phdc Endpoint

Convert a FHIR bundle to a Public Health Document Container (PHDC).

+
Request Body schema: application/json
phdc_report_type
required
string (Phdc Report Type)
Enum: "case_report" "contact_record" "lab_report" "morbidity_report"

The type of PHDC document the user wants returned to them. The choice of report type should reflect the type of the incoming data and determines which PHDC schema is used when extracting.

+
message
required
object (Message)

The FHIR bundle to extract from.

+

Responses

Request samples

Content type
application/json
{
  • "phdc_report_type": "case_report",
  • "message": { }
}

Response samples

Content type
application/json
{
  • "message": "FHIR extraction succeeded!",
  • "parsed_values": {
    }
}

List Schemas

Get a list of all the parsing schemas currently available. Default schemas are ones +that are packaged by default with this service. Custom schemas are any additional +schema that users have chosen to upload to this service (this feature is not yet +implemented)

+

Responses

Response samples

Content type
application/json
{
  • "default_schemas": [
    ],
  • "custom_schemas": [ ]
}

Get Schema

Get the schema specified by 'parsing_schema_name'.

+
path Parameters
parsing_schema_name
required
string (Parsing Schema Name)

Responses

Response samples

Content type
application/json
{
  • "message": "Schema found!",
  • "parsing_schema": {
    }
}

Upload Schema

Upload a new parsing schema to the service or update an existing schema.

+
path Parameters
parsing_schema_name
required
string (Parsing Schema Name)
Request Body schema: application/json
required
object (Parsing Schema)

A JSON formatted parsing schema to upload.

+
overwrite
boolean (Overwrite)
Default: false

When true if a schema already exists for the provided name it will be replaced. When false no action will be taken and the response will indicate that a schema for the given name already exists. To proceed submit a new request with a different schema name or set this field to true.

+

Responses

Request samples

Content type
application/json
{
  • "parsing_schema": {
    },
  • "overwrite": false
}

Response samples

Content type
application/json
{
  • "message": "Schema uploaded successfully!"
}
+ + + + \ No newline at end of file diff --git a/docs/v1.2.7/containers/orchestration.html b/docs/v1.2.7/containers/orchestration.html new file mode 100644 index 0000000000..f3d93465d3 --- /dev/null +++ b/docs/v1.2.7/containers/orchestration.html @@ -0,0 +1,2304 @@ + + + + + + PHDI Orchestration + + + + + + + + + +
API docs by Redocly

PHDI Orchestration (1.2.7)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Getting Started with the DIBBs Orchestration

Introduction

+

The PHDI Orchestration app offers a REST API for processing messages through a series of microservices.

+

Running Orchestration

+

The Orchestration app can be run using Docker (or any other OCI container runtime e.g., Podman), or directly from the Python source code.

+ +

To run the Orchestration app with Docker, follow these steps.

+
    +
  1. Confirm that you have Docker installed by running docker -v. If you do not see a response similar to what is shown below, follow these instructions to install Docker.
    ❯ docker -v
+Docker version 20.10.21, build baeda1f
+
    +
    2. +
  2. Download a copy of the Docker image from the PHDI repository by running docker pull ghcr.io/cdcgov/phdi/orchestration:latest.
    3. +
  3. Run the service with docker run -p 8080:8080 orchestration:latest.
    4. +
+

Congratulations, the Orchestration app should now be running on localhost:8080!

+

Running from Python Source Code

+

We recommend running the Orchestration app from a container, but if that is not feasible for a given use-case, it may also be run directly from Python using the steps below.

+
    +
  1. Ensure that both Git and Python 3.10 or higher are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/orchestration/.
    4. +
  4. Make a fresh virtual environment with python -m venv .venv.
    5. +
  5. Activate the virtual environment with source .venv/bin/activate (MacOS and Linux), venv\Scripts\activate (Windows Command Prompt), or .venv\Scripts\Activate.ps1 (Windows Power Shell).
    6. +
  6. Install all of the Python dependencies for the Orchestration app with pip install -r requirements.txt into your virtual environment.
    7. +
  7. Run the Orchestration app on localhost:8080 with python -m uvicorn app.main:app --host 0.0.0.0 --port 8080.
    8. +
+

Building the Docker Image

+

To build the Docker image for the Orchestration app from source instead of downloading it from the PHDI repository follow these steps.

+
    +
  1. Ensure that both Git and Docker are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/orchestration/.
    4. +
  4. Run docker build -t orchestration ..
    5. +
+

The API

+

When viewing these docs from the /redoc endpoint on a running instance of the Orchestration app or the PHDI website, detailed documentation on the API will be available below.

+

Health Check

Check service status. If an HTTP 200 status code is returned along with +'{"status": "OK"}' then the service is available and running properly.

+

Responses

Response samples

Content type
application/json
{
  • "status": "OK"
}

Process Endpoint

Wrapper function for unpacking an uploaded file, determining appropriate +parameter and application settings, and applying a config-driven workflow +to the data in that file. This is one of two endpoints that can actually +invoke and apply a config workflow to data and is meant to be used to +process files.

+

:param message_type: The type of stream of the uploaded file's underlying + data (e.g. ecr, elr, etc.). If the data is in FHIR format, set to FHIR. +:param data_type: The type of data held in the uploaded file. Eligible + values include ecr, zip, fhir, and hl7. +:param config_file_name: The name of the configuration file to load on + the service's back-end, specifying the workflow to apply. +:param upload_file: A file containing clinical health care information. +:return: A response holding whether the workflow application was + successful as well as the results of the workflow.

+
Request Body schema: multipart/form-data
message_type
string (Message Type)
data_type
string (Data Type)
config_file_name
string (Config File Name)
upload_file
string <binary> (Upload File)

Responses

Response samples

Content type
application/json
Example
{
  • "message": "Processing succeeded!",
  • "content": {
    }
}

Process Message Endpoint

Wrapper function for unpacking a message processing input and using those +settings to apply a config-driven workflow to a raw string of data. +This endpoint is the second of two workflow-driven endpoints and is meant +to be used with raw string data (meaning if the data is JSON, it must be +string serialized with json.dumps).

+

:param request: A response holding whether the workflow application was + successful as well as the results of the workflow.

+
Request Body schema: application/json
message_type
required
string (Message Type)
Enum: "ecr" "elr" "vxu" "fhir"

The type of message to be validated.

+
data_type
required
string (Data Type)
Enum: "ecr" "zip" "fhir" "hl7"

The type of data of the passed-in message. Must be one of 'ecr', 'fhir', or 'zip'. If data_type is set to 'zip', the underlying unzipped data is assumed to be ecr.

+
config_file_name
required
string (Config File Name)

The name of a config file in either the default/ or custom/ schemas directory that will define the workflow applied to the passed data.

+
required
Message (object) or Message (string) (Message)

The message to be validated.

+
rr_data
string (Rr Data)

If an eICR message, the accompanying Reportability Response data.

+

Responses

Request samples

Content type
application/json
{
  • "message_type": "ecr",
  • "data_type": "ecr",
  • "config_file_name": "string",
  • "message": { },
  • "rr_data": "string"
}

Response samples

Content type
application/json
Example
{
  • "message": "Processing succeeded!",
  • "content": {
    }
}

List Configs

Get a list of all the process configs currently available. Default configs are ones +that are packaged by default with this service. Custom configs are any additional +config that users have chosen to upload to this service (this feature is not yet +implemented)

+

Responses

Response samples

Content type
application/json
{
  • "default_configs": [
    ],
  • "custom_configs": [ ]
}

Get Config

Get the config specified by 'processing_config_name'.

+

:param processing_config_name: The name of the processing configuration to retrieve. +:param response: The response object used to modify the response status and body.

+
path Parameters
processing_config_name
required
string (Processing Config Name)

Responses

Response samples

Content type
application/json
{
  • "message": "Config found!",
  • "workflow": {
    }
}

Upload Config

Upload a new processing config to the service or update an existing config.

+

:param processing_config_name: The name of the processing configuration to be + uploaded or updated. +:param input: A Pydantic model representing the processing configuration data. +:param response: The response object used to modify the response status and body.

+
path Parameters
processing_config_name
required
string (Processing Config Name)
Request Body schema: application/json
required
object (Workflow)

A JSON-formatted config dict containing a single key workflow that maps to a list of WorkflowServiceStep objects, each defining one step in the orchestration configuration to upload.

+
overwrite
boolean (Overwrite)
Default: false

When true if a config already exists for the provided name it will be replaced. When false no action will be taken and the response will indicate that a config for the given name already exists. To proceed submit a new request with a different config name or set this field to true.

+

Responses

Request samples

Content type
application/json
{
  • "workflow": {
    },
  • "overwrite": false
}

Response samples

Content type
application/json
{
  • "message": "Config uploaded successfully!"
}
+ + + + \ No newline at end of file diff --git a/docs/v1.2.7/containers/record-linkage.html b/docs/v1.2.7/containers/record-linkage.html new file mode 100644 index 0000000000..217c7ac6c1 --- /dev/null +++ b/docs/v1.2.7/containers/record-linkage.html @@ -0,0 +1,2261 @@ + + + + + + DIBBs Record Linkage Service + + + + + + + + + +
API docs by Redocly

DIBBs Record Linkage Service (1.2.7)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Getting Started with the DIBBs Record Linkage Service

Introduction

+

The DIBBs record linkage service offers a REST API for linking new health care messages to existing records if a connection exists.

+

Running the Record Linkage Service

+

The record linkage service can be run using Docker (or any other OCI container runtime e.g., Podman), or directly from the Python source code.

+ +

To run the record linkage service with Docker Compose follow these steps.

+
    +

  1. Confirm that you have Docker installed by running docker -v. If you do not see a response similar what is shown below, follow these instructions to install Docker.

    +
    ❯ docker -v
+Docker version 20.10.21, build baeda1f
+
    +
    2. +

  2. Navigate to the containers/record-linkage folder and start the service by running docker compose up --build

    +
    3. +
+

Congratulations the record-linkage should now be running on localhost:8080!

+

Running with Docker

+

To run the record linkage service with Docker follow these steps.

+
    +
  1. Confirm that you have Docker installed by running docker -v. If you do not see a response similar to what is shown below, follow these instructions to install Docker.
    ❯ docker -v
+Docker version 20.10.21, build baeda1f
+
    +
    2. +
  2. Download a copy of the Docker image from the DIBBs repository by running docker pull ghcr.io/cdcgov/phdi/record-linkage:latest.
    3. +
  3. Run the service with docker run -p 8080:8080 record-linkage:latest.
    4. +
+

Congratulations, the record linkage service should now be running on localhost:8080!

+

Running from Python Source Code

+

We recommend running the record linkage service from a container, but if that is not feasible for a given use case, it may also be run directly from Python using the steps below.

+
    +
  1. Ensure that both Git and Python 3.10 or higher are installed.
    2. +
  2. Clone the DIBBs repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/record-linkage/.
    4. +
  4. Make a fresh virtual environment with python -m venv .venv.
    5. +
  5. Activate the virtual environment with source .venv/bin/activate (MacOS and Linux), venv\Scripts\activate (Windows Command Prompt), or .venv\Scripts\Activate.ps1 (Windows PowerShell).
    6. +
  6. Install all Python dependencies for the record linkage service with pip install -r requirements.txt into your virtual environment.
    7. +
  7. Run the record linkage service on localhost:8080 with python -m uvicorn app.main:app --host 0.0.0.0 --port 8080 --log-config app/log_config.yml.
    8. +
+

Building the Docker Image

+

To build the Docker image for the record linkage service from source code instead of downloading it from the DIBBs repository follow these steps.

+
    +
  1. Ensure that both Git and Docker are installed.
    2. +
  2. Clone the DIBBs repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/record-linkage/.
    4. +
  4. Run docker build -t record-linkage ..
    5. +
+

The API

+

When viewing these docs from the /redoc endpoint on a running instance of the record linkage service or the DIBBs website, detailed documentation on the API will be available below.

+

Health Check

Check the status of this service and its connection to Master Patient Index(MPI). If +an HTTP 200 status code is returned along with '{"status": "OK"}' then the record +linkage service is available and running properly. The mpi_connection_status field +contains a description of the connection health to the MPI database.

+

Responses

Response samples

Content type
application/json
{
  • "status": "string",
  • "mpi_connection_status": "string"
}

Link Record

Compare a FHIR bundle with records in the Master Patient Index (MPI) to +check for matches with existing patient records If matches are found, +returns the bundle with updated references to existing patients.

+
Request Body schema: application/json
bundle
required
object (Bundle)

A FHIR bundle containing a patient resource to be checked for links to existing patient records

+
use_enhanced
boolean (Use Enhanced)
Default: false

Optionally, a boolean flag indicating whether to use the DIBBs enhanced algorithm (with statistical correction) for record linkage. If False and no optional algo_config is provided, the service will use the DIBBs basic algorithm. If this parameter is set to True, the enhanced algorithm will be used in place of any configuration supplied in algo_config.

+
algo_config
object (Algo Config)
Default: {}

A JSON dictionary containing the specification for a linkage algorithm, as defined in the SDK functions read_algo_config and write_algo_config. Default value uses the DIBBS in-house basic algorithm.

+
external_person_id
string (External Person Id)

The External Identifier, provided by the client, for a unique patient/person that is linked to patient(s)

+

Responses

Request samples

Content type
application/json
{
  • "bundle": { },
  • "use_enhanced": false,
  • "algo_config": { },
  • "external_person_id": "string"
}

Response samples

Content type
application/json
Example
{
  • "found_match": true,
  • "updated_bundle": {
    }
}
+ + + + \ No newline at end of file diff --git a/docs/v1.2.7/containers/standardization.html b/docs/v1.2.7/containers/standardization.html new file mode 100644 index 0000000000..6fcc351045 --- /dev/null +++ b/docs/v1.2.7/containers/standardization.html @@ -0,0 +1,2140 @@ + + + + + + DIBBs Standardization Service + + + + + + + + + +
API docs by Redocly

DIBBs Standardization Service (1.2.7)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Getting Started with the DIBBs Standardization Service

TODO: Add description

+

Health Check

A health check endpoint for the service.

+

Responses

Response samples

Content type
application/json
{
  • "status": "string"
}
+ + + + \ No newline at end of file diff --git a/docs/v1.2.7/containers/tabulation.html b/docs/v1.2.7/containers/tabulation.html new file mode 100644 index 0000000000..62afa5d928 --- /dev/null +++ b/docs/v1.2.7/containers/tabulation.html @@ -0,0 +1,2237 @@ + + + + + + PHDI Tabulation Service + + + + + + + + + +
API docs by Redocly

PHDI Tabulation Service (1.2.7)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Getting Started with the PHDI Tabulation Service

Introduction

+

The PHDI tabulation service offers a REST API to extract and tabulate data from a FHIR server according to a user-defined schema, and then persist the data in one of serveral supported formats. More information about this process and writing schemas can be found here.

+

Running the Tabulation Service

+

The tabulation service can be run using Docker (or any other OCI container runtime e.g., Podman), or directly from the Python source code.

+ +

To run the tabulation service with Docker follow these steps.

+
    +
  1. Confirm that you have Docker installed by running docker -v. If you do not see a response similar to what is shown below, follow these instructions to install Docker.
    ❯ docker -v
+Docker version 20.10.21, build baeda1f
+
    +
    2. +
  2. Download a copy of the Docker image from the PHDI repository by running docker pull ghcr.io/cdcgov/phdi/tabulation:latest.
    3. +
  3. Run the service with docker run -p 8080:8080 -v $(pwd):/code tabulation:latest.
    4. +
+

Congratulations, the tabulation service should now be running on localhost:8080!

+

Running from Python Source Code

+

We recommend running the tabulation service from a container, but if that is not feasible for a given use case, it may also be run directly from Python using the steps below.

+
    +
  1. Ensure that both Git and Python 3.10 or higher are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/tabulation/.
    4. +
  4. Make a fresh virtual environment with python -m venv .venv.
    5. +
  5. Activate the virtual environment with source .venv/bin/activate (MacOS and Linux), venv\Scripts\activate (Windows Command Prompt), or .venv\Scripts\Activate.ps1 (Windows PowerShell).
    6. +
  6. Install all of the Python dependencies for the tabulation service with pip install -r requirements.txt into your virtual environment.
    7. +
  7. Run the FHIR Converter on localhost:8080 with python -m uvicorn app.main:app --host 0.0.0.0 --port 8080.
    8. +
+

Building the Docker Image

+

To build the Docker image for the tabulation service from source code instead of downloading it from the PHDI repository, follow these steps.

+
    +
  1. Ensure that both Git and Docker are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/tabulation/.
    4. +
  4. Run docker build -t tabulation ..
    5. +
+

The API

+

When viewing these docs from the /redoc endpoint on a running instance of the tabulation service or the PHDI website, detailed documentation on the API will be available below.

+

Health Check

Check service status. If an HTTP 200 status code is returned along with +'{"status": "OK"}' then the service is available and running properly.

+

Responses

Response samples

Content type
application/json
{
  • "status": "OK"
}

Validate Schema Endpoint

Request Body schema: application/json
schema
required
object (Schema)

A JSON formatted PHDI schema.

+

Responses

Request samples

Content type
application/json
{
  • "schema": { }
}

Response samples

Content type
application/json
null

Tabulate Endpoint

This endpoint will extract, tabulate, and persist data from a FHIR server according +to a user-defined schema in the method of the user's choosing.

+
Request Body schema: application/json
schema
required
object (Schema)

A JSON formatted PHDI schema.

+
output_type
required
string (Output Type)
Enum: "parquet" "csv" "sql"

Method for persisting data after extraction from the FHIR server and tabulation.

+
fhir_url
string (Fhir Url)

The URL of the FHIR server from which data should be extracted, should end with '/fhir'. If not provided here then it must be set as an environment variable.

+
cred_manager
string (Cred Manager)
Enum: "azure" "gcp"

Chose a PHDI credential manager to use for authentication with the FHIR. May be set here or as an environment variable. If not provided anywhere then un-authenticated FHIR server requests will be attempted.

+

Responses

Request samples

Content type
application/json
{
  • "schema": { },
  • "output_type": "parquet",
  • "fhir_url": "string",
  • "cred_manager": "azure"
}

Response samples

Content type
application/json
null
+ + + + \ No newline at end of file diff --git a/docs/v1.2.7/containers/tefca-viewer.html b/docs/v1.2.7/containers/tefca-viewer.html new file mode 100644 index 0000000000..2f6dd9a9b2 --- /dev/null +++ b/docs/v1.2.7/containers/tefca-viewer.html @@ -0,0 +1,2187 @@ + + + + + + TEFCA Viewer + + + + + + + + + +
API docs by Redocly

TEFCA Viewer (1.1.11)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Use Case Query

path Parameters
use_case
required
string (Use Case)
Enum: "social-determinants" "newborn-screening" "syphilis" "cancer"
Request Body schema: application/json
fhir_server
required
string (Fhir Server)
Enum: "meld" "ehealthexchange"
first_name
required
string (First Name)
last_name
required
string (Last Name)
dob
required
string (Dob)
mrn
string (Mrn)
phone
string (Phone)
street
string (Street)
city
string (City)
state
string (State)
zip
string (Zip)

Responses

Request samples

Content type
application/json
{
  • "fhir_server": "meld",
  • "first_name": "string",
  • "last_name": "string",
  • "dob": "string",
  • "mrn": "string",
  • "phone": "string",
  • "street": "string",
  • "city": "string",
  • "state": "string",
  • "zip": "string"
}

Response samples

Content type
application/json
null

Root

Responses

Response samples

Content type
application/json
null

Health Check

Check service status. If an HTTP 200 status code is returned along with +'{"status": "OK"}' then the FHIR conversion service is available and running +properly.

+

Responses

Response samples

Content type
application/json
null
+ + + + \ No newline at end of file diff --git a/docs/v1.2.7/containers/validation.html b/docs/v1.2.7/containers/validation.html new file mode 100644 index 0000000000..6b33e4de52 --- /dev/null +++ b/docs/v1.2.7/containers/validation.html @@ -0,0 +1,2246 @@ + + + + + + PHDI Validation Service + + + + + + + + + +
API docs by Redocly

PHDI Validation Service (1.2.7)

Download OpenAPI specification:Download

CDC Public Health Data Infrastructure: dmibuildingblocks@cdc.gov URL: https://cdcgov.github.io/phdi-site/ License: Creative Commons Zero v1.0 Universal

Getting Started with the PHDI Validation Service

Introduction

+

The PHDI validation service offers a REST API for validating health care messages (e.g., whether health care messages are in the proper format and contain user-defined fields of interest).

+

Running the Validation Service

+

The validation service can be run using Docker (or any other OCI container runtime e.g., Podman), or directly from the Python source code.

+ +

To run the validation service with Docker follow these steps.

+
    +
  1. Confirm that you have Docker installed by running docker -v. If you do not see a response similar to what is shown below, follow these instructions to install Docker.
    ❯ docker -v
+Docker version 20.10.21, build baeda1f
+
    +
    2. +
  2. Download a copy of the Docker image from the PHDI repository by running docker pull ghcr.io/cdcgov/phdi/validation:latest.
    3. +
  3. Run the service with docker run -p 8080:8080 validation:latest.
    4. +
+

Congratulations, the validation service should now be running on localhost:8080!

+

Running from Python Source Code

+

We recommend running the validation service from a container, but if that is not feasible for a given use case, it may also be run directly from Python using the steps below.

+
    +
  1. Ensure that both Git and Python 3.10 or higher are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/validation/.
    4. +
  4. Make a fresh virtual environment with python -m venv .venv.
    5. +
  5. Activate the virtual environment with source .venv/bin/activate (MacOS and Linux), venv\Scripts\activate (Windows Command Prompt), or .venv\Scripts\Activate.ps1 (Windows PowerShell).
    6. +
  6. Install all Python dependencies for the validation service with pip install -r requirements.txt into your virtual environment.
    7. +
  7. Run the FHIR Converter on localhost:8080 with python -m uvicorn app.main:app --host 0.0.0.0 --port 8080.
    8. +
+

Building the Docker Image

+

To build the Docker image for the validation service from source code instead of downloading it from the PHDI repository, follow these steps.

+
    +
  1. Ensure that both Git and Docker are installed.
    2. +
  2. Clone the PHDI repository with git clone https://github.com/CDCgov/phdi.
    3. +
  3. Navigate to /phdi/containers/validation/.
    4. +
  4. Run docker build -t validation ..
    5. +
+

The API

+

When viewing these docs from the /redoc endpoint on a running instance of the validation service or the PHDI website, detailed documentation on the API will be available below.

+

Health Check

Check service status. If an HTTP 200 status code is returned along with +'{"status": "OK"}' then the service is available and running properly.

+

Responses

Response samples

Content type
application/json
{
  • "status": "OK"
}

Validate Endpoint

Check if the value presented in the 'message' key is a valid example +of the type of message specified in the 'message_type'.

+
Request Body schema: application/json
message_type
required
string (Message Type)
Enum: "ecr" "elr" "vxu" "fhir"

The type of message to be validated.

+
include_error_types
required
string (Include Error Types)

A comma separated list of the types of errors that should be included in the return response. Valid types are fatal, errors, warnings, information

+
message
required
string (Message)

The message to be validated.

+
rr_data
string (Rr Data)

If validating an eICR message, the accompanying Reportability Response data.

+

Responses

Request samples

Content type
application/json
{
  • "message_type": "ecr",
  • "include_error_types": "string",
  • "message": "string",
  • "rr_data": "string"
}

Response samples

Content type
application/json
Example
{
  • "message_valid": "True",
  • "validation_results": {
    }
}
+ + + + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/index.html b/docs/v1.2.7/sdk/index.html new file mode 100644 index 0000000000..f1d2f7bc22 --- /dev/null +++ b/docs/v1.2.7/sdk/index.html @@ -0,0 +1,7 @@ + + + + + + + diff --git a/docs/v1.2.7/sdk/phdi.html b/docs/v1.2.7/sdk/phdi.html new file mode 100644 index 0000000000..2e536ef843 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi.html @@ -0,0 +1,249 @@ + + + + + + + phdi API documentation + + + + + + + + + +
+
+

+phdi

+ + + + + + + 
1__version__ = "1.2.7"
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/cloud.html b/docs/v1.2.7/sdk/phdi/cloud.html new file mode 100644 index 0000000000..1cd224f2bf --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/cloud.html @@ -0,0 +1,239 @@ + + + + + + + phdi.cloud API documentation + + + + + + + + + +
+
+

+phdi.cloud

+ + + + + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/cloud/azure.html b/docs/v1.2.7/sdk/phdi/cloud/azure.html new file mode 100644 index 0000000000..1bbdb0055d --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/cloud/azure.html @@ -0,0 +1,1262 @@ + + + + + + + phdi.cloud.azure API documentation + + + + + + + + + +
+
+

+phdi.cloud.azure

+ + + + + + + 
  1import json
+  2from datetime import datetime
+  3from datetime import timezone
+  4from typing import List
+  5from typing import Literal
+  6from typing import Union
+  7
+  8from azure.core.credentials import AccessToken
+  9from azure.identity import DefaultAzureCredential
+ 10from azure.keyvault.secrets import SecretClient
+ 11from azure.storage.blob import BlobServiceClient
+ 12from azure.storage.blob import ContainerClient
+ 13
+ 14from phdi.cloud.core import BaseCloudStorageConnection
+ 15from phdi.cloud.core import BaseCredentialManager
+ 16
+ 17
+ 18class AzureCredentialManager(BaseCredentialManager):
+ 19    """
+ 20    Defines a credential manager used for connecting to Azure.
+ 21    """
+ 22
+ 23    @property
+ 24    def resource_location(self) -> str:
+ 25        return self.__resource_location
+ 26
+ 27    @property
+ 28    def scope(self) -> str:
+ 29        return self.__scope
+ 30
+ 31    @property
+ 32    def access_token(self) -> AccessToken:
+ 33        return self.__access_token
+ 34
+ 35    def __init__(self, resource_location: str = None, scope: str = None):
+ 36        """
+ 37        Creates a new AzureCredentialManager object.
+ 38
+ 39        :param resource_location: The URL or other location of the requested resource.
+ 40        :param scope: A space-delimited list of scopes to limit access to resource.
+ 41          Default: `None`
+ 42        """
+ 43        self.__resource_location = resource_location
+ 44        self.__scope = scope
+ 45        self.__access_token = None
+ 46
+ 47        if self.scope is None:
+ 48            self.__scope = f"{self.resource_location}/.default"
+ 49
+ 50    def get_credential_object(self) -> object:
+ 51        """
+ 52        Gets an Azure-specific credential object.
+ 53
+ 54        :return: An instance of one of the \\*Credential objects from the
+ 55          `azure.identity` package.
+ 56        """
+ 57        return DefaultAzureCredential()
+ 58
+ 59    def get_access_token(self, force_refresh: bool = False) -> str:
+ 60        """
+ 61        Obtains an access token from the Azure identity provider. Returns the
+ 62        access token string, refreshed if expired or force_refresh is specified.
+ 63
+ 64        :param force_refresh: `True` if a new token should be requested, regardless
+ 65          of expiration timestamp. `False` otherwise. Default: `False`
+ 66        :return: An Azure access token.
+ 67        """
+ 68        if force_refresh or (self.access_token is None) or self._need_new_token():
+ 69            creds = self.get_credential_object()
+ 70            self.__access_token = creds.get_token(self.scope)
+ 71
+ 72        return self.access_token.token
+ 73
+ 74    def _need_new_token(self) -> bool:
+ 75        """
+ 76        Determines whether the token already stored for this object can be reused,
+ 77        or if it needs to be re-requested. A new token is needed if a token has not
+ 78        yet been created, or if the current token has expired.
+ 79
+ 80        :return: True if a new Azure access token is needed; false otherwise.
+ 81        """
+ 82        try:
+ 83            current_time_utc = datetime.now(timezone.utc).timestamp()
+ 84            return self.access_token.expires_on < current_time_utc
+ 85        except AttributeError:
+ 86            # access_token not set
+ 87            return True
+ 88
+ 89    def get_secret(self, secret_name: str, key_vault_name: str) -> str:
+ 90        """
+ 91        Get the value of a secret from an Azure key vault given the names of the vault
+ 92        and the secret.
+ 93
+ 94        :param secret_name: The name of the secret whose value should be retrieved from
+ 95            the key vault.
+ 96        :param key_vault_name: The name of the key vault where the secret is stored.
+ 97        :return: The value of the secret specified by secret_name.
+ 98        """
+ 99
+100        vault_url = f"https://{key_vault_name}.vault.azure.net"
+101        secret_client = SecretClient(
+102            vault_url=vault_url, credential=self.get_credential_object()
+103        )
+104        return secret_client.get_secret(secret_name).value
+105
+106
+107class AzureCloudContainerConnection(BaseCloudStorageConnection):
+108    """
+109    Defines a connection used for interacting with cloud storage in Azure.
+110    """
+111
+112    @property
+113    def storage_account_url(self) -> str:
+114        return self.__storage_account_url
+115
+116    @property
+117    def cred_manager(self) -> AzureCredentialManager:
+118        return self.__cred_manager
+119
+120    def __init__(self, storage_account_url: str, cred_manager: AzureCredentialManager):
+121        """
+122        Creates a new AzureCloudContainerConnection object.
+123
+124        :param storage_account_url: The storage account location of the requested
+125          resource.
+126        :param cred_manager: The credential manager used to authenticate to the
+127          FHIR server.
+128        """
+129        self.__storage_account_url = storage_account_url
+130        self.__cred_manager = cred_manager
+131
+132    def _get_container_client(self, container_url: str) -> ContainerClient:
+133        """
+134        Obtains a client connected to an Azure storage container by
+135        utilizing the first valid credentials Azure can find. For
+136        more information on the order in which the credentials are
+137        checked, see the Azure documentation:
+138        https://docs.microsoft.com/en-us/azure/developer/python/sdk/authentication-overview#sequence-of-authentication-methods-when-using-defaultazurecredential
+139
+140        :param container_url: The url at which to access the container.
+141        :return: The Azure `ContainerClient`.
+142        """
+143        creds = self.cred_manager.get_credential_object()
+144        return ContainerClient.from_container_url(container_url, credential=creds)
+145
+146    def download_object(
+147        self,
+148        container_name: str,
+149        filename: str,
+150        encoding: Literal[None, str] = "UTF-8",
+151    ) -> Literal[str, bytes]:
+152        """
+153        Downloads a blob from storage and returns it as a string or bytes.
+154
+155        :param container_name: The name of the container containing object to download.
+156        :param filename: The location of the file within Azure blob storage.
+157        :param encoding: The encoding applied to the downloaded content. If set to None
+158            then the blob contents will be returned as bytes. Default: UTF-8
+159        :return: A character blob as a string from the given container and filename.
+160        """
+161        container_location = f"{self.storage_account_url}/{container_name}"
+162        container_client = self._get_container_client(container_location)
+163        blob_client = container_client.get_blob_client(filename)
+164
+165        downloader = blob_client.download_blob(encoding=encoding)
+166
+167        blob_contents = downloader.readall()
+168
+169        return blob_contents
+170
+171    def upload_object(
+172        self,
+173        message: Union[str, dict],
+174        container_name: str,
+175        filename: str,
+176    ) -> None:
+177        """
+178        Uploads the content of a given message to Azure blob storage.
+179        The message can be passed either as a raw string or as JSON.
+180
+181        :param message: The contents of a message, encoded either as a
+182          string or a JSON-formatted dictionary.
+183        :param container_name: The name of the target container for upload.
+184        :param filename: The location of file to upload within Azure blob storage.
+185        """
+186        container_location = f"{self.storage_account_url}/{container_name}"
+187        container_client = self._get_container_client(container_location)
+188        blob_client = container_client.get_blob_client(filename)
+189
+190        if isinstance(message, str):
+191            blob_client.upload_blob(bytes(message, "utf-8"), overwrite=True)
+192        elif isinstance(message, dict):
+193            blob_client.upload_blob(json.dumps(message).encode("utf-8"), overwrite=True)
+194
+195    def list_containers(self) -> List[str]:
+196        """
+197        Lists names for this CloudContainerConnection's containers.
+198
+199        :return: A list of container names.
+200        """
+201        creds = self.cred_manager.get_credential_object()
+202        service_client = BlobServiceClient(
+203            account_url=self.storage_account_url, credential=creds
+204        )
+205        container_properties_generator = service_client.list_containers()
+206
+207        container_name_list = []
+208        for container_propreties in container_properties_generator:
+209            container_name_list.append(container_propreties.name)
+210
+211        return container_name_list
+212
+213    def list_objects(self, container_name: str, prefix: str = "") -> List[str]:
+214        """
+215        Lists names for objects within a container.
+216
+217        :param container_name: The name of the container to look for objects.
+218        :param prefix: Filter the objects returned to filenames beginning
+219          with this value.
+220        :return: A list of names for objects in given container.
+221        """
+222        container_location = f"{self.storage_account_url}/{container_name}"
+223        container_client = self._get_container_client(container_location)
+224
+225        blob_properties_generator = container_client.list_blobs(name_starts_with=prefix)
+226
+227        blob_name_list = []
+228        for blob_propreties in blob_properties_generator:
+229            blob_name_list.append(blob_propreties.name)
+230
+231        return blob_name_list
+232
+233    def blob_exists(self, container_name: str, filename: str) -> bool:
+234        """
+235        Check if a blob exists within a container given its name and the name of the
+236        container.
+237
+238        :param container_name: The name of the container to look for the blob in.
+239        :param filename: The name of the blob to check the existence of.
+240        :param prefix: Filter the objects returned to filenames beginning
+241          with this value.
+242        :return: A boolean of true if the file exists and false if it does not.
+243        """
+244
+245        container_location = f"{self.storage_account_url}/{container_name}"
+246        container_client = self._get_container_client(container_location)
+247        blob_client = container_client.get_blob_client(filename)
+248        return blob_client.exists()
+
+ + +
+
+ +
+ + class + AzureCredentialManager(phdi.cloud.core.BaseCredentialManager): + + + +
+ + 
 19class AzureCredentialManager(BaseCredentialManager):
+ 20    """
+ 21    Defines a credential manager used for connecting to Azure.
+ 22    """
+ 23
+ 24    @property
+ 25    def resource_location(self) -> str:
+ 26        return self.__resource_location
+ 27
+ 28    @property
+ 29    def scope(self) -> str:
+ 30        return self.__scope
+ 31
+ 32    @property
+ 33    def access_token(self) -> AccessToken:
+ 34        return self.__access_token
+ 35
+ 36    def __init__(self, resource_location: str = None, scope: str = None):
+ 37        """
+ 38        Creates a new AzureCredentialManager object.
+ 39
+ 40        :param resource_location: The URL or other location of the requested resource.
+ 41        :param scope: A space-delimited list of scopes to limit access to resource.
+ 42          Default: `None`
+ 43        """
+ 44        self.__resource_location = resource_location
+ 45        self.__scope = scope
+ 46        self.__access_token = None
+ 47
+ 48        if self.scope is None:
+ 49            self.__scope = f"{self.resource_location}/.default"
+ 50
+ 51    def get_credential_object(self) -> object:
+ 52        """
+ 53        Gets an Azure-specific credential object.
+ 54
+ 55        :return: An instance of one of the \\*Credential objects from the
+ 56          `azure.identity` package.
+ 57        """
+ 58        return DefaultAzureCredential()
+ 59
+ 60    def get_access_token(self, force_refresh: bool = False) -> str:
+ 61        """
+ 62        Obtains an access token from the Azure identity provider. Returns the
+ 63        access token string, refreshed if expired or force_refresh is specified.
+ 64
+ 65        :param force_refresh: `True` if a new token should be requested, regardless
+ 66          of expiration timestamp. `False` otherwise. Default: `False`
+ 67        :return: An Azure access token.
+ 68        """
+ 69        if force_refresh or (self.access_token is None) or self._need_new_token():
+ 70            creds = self.get_credential_object()
+ 71            self.__access_token = creds.get_token(self.scope)
+ 72
+ 73        return self.access_token.token
+ 74
+ 75    def _need_new_token(self) -> bool:
+ 76        """
+ 77        Determines whether the token already stored for this object can be reused,
+ 78        or if it needs to be re-requested. A new token is needed if a token has not
+ 79        yet been created, or if the current token has expired.
+ 80
+ 81        :return: True if a new Azure access token is needed; false otherwise.
+ 82        """
+ 83        try:
+ 84            current_time_utc = datetime.now(timezone.utc).timestamp()
+ 85            return self.access_token.expires_on < current_time_utc
+ 86        except AttributeError:
+ 87            # access_token not set
+ 88            return True
+ 89
+ 90    def get_secret(self, secret_name: str, key_vault_name: str) -> str:
+ 91        """
+ 92        Get the value of a secret from an Azure key vault given the names of the vault
+ 93        and the secret.
+ 94
+ 95        :param secret_name: The name of the secret whose value should be retrieved from
+ 96            the key vault.
+ 97        :param key_vault_name: The name of the key vault where the secret is stored.
+ 98        :return: The value of the secret specified by secret_name.
+ 99        """
+100
+101        vault_url = f"https://{key_vault_name}.vault.azure.net"
+102        secret_client = SecretClient(
+103            vault_url=vault_url, credential=self.get_credential_object()
+104        )
+105        return secret_client.get_secret(secret_name).value
+
+ + +

Defines a credential manager used for connecting to Azure.

+
+ + +
+ +
+ + AzureCredentialManager(resource_location: str = None, scope: str = None) + + + +
+ + 
36    def __init__(self, resource_location: str = None, scope: str = None):
+37        """
+38        Creates a new AzureCredentialManager object.
+39
+40        :param resource_location: The URL or other location of the requested resource.
+41        :param scope: A space-delimited list of scopes to limit access to resource.
+42          Default: `None`
+43        """
+44        self.__resource_location = resource_location
+45        self.__scope = scope
+46        self.__access_token = None
+47
+48        if self.scope is None:
+49            self.__scope = f"{self.resource_location}/.default"
+
+ + +

Creates a new AzureCredentialManager object.

+ +
Parameters
+ +
    +
  • resource_location: The URL or other location of the requested resource.
    • +
  • scope: A space-delimited list of scopes to limit access to resource. +Default: None
    • +
+
+ + +
+
+ +
+ + def + get_credential_object(self) -> object: + + + +
+ + 
51    def get_credential_object(self) -> object:
+52        """
+53        Gets an Azure-specific credential object.
+54
+55        :return: An instance of one of the \\*Credential objects from the
+56          `azure.identity` package.
+57        """
+58        return DefaultAzureCredential()
+
+ + +

Gets an Azure-specific credential object.

+ +
Returns
+ +
+

An instance of one of the *Credential objects from the + azure.identity package.

+
+
+ + +
+
+ +
+ + def + get_access_token(self, force_refresh: bool = False) -> str: + + + +
+ + 
60    def get_access_token(self, force_refresh: bool = False) -> str:
+61        """
+62        Obtains an access token from the Azure identity provider. Returns the
+63        access token string, refreshed if expired or force_refresh is specified.
+64
+65        :param force_refresh: `True` if a new token should be requested, regardless
+66          of expiration timestamp. `False` otherwise. Default: `False`
+67        :return: An Azure access token.
+68        """
+69        if force_refresh or (self.access_token is None) or self._need_new_token():
+70            creds = self.get_credential_object()
+71            self.__access_token = creds.get_token(self.scope)
+72
+73        return self.access_token.token
+
+ + +

Obtains an access token from the Azure identity provider. Returns the +access token string, refreshed if expired or force_refresh is specified.

+ +
Parameters
+ +
    +
  • force_refresh: True if a new token should be requested, regardless +of expiration timestamp. False otherwise. Default: False
    • +
+ +
Returns
+ +
+

An Azure access token.

+
+
+ + +
+
+ +
+ + def + get_secret(self, secret_name: str, key_vault_name: str) -> str: + + + +
+ + 
 90    def get_secret(self, secret_name: str, key_vault_name: str) -> str:
+ 91        """
+ 92        Get the value of a secret from an Azure key vault given the names of the vault
+ 93        and the secret.
+ 94
+ 95        :param secret_name: The name of the secret whose value should be retrieved from
+ 96            the key vault.
+ 97        :param key_vault_name: The name of the key vault where the secret is stored.
+ 98        :return: The value of the secret specified by secret_name.
+ 99        """
+100
+101        vault_url = f"https://{key_vault_name}.vault.azure.net"
+102        secret_client = SecretClient(
+103            vault_url=vault_url, credential=self.get_credential_object()
+104        )
+105        return secret_client.get_secret(secret_name).value
+
+ + +

Get the value of a secret from an Azure key vault given the names of the vault +and the secret.

+ +
Parameters
+ +
    +
  • secret_name: The name of the secret whose value should be retrieved from +the key vault.
    • +
  • key_vault_name: The name of the key vault where the secret is stored.
    • +
+ +
Returns
+ +
+

The value of the secret specified by secret_name.

+
+
+ + +
+
+
+ +
+ + class + AzureCloudContainerConnection(phdi.cloud.core.BaseCloudStorageConnection): + + + +
+ + 
108class AzureCloudContainerConnection(BaseCloudStorageConnection):
+109    """
+110    Defines a connection used for interacting with cloud storage in Azure.
+111    """
+112
+113    @property
+114    def storage_account_url(self) -> str:
+115        return self.__storage_account_url
+116
+117    @property
+118    def cred_manager(self) -> AzureCredentialManager:
+119        return self.__cred_manager
+120
+121    def __init__(self, storage_account_url: str, cred_manager: AzureCredentialManager):
+122        """
+123        Creates a new AzureCloudContainerConnection object.
+124
+125        :param storage_account_url: The storage account location of the requested
+126          resource.
+127        :param cred_manager: The credential manager used to authenticate to the
+128          FHIR server.
+129        """
+130        self.__storage_account_url = storage_account_url
+131        self.__cred_manager = cred_manager
+132
+133    def _get_container_client(self, container_url: str) -> ContainerClient:
+134        """
+135        Obtains a client connected to an Azure storage container by
+136        utilizing the first valid credentials Azure can find. For
+137        more information on the order in which the credentials are
+138        checked, see the Azure documentation:
+139        https://docs.microsoft.com/en-us/azure/developer/python/sdk/authentication-overview#sequence-of-authentication-methods-when-using-defaultazurecredential
+140
+141        :param container_url: The url at which to access the container.
+142        :return: The Azure `ContainerClient`.
+143        """
+144        creds = self.cred_manager.get_credential_object()
+145        return ContainerClient.from_container_url(container_url, credential=creds)
+146
+147    def download_object(
+148        self,
+149        container_name: str,
+150        filename: str,
+151        encoding: Literal[None, str] = "UTF-8",
+152    ) -> Literal[str, bytes]:
+153        """
+154        Downloads a blob from storage and returns it as a string or bytes.
+155
+156        :param container_name: The name of the container containing object to download.
+157        :param filename: The location of the file within Azure blob storage.
+158        :param encoding: The encoding applied to the downloaded content. If set to None
+159            then the blob contents will be returned as bytes. Default: UTF-8
+160        :return: A character blob as a string from the given container and filename.
+161        """
+162        container_location = f"{self.storage_account_url}/{container_name}"
+163        container_client = self._get_container_client(container_location)
+164        blob_client = container_client.get_blob_client(filename)
+165
+166        downloader = blob_client.download_blob(encoding=encoding)
+167
+168        blob_contents = downloader.readall()
+169
+170        return blob_contents
+171
+172    def upload_object(
+173        self,
+174        message: Union[str, dict],
+175        container_name: str,
+176        filename: str,
+177    ) -> None:
+178        """
+179        Uploads the content of a given message to Azure blob storage.
+180        The message can be passed either as a raw string or as JSON.
+181
+182        :param message: The contents of a message, encoded either as a
+183          string or a JSON-formatted dictionary.
+184        :param container_name: The name of the target container for upload.
+185        :param filename: The location of file to upload within Azure blob storage.
+186        """
+187        container_location = f"{self.storage_account_url}/{container_name}"
+188        container_client = self._get_container_client(container_location)
+189        blob_client = container_client.get_blob_client(filename)
+190
+191        if isinstance(message, str):
+192            blob_client.upload_blob(bytes(message, "utf-8"), overwrite=True)
+193        elif isinstance(message, dict):
+194            blob_client.upload_blob(json.dumps(message).encode("utf-8"), overwrite=True)
+195
+196    def list_containers(self) -> List[str]:
+197        """
+198        Lists names for this CloudContainerConnection's containers.
+199
+200        :return: A list of container names.
+201        """
+202        creds = self.cred_manager.get_credential_object()
+203        service_client = BlobServiceClient(
+204            account_url=self.storage_account_url, credential=creds
+205        )
+206        container_properties_generator = service_client.list_containers()
+207
+208        container_name_list = []
+209        for container_propreties in container_properties_generator:
+210            container_name_list.append(container_propreties.name)
+211
+212        return container_name_list
+213
+214    def list_objects(self, container_name: str, prefix: str = "") -> List[str]:
+215        """
+216        Lists names for objects within a container.
+217
+218        :param container_name: The name of the container to look for objects.
+219        :param prefix: Filter the objects returned to filenames beginning
+220          with this value.
+221        :return: A list of names for objects in given container.
+222        """
+223        container_location = f"{self.storage_account_url}/{container_name}"
+224        container_client = self._get_container_client(container_location)
+225
+226        blob_properties_generator = container_client.list_blobs(name_starts_with=prefix)
+227
+228        blob_name_list = []
+229        for blob_propreties in blob_properties_generator:
+230            blob_name_list.append(blob_propreties.name)
+231
+232        return blob_name_list
+233
+234    def blob_exists(self, container_name: str, filename: str) -> bool:
+235        """
+236        Check if a blob exists within a container given its name and the name of the
+237        container.
+238
+239        :param container_name: The name of the container to look for the blob in.
+240        :param filename: The name of the blob to check the existence of.
+241        :param prefix: Filter the objects returned to filenames beginning
+242          with this value.
+243        :return: A boolean of true if the file exists and false if it does not.
+244        """
+245
+246        container_location = f"{self.storage_account_url}/{container_name}"
+247        container_client = self._get_container_client(container_location)
+248        blob_client = container_client.get_blob_client(filename)
+249        return blob_client.exists()
+
+ + +

Defines a connection used for interacting with cloud storage in Azure.

+
+ + +
+ +
+ + AzureCloudContainerConnection( storage_account_url: str, cred_manager: phdi.cloud.azure.AzureCredentialManager) + + + +
+ + 
121    def __init__(self, storage_account_url: str, cred_manager: AzureCredentialManager):
+122        """
+123        Creates a new AzureCloudContainerConnection object.
+124
+125        :param storage_account_url: The storage account location of the requested
+126          resource.
+127        :param cred_manager: The credential manager used to authenticate to the
+128          FHIR server.
+129        """
+130        self.__storage_account_url = storage_account_url
+131        self.__cred_manager = cred_manager
+
+ + +

Creates a new AzureCloudContainerConnection object.

+ +
Parameters
+ +
    +
  • storage_account_url: The storage account location of the requested +resource.
    • +
  • cred_manager: The credential manager used to authenticate to the +FHIR server.
    • +
+
+ + +
+
+ +
+ + def + download_object( self, container_name: str, filename: str, encoding: Literal[None, str] = 'UTF-8') -> Literal[str, bytes]: + + + +
+ + 
147    def download_object(
+148        self,
+149        container_name: str,
+150        filename: str,
+151        encoding: Literal[None, str] = "UTF-8",
+152    ) -> Literal[str, bytes]:
+153        """
+154        Downloads a blob from storage and returns it as a string or bytes.
+155
+156        :param container_name: The name of the container containing object to download.
+157        :param filename: The location of the file within Azure blob storage.
+158        :param encoding: The encoding applied to the downloaded content. If set to None
+159            then the blob contents will be returned as bytes. Default: UTF-8
+160        :return: A character blob as a string from the given container and filename.
+161        """
+162        container_location = f"{self.storage_account_url}/{container_name}"
+163        container_client = self._get_container_client(container_location)
+164        blob_client = container_client.get_blob_client(filename)
+165
+166        downloader = blob_client.download_blob(encoding=encoding)
+167
+168        blob_contents = downloader.readall()
+169
+170        return blob_contents
+
+ + +

Downloads a blob from storage and returns it as a string or bytes.

+ +
Parameters
+ +
    +
  • container_name: The name of the container containing object to download.
    • +
  • filename: The location of the file within Azure blob storage.
    • +
  • encoding: The encoding applied to the downloaded content. If set to None +then the blob contents will be returned as bytes. Default: UTF-8
    • +
+ +
Returns
+ +
+

A character blob as a string from the given container and filename.

+
+
+ + +
+
+ +
+ + def + upload_object( self, message: Union[str, dict], container_name: str, filename: str) -> None: + + + +
+ + 
172    def upload_object(
+173        self,
+174        message: Union[str, dict],
+175        container_name: str,
+176        filename: str,
+177    ) -> None:
+178        """
+179        Uploads the content of a given message to Azure blob storage.
+180        The message can be passed either as a raw string or as JSON.
+181
+182        :param message: The contents of a message, encoded either as a
+183          string or a JSON-formatted dictionary.
+184        :param container_name: The name of the target container for upload.
+185        :param filename: The location of file to upload within Azure blob storage.
+186        """
+187        container_location = f"{self.storage_account_url}/{container_name}"
+188        container_client = self._get_container_client(container_location)
+189        blob_client = container_client.get_blob_client(filename)
+190
+191        if isinstance(message, str):
+192            blob_client.upload_blob(bytes(message, "utf-8"), overwrite=True)
+193        elif isinstance(message, dict):
+194            blob_client.upload_blob(json.dumps(message).encode("utf-8"), overwrite=True)
+
+ + +

Uploads the content of a given message to Azure blob storage. +The message can be passed either as a raw string or as JSON.

+ +
Parameters
+ +
    +
  • message: The contents of a message, encoded either as a +string or a JSON-formatted dictionary.
    • +
  • container_name: The name of the target container for upload.
    • +
  • filename: The location of file to upload within Azure blob storage.
    • +
+
+ + +
+
+ +
+ + def + list_containers(self) -> List[str]: + + + +
+ + 
196    def list_containers(self) -> List[str]:
+197        """
+198        Lists names for this CloudContainerConnection's containers.
+199
+200        :return: A list of container names.
+201        """
+202        creds = self.cred_manager.get_credential_object()
+203        service_client = BlobServiceClient(
+204            account_url=self.storage_account_url, credential=creds
+205        )
+206        container_properties_generator = service_client.list_containers()
+207
+208        container_name_list = []
+209        for container_propreties in container_properties_generator:
+210            container_name_list.append(container_propreties.name)
+211
+212        return container_name_list
+
+ + +

Lists names for this CloudContainerConnection's containers.

+ +
Returns
+ +
+

A list of container names.

+
+
+ + +
+
+ +
+ + def + list_objects(self, container_name: str, prefix: str = '') -> List[str]: + + + +
+ + 
214    def list_objects(self, container_name: str, prefix: str = "") -> List[str]:
+215        """
+216        Lists names for objects within a container.
+217
+218        :param container_name: The name of the container to look for objects.
+219        :param prefix: Filter the objects returned to filenames beginning
+220          with this value.
+221        :return: A list of names for objects in given container.
+222        """
+223        container_location = f"{self.storage_account_url}/{container_name}"
+224        container_client = self._get_container_client(container_location)
+225
+226        blob_properties_generator = container_client.list_blobs(name_starts_with=prefix)
+227
+228        blob_name_list = []
+229        for blob_propreties in blob_properties_generator:
+230            blob_name_list.append(blob_propreties.name)
+231
+232        return blob_name_list
+
+ + +

Lists names for objects within a container.

+ +
Parameters
+ +
    +
  • container_name: The name of the container to look for objects.
    • +
  • prefix: Filter the objects returned to filenames beginning +with this value.
    • +
+ +
Returns
+ +
+

A list of names for objects in given container.

+
+
+ + +
+
+ +
+ + def + blob_exists(self, container_name: str, filename: str) -> bool: + + + +
+ + 
234    def blob_exists(self, container_name: str, filename: str) -> bool:
+235        """
+236        Check if a blob exists within a container given its name and the name of the
+237        container.
+238
+239        :param container_name: The name of the container to look for the blob in.
+240        :param filename: The name of the blob to check the existence of.
+241        :param prefix: Filter the objects returned to filenames beginning
+242          with this value.
+243        :return: A boolean of true if the file exists and false if it does not.
+244        """
+245
+246        container_location = f"{self.storage_account_url}/{container_name}"
+247        container_client = self._get_container_client(container_location)
+248        blob_client = container_client.get_blob_client(filename)
+249        return blob_client.exists()
+
+ + +

Check if a blob exists within a container given its name and the name of the +container.

+ +
Parameters
+ +
    +
  • container_name: The name of the container to look for the blob in.
    • +
  • filename: The name of the blob to check the existence of.
    • +
  • prefix: Filter the objects returned to filenames beginning +with this value.
    • +
+ +
Returns
+ +
+

A boolean of true if the file exists and false if it does not.

+
+
+ + +
+
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/cloud/core.html b/docs/v1.2.7/sdk/phdi/cloud/core.html new file mode 100644 index 0000000000..497e29f3a0 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/cloud/core.html @@ -0,0 +1,713 @@ + + + + + + + phdi.cloud.core API documentation + + + + + + + + + +
+
+

+phdi.cloud.core

+ + + + + + + 
 1from abc import ABC
+ 2from abc import abstractmethod
+ 3from typing import List
+ 4from typing import Union
+ 5
+ 6
+ 7class BaseCredentialManager(ABC):
+ 8    """
+ 9    Provides a common interface for managing service credentials.
+10    """
+11
+12    @abstractmethod
+13    def get_credential_object(self) -> object:
+14        """
+15        Gets a cloud-specific credential object.
+16
+17        :return: A credential object.
+18        """
+19        pass  # pragma: no cover
+20
+21    @abstractmethod
+22    def get_access_token(self) -> str:
+23        """
+24        Gets an access token using the managed credentials.
+25
+26        :return: An access token.
+27        """
+28        pass  # pragma: no cover
+29
+30
+31class BaseCloudStorageConnection(ABC):
+32    @abstractmethod
+33    def download_object(
+34        self, container_name: str, filename: str, encoding: str = "utf-8"
+35    ) -> str:
+36        """
+37        Downloads a blob from storage.
+38
+39        :param container_name: The name of the container containing object to download.
+40        :param filename: The location of file within storage.
+41        :param encoding: The character encoding applied to the downloaded content.
+42        :return: The `stream` parameter, if supplied. Otherwise a new stream object
+43          containing blob content.
+44        """
+45        pass  # pragma: no cover
+46
+47    @abstractmethod
+48    def upload_object(
+49        self,
+50        message: Union[str, dict],
+51        container_name: str,
+52        filename: str,
+53    ) -> None:
+54        """
+55        Uploads the content of a given message to blob storage.
+56        The message can be passed either as a raw string or as JSON.
+57
+58        :param message: The contents of a message, encoded either as a
+59          string or in a JSON format.
+60        :param container_name: The name of the target container for upload.
+61        :param filename: The location of file within storage container.
+62        """
+63        pass  # pragma: no cover
+64
+65    @abstractmethod
+66    def list_containers(self) -> List[str]:
+67        """
+68        Lists names for this CloudContainerConnection's containers.
+69
+70        :return: A list of container names.
+71        """
+72        pass  # pragma: no cover
+73
+74    @abstractmethod
+75    def list_objects(self, container_name: str, prefix: str) -> List[str]:
+76        """
+77        Lists names for objects within a container.
+78
+79        :param container_name: The name of the container to look for objects.
+80        :param prefix: Filter the objects returned to filenames beginning
+81          with this value.
+82        :return: A list of objects within a container.
+83        """
+84        pass  # pragma: no cover
+
+ + +
+
+ +
+ + class + BaseCredentialManager(abc.ABC): + + + +
+ + 
 8class BaseCredentialManager(ABC):
+ 9    """
+10    Provides a common interface for managing service credentials.
+11    """
+12
+13    @abstractmethod
+14    def get_credential_object(self) -> object:
+15        """
+16        Gets a cloud-specific credential object.
+17
+18        :return: A credential object.
+19        """
+20        pass  # pragma: no cover
+21
+22    @abstractmethod
+23    def get_access_token(self) -> str:
+24        """
+25        Gets an access token using the managed credentials.
+26
+27        :return: An access token.
+28        """
+29        pass  # pragma: no cover
+
+ + +

Provides a common interface for managing service credentials.

+
+ + +
+ +
+
@abstractmethod
+ + def + get_credential_object(self) -> object: + + + +
+ + 
13    @abstractmethod
+14    def get_credential_object(self) -> object:
+15        """
+16        Gets a cloud-specific credential object.
+17
+18        :return: A credential object.
+19        """
+20        pass  # pragma: no cover
+
+ + +

Gets a cloud-specific credential object.

+ +
Returns
+ +
+

A credential object.

+
+
+ + +
+
+ +
+
@abstractmethod
+ + def + get_access_token(self) -> str: + + + +
+ + 
22    @abstractmethod
+23    def get_access_token(self) -> str:
+24        """
+25        Gets an access token using the managed credentials.
+26
+27        :return: An access token.
+28        """
+29        pass  # pragma: no cover
+
+ + +

Gets an access token using the managed credentials.

+ +
Returns
+ +
+

An access token.

+
+
+ + +
+
+
+ +
+ + class + BaseCloudStorageConnection(abc.ABC): + + + +
+ + 
32class BaseCloudStorageConnection(ABC):
+33    @abstractmethod
+34    def download_object(
+35        self, container_name: str, filename: str, encoding: str = "utf-8"
+36    ) -> str:
+37        """
+38        Downloads a blob from storage.
+39
+40        :param container_name: The name of the container containing object to download.
+41        :param filename: The location of file within storage.
+42        :param encoding: The character encoding applied to the downloaded content.
+43        :return: The `stream` parameter, if supplied. Otherwise a new stream object
+44          containing blob content.
+45        """
+46        pass  # pragma: no cover
+47
+48    @abstractmethod
+49    def upload_object(
+50        self,
+51        message: Union[str, dict],
+52        container_name: str,
+53        filename: str,
+54    ) -> None:
+55        """
+56        Uploads the content of a given message to blob storage.
+57        The message can be passed either as a raw string or as JSON.
+58
+59        :param message: The contents of a message, encoded either as a
+60          string or in a JSON format.
+61        :param container_name: The name of the target container for upload.
+62        :param filename: The location of file within storage container.
+63        """
+64        pass  # pragma: no cover
+65
+66    @abstractmethod
+67    def list_containers(self) -> List[str]:
+68        """
+69        Lists names for this CloudContainerConnection's containers.
+70
+71        :return: A list of container names.
+72        """
+73        pass  # pragma: no cover
+74
+75    @abstractmethod
+76    def list_objects(self, container_name: str, prefix: str) -> List[str]:
+77        """
+78        Lists names for objects within a container.
+79
+80        :param container_name: The name of the container to look for objects.
+81        :param prefix: Filter the objects returned to filenames beginning
+82          with this value.
+83        :return: A list of objects within a container.
+84        """
+85        pass  # pragma: no cover
+
+ + +

Helper class that provides a standard way to create an ABC using +inheritance.

+
+ + +
+ +
+
@abstractmethod
+ + def + download_object(self, container_name: str, filename: str, encoding: str = 'utf-8') -> str: + + + +
+ + 
33    @abstractmethod
+34    def download_object(
+35        self, container_name: str, filename: str, encoding: str = "utf-8"
+36    ) -> str:
+37        """
+38        Downloads a blob from storage.
+39
+40        :param container_name: The name of the container containing object to download.
+41        :param filename: The location of file within storage.
+42        :param encoding: The character encoding applied to the downloaded content.
+43        :return: The `stream` parameter, if supplied. Otherwise a new stream object
+44          containing blob content.
+45        """
+46        pass  # pragma: no cover
+
+ + +

Downloads a blob from storage.

+ +
Parameters
+ +
    +
  • container_name: The name of the container containing object to download.
    • +
  • filename: The location of file within storage.
    • +
  • encoding: The character encoding applied to the downloaded content.
    • +
+ +
Returns
+ +
+

The stream parameter, if supplied. Otherwise a new stream object + containing blob content.

+
+
+ + +
+
+ +
+
@abstractmethod
+ + def + upload_object( self, message: Union[str, dict], container_name: str, filename: str) -> None: + + + +
+ + 
48    @abstractmethod
+49    def upload_object(
+50        self,
+51        message: Union[str, dict],
+52        container_name: str,
+53        filename: str,
+54    ) -> None:
+55        """
+56        Uploads the content of a given message to blob storage.
+57        The message can be passed either as a raw string or as JSON.
+58
+59        :param message: The contents of a message, encoded either as a
+60          string or in a JSON format.
+61        :param container_name: The name of the target container for upload.
+62        :param filename: The location of file within storage container.
+63        """
+64        pass  # pragma: no cover
+
+ + +

Uploads the content of a given message to blob storage. +The message can be passed either as a raw string or as JSON.

+ +
Parameters
+ +
    +
  • message: The contents of a message, encoded either as a +string or in a JSON format.
    • +
  • container_name: The name of the target container for upload.
    • +
  • filename: The location of file within storage container.
    • +
+
+ + +
+
+ +
+
@abstractmethod
+ + def + list_containers(self) -> List[str]: + + + +
+ + 
66    @abstractmethod
+67    def list_containers(self) -> List[str]:
+68        """
+69        Lists names for this CloudContainerConnection's containers.
+70
+71        :return: A list of container names.
+72        """
+73        pass  # pragma: no cover
+
+ + +

Lists names for this CloudContainerConnection's containers.

+ +
Returns
+ +
+

A list of container names.

+
+
+ + +
+
+ +
+
@abstractmethod
+ + def + list_objects(self, container_name: str, prefix: str) -> List[str]: + + + +
+ + 
75    @abstractmethod
+76    def list_objects(self, container_name: str, prefix: str) -> List[str]:
+77        """
+78        Lists names for objects within a container.
+79
+80        :param container_name: The name of the container to look for objects.
+81        :param prefix: Filter the objects returned to filenames beginning
+82          with this value.
+83        :return: A list of objects within a container.
+84        """
+85        pass  # pragma: no cover
+
+ + +

Lists names for objects within a container.

+ +
Parameters
+ +
    +
  • container_name: The name of the container to look for objects.
    • +
  • prefix: Filter the objects returned to filenames beginning +with this value.
    • +
+ +
Returns
+ +
+

A list of objects within a container.

+
+
+ + +
+
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/cloud/gcp.html b/docs/v1.2.7/sdk/phdi/cloud/gcp.html new file mode 100644 index 0000000000..85a12d2bf7 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/cloud/gcp.html @@ -0,0 +1,1069 @@ + + + + + + + phdi.cloud.gcp API documentation + + + + + + + + + +
+
+

+phdi.cloud.gcp

+ + + + + + + 
  1import json
+  2from typing import List
+  3from typing import Union
+  4
+  5import google.auth.transport.requests
+  6from google.auth.credentials import Credentials
+  7from google.cloud import storage
+  8
+  9from .core import BaseCloudStorageConnection
+ 10from .core import BaseCredentialManager
+ 11
+ 12
+ 13class GcpCredentialManager(BaseCredentialManager):
+ 14    """
+ 15    Provides a GCP-specific credential manager.
+ 16    """
+ 17
+ 18    @property
+ 19    def scope(self) -> str:
+ 20        return self.__scope
+ 21
+ 22    @property
+ 23    def scoped_credentials(self) -> Credentials:
+ 24        return self.__scoped_credentials
+ 25
+ 26    @property
+ 27    def project_id(self) -> str:
+ 28        return self.__project_id
+ 29
+ 30    def __init__(self, scope: list = None):
+ 31        """
+ 32        Creates a new GcpCredentialManager object.
+ 33
+ 34        :param scope: A list of scopes to limit access to resource.
+ 35        """
+ 36        self.__scope = scope
+ 37        self.__scoped_credentials = None
+ 38        self.__project_id = None
+ 39
+ 40        if self.scope is None:
+ 41            self.__scope = ["https://www.googleapis.com/auth/cloud-platform"]
+ 42
+ 43    def get_credential_object(self) -> Credentials:
+ 44        """
+ 45        Gets a GCP-specific credential object.
+ 46
+ 47        :return: A scoped instance of the Credentials class from google.auth
+ 48            package, refreshed if necessary.
+ 49        """
+ 50        # Get credentials if they don't exist or are expired.
+ 51        if self.__scoped_credentials is None:
+ 52            self.__scoped_credentials, self.__project_id = google.auth.default(
+ 53                scopes=self.scope
+ 54            )
+ 55        elif self.__scoped_credentials.expired:
+ 56            self.__scoped_credentials, self.__project_id = google.auth.default(
+ 57                scopes=self.scope
+ 58            )
+ 59
+ 60        return self.__scoped_credentials
+ 61
+ 62    def get_project_id(self) -> str:
+ 63        """
+ 64        Gets the ID of the current GCP project.
+ 65
+ 66        :return: The current GCP project ID.
+ 67        """
+ 68
+ 69        if self.__project_id is None:
+ 70            self.__scoped_credentials, self.__project_id = google.auth.default(
+ 71                scopes=self.scope
+ 72            )
+ 73        return self.__project_id
+ 74
+ 75    def get_access_token(self) -> str:
+ 76        """
+ 77        Obtains an access token from GCP.
+ 78
+ 79        :return: The access token, refreshed if necessary.
+ 80        """
+ 81
+ 82        creds = self.get_credential_object()
+ 83        if not creds.valid:
+ 84            request = google.auth.transport.requests.Request()
+ 85            creds.refresh(request=request)
+ 86
+ 87        access_token = creds.token
+ 88
+ 89        return access_token
+ 90
+ 91
+ 92class GcpCloudStorageConnection(BaseCloudStorageConnection):
+ 93    """
+ 94    Defines a connection used for interacting with cloud storage in GCP.
+ 95    """
+ 96
+ 97    @property
+ 98    def storage_client(self) -> storage.Client:
+ 99        return self.__storage_client
+100
+101    def __init__(self):
+102        """
+103        Creates a new GcpCloudContainerConnection object.
+104        """
+105
+106        self.__storage_client = None
+107
+108    def _get_storage_client(self) -> storage.Client:
+109        """
+110        Obtains a client connected to an GCP storage container by
+111        utilizing the first valid credentials GCP can find. Credential validation
+112        is handeled by GCP.
+113
+114        :return: The GCP storage client.
+115        """
+116
+117        if self.__storage_client is None:
+118            self.__storage_client = storage.Client()
+119
+120        return self.__storage_client
+121
+122    def download_object(
+123        self, container_name: str, filename: str, encoding: str = "utf-8"
+124    ) -> str:
+125        """
+126        Downloads a character blob from storage and returns it as a string.
+127
+128        :param container_name: The name of the bucket containing object to download.
+129        :param filename: The location of file within GCP blob storage.
+130        :param encoding: The encoding applied to the downloaded content.
+131        :return: A character blob (as a string) from given bucket and filename.
+132        """
+133        storage_client = self._get_storage_client()
+134        blob = storage_client.bucket(container_name).blob(filename)
+135        return blob.download_as_text(encoding=encoding)
+136
+137    def upload_object(
+138        self,
+139        message: Union[str, dict],
+140        container_name: str,
+141        filename: str,
+142        content_type="application/json",
+143    ) -> None:
+144        """
+145        Uploads the content of a given message to GCP blob storage.
+146        The message can be passed either as a raw string or as JSON.
+147
+148        :param message: The contents of a message, encoded either as a
+149          string or in a JSON-formatted dictionary.
+150        :param container_name: The name of the target bucket for upload.
+151        :param filename: The location of file within GCP blob storage.
+152        """
+153
+154        storage_client = self._get_storage_client()
+155        bucket = storage_client.bucket(container_name)
+156
+157        blob = bucket.blob(filename)
+158
+159        if isinstance(message, dict):
+160            message = json.dumps(message).encode("utf-8")
+161
+162        blob.upload_from_string(data=message, content_type=content_type)
+163
+164    def list_containers(self) -> List[str]:
+165        """
+166        Lists bucket names in storage.
+167
+168        :return: A list of bucket names in storage.
+169        """
+170        storage_client = self._get_storage_client()
+171
+172        bucket_name_list = []
+173        for bucket in storage_client.list_buckets():
+174            bucket_name_list.append(bucket)
+175        return bucket_name_list
+176
+177    def list_objects(self, container_name: str, prefix: str = "") -> List[str]:
+178        """
+179        Lists names for objects within a bucket.
+180
+181        :param container_name: The name of the bucket to look for objects.
+182        :param prefix: Filter the objects returned to filenames beginning
+183          with this value.
+184        :return: A list of names for objects in given bucket.
+185        """
+186        storage_client = self._get_storage_client()
+187
+188        blob_properties_generator = storage_client.list_blobs(
+189            container_name, prefix=prefix
+190        )
+191
+192        blob_name_list = []
+193        for blob_propreties in blob_properties_generator:
+194            blob_name_list.append(blob_propreties.name)
+195
+196        return blob_name_list
+
+ + +
+
+ +
+ + class + GcpCredentialManager(phdi.cloud.core.BaseCredentialManager): + + + +
+ + 
14class GcpCredentialManager(BaseCredentialManager):
+15    """
+16    Provides a GCP-specific credential manager.
+17    """
+18
+19    @property
+20    def scope(self) -> str:
+21        return self.__scope
+22
+23    @property
+24    def scoped_credentials(self) -> Credentials:
+25        return self.__scoped_credentials
+26
+27    @property
+28    def project_id(self) -> str:
+29        return self.__project_id
+30
+31    def __init__(self, scope: list = None):
+32        """
+33        Creates a new GcpCredentialManager object.
+34
+35        :param scope: A list of scopes to limit access to resource.
+36        """
+37        self.__scope = scope
+38        self.__scoped_credentials = None
+39        self.__project_id = None
+40
+41        if self.scope is None:
+42            self.__scope = ["https://www.googleapis.com/auth/cloud-platform"]
+43
+44    def get_credential_object(self) -> Credentials:
+45        """
+46        Gets a GCP-specific credential object.
+47
+48        :return: A scoped instance of the Credentials class from google.auth
+49            package, refreshed if necessary.
+50        """
+51        # Get credentials if they don't exist or are expired.
+52        if self.__scoped_credentials is None:
+53            self.__scoped_credentials, self.__project_id = google.auth.default(
+54                scopes=self.scope
+55            )
+56        elif self.__scoped_credentials.expired:
+57            self.__scoped_credentials, self.__project_id = google.auth.default(
+58                scopes=self.scope
+59            )
+60
+61        return self.__scoped_credentials
+62
+63    def get_project_id(self) -> str:
+64        """
+65        Gets the ID of the current GCP project.
+66
+67        :return: The current GCP project ID.
+68        """
+69
+70        if self.__project_id is None:
+71            self.__scoped_credentials, self.__project_id = google.auth.default(
+72                scopes=self.scope
+73            )
+74        return self.__project_id
+75
+76    def get_access_token(self) -> str:
+77        """
+78        Obtains an access token from GCP.
+79
+80        :return: The access token, refreshed if necessary.
+81        """
+82
+83        creds = self.get_credential_object()
+84        if not creds.valid:
+85            request = google.auth.transport.requests.Request()
+86            creds.refresh(request=request)
+87
+88        access_token = creds.token
+89
+90        return access_token
+
+ + +

Provides a GCP-specific credential manager.

+
+ + +
+ +
+ + GcpCredentialManager(scope: list = None) + + + +
+ + 
31    def __init__(self, scope: list = None):
+32        """
+33        Creates a new GcpCredentialManager object.
+34
+35        :param scope: A list of scopes to limit access to resource.
+36        """
+37        self.__scope = scope
+38        self.__scoped_credentials = None
+39        self.__project_id = None
+40
+41        if self.scope is None:
+42            self.__scope = ["https://www.googleapis.com/auth/cloud-platform"]
+
+ + +

Creates a new GcpCredentialManager object.

+ +
Parameters
+ +
    +
  • scope: A list of scopes to limit access to resource.
    • +
+
+ + +
+
+ +
+ + def + get_credential_object(self) -> google.auth.credentials.Credentials: + + + +
+ + 
44    def get_credential_object(self) -> Credentials:
+45        """
+46        Gets a GCP-specific credential object.
+47
+48        :return: A scoped instance of the Credentials class from google.auth
+49            package, refreshed if necessary.
+50        """
+51        # Get credentials if they don't exist or are expired.
+52        if self.__scoped_credentials is None:
+53            self.__scoped_credentials, self.__project_id = google.auth.default(
+54                scopes=self.scope
+55            )
+56        elif self.__scoped_credentials.expired:
+57            self.__scoped_credentials, self.__project_id = google.auth.default(
+58                scopes=self.scope
+59            )
+60
+61        return self.__scoped_credentials
+
+ + +

Gets a GCP-specific credential object.

+ +
Returns
+ +
+

A scoped instance of the Credentials class from google.auth + package, refreshed if necessary.

+
+
+ + +
+
+ +
+ + def + get_project_id(self) -> str: + + + +
+ + 
63    def get_project_id(self) -> str:
+64        """
+65        Gets the ID of the current GCP project.
+66
+67        :return: The current GCP project ID.
+68        """
+69
+70        if self.__project_id is None:
+71            self.__scoped_credentials, self.__project_id = google.auth.default(
+72                scopes=self.scope
+73            )
+74        return self.__project_id
+
+ + +

Gets the ID of the current GCP project.

+ +
Returns
+ +
+

The current GCP project ID.

+
+
+ + +
+
+ +
+ + def + get_access_token(self) -> str: + + + +
+ + 
76    def get_access_token(self) -> str:
+77        """
+78        Obtains an access token from GCP.
+79
+80        :return: The access token, refreshed if necessary.
+81        """
+82
+83        creds = self.get_credential_object()
+84        if not creds.valid:
+85            request = google.auth.transport.requests.Request()
+86            creds.refresh(request=request)
+87
+88        access_token = creds.token
+89
+90        return access_token
+
+ + +

Obtains an access token from GCP.

+ +
Returns
+ +
+

The access token, refreshed if necessary.

+
+
+ + +
+
+
+ +
+ + class + GcpCloudStorageConnection(phdi.cloud.core.BaseCloudStorageConnection): + + + +
+ + 
 93class GcpCloudStorageConnection(BaseCloudStorageConnection):
+ 94    """
+ 95    Defines a connection used for interacting with cloud storage in GCP.
+ 96    """
+ 97
+ 98    @property
+ 99    def storage_client(self) -> storage.Client:
+100        return self.__storage_client
+101
+102    def __init__(self):
+103        """
+104        Creates a new GcpCloudContainerConnection object.
+105        """
+106
+107        self.__storage_client = None
+108
+109    def _get_storage_client(self) -> storage.Client:
+110        """
+111        Obtains a client connected to an GCP storage container by
+112        utilizing the first valid credentials GCP can find. Credential validation
+113        is handeled by GCP.
+114
+115        :return: The GCP storage client.
+116        """
+117
+118        if self.__storage_client is None:
+119            self.__storage_client = storage.Client()
+120
+121        return self.__storage_client
+122
+123    def download_object(
+124        self, container_name: str, filename: str, encoding: str = "utf-8"
+125    ) -> str:
+126        """
+127        Downloads a character blob from storage and returns it as a string.
+128
+129        :param container_name: The name of the bucket containing object to download.
+130        :param filename: The location of file within GCP blob storage.
+131        :param encoding: The encoding applied to the downloaded content.
+132        :return: A character blob (as a string) from given bucket and filename.
+133        """
+134        storage_client = self._get_storage_client()
+135        blob = storage_client.bucket(container_name).blob(filename)
+136        return blob.download_as_text(encoding=encoding)
+137
+138    def upload_object(
+139        self,
+140        message: Union[str, dict],
+141        container_name: str,
+142        filename: str,
+143        content_type="application/json",
+144    ) -> None:
+145        """
+146        Uploads the content of a given message to GCP blob storage.
+147        The message can be passed either as a raw string or as JSON.
+148
+149        :param message: The contents of a message, encoded either as a
+150          string or in a JSON-formatted dictionary.
+151        :param container_name: The name of the target bucket for upload.
+152        :param filename: The location of file within GCP blob storage.
+153        """
+154
+155        storage_client = self._get_storage_client()
+156        bucket = storage_client.bucket(container_name)
+157
+158        blob = bucket.blob(filename)
+159
+160        if isinstance(message, dict):
+161            message = json.dumps(message).encode("utf-8")
+162
+163        blob.upload_from_string(data=message, content_type=content_type)
+164
+165    def list_containers(self) -> List[str]:
+166        """
+167        Lists bucket names in storage.
+168
+169        :return: A list of bucket names in storage.
+170        """
+171        storage_client = self._get_storage_client()
+172
+173        bucket_name_list = []
+174        for bucket in storage_client.list_buckets():
+175            bucket_name_list.append(bucket)
+176        return bucket_name_list
+177
+178    def list_objects(self, container_name: str, prefix: str = "") -> List[str]:
+179        """
+180        Lists names for objects within a bucket.
+181
+182        :param container_name: The name of the bucket to look for objects.
+183        :param prefix: Filter the objects returned to filenames beginning
+184          with this value.
+185        :return: A list of names for objects in given bucket.
+186        """
+187        storage_client = self._get_storage_client()
+188
+189        blob_properties_generator = storage_client.list_blobs(
+190            container_name, prefix=prefix
+191        )
+192
+193        blob_name_list = []
+194        for blob_propreties in blob_properties_generator:
+195            blob_name_list.append(blob_propreties.name)
+196
+197        return blob_name_list
+
+ + +

Defines a connection used for interacting with cloud storage in GCP.

+
+ + +
+ +
+ + GcpCloudStorageConnection() + + + +
+ + 
102    def __init__(self):
+103        """
+104        Creates a new GcpCloudContainerConnection object.
+105        """
+106
+107        self.__storage_client = None
+
+ + +

Creates a new GcpCloudContainerConnection object.

+
+ + +
+
+ +
+ + def + download_object(self, container_name: str, filename: str, encoding: str = 'utf-8') -> str: + + + +
+ + 
123    def download_object(
+124        self, container_name: str, filename: str, encoding: str = "utf-8"
+125    ) -> str:
+126        """
+127        Downloads a character blob from storage and returns it as a string.
+128
+129        :param container_name: The name of the bucket containing object to download.
+130        :param filename: The location of file within GCP blob storage.
+131        :param encoding: The encoding applied to the downloaded content.
+132        :return: A character blob (as a string) from given bucket and filename.
+133        """
+134        storage_client = self._get_storage_client()
+135        blob = storage_client.bucket(container_name).blob(filename)
+136        return blob.download_as_text(encoding=encoding)
+
+ + +

Downloads a character blob from storage and returns it as a string.

+ +
Parameters
+ +
    +
  • container_name: The name of the bucket containing object to download.
    • +
  • filename: The location of file within GCP blob storage.
    • +
  • encoding: The encoding applied to the downloaded content.
    • +
+ +
Returns
+ +
+

A character blob (as a string) from given bucket and filename.

+
+
+ + +
+
+ +
+ + def + upload_object( self, message: Union[str, dict], container_name: str, filename: str, content_type='application/json') -> None: + + + +
+ + 
138    def upload_object(
+139        self,
+140        message: Union[str, dict],
+141        container_name: str,
+142        filename: str,
+143        content_type="application/json",
+144    ) -> None:
+145        """
+146        Uploads the content of a given message to GCP blob storage.
+147        The message can be passed either as a raw string or as JSON.
+148
+149        :param message: The contents of a message, encoded either as a
+150          string or in a JSON-formatted dictionary.
+151        :param container_name: The name of the target bucket for upload.
+152        :param filename: The location of file within GCP blob storage.
+153        """
+154
+155        storage_client = self._get_storage_client()
+156        bucket = storage_client.bucket(container_name)
+157
+158        blob = bucket.blob(filename)
+159
+160        if isinstance(message, dict):
+161            message = json.dumps(message).encode("utf-8")
+162
+163        blob.upload_from_string(data=message, content_type=content_type)
+
+ + +

Uploads the content of a given message to GCP blob storage. +The message can be passed either as a raw string or as JSON.

+ +
Parameters
+ +
    +
  • message: The contents of a message, encoded either as a +string or in a JSON-formatted dictionary.
    • +
  • container_name: The name of the target bucket for upload.
    • +
  • filename: The location of file within GCP blob storage.
    • +
+
+ + +
+
+ +
+ + def + list_containers(self) -> List[str]: + + + +
+ + 
165    def list_containers(self) -> List[str]:
+166        """
+167        Lists bucket names in storage.
+168
+169        :return: A list of bucket names in storage.
+170        """
+171        storage_client = self._get_storage_client()
+172
+173        bucket_name_list = []
+174        for bucket in storage_client.list_buckets():
+175            bucket_name_list.append(bucket)
+176        return bucket_name_list
+
+ + +

Lists bucket names in storage.

+ +
Returns
+ +
+

A list of bucket names in storage.

+
+
+ + +
+
+ +
+ + def + list_objects(self, container_name: str, prefix: str = '') -> List[str]: + + + +
+ + 
178    def list_objects(self, container_name: str, prefix: str = "") -> List[str]:
+179        """
+180        Lists names for objects within a bucket.
+181
+182        :param container_name: The name of the bucket to look for objects.
+183        :param prefix: Filter the objects returned to filenames beginning
+184          with this value.
+185        :return: A list of names for objects in given bucket.
+186        """
+187        storage_client = self._get_storage_client()
+188
+189        blob_properties_generator = storage_client.list_blobs(
+190            container_name, prefix=prefix
+191        )
+192
+193        blob_name_list = []
+194        for blob_propreties in blob_properties_generator:
+195            blob_name_list.append(blob_propreties.name)
+196
+197        return blob_name_list
+
+ + +

Lists names for objects within a bucket.

+ +
Parameters
+ +
    +
  • container_name: The name of the bucket to look for objects.
    • +
  • prefix: Filter the objects returned to filenames beginning +with this value.
    • +
+ +
Returns
+ +
+

A list of names for objects in given bucket.

+
+
+ + +
+
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/containers.html b/docs/v1.2.7/sdk/phdi/containers.html new file mode 100644 index 0000000000..308ad7e4c5 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/containers.html @@ -0,0 +1,237 @@ + + + + + + + phdi.containers API documentation + + + + + + + + + +
+
+

+phdi.containers

+ + + + + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/containers/base_service.html b/docs/v1.2.7/sdk/phdi/containers/base_service.html new file mode 100644 index 0000000000..27b254b3eb --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/containers/base_service.html @@ -0,0 +1,670 @@ + + + + + + + phdi.containers.base_service API documentation + + + + + + + + + +
+
+

+phdi.containers.base_service

+ + + + + + + 
  1from importlib import metadata
+  2from pathlib import Path
+  3from typing import Literal
+  4
+  5from fastapi import FastAPI
+  6from pydantic import BaseModel
+  7
+  8
+  9# create a class with the DIBBs default Creative Commons Zero v1.0 and
+ 10# MIT license to be used by the BaseService class
+ 11LICENSES = {
+ 12    "CreativeCommonsZero": {
+ 13        "name": "Creative Commons Zero v1.0 Universal",
+ 14        "url": "https://creativecommons.org/publicdomain/zero/1.0/",
+ 15    },
+ 16    "MIT": {"name": "The MIT License", "url": "https://mit-license.org/"},
+ 17}
+ 18
+ 19DIBBS_CONTACT = {
+ 20    "name": "CDC Public Health Data Infrastructure",
+ 21    "url": "https://cdcgov.github.io/phdi-site/",
+ 22    "email": "dmibuildingblocks@cdc.gov",
+ 23}
+ 24
+ 25
+ 26STATUS_OK = {"status": "OK"}
+ 27
+ 28
+ 29class StatusResponse(BaseModel):
+ 30    """
+ 31    The schema for the response from the health check endpoint.
+ 32    """
+ 33
+ 34    status: Literal["OK"]
+ 35
+ 36
+ 37class BaseService:
+ 38    def __init__(
+ 39        self,
+ 40        service_name: str,
+ 41        service_path: str,
+ 42        description_path: str,
+ 43        include_health_check_endpoint: bool = True,
+ 44        license_info: Literal["CreativeCommonsZero", "MIT"] = "CreativeCommonsZero",
+ 45    ):
+ 46        """
+ 47        Initialize a BaseService instance.
+ 48
+ 49        :param service_name: The name of the service.
+ 50        :param service_path: The path to used to access the service from a gateway.
+ 51        :param description_path: The path to a markdown file containing a description of
+ 52            the service.
+ 53        :param include_health_check_endpoint: If True, the standard DIBBs health check
+ 54            endpoint will be added.
+ 55        :param license_info: If empty, the standard DIBBs Creative Commons Zero v1.0
+ 56            Universal license will be used. The other available option is to use the
+ 57            MIT license.
+ 58        """
+ 59        description = Path(description_path).read_text(encoding="utf-8")
+ 60        self.service_path = service_path
+ 61        self.include_health_check_endpoint = include_health_check_endpoint
+ 62        self.app = FastAPI(
+ 63            title=service_name,
+ 64            version=metadata.version("phdi"),
+ 65            contact=DIBBS_CONTACT,
+ 66            license_info=LICENSES[license_info],
+ 67            description=description,
+ 68        )
+ 69
+ 70    def add_path_rewrite_middleware(self):
+ 71        """
+ 72        Add middleware to the FastAPI instance to strip the service_path
+ 73        from the URL path if it is present. This is useful when the service
+ 74        is behind a gateway that is using a path-based routing strategy.
+ 75        """
+ 76
+ 77        @self.app.middleware("http")
+ 78        async def rewrite_path(request, call_next):
+ 79            if request.url.path.startswith(self.service_path):
+ 80                request.scope["path"] = request.scope["path"].replace(
+ 81                    self.service_path, ""
+ 82                )
+ 83                if request.scope["path"] == "":
+ 84                    request.scope["path"] = "/"
+ 85            return await call_next(request)
+ 86
+ 87    def add_health_check_endpoint(self):
+ 88        @self.app.get("/")
+ 89        async def health_check() -> StatusResponse:
+ 90            """
+ 91            Check service status. If an HTTP 200 status code is returned along with
+ 92            '{"status": "OK"}' then the service is available and running properly.
+ 93            """
+ 94            return STATUS_OK
+ 95
+ 96    def start(self) -> FastAPI:
+ 97        """
+ 98        Return a FastAPI instance with DIBBs metadata set. If
+ 99        `include_health_check_endpoint` is True, then the health check endpoint
+100        will be added.
+101
+102        :return: The FastAPI instance.
+103        """
+104        self.add_path_rewrite_middleware()
+105        if self.include_health_check_endpoint:
+106            self.add_health_check_endpoint()
+107        return self.app
+
+ + +
+
+ +
+ + class + StatusResponse(pydantic.main.BaseModel): + + + +
+ + 
30class StatusResponse(BaseModel):
+31    """
+32    The schema for the response from the health check endpoint.
+33    """
+34
+35    status: Literal["OK"]
+
+ + +

The schema for the response from the health check endpoint.

+
+ + +
+
Inherited Members
+
+
pydantic.main.BaseModel
+
BaseModel
+
dict
+
json
+
parse_obj
+
parse_raw
+
parse_file
+
from_orm
+
construct
+
copy
+
schema
+
schema_json
+
validate
+
update_forward_refs
+ +
+
+
+
+
+ +
+ + class + BaseService: + + + +
+ + 
 38class BaseService:
+ 39    def __init__(
+ 40        self,
+ 41        service_name: str,
+ 42        service_path: str,
+ 43        description_path: str,
+ 44        include_health_check_endpoint: bool = True,
+ 45        license_info: Literal["CreativeCommonsZero", "MIT"] = "CreativeCommonsZero",
+ 46    ):
+ 47        """
+ 48        Initialize a BaseService instance.
+ 49
+ 50        :param service_name: The name of the service.
+ 51        :param service_path: The path to used to access the service from a gateway.
+ 52        :param description_path: The path to a markdown file containing a description of
+ 53            the service.
+ 54        :param include_health_check_endpoint: If True, the standard DIBBs health check
+ 55            endpoint will be added.
+ 56        :param license_info: If empty, the standard DIBBs Creative Commons Zero v1.0
+ 57            Universal license will be used. The other available option is to use the
+ 58            MIT license.
+ 59        """
+ 60        description = Path(description_path).read_text(encoding="utf-8")
+ 61        self.service_path = service_path
+ 62        self.include_health_check_endpoint = include_health_check_endpoint
+ 63        self.app = FastAPI(
+ 64            title=service_name,
+ 65            version=metadata.version("phdi"),
+ 66            contact=DIBBS_CONTACT,
+ 67            license_info=LICENSES[license_info],
+ 68            description=description,
+ 69        )
+ 70
+ 71    def add_path_rewrite_middleware(self):
+ 72        """
+ 73        Add middleware to the FastAPI instance to strip the service_path
+ 74        from the URL path if it is present. This is useful when the service
+ 75        is behind a gateway that is using a path-based routing strategy.
+ 76        """
+ 77
+ 78        @self.app.middleware("http")
+ 79        async def rewrite_path(request, call_next):
+ 80            if request.url.path.startswith(self.service_path):
+ 81                request.scope["path"] = request.scope["path"].replace(
+ 82                    self.service_path, ""
+ 83                )
+ 84                if request.scope["path"] == "":
+ 85                    request.scope["path"] = "/"
+ 86            return await call_next(request)
+ 87
+ 88    def add_health_check_endpoint(self):
+ 89        @self.app.get("/")
+ 90        async def health_check() -> StatusResponse:
+ 91            """
+ 92            Check service status. If an HTTP 200 status code is returned along with
+ 93            '{"status": "OK"}' then the service is available and running properly.
+ 94            """
+ 95            return STATUS_OK
+ 96
+ 97    def start(self) -> FastAPI:
+ 98        """
+ 99        Return a FastAPI instance with DIBBs metadata set. If
+100        `include_health_check_endpoint` is True, then the health check endpoint
+101        will be added.
+102
+103        :return: The FastAPI instance.
+104        """
+105        self.add_path_rewrite_middleware()
+106        if self.include_health_check_endpoint:
+107            self.add_health_check_endpoint()
+108        return self.app
+
+ + + + +
+ +
+ + BaseService( service_name: str, service_path: str, description_path: str, include_health_check_endpoint: bool = True, license_info: Literal['CreativeCommonsZero', 'MIT'] = 'CreativeCommonsZero') + + + +
+ + 
39    def __init__(
+40        self,
+41        service_name: str,
+42        service_path: str,
+43        description_path: str,
+44        include_health_check_endpoint: bool = True,
+45        license_info: Literal["CreativeCommonsZero", "MIT"] = "CreativeCommonsZero",
+46    ):
+47        """
+48        Initialize a BaseService instance.
+49
+50        :param service_name: The name of the service.
+51        :param service_path: The path to used to access the service from a gateway.
+52        :param description_path: The path to a markdown file containing a description of
+53            the service.
+54        :param include_health_check_endpoint: If True, the standard DIBBs health check
+55            endpoint will be added.
+56        :param license_info: If empty, the standard DIBBs Creative Commons Zero v1.0
+57            Universal license will be used. The other available option is to use the
+58            MIT license.
+59        """
+60        description = Path(description_path).read_text(encoding="utf-8")
+61        self.service_path = service_path
+62        self.include_health_check_endpoint = include_health_check_endpoint
+63        self.app = FastAPI(
+64            title=service_name,
+65            version=metadata.version("phdi"),
+66            contact=DIBBS_CONTACT,
+67            license_info=LICENSES[license_info],
+68            description=description,
+69        )
+
+ + +

Initialize a BaseService instance.

+ +
Parameters
+ +
    +
  • service_name: The name of the service.
    • +
  • service_path: The path to used to access the service from a gateway.
    • +
  • description_path: The path to a markdown file containing a description of +the service.
    • +
  • include_health_check_endpoint: If True, the standard DIBBs health check +endpoint will be added.
    • +
  • license_info: If empty, the standard DIBBs Creative Commons Zero v1.0 +Universal license will be used. The other available option is to use the +MIT license.
    • +
+
+ + +
+
+ +
+ + def + add_path_rewrite_middleware(self): + + + +
+ + 
71    def add_path_rewrite_middleware(self):
+72        """
+73        Add middleware to the FastAPI instance to strip the service_path
+74        from the URL path if it is present. This is useful when the service
+75        is behind a gateway that is using a path-based routing strategy.
+76        """
+77
+78        @self.app.middleware("http")
+79        async def rewrite_path(request, call_next):
+80            if request.url.path.startswith(self.service_path):
+81                request.scope["path"] = request.scope["path"].replace(
+82                    self.service_path, ""
+83                )
+84                if request.scope["path"] == "":
+85                    request.scope["path"] = "/"
+86            return await call_next(request)
+
+ + +

Add middleware to the FastAPI instance to strip the service_path +from the URL path if it is present. This is useful when the service +is behind a gateway that is using a path-based routing strategy.

+
+ + +
+
+ +
+ + def + add_health_check_endpoint(self): + + + +
+ + 
88    def add_health_check_endpoint(self):
+89        @self.app.get("/")
+90        async def health_check() -> StatusResponse:
+91            """
+92            Check service status. If an HTTP 200 status code is returned along with
+93            '{"status": "OK"}' then the service is available and running properly.
+94            """
+95            return STATUS_OK
+
+ + + + +
+
+ +
+ + def + start(self) -> fastapi.applications.FastAPI: + + + +
+ + 
 97    def start(self) -> FastAPI:
+ 98        """
+ 99        Return a FastAPI instance with DIBBs metadata set. If
+100        `include_health_check_endpoint` is True, then the health check endpoint
+101        will be added.
+102
+103        :return: The FastAPI instance.
+104        """
+105        self.add_path_rewrite_middleware()
+106        if self.include_health_check_endpoint:
+107            self.add_health_check_endpoint()
+108        return self.app
+
+ + +

Return a FastAPI instance with DIBBs metadata set. If +include_health_check_endpoint is True, then the health check endpoint +will be added.

+ +
Returns
+ +
+

The FastAPI instance.

+
+
+ + +
+
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/fhir.html b/docs/v1.2.7/sdk/phdi/fhir.html new file mode 100644 index 0000000000..6ead12b3d0 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/fhir.html @@ -0,0 +1,244 @@ + + + + + + + phdi.fhir API documentation + + + + + + + + + +
+
+

+phdi.fhir

+ + + + + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/fhir/cloud.html b/docs/v1.2.7/sdk/phdi/fhir/cloud.html new file mode 100644 index 0000000000..2e2c70947b --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/fhir/cloud.html @@ -0,0 +1,318 @@ + + + + + + + phdi.fhir.cloud API documentation + + + + + + + + + +
+
+

+phdi.fhir.cloud

+ + + + + + + 
1from phdi.fhir.cloud.azure import download_from_fhir_export_response
+2
+3__all__ = ["download_from_fhir_export_response"]
+
+ + +
+
+ +
+ + def + download_from_fhir_export_response( export_response: dict, cred_manager: phdi.cloud.azure.AzureCredentialManager) -> Iterator[Tuple[str, TextIO]]: + + + +
+ + 
12def download_from_fhir_export_response(
+13    export_response: dict,
+14    cred_manager: AzureCredentialManager,
+15) -> Iterator[Tuple[str, TextIO]]:
+16    """
+17    Accepts the export response content as specified here:
+18    https://hl7.org/fhir/uv/bulkdata/export/index.html#response---complete-status
+19
+20    Loops through the "output" array and yields the resource_type (e.g., Patient)
+21    along with TextIO wrapping ndjson content.
+22
+23    :param export_response: A dictionary holding the final export response.
+24    :param cred_manager: The credential manager used to authenticate to the
+25      storage account.
+26    :return: An iterator of tuples. Each tuple is comprised of:
+27
+28      * FHIR resource type (str)
+29      * Export file content (io.TextIO)
+30    """
+31    # TODO: Handle error array that could be contained in the response content.
+32
+33    for export_entry in export_response.get("output", []):
+34        resource_type = export_entry.get("type")
+35        blob_url = export_entry.get("url")
+36
+37        yield (
+38            resource_type,
+39            _download_export_blob(blob_url=blob_url, cred_manager=cred_manager),
+40        )
+
+ + +

Accepts the export response content as specified here: +https://hl7.org/fhir/uv/bulkdata/export/index.html#response---complete-status

+ +

Loops through the "output" array and yields the resource_type (e.g., Patient) +along with TextIO wrapping ndjson content.

+ +
Parameters
+ +
    +
  • export_response: A dictionary holding the final export response.
    • +
  • cred_manager: The credential manager used to authenticate to the +storage account.
    • +
+ +
Returns
+ +
+

An iterator of tuples. Each tuple is comprised of:

+ +
    +
  • FHIR resource type (str)
    • +
  • Export file content (io.TextIO)
    • +
+
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/fhir/conversion.html b/docs/v1.2.7/sdk/phdi/fhir/conversion.html new file mode 100644 index 0000000000..57780ab964 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/fhir/conversion.html @@ -0,0 +1,534 @@ + + + + + + + phdi.fhir.conversion API documentation + + + + + + + + + +
+
+

+phdi.fhir.conversion

+ + + + + + + 
1from phdi.fhir.conversion.convert import add_rr_data_to_eicr
+2from phdi.fhir.conversion.convert import convert_to_fhir
+3
+4__all__ = (
+5    "add_rr_data_to_eicr",
+6    "convert_to_fhir",
+7)
+
+ + +
+
+ +
+ + def + add_rr_data_to_eicr(rr, ecr): + + + +
+ + 
 27def add_rr_data_to_eicr(rr, ecr):
+ 28    """
+ 29    Extracts relevant fields from an RR document, and inserts them into a
+ 30    given eICR document. Ensures that the eICR contains properly formatted
+ 31    RR fields, including templateId, id, code, title, effectiveTime,
+ 32    confidentialityCode, and corresponding entries; and required format tags.
+ 33
+ 34    :param rr: A serialized xml format reportability response (RR) document.
+ 35    :param ecr: A serialized xml format electronic initial case report (eICR) document.
+ 36    :return: An xml format eICR document with additional fields extracted from the RR.
+ 37    """
+ 38    # add xmlns:xsi attribute if not there
+ 39    lines = ecr.splitlines()
+ 40    xsi_tag = "xmlns:xsi"
+ 41    if xsi_tag not in lines[0]:
+ 42        lines[0] = lines[0].replace(
+ 43            'xmlns="urn:hl7-org:v3"',
+ 44            'xmlns="urn:hl7-org:v3" '
+ 45            'xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"',
+ 46        )
+ 47        ecr = "\n".join(lines)
+ 48
+ 49    rr = etree.fromstring(rr)
+ 50    ecr = etree.fromstring(ecr)
+ 51
+ 52    if ecr.xpath('//*[@code="88085-6"]'):
+ 53        print("This eCR has already been merged with RR data.")
+ 54        return etree.tostring(ecr, encoding="unicode", method="xml")
+ 55
+ 56    # Create the tags for elements we'll be looking for
+ 57    rr_tags = [
+ 58        "templateId",
+ 59        "id",
+ 60        "code",
+ 61        "title",
+ 62        "effectiveTime",
+ 63        "confidentialityCode",
+ 64    ]
+ 65    rr_tags = ["{urn:hl7-org:v3}" + tag for tag in rr_tags]
+ 66    rr_elements = []
+ 67
+ 68    # Find root-level elements and add them to a list
+ 69    for tag in rr_tags:
+ 70        rr_elements.append(rr.find(f"./{tag}", namespaces=rr.nsmap))
+ 71
+ 72    # Find the nested entry element that we need
+ 73    entry_tag = "{urn:hl7-org:v3}" + "component/structuredBody/component/section/entry"
+ 74    rr_nested_entries = rr.findall(f"./{entry_tag}", namespaces=rr.nsmap)
+ 75
+ 76    organizer_tag = "{urn:hl7-org:v3}" + "organizer"
+ 77
+ 78    # For now we assume there is only one matching entry
+ 79    rr_entry = None
+ 80    for entry in rr_nested_entries:
+ 81        if entry.attrib and "DRIV" in entry.attrib["typeCode"]:
+ 82            organizer = entry.find(f"./{organizer_tag}", namespaces=entry.nsmap)
+ 83            if (
+ 84                organizer is not None
+ 85                and "CLUSTER" in organizer.attrib["classCode"]
+ 86                and "EVN" in organizer.attrib["moodCode"]
+ 87            ):
+ 88                rr_entry = entry
+ 89                exit
+ 90
+ 91    # find the status in the RR utilizing the templateid root
+ 92    # codes specified from the APHL/LAC Spec
+ 93    base_tag_for_status = (
+ 94        "{urn:hl7-org:v3}" + "component/structuredBody/component/section"
+ 95    )
+ 96    template_id_tag = "{urn:hl7-org:v3}" + "templateId"
+ 97    entry_status_tag = "{urn:hl7-org:v3}" + "entry"
+ 98    act_status_tag = "{urn:hl7-org:v3}" + "act"
+ 99    sections_for_status = rr.findall(f"./{base_tag_for_status}", namespaces=rr.nsmap)
+100    rr_entry_for_status_codes = None
+101    for status_section in sections_for_status:
+102        template_id = status_section.find(
+103            f"./{template_id_tag}", namespaces=status_section.nsmap
+104        )
+105        if (
+106            template_id is not None
+107            and "2.16.840.1.113883.10.20.15.2.2.3" in template_id.attrib["root"]
+108        ):
+109            for entry in status_section.findall(
+110                f"./{entry_status_tag}", namespaces=status_section.nsmap
+111            ):
+112                for act in entry.findall(f"./{act_status_tag}", namespaces=entry.nsmap):
+113                    entry_act_template_id = act.find(
+114                        f"./{template_id_tag}", namespaces=act.nsmap
+115                    )
+116                    if (
+117                        entry_act_template_id is not None
+118                        and "2.16.840.1.113883.10.20.15.2.3.29"
+119                        in entry_act_template_id.attrib["root"]
+120                    ):
+121                        # only anticipating one status code
+122                        rr_entry_for_status_codes = entry
+123                        exit
+124
+125    # Create the section element with root-level elements
+126    # and entry to insert in the eICR
+127    ecr_section = None
+128    if rr_entry is not None:
+129        ecr_section_tag = "{urn:hl7-org:v3}" + "section"
+130        ecr_section = etree.Element(ecr_section_tag)
+131        ecr_section.extend(rr_elements)
+132        if rr_entry_for_status_codes is not None:
+133            ecr_section.append(rr_entry_for_status_codes)
+134        ecr_section.append(rr_entry)
+135
+136        # Append the ecr section into the eCR - puts it at the end
+137        ecr.append(ecr_section)
+138
+139    ecr = etree.tostring(ecr, encoding="unicode", method="xml")
+140
+141    return ecr
+
+ + +

Extracts relevant fields from an RR document, and inserts them into a +given eICR document. Ensures that the eICR contains properly formatted +RR fields, including templateId, id, code, title, effectiveTime, +confidentialityCode, and corresponding entries; and required format tags.

+ +
Parameters
+ +
    +
  • rr: A serialized xml format reportability response (RR) document.
    • +
  • ecr: A serialized xml format electronic initial case report (eICR) document.
    • +
+ +
Returns
+ +
+

An xml format eICR document with additional fields extracted from the RR.

+
+
+ + +
+
+ +
+ + def + convert_to_fhir( message: str, url: str, cred_manager: phdi.cloud.core.BaseCredentialManager = None, headers: dict = {}, use_default_ccda=False): + + + +
+ + 
144def convert_to_fhir(
+145    message: str,
+146    url: str,
+147    cred_manager: BaseCredentialManager = None,
+148    headers: dict = {},
+149    use_default_ccda=False,
+150):
+151    """
+152    Converts a given message from either HL7 v2 (pipe-delimited flat file) or CCDA (XML)
+153    into FHIR format (JSON) for further processing using the FHIR server. Standardizes
+154    datetimes in HL7v2 messages before conversion.
+155
+156    This function uses a containerized version of the
+157    [Azure FHIR Converter](https://github.com/microsoft/FHIR-Converter).
+158
+159    If conversion succeeds, a `requests.Response` object will be returned with the
+160    conversion response. Otherwise, a `ConversionError` is raised, with the
+161    `requests.Response` available as a property for troubleshooting and reporting
+162    purposes.
+163
+164    :param message: The raw message that needs to be converted to
+165      FHIR. Currently, only HL7v2 or CCDA are supported.
+166    :param url: A URL that points to the location of the converter API.
+167    :param cred_manager: Service used to get an access token used to
+168      make a request.
+169    :param headers: JSON-type dictionary of headers to make the request with.
+170    :param use_default_ccda: Whether to default to the
+171      base "CCD" root template if a resource's LOINC code doesn't
+172      map to a specific supported template (Optional, default is No)
+173    :raises requests.HttpError: If the HTTP request was unsuccessful.
+174    :raises ConversionError: If the message could not be converted.
+175    :return: A requests.Response object
+176
+177    """
+178    # TODO Update documentation with a link to the containerized FHIR converter, once
+179    # it's been ported over to the phdi repository.
+180
+181    conversion_settings = _get_fhir_conversion_settings(message, use_default_ccda)
+182    if conversion_settings.get("input_type") == "hl7v2":
+183        message = standardize_hl7_datetimes(message)
+184
+185    url = f"{url}"
+186    data = {
+187        "input_data": message,
+188        "input_type": conversion_settings.get("input_type"),
+189        "root_template": conversion_settings.get("root_template"),
+190    }
+191
+192    if cred_manager:
+193        access_token = cred_manager.get_access_token()
+194        headers["Authorization"] = f"Bearer {access_token}"
+195        response = http_request_with_reauth(
+196            cred_manager=cred_manager,
+197            url=url,
+198            retry_count=3,
+199            request_type="POST",
+200            allowed_methods=["POST"],
+201            headers=headers,
+202            data=data,
+203        )
+204    else:
+205        response = http_request_with_retry(
+206            url=url,
+207            retry_count=3,
+208            request_type="POST",
+209            allowed_methods=["POST"],
+210            headers=headers,
+211            data=data,
+212        )
+213
+214    if response.status_code != 200:
+215        raise ConversionError(response)
+216
+217    return response
+
+ + +

Converts a given message from either HL7 v2 (pipe-delimited flat file) or CCDA (XML) +into FHIR format (JSON) for further processing using the FHIR server. Standardizes +datetimes in HL7v2 messages before conversion.

+ +

This function uses a containerized version of the +Azure FHIR Converter.

+ +

If conversion succeeds, a requests.Response object will be returned with the +conversion response. Otherwise, a ConversionError is raised, with the +requests.Response available as a property for troubleshooting and reporting +purposes.

+ +
Parameters
+ +
    +
  • message: The raw message that needs to be converted to +FHIR. Currently, only HL7v2 or CCDA are supported.
    • +
  • url: A URL that points to the location of the converter API.
    • +
  • cred_manager: Service used to get an access token used to +make a request.
    • +
  • headers: JSON-type dictionary of headers to make the request with.
    • +
  • use_default_ccda: Whether to default to the +base "CCD" root template if a resource's LOINC code doesn't +map to a specific supported template (Optional, default is No)
    • +
+ +
Raises
+ +
    +
  • requests.HttpError: If the HTTP request was unsuccessful.
    • +
  • ConversionError: If the message could not be converted.
    • +
+ +
Returns
+ +
+

A requests.Response object

+
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/fhir/geospatial.html b/docs/v1.2.7/sdk/phdi/fhir/geospatial.html new file mode 100644 index 0000000000..08156845a8 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/fhir/geospatial.html @@ -0,0 +1,1011 @@ + + + + + + + phdi.fhir.geospatial API documentation + + + + + + + + + +
+
+

+phdi.fhir.geospatial

+ + + + + + + 
1from phdi.fhir.geospatial.census import CensusFhirGeocodeClient
+2from phdi.fhir.geospatial.core import BaseFhirGeocodeClient
+3from phdi.fhir.geospatial.smarty import SmartyFhirGeocodeClient
+4
+5__all__ = (
+6    "BaseFhirGeocodeClient",
+7    "SmartyFhirGeocodeClient",
+8    "CensusFhirGeocodeClient",
+9)
+
+ + +
+
+ +
+ + class + BaseFhirGeocodeClient(abc.ABC): + + + +
+ + 
  6class BaseFhirGeocodeClient(ABC):
+  7    """
+  8    Represents a vendor-agnostic geocoder client designed to process
+  9    FHIR-based data. Implementing classes should define methods to
+ 10    geocode from both bundles and resources. Callers should use the
+ 11    provided interface functions (e.g., geocode_resource) to interact with
+ 12    the underlying vendor-specific client property.
+ 13    """
+ 14
+ 15    @abstractmethod
+ 16    def geocode_resource(self, resource: dict, overwrite=True) -> dict:
+ 17        """
+ 18        Performs geocoding, using the implementing client, on the provided resource,
+ 19        which is passed in as a dictionary.
+ 20
+ 21        :param resource: A FHIR resource to be geocoded.
+ 22        :param overwrite: If true, `resource` is modified in-place;
+ 23          if false, a copy of `resource` modified and returned.  Default: `True`
+ 24        :return: The geocoded resource as a dict.
+ 25        """
+ 26        pass  # pragma: no cover
+ 27
+ 28    @abstractmethod
+ 29    def geocode_bundle(self, bundle: dict, overwrite=True) -> dict:
+ 30        """
+ 31        Performs geocoding, using the implementing client, on all supported resources in
+ 32        the provided FHIR bundle which is passed in as a dictionary.
+ 33
+ 34        :param bundle: A bundle of FHIR resources.
+ 35        :param overwrite: If true, `bundle` is modified in-place;
+ 36          if false, a copy of `bundle` modified and returned.  Default: `True`
+ 37        :return: The geocoded FHIR bundle as a dict.
+ 38        """
+ 39        pass  # pragma: no cover
+ 40
+ 41    @staticmethod
+ 42    def _store_lat_long_extension(address: dict, lat: float, long: float) -> None:
+ 43        """
+ 44        Adds extension data for latitude and longitude, if the fields aren't already
+ 45        present, to a given FHIR-formatted dictionary holding address fields.
+ 46        The latitude and longitude data is added directly to the input dictionary.
+ 47
+ 48        :param address: A FHIR formatted dictionary holding address fields.
+ 49        :param lat: The latitude to add to the FHIR data as an extension.
+ 50        :param long: The longitude to add to the FHIR data as an extension.
+ 51        """
+ 52        if "extension" not in address:
+ 53            address["extension"] = []
+ 54
+ 55        # Append with a properly resolving URL for FHIR's canonical geospatial
+ 56        # structure definition, as all extensions are required to have this
+ 57        # attribute; see https://www.hl7.org/fhir/extensibility.html
+ 58        address["extension"].append(
+ 59            {
+ 60                "url": "http://hl7.org/fhir/StructureDefinition/geolocation",
+ 61                "extension": [
+ 62                    {
+ 63                        "url": "latitude",
+ 64                        "valueDecimal": lat,
+ 65                    },
+ 66                    {
+ 67                        "url": "longitude",
+ 68                        "valueDecimal": long,
+ 69                    },
+ 70                ],
+ 71            }
+ 72        )
+ 73
+ 74    @staticmethod
+ 75    def _store_census_tract_extension(address: dict, census_tract: str) -> None:
+ 76        """
+ 77        Adds appropriate extension data for census tract for each element in an address
+ 78        line, if the field isn't already present, to a given FHIR-formatted dictionary
+ 79        holding address fields. Add the extension data directly to the input dictionary,
+ 80        leaving census tract as a FHIR-identified geolocation element.
+ 81
+ 82        :param address: A FHIR formatted dictionary holding address fields
+ 83        :param census_tract: The census tract to add to the FHIR data as an extension
+ 84        """
+ 85
+ 86        # Append with a properly resolving URL for FHIR's canonical censusTract
+ 87        # structure definition, as all extensions are required to have this
+ 88        # attribute; see https://www.hl7.org/fhir/extensibility.html
+ 89
+ 90        census_extension = {
+ 91            "url": "http://hl7.org/fhir/StructureDefinition/iso21090-ADXP-censusTract",
+ 92            "valueString": census_tract,
+ 93        }
+ 94
+ 95        if address.get("_line") is None:
+ 96            address["_line"] = []
+ 97        for element_counter in range(len(address["line"])):
+ 98            try:
+ 99                address["_line"][element_counter].get("extension").append(
+100                    census_extension
+101                )
+102            except AttributeError:
+103                address["_line"][element_counter] = {"extension": []}
+104                address["_line"][element_counter].get("extension").append(
+105                    census_extension
+106                )
+107            except IndexError:
+108                address["_line"].append({"extension": [census_extension]})
+
+ + +

Represents a vendor-agnostic geocoder client designed to process +FHIR-based data. Implementing classes should define methods to +geocode from both bundles and resources. Callers should use the +provided interface functions (e.g., geocode_resource) to interact with +the underlying vendor-specific client property.

+
+ + +
+ +
+
@abstractmethod
+ + def + geocode_resource(self, resource: dict, overwrite=True) -> dict: + + + +
+ + 
15    @abstractmethod
+16    def geocode_resource(self, resource: dict, overwrite=True) -> dict:
+17        """
+18        Performs geocoding, using the implementing client, on the provided resource,
+19        which is passed in as a dictionary.
+20
+21        :param resource: A FHIR resource to be geocoded.
+22        :param overwrite: If true, `resource` is modified in-place;
+23          if false, a copy of `resource` modified and returned.  Default: `True`
+24        :return: The geocoded resource as a dict.
+25        """
+26        pass  # pragma: no cover
+
+ + +

Performs geocoding, using the implementing client, on the provided resource, +which is passed in as a dictionary.

+ +
Parameters
+ +
    +
  • resource: A FHIR resource to be geocoded.
    • +
  • overwrite: If true, resource is modified in-place; +if false, a copy of resource modified and returned. Default: True
    • +
+ +
Returns
+ +
+

The geocoded resource as a dict.

+
+
+ + +
+
+ +
+
@abstractmethod
+ + def + geocode_bundle(self, bundle: dict, overwrite=True) -> dict: + + + +
+ + 
28    @abstractmethod
+29    def geocode_bundle(self, bundle: dict, overwrite=True) -> dict:
+30        """
+31        Performs geocoding, using the implementing client, on all supported resources in
+32        the provided FHIR bundle which is passed in as a dictionary.
+33
+34        :param bundle: A bundle of FHIR resources.
+35        :param overwrite: If true, `bundle` is modified in-place;
+36          if false, a copy of `bundle` modified and returned.  Default: `True`
+37        :return: The geocoded FHIR bundle as a dict.
+38        """
+39        pass  # pragma: no cover
+
+ + +

Performs geocoding, using the implementing client, on all supported resources in +the provided FHIR bundle which is passed in as a dictionary.

+ +
Parameters
+ +
    +
  • bundle: A bundle of FHIR resources.
    • +
  • overwrite: If true, bundle is modified in-place; +if false, a copy of bundle modified and returned. Default: True
    • +
+ +
Returns
+ +
+

The geocoded FHIR bundle as a dict.

+
+
+ + +
+
+
+ +
+ + class + SmartyFhirGeocodeClient(phdi.fhir.geospatial.BaseFhirGeocodeClient): + + + +
+ + 
 11class SmartyFhirGeocodeClient(BaseFhirGeocodeClient):
+ 12    """
+ 13    Implementation of a geocoding client designed to handle FHIR-
+ 14    formatted data using the SmartyStreets API.
+ 15    Requires an authorization ID as well as an authentication token
+ 16    in order to build a street lookup client.
+ 17    """
+ 18
+ 19    def __init__(
+ 20        self,
+ 21        smarty_auth_id: str,
+ 22        smarty_auth_token: str,
+ 23        licenses: list[str] = ["us-standard-cloud"],
+ 24    ):
+ 25        self.__client = SmartyGeocodeClient(smarty_auth_id, smarty_auth_token, licenses)
+ 26
+ 27    @property
+ 28    def geocode_client(self) -> us_street.Client:
+ 29        """
+ 30        An instance of the underlying Smarty client.
+ 31        Allows the FHIR wrapper to access a SmartyStreets-
+ 32        specific connection client without instantiating its own
+ 33        copy. Provides access to the respective `geocode_from_str`
+ 34        and `geocode_from_dict` methods if they're desired.
+ 35        """
+ 36        return self.__client
+ 37
+ 38    def geocode_resource(self, resource: dict, overwrite=True) -> dict:
+ 39        """
+ 40        Performs geocoding on one or more addresses in a given FHIR
+ 41        resource and returns either the result or a copy thereof.
+ 42        Currently supported resource types are:
+ 43
+ 44        * Patient
+ 45
+ 46        :param resource: The resource whose addresses should be geocoded.
+ 47        :param overwrite: If true, `resource` is modified in-place;
+ 48          if false, a copy of `resource` modified and returned.  Default: `True`
+ 49        :return: The geocoded resource as a dict.
+ 50        """
+ 51        if not overwrite:
+ 52            resource = copy.deepcopy(resource)
+ 53
+ 54        resource_type = resource.get("resourceType", "")
+ 55        if resource_type == "Patient":
+ 56            self._geocode_patient_resource(resource)
+ 57
+ 58        return resource
+ 59
+ 60    def _geocode_patient_resource(self, patient: dict) -> None:
+ 61        """
+ 62        Geocodes all addresses in a patient resource.
+ 63
+ 64        :param patient: A FHIR Patient resource.
+ 65        """
+ 66        for address in patient.get("address", []):
+ 67            address_str = get_one_line_address(address)
+ 68            standardized_address = self.__client.geocode_from_str(address_str)
+ 69
+ 70            # Update fields with new, standardized information
+ 71            if standardized_address:
+ 72                address["line"] = standardized_address.line
+ 73                address["city"] = standardized_address.city
+ 74                address["state"] = standardized_address.state
+ 75                address["county"] = standardized_address.county_name
+ 76                address["postalCode"] = standardized_address.postal_code
+ 77                self._store_lat_long_extension(
+ 78                    address, standardized_address.lat, standardized_address.lng
+ 79                )
+ 80
+ 81    def geocode_bundle(self, bundle: dict, overwrite=True) -> dict:
+ 82        """
+ 83        Geocodes on all resources in a given FHIR bundle whose
+ 84        resource type is among those supported by the PHDI SDK. Currently,
+ 85        this includes:
+ 86
+ 87        * Patient
+ 88
+ 89        :param bundle: A bundle of FHIR resources.
+ 90        :param overwrite: If true, `bundle` is modified in-place;
+ 91          if false, a copy of `bundle` modified and returned.  Default: `True`
+ 92        :return: The FHIR bundle with geocoded address(es).
+ 93        """
+ 94        if not overwrite:
+ 95            bundle = copy.deepcopy(bundle)
+ 96
+ 97        for entry in bundle.get("entry", []):
+ 98            _ = self.geocode_resource(entry.get("resource", {}), overwrite=True)
+ 99
+100        return bundle
+
+ + +

Implementation of a geocoding client designed to handle FHIR- +formatted data using the SmartyStreets API. +Requires an authorization ID as well as an authentication token +in order to build a street lookup client.

+
+ + +
+ +
+ + SmartyFhirGeocodeClient( smarty_auth_id: str, smarty_auth_token: str, licenses: list[str] = ['us-standard-cloud']) + + + +
+ + 
19    def __init__(
+20        self,
+21        smarty_auth_id: str,
+22        smarty_auth_token: str,
+23        licenses: list[str] = ["us-standard-cloud"],
+24    ):
+25        self.__client = SmartyGeocodeClient(smarty_auth_id, smarty_auth_token, licenses)
+
+ + + + +
+
+
+ geocode_client: smartystreets_python_sdk.us_street.client.Client + + +
+ + +

An instance of the underlying Smarty client. +Allows the FHIR wrapper to access a SmartyStreets- +specific connection client without instantiating its own +copy. Provides access to the respective geocode_from_str +and geocode_from_dict methods if they're desired.

+
+ + +
+
+ +
+ + def + geocode_resource(self, resource: dict, overwrite=True) -> dict: + + + +
+ + 
38    def geocode_resource(self, resource: dict, overwrite=True) -> dict:
+39        """
+40        Performs geocoding on one or more addresses in a given FHIR
+41        resource and returns either the result or a copy thereof.
+42        Currently supported resource types are:
+43
+44        * Patient
+45
+46        :param resource: The resource whose addresses should be geocoded.
+47        :param overwrite: If true, `resource` is modified in-place;
+48          if false, a copy of `resource` modified and returned.  Default: `True`
+49        :return: The geocoded resource as a dict.
+50        """
+51        if not overwrite:
+52            resource = copy.deepcopy(resource)
+53
+54        resource_type = resource.get("resourceType", "")
+55        if resource_type == "Patient":
+56            self._geocode_patient_resource(resource)
+57
+58        return resource
+
+ + +

Performs geocoding on one or more addresses in a given FHIR +resource and returns either the result or a copy thereof. +Currently supported resource types are:

+ +
    +
  • Patient
    • +
+ +
Parameters
+ +
    +
  • resource: The resource whose addresses should be geocoded.
    • +
  • overwrite: If true, resource is modified in-place; +if false, a copy of resource modified and returned. Default: True
    • +
+ +
Returns
+ +
+

The geocoded resource as a dict.

+
+
+ + +
+
+ +
+ + def + geocode_bundle(self, bundle: dict, overwrite=True) -> dict: + + + +
+ + 
 81    def geocode_bundle(self, bundle: dict, overwrite=True) -> dict:
+ 82        """
+ 83        Geocodes on all resources in a given FHIR bundle whose
+ 84        resource type is among those supported by the PHDI SDK. Currently,
+ 85        this includes:
+ 86
+ 87        * Patient
+ 88
+ 89        :param bundle: A bundle of FHIR resources.
+ 90        :param overwrite: If true, `bundle` is modified in-place;
+ 91          if false, a copy of `bundle` modified and returned.  Default: `True`
+ 92        :return: The FHIR bundle with geocoded address(es).
+ 93        """
+ 94        if not overwrite:
+ 95            bundle = copy.deepcopy(bundle)
+ 96
+ 97        for entry in bundle.get("entry", []):
+ 98            _ = self.geocode_resource(entry.get("resource", {}), overwrite=True)
+ 99
+100        return bundle
+
+ + +

Geocodes on all resources in a given FHIR bundle whose +resource type is among those supported by the PHDI SDK. Currently, +this includes:

+ +
    +
  • Patient
    • +
+ +
Parameters
+ +
    +
  • bundle: A bundle of FHIR resources.
    • +
  • overwrite: If true, bundle is modified in-place; +if false, a copy of bundle modified and returned. Default: True
    • +
+ +
Returns
+ +
+

The FHIR bundle with geocoded address(es).

+
+
+ + +
+
+
+ +
+ + class + CensusFhirGeocodeClient(phdi.fhir.geospatial.BaseFhirGeocodeClient): + + + +
+ + 
 8class CensusFhirGeocodeClient(BaseFhirGeocodeClient):
+ 9    """
+10    Implementation of a geocoding client designed to handle FHIR-
+11    formatted data using the Census API.
+12    """
+13
+14    def __init__(self):
+15        self.__client = CensusGeocodeClient()
+16
+17    def geocode_resource(self, resource: dict, overwrite=True) -> dict:
+18        """
+19        Performs geocoding on one or more addresses in a given FHIR
+20        resource and returns either the result or a copy thereof. The original street
+21        name, number, and any secondary address line information are returned in the
+22        original form.
+23        Currently supported resource types are:
+24
+25            - Patient
+26
+27        :param resource: The resource whose addresses should be geocoded.
+28        :param overwrite: Whether to save the geocoding information over
+29          the raw data, or to create a copy of the given data and write
+30          over that instead. Defaults to True (write over given data).
+31        :return: Geocoded resource as a dict.
+32        """
+33        # TODO: research additional APIs that return Apt (and other 2nd line addresses)
+34        # so that address.line can be overwritten
+35        if not overwrite:
+36            resource = copy.deepcopy(resource)
+37
+38        resource_type = resource.get("resourceType", "")
+39        if resource_type == "Patient":
+40            self._geocode_patient_resource(resource)
+41
+42        return resource
+43
+44    def _geocode_patient_resource(self, patient: dict) -> None:
+45        """
+46        Handles geocoding of all addresses in a given patient resource.
+47        :param patient: The patient resource whose addresses should be geocoded.
+48        """
+49        for address in patient.get("address", []):
+50            address["street"] = " ".join(item for item in address["line"])
+51            standardized_address = self.__client.geocode_from_dict(address)
+52
+53            # Update fields with new, standardized information
+54            if standardized_address:
+55                address["city"] = standardized_address.city
+56                address["state"] = standardized_address.state
+57                address["postalCode"] = standardized_address.postal_code
+58                self._store_lat_long_extension(
+59                    address, standardized_address.lat, standardized_address.lng
+60                )
+61                self._store_census_tract_extension(
+62                    address, standardized_address.census_tract
+63                )
+64
+65                # Remove dict entry needed only for geocode_from_dict()
+66                del address["street"]
+67
+68    def geocode_bundle(self, bundle: dict, overwrite=True) -> dict:
+69        """
+70        Performs geocoding on all resources in a given FHIR bundle whose
+71        resource type is among those supported by the PHDI SDK. Currently,
+72        this includes:
+73
+74            - Patient
+75
+76        :param bundle: A bundle of fhir resources.
+77        :param overwrite: Whether to overwrite the address data in the given
+78          bundle's resources (True), or whether to create a copy of the bundle
+79          and overwrite that instead (False). Defaults to True.
+80        :return: A FHIR bundle with geocoded address(es).
+81        """
+82        if not overwrite:
+83            bundle = copy.deepcopy(bundle)
+84
+85        for entry in bundle.get("entry", []):
+86            self.geocode_resource(entry.get("resource", {}), overwrite=True)
+87
+88        return bundle
+
+ + +

Implementation of a geocoding client designed to handle FHIR- +formatted data using the Census API.

+
+ + +
+ +
+ + def + geocode_resource(self, resource: dict, overwrite=True) -> dict: + + + +
+ + 
17    def geocode_resource(self, resource: dict, overwrite=True) -> dict:
+18        """
+19        Performs geocoding on one or more addresses in a given FHIR
+20        resource and returns either the result or a copy thereof. The original street
+21        name, number, and any secondary address line information are returned in the
+22        original form.
+23        Currently supported resource types are:
+24
+25            - Patient
+26
+27        :param resource: The resource whose addresses should be geocoded.
+28        :param overwrite: Whether to save the geocoding information over
+29          the raw data, or to create a copy of the given data and write
+30          over that instead. Defaults to True (write over given data).
+31        :return: Geocoded resource as a dict.
+32        """
+33        # TODO: research additional APIs that return Apt (and other 2nd line addresses)
+34        # so that address.line can be overwritten
+35        if not overwrite:
+36            resource = copy.deepcopy(resource)
+37
+38        resource_type = resource.get("resourceType", "")
+39        if resource_type == "Patient":
+40            self._geocode_patient_resource(resource)
+41
+42        return resource
+
+ + +

Performs geocoding on one or more addresses in a given FHIR +resource and returns either the result or a copy thereof. The original street +name, number, and any secondary address line information are returned in the +original form. +Currently supported resource types are:

+ +
- Patient
+
+ +
Parameters
+ +
    +
  • resource: The resource whose addresses should be geocoded.
    • +
  • overwrite: Whether to save the geocoding information over +the raw data, or to create a copy of the given data and write +over that instead. Defaults to True (write over given data).
    • +
+ +
Returns
+ +
+

Geocoded resource as a dict.

+
+
+ + +
+
+ +
+ + def + geocode_bundle(self, bundle: dict, overwrite=True) -> dict: + + + +
+ + 
68    def geocode_bundle(self, bundle: dict, overwrite=True) -> dict:
+69        """
+70        Performs geocoding on all resources in a given FHIR bundle whose
+71        resource type is among those supported by the PHDI SDK. Currently,
+72        this includes:
+73
+74            - Patient
+75
+76        :param bundle: A bundle of fhir resources.
+77        :param overwrite: Whether to overwrite the address data in the given
+78          bundle's resources (True), or whether to create a copy of the bundle
+79          and overwrite that instead (False). Defaults to True.
+80        :return: A FHIR bundle with geocoded address(es).
+81        """
+82        if not overwrite:
+83            bundle = copy.deepcopy(bundle)
+84
+85        for entry in bundle.get("entry", []):
+86            self.geocode_resource(entry.get("resource", {}), overwrite=True)
+87
+88        return bundle
+
+ + +

Performs geocoding on all resources in a given FHIR bundle whose +resource type is among those supported by the PHDI SDK. Currently, +this includes:

+ +
- Patient
+
+ +
Parameters
+ +
    +
  • bundle: A bundle of fhir resources.
    • +
  • overwrite: Whether to overwrite the address data in the given +bundle's resources (True), or whether to create a copy of the bundle +and overwrite that instead (False). Defaults to True.
    • +
+ +
Returns
+ +
+

A FHIR bundle with geocoded address(es).

+
+
+ + +
+
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/fhir/harmonization.html b/docs/v1.2.7/sdk/phdi/fhir/harmonization.html new file mode 100644 index 0000000000..1c892fbe0c --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/fhir/harmonization.html @@ -0,0 +1,638 @@ + + + + + + + phdi.fhir.harmonization API documentation + + + + + + + + + +
+
+

+phdi.fhir.harmonization

+ + + + + + + 
 1from phdi.fhir.harmonization.standardization import double_metaphone_bundle
+ 2from phdi.fhir.harmonization.standardization import double_metaphone_patient
+ 3from phdi.fhir.harmonization.standardization import standardize_dob
+ 4from phdi.fhir.harmonization.standardization import standardize_names
+ 5from phdi.fhir.harmonization.standardization import standardize_phones
+ 6
+ 7__all__ = (
+ 8    "double_metaphone_bundle",
+ 9    "double_metaphone_patient",
+10    "standardize_names",
+11    "standardize_phones",
+12    "standardize_dob",
+13)
+
+ + +
+
+ +
+ + def + double_metaphone_bundle(bundle: dict, overwrite=True) -> dict: + + + +
+ + 
15def double_metaphone_bundle(bundle: dict, overwrite=True) -> dict:
+16    """
+17    Performs the double metaphone algorithm on each name of each patient in a
+18    given FHIR bundle.
+19
+20    :param bundle: A FHIR bundle of data containing one or more patient
+21      resources.
+22    :param overwrite: If true, `data` is modified in-place; if false, a
+23      copy of `data` modified and returned.  Default: `True`.
+24    :return: A dictionary mapping the FHIR IDs of patients in the bundle
+25      to lists holding the double metaphone representations of their
+26      names for each FHIR use case their resource includes.
+27    """
+28    if not overwrite:
+29        bundle = copy.deepcopy(bundle)
+30
+31    dmeta = DoubleMetaphone()
+32    for entry in bundle.get("entry", []):
+33        resource = entry.get("resource", {})
+34        if resource.get("resourceType", "") == "Patient":
+35            double_metaphone_patient(resource, dmeta, overwrite=True)
+36    return bundle
+
+ + +

Performs the double metaphone algorithm on each name of each patient in a +given FHIR bundle.

+ +
Parameters
+ +
    +
  • bundle: A FHIR bundle of data containing one or more patient +resources.
    • +
  • overwrite: If true, data is modified in-place; if false, a +copy of data modified and returned. Default: True.
    • +
+ +
Returns
+ +
+

A dictionary mapping the FHIR IDs of patients in the bundle + to lists holding the double metaphone representations of their + names for each FHIR use case their resource includes.

+
+
+ + +
+
+ +
+ + def + double_metaphone_patient(patient: dict, dmeta=None, overwrite=True) -> dict: + + + +
+ + 
39def double_metaphone_patient(patient: dict, dmeta=None, overwrite=True) -> dict:
+40    """
+41    Performs the double metaphone algorithm for each name in a given patient
+42    resource. The algorithm is performed on each component of the name (first,
+43    middle, last), and the resulting representations are ordered in a list
+44    such that the first element is first name, the last element is last name,
+45    and all other elements are one or more middle names in the order of
+46    name presentation. These lists of phonetic representations are stored as
+47    the values of dictionaries whose keys are the FHIR uses of the name in
+48    the patient resource (e.g. "official"), and all such dictionaries are
+49    returned to the caller in a list ordered the same as the names within
+50    the given resource.
+51
+52    :param patient: A FHIR-formatted JSON dictionary representing a patient
+53      resource.
+54    :param dmeta: An optional existing instantiation of a double metaphone
+55      object for use in bulk processing.
+56    :param overwrite: If true, `data` is modified in-place; if false, a
+57      copy of `data` modified and returned.  Default: `True`.
+58    :return: A list of dictionaries mapping FHIR uses to the phonetic
+59      representations of names associated with those uses, in presentation
+60      order (first, middle, last).
+61    """
+62
+63    if not overwrite:
+64        patient = copy.deepcopy(patient)
+65
+66    for name in patient.get("name", []):
+67        # Processing last name separately allows us to note in the result
+68        # whether last name wasn't present ( = [None, None])
+69        dm_last = double_metaphone_string(name.get("family", ""), dmeta)
+70        dm_givens = []
+71
+72        # Each name is processed sequentially because FHIR expects given
+73        # names to already follow proper presentation order
+74        for given in name.get("given", []):
+75            dm_givens.append(double_metaphone_string(given, dmeta))
+76
+77        # Cleanest way to store computed encodings is as an extension directly
+78        # within the HumanName objects of the patient's `name` field
+79        if name.get("extension", []) == []:
+80            name["extension"] = []
+81
+82        name.get("extension").append(
+83            {
+84                "url": "https://xlinux.nist.gov/dads/HTML/doubleMetaphone.html",
+85                "extension": [
+86                    {"url": "familyName", "valueString": dm_last},
+87                    {"url": "givenName", "valueString": dm_givens},
+88                ],
+89            }
+90        )
+91
+92    return patient
+
+ + +

Performs the double metaphone algorithm for each name in a given patient +resource. The algorithm is performed on each component of the name (first, +middle, last), and the resulting representations are ordered in a list +such that the first element is first name, the last element is last name, +and all other elements are one or more middle names in the order of +name presentation. These lists of phonetic representations are stored as +the values of dictionaries whose keys are the FHIR uses of the name in +the patient resource (e.g. "official"), and all such dictionaries are +returned to the caller in a list ordered the same as the names within +the given resource.

+ +
Parameters
+ +
    +
  • patient: A FHIR-formatted JSON dictionary representing a patient +resource.
    • +
  • dmeta: An optional existing instantiation of a double metaphone +object for use in bulk processing.
    • +
  • overwrite: If true, data is modified in-place; if false, a +copy of data modified and returned. Default: True.
    • +
+ +
Returns
+ +
+

A list of dictionaries mapping FHIR uses to the phonetic + representations of names associated with those uses, in presentation + order (first, middle, last).

+
+
+ + +
+
+ +
+ + def + standardize_names( data: dict, trim: bool = True, case: Literal['upper', 'lower', 'title'] = 'upper', remove_numbers: bool = True, overwrite: bool = True) -> dict: + + + +
+ + 
 95def standardize_names(
+ 96    data: dict,
+ 97    trim: bool = True,
+ 98    case: Literal["upper", "lower", "title"] = "upper",
+ 99    remove_numbers: bool = True,
+100    overwrite: bool = True,
+101) -> dict:
+102    """
+103    Standardizes all names contained in a given FHIR bundle or a FHIR resource. The
+104    default standardization behavior is our defined non-numeric, space-trimming, full
+105    capitalization standardization, but other modes may be specified.
+106
+107    :param data: A FHIR-formatted JSON dict.
+108    :param trim: Whether leading/trailing whitespace should be removed. Default: `True`
+109    :param case: The type of casing that should be used. Default: `upper`
+110    :param remove_numbers: If true, delete numeric characters; if false leave numbers
+111      in place. Default: `True`
+112    :param overwrite: If true, `data` is modified in-place;
+113      if false, a copy of `data` modified and returned.  Default: `True`
+114    :return: The bundle or resource with names appropriately standardized.
+115    """
+116    # Copy the data if we don't want to overwrite the original
+117    if not overwrite:
+118        data = copy.deepcopy(data)
+119
+120    # Allow users to pass in either a resource or a bundle
+121    bundle = data
+122    if "entry" not in data:
+123        bundle = {"entry": [{"resource": data}]}
+124
+125    # Handle all resources individually
+126    for entry in bundle.get("entry"):
+127        resource = entry.get("resource", {})
+128        resource = _standardize_names_in_resource(
+129            resource, trim, case, remove_numbers, overwrite
+130        )
+131
+132    if "entry" not in data:
+133        return bundle.get("entry", [{}])[0].get("resource", {})
+134    return bundle
+
+ + +

Standardizes all names contained in a given FHIR bundle or a FHIR resource. The +default standardization behavior is our defined non-numeric, space-trimming, full +capitalization standardization, but other modes may be specified.

+ +
Parameters
+ +
    +
  • data: A FHIR-formatted JSON dict.
    • +
  • trim: Whether leading/trailing whitespace should be removed. Default: True
    • +
  • case: The type of casing that should be used. Default: upper
    • +
  • remove_numbers: If true, delete numeric characters; if false leave numbers +in place. Default: True
    • +
  • overwrite: If true, data is modified in-place; +if false, a copy of data modified and returned. Default: True
    • +
+ +
Returns
+ +
+

The bundle or resource with names appropriately standardized.

+
+
+ + +
+
+ +
+ + def + standardize_phones(data: dict, overwrite=True) -> dict: + + + +
+ + 
137def standardize_phones(data: dict, overwrite=True) -> dict:
+138    """
+139    Standardizes all phone numbers in a given FHIR bundle or a FHIR resource.
+140    Standardization is done according to the underlying `standardize_phone`
+141    function in `phdi.harmonization`.
+142
+143    :param data: A FHIR bundle or FHIR-formatted JSON dict.
+144    :param overwrite: If true, `data` is modified in-place;
+145      if false, a copy of `data` modified and returned.  Default: `True`
+146    :return: The bundle or resource with phones appropriately standardized.
+147    """
+148
+149    if not overwrite:
+150        data = copy.deepcopy(data)
+151
+152    # Allow users to pass in either a resource or a bundle
+153    bundle = data
+154    if "entry" not in data:
+155        bundle = {"entry": [{"resource": data}]}
+156
+157    for entry in bundle.get("entry"):
+158        resource = entry.get("resource", {})
+159        resource = _standardize_phones_in_resource(resource, overwrite)
+160
+161    if "entry" not in data:
+162        return bundle.get("entry", [{}])[0].get("resource", {})
+163    return bundle
+
+ + +

Standardizes all phone numbers in a given FHIR bundle or a FHIR resource. +Standardization is done according to the underlying standardize_phone +function in phdi.harmonization.

+ +
Parameters
+ +
    +
  • data: A FHIR bundle or FHIR-formatted JSON dict.
    • +
  • overwrite: If true, data is modified in-place; +if false, a copy of data modified and returned. Default: True
    • +
+ +
Returns
+ +
+

The bundle or resource with phones appropriately standardized.

+
+
+ + +
+
+ +
+ + def + standardize_dob(data: dict, format: str = '%Y-%m-%d', overwrite=True) -> dict: + + + +
+ + 
277def standardize_dob(data: dict, format: str = "%Y-%m-%d", overwrite=True) -> dict:
+278    """
+279    Standardizes all birth dates in a given FHIR bundle or a FHIR resource.
+280    Standardization is done according to the underlying `standardize_dob` function in
+281    `phdi.harmonization`.  The final birthDate will follow the FHIR STu3/R4 format
+282    of YYYY-MM-DD which will be stored in the Patient resource.
+283
+284    :param data: A FHIR bundle or FHIR-formatted JSON dict.
+285    :param format: A python DateTime format used to parse the birthDate within
+286      the Patient resource.  Default: `%Y-%m-%d` (also known as YYYY-MM-DD)
+287    :param overwrite: If true, `data` is modified in-place;
+288      if false, a copy of `data` modified and returned.  Default: `True`
+289    :return: The bundle or resource with bith dates appropriately standardized.
+290    """
+291
+292    if not overwrite:
+293        data = copy.deepcopy(data)
+294
+295    # Allow users to pass in either a resource or a bundle
+296    bundle = data
+297    if "entry" not in data:
+298        bundle = {"entry": [{"resource": data}]}
+299
+300    for entry in bundle.get("entry"):
+301        resource = entry.get("resource", {})
+302        resource = _standardize_dob_in_resource(resource, format, overwrite)
+303
+304    if "entry" not in data:
+305        return bundle.get("entry", [{}])[0].get("resource", {})
+306    return bundle
+
+ + +

Standardizes all birth dates in a given FHIR bundle or a FHIR resource. +Standardization is done according to the underlying standardize_dob function in +phdi.harmonization. The final birthDate will follow the FHIR STu3/R4 format +of YYYY-MM-DD which will be stored in the Patient resource.

+ +
Parameters
+ +
    +
  • data: A FHIR bundle or FHIR-formatted JSON dict.
    • +
  • format: A python DateTime format used to parse the birthDate within +the Patient resource. Default: %Y-%m-%d (also known as YYYY-MM-DD)
    • +
  • overwrite: If true, data is modified in-place; +if false, a copy of data modified and returned. Default: True
    • +
+ +
Returns
+ +
+

The bundle or resource with bith dates appropriately standardized.

+
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/fhir/linkage.html b/docs/v1.2.7/sdk/phdi/fhir/linkage.html new file mode 100644 index 0000000000..c1cb9c6251 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/fhir/linkage.html @@ -0,0 +1,414 @@ + + + + + + + phdi.fhir.linkage API documentation + + + + + + + + + +
+
+

+phdi.fhir.linkage

+ + + + + + + 
1from phdi.fhir.linkage.link import add_patient_identifier
+2from phdi.fhir.linkage.link import add_patient_identifier_in_bundle
+3
+4__all__ = ["add_patient_identifier_in_bundle", "add_patient_identifier"]
+
+ + +
+
+ +
+ + def + add_patient_identifier_in_bundle(bundle: dict, salt_str: str, overwrite: bool = True) -> dict: + + + +
+ + 
10def add_patient_identifier_in_bundle(
+11    bundle: dict, salt_str: str, overwrite: bool = True
+12) -> dict:
+13    """
+14    Given a FHIR resource bundle:
+15
+16    * Identifies all patient resource(s) in the bundle
+17    * Adds the hash string to the list of identifiers held in that patient resource
+18
+19    :param bundle: The FHIR bundle for whose patients to add a linking identifier.
+20    :param salt_str: The salt to use with the hash. This is intended to prevent
+21      reverse engineering of the PII used to create the hash.
+22    :param overwrite: If true, `bundle` is modified in-place;
+23      if false, a copy of `bundle` modified and returned.  Default: `True`
+24    :return: The bundle, resources updated with additional patient identifier.
+25    """
+26    if not overwrite:
+27        bundle = copy.deepcopy(bundle)
+28
+29    for entry in find_entries_by_resource_type(bundle, "Patient"):
+30        patient = entry.get("resource")
+31        add_patient_identifier(patient, salt_str)
+32    return bundle
+
+ + +

Given a FHIR resource bundle:

+ +
    +
  • Identifies all patient resource(s) in the bundle
    • +
  • Adds the hash string to the list of identifiers held in that patient resource
    • +
+ +
Parameters
+ +
    +
  • bundle: The FHIR bundle for whose patients to add a linking identifier.
    • +
  • salt_str: The salt to use with the hash. This is intended to prevent +reverse engineering of the PII used to create the hash.
    • +
  • overwrite: If true, bundle is modified in-place; +if false, a copy of bundle modified and returned. Default: True
    • +
+ +
Returns
+ +
+

The bundle, resources updated with additional patient identifier.

+
+
+ + +
+
+ +
+ + def + add_patient_identifier(patient_resource: dict, salt_str: str, overwrite: bool = True): + + + +
+ + 
35def add_patient_identifier(
+36    patient_resource: dict, salt_str: str, overwrite: bool = True
+37):
+38    """
+39    Given a FHIR Patient resource:
+40
+41    * Extracts name, DOB, and address information
+42    * Computes a unique hash string based on these fields
+43    * Adds the hash string to resource
+44
+45    :param patient_resource: The FHIR patient resource to add a linking identifier.
+46    :param salt_str: The salt to use with the hash. This is intended to prevent
+47      reverse engineering of the PII used to create the hash.
+48    :param overwrite: If true, `patient_resource` is modified in-place;
+49      if false, a copy of `patient_resource` modified and returned.  Default: `True`
+50    :return: The resource updated with additional patient identifier.
+51    """
+52    if not overwrite:
+53        patient_resource = copy.deepcopy(patient_resource)
+54
+55    # Combine given and family name
+56    recent_name = (
+57        get_field(patient_resource, field="name", use="official", require_use=False)
+58        or {}
+59    )
+60    name_parts = recent_name.get("given", []) + [recent_name.get("family", "")]
+61    name_str = "-".join([n for n in name_parts if n])
+62
+63    address_line = ""
+64    if "address" in patient_resource:
+65        address = (
+66            get_field(patient_resource, field="address", use="home", require_use=False)
+67            or {}
+68        )
+69        address_line = get_one_line_address(address)
+70
+71    # TODO Determine if minimum quality criteria should be included, such as min
+72    # number of characters in last name, valid birth date, or address line
+73    # Generate and store unique hash code
+74    link_str = f'{name_str}-{patient_resource["birthDate"]}-{address_line}'
+75    hashcode = generate_hash_str(link_str, salt_str)
+76
+77    if "identifier" not in patient_resource:
+78        patient_resource["identifier"] = []
+79
+80    # TODO Follow up on the validity and source of the comment about the system
+81    # value corresponding to the FHIR specification. Need to either add a citation
+82    # or correct the wording to more properly reflect what it represents.
+83    patient_resource["identifier"].append(
+84        {
+85            "value": hashcode,
+86            # Note: this system value corresponds to the FHIR specification
+87            # for a globally used / generated ID or UUID--the standard here
+88            # is to make the use "temporary" even if it's not
+89            "system": "urn:ietf:rfc:3986",
+90            "use": "temp",
+91        }
+92    )
+93    return patient_resource
+
+ + +

Given a FHIR Patient resource:

+ +
    +
  • Extracts name, DOB, and address information
    • +
  • Computes a unique hash string based on these fields
    • +
  • Adds the hash string to resource
    • +
+ +
Parameters
+ +
    +
  • patient_resource: The FHIR patient resource to add a linking identifier.
    • +
  • salt_str: The salt to use with the hash. This is intended to prevent +reverse engineering of the PII used to create the hash.
    • +
  • overwrite: If true, patient_resource is modified in-place; +if false, a copy of patient_resource modified and returned. Default: True
    • +
+ +
Returns
+ +
+

The resource updated with additional patient identifier.

+
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/fhir/tabulation.html b/docs/v1.2.7/sdk/phdi/fhir/tabulation.html new file mode 100644 index 0000000000..68d7e9287b --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/fhir/tabulation.html @@ -0,0 +1,745 @@ + + + + + + + phdi.fhir.tabulation API documentation + + + + + + + + + +
+
+

+phdi.fhir.tabulation

+ + + + + + + 
 1from phdi.fhir.tabulation.tables import drop_invalid
+ 2from phdi.fhir.tabulation.tables import extract_data_from_fhir_search
+ 3from phdi.fhir.tabulation.tables import extract_data_from_fhir_search_incremental
+ 4from phdi.fhir.tabulation.tables import extract_data_from_schema
+ 5from phdi.fhir.tabulation.tables import tabulate_data
+ 6
+ 7__all__ = [
+ 8    "drop_invalid",
+ 9    "extract_data_from_fhir_search",
+10    "extract_data_from_fhir_search_incremental",
+11    "extract_data_from_schema",
+12    "tabulate_data",
+13]
+
+ + +
+
+ +
+ + def + drop_invalid(data: List[list], schema: Dict, table_name: str) -> List[list]: + + + +
+ + 
22def drop_invalid(data: List[list], schema: Dict, table_name: str) -> List[list]:
+23    """
+24    Removes resources from tabulated data if the resource contains an invalid value, as
+25    specified in the invalid_values field in a user-defined schema. Users may provide
+26    invalid values as a list, including empty string values ("") and
+27    None/null values (null).
+28    :param data: A list of lists containing data for a table. The first list in
+29        the data value is a list of headers serving as the columns, and all subsequent
+30        lists are rows in the table.
+31    :param schema: A declarative, user-defined specification, for one or more tables,
+32        that defines the metadata, properties, and columns of those tables as they
+33        relate to FHIR resources.
+34    :param table_name: Name of the table to drop invalid values.
+35    :param return: A list of lists, without rows of data derived from the FHIR
+36        resources and elements that contained invalid values.
+37        The first list in the data value is a list of headers serving as the
+38        columns, and all subsequent lists are rows in the table.
+39    """
+40    invalid_values_by_column_index = {}
+41
+42    # Identify columns to drop invalid values for each table in schema
+43    columns = schema["tables"][table_name]["columns"]
+44    # Identify indices in List of Lists to check for invalid values
+45    invalid_values_by_column_index[table_name] = {
+46        i: columns[col].get("invalid_values")
+47        for i, col in enumerate(columns)
+48        if columns[col].get("invalid_values", [])
+49    }
+50
+51    # Check if resource contains invalid values to be dropped
+52    rows_to_remove = []
+53    if len(invalid_values_by_column_index) > 0:
+54        for i in range(len(data)):
+55            for index, invalid_values in invalid_values_by_column_index[
+56                table_name
+57            ].items():
+58                if data[i][index] in invalid_values:
+59                    rows_to_remove.append(i)
+60                    break
+61
+62    # Remove rows with invalid values
+63    for idx, i in enumerate(rows_to_remove):
+64        del data[i - idx]
+65
+66    return data
+
+ + +

Removes resources from tabulated data if the resource contains an invalid value, as +specified in the invalid_values field in a user-defined schema. Users may provide +invalid values as a list, including empty string values ("") and +None/null values (null).

+ +
Parameters
+ +
    +
  • data: A list of lists containing data for a table. The first list in +the data value is a list of headers serving as the columns, and all subsequent +lists are rows in the table.
    • +
  • schema: A declarative, user-defined specification, for one or more tables, +that defines the metadata, properties, and columns of those tables as they +relate to FHIR resources.
    • +
  • table_name: Name of the table to drop invalid values.
    • +
  • return: A list of lists, without rows of data derived from the FHIR +resources and elements that contained invalid values. +The first list in the data value is a list of headers serving as the +columns, and all subsequent lists are rows in the table.
    • +
+
+ + +
+ +
+ +
+ + def + extract_data_from_fhir_search_incremental( search_url: str, cred_manager: phdi.cloud.core.BaseCredentialManager = None) -> Tuple[List[dict], str]: + + + +
+ + 
101def extract_data_from_fhir_search_incremental(
+102    search_url: str, cred_manager: BaseCredentialManager = None
+103) -> Tuple[List[dict], str]:
+104    """
+105    Performs a FHIR search for a single page of data and returns a dictionary containing
+106    the data and a next URL. If there is no next URL (this is the last page of data),
+107    then return None as the next URL.
+108    :param search_url: The URL to a FHIR server with search criteria.
+109    :param cred_manager: The credential manager used to authenticate to the FHIR server.
+110    :raises requests.HttpError: If the HTTP request was unsuccessful.
+111    :return: Tuple containing single page of data as a list of dictionaries and the next
+112        URL.
+113    """
+114
+115    # TODO: Modify fhir_server_get (and http_request_with_reauth) to function without
+116    # mandating a credential manager. Then replace the direct call to
+117    # http_request_with_reauth with fhir_server_get.
+118    # response = fhir_server_get(url=full_url, cred_manager=cred_manager)
+119    headers = {}
+120    if cred_manager is not None:
+121        access_token = cred_manager.get_access_token()
+122        headers = {
+123            "Authorization": f"Bearer {access_token}",
+124            "Accept": "application/fhir+json",
+125            "Content-Type": "application/fhir+json",
+126        }
+127
+128    response = http_request_with_reauth(
+129        url=search_url,
+130        cred_manager=cred_manager,
+131        retry_count=2,
+132        request_type="GET",
+133        allowed_methods=["GET"],
+134        headers=headers,
+135    )
+136
+137    if response.status_code != 200:  # pragma: no cover
+138        raise requests.HTTPError(response=response)
+139
+140    next_url = None
+141    content = json.loads(response._content.decode("utf-8"))
+142    if len(content) == 0:
+143        warnings.warn(
+144            message=f"The search_url returned no incremental results: {search_url}",
+145        )
+146        content = []
+147    else:
+148        for link in content.get("link", []):
+149            if link.get("relation") == "next":
+150                next_url = link.get("url")
+151
+152        content = content.get("entry")
+153
+154    return content, next_url
+
+ + +

Performs a FHIR search for a single page of data and returns a dictionary containing +the data and a next URL. If there is no next URL (this is the last page of data), +then return None as the next URL.

+ +
Parameters
+ +
    +
  • search_url: The URL to a FHIR server with search criteria.
    • +
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • +
+ +
Raises
+ +
    +
  • requests.HttpError: If the HTTP request was unsuccessful.
    • +
+ +
Returns
+ +
+

Tuple containing single page of data as a list of dictionaries and the next + URL.

+
+
+ + +
+
+ +
+ + def + extract_data_from_schema( schema: dict, fhir_url: str, cred_manager: phdi.cloud.core.BaseCredentialManager = None) -> Dict[str, List[dict]]: + + + +
+ + 
157def extract_data_from_schema(
+158    schema: dict, fhir_url: str, cred_manager: BaseCredentialManager = None
+159) -> Dict[str, List[dict]]:
+160    """
+161    Performs a full FHIR search for each table in the specified `schema`,
+162    and returns a dictionary mapping the table name to corresponding search results.
+163    :param schema: A declarative, user-defined specification, for one or more tables,
+164        that defines the metadata, properties, and columns of those tables as they
+165        relate to FHIR resources.
+166    :param cred_manager: The credential manager used to authenticate to the FHIR server.
+167    :return: A dict containing the mapping of a table and its columns, grouped by
+168        table name, to a list of FHIR resource element results returned from
+169        the search for each subsequent table name.
+170    """
+171
+172    search_urls = _generate_search_urls(schema=schema)
+173
+174    results = {}
+175    for table_name, search_url in search_urls.items():
+176        results[table_name] = extract_data_from_fhir_search(
+177            search_url=f"{fhir_url}/{search_url}", cred_manager=cred_manager
+178        )
+179
+180    return results
+
+ + +

Performs a full FHIR search for each table in the specified schema, +and returns a dictionary mapping the table name to corresponding search results.

+ +
Parameters
+ +
    +
  • schema: A declarative, user-defined specification, for one or more tables, +that defines the metadata, properties, and columns of those tables as they +relate to FHIR resources.
    • +
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • +
+ +
Returns
+ +
+

A dict containing the mapping of a table and its columns, grouped by + table name, to a list of FHIR resource element results returned from + the search for each subsequent table name.

+
+
+ + +
+
+ +
+ + def + tabulate_data(data: List[dict], schema: dict, table_name: str) -> List[list]: + + + +
+ + 
183def tabulate_data(data: List[dict], schema: dict, table_name: str) -> List[list]:
+184    """
+185    Transforms a list of FHIR bundle resource entries into a tabular
+186    format (given by a list of lists) using a user-defined schema.
+187    Tabulation works using a two-pass procedure. First, resources
+188    that are associated with one another in the provided schema
+189    (identified by the presence of a `reference_location` field in
+190    one of the schema's columns) are grouped together. For each
+191    table, one type of resource serves as the "anchor", which
+192    defines the number of rows in the table, while referenced
+193    resources are either "forwards" or "reverse" references,
+194    depending on their relationship to the anchor type. Second,
+195    the aggregated resources are parsed for value extraction using
+196    the schema's columns, and the results are stored in a list of
+197    lists for that table. The first entry in this list are the headers
+198    of the data, taken from the schema. This functions performs the
+199    above procedure on one table from the schema, specified by a
+200    table name.
+201    :param data: A list of FHIR bundle resource entries to tabulate.
+202    :param schema: A declarative, user-defined specification, for one or more tables,
+203        that defines the metadata, properties, and columns of those tables as they
+204        relate to FHIR resources.
+205    :param table_name: A string specifying the name of a table defined
+206      in the given schema.
+207    :raises KeyError: If the given `table_name` does not occur in the
+208      provided schema.
+209    :return: A list of lists denoting the tabulated form of the data.
+210      The first list is a list of headers serving as the columns,
+211      and all subsequent lists are rows in the table.
+212    """
+213
+214    if table_name not in schema.get("tables", {}):
+215        raise KeyError(f"Provided table name {table_name} not found in schema")
+216
+217    # First pass: build mapping of references for easy lookup
+218    ref_directions = _get_reference_directions(schema)
+219    ref_dicts = _build_reference_dicts(data, ref_directions)
+220
+221    # Get the columns from the schema so we always iterate through
+222    # them in a consistent order
+223    table_params = schema["tables"][table_name]
+224    column_items = table_params["columns"].items()
+225    headers = [column_name for column_name, _ in column_items]
+226    tabulated_data = [headers]
+227    anchor_type = schema["tables"][table_name]["resource_type"]
+228
+229    # Second pass over just the anchor data, since that
+230    # defines the table's rows
+231    for anchor_resource, is_result_because in (
+232        ref_dicts.get(table_name, {}).get(anchor_type, {}).values()
+233    ):
+234        # Resources that aren't matches to the original criteria
+235        # don't generate rows because they were included via a
+236        # reference
+237        if is_result_because != "match":
+238            continue
+239
+240        row = []
+241
+242        for _, column_params in column_items:
+243            path_to_use = column_params["fhir_path"]
+244            resource_to_use = anchor_resource
+245
+246            # Determine if we need to make a lookup in our
+247            # first-pass reference mapping
+248            if "reference_location" in column_params:
+249                resource_to_use = _dereference_included_resource(
+250                    resource_to_use,
+251                    path_to_use,
+252                    anchor_resource,
+253                    column_params,
+254                    ref_dicts,
+255                    table_name,
+256                )
+257                if resource_to_use is None:
+258                    row.append(None)
+259                    continue
+260
+261            # Forward pointers are many-to-one anchor:target (i.e. many patients
+262            # could point to the same general practitioner), so we only need a
+263            # single value for them
+264            if isinstance(resource_to_use, dict):
+265                row.append(
+266                    extract_value_with_resource_path(
+267                        resource_to_use,
+268                        path_to_use,
+269                        column_params["selection_criteria"],
+270                    )
+271                )
+272
+273            # Reverse pointers are one-to-many (one patient could have multiple
+274            # observations pointing to them), so they need to be stored in a list
+275            else:
+276                values = [
+277                    extract_value_with_resource_path(
+278                        r, path_to_use, column_params["selection_criteria"]
+279                    )
+280                    for r in resource_to_use
+281                ]
+282                row.append(values)
+283
+284        tabulated_data.append(row)
+285
+286    # Drop invalid values specified in the schema
+287    tabulated_data = drop_invalid(tabulated_data, schema, table_name)
+288
+289    return tabulated_data
+
+ + +

Transforms a list of FHIR bundle resource entries into a tabular +format (given by a list of lists) using a user-defined schema. +Tabulation works using a two-pass procedure. First, resources +that are associated with one another in the provided schema +(identified by the presence of a reference_location field in +one of the schema's columns) are grouped together. For each +table, one type of resource serves as the "anchor", which +defines the number of rows in the table, while referenced +resources are either "forwards" or "reverse" references, +depending on their relationship to the anchor type. Second, +the aggregated resources are parsed for value extraction using +the schema's columns, and the results are stored in a list of +lists for that table. The first entry in this list are the headers +of the data, taken from the schema. This functions performs the +above procedure on one table from the schema, specified by a +table name.

+ +
Parameters
+ +
    +
  • data: A list of FHIR bundle resource entries to tabulate.
    • +
  • schema: A declarative, user-defined specification, for one or more tables, +that defines the metadata, properties, and columns of those tables as they +relate to FHIR resources.
    • +
  • table_name: A string specifying the name of a table defined +in the given schema.
    • +
+ +
Raises
+ +
    +
  • KeyError: If the given table_name does not occur in the +provided schema.
    • +
+ +
Returns
+ +
+

A list of lists denoting the tabulated form of the data. + The first list is a list of headers serving as the columns, + and all subsequent lists are rows in the table.

+
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/fhir/transport.html b/docs/v1.2.7/sdk/phdi/fhir/transport.html new file mode 100644 index 0000000000..9ad57801ad --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/fhir/transport.html @@ -0,0 +1,654 @@ + + + + + + + phdi.fhir.transport API documentation + + + + + + + + + +
+
+

+phdi.fhir.transport

+ + + + + + + 
 1from phdi.fhir.transport.export import export_from_fhir_server
+ 2from phdi.fhir.transport.http import fhir_server_get
+ 3from phdi.fhir.transport.http import http_request_with_reauth
+ 4from phdi.fhir.transport.http import upload_bundle_to_fhir_server
+ 5
+ 6__all__ = [
+ 7    "http_request_with_reauth",
+ 8    "fhir_server_get",
+ 9    "upload_bundle_to_fhir_server",
+10    "export_from_fhir_server",
+11]
+
+ + +
+
+ +
+ + def + http_request_with_reauth( cred_manager: phdi.cloud.core.BaseCredentialManager, url: str, retry_count: int, request_type: Literal['GET', 'POST'], allowed_methods: List[str], headers: dict, data: dict = None) -> requests.models.Response: + + + +
+ + 
12def http_request_with_reauth(
+13    cred_manager: BaseCredentialManager,
+14    url: str,
+15    retry_count: int,
+16    request_type: Literal["GET", "POST"],
+17    allowed_methods: List[str],
+18    headers: dict,
+19    data: dict = None,
+20) -> requests.Response:
+21    """
+22    First, calls :func:`phdi.transport.http.http_request_with_retry`. If the first call
+23    fails with an authorization error (HTTP status 401), obtains a new token using the
+24    `cred_manager`. If the original request had an Authorization header, replaces
+25    it with the new token and re-initiates
+26    :func:`phdi.transport.http.http_request_with_retry`.
+27
+28    :param cred_manager: The credential manager used to authenticate to the FHIR server.
+29    :param url: The url at which to make the HTTP request.
+30    :param retry_count: The number of times to retry the request, if the
+31      first attempt fails.
+32    :param request_type: The type of request to be made.
+33    :param allowed_methods: The list of allowed HTTP request methods (i.e.,
+34      POST, PUT, etc.) for the specific URL and query.
+35    :param headers: JSON-type dictionary of headers to make the request with,
+36      including Authorization and content-type.
+37    :param data: JSON data in the case that the request requires data to be
+38      posted. Default: `None`
+39    :return: A `requests.Request` object containing the response from the FHIR server.
+40    """
+41
+42    response = http_request_with_retry(
+43        url=url,
+44        retry_count=retry_count,
+45        request_type=request_type,
+46        allowed_methods=allowed_methods,
+47        headers=headers,
+48        data=data,
+49    )
+50
+51    # Retry with new token in case it expired since creation (or from cache)
+52    if response.status_code == 401:
+53        if headers.get("Authorization", "").startswith("Bearer "):
+54            new_access_token = cred_manager.get_access_token()
+55            headers["Authorization"] = f"Bearer {new_access_token}"
+56
+57        response = http_request_with_retry(
+58            url=url,
+59            retry_count=retry_count,
+60            request_type=request_type,
+61            allowed_methods=allowed_methods,
+62            headers=headers,
+63            data=data,
+64        )
+65
+66    return response
+
+ + +

First, calls phdi.transport.http.http_request_with_retry(). If the first call +fails with an authorization error (HTTP status 401), obtains a new token using the +cred_manager. If the original request had an Authorization header, replaces +it with the new token and re-initiates +phdi.transport.http.http_request_with_retry().

+ +
Parameters
+ +
    +
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • +
  • url: The url at which to make the HTTP request.
    • +
  • retry_count: The number of times to retry the request, if the +first attempt fails.
    • +
  • request_type: The type of request to be made.
    • +
  • allowed_methods: The list of allowed HTTP request methods (i.e., +POST, PUT, etc.) for the specific URL and query.
    • +
  • headers: JSON-type dictionary of headers to make the request with, +including Authorization and content-type.
    • +
  • data: JSON data in the case that the request requires data to be +posted. Default: None
    • +
+ +
Returns
+ +
+

A requests.Request object containing the response from the FHIR server.

+
+
+ + +
+
+ +
+ + def + fhir_server_get( url: str, cred_manager: phdi.cloud.core.BaseCredentialManager) -> requests.models.Response: + + + +
+ + 
138def fhir_server_get(url: str, cred_manager: BaseCredentialManager) -> requests.Response:
+139    """
+140    Submits a GET request to a FHIR server given a url and access token for
+141    authentication.
+142
+143    :param url: A URL specifying a GET request on a FHIR server.
+144    :param cred_manager: The credential manager used to authenticate to the FHIR server.
+145    :return: A `requests.Request` object containing the response from the FHIR server.
+146    """
+147    access_token = cred_manager.get_access_token()
+148    # Open connection to the export operation and kickoff process
+149    response = http_request_with_reauth(
+150        cred_manager=cred_manager,
+151        url=url,
+152        retry_count=3,
+153        request_type="GET",
+154        allowed_methods=["GET"],
+155        headers={"Authorization": f"Bearer {access_token}"},
+156    )
+157
+158    _log_fhir_server_error(response.status_code)
+159
+160    return response
+
+ + +

Submits a GET request to a FHIR server given a url and access token for +authentication.

+ +
Parameters
+ +
    +
  • url: A URL specifying a GET request on a FHIR server.
    • +
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • +
+ +
Returns
+ +
+

A requests.Request object containing the response from the FHIR server.

+
+
+ + +
+
+ +
+ + def + upload_bundle_to_fhir_server( bundle: dict, cred_manager: phdi.cloud.core.BaseCredentialManager, fhir_url: str, max_bundle_size: int = 500) -> list[requests.models.Response]: + + + +
+ + 
 69def upload_bundle_to_fhir_server(
+ 70    bundle: dict,
+ 71    cred_manager: BaseCredentialManager,
+ 72    fhir_url: str,
+ 73    max_bundle_size: int = 500,
+ 74) -> list[requests.Response]:
+ 75    """
+ 76    Uploads a FHIR resource bundle to the FHIR server.
+ 77
+ 78    :param bundle: A FHIR bundle (type "batch" or "transaction") to post.  Each entry in
+ 79      the bundle must contain a `request` element in addition to a `resource`.
+ 80      The FHIR API provides additional details on creating
+ 81      [FHIR-conformant batch/transaction](https://hl7.org/fhir/http.html#transaction)
+ 82      bundles.
+ 83    :param cred_manager: The credential manager used to authenticate to the FHIR server.
+ 84    :param fhir_url: The url of the FHIR server to upload to.
+ 85    :param max_bundle_size: The maximum number of resources per bundle to upload to
+ 86      the FHIR server.
+ 87    :return: A `requests.Response` object containing the response from the FHIR server.
+ 88    """
+ 89
+ 90    access_token = cred_manager.get_access_token()
+ 91    responses = []
+ 92
+ 93    # ensure that bundles are below the set maximum size of resources
+ 94    split_bundles = _split_bundle_resources(bundle, max_bundle_size)
+ 95
+ 96    for single_bundle in split_bundles:
+ 97        response = http_request_with_reauth(
+ 98            cred_manager=cred_manager,
+ 99            url=fhir_url,
+100            retry_count=3,
+101            request_type="POST",
+102            allowed_methods=["POST"],
+103            headers={
+104                "Authorization": f"Bearer {access_token}",
+105                "Accept": "application/fhir+json",
+106                "Content-Type": "application/fhir+json",
+107            },
+108            data=single_bundle,
+109        )
+110        # FHIR uploads are sent as a batch.  Although the batch succeeds,
+111        # individual entries within the batch may fail, so we log them here
+112        if response.status_code == 200:
+113            response_json = response.json()
+114
+115            entries = response_json.get("entry", [])
+116            for entry_index, entry in enumerate(entries):
+117                entry_response = entry.get("response", {})
+118
+119                # FHIR bundle.entry.response.status is string type - integer status code
+120                # plus may inlude a message
+121                if entry_response and entry_response.get("status", "") not in [
+122                    "200 OK",
+123                    "201 Created",
+124                    "200",
+125                    "201",
+126                ]:
+127                    _log_fhir_server_error(
+128                        status_code=int(entry_response["status"][0:3]),
+129                        batch_entry_index=entry_index,
+130                    )
+131        else:
+132            _log_fhir_server_error(response.status_code)
+133        responses.append(response)
+134
+135    return responses
+
+ + +

Uploads a FHIR resource bundle to the FHIR server.

+ +
Parameters
+ +
    +
  • bundle: A FHIR bundle (type "batch" or "transaction") to post. Each entry in +the bundle must contain a request element in addition to a resource. +The FHIR API provides additional details on creating +FHIR-conformant batch/transaction +bundles.
    • +
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • +
  • fhir_url: The url of the FHIR server to upload to.
    • +
  • max_bundle_size: The maximum number of resources per bundle to upload to +the FHIR server.
    • +
+ +
Returns
+ +
+

A requests.Response object containing the response from the FHIR server.

+
+
+ + +
+
+ +
+ + def + export_from_fhir_server( cred_manager: phdi.cloud.core.BaseCredentialManager, fhir_url: str, export_scope: str = '', since: str = '', resource_type: str = '', container: str = '', poll_step: float = 30, poll_timeout: float = 300) -> dict: + + + +
+ + 
11def export_from_fhir_server(
+12    cred_manager: BaseCredentialManager,
+13    fhir_url: str,
+14    export_scope: str = "",
+15    since: str = "",
+16    resource_type: str = "",
+17    container: str = "",
+18    poll_step: float = 30,
+19    poll_timeout: float = 300,
+20) -> dict:
+21    """
+22    Initiates a FHIR $export operation, polls until it completes, and returns the
+23    successful result.
+24
+25    :param cred_manager: The credential manager used to authenticate to the FHIR server.
+26    :param fhir_url: The FHIR server base URL.
+27    :param export_scope: Either `Patient` or `Group/[id]` as specified in the FHIR spec
+28      (https://hl7.org/fhir/uv/bulkdata/export/index.html#bulk-data-kick-off-request).
+29    :param since: A FHIR instant (https://build.fhir.org/datatypes.html#instant)
+30      instructing the export to include only resources created or modified after the
+31      specified instant.
+32    :param resource_type: A comma-delimited list of FHIR resource types to include
+33      in exported files.
+34    :param container: The name of the storage container used to store exported files.
+35    :param poll_step: The number of seconds to wait between poll requests, waiting
+36      for export files to be generated.
+37    :param poll_timeout: The maximum number of seconds to wait for export files to
+38      be generated.
+39    :raises polling.TimeoutException: If the FHIR server continually returns a 202
+40      status indicating in progress until the timeout is reached.
+41    :return: The JSON-formatted HTTP response of a completed export operation
+42      as a dictionary.
+43    """
+44    # TODO consider putting implementation-specific parameters (e.g. container) in a
+45    # flexible dictionary rather than listing as explicit parameters.
+46
+47    # Combine template variables into export endpoint
+48    access_token = cred_manager.get_access_token()
+49    export_url = _compose_export_url(
+50        fhir_url=fhir_url,
+51        export_scope=export_scope,
+52        since=since,
+53        resource_type=resource_type,
+54        container=container,
+55    )
+56
+57    # Open connection to the export operation and kickoff process
+58    response = http_request_with_reauth(
+59        cred_manager=cred_manager,
+60        url=export_url,
+61        retry_count=3,
+62        request_type="GET",
+63        allowed_methods=["GET"],
+64        headers={
+65            "Authorization": f"Bearer {access_token}",
+66            "Accept": "application/fhir+json",
+67            "Prefer": "respond-async",
+68        },
+69    )
+70
+71    # TODO handle export failure conditions and timeouts.
+72    if response.status_code == 202:
+73        # Repeatedly poll the endpoint the FHIR server creates for us
+74        # until either the connection times out (as we configured) or
+75        # we have the response in hand
+76        poll_response = export_from_fhir_server_poll(
+77            poll_url=response.headers.get("Content-Location"),
+78            cred_manager=cred_manager,
+79            poll_step=poll_step,
+80            poll_timeout=poll_timeout,
+81        )
+82
+83        # We successfully completed the full export
+84        if poll_response.status_code == 200:
+85            return poll_response.json()
+
+ + +

Initiates a FHIR $export operation, polls until it completes, and returns the +successful result.

+ +
Parameters
+ +
    +
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • +
  • fhir_url: The FHIR server base URL.
    • +
  • export_scope: Either Patient or Group/[id] as specified in the FHIR spec +(https://hl7.org/fhir/uv/bulkdata/export/index.html#bulk-data-kick-off-request).
    • +
  • since: A FHIR instant (https: //build.fhir.org/datatypes.html#instant) +instructing the export to include only resources created or modified after the +specified instant.
    • +
  • resource_type: A comma-delimited list of FHIR resource types to include +in exported files.
    • +
  • container: The name of the storage container used to store exported files.
    • +
  • poll_step: The number of seconds to wait between poll requests, waiting +for export files to be generated.
    • +
  • poll_timeout: The maximum number of seconds to wait for export files to +be generated.
    • +
+ +
Raises
+ +
    +
  • polling.TimeoutException: If the FHIR server continually returns a 202 +status indicating in progress until the timeout is reached.
    • +
+ +
Returns
+ +
+

The JSON-formatted HTTP response of a completed export operation + as a dictionary.

+
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/fhir/utils.html b/docs/v1.2.7/sdk/phdi/fhir/utils.html new file mode 100644 index 0000000000..70ea712500 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/fhir/utils.html @@ -0,0 +1,808 @@ + + + + + + + phdi.fhir.utils API documentation + + + + + + + + + +
+
+

+phdi.fhir.utils

+ + + + + + + 
  1import json
+  2import random
+  3from functools import cache
+  4from typing import Any
+  5from typing import Callable
+  6from typing import List
+  7from typing import Literal
+  8from typing import Union
+  9
+ 10import fhirpathpy
+ 11
+ 12selection_criteria_types = Literal["first", "last", "random", "all"]
+ 13
+ 14
+ 15def apply_selection_criteria(
+ 16    value: List[Any],
+ 17    selection_criteria: selection_criteria_types,
+ 18) -> str | List:
+ 19    """
+ 20    Returns value(s), according to the selection criteria, from a given list of values
+ 21    parsed from a FHIR resource. A single string value is returned - if the selected
+ 22    value is a complex structure (list or dict), it is converted to a string.
+ 23    :param value: A list containing the values parsed from a FHIR resource.
+ 24    :param selection_criteria: A string indicating which element(s) of a list to select.
+ 25    :return: Value(s) parsed from a FHIR resource that conform to the selection
+ 26      criteria.
+ 27    """
+ 28
+ 29    if selection_criteria == "first":
+ 30        value = value[0]
+ 31    elif selection_criteria == "last":
+ 32        value = value[-1]
+ 33    elif selection_criteria == "random":
+ 34        value = random.choice(value)
+ 35    elif selection_criteria == "all":
+ 36        return value
+ 37    else:
+ 38        raise ValueError(
+ 39            f'Selection criteria {selection_criteria} is not a valid option. Must be one of "first", "last", "random", or "all".'  # noqa
+ 40        )
+ 41
+ 42    # Temporary hack to ensure no structured data is written using pyarrow.
+ 43    # Currently Pyarrow does not support mixing non-structured and structured data.
+ 44    # https://github.com/awslabs/aws-data-wrangler/issues/463
+ 45    # Will need to consider other methods of writing to parquet if this is an essential
+ 46    # feature.
+ 47    if type(value) is dict:  # pragma: no cover
+ 48        value = json.dumps(value)
+ 49    elif type(value) is list:
+ 50        value = ",".join(value)
+ 51    return value
+ 52
+ 53
+ 54def extract_value_with_resource_path(
+ 55    resource: dict,
+ 56    path: str,
+ 57    selection_criteria: Literal["first", "last", "random", "all"] = "first",
+ 58) -> Union[Any, None]:
+ 59    """
+ 60    Yields a single value from a resource based on a provided `fhir_path`.
+ 61    If the path doesn't map to an extant value in the first, returns
+ 62    `None` instead.
+ 63    :param resource: The FHIR resource to extract a value from.
+ 64    :param path: The `fhir_path` at which the value can be found in the
+ 65      resource.
+ 66    :param selection_criteria: A string dictating which value to extract,
+ 67      if multiple values exist at the path location.
+ 68    :return: The extracted value, or `None` if the value doesn't exist.
+ 69    """
+ 70    parse_function = get_fhirpathpy_parser(path)
+ 71    value = parse_function(resource)
+ 72    if len(value) == 0:
+ 73        return None
+ 74    else:
+ 75        value = apply_selection_criteria(value, selection_criteria)
+ 76        return value
+ 77
+ 78
+ 79def find_entries_by_resource_type(bundle: dict, resource_type: str) -> List[dict]:
+ 80    """
+ 81    Collect all entries of a specific type in a bundle of FHIR data and
+ 82    return references to them in a list.
+ 83
+ 84    :param bundle: The FHIR bundle to search for resource entries.
+ 85    :param resource_type: The type of FHIR resource to find.
+ 86    :return: A list holding all entries of the requested resource type that were
+ 87      found in the input bundle.
+ 88    """
+ 89    return [
+ 90        entry
+ 91        for entry in bundle.get("entry", [])
+ 92        if entry.get("resource", {}).get("resourceType", "") == resource_type
+ 93    ]
+ 94
+ 95
+ 96def get_field(
+ 97    resource: dict,
+ 98    field: str,
+ 99    index: int = 1,
+100    use: str = None,
+101    require_use: bool = True,
+102) -> Any:
+103    """
+104    Finds an instance of the specified field in a given FHIR- formatted JSON dictionary.
+105    Optionally, a particular "use" of a field can be provided such that only instances
+106    with that purpose are considered. For example, find the name for a patient that has
+107    a "use" of "official". "Use" here refers to the FHIR-based usage of classifying a
+108    value's purpose. If no instance of a field with the requested use case can be found,
+109    instead return a specified default value for the field.
+110
+111    :param resource: A FHIR-formatted resource.
+112    :param field: The field to extract.
+113    :param index: The nth element of the field to return. If the index is greater than
+114      the number of elements in the field, the last element will be returned. If the
+115      index is less than 1, the first element will be returned. Default: 1.
+116    :param use: The 'use' the field must have to qualify for selection. Default: None.
+117    :param require_use: If True and no elements of the specified field have that
+118      use, none will be returned. If False and no elements of the specified field have
+119      that use, the nth element as indicated by the index parameter will be returned.
+120      This parameter is ignored if no use is specified. Default: True.
+121    :return: The first instance of the field value matching the desired
+122      use, or a default field value if a match couldn't be found.
+123    """
+124    # TODO revisit the `default_field` logic, and confirm this is the best way to handle
+125    # choosing a default
+126    if field == "":
+127        raise ValueError("The field parameter must be a defined, non-empty string.")
+128    if use == "":
+129        raise ValueError(
+130            "The use parameter should be a defined, non-empty string. If you don't want to include a use, set the parameter to None."  # noqa
+131        )
+132    if field not in resource:
+133        raise KeyError(f"This resource does not contain a field called {field}.")
+134
+135    elements = resource.get(field, [])
+136    if use is not None:
+137        elements_with_use = [item for item in elements if item.get("use") == use]
+138        if len(elements_with_use) == 0 and require_use:
+139            return None
+140        if len(elements_with_use) > 0:
+141            elements = elements_with_use
+142
+143    # min(...) ensures index <= len(elements) and the -1 shifts back to 0-index
+144    # max(...) ensures the index is not negative
+145    index = max(min(index, len(elements)) - 1, 0)
+146
+147    return elements[index] if len(elements) > 0 else None
+148
+149
+150@cache
+151def get_fhirpathpy_parser(fhirpath_expression: str) -> Callable:
+152    """
+153    Accepts a FHIRPath expression, and returns a callable function
+154    which returns the evaluated value at fhirpath_expression for
+155    a specified FHIR resource.
+156    :param fhirpath_expression: The FHIRPath expression to evaluate.
+157    :return: A function that, when called passing in a FHIR resource,
+158      will return value at `fhirpath_expression`.
+159    """
+160    return fhirpathpy.compile(fhirpath_expression)
+161
+162
+163def get_one_line_address(address: dict) -> str:
+164    """
+165    Extracts a one-line string representation of an address from a
+166    JSON dictionary holding address information.
+167
+168    :param address: The FHIR-formatted address.
+169    :return: A one-line string representation of an address.
+170    """
+171    if len(address) == 0:
+172        return ""
+173    raw_one_line = " ".join(address.get("line", []))
+174    raw_one_line += f" {address.get('city', '')}, {address.get('state', '')}"
+175    if address.get("postalCode", ""):
+176        raw_one_line += f" {address['postalCode']}"
+177    return raw_one_line
+
+ + +
+
+ +
+ + def + apply_selection_criteria( value: List[Any], selection_criteria: Literal['first', 'last', 'random', 'all']) -> Union[str, List]: + + + +
+ + 
16def apply_selection_criteria(
+17    value: List[Any],
+18    selection_criteria: selection_criteria_types,
+19) -> str | List:
+20    """
+21    Returns value(s), according to the selection criteria, from a given list of values
+22    parsed from a FHIR resource. A single string value is returned - if the selected
+23    value is a complex structure (list or dict), it is converted to a string.
+24    :param value: A list containing the values parsed from a FHIR resource.
+25    :param selection_criteria: A string indicating which element(s) of a list to select.
+26    :return: Value(s) parsed from a FHIR resource that conform to the selection
+27      criteria.
+28    """
+29
+30    if selection_criteria == "first":
+31        value = value[0]
+32    elif selection_criteria == "last":
+33        value = value[-1]
+34    elif selection_criteria == "random":
+35        value = random.choice(value)
+36    elif selection_criteria == "all":
+37        return value
+38    else:
+39        raise ValueError(
+40            f'Selection criteria {selection_criteria} is not a valid option. Must be one of "first", "last", "random", or "all".'  # noqa
+41        )
+42
+43    # Temporary hack to ensure no structured data is written using pyarrow.
+44    # Currently Pyarrow does not support mixing non-structured and structured data.
+45    # https://github.com/awslabs/aws-data-wrangler/issues/463
+46    # Will need to consider other methods of writing to parquet if this is an essential
+47    # feature.
+48    if type(value) is dict:  # pragma: no cover
+49        value = json.dumps(value)
+50    elif type(value) is list:
+51        value = ",".join(value)
+52    return value
+
+ + +

Returns value(s), according to the selection criteria, from a given list of values +parsed from a FHIR resource. A single string value is returned - if the selected +value is a complex structure (list or dict), it is converted to a string.

+ +
Parameters
+ +
    +
  • value: A list containing the values parsed from a FHIR resource.
    • +
  • selection_criteria: A string indicating which element(s) of a list to select.
    • +
+ +
Returns
+ +
+

Value(s) parsed from a FHIR resource that conform to the selection + criteria.

+
+
+ + +
+
+ +
+ + def + extract_value_with_resource_path( resource: dict, path: str, selection_criteria: Literal['first', 'last', 'random', 'all'] = 'first') -> Optional[Any]: + + + +
+ + 
55def extract_value_with_resource_path(
+56    resource: dict,
+57    path: str,
+58    selection_criteria: Literal["first", "last", "random", "all"] = "first",
+59) -> Union[Any, None]:
+60    """
+61    Yields a single value from a resource based on a provided `fhir_path`.
+62    If the path doesn't map to an extant value in the first, returns
+63    `None` instead.
+64    :param resource: The FHIR resource to extract a value from.
+65    :param path: The `fhir_path` at which the value can be found in the
+66      resource.
+67    :param selection_criteria: A string dictating which value to extract,
+68      if multiple values exist at the path location.
+69    :return: The extracted value, or `None` if the value doesn't exist.
+70    """
+71    parse_function = get_fhirpathpy_parser(path)
+72    value = parse_function(resource)
+73    if len(value) == 0:
+74        return None
+75    else:
+76        value = apply_selection_criteria(value, selection_criteria)
+77        return value
+
+ + +

Yields a single value from a resource based on a provided fhir_path. +If the path doesn't map to an extant value in the first, returns +None instead.

+ +
Parameters
+ +
    +
  • resource: The FHIR resource to extract a value from.
    • +
  • path: The fhir_path at which the value can be found in the +resource.
    • +
  • selection_criteria: A string dictating which value to extract, +if multiple values exist at the path location.
    • +
+ +
Returns
+ +
+

The extracted value, or None if the value doesn't exist.

+
+
+ + +
+
+ +
+ + def + find_entries_by_resource_type(bundle: dict, resource_type: str) -> List[dict]: + + + +
+ + 
80def find_entries_by_resource_type(bundle: dict, resource_type: str) -> List[dict]:
+81    """
+82    Collect all entries of a specific type in a bundle of FHIR data and
+83    return references to them in a list.
+84
+85    :param bundle: The FHIR bundle to search for resource entries.
+86    :param resource_type: The type of FHIR resource to find.
+87    :return: A list holding all entries of the requested resource type that were
+88      found in the input bundle.
+89    """
+90    return [
+91        entry
+92        for entry in bundle.get("entry", [])
+93        if entry.get("resource", {}).get("resourceType", "") == resource_type
+94    ]
+
+ + +

Collect all entries of a specific type in a bundle of FHIR data and +return references to them in a list.

+ +
Parameters
+ +
    +
  • bundle: The FHIR bundle to search for resource entries.
    • +
  • resource_type: The type of FHIR resource to find.
    • +
+ +
Returns
+ +
+

A list holding all entries of the requested resource type that were + found in the input bundle.

+
+
+ + +
+
+ +
+ + def + get_field( resource: dict, field: str, index: int = 1, use: str = None, require_use: bool = True) -> Any: + + + +
+ + 
 97def get_field(
+ 98    resource: dict,
+ 99    field: str,
+100    index: int = 1,
+101    use: str = None,
+102    require_use: bool = True,
+103) -> Any:
+104    """
+105    Finds an instance of the specified field in a given FHIR- formatted JSON dictionary.
+106    Optionally, a particular "use" of a field can be provided such that only instances
+107    with that purpose are considered. For example, find the name for a patient that has
+108    a "use" of "official". "Use" here refers to the FHIR-based usage of classifying a
+109    value's purpose. If no instance of a field with the requested use case can be found,
+110    instead return a specified default value for the field.
+111
+112    :param resource: A FHIR-formatted resource.
+113    :param field: The field to extract.
+114    :param index: The nth element of the field to return. If the index is greater than
+115      the number of elements in the field, the last element will be returned. If the
+116      index is less than 1, the first element will be returned. Default: 1.
+117    :param use: The 'use' the field must have to qualify for selection. Default: None.
+118    :param require_use: If True and no elements of the specified field have that
+119      use, none will be returned. If False and no elements of the specified field have
+120      that use, the nth element as indicated by the index parameter will be returned.
+121      This parameter is ignored if no use is specified. Default: True.
+122    :return: The first instance of the field value matching the desired
+123      use, or a default field value if a match couldn't be found.
+124    """
+125    # TODO revisit the `default_field` logic, and confirm this is the best way to handle
+126    # choosing a default
+127    if field == "":
+128        raise ValueError("The field parameter must be a defined, non-empty string.")
+129    if use == "":
+130        raise ValueError(
+131            "The use parameter should be a defined, non-empty string. If you don't want to include a use, set the parameter to None."  # noqa
+132        )
+133    if field not in resource:
+134        raise KeyError(f"This resource does not contain a field called {field}.")
+135
+136    elements = resource.get(field, [])
+137    if use is not None:
+138        elements_with_use = [item for item in elements if item.get("use") == use]
+139        if len(elements_with_use) == 0 and require_use:
+140            return None
+141        if len(elements_with_use) > 0:
+142            elements = elements_with_use
+143
+144    # min(...) ensures index <= len(elements) and the -1 shifts back to 0-index
+145    # max(...) ensures the index is not negative
+146    index = max(min(index, len(elements)) - 1, 0)
+147
+148    return elements[index] if len(elements) > 0 else None
+
+ + +

Finds an instance of the specified field in a given FHIR- formatted JSON dictionary. +Optionally, a particular "use" of a field can be provided such that only instances +with that purpose are considered. For example, find the name for a patient that has +a "use" of "official". "Use" here refers to the FHIR-based usage of classifying a +value's purpose. If no instance of a field with the requested use case can be found, +instead return a specified default value for the field.

+ +
Parameters
+ +
    +
  • resource: A FHIR-formatted resource.
    • +
  • field: The field to extract.
    • +
  • index: The nth element of the field to return. If the index is greater than +the number of elements in the field, the last element will be returned. If the +index is less than 1, the first element will be returned. Default: 1.
    • +
  • use: The 'use' the field must have to qualify for selection. Default: None.
    • +
  • require_use: If True and no elements of the specified field have that +use, none will be returned. If False and no elements of the specified field have +that use, the nth element as indicated by the index parameter will be returned. +This parameter is ignored if no use is specified. Default: True.
    • +
+ +
Returns
+ +
+

The first instance of the field value matching the desired + use, or a default field value if a match couldn't be found.

+
+
+ + +
+
+ +
+
@cache
+ + def + get_fhirpathpy_parser(fhirpath_expression: str) -> Callable: + + + +
+ + 
151@cache
+152def get_fhirpathpy_parser(fhirpath_expression: str) -> Callable:
+153    """
+154    Accepts a FHIRPath expression, and returns a callable function
+155    which returns the evaluated value at fhirpath_expression for
+156    a specified FHIR resource.
+157    :param fhirpath_expression: The FHIRPath expression to evaluate.
+158    :return: A function that, when called passing in a FHIR resource,
+159      will return value at `fhirpath_expression`.
+160    """
+161    return fhirpathpy.compile(fhirpath_expression)
+
+ + +

Accepts a FHIRPath expression, and returns a callable function +which returns the evaluated value at fhirpath_expression for +a specified FHIR resource.

+ +
Parameters
+ +
    +
  • fhirpath_expression: The FHIRPath expression to evaluate.
    • +
+ +
Returns
+ +
+

A function that, when called passing in a FHIR resource, + will return value at fhirpath_expression.

+
+
+ + +
+
+ +
+ + def + get_one_line_address(address: dict) -> str: + + + +
+ + 
164def get_one_line_address(address: dict) -> str:
+165    """
+166    Extracts a one-line string representation of an address from a
+167    JSON dictionary holding address information.
+168
+169    :param address: The FHIR-formatted address.
+170    :return: A one-line string representation of an address.
+171    """
+172    if len(address) == 0:
+173        return ""
+174    raw_one_line = " ".join(address.get("line", []))
+175    raw_one_line += f" {address.get('city', '')}, {address.get('state', '')}"
+176    if address.get("postalCode", ""):
+177        raw_one_line += f" {address['postalCode']}"
+178    return raw_one_line
+
+ + +

Extracts a one-line string representation of an address from a +JSON dictionary holding address information.

+ +
Parameters
+ +
    +
  • address: The FHIR-formatted address.
    • +
+ +
Returns
+ +
+

A one-line string representation of an address.

+
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/geospatial.html b/docs/v1.2.7/sdk/phdi/geospatial.html new file mode 100644 index 0000000000..c10e1591e7 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/geospatial.html @@ -0,0 +1,1294 @@ + + + + + + + phdi.geospatial API documentation + + + + + + + + + +
+
+

+phdi.geospatial

+ + + + + + + 
 1from phdi.geospatial.census import CensusGeocodeClient
+ 2from phdi.geospatial.core import BaseGeocodeClient
+ 3from phdi.geospatial.core import GeocodeResult
+ 4from phdi.geospatial.smarty import SmartyGeocodeClient
+ 5
+ 6__all__ = (
+ 7    "GeocodeResult",
+ 8    "BaseGeocodeClient",
+ 9    "SmartyGeocodeClient",
+10    "CensusGeocodeClient",
+11)
+
+ + +
+
+ +
+
@dataclass
+ + class + GeocodeResult: + + + +
+ + 
10@dataclass
+11class GeocodeResult:
+12    """
+13    Represents a successful geocoding response.
+14    Based on the field nomenclature of a FHIR address, specified at
+15    https://www.hl7.org/fhir/datatypes.html#Address.
+16    """
+17
+18    line: List[str]
+19    city: str
+20    state: str
+21    postal_code: str
+22    county_fips: str
+23    lat: float
+24    lng: float
+25    district: Optional[str] = None
+26    country: Optional[str] = None
+27    county_name: Optional[str] = None
+28    precision: Optional[str] = None
+29    geoid: Optional[str] = None
+30    census_tract: Optional[str] = None
+31    census_block: Optional[str] = None
+
+ + +

Represents a successful geocoding response. +Based on the field nomenclature of a FHIR address, specified at +https://www.hl7.org/fhir/datatypes.html#Address.

+
+ + +
+
+ + GeocodeResult( line: List[str], city: str, state: str, postal_code: str, county_fips: str, lat: float, lng: float, district: Optional[str] = None, country: Optional[str] = None, county_name: Optional[str] = None, precision: Optional[str] = None, geoid: Optional[str] = None, census_tract: Optional[str] = None, census_block: Optional[str] = None) + + +
+ + + + +
+
+
+ +
+ + class + BaseGeocodeClient(abc.ABC): + + + +
+ + 
34class BaseGeocodeClient(ABC):
+35    """
+36    Represents a vendor-agnostic geocoder client. Requires implementing
+37    classes to define methods to geocode from both strings and dictionaries.
+38    Callers should use the provided interface functions (e.g., geocode_from_str)
+39    to interact with the underlying vendor-specific client property.
+40    """
+41
+42    @abstractmethod
+43    def geocode_from_str(self, address: str) -> Union[GeocodeResult, None]:
+44        """
+45        Geocodes the provided address, which is formatted as a string.
+46
+47        :param address: The address to geocode, given as a string.
+48        :param overwrite: If true, `resource` is modified in-place;
+49          if false, a copy of `resource` modified and returned.  Default: `True`
+50        :return: A geocoded address (if valid result) or None (if no valid result).
+51        """
+52        pass  # pragma: no cover
+53
+54    @abstractmethod
+55    def geocode_from_dict(self, address: dict) -> Union[GeocodeResult, None]:
+56        """
+57        Geocodes the provided address, which is formatted as a dictionary.
+58
+59        The given dictionary should conform to standard nomenclature around address
+60        fields, including:
+61
+62        * `street`: the number and street address
+63        * `street2`: additional street level information (if needed)
+64        * `apartment`: apartment or suite number (if needed)
+65        * `city`: city to geocode
+66        * `state`: state to geocode
+67        * `postal_code`: the postal code to use
+68        * `urbanization`: urbanization code for area, sector, or regional
+69        * `development`: (only used for Puerto Rican addresses)
+70
+71        There is no minimum number of fields that must be specified to use this
+72        function; however, a minimum of street, city, and state are suggested
+73        for the best matches.
+74
+75        :param address: A dictionary with fields outlined above.
+76        :return: A geocoded address (if valid result) or None (if no valid result).
+77        """
+78        pass  # pragma: no cover
+
+ + +

Represents a vendor-agnostic geocoder client. Requires implementing +classes to define methods to geocode from both strings and dictionaries. +Callers should use the provided interface functions (e.g., geocode_from_str) +to interact with the underlying vendor-specific client property.

+
+ + +
+ +
+
@abstractmethod
+ + def + geocode_from_str(self, address: str) -> Optional[phdi.geospatial.GeocodeResult]: + + + +
+ + 
42    @abstractmethod
+43    def geocode_from_str(self, address: str) -> Union[GeocodeResult, None]:
+44        """
+45        Geocodes the provided address, which is formatted as a string.
+46
+47        :param address: The address to geocode, given as a string.
+48        :param overwrite: If true, `resource` is modified in-place;
+49          if false, a copy of `resource` modified and returned.  Default: `True`
+50        :return: A geocoded address (if valid result) or None (if no valid result).
+51        """
+52        pass  # pragma: no cover
+
+ + +

Geocodes the provided address, which is formatted as a string.

+ +
Parameters
+ +
    +
  • address: The address to geocode, given as a string.
    • +
  • overwrite: If true, resource is modified in-place; +if false, a copy of resource modified and returned. Default: True
    • +
+ +
Returns
+ +
+

A geocoded address (if valid result) or None (if no valid result).

+
+
+ + +
+
+ +
+
@abstractmethod
+ + def + geocode_from_dict(self, address: dict) -> Optional[phdi.geospatial.GeocodeResult]: + + + +
+ + 
54    @abstractmethod
+55    def geocode_from_dict(self, address: dict) -> Union[GeocodeResult, None]:
+56        """
+57        Geocodes the provided address, which is formatted as a dictionary.
+58
+59        The given dictionary should conform to standard nomenclature around address
+60        fields, including:
+61
+62        * `street`: the number and street address
+63        * `street2`: additional street level information (if needed)
+64        * `apartment`: apartment or suite number (if needed)
+65        * `city`: city to geocode
+66        * `state`: state to geocode
+67        * `postal_code`: the postal code to use
+68        * `urbanization`: urbanization code for area, sector, or regional
+69        * `development`: (only used for Puerto Rican addresses)
+70
+71        There is no minimum number of fields that must be specified to use this
+72        function; however, a minimum of street, city, and state are suggested
+73        for the best matches.
+74
+75        :param address: A dictionary with fields outlined above.
+76        :return: A geocoded address (if valid result) or None (if no valid result).
+77        """
+78        pass  # pragma: no cover
+
+ + +

Geocodes the provided address, which is formatted as a dictionary.

+ +

The given dictionary should conform to standard nomenclature around address +fields, including:

+ +
    +
  • street: the number and street address
    • +
  • street2: additional street level information (if needed)
    • +
  • apartment: apartment or suite number (if needed)
    • +
  • city: city to geocode
    • +
  • state: state to geocode
    • +
  • postal_code: the postal code to use
    • +
  • urbanization: urbanization code for area, sector, or regional
    • +
  • development: (only used for Puerto Rican addresses)
    • +
+ +

There is no minimum number of fields that must be specified to use this +function; however, a minimum of street, city, and state are suggested +for the best matches.

+ +
Parameters
+ +
    +
  • address: A dictionary with fields outlined above.
    • +
+ +
Returns
+ +
+

A geocoded address (if valid result) or None (if no valid result).

+
+
+ + +
+
+
+ +
+ + class + SmartyGeocodeClient(phdi.geospatial.BaseGeocodeClient): + + + +
+ + 
 13class SmartyGeocodeClient(BaseGeocodeClient):
+ 14    """
+ 15    Represents a PHDI-supplied geocoding client using the Smarty API.
+ 16    Requires an authorization ID as well as an authentication token
+ 17    in order to build a street lookup client.
+ 18    """
+ 19
+ 20    def __init__(
+ 21        self,
+ 22        smarty_auth_id: str,
+ 23        smarty_auth_token: str,
+ 24        licenses: list[str] = ["us-standard-cloud"],
+ 25    ):
+ 26        self.smarty_auth_id = smarty_auth_id
+ 27        self.smarty_auth_token = smarty_auth_token
+ 28        creds = StaticCredentials(smarty_auth_id, smarty_auth_token)
+ 29        self.__client = (
+ 30            ClientBuilder(creds).with_licenses(licenses).build_us_street_api_client()
+ 31        )
+ 32
+ 33    @property
+ 34    def client(self) -> us_street.Client:
+ 35        """
+ 36        This property:
+ 37          1. defines a private instance variable __client
+ 38          2. makes it accessible through the use of .client()
+ 39
+ 40        This property holds a Smarty-specific connection client that
+ 41        allows a user to geocode without directly referencing the
+ 42        underlying vendor service client.
+ 43        """
+ 44        return self.__client
+ 45
+ 46    def geocode_from_str(self, address: str) -> Union[GeocodeResult, None]:
+ 47        """
+ 48        Geocodes the provided address, which is formatted as a string. If the
+ 49        result cannot be latitude- or longitude-located, then Smarty failed
+ 50        to precisely geocode the address, so no result is returned. Raises
+ 51        an error if the provided address is empty.
+ 52
+ 53        :param address: The address to geocode, given as a string.
+ 54        :raises ValueError: When the address does not include street number and name.
+ 55        :return: A geocoded address (if valid result) or None (if no valid result).
+ 56        """
+ 57
+ 58        # The smarty Lookup class will parse a BadRequestError but retry
+ 59        # 5 times if the lookup address is blank, so catch that here
+ 60        if address == "":
+ 61            raise ValueError("Address must include street number and name at a minimum")
+ 62
+ 63        lookup = Lookup(street=address)
+ 64        self.__client.send_lookup(lookup)
+ 65        return self._parse_smarty_result(lookup)
+ 66
+ 67    def geocode_from_dict(self, address: dict) -> Union[GeocodeResult, None]:
+ 68        """
+ 69        Geocodes the provided address, which is formatted as a dictionary.
+ 70
+ 71        The given dictionary should conform to standard nomenclature around address
+ 72        fields, including:
+ 73
+ 74        * `street`: the number and street address
+ 75        * `street2`: additional street level information (if needed)
+ 76        * `apartment`: apartment or suite number (if needed)
+ 77        * `city`: city to geocode
+ 78        * `state`: state to geocode
+ 79        * `postal_code`: the postal code to use
+ 80        * `urbanization`: urbanization code for area, sector, or regional
+ 81        * `development`: (only used for Puerto Rican addresses)
+ 82
+ 83        There is no minimum number of fields that must be specified to use this
+ 84        function; however, a minimum of street, city, and state are suggested
+ 85        for the best matches.
+ 86
+ 87        :param address: A dictionary with fields outlined above.
+ 88        :raises Exception: When the address street is an empty string.
+ 89        :return: A geocoded address (if valid result) or None (if no valid result).
+ 90        """
+ 91
+ 92        # Smarty geocode requests must include a street level
+ 93        # field in the payload, otherwise generates BadRequestError
+ 94        if address.get("street", "") == "":
+ 95            raise ValueError("Address must include street number and name at a minimum")
+ 96
+ 97        # Configure the lookup with whatever provided address values
+ 98        # were in the user-given dictionary
+ 99        lookup = Lookup()
+100        lookup.street = address.get("street", "")
+101        lookup.street2 = address.get("street2", "")
+102        lookup.secondary = address.get("apartment", "")
+103        lookup.city = address.get("city", "")
+104        lookup.state = address.get("state", "")
+105        lookup.zipcode = address.get("postal_code", "")
+106        lookup.urbanization = address.get("urbanization", "")
+107        lookup.match = "strict"
+108
+109        self.__client.send_lookup(lookup)
+110        return self._parse_smarty_result(lookup)
+111
+112    @staticmethod
+113    def _parse_smarty_result(lookup) -> Union[GeocodeResult, None]:
+114        """
+115        Parses a returned Smarty geocoding result into a GeocodeResult object.
+116        If the Smarty lookup is null or doesn't include latitude and longitude
+117        information, returns None instead.
+118
+119        :param lookup: The us_street.lookup client instantiated for geocoding.
+120        :return: The geocoded address (if valid result) or None (if no valid result).
+121        """
+122        # Valid responses have results with lat/long
+123        if lookup.result and lookup.result[0].metadata.latitude:
+124            smartystreets_result = lookup.result[0]
+125            street_address = [smartystreets_result.delivery_line_1]
+126            if smartystreets_result.delivery_line_2:
+127                street_address.append(smartystreets_result.delivery_line_2)
+128
+129            # Format the Smarty result into our standard dataclass object
+130            return GeocodeResult(
+131                line=street_address,
+132                city=smartystreets_result.components.city_name,
+133                state=smartystreets_result.components.state_abbreviation,
+134                postal_code=smartystreets_result.components.zipcode,
+135                county_fips=smartystreets_result.metadata.county_fips,
+136                county_name=smartystreets_result.metadata.county_name,
+137                lat=smartystreets_result.metadata.latitude,
+138                lng=smartystreets_result.metadata.longitude,
+139                precision=smartystreets_result.metadata.precision,
+140            )
+141
+142        return
+
+ + +

Represents a PHDI-supplied geocoding client using the Smarty API. +Requires an authorization ID as well as an authentication token +in order to build a street lookup client.

+
+ + +
+ +
+ + SmartyGeocodeClient( smarty_auth_id: str, smarty_auth_token: str, licenses: list[str] = ['us-standard-cloud']) + + + +
+ + 
20    def __init__(
+21        self,
+22        smarty_auth_id: str,
+23        smarty_auth_token: str,
+24        licenses: list[str] = ["us-standard-cloud"],
+25    ):
+26        self.smarty_auth_id = smarty_auth_id
+27        self.smarty_auth_token = smarty_auth_token
+28        creds = StaticCredentials(smarty_auth_id, smarty_auth_token)
+29        self.__client = (
+30            ClientBuilder(creds).with_licenses(licenses).build_us_street_api_client()
+31        )
+
+ + + + +
+
+
+ client: smartystreets_python_sdk.us_street.client.Client + + +
+ + +

This property:

+ +
    +
  1. defines a private instance variable __client
    2. +
  2. makes it accessible through the use of .client()
    3. +
+ +

This property holds a Smarty-specific connection client that +allows a user to geocode without directly referencing the +underlying vendor service client.

+
+ + +
+
+ +
+ + def + geocode_from_str(self, address: str) -> Optional[phdi.geospatial.GeocodeResult]: + + + +
+ + 
46    def geocode_from_str(self, address: str) -> Union[GeocodeResult, None]:
+47        """
+48        Geocodes the provided address, which is formatted as a string. If the
+49        result cannot be latitude- or longitude-located, then Smarty failed
+50        to precisely geocode the address, so no result is returned. Raises
+51        an error if the provided address is empty.
+52
+53        :param address: The address to geocode, given as a string.
+54        :raises ValueError: When the address does not include street number and name.
+55        :return: A geocoded address (if valid result) or None (if no valid result).
+56        """
+57
+58        # The smarty Lookup class will parse a BadRequestError but retry
+59        # 5 times if the lookup address is blank, so catch that here
+60        if address == "":
+61            raise ValueError("Address must include street number and name at a minimum")
+62
+63        lookup = Lookup(street=address)
+64        self.__client.send_lookup(lookup)
+65        return self._parse_smarty_result(lookup)
+
+ + +

Geocodes the provided address, which is formatted as a string. If the +result cannot be latitude- or longitude-located, then Smarty failed +to precisely geocode the address, so no result is returned. Raises +an error if the provided address is empty.

+ +
Parameters
+ +
    +
  • address: The address to geocode, given as a string.
    • +
+ +
Raises
+ +
    +
  • ValueError: When the address does not include street number and name.
    • +
+ +
Returns
+ +
+

A geocoded address (if valid result) or None (if no valid result).

+
+
+ + +
+
+ +
+ + def + geocode_from_dict(self, address: dict) -> Optional[phdi.geospatial.GeocodeResult]: + + + +
+ + 
 67    def geocode_from_dict(self, address: dict) -> Union[GeocodeResult, None]:
+ 68        """
+ 69        Geocodes the provided address, which is formatted as a dictionary.
+ 70
+ 71        The given dictionary should conform to standard nomenclature around address
+ 72        fields, including:
+ 73
+ 74        * `street`: the number and street address
+ 75        * `street2`: additional street level information (if needed)
+ 76        * `apartment`: apartment or suite number (if needed)
+ 77        * `city`: city to geocode
+ 78        * `state`: state to geocode
+ 79        * `postal_code`: the postal code to use
+ 80        * `urbanization`: urbanization code for area, sector, or regional
+ 81        * `development`: (only used for Puerto Rican addresses)
+ 82
+ 83        There is no minimum number of fields that must be specified to use this
+ 84        function; however, a minimum of street, city, and state are suggested
+ 85        for the best matches.
+ 86
+ 87        :param address: A dictionary with fields outlined above.
+ 88        :raises Exception: When the address street is an empty string.
+ 89        :return: A geocoded address (if valid result) or None (if no valid result).
+ 90        """
+ 91
+ 92        # Smarty geocode requests must include a street level
+ 93        # field in the payload, otherwise generates BadRequestError
+ 94        if address.get("street", "") == "":
+ 95            raise ValueError("Address must include street number and name at a minimum")
+ 96
+ 97        # Configure the lookup with whatever provided address values
+ 98        # were in the user-given dictionary
+ 99        lookup = Lookup()
+100        lookup.street = address.get("street", "")
+101        lookup.street2 = address.get("street2", "")
+102        lookup.secondary = address.get("apartment", "")
+103        lookup.city = address.get("city", "")
+104        lookup.state = address.get("state", "")
+105        lookup.zipcode = address.get("postal_code", "")
+106        lookup.urbanization = address.get("urbanization", "")
+107        lookup.match = "strict"
+108
+109        self.__client.send_lookup(lookup)
+110        return self._parse_smarty_result(lookup)
+
+ + +

Geocodes the provided address, which is formatted as a dictionary.

+ +

The given dictionary should conform to standard nomenclature around address +fields, including:

+ +
    +
  • street: the number and street address
    • +
  • street2: additional street level information (if needed)
    • +
  • apartment: apartment or suite number (if needed)
    • +
  • city: city to geocode
    • +
  • state: state to geocode
    • +
  • postal_code: the postal code to use
    • +
  • urbanization: urbanization code for area, sector, or regional
    • +
  • development: (only used for Puerto Rican addresses)
    • +
+ +

There is no minimum number of fields that must be specified to use this +function; however, a minimum of street, city, and state are suggested +for the best matches.

+ +
Parameters
+ +
    +
  • address: A dictionary with fields outlined above.
    • +
+ +
Raises
+ +
    +
  • Exception: When the address street is an empty string.
    • +
+ +
Returns
+ +
+

A geocoded address (if valid result) or None (if no valid result).

+
+
+ + +
+
+
+ +
+ + class + CensusGeocodeClient(phdi.geospatial.BaseGeocodeClient): + + + +
+ + 
 12class CensusGeocodeClient(BaseGeocodeClient):
+ 13    """
+ 14    Implementation of a geocoding client using the Census API.
+ 15    """
+ 16
+ 17    def __init__(self):
+ 18        self.__client = ()
+ 19
+ 20    def geocode_from_str(self, address: str) -> Union[GeocodeResult, None]:
+ 21        """
+ 22        Geocodes a string-formatted address using Census API with searchtype =
+ 23        "onelineaddress". If a result is found, encodes as a GeocodeResult object and
+ 24        return, otherwise the return None.
+ 25
+ 26        :param address: The address to geocode, given as a string.
+ 27        :param searchtype: onelineaddress OR address # doesn't yet support coordinates.
+ 28        :raises ValueError: If address does not include street number and name.
+ 29        :return: A standardized address enriched with lat, lon, census tract, and more.
+ 30            Returns None if no valid result.
+ 31        """
+ 32        # Check for street num and name at minimum
+ 33        if address == "":
+ 34            raise ValueError("Address must include street number and name at a minimum")
+ 35
+ 36        formatted_address = self._format_address(address, searchtype="onelineaddress")
+ 37        url = self._get_url(formatted_address)
+ 38        response = self._call_census_api(url)
+ 39
+ 40        return self._parse_census_result(response)
+ 41
+ 42    def geocode_from_dict(self, address: dict) -> Union[GeocodeResult, None]:
+ 43        """
+ 44        Geocodes the provided address, which is formatted as a dictionary.
+ 45        using the Census API with searchtype = "address". If a result is found, encodes
+ 46        as a GeocodeResult object and return, otherwise returns None.
+ 47
+ 48        The given dictionary should conform to standard nomenclature around address
+ 49        fields, including:
+ 50
+ 51        * `street`: the number and street address
+ 52        * `street2`: additional street level information (if needed)
+ 53        * `apartment`: apartment or suite number (if needed)
+ 54        * `city`: city to geocode
+ 55        * `state`: state to geocode
+ 56        * `postal_code`: the postal code to use
+ 57        * `urbanization`: urbanization code for area, sector, or regional
+ 58        * `development`: (only used for Puerto Rican addresses)
+ 59
+ 60        Street must be included to use this function; however, a minimum of street,
+ 61        city, and state are suggested for the best matches.
+ 62
+ 63        :param address: A dictionary with fields outlined above.
+ 64        :raises ValueError: If address does not include street number and name.
+ 65        :return: A standardized address enriched with lat, lon, census tract, and more.
+ 66            Returns None if no valid result.
+ 67        """
+ 68
+ 69        # Check for street num and name at minimum
+ 70        if address.get("street", "") == "":
+ 71            raise ValueError("Address must include street number and name at a minimum")
+ 72
+ 73        # Configure the lookup with whatever provided address values
+ 74        # were in the user-given dictionary
+ 75        formatted_address = self._format_address(address, searchtype="address")
+ 76        url = self._get_url(formatted_address)
+ 77        response = self._call_census_api(url)
+ 78
+ 79        return self._parse_census_result(response)
+ 80
+ 81    @staticmethod
+ 82    def _format_address(
+ 83        address: Union[str, dict], searchtype: Literal["onelineaddress", "address"]
+ 84    ):
+ 85        """
+ 86        Formats an address for Census API call according to the given address type. A
+ 87        single line address, e.g, "100 5th Ave New York, NY" uses the "onelineaddress"
+ 88        searchtype while a dictionary formatted address uses the "address" searchtype.
+ 89
+ 90        :param address: The address to geocode, given as a string or dictionary.
+ 91        :param searchtype: onelineaddress OR address.
+ 92        :raises ValueError: If address cannot be geocoded with specificity because it
+ 93            does not include city, state, and/or zipcode.
+ 94        :return: A properly formatted address for the Census API call, given as a
+ 95            string.
+ 96        """
+ 97        # Check that the address contains structure number and street name
+ 98        if searchtype == "onelineaddress":
+ 99            address = address.replace(" ", "+").replace(",", "%2C")
+100            return f"onelineaddress?address={address}"
+101        elif searchtype == "address" and type(address) is dict:
+102            street = address.get("street", "").replace(" ", "+").replace(",", "%2C")
+103            city = address.get("city", "").replace(" ", "+").replace(",", "%2C")
+104            state = address.get("state", "").replace(" ", "+").replace(",", "%2C")
+105            zip = address.get("zip", "").replace(" ", "+").replace(",", "%2C")
+106
+107            # If only "street" is present, format address with
+108            # searchtype = "onelineaddress"
+109            if any(element != "" for element in [city, state, zip]):
+110                # Add non-empty elements
+111                formatted_address = f"address?street={street}"
+112                for element in [city, state, zip]:
+113                    if element == "":
+114                        continue
+115                    else:
+116                        if element == city:
+117                            formatted_address += f"&city={city}"
+118                        elif element == state:
+119                            formatted_address += f"&state={state}"
+120                        elif element == zip:
+121                            formatted_address += f"&zip={zip}"
+122                return formatted_address
+123
+124            else:
+125                return f"onelineaddress?address={street}"
+126
+127    @staticmethod
+128    def _get_url(address: str):
+129        """
+130        Gets URL for Census API given inputs.
+131
+132        :param address: The formatted address to geocode, given as a string.
+133        :return: A URL for the Census API request, as a string.
+134        """
+135        url = (
+136            f"https://geocoding.geo.census.gov/geocoder/geographies/{address}"
+137            + "&benchmark=Public_AR_Census2020"
+138            + "&vintage=Census2020_Census2020"
+139            + "&layers=[10]"
+140            + "&format=json"
+141        )
+142        return url
+143
+144    @staticmethod
+145    def _call_census_api(url):
+146        """
+147        Calls the Census endpoint with a given URL using the http_request_with_retry
+148        method.
+149
+150        :param url: A URL for the Census API request, as a string.
+151        :raises requests.HTTPError: If an unexpected status code is returned.
+152        :return: A response from queried endpoint.
+153        """
+154        http_url = url
+155        http_action = "GET"
+156        http_header = {"some-header": "some-header-value"}
+157        http_retry_count = 5
+158
+159        response = http_request_with_retry(
+160            http_url,
+161            http_retry_count,
+162            http_action,
+163            [http_action],
+164            http_header,
+165        )
+166
+167        if response.status_code != 200:
+168            raise requests.HTTPError(response=response)
+169        else:
+170            return response.json()["result"]
+171
+172    @staticmethod
+173    def _parse_census_result(lookup) -> Union[GeocodeResult, None]:
+174        """
+175        Parses a returned Census geocoding result into our standardized GeocodeResult
+176        class. If the Census lookup is null or doesn't include matched address
+177        information, returns None instead.
+178
+179        :param response: The Census API client instantiated for geocoding.
+180        :return: A parsed and standardized address enriched with lat, lon, census tract,
+181             and more. Returns None if no valid result.
+182        """
+183
+184        if lookup is not None and lookup.get("addressMatches"):
+185            addressComponents = lookup.get("addressMatches", [{}])[0].get(
+186                "addressComponents", {}
+187            )
+188            blockComponents = (
+189                lookup.get("addressMatches", [{}])[0]
+190                .get("geographies", {})
+191                .get("Census Blocks", [None])[0]
+192            )
+193            tractComponents = (
+194                lookup.get("addressMatches", [{}])[0]
+195                .get("geographies", {})
+196                .get("Census Tracts", [None])[0]
+197            )
+198            countyComponents = (
+199                lookup.get("addressMatches", [{}])[0]
+200                .get("geographies", {})
+201                .get("Counties", [None])[0]
+202            )
+203            coordinateComponents = lookup.get("addressMatches", [{}])[0].get(
+204                "coordinates", {}
+205            )
+206
+207            # Format the Census result into our standard dataclass object
+208            return GeocodeResult(
+209                line=[
+210                    lookup["addressMatches"][0]["matchedAddress"].split(",")[0].strip()
+211                ],
+212                city=addressComponents.get("city", ""),
+213                state=addressComponents.get("state", ""),
+214                postal_code=addressComponents.get("zip", ""),
+215                county_fips=blockComponents.get("STATE", "")
+216                + blockComponents.get("COUNTY", ""),
+217                county_name=countyComponents.get("BASENAME", ""),
+218                lat=coordinateComponents.get("y", None),
+219                lng=coordinateComponents.get("x", None),
+220                geoid=blockComponents.get("GEOID", ""),
+221                census_tract=tractComponents.get("BASENAME", ""),
+222                census_block=blockComponents.get("BASENAME", ""),
+223            )
+
+ + +

Implementation of a geocoding client using the Census API.

+
+ + +
+ +
+ + def + geocode_from_str(self, address: str) -> Optional[phdi.geospatial.GeocodeResult]: + + + +
+ + 
20    def geocode_from_str(self, address: str) -> Union[GeocodeResult, None]:
+21        """
+22        Geocodes a string-formatted address using Census API with searchtype =
+23        "onelineaddress". If a result is found, encodes as a GeocodeResult object and
+24        return, otherwise the return None.
+25
+26        :param address: The address to geocode, given as a string.
+27        :param searchtype: onelineaddress OR address # doesn't yet support coordinates.
+28        :raises ValueError: If address does not include street number and name.
+29        :return: A standardized address enriched with lat, lon, census tract, and more.
+30            Returns None if no valid result.
+31        """
+32        # Check for street num and name at minimum
+33        if address == "":
+34            raise ValueError("Address must include street number and name at a minimum")
+35
+36        formatted_address = self._format_address(address, searchtype="onelineaddress")
+37        url = self._get_url(formatted_address)
+38        response = self._call_census_api(url)
+39
+40        return self._parse_census_result(response)
+
+ + +

Geocodes a string-formatted address using Census API with searchtype = +"onelineaddress". If a result is found, encodes as a GeocodeResult object and +return, otherwise the return None.

+ +
Parameters
+ +
    +
  • address: The address to geocode, given as a string.
    • +
  • searchtype: onelineaddress OR address # doesn't yet support coordinates.
    • +
+ +
Raises
+ +
    +
  • ValueError: If address does not include street number and name.
    • +
+ +
Returns
+ +
+

A standardized address enriched with lat, lon, census tract, and more. + Returns None if no valid result.

+
+
+ + +
+
+ +
+ + def + geocode_from_dict(self, address: dict) -> Optional[phdi.geospatial.GeocodeResult]: + + + +
+ + 
42    def geocode_from_dict(self, address: dict) -> Union[GeocodeResult, None]:
+43        """
+44        Geocodes the provided address, which is formatted as a dictionary.
+45        using the Census API with searchtype = "address". If a result is found, encodes
+46        as a GeocodeResult object and return, otherwise returns None.
+47
+48        The given dictionary should conform to standard nomenclature around address
+49        fields, including:
+50
+51        * `street`: the number and street address
+52        * `street2`: additional street level information (if needed)
+53        * `apartment`: apartment or suite number (if needed)
+54        * `city`: city to geocode
+55        * `state`: state to geocode
+56        * `postal_code`: the postal code to use
+57        * `urbanization`: urbanization code for area, sector, or regional
+58        * `development`: (only used for Puerto Rican addresses)
+59
+60        Street must be included to use this function; however, a minimum of street,
+61        city, and state are suggested for the best matches.
+62
+63        :param address: A dictionary with fields outlined above.
+64        :raises ValueError: If address does not include street number and name.
+65        :return: A standardized address enriched with lat, lon, census tract, and more.
+66            Returns None if no valid result.
+67        """
+68
+69        # Check for street num and name at minimum
+70        if address.get("street", "") == "":
+71            raise ValueError("Address must include street number and name at a minimum")
+72
+73        # Configure the lookup with whatever provided address values
+74        # were in the user-given dictionary
+75        formatted_address = self._format_address(address, searchtype="address")
+76        url = self._get_url(formatted_address)
+77        response = self._call_census_api(url)
+78
+79        return self._parse_census_result(response)
+
+ + +

Geocodes the provided address, which is formatted as a dictionary. +using the Census API with searchtype = "address". If a result is found, encodes +as a GeocodeResult object and return, otherwise returns None.

+ +

The given dictionary should conform to standard nomenclature around address +fields, including:

+ +
    +
  • street: the number and street address
    • +
  • street2: additional street level information (if needed)
    • +
  • apartment: apartment or suite number (if needed)
    • +
  • city: city to geocode
    • +
  • state: state to geocode
    • +
  • postal_code: the postal code to use
    • +
  • urbanization: urbanization code for area, sector, or regional
    • +
  • development: (only used for Puerto Rican addresses)
    • +
+ +

Street must be included to use this function; however, a minimum of street, +city, and state are suggested for the best matches.

+ +
Parameters
+ +
    +
  • address: A dictionary with fields outlined above.
    • +
+ +
Raises
+ +
    +
  • ValueError: If address does not include street number and name.
    • +
+ +
Returns
+ +
+

A standardized address enriched with lat, lon, census tract, and more. + Returns None if no valid result.

+
+
+ + +
+
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/harmonization.html b/docs/v1.2.7/sdk/phdi/harmonization.html new file mode 100644 index 0000000000..3ed30d3be0 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/harmonization.html @@ -0,0 +1,3174 @@ + + + + + + + phdi.harmonization API documentation + + + + + + + + + +
+
+

+phdi.harmonization

+ + + + + + + 
 1from phdi.harmonization.double_metaphone import DoubleMetaphone
+ 2from phdi.harmonization.hl7 import convert_hl7_batch_messages_to_list
+ 3from phdi.harmonization.hl7 import default_hl7_value
+ 4from phdi.harmonization.hl7 import normalize_hl7_datetime
+ 5from phdi.harmonization.hl7 import normalize_hl7_datetime_segment
+ 6from phdi.harmonization.hl7 import standardize_hl7_datetimes
+ 7from phdi.harmonization.standardization import double_metaphone_string
+ 8from phdi.harmonization.standardization import standardize_birth_date
+ 9from phdi.harmonization.standardization import standardize_country_code
+10from phdi.harmonization.standardization import standardize_name
+11from phdi.harmonization.standardization import standardize_phone
+12from phdi.harmonization.utils import compare_strings
+13
+14__all__ = (
+15    "standardize_hl7_datetimes",
+16    "normalize_hl7_datetime_segment",
+17    "normalize_hl7_datetime",
+18    "default_hl7_value",
+19    "convert_hl7_batch_messages_to_list",
+20    "standardize_country_code",
+21    "standardize_phone",
+22    "standardize_name",
+23    "double_metaphone_string",
+24    "compare_strings",
+25    "DoubleMetaphone",
+26    "standardize_birth_date",
+27)
+
+ + +
+
+ +
+ + def + standardize_hl7_datetimes(message: str) -> str: + + + +
+ + 
 9def standardize_hl7_datetimes(message: str) -> str:
+10    """
+11    Prepares an HL7 message for conversion by normalizing / sanitizing
+12    fields that are known to contain datetime data in problematic formats. This
+13    function helps messages conform to expectations.
+14
+15    This function accepts either segments terminated by `\\r` or `\\n`, but always
+16    returns data with `\\n` as the segment terminator.
+17
+18    :param message: The raw HL7 message to sanitize.
+19    :return: The HL7 message with potential problem formats resolved. If the function
+20      is unable to parse a date, the original value is retained.
+21    """
+22    parsed_message: hl7.Message = None
+23    try:
+24        # The hl7 module requires \n characters be replaced with \r
+25        parsed_message = hl7.parse(message.replace("\n", "\r"))
+26
+27        # MSH-7 - Message date/time
+28        normalize_hl7_datetime_segment(parsed_message, "MSH", [7])
+29
+30        # PID-7 - Date of Birth
+31        # PID-29 - Date of Death
+32        # PID-33 - Last update date/time
+33        normalize_hl7_datetime_segment(parsed_message, "PID", [7, 29, 33])
+34
+35        # PV1-44 - Admission Date
+36        # PV1-45 - Discharge Date
+37        normalize_hl7_datetime_segment(parsed_message, "PV1", [44, 45])
+38
+39        # ORC-9 Date/time of transaction
+40        # ORC-15 Order effective date/time
+41        # ORC-27 Filler's expected availability date/time
+42        normalize_hl7_datetime_segment(parsed_message, "ORC", [9, 15, 27])
+43
+44        # OBR-7 Observation date/time
+45        # OBR-8 Observation end date/time
+46        # OBR-22 Status change date/time
+47        # OBR-36 Scheduled date/time
+48        normalize_hl7_datetime_segment(parsed_message, "OBR", [7, 8, 22, 36])
+49
+50        # OBX-12 Effective date/time of reference range
+51        # OBX-14 Date/time of observation
+52        # OBX-19 Date/time of analysis
+53        normalize_hl7_datetime_segment(parsed_message, "OBX", [12, 14, 19])
+54
+55        # TQ1-7 Start date/time
+56        # TQ1-8 End date/time
+57        normalize_hl7_datetime_segment(parsed_message, "TQ1", [7, 8])
+58
+59        # SPM-18 Specimen received date/time
+60        # SPM-19 Specimen expiration date/time
+61        normalize_hl7_datetime_segment(parsed_message, "SPM", [18, 19])
+62
+63        # RXA-3 Date/time start of administration
+64        # RXA-4 Date/time end of administration
+65        # RXA-16 Substance expiration date
+66        # RXA-22 System entry date/time
+67        normalize_hl7_datetime_segment(parsed_message, "RXA", [3, 4, 16, 22])
+68
+69    # @TODO: Eliminate logging, raise an exception, document the exception
+70    # in the docstring, and make this fit into our new structure of allowing
+71    # the caller to implement more robust error handling
+72    except Exception:
+73        logging.exception(
+74            "Exception occurred while cleaning message.  "
+75            + "Passing through original message."
+76        )
+77
+78        return message
+79
+80    return str(parsed_message).replace("\r", "\n")
+
+ + +

Prepares an HL7 message for conversion by normalizing / sanitizing +fields that are known to contain datetime data in problematic formats. This +function helps messages conform to expectations.

+ +

This function accepts either segments terminated by \r or \n, but always +returns data with \n as the segment terminator.

+ +
Parameters
+ +
    +
  • message: The raw HL7 message to sanitize.
    • +
+ +
Returns
+ +
+

The HL7 message with potential problem formats resolved. If the function + is unable to parse a date, the original value is retained.

+
+
+ + +
+
+ +
+ + def + normalize_hl7_datetime_segment( message: hl7.containers.Message, segment_id: str, field_list: list) -> None: + + + +
+ + 
200def normalize_hl7_datetime_segment(
+201    message: hl7.Message, segment_id: str, field_list: list
+202) -> None:
+203    """
+204    Applies datetime normalization to multiple fields in a segment,
+205    overwriting values in the input segment as necessary.
+206
+207    :param message: The HL7 message, represented as a list
+208      of indexable component strings (which is how the HL7 library
+209      processes and returns messages).
+210    :param segment_id: The segment type (MSH, PID, etc) of the field to replace.
+211    :param field_num: The field number to replace in the segment named by `segment_id`.
+212    :param field_list: The list of field numbers to replace in the segment named
+213      by `segement_id`.
+214    """
+215    try:
+216        for segment in message.segments(segment_id):
+217            for field_num in field_list:
+218                # Datetime value is always in first component
+219                component_num = 0
+220                if len(segment) > field_num and segment[field_num][component_num] != "":
+221                    cleaned_datetime = normalize_hl7_datetime(segment[field_num][0])
+222                    segment[field_num][0] = cleaned_datetime
+223
+224    # @TODO: Eliminate logging, raise an exception, document the exception
+225    # in the docstring, and make this fit into our new structure of allowing
+226    # the caller to implement more robust error handling
+227    except KeyError:
+228        logging.debug(f"Segment {segment_id} not found in message.")
+
+ + +

Applies datetime normalization to multiple fields in a segment, +overwriting values in the input segment as necessary.

+ +
Parameters
+ +
    +
  • message: The HL7 message, represented as a list +of indexable component strings (which is how the HL7 library +processes and returns messages).
    • +
  • segment_id: The segment type (MSH, PID, etc) of the field to replace.
    • +
  • field_num: The field number to replace in the segment named by segment_id.
    • +
  • field_list: The list of field numbers to replace in the segment named +by segement_id.
    • +
+
+ + +
+
+ +
+ + def + normalize_hl7_datetime(hl7_datetime: str) -> str: + + + +
+ + 
231def normalize_hl7_datetime(hl7_datetime: str) -> str:
+232    """
+233    Splits HL7 datetime-formatted fields into the following parts:
+234    <integer 8+ digits>[.<integer 1+ digits>][+/-<integer 4+ digits>]
+235
+236    Each group of integers is truncated to conform to the HL7
+237    specification:
+238
+239    - first integer group: max 14 digits
+240    - following decimal point: max 4 digits
+241    - following +/- (timezone): 4 digits
+242
+243    This normalization facilitates downstream processing using
+244    cloud providers that have particular requirements for dates.
+245
+246    :param hl7_datetime: The raw datetime string to clean.
+247    :return: The datetime string with normalizing substitutions
+248      performed, or the original HL7 datetime if no matching
+249      format could be found.
+250    """
+251
+252    hl7_datetime_match = re.match(r"(\d{8}\d*)(\.\d+)?([+-]\d+)?", hl7_datetime)
+253
+254    if not hl7_datetime_match:
+255        return hl7_datetime
+256
+257    hl7_datetime_parts = hl7_datetime_match.groups()
+258
+259    # Start with date base
+260    normalized_datetime = hl7_datetime_parts[0][:14]  # First 14 digits
+261
+262    # Add date decimal if present
+263    if hl7_datetime_parts[1]:
+264        normalized_datetime += hl7_datetime_parts[1][:5]  # . plus first 4 digits
+265
+266    # Add timezone information if present
+267    if hl7_datetime_parts[2] and len(hl7_datetime_parts[2]) >= 5:
+268        normalized_datetime += hl7_datetime_parts[2][:5]  # +/- plus 4 digits
+269
+270    return normalized_datetime
+
+ + +

Splits HL7 datetime-formatted fields into the following parts: +[.][+/-]

+ +

Each group of integers is truncated to conform to the HL7 +specification:

+ +
    +
  • first integer group: max 14 digits
    • +
  • following decimal point: max 4 digits
    • +
  • following +/- (timezone): 4 digits
    • +
+ +

This normalization facilitates downstream processing using +cloud providers that have particular requirements for dates.

+ +
Parameters
+ +
    +
  • hl7_datetime: The raw datetime string to clean.
    • +
+ +
Returns
+ +
+

The datetime string with normalizing substitutions + performed, or the original HL7 datetime if no matching + format could be found.

+
+
+ + +
+
+ +
+ + def + default_hl7_value(message: str, segment_id: str, field_num: int, default_value: str): + + + +
+ + 
148def default_hl7_value(
+149    message: str, segment_id: str, field_num: int, default_value: str
+150):
+151    """
+152    Defaults a field value in an HL7 message.
+153
+154    This function accepts either segments terminated by `\\r` or `\\n`, but always
+155    returns data with `\\n` as the segment terminator.
+156
+157    :param message: A string representing the HL7 message used to modify
+158      a value.
+159    :param segment_id: The segment type (MSH, PID, etc) of the field to replace.
+160    :param field_num: The field number to replace in the segment named by `segment_id`.
+161    :param default_value: If the selected field is blank, set the
+162      field's value to this value.
+163    :return: The HL7 message with default value inserted at the
+164      specified segment location, if possible. If not, then the
+165      original message.
+166    """
+167
+168    parsed_message: hl7.Message = None
+169    try:
+170        # The hl7 module requires \n characters be replaced with \r
+171        parsed_message = hl7.parse(message.replace("\n", "\r"))
+172
+173        segment: hl7.Segment = None
+174        try:
+175            segment = parsed_message.segment(segment_id=segment_id)
+176        except KeyError:
+177            # If the segment is not found, there is nothing to do
+178            return message
+179
+180        if (
+181            segment.extract_field(field_num=field_num) is None
+182            or segment.extract_field(field_num=field_num) == ""
+183        ):
+184            segment.assign_field(value=default_value, field_num=field_num)
+185
+186    # @TODO: Eliminate logging, raise an exception, document the exception
+187    # in the docstring, and make this fit into our new structure of allowing
+188    # the caller to implement more robust error handling
+189    except Exception:
+190        logging.exception(
+191            "Exception occurred while cleaning message.  "
+192            + "Passing through original message."
+193        )
+194
+195        return message
+196
+197    return str(parsed_message).replace("\r", "\n")
+
+ + +

Defaults a field value in an HL7 message.

+ +

This function accepts either segments terminated by \r or \n, but always +returns data with \n as the segment terminator.

+ +
Parameters
+ +
    +
  • message: A string representing the HL7 message used to modify +a value.
    • +
  • segment_id: The segment type (MSH, PID, etc) of the field to replace.
    • +
  • field_num: The field number to replace in the segment named by segment_id.
    • +
  • default_value: If the selected field is blank, set the +field's value to this value.
    • +
+ +
Returns
+ +
+

The HL7 message with default value inserted at the + specified segment location, if possible. If not, then the + original message.

+
+
+ + +
+
+ +
+ + def + convert_hl7_batch_messages_to_list(content: str, delimiter: str = '\n') -> List[str]: + + + +
+ + 
 83def convert_hl7_batch_messages_to_list(
+ 84    content: str, delimiter: str = "\n"
+ 85) -> List[str]:
+ 86    """
+ 87    Converts a batch file of messages into a list of strings
+ 88    representing parts of the message. This function is based
+ 89    on the following header/tail segments:
+ 90
+ 91    * FHS is a "File Header Segment," which is used to head a file
+ 92        (group of batches)
+ 93    * FTS is a "File Trailer Segment," which defines the end of a file
+ 94    * BHS is "Batch Header Segment," which defines the start of a batch
+ 95    * BTS is "Batch Trailer Segment," which defines the end of a batch
+ 96
+ 97    The structure of an HL7 Batch looks like this:
+ 98    [FHS] (file header segment) { [BHS] (batch header segment)
+ 99    { [MSH (zero or more HL7 messages)
+100    ....
+101    ....
+102    ....
+103    ] }
+104    [BTS] (batch trailer segment)
+105    }
+106    [FTS] (file trailer segment)
+107
+108    Ignores lines that start with these header/tail segments since we don't want to
+109    include them in a message.
+110
+111    :param content: The batch content to turn into a list.
+112    :param delimiter: The character delimiting messages in the batch.
+113    :return: A list of separated, cleaned HL7 messages.
+114    """
+115
+116    cleaned_batch = _clean_hl7_batch(content)
+117    message_lines = cleaned_batch.split(delimiter)
+118    next_message = ""
+119    output = []
+120
+121    for line in message_lines:
+122        if line.startswith(("FHS", "BHS", "BTS", "FTS")):
+123            continue
+124
+125        # If we reach a line that starts with MSH and we have
+126        # content in nextMessage, then by definition we have
+127        # a full message in next_message and need to append it
+128        # to output. This will not trigger the first time we
+129        # see a line with MSH since next_message will be empty
+130        # at that time.
+131        if next_message != "" and line.startswith("MSH"):
+132            output.append(next_message)
+133            next_message = ""
+134
+135        # Otherwise, continue to add the line of text to next_message
+136        if line != "":
+137            next_message += f"{line}\r"
+138
+139    # Since our loop only adds messages to output when it finds
+140    # a line that starts with MSH, the last message would never
+141    # be added. So we explicitly add it here.
+142    if next_message != "":
+143        output.append(next_message)
+144
+145    return output
+
+ + +

Converts a batch file of messages into a list of strings +representing parts of the message. This function is based +on the following header/tail segments:

+ +
    +
  • FHS is a "File Header Segment," which is used to head a file +(group of batches)
    • +
  • FTS is a "File Trailer Segment," which defines the end of a file
    • +
  • BHS is "Batch Header Segment," which defines the start of a batch
    • +
  • BTS is "Batch Trailer Segment," which defines the end of a batch
    • +
+ +

The structure of an HL7 Batch looks like this: +[FHS] (file header segment) { [BHS] (batch header segment) +{ [MSH (zero or more HL7 messages) +.... +.... +.... +] } +[BTS] (batch trailer segment) +} +[FTS] (file trailer segment)

+ +

Ignores lines that start with these header/tail segments since we don't want to +include them in a message.

+ +
Parameters
+ +
    +
  • content: The batch content to turn into a list.
    • +
  • delimiter: The character delimiting messages in the batch.
    • +
+ +
Returns
+ +
+

A list of separated, cleaned HL7 messages.

+
+
+ + +
+
+ +
+ + def + standardize_country_code( raw_country: str, code_type: Literal['alpha_2', 'alpha_3', 'numeric'] = 'alpha_2') -> str: + + + +
+ + 
39def standardize_country_code(
+40    raw_country: str, code_type: Literal["alpha_2", "alpha_3", "numeric"] = "alpha_2"
+41) -> str:
+42    """
+43    Identifies the country represented and generates the desired type of the ISO
+44    3611 standardized country identifier for a given string representation of a country
+45    (whether a full name such as "United States," or an abbreviation such as "US"
+46    or "USA"). If the country identifier cannot be determined, returns None.
+47
+48    Example: If raw_country = "United States of America," then
+49
+50    * alpha_2 would be "US"
+51    * alpha_3 would be "USA"
+52    * numeric would be "840"
+53
+54    :param raw_country: The string representation of the country to be
+55      put in ISO 3611 standardized form.
+56    :param code_type: One of 'alpha_2', 'alpha_3', or 'numeric'; the
+57      desired identifier type to generate.
+58    :return: The standardized country identifier found in the resource's addresses.
+59    """
+60
+61    # @TODO: Potentially do some minor restructuring around this logic
+62    # to make it shorter/clearer. A private helper was discussed, but
+63    # prevailing consensus was that this logic is a guiding nice-to-have
+64    # here, where it is, so we'll likely keep it. But this todo marks
+65    # a revisit later around whether the logic can be restructuerd.
+66
+67    # First, identify what country the input is referencing
+68    standard = None
+69    raw_country = raw_country.strip().upper()
+70    if len(raw_country) == 2:
+71        standard = pycountry.countries.get(alpha_2=raw_country)
+72    elif len(raw_country) == 3:
+73        standard = pycountry.countries.get(alpha_3=raw_country)
+74        if standard is None:
+75            standard = pycountry.countries.get(numeric=raw_country)
+76    elif len(raw_country) >= 4:
+77        standard = pycountry.countries.get(name=raw_country)
+78        if standard is None:
+79            standard = pycountry.countries.get(official_name=raw_country)
+80
+81    # Then, if we figured that out, convert it to desired form
+82    if standard is not None:
+83        if code_type == "alpha_2":
+84            standard = standard.alpha_2
+85        elif code_type == "alpha_3":
+86            standard = standard.alpha_3
+87        elif code_type == "numeric":
+88            standard = standard.numeric
+89
+90    return standard
+
+ + +

Identifies the country represented and generates the desired type of the ISO +3611 standardized country identifier for a given string representation of a country +(whether a full name such as "United States," or an abbreviation such as "US" +or "USA"). If the country identifier cannot be determined, returns None.

+ +

Example: If raw_country = "United States of America," then

+ +
    +
  • alpha_2 would be "US"
    • +
  • alpha_3 would be "USA"
    • +
  • numeric would be "840"
    • +
+ +
Parameters
+ +
    +
  • raw_country: The string representation of the country to be +put in ISO 3611 standardized form.
    • +
  • code_type: One of 'alpha_2', 'alpha_3', or 'numeric'; the +desired identifier type to generate.
    • +
+ +
Returns
+ +
+

The standardized country identifier found in the resource's addresses.

+
+
+ + +
+
+ +
+ + def + standardize_phone( raw_phone: Union[str, List[str]], countries: List = [None, 'US']) -> Union[str, List[str]]: + + + +
+ + 
 93def standardize_phone(
+ 94    raw_phone: Union[str, List[str]], countries: List = [None, "US"]
+ 95) -> Union[str, List[str]]:
+ 96    """
+ 97    Parses phone number and generates its standardized ISO E.164 international format
+ 98    for each given phone number and optional list of associated countries. If an input
+ 99    phone number can't be parsed, that number returns the empty string. Attempts
+100    to parse the inputs using the first successful strategy out of the following:
+101
+102    1. parses the phone number on its own
+103    2. parses the phone number using the provided list of possible
+104       associated countries
+105    3. parses the phone number using the US as country
+106
+107    :param raw_phone: One or more raw phone number(s) to standardize.
+108    :param countries: An optional list containing 2 letter ISO codes
+109      associated with the phone numbers, signifying to which countries
+110      the phone numbers might belong.
+111    :return: Either a string or a list of strings, depending on the
+112      input of raw_phone, holding the standardized phone number(s).
+113    """
+114
+115    # Base cases: we always want to try the phone # on its own first;
+116    # we also want to try the phone # with the US if all else fails
+117    if None not in countries:
+118        countries.insert(0, None)
+119    if "US" not in countries:
+120        countries.append("US")
+121
+122    phones_to_clean = raw_phone
+123    if isinstance(raw_phone, str):
+124        phones_to_clean = [raw_phone]
+125    outputs = []
+126
+127    for phone in phones_to_clean:
+128        standardized = ""
+129        for country in countries:
+130            # We were able to pull the phone # and corresponding country
+131            try:
+132                standardized = phonenumbers.parse(phone, country)
+133                break
+134
+135            # This combo of given phone # and country isn't valid
+136            except phonenumbers.phonenumberutil.NumberParseException:
+137                continue
+138
+139        # If we got a match, format it according to ISO standards
+140        if standardized != "" and phonenumbers.is_possible_number(standardized):
+141            standardized = str(
+142                phonenumbers.format_number(
+143                    standardized, phonenumbers.PhoneNumberFormat.E164
+144                )
+145            )
+146            outputs.append(standardized)
+147        else:
+148            outputs.append("")
+149
+150    if isinstance(raw_phone, str):
+151        return outputs[0]
+152    return outputs
+
+ + +

Parses phone number and generates its standardized ISO E.164 international format +for each given phone number and optional list of associated countries. If an input +phone number can't be parsed, that number returns the empty string. Attempts +to parse the inputs using the first successful strategy out of the following:

+ +
    +
  1. parses the phone number on its own
    2. +
  2. parses the phone number using the provided list of possible +associated countries
    3. +
  3. parses the phone number using the US as country
    4. +
+ +
Parameters
+ +
    +
  • raw_phone: One or more raw phone number(s) to standardize.
    • +
  • countries: An optional list containing 2 letter ISO codes +associated with the phone numbers, signifying to which countries +the phone numbers might belong.
    • +
+ +
Returns
+ +
+

Either a string or a list of strings, depending on the + input of raw_phone, holding the standardized phone number(s).

+
+
+ + +
+
+ +
+ + def + standardize_name( raw_name: Union[str, List[str]], trim: bool = True, case: Literal['upper', 'lower', 'title'] = 'upper', remove_numbers: bool = True) -> Union[str, List[str]]: + + + +
+ + 
155def standardize_name(
+156    raw_name: Union[str, List[str]],
+157    trim: bool = True,
+158    case: Literal["upper", "lower", "title"] = "upper",
+159    remove_numbers: bool = True,
+160) -> Union[str, List[str]]:
+161    """
+162    Performs basic standardization (described below) on each given name. Removes
+163    punctuation characters and performs a variety of additional cleaning operations.
+164    Other options can be toggled on or off using the relevant parameter.
+165
+166    All options specified will be applied uniformly to each input name,
+167    i.e., specifying case = "lower" will make all given names lower case.
+168
+169    :param raw_name: Either a single string name or a list of strings,
+170      each representing a name.
+171    :param trim: If true, strips leading/trailing whitespace;
+172      if false, retains whitespace. Default: `True`
+173    :param case: What case to enforce on each name.
+174
+175      * `upper`: All upper case
+176      * `lower`: All lower case
+177      * `title`: Title case
+178
+179      Default: `upper`
+180    :remove_numbers: If true, removes numeric characters from inputs;
+181      if false, retains numeric characters. Default `True`
+182    :return: Either a string or a list of strings, depending on the
+183      input of raw_name, holding the cleaned name(s).
+184    """
+185    names_to_clean = raw_name
+186    if isinstance(raw_name, str):
+187        names_to_clean = [raw_name]
+188    outputs = []
+189
+190    for name in names_to_clean:
+191        # Remove all punctuation
+192        cleaned_name = "".join([ltr for ltr in name if ltr.isalnum() or ltr == " "])
+193        if remove_numbers:
+194            cleaned_name = "".join([ltr for ltr in cleaned_name if not ltr.isnumeric()])
+195        if trim:
+196            cleaned_name = cleaned_name.strip()
+197        if case == "upper":
+198            cleaned_name = cleaned_name.upper()
+199        if case == "lower":
+200            cleaned_name = cleaned_name.lower()
+201        if case == "title":
+202            cleaned_name = cleaned_name.title()
+203        outputs.append(cleaned_name)
+204
+205    if isinstance(raw_name, str):
+206        return outputs[0]
+207    return outputs
+
+ + +

Performs basic standardization (described below) on each given name. Removes +punctuation characters and performs a variety of additional cleaning operations. +Other options can be toggled on or off using the relevant parameter.

+ +

All options specified will be applied uniformly to each input name, +i.e., specifying case = "lower" will make all given names lower case.

+ +
Parameters
+ +
    +
  • raw_name: Either a single string name or a list of strings, +each representing a name.
    • +
  • trim: If true, strips leading/trailing whitespace; +if false, retains whitespace. Default: True
    • +

  • case: What case to enforce on each name.

    + +
      +
    • upper: All upper case
      • +
    • lower: All lower case
      • +
    • title: Title case
      • +
    + +

    Default: upper +:remove_numbers: If true, removes numeric characters from inputs; +if false, retains numeric characters. Default True

    • +
+ +
Returns
+ +
+

Either a string or a list of strings, depending on the + input of raw_name, holding the cleaned name(s).

+
+
+ + +
+
+ +
+ + def + double_metaphone_string(string: str, dmeta=None) -> List[Optional[str]]: + + + +
+ + 
19def double_metaphone_string(string: str, dmeta=None) -> List[Union[str, None]]:
+20    """
+21    Performs the double metaphone phonetic encoding algorithm on the given
+22    string. Returns a list holding the primary and secondary phonetic
+23    representations of the string (including None if there is no valid
+24    secondary encoding). This function expects basic text cleaning (e.g.
+25    removal of numeric characters, trimming of spaces, etc.) to already
+26    have been performed.
+27
+28    :param string: The string to phonetically encode.
+29    :param dmeta: An optional existing double metaphone object, in the case
+30      one has already been instantiated for bulk processing.
+31    :return: A list of the primary and secondary encodings of the given
+32      string.
+33    """
+34    if dmeta is None:
+35        dmeta = DoubleMetaphone()
+36    return dmeta(string)
+
+ + +

Performs the double metaphone phonetic encoding algorithm on the given +string. Returns a list holding the primary and secondary phonetic +representations of the string (including None if there is no valid +secondary encoding). This function expects basic text cleaning (e.g. +removal of numeric characters, trimming of spaces, etc.) to already +have been performed.

+ +
Parameters
+ +
    +
  • string: The string to phonetically encode.
    • +
  • dmeta: An optional existing double metaphone object, in the case +one has already been instantiated for bulk processing.
    • +
+ +
Returns
+ +
+

A list of the primary and secondary encodings of the given + string.

+
+
+ + +
+
+ +
+ + def + compare_strings( string1: str, string2: str, similarity_measure: Literal['JaroWinkler', 'Levenshtein', 'DamerauLevenshtein'] = 'JaroWinkler') -> float: + + + +
+ + 
 7def compare_strings(
+ 8    string1: str,
+ 9    string2: str,
+10    similarity_measure: Literal[
+11        "JaroWinkler", "Levenshtein", "DamerauLevenshtein"
+12    ] = "JaroWinkler",
+13) -> float:
+14    """
+15    Returns the normalized similarity measure between string1 and string2, as
+16    determined by the similarlity measure. The higher the normalized similarity measure
+17    (up to 1.0), the more similar string1 and string2 are. A normalized similarity
+18    measure of 0.0 means string1 and string 2 are not at all similar. This function
+19    expects basic text cleaning (e.g. removal of numeric characters, trimming of spaces,
+20    etc.) to already have been performed on the input strings.
+21
+22    :param string1: First string for comparison.
+23    :param string2: Second string for comparison.
+24    :param similarity_measure: The method used to measure the similarity between two
+25        strings, defaults to "JaroWinkler".
+26     - JaroWinkler: a ratio of matching characters and transpositions needed to
+27        transform string1 into string2.
+28     - Levenshtein: the number of edits (excluding transpositions) needed to transform
+29        string1 into string2.
+30     - DamerauLevenshtein: the number of edits (including transpositions) needed to
+31        transform string1 into string2.
+32    :return: The normalized similarity between string1 and string2, with 0 representing
+33        no similarity between string1 and string2, and 1 meaning string1 and string2 are
+34        dentical words.
+35    """
+36    if similarity_measure == "JaroWinkler":
+37        return rapidfuzz.distance.JaroWinkler.normalized_similarity(string1, string2)
+38    elif similarity_measure == "Levenshtein":
+39        return rapidfuzz.distance.Levenshtein.normalized_similarity(string1, string2)
+40    elif similarity_measure == "DamerauLevenshtein":
+41        return rapidfuzz.distance.DamerauLevenshtein.normalized_similarity(
+42            string1, string2
+43        )
+
+ + +

Returns the normalized similarity measure between string1 and string2, as +determined by the similarlity measure. The higher the normalized similarity measure +(up to 1.0), the more similar string1 and string2 are. A normalized similarity +measure of 0.0 means string1 and string 2 are not at all similar. This function +expects basic text cleaning (e.g. removal of numeric characters, trimming of spaces, +etc.) to already have been performed on the input strings.

+ +
Parameters
+ +
    +
  • string1: First string for comparison.
    • +
  • string2: Second string for comparison.
    • +
  • similarity_measure: The method used to measure the similarity between two +strings, defaults to "JaroWinkler".
    • +
  • JaroWinkler: a ratio of matching characters and transpositions needed to +transform string1 into string2.
    • +
  • Levenshtein: the number of edits (excluding transpositions) needed to transform +string1 into string2.
    • +
  • DamerauLevenshtein: the number of edits (including transpositions) needed to +transform string1 into string2.
    • +
+ +
Returns
+ +
+

The normalized similarity between string1 and string2, with 0 representing + no similarity between string1 and string2, and 1 meaning string1 and string2 are + dentical words.

+
+
+ + +
+
+ +
+ + class + DoubleMetaphone: + + + +
+ + 
 23class DoubleMetaphone(object):
+ 24    """
+ 25    A Double Metaphone parsing object capable of performing the double
+ 26    coding algorithm on a given input string.
+ 27    """
+ 28
+ 29    def __init__(self):
+ 30        self.position = 0
+ 31        self.primary_phone = ""
+ 32        self.secondary_phone = ""
+ 33        # next is set to a tuple of the next characters in the primary and
+ 34        # secondary codes and to indicate how many characters to move forward
+ 35        # in the string.  The secondary code letter is given only when it is
+ 36        # different than the primary.
+ 37        self.next = (None, 1)
+ 38
+ 39    def __call__(self, string: str):
+ 40        return self.parse(string)
+ 41
+ 42    def check_word_start(self):
+ 43        # Skip silent letters when they start a word (because they're not
+ 44        # phonetic if they're silent)
+ 45        if self.word.get_letters(0, 2) in SILENT_STARTERS:
+ 46            self.position += 1
+ 47        # Starting with 'X' frequently pronounced 'Z' e.g. 'Xavier'
+ 48        if self.word.get_letters(0) == "X":
+ 49            # 'Z' maps to 'S'
+ 50            self.primary_phone = self.secondary_phone = "S"
+ 51            self.position += 1
+ 52
+ 53    def process_vowel(self):
+ 54        self.next = (None, 1)
+ 55
+ 56        # All starting vowels map to 'A'
+ 57        if self.position == self.word.start_index:
+ 58            self.next = ("A", 1)
+ 59
+ 60    def process_b(self):
+ 61        # "-mb", e.g., "dumb", already accounted for, see 'M'
+ 62        if self.word.buffer[self.position + 1] == "B":
+ 63            self.next = ("P", 2)
+ 64        else:
+ 65            self.next = ("P", 1)
+ 66
+ 67    def process_c(self):
+ 68        buffer = self.word.buffer
+ 69        position = self.position
+ 70        start_index = self.word.start_index
+ 71
+ 72        # Handle some germanic linguistics
+ 73        if (
+ 74            position > start_index + 1
+ 75            and buffer[position - 2] not in VOWELS
+ 76            and buffer[position - 1 : self.position + 2] == "ACH"
+ 77            and buffer[position + 2] not in ["I"]
+ 78            and (
+ 79                buffer[position + 2] not in ["E"]
+ 80                or buffer[position - 2 : position + 4] in ["BACHER", "MACHER"]
+ 81            )
+ 82        ):
+ 83            self.next = ("K", 2)
+ 84
+ 85        # Special case 'CAESAR'
+ 86        elif (
+ 87            position == start_index
+ 88            and buffer[start_index : start_index + 6] == "CAESAR"
+ 89        ):
+ 90            self.next = ("S", 2)
+ 91
+ 92        # Italian 'chianti'
+ 93        elif buffer[position : position + 4] == "CHIA":
+ 94            self.next = ("K", 2)
+ 95        elif buffer[position : position + 2] == "CH":
+ 96            # e.g. 'michael'
+ 97            if position > start_index and buffer[position : position + 4] == "CHAE":
+ 98                self.next = ("K", "X", 2)
+ 99            elif (
+100                position == start_index
+101                and (
+102                    buffer[position + 1 : position + 6] in ["HARAC", "HARIS"]
+103                    or buffer[position + 1 : position + 4]
+104                    in ["HOR", "HYM", "HIA", "HEM"]
+105                )
+106                and buffer[start_index : start_index + 5] != "CHORE"
+107            ):
+108                self.next = ("K", 2)
+109
+110            # Germanic, greek, or other phonetic 'ch' for 'kh' sound
+111            elif (
+112                buffer[start_index : start_index + 4] in ["VAN ", "VON "]
+113                or buffer[start_index : start_index + 3] == "SCH"
+114                or buffer[position - 2 : position + 4] in ["ORCHES", "ARCHIT", "ORCHID"]
+115                or buffer[position + 2] in ["T", "S"]
+116                or (
+117                    (
+118                        buffer[position - 1] in ["A", "O", "U", "E"]
+119                        or position == start_index
+120                    )
+121                    and (
+122                        buffer[position + 2]
+123                        in ["L", "R", "N", "M", "B", "H", "F", "V", "W", " "]
+124                    )
+125                )
+126            ):
+127                self.next = ("K", 2)
+128            else:
+129                if position > start_index:
+130                    if buffer[start_index : start_index + 2] == "MC":
+131                        self.next = ("K", 2)
+132                    else:
+133                        self.next = ("X", "K", 2)
+134                else:
+135                    self.next = ("X", 2)
+136
+137        # e.g, 'czerny'
+138        elif (
+139            buffer[position : position + 2] == "CZ"
+140            and buffer[position - 2 : position + 2] != "WICZ"
+141        ):
+142            self.next = ("S", "X", 2)
+143
+144        # e.g., 'focaccia'
+145        elif buffer[position + 1 : position + 4] == "CIA":
+146            self.next = ("X", 3)
+147
+148        # Double 'C', but not if e.g. 'McClellan'
+149        elif buffer[position : position + 2] == "CC" and not (
+150            position == (start_index + 1) and buffer[start_index] == "M"
+151        ):
+152            # 'bellocchio' but not 'bacchus'
+153            if (
+154                buffer[position + 2] in ["I", "E", "H"]
+155                and buffer[position + 2 : position + 4] != "HU"
+156            ):
+157                # 'accident', 'accede' 'succeed'
+158                if (
+159                    position == (start_index + 1) and buffer[start_index] == "A"
+160                ) or buffer[position - 1 : position + 4] in ["UCCEE", "UCCES"]:
+161                    self.next = ("KS", 3)
+162
+163                # 'bacci', 'bertucci', other italian
+164                else:
+165                    self.next = ("X", 3)
+166            else:
+167                self.next = ("K", 2)
+168
+169        elif buffer[position : position + 2] in ["CK", "CG", "CQ"]:
+170            self.next = ("K", 2)
+171        elif buffer[position : position + 2] in ["CI", "CE", "CY"]:
+172            # Italian vs. English
+173            if buffer[position : position + 3] in ["CIO", "CIE", "CIA"]:
+174                self.next = ("S", "X", 2)
+175            else:
+176                self.next = ("S", 2)
+177        else:
+178            # Name set in 'mac caffrey', 'mac gregor'
+179            if buffer[position + 1 : position + 3] in [" C", " Q", " G"]:
+180                self.next = ("K", 3)
+181            else:
+182                if buffer[position + 1] in ["C", "K", "Q"] and buffer[
+183                    position + 1 : position + 3
+184                ] not in ["CE", "CI"]:
+185                    self.next = ("K", 2)
+186
+187                # Default sound for 'C'
+188                else:
+189                    self.next = ("K", 1)
+190
+191    def process_d(self):
+192        if self.word.buffer[self.position : self.position + 2] == "DG":
+193            # e.g. 'edge'
+194            if self.word.buffer[self.position + 2] in ["I", "E", "Y"]:
+195                self.next = ("J", 3)
+196            else:
+197                self.next = ("TK", 2)
+198        elif self.word.buffer[self.position : self.position + 2] in ["DT", "DD"]:
+199            self.next = ("T", 2)
+200        else:
+201            self.next = ("T", 1)
+202
+203    def process_f(self):
+204        if self.word.buffer[self.position + 1] == "F":
+205            self.next = ("F", 2)
+206        else:
+207            self.next = ("F", 1)
+208
+209    def process_g(self):
+210        buffer = self.word.buffer
+211        position = self.position
+212        start_index = self.word.start_index
+213        if buffer[position + 1] == "H":
+214            if position > start_index and buffer[position - 1] not in VOWELS:
+215                self.next = ("K", 2)
+216            elif position < (start_index + 3):
+217                # 'Ghislane', 'Ghiradelli'
+218                if position == start_index:
+219                    if buffer[position + 2] == "I":
+220                        self.next = ("J", 2)
+221                    else:
+222                        self.next = ("K", 2)
+223
+224            # Parker's rule for e.g., 'Hugh'
+225            elif (
+226                (
+227                    position > (start_index + 1)
+228                    and buffer[position - 2] in ["B", "H", "D"]
+229                )
+230                or (
+231                    position > (start_index + 2)
+232                    and buffer[position - 3] in ["B", "H", "D"]
+233                )
+234                or (position > (start_index + 3) and buffer[position - 4] in ["B", "H"])
+235            ):
+236                self.next = (None, 2)
+237
+238            else:
+239                # e.g., 'laugh', 'McLaughlin', 'cough', 'gough', 'rough', 'tough'
+240                if (
+241                    position > (start_index + 2)
+242                    and buffer[position - 1] == "U"
+243                    and buffer[position - 3] in ["C", "G", "L", "R", "T"]
+244                ):
+245                    self.next = ("F", 2)
+246                else:
+247                    if position > start_index and buffer[position - 1] != "I":
+248                        self.next = ("K", 2)
+249
+250        elif buffer[position + 1] == "N":
+251            if (
+252                position == (start_index + 1)
+253                and buffer[start_index] in VOWELS
+254                and not self.word.is_slavo_germanic
+255            ):
+256                self.next = ("KN", "N", 2)
+257
+258            else:
+259                # Not e.g. 'cagney'
+260                if (
+261                    buffer[position + 2 : position + 4] != "EY"
+262                    and buffer[position + 1] != "Y"
+263                    and not self.word.is_slavo_germanic
+264                ):
+265                    self.next = ("N", "KN", 2)
+266                else:
+267                    self.next = ("KN", 2)
+268
+269        # e.g. 'Tagliaro'
+270        elif (
+271            buffer[position + 1 : position + 3] == "LI"
+272            and not self.word.is_slavo_germanic
+273        ):
+274            self.next = ("KL", "L", 2)
+275
+276        # -ges-,-gep-,-gel-, -gie- at beginning
+277        elif position == start_index and (
+278            buffer[position + 1] == "Y"
+279            or buffer[position + 1 : position + 3]
+280            in ["ES", "EP", "EB", "EL", "EY", "IB", "IL", "IN", "IE", "EI", "ER"]
+281        ):
+282            self.next = ("K", "J", 2)
+283
+284        # -ger-,  -gy-
+285        elif (
+286            (buffer[position + 1 : position + 3] == "ER" or buffer[position + 1] == "Y")
+287            and buffer[start_index : start_index + 6]
+288            not in ["DANGER", "RANGER", "MANGER"]
+289            and buffer[position - 1] not in ["E", "I"]
+290            and buffer[position - 1 : position + 2] not in ["RGY", "OGY"]
+291        ):
+292            self.next = ("K", "J", 2)
+293
+294        # Italian e.g, 'Biaggi'
+295        elif buffer[position + 1] in ["E", "I", "Y"] or buffer[
+296            position - 1 : position + 3
+297        ] in ["AGGI", "OGGI"]:
+298            # Germanic
+299            if (
+300                buffer[start_index : start_index + 4] in ["VON ", "VAN "]
+301                or buffer[start_index : start_index + 3] == "SCH"
+302                or buffer[position + 1 : position + 3] == "ET"
+303            ):
+304                self.next = ("K", 2)
+305
+306            else:
+307                # Always soft if following the French ending
+308                if buffer[position + 1 : position + 5] == "IER ":
+309                    self.next = ("J", 2)
+310                else:
+311                    self.next = ("J", "K", 2)
+312
+313        elif buffer[position + 1] == "G":
+314            self.next = ("K", 2)
+315        else:
+316            self.next = ("K", 1)
+317
+318    def process_h(self):
+319        # Keep if self.word.start_index & before vowel, or between 2 vowels
+320        if (
+321            self.position == self.word.start_index
+322            or self.word.buffer[self.position - 1] in VOWELS
+323        ) and self.word.buffer[self.position + 1] in VOWELS:
+324            self.next = ("H", 2)
+325        else:
+326            self.next = (None, 1)
+327
+328    def process_j(self):
+329        buffer = self.word.buffer
+330        position = self.position
+331        start_index = self.word.start_index
+332
+333        # Spanish, 'Jose', 'Jacinto', etc.
+334        if (
+335            buffer[self.position : self.position + 4] == "JOSE"
+336            or buffer[start_index : start_index + 4] == "SAN "
+337        ):
+338            if (position == start_index and buffer[position + 4] == " ") or buffer[
+339                start_index : start_index + 4
+340            ] == "SAN ":
+341                self.next = ("H",)
+342            else:
+343                self.next = ("J", "H")
+344
+345        # Yankelovich/Jankelowicz
+346        elif (
+347            position == start_index
+348            and buffer[self.position : self.position + 4] != "JOSE"
+349        ):
+350            self.next = ("J", "A")
+351
+352        else:
+353            # Spanish pronunciation of e.g. 'Bajador'
+354            if (
+355                buffer[position - 1] in VOWELS
+356                and not self.word.is_slavo_germanic
+357                and buffer[position + 1] in ["A", "O"]
+358            ):
+359                self.next = ("J", "H")
+360            else:
+361                if position == self.word.end_index:
+362                    self.next = ("J", " ")
+363                else:
+364                    if buffer[position + 1] not in [
+365                        "L",
+366                        "T",
+367                        "K",
+368                        "S",
+369                        "N",
+370                        "M",
+371                        "B",
+372                        "Z",
+373                    ] and buffer[position - 1] not in ["S", "K", "L"]:
+374                        self.next = ("J",)
+375                    else:
+376                        self.next = (None,)
+377
+378        if buffer[position + 1] == "J":
+379            self.next = self.next + (2,)
+380        else:
+381            self.next = self.next + (1,)
+382
+383    def process_k(self):
+384        if self.word.buffer[self.position + 1] == "K":
+385            self.next = ("K", 2)
+386        else:
+387            self.next = ("K", 1)
+388
+389    def process_l(self):
+390        buffer = self.word.buffer
+391        position = self.position
+392        end_index = self.word.end_index
+393
+394        if buffer[position + 1] == "L":
+395            # Spanish e.g. 'cabrillo', 'gallegos'
+396            if (
+397                position == (end_index - 2)
+398                and buffer[position - 1 : position + 3] in ["ILLO", "ILLA", "ALLE"]
+399            ) or (
+400                (
+401                    buffer[end_index - 1 : end_index + 1] in ["AS", "OS"]
+402                    or buffer[end_index] in ["A", "O"]
+403                )
+404                and buffer[position - 1 : position + 3] == "ALLE"
+405            ):
+406                self.next = ("L", "", 2)
+407            else:
+408                self.next = ("L", 2)
+409        else:
+410            self.next = ("L", 1)
+411
+412    def process_m(self):
+413        buffer = self.word.buffer
+414        position = self.position
+415        if (
+416            buffer[position + 1 : position + 4] == "UMB"
+417            and (
+418                position + 1 == self.word.end_index
+419                or buffer[position + 2 : position + 4] == "ER"
+420            )
+421        ) or buffer[position + 1] == "M":
+422            self.next = ("M", 2)
+423        else:
+424            self.next = ("M", 1)
+425
+426    def process_n(self):
+427        if self.word.buffer[self.position + 1] == "N":
+428            self.next = ("N", 2)
+429        else:
+430            self.next = ("N", 1)
+431
+432    def process_p(self):
+433        if self.word.buffer[self.position + 1] == "H":
+434            self.next = ("F", 2)
+435
+436        # Account for "Campbell", "raspberry"
+437        elif self.word.buffer[self.position + 1] in ["P", "B"]:
+438            self.next = ("P", 2)
+439        else:
+440            self.next = ("P", 1)
+441
+442    def process_q(self):
+443        if self.word.buffer[self.position + 1] == "Q":
+444            self.next = ("K", 2)
+445        else:
+446            self.next = ("K", 1)
+447
+448    def process_r(self):
+449        buffer = self.word.buffer
+450        position = self.position
+451        end_index = self.word.end_index
+452
+453        # French e.g. 'Rogier', but exclude e.g. 'Hochmeier'
+454        if (
+455            position == end_index
+456            and not self.word.is_slavo_germanic
+457            and buffer[position - 2 : position] == "IE"
+458            and buffer[position - 4 : position - 2] not in ["ME", "MA"]
+459        ):
+460            self.next = ("", "R")
+461        else:
+462            self.next = ("R",)
+463        if buffer[position + 1] == "R":
+464            self.next = self.next + (2,)
+465        else:
+466            self.next = self.next + (1,)
+467
+468    def process_s(self):
+469        buffer = self.word.buffer
+470        position = self.position
+471        start_index = self.word.start_index
+472        end_index = self.word.end_index
+473
+474        # Special cases like 'Carlisle', 'Carlysle'
+475        if buffer[position - 1 : position + 2] in ["ISL", "YSL"]:
+476            self.next = (None, 1)
+477
+478        # special case 'sugar-'
+479        elif (
+480            position == start_index and buffer[start_index : start_index + 5] == "SUGAR"
+481        ):
+482            self.next = ("X", "S", 1)
+483
+484        elif buffer[position : position + 2] == "SH":
+485            # Germanic
+486            if buffer[position + 1 : position + 5] in ["HEIM", "HOEK", "HOLM", "HOLZ"]:
+487                self.next = ("S", 2)
+488            else:
+489                self.next = ("X", 2)
+490
+491        # Italian & Armenian
+492        elif (
+493            buffer[position : position + 3] in ["SIO", "SIA"]
+494            or buffer[position : position + 4] == "SIAN"
+495        ):
+496            if not self.word.is_slavo_germanic:
+497                self.next = ("S", "X", 3)
+498            else:
+499                self.next = ("S", 3)
+500
+501        # Lots of anglicisations to match here
+502        # Germanic, e.g. 'Smith' == 'Schmidt', 'Snider' == 'Schneider'
+503        # Slavic languages, catch -sz- and the tricky Hungarian
+504        # pronunciation with an 's'
+505        elif (
+506            position == start_index and buffer[position + 1] in ["M", "N", "L", "W"]
+507        ) or buffer[position + 1] == "Z":
+508            self.next = ("S", "X")
+509            if buffer[position + 1] == "Z":
+510                self.next = self.next + (2,)
+511            else:
+512                self.next = self.next + (1,)
+513
+514        elif buffer[position : position + 2] == "SC":
+515            # Schlesinger's rule
+516            if buffer[position + 2] == "H":
+517                # Dutch origin, e.g. 'school', 'schooner'
+518                if buffer[position + 3 : position + 5] in [
+519                    "OO",
+520                    "ER",
+521                    "EN",
+522                    "UY",
+523                    "ED",
+524                    "EM",
+525                ]:
+526                    # 'Schermerhorn', 'Schenker'
+527                    if buffer[position + 3 : position + 5] in ["ER", "EN"]:
+528                        self.next = ("X", "SK", 3)
+529                    else:
+530                        self.next = ("SK", 3)
+531
+532                else:
+533                    if (
+534                        position == start_index
+535                        and buffer[start_index + 3] not in VOWELS
+536                        and buffer[start_index + 3] != "W"
+537                    ):
+538                        self.next = ("X", "S", 3)
+539                    else:
+540                        self.next = ("X", 3)
+541
+542            elif buffer[position + 2] in ["I", "E", "Y"]:
+543                self.next = ("S", 3)
+544            else:
+545                self.next = ("SK", 3)
+546
+547        # French e.g. 'Resnais', 'Artois'
+548        elif position == end_index and buffer[position - 2 : position] in ["AI", "OI"]:
+549            self.next = ("", "S", 1)
+550        else:
+551            self.next = ("S",)
+552            if buffer[position + 1] in ["S", "Z"]:
+553                self.next = self.next + (2,)
+554            else:
+555                self.next = self.next + (1,)
+556
+557    def process_t(self):
+558        buffer = self.word.buffer
+559        position = self.position
+560        start_index = self.word.start_index
+561
+562        if buffer[position : position + 4] == "TION":
+563            self.next = ("X", 3)
+564        elif buffer[position : position + 3] in ["TIA", "TCH"]:
+565            self.next = ("X", 3)
+566        elif (
+567            buffer[position : position + 2] == "TH"
+568            or buffer[position : position + 3] == "TTH"
+569        ):
+570            # 'Thomas', 'Thames' or hard-sound Germanic
+571            if (
+572                buffer[position + 2 : position + 4] in ["OM", "AM"]
+573                or buffer[start_index : start_index + 4] in ["VON ", "VAN "]
+574                or buffer[start_index : start_index + 3] == "SCH"
+575            ):
+576                self.next = ("T", 2)
+577            else:
+578                self.next = ("0", "T", 2)
+579
+580        elif buffer[position + 1] in ["T", "D"]:
+581            self.next = ("T", 2)
+582        else:
+583            self.next = ("T", 1)
+584
+585    def process_v(self):
+586        if self.word.buffer[self.position + 1] == "V":
+587            self.next = ("F", 2)
+588        else:
+589            self.next = ("F", 1)
+590
+591    def process_w(self):
+592        buffer = self.word.buffer
+593        position = self.position
+594        start_index = self.word.start_index
+595
+596        if buffer[position : position + 2] == "WR":
+597            self.next = ("R", 2)
+598        elif position == start_index and (
+599            buffer[position + 1] in VOWELS or buffer[position : position + 2] == "WH"
+600        ):
+601            # Wasserman should match Vasserman
+602            if buffer[position + 1] in VOWELS:
+603                self.next = ("A", "F", 1)
+604            else:
+605                self.next = ("A", 1)
+606
+607        # Arnow should match Arnoff
+608        elif (
+609            (position == self.word.end_index and buffer[position - 1] in VOWELS)
+610            or buffer[position - 1 : position + 4]
+611            in ["EWSKI", "EWSKY", "OWSKI", "OWSKY"]
+612            or buffer[start_index : start_index + 3] == "SCH"
+613        ):
+614            self.next = ("", "F", 1)
+615
+616        # Polish e.g. 'Filipowicz'
+617        elif buffer[position : position + 4] in ["WICZ", "WITZ"]:
+618            self.next = ("TS", "FX", 4)
+619
+620        # By default, 'W' is skipped phonetically
+621        else:
+622            self.next = (None, 1)
+623
+624    def process_x(self):
+625        buffer = self.word.buffer
+626        position = self.position
+627
+628        # French e.g. 'Breaux'
+629        self.next = (None,)
+630        if not (
+631            position == self.word.end_index
+632            and (
+633                buffer[position - 3 : position] in ["IAU", "EAU"]
+634                or buffer[position - 2 : position] in ["AU", "OU"]
+635            )
+636        ):
+637            self.next = ("KS",)
+638
+639        if buffer[position + 1] in ["C", "X"]:
+640            self.next = self.next + (2,)
+641        else:
+642            self.next = self.next + (1,)
+643
+644    def process_z(self):
+645        # Chinese pinyin e.g. 'zhao'
+646        if self.word.buffer[self.position + 1] == "H":
+647            self.next = ("J",)
+648        elif self.word.buffer[self.position + 1 : self.position + 3] in [
+649            "ZO",
+650            "ZI",
+651            "ZA",
+652        ] or (
+653            self.word.is_slavo_germanic
+654            and self.position > self.word.start_index
+655            and self.word.buffer[self.position - 1] != "T"
+656        ):
+657            self.next = ("S", "TS")
+658        else:
+659            self.next = ("S",)
+660        if (
+661            self.word.buffer[self.position + 1] == "Z"
+662            or self.word.buffer[self.position + 1] == "H"
+663        ):
+664            self.next = self.next + (2,)
+665        else:
+666            self.next = self.next + (1,)
+667
+668    def parse(self, input):
+669        self.word = Word(input)
+670        self.position = self.word.start_index
+671        self.primary_phone = ""
+672        self.secondary_phone = ""
+673        self.next = (None, 1)
+674        self.check_word_start()
+675
+676        # Loop through chars in word.buffer
+677        while self.position <= self.word.end_index:
+678            character = self.word.buffer[self.position]
+679
+680            # Vowels and spaces get special handling
+681            if character in VOWELS:
+682                self.process_vowel()
+683            elif character == " ":
+684                self.position += 1
+685                continue
+686
+687            # Other letters each have their own function
+688            elif character == "B":
+689                self.process_b()
+690            elif character == "C":
+691                self.process_c()
+692            elif character == "D":
+693                self.process_d()
+694            elif character == "F":
+695                self.process_f()
+696            elif character == "G":
+697                self.process_g()
+698            elif character == "H":
+699                self.process_h()
+700            elif character == "J":
+701                self.process_j()
+702            elif character == "K":
+703                self.process_k()
+704            elif character == "L":
+705                self.process_l()
+706            elif character == "M":
+707                self.process_m()
+708            elif character == "N":
+709                self.process_n()
+710            elif character == "P":
+711                self.process_p()
+712            elif character == "Q":
+713                self.process_q()
+714            elif character == "R":
+715                self.process_r()
+716            elif character == "S":
+717                self.process_s()
+718            elif character == "T":
+719                self.process_t()
+720            elif character == "V":
+721                self.process_v()
+722            elif character == "W":
+723                self.process_w()
+724            elif character == "X":
+725                self.process_x()
+726            elif character == "Z":
+727                self.process_z()
+728
+729            # Handle any residual unprocessed sound clusters
+730            if len(self.next) == 2:
+731                if self.next[0]:
+732                    self.primary_phone += self.next[0]
+733                    self.secondary_phone += self.next[0]
+734                self.position += self.next[1]
+735            elif len(self.next) == 3:
+736                if self.next[0]:
+737                    self.primary_phone += self.next[0]
+738                if self.next[1]:
+739                    self.secondary_phone += self.next[1]
+740                self.position += self.next[2]
+741
+742        # Standardize all representations to the dominant
+743        # first sound clusters
+744        if len(self.primary_phone) > 4:
+745            self.primary_phone = self.primary_phone[:4]
+746        if len(self.secondary_phone) > 4:
+747            self.secondary_phone = self.secondary_phone[:4]
+748
+749        if self.primary_phone == self.secondary_phone:
+750            self.secondary_phone = ""
+751        return [self.primary_phone, self.secondary_phone]
+
+ + +

A Double Metaphone parsing object capable of performing the double +coding algorithm on a given input string.

+
+ + +
+ +
+ + def + check_word_start(self): + + + +
+ + 
42    def check_word_start(self):
+43        # Skip silent letters when they start a word (because they're not
+44        # phonetic if they're silent)
+45        if self.word.get_letters(0, 2) in SILENT_STARTERS:
+46            self.position += 1
+47        # Starting with 'X' frequently pronounced 'Z' e.g. 'Xavier'
+48        if self.word.get_letters(0) == "X":
+49            # 'Z' maps to 'S'
+50            self.primary_phone = self.secondary_phone = "S"
+51            self.position += 1
+
+ + + + +
+
+ +
+ + def + process_vowel(self): + + + +
+ + 
53    def process_vowel(self):
+54        self.next = (None, 1)
+55
+56        # All starting vowels map to 'A'
+57        if self.position == self.word.start_index:
+58            self.next = ("A", 1)
+
+ + + + +
+
+ +
+ + def + process_b(self): + + + +
+ + 
60    def process_b(self):
+61        # "-mb", e.g., "dumb", already accounted for, see 'M'
+62        if self.word.buffer[self.position + 1] == "B":
+63            self.next = ("P", 2)
+64        else:
+65            self.next = ("P", 1)
+
+ + + + +
+
+ +
+ + def + process_c(self): + + + +
+ + 
 67    def process_c(self):
+ 68        buffer = self.word.buffer
+ 69        position = self.position
+ 70        start_index = self.word.start_index
+ 71
+ 72        # Handle some germanic linguistics
+ 73        if (
+ 74            position > start_index + 1
+ 75            and buffer[position - 2] not in VOWELS
+ 76            and buffer[position - 1 : self.position + 2] == "ACH"
+ 77            and buffer[position + 2] not in ["I"]
+ 78            and (
+ 79                buffer[position + 2] not in ["E"]
+ 80                or buffer[position - 2 : position + 4] in ["BACHER", "MACHER"]
+ 81            )
+ 82        ):
+ 83            self.next = ("K", 2)
+ 84
+ 85        # Special case 'CAESAR'
+ 86        elif (
+ 87            position == start_index
+ 88            and buffer[start_index : start_index + 6] == "CAESAR"
+ 89        ):
+ 90            self.next = ("S", 2)
+ 91
+ 92        # Italian 'chianti'
+ 93        elif buffer[position : position + 4] == "CHIA":
+ 94            self.next = ("K", 2)
+ 95        elif buffer[position : position + 2] == "CH":
+ 96            # e.g. 'michael'
+ 97            if position > start_index and buffer[position : position + 4] == "CHAE":
+ 98                self.next = ("K", "X", 2)
+ 99            elif (
+100                position == start_index
+101                and (
+102                    buffer[position + 1 : position + 6] in ["HARAC", "HARIS"]
+103                    or buffer[position + 1 : position + 4]
+104                    in ["HOR", "HYM", "HIA", "HEM"]
+105                )
+106                and buffer[start_index : start_index + 5] != "CHORE"
+107            ):
+108                self.next = ("K", 2)
+109
+110            # Germanic, greek, or other phonetic 'ch' for 'kh' sound
+111            elif (
+112                buffer[start_index : start_index + 4] in ["VAN ", "VON "]
+113                or buffer[start_index : start_index + 3] == "SCH"
+114                or buffer[position - 2 : position + 4] in ["ORCHES", "ARCHIT", "ORCHID"]
+115                or buffer[position + 2] in ["T", "S"]
+116                or (
+117                    (
+118                        buffer[position - 1] in ["A", "O", "U", "E"]
+119                        or position == start_index
+120                    )
+121                    and (
+122                        buffer[position + 2]
+123                        in ["L", "R", "N", "M", "B", "H", "F", "V", "W", " "]
+124                    )
+125                )
+126            ):
+127                self.next = ("K", 2)
+128            else:
+129                if position > start_index:
+130                    if buffer[start_index : start_index + 2] == "MC":
+131                        self.next = ("K", 2)
+132                    else:
+133                        self.next = ("X", "K", 2)
+134                else:
+135                    self.next = ("X", 2)
+136
+137        # e.g, 'czerny'
+138        elif (
+139            buffer[position : position + 2] == "CZ"
+140            and buffer[position - 2 : position + 2] != "WICZ"
+141        ):
+142            self.next = ("S", "X", 2)
+143
+144        # e.g., 'focaccia'
+145        elif buffer[position + 1 : position + 4] == "CIA":
+146            self.next = ("X", 3)
+147
+148        # Double 'C', but not if e.g. 'McClellan'
+149        elif buffer[position : position + 2] == "CC" and not (
+150            position == (start_index + 1) and buffer[start_index] == "M"
+151        ):
+152            # 'bellocchio' but not 'bacchus'
+153            if (
+154                buffer[position + 2] in ["I", "E", "H"]
+155                and buffer[position + 2 : position + 4] != "HU"
+156            ):
+157                # 'accident', 'accede' 'succeed'
+158                if (
+159                    position == (start_index + 1) and buffer[start_index] == "A"
+160                ) or buffer[position - 1 : position + 4] in ["UCCEE", "UCCES"]:
+161                    self.next = ("KS", 3)
+162
+163                # 'bacci', 'bertucci', other italian
+164                else:
+165                    self.next = ("X", 3)
+166            else:
+167                self.next = ("K", 2)
+168
+169        elif buffer[position : position + 2] in ["CK", "CG", "CQ"]:
+170            self.next = ("K", 2)
+171        elif buffer[position : position + 2] in ["CI", "CE", "CY"]:
+172            # Italian vs. English
+173            if buffer[position : position + 3] in ["CIO", "CIE", "CIA"]:
+174                self.next = ("S", "X", 2)
+175            else:
+176                self.next = ("S", 2)
+177        else:
+178            # Name set in 'mac caffrey', 'mac gregor'
+179            if buffer[position + 1 : position + 3] in [" C", " Q", " G"]:
+180                self.next = ("K", 3)
+181            else:
+182                if buffer[position + 1] in ["C", "K", "Q"] and buffer[
+183                    position + 1 : position + 3
+184                ] not in ["CE", "CI"]:
+185                    self.next = ("K", 2)
+186
+187                # Default sound for 'C'
+188                else:
+189                    self.next = ("K", 1)
+
+ + + + +
+
+ +
+ + def + process_d(self): + + + +
+ + 
191    def process_d(self):
+192        if self.word.buffer[self.position : self.position + 2] == "DG":
+193            # e.g. 'edge'
+194            if self.word.buffer[self.position + 2] in ["I", "E", "Y"]:
+195                self.next = ("J", 3)
+196            else:
+197                self.next = ("TK", 2)
+198        elif self.word.buffer[self.position : self.position + 2] in ["DT", "DD"]:
+199            self.next = ("T", 2)
+200        else:
+201            self.next = ("T", 1)
+
+ + + + +
+
+ +
+ + def + process_f(self): + + + +
+ + 
203    def process_f(self):
+204        if self.word.buffer[self.position + 1] == "F":
+205            self.next = ("F", 2)
+206        else:
+207            self.next = ("F", 1)
+
+ + + + +
+
+ +
+ + def + process_g(self): + + + +
+ + 
209    def process_g(self):
+210        buffer = self.word.buffer
+211        position = self.position
+212        start_index = self.word.start_index
+213        if buffer[position + 1] == "H":
+214            if position > start_index and buffer[position - 1] not in VOWELS:
+215                self.next = ("K", 2)
+216            elif position < (start_index + 3):
+217                # 'Ghislane', 'Ghiradelli'
+218                if position == start_index:
+219                    if buffer[position + 2] == "I":
+220                        self.next = ("J", 2)
+221                    else:
+222                        self.next = ("K", 2)
+223
+224            # Parker's rule for e.g., 'Hugh'
+225            elif (
+226                (
+227                    position > (start_index + 1)
+228                    and buffer[position - 2] in ["B", "H", "D"]
+229                )
+230                or (
+231                    position > (start_index + 2)
+232                    and buffer[position - 3] in ["B", "H", "D"]
+233                )
+234                or (position > (start_index + 3) and buffer[position - 4] in ["B", "H"])
+235            ):
+236                self.next = (None, 2)
+237
+238            else:
+239                # e.g., 'laugh', 'McLaughlin', 'cough', 'gough', 'rough', 'tough'
+240                if (
+241                    position > (start_index + 2)
+242                    and buffer[position - 1] == "U"
+243                    and buffer[position - 3] in ["C", "G", "L", "R", "T"]
+244                ):
+245                    self.next = ("F", 2)
+246                else:
+247                    if position > start_index and buffer[position - 1] != "I":
+248                        self.next = ("K", 2)
+249
+250        elif buffer[position + 1] == "N":
+251            if (
+252                position == (start_index + 1)
+253                and buffer[start_index] in VOWELS
+254                and not self.word.is_slavo_germanic
+255            ):
+256                self.next = ("KN", "N", 2)
+257
+258            else:
+259                # Not e.g. 'cagney'
+260                if (
+261                    buffer[position + 2 : position + 4] != "EY"
+262                    and buffer[position + 1] != "Y"
+263                    and not self.word.is_slavo_germanic
+264                ):
+265                    self.next = ("N", "KN", 2)
+266                else:
+267                    self.next = ("KN", 2)
+268
+269        # e.g. 'Tagliaro'
+270        elif (
+271            buffer[position + 1 : position + 3] == "LI"
+272            and not self.word.is_slavo_germanic
+273        ):
+274            self.next = ("KL", "L", 2)
+275
+276        # -ges-,-gep-,-gel-, -gie- at beginning
+277        elif position == start_index and (
+278            buffer[position + 1] == "Y"
+279            or buffer[position + 1 : position + 3]
+280            in ["ES", "EP", "EB", "EL", "EY", "IB", "IL", "IN", "IE", "EI", "ER"]
+281        ):
+282            self.next = ("K", "J", 2)
+283
+284        # -ger-,  -gy-
+285        elif (
+286            (buffer[position + 1 : position + 3] == "ER" or buffer[position + 1] == "Y")
+287            and buffer[start_index : start_index + 6]
+288            not in ["DANGER", "RANGER", "MANGER"]
+289            and buffer[position - 1] not in ["E", "I"]
+290            and buffer[position - 1 : position + 2] not in ["RGY", "OGY"]
+291        ):
+292            self.next = ("K", "J", 2)
+293
+294        # Italian e.g, 'Biaggi'
+295        elif buffer[position + 1] in ["E", "I", "Y"] or buffer[
+296            position - 1 : position + 3
+297        ] in ["AGGI", "OGGI"]:
+298            # Germanic
+299            if (
+300                buffer[start_index : start_index + 4] in ["VON ", "VAN "]
+301                or buffer[start_index : start_index + 3] == "SCH"
+302                or buffer[position + 1 : position + 3] == "ET"
+303            ):
+304                self.next = ("K", 2)
+305
+306            else:
+307                # Always soft if following the French ending
+308                if buffer[position + 1 : position + 5] == "IER ":
+309                    self.next = ("J", 2)
+310                else:
+311                    self.next = ("J", "K", 2)
+312
+313        elif buffer[position + 1] == "G":
+314            self.next = ("K", 2)
+315        else:
+316            self.next = ("K", 1)
+
+ + + + +
+
+ +
+ + def + process_h(self): + + + +
+ + 
318    def process_h(self):
+319        # Keep if self.word.start_index & before vowel, or between 2 vowels
+320        if (
+321            self.position == self.word.start_index
+322            or self.word.buffer[self.position - 1] in VOWELS
+323        ) and self.word.buffer[self.position + 1] in VOWELS:
+324            self.next = ("H", 2)
+325        else:
+326            self.next = (None, 1)
+
+ + + + +
+
+ +
+ + def + process_j(self): + + + +
+ + 
328    def process_j(self):
+329        buffer = self.word.buffer
+330        position = self.position
+331        start_index = self.word.start_index
+332
+333        # Spanish, 'Jose', 'Jacinto', etc.
+334        if (
+335            buffer[self.position : self.position + 4] == "JOSE"
+336            or buffer[start_index : start_index + 4] == "SAN "
+337        ):
+338            if (position == start_index and buffer[position + 4] == " ") or buffer[
+339                start_index : start_index + 4
+340            ] == "SAN ":
+341                self.next = ("H",)
+342            else:
+343                self.next = ("J", "H")
+344
+345        # Yankelovich/Jankelowicz
+346        elif (
+347            position == start_index
+348            and buffer[self.position : self.position + 4] != "JOSE"
+349        ):
+350            self.next = ("J", "A")
+351
+352        else:
+353            # Spanish pronunciation of e.g. 'Bajador'
+354            if (
+355                buffer[position - 1] in VOWELS
+356                and not self.word.is_slavo_germanic
+357                and buffer[position + 1] in ["A", "O"]
+358            ):
+359                self.next = ("J", "H")
+360            else:
+361                if position == self.word.end_index:
+362                    self.next = ("J", " ")
+363                else:
+364                    if buffer[position + 1] not in [
+365                        "L",
+366                        "T",
+367                        "K",
+368                        "S",
+369                        "N",
+370                        "M",
+371                        "B",
+372                        "Z",
+373                    ] and buffer[position - 1] not in ["S", "K", "L"]:
+374                        self.next = ("J",)
+375                    else:
+376                        self.next = (None,)
+377
+378        if buffer[position + 1] == "J":
+379            self.next = self.next + (2,)
+380        else:
+381            self.next = self.next + (1,)
+
+ + + + +
+
+ +
+ + def + process_k(self): + + + +
+ + 
383    def process_k(self):
+384        if self.word.buffer[self.position + 1] == "K":
+385            self.next = ("K", 2)
+386        else:
+387            self.next = ("K", 1)
+
+ + + + +
+
+ +
+ + def + process_l(self): + + + +
+ + 
389    def process_l(self):
+390        buffer = self.word.buffer
+391        position = self.position
+392        end_index = self.word.end_index
+393
+394        if buffer[position + 1] == "L":
+395            # Spanish e.g. 'cabrillo', 'gallegos'
+396            if (
+397                position == (end_index - 2)
+398                and buffer[position - 1 : position + 3] in ["ILLO", "ILLA", "ALLE"]
+399            ) or (
+400                (
+401                    buffer[end_index - 1 : end_index + 1] in ["AS", "OS"]
+402                    or buffer[end_index] in ["A", "O"]
+403                )
+404                and buffer[position - 1 : position + 3] == "ALLE"
+405            ):
+406                self.next = ("L", "", 2)
+407            else:
+408                self.next = ("L", 2)
+409        else:
+410            self.next = ("L", 1)
+
+ + + + +
+
+ +
+ + def + process_m(self): + + + +
+ + 
412    def process_m(self):
+413        buffer = self.word.buffer
+414        position = self.position
+415        if (
+416            buffer[position + 1 : position + 4] == "UMB"
+417            and (
+418                position + 1 == self.word.end_index
+419                or buffer[position + 2 : position + 4] == "ER"
+420            )
+421        ) or buffer[position + 1] == "M":
+422            self.next = ("M", 2)
+423        else:
+424            self.next = ("M", 1)
+
+ + + + +
+
+ +
+ + def + process_n(self): + + + +
+ + 
426    def process_n(self):
+427        if self.word.buffer[self.position + 1] == "N":
+428            self.next = ("N", 2)
+429        else:
+430            self.next = ("N", 1)
+
+ + + + +
+
+ +
+ + def + process_p(self): + + + +
+ + 
432    def process_p(self):
+433        if self.word.buffer[self.position + 1] == "H":
+434            self.next = ("F", 2)
+435
+436        # Account for "Campbell", "raspberry"
+437        elif self.word.buffer[self.position + 1] in ["P", "B"]:
+438            self.next = ("P", 2)
+439        else:
+440            self.next = ("P", 1)
+
+ + + + +
+
+ +
+ + def + process_q(self): + + + +
+ + 
442    def process_q(self):
+443        if self.word.buffer[self.position + 1] == "Q":
+444            self.next = ("K", 2)
+445        else:
+446            self.next = ("K", 1)
+
+ + + + +
+
+ +
+ + def + process_r(self): + + + +
+ + 
448    def process_r(self):
+449        buffer = self.word.buffer
+450        position = self.position
+451        end_index = self.word.end_index
+452
+453        # French e.g. 'Rogier', but exclude e.g. 'Hochmeier'
+454        if (
+455            position == end_index
+456            and not self.word.is_slavo_germanic
+457            and buffer[position - 2 : position] == "IE"
+458            and buffer[position - 4 : position - 2] not in ["ME", "MA"]
+459        ):
+460            self.next = ("", "R")
+461        else:
+462            self.next = ("R",)
+463        if buffer[position + 1] == "R":
+464            self.next = self.next + (2,)
+465        else:
+466            self.next = self.next + (1,)
+
+ + + + +
+
+ +
+ + def + process_s(self): + + + +
+ + 
468    def process_s(self):
+469        buffer = self.word.buffer
+470        position = self.position
+471        start_index = self.word.start_index
+472        end_index = self.word.end_index
+473
+474        # Special cases like 'Carlisle', 'Carlysle'
+475        if buffer[position - 1 : position + 2] in ["ISL", "YSL"]:
+476            self.next = (None, 1)
+477
+478        # special case 'sugar-'
+479        elif (
+480            position == start_index and buffer[start_index : start_index + 5] == "SUGAR"
+481        ):
+482            self.next = ("X", "S", 1)
+483
+484        elif buffer[position : position + 2] == "SH":
+485            # Germanic
+486            if buffer[position + 1 : position + 5] in ["HEIM", "HOEK", "HOLM", "HOLZ"]:
+487                self.next = ("S", 2)
+488            else:
+489                self.next = ("X", 2)
+490
+491        # Italian & Armenian
+492        elif (
+493            buffer[position : position + 3] in ["SIO", "SIA"]
+494            or buffer[position : position + 4] == "SIAN"
+495        ):
+496            if not self.word.is_slavo_germanic:
+497                self.next = ("S", "X", 3)
+498            else:
+499                self.next = ("S", 3)
+500
+501        # Lots of anglicisations to match here
+502        # Germanic, e.g. 'Smith' == 'Schmidt', 'Snider' == 'Schneider'
+503        # Slavic languages, catch -sz- and the tricky Hungarian
+504        # pronunciation with an 's'
+505        elif (
+506            position == start_index and buffer[position + 1] in ["M", "N", "L", "W"]
+507        ) or buffer[position + 1] == "Z":
+508            self.next = ("S", "X")
+509            if buffer[position + 1] == "Z":
+510                self.next = self.next + (2,)
+511            else:
+512                self.next = self.next + (1,)
+513
+514        elif buffer[position : position + 2] == "SC":
+515            # Schlesinger's rule
+516            if buffer[position + 2] == "H":
+517                # Dutch origin, e.g. 'school', 'schooner'
+518                if buffer[position + 3 : position + 5] in [
+519                    "OO",
+520                    "ER",
+521                    "EN",
+522                    "UY",
+523                    "ED",
+524                    "EM",
+525                ]:
+526                    # 'Schermerhorn', 'Schenker'
+527                    if buffer[position + 3 : position + 5] in ["ER", "EN"]:
+528                        self.next = ("X", "SK", 3)
+529                    else:
+530                        self.next = ("SK", 3)
+531
+532                else:
+533                    if (
+534                        position == start_index
+535                        and buffer[start_index + 3] not in VOWELS
+536                        and buffer[start_index + 3] != "W"
+537                    ):
+538                        self.next = ("X", "S", 3)
+539                    else:
+540                        self.next = ("X", 3)
+541
+542            elif buffer[position + 2] in ["I", "E", "Y"]:
+543                self.next = ("S", 3)
+544            else:
+545                self.next = ("SK", 3)
+546
+547        # French e.g. 'Resnais', 'Artois'
+548        elif position == end_index and buffer[position - 2 : position] in ["AI", "OI"]:
+549            self.next = ("", "S", 1)
+550        else:
+551            self.next = ("S",)
+552            if buffer[position + 1] in ["S", "Z"]:
+553                self.next = self.next + (2,)
+554            else:
+555                self.next = self.next + (1,)
+
+ + + + +
+
+ +
+ + def + process_t(self): + + + +
+ + 
557    def process_t(self):
+558        buffer = self.word.buffer
+559        position = self.position
+560        start_index = self.word.start_index
+561
+562        if buffer[position : position + 4] == "TION":
+563            self.next = ("X", 3)
+564        elif buffer[position : position + 3] in ["TIA", "TCH"]:
+565            self.next = ("X", 3)
+566        elif (
+567            buffer[position : position + 2] == "TH"
+568            or buffer[position : position + 3] == "TTH"
+569        ):
+570            # 'Thomas', 'Thames' or hard-sound Germanic
+571            if (
+572                buffer[position + 2 : position + 4] in ["OM", "AM"]
+573                or buffer[start_index : start_index + 4] in ["VON ", "VAN "]
+574                or buffer[start_index : start_index + 3] == "SCH"
+575            ):
+576                self.next = ("T", 2)
+577            else:
+578                self.next = ("0", "T", 2)
+579
+580        elif buffer[position + 1] in ["T", "D"]:
+581            self.next = ("T", 2)
+582        else:
+583            self.next = ("T", 1)
+
+ + + + +
+
+ +
+ + def + process_v(self): + + + +
+ + 
585    def process_v(self):
+586        if self.word.buffer[self.position + 1] == "V":
+587            self.next = ("F", 2)
+588        else:
+589            self.next = ("F", 1)
+
+ + + + +
+
+ +
+ + def + process_w(self): + + + +
+ + 
591    def process_w(self):
+592        buffer = self.word.buffer
+593        position = self.position
+594        start_index = self.word.start_index
+595
+596        if buffer[position : position + 2] == "WR":
+597            self.next = ("R", 2)
+598        elif position == start_index and (
+599            buffer[position + 1] in VOWELS or buffer[position : position + 2] == "WH"
+600        ):
+601            # Wasserman should match Vasserman
+602            if buffer[position + 1] in VOWELS:
+603                self.next = ("A", "F", 1)
+604            else:
+605                self.next = ("A", 1)
+606
+607        # Arnow should match Arnoff
+608        elif (
+609            (position == self.word.end_index and buffer[position - 1] in VOWELS)
+610            or buffer[position - 1 : position + 4]
+611            in ["EWSKI", "EWSKY", "OWSKI", "OWSKY"]
+612            or buffer[start_index : start_index + 3] == "SCH"
+613        ):
+614            self.next = ("", "F", 1)
+615
+616        # Polish e.g. 'Filipowicz'
+617        elif buffer[position : position + 4] in ["WICZ", "WITZ"]:
+618            self.next = ("TS", "FX", 4)
+619
+620        # By default, 'W' is skipped phonetically
+621        else:
+622            self.next = (None, 1)
+
+ + + + +
+
+ +
+ + def + process_x(self): + + + +
+ + 
624    def process_x(self):
+625        buffer = self.word.buffer
+626        position = self.position
+627
+628        # French e.g. 'Breaux'
+629        self.next = (None,)
+630        if not (
+631            position == self.word.end_index
+632            and (
+633                buffer[position - 3 : position] in ["IAU", "EAU"]
+634                or buffer[position - 2 : position] in ["AU", "OU"]
+635            )
+636        ):
+637            self.next = ("KS",)
+638
+639        if buffer[position + 1] in ["C", "X"]:
+640            self.next = self.next + (2,)
+641        else:
+642            self.next = self.next + (1,)
+
+ + + + +
+
+ +
+ + def + process_z(self): + + + +
+ + 
644    def process_z(self):
+645        # Chinese pinyin e.g. 'zhao'
+646        if self.word.buffer[self.position + 1] == "H":
+647            self.next = ("J",)
+648        elif self.word.buffer[self.position + 1 : self.position + 3] in [
+649            "ZO",
+650            "ZI",
+651            "ZA",
+652        ] or (
+653            self.word.is_slavo_germanic
+654            and self.position > self.word.start_index
+655            and self.word.buffer[self.position - 1] != "T"
+656        ):
+657            self.next = ("S", "TS")
+658        else:
+659            self.next = ("S",)
+660        if (
+661            self.word.buffer[self.position + 1] == "Z"
+662            or self.word.buffer[self.position + 1] == "H"
+663        ):
+664            self.next = self.next + (2,)
+665        else:
+666            self.next = self.next + (1,)
+
+ + + + +
+
+ +
+ + def + parse(self, input): + + + +
+ + 
668    def parse(self, input):
+669        self.word = Word(input)
+670        self.position = self.word.start_index
+671        self.primary_phone = ""
+672        self.secondary_phone = ""
+673        self.next = (None, 1)
+674        self.check_word_start()
+675
+676        # Loop through chars in word.buffer
+677        while self.position <= self.word.end_index:
+678            character = self.word.buffer[self.position]
+679
+680            # Vowels and spaces get special handling
+681            if character in VOWELS:
+682                self.process_vowel()
+683            elif character == " ":
+684                self.position += 1
+685                continue
+686
+687            # Other letters each have their own function
+688            elif character == "B":
+689                self.process_b()
+690            elif character == "C":
+691                self.process_c()
+692            elif character == "D":
+693                self.process_d()
+694            elif character == "F":
+695                self.process_f()
+696            elif character == "G":
+697                self.process_g()
+698            elif character == "H":
+699                self.process_h()
+700            elif character == "J":
+701                self.process_j()
+702            elif character == "K":
+703                self.process_k()
+704            elif character == "L":
+705                self.process_l()
+706            elif character == "M":
+707                self.process_m()
+708            elif character == "N":
+709                self.process_n()
+710            elif character == "P":
+711                self.process_p()
+712            elif character == "Q":
+713                self.process_q()
+714            elif character == "R":
+715                self.process_r()
+716            elif character == "S":
+717                self.process_s()
+718            elif character == "T":
+719                self.process_t()
+720            elif character == "V":
+721                self.process_v()
+722            elif character == "W":
+723                self.process_w()
+724            elif character == "X":
+725                self.process_x()
+726            elif character == "Z":
+727                self.process_z()
+728
+729            # Handle any residual unprocessed sound clusters
+730            if len(self.next) == 2:
+731                if self.next[0]:
+732                    self.primary_phone += self.next[0]
+733                    self.secondary_phone += self.next[0]
+734                self.position += self.next[1]
+735            elif len(self.next) == 3:
+736                if self.next[0]:
+737                    self.primary_phone += self.next[0]
+738                if self.next[1]:
+739                    self.secondary_phone += self.next[1]
+740                self.position += self.next[2]
+741
+742        # Standardize all representations to the dominant
+743        # first sound clusters
+744        if len(self.primary_phone) > 4:
+745            self.primary_phone = self.primary_phone[:4]
+746        if len(self.secondary_phone) > 4:
+747            self.secondary_phone = self.secondary_phone[:4]
+748
+749        if self.primary_phone == self.secondary_phone:
+750            self.secondary_phone = ""
+751        return [self.primary_phone, self.secondary_phone]
+
+ + + + +
+
+
+ +
+ + def + standardize_birth_date(raw_dob: str, existing_format: str = '%Y-%m-%d') -> str: + + + +
+ + 
296def standardize_birth_date(
+297    raw_dob: str, existing_format: str = FHIR_DATE_FORMAT
+298) -> str:
+299    """
+300    Validates and standardizes a date of birth string into YYYY-MM-DD format.
+301
+302    :param raw_dob: One date of birth (dob) to standardize.
+303    :param existing_format: A python DateTime format used to parse the date of
+304        birth within the Patient resource.  Default: `%Y-%m-%d` (YYYY-MM-DD).
+305    :return: Date of birth as a string in YYYY-MM-DD format
+306        or None if date of birth is invalid.
+307    """
+308
+309    #  Need to make sure dob is not None or null ("")
+310    #  or detect() will end up in an infinite loop
+311    if raw_dob is None or len(raw_dob) == 0:
+312        raise ValueError("Date of Birth must be supplied!")
+313
+314    standardized_dob = _standardize_date(
+315        raw_date=raw_dob, date_format=existing_format, future=True
+316    )
+317
+318    return standardized_dob
+
+ + +

Validates and standardizes a date of birth string into YYYY-MM-DD format.

+ +
Parameters
+ +
    +
  • raw_dob: One date of birth (dob) to standardize.
    • +
  • existing_format: A python DateTime format used to parse the date of +birth within the Patient resource. Default: %Y-%m-%d (YYYY-MM-DD).
    • +
+ +
Returns
+ +
+

Date of birth as a string in YYYY-MM-DD format + or None if date of birth is invalid.

+
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/linkage.html b/docs/v1.2.7/sdk/phdi/linkage.html new file mode 100644 index 0000000000..b5740b5daa --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/linkage.html @@ -0,0 +1,3915 @@ + + + + + + + phdi.linkage API documentation + + + + + + + + + +
+
+

+phdi.linkage

+ + + + + + + 
 1from phdi.linkage.algorithms import DIBBS_BASIC
+ 2from phdi.linkage.algorithms import DIBBS_ENHANCED
+ 3from phdi.linkage.core import BaseMPIConnectorClient
+ 4from phdi.linkage.link import add_person_resource
+ 5from phdi.linkage.link import aggregate_given_names_for_linkage
+ 6from phdi.linkage.link import block_data
+ 7from phdi.linkage.link import calculate_log_odds
+ 8from phdi.linkage.link import calculate_m_probs
+ 9from phdi.linkage.link import calculate_u_probs
+10from phdi.linkage.link import compile_match_lists
+11from phdi.linkage.link import eval_log_odds_cutoff
+12from phdi.linkage.link import eval_perfect_match
+13from phdi.linkage.link import extract_blocking_values_from_record
+14from phdi.linkage.link import feature_match_exact
+15from phdi.linkage.link import feature_match_four_char
+16from phdi.linkage.link import feature_match_fuzzy_string
+17from phdi.linkage.link import feature_match_log_odds_exact
+18from phdi.linkage.link import feature_match_log_odds_fuzzy_compare
+19from phdi.linkage.link import generate_hash_str
+20from phdi.linkage.link import link_record_against_mpi
+21from phdi.linkage.link import load_json_probs
+22from phdi.linkage.link import match_within_block
+23from phdi.linkage.link import perform_linkage_pass
+24from phdi.linkage.link import profile_log_odds
+25from phdi.linkage.link import read_linkage_config
+26from phdi.linkage.link import score_linkage_vs_truth
+27from phdi.linkage.link import write_linkage_config
+28from phdi.linkage.mpi import DIBBsMPIConnectorClient
+29from phdi.linkage.seed import convert_to_patient_fhir_resources
+30from phdi.linkage.utils import datetime_to_str
+31
+32
+33__all__ = [
+34    "DIBBS_BASIC",
+35    "DIBBS_ENHANCED",
+36    "generate_hash_str",
+37    "block_data",
+38    "match_within_block",
+39    "feature_match_exact",
+40    "feature_match_fuzzy_string",
+41    "eval_perfect_match",
+42    "compile_match_lists",
+43    "feature_match_four_char",
+44    "perform_linkage_pass",
+45    "score_linkage_vs_truth",
+46    "calculate_m_probs",
+47    "calculate_u_probs",
+48    "load_json_probs",
+49    "calculate_log_odds",
+50    "feature_match_log_odds_exact",
+51    "feature_match_log_odds_fuzzy_compare",
+52    "profile_log_odds",
+53    "eval_log_odds_cutoff",
+54    "BaseMPIConnectorClient",
+55    "extract_blocking_values_from_record",
+56    "write_linkage_config",
+57    "read_linkage_config",
+58    "link_record_against_mpi",
+59    "add_person_resource",
+60    "_compare_address_elements",
+61    "_compare_name_elements",
+62    "convert_to_patient_fhir_resources",
+63    "DIBBsMPIConnectorClient",
+64    "datetime_to_str",
+65    "aggregate_given_names_for_linkage",
+66]
+
+ + +
+
+
+ DIBBS_BASIC = + + [{'funcs': {'first_name': 'feature_match_fuzzy_string', 'last_name': 'feature_match_fuzzy_string', 'birthdate': 'feature_match_fuzzy_string'}, 'blocks': [{'value': 'mrn', 'transformation': 'last4'}, {'value': 'address', 'transformation': 'first4'}], 'matching_rule': 'eval_perfect_match', 'cluster_ratio': 0.9}, {'funcs': {'address': 'feature_match_fuzzy_string', 'city': 'feature_match_fuzzy_string'}, 'blocks': [{'value': 'first_name', 'transformation': 'first4'}, {'value': 'last_name', 'transformation': 'first4'}], 'matching_rule': 'eval_perfect_match', 'cluster_ratio': 0.9}] + + +
+ + + + +
+
+
+ DIBBS_ENHANCED = + + [{'funcs': {'birthdate': 'feature_match_log_odds_fuzzy_compare', 'first_name': 'feature_match_log_odds_fuzzy_compare', 'last_name': 'feature_match_log_odds_fuzzy_compare'}, 'blocks': [{'value': 'mrn', 'transformation': 'last4'}, {'value': 'address', 'transformation': 'first4'}], 'matching_rule': 'eval_log_odds_cutoff', 'cluster_ratio': 0.9, 'kwargs': {'similarity_measure': 'JaroWinkler', 'threshold': 0.7, 'true_match_threshold': 16.5, 'log_odds': {'birthdate': 9.944142836217619, 'first_name': 8.009121400325398, 'last_name': 5.327681398982514, 'sex': 0.6964525713514773, 'address': 5.769942276960749, 'city': 1.8002552875091014, 'state': 0.0, 'zip': 4.909466232098861, 'mrn': 1.464232660081324}}}, {'funcs': {'address': 'feature_match_log_odds_fuzzy_compare', 'city': 'feature_match_log_odds_fuzzy_compare'}, 'blocks': [{'value': 'first_name', 'transformation': 'first4'}, {'value': 'last_name', 'transformation': 'first4'}], 'matching_rule': 'eval_log_odds_cutoff', 'cluster_ratio': 0.9, 'kwargs': {'similarity_measure': 'JaroWinkler', 'threshold': 0.7, 'true_match_threshold': 7.0, 'log_odds': {'birthdate': 9.944142836217619, 'first_name': 8.009121400325398, 'last_name': 5.327681398982514, 'sex': 0.6964525713514773, 'address': 5.769942276960749, 'city': 1.8002552875091014, 'state': 0.0, 'zip': 4.909466232098861, 'mrn': 1.464232660081324}}}] + + +
+ + + + +
+
+ +
+ + def + generate_hash_str(linking_identifier: str, salt_str: str) -> str: + + + +
+ + 
529def generate_hash_str(linking_identifier: str, salt_str: str) -> str:
+530    """
+531    Generates a hash for a given string of concatenated patient information. The hash
+532    serves as a "unique" identifier for the patient.
+533
+534    :param linking_identifier: The value to be hashed.  For example, the concatenation
+535      of a patient's name, address, and date of birth, delimited by dashes.
+536    :param salt_str: The salt to use with the hash. This is intended to prevent
+537      reverse engineering of the PII used to create the hash.
+538    :return: The hash of the linking_identifier string.
+539    """
+540    hash_obj = hashlib.sha256()
+541    to_encode = (linking_identifier + salt_str).encode("utf-8")
+542    hash_obj.update(to_encode)
+543    return hash_obj.hexdigest()
+
+ + +

Generates a hash for a given string of concatenated patient information. The hash +serves as a "unique" identifier for the patient.

+ +
Parameters
+ +
    +
  • linking_identifier: The value to be hashed. For example, the concatenation +of a patient's name, address, and date of birth, delimited by dashes.
    • +
  • salt_str: The salt to use with the hash. This is intended to prevent +reverse engineering of the PII used to create the hash.
    • +
+ +
Returns
+ +
+

The hash of the linking_identifier string.

+
+
+ + +
+
+ +
+ + def + block_data(data: pandas.core.frame.DataFrame, blocks: List) -> dict: + + + +
+ + 
38def block_data(data: pd.DataFrame, blocks: List) -> dict:
+39    """
+40    Generates dictionary of blocked data where each key is a block
+41    and each value is a distinct list of lists containing the data
+42    for a given block.
+43
+44    :param data: A pandas dataframe of records to be linked.
+45    :param blocks: List of columns to be used in blocks.
+46    :return: A dictionary of with the keys as the blocks and the
+47      values as the data within each block, stored as a list of
+48      lists.
+49    """
+50    blocked_data_tuples = tuple(data.groupby(blocks))
+51
+52    # Convert data to list of lists within dict
+53    blocked_data = dict()
+54    for block, df in blocked_data_tuples:
+55        blocked_data[block] = df.values.tolist()
+56
+57    return blocked_data
+
+ + +

Generates dictionary of blocked data where each key is a block +and each value is a distinct list of lists containing the data +for a given block.

+ +
Parameters
+ +
    +
  • data: A pandas dataframe of records to be linked.
    • +
  • blocks: List of columns to be used in blocks.
    • +
+ +
Returns
+ +
+

A dictionary of with the keys as the blocks and the + values as the data within each block, stored as a list of + lists.

+
+
+ + +
+
+ +
+ + def + match_within_block( block: List[List], feature_funcs: dict[str, typing.Callable], col_to_idx: dict[str, int], match_eval: Callable, **kwargs) -> List[tuple]: + + + +
+ + 
738def match_within_block(
+739    block: List[List],
+740    feature_funcs: dict[str, Callable],
+741    col_to_idx: dict[str, int],
+742    match_eval: Callable,
+743    **kwargs,
+744) -> List[tuple]:
+745    """
+746    Performs matching on all candidate pairs of records within a given block
+747    of data. Actual partitioning of the data should be done outside this
+748    function, as it compares all possible pairs within the provided partition.
+749    Uses a given construction of feature comparison rules as well as a
+750    match evaluation rule to determine the final verdict on whether two
+751    records are indeed a match.
+752
+753    A feature function is of the form "feature_match_X" for some condition
+754    X; it must accept two records (lists of data), an index i in which the
+755    feature to compare is stored, and the parameter **kwargs. It must return
+756    a boolean indicating whether the features "match" for whatever definition
+757    of match the function uses (i.e. this allows modular logic to apply to
+758    different features in the compared records). Note that not all features
+759    in a record need a comparison function defined.
+760
+761    A match evaluation rule is a function of the form "eval_X" for some
+762    condition X. It accepts as input a list of booleans, one for each feature
+763    that was compared with feature funcs, and determines whether the
+764    comparisons constitute a match according to X.
+765
+766    :param block: A list of records to check for matches. Each record in
+767      the list is itself a list of features. The first feature of the
+768      record must be an "id" for the record.
+769    :param feature_funcs: A dictionary mapping feature indices to functions
+770      used to evaluate those features for a match.
+771    :param col_to_idx: A dictionary mapping column names to the numeric index
+772      in which they occur in order in the data.
+773    :param match_eval: A function for determining whether a given set of
+774      feature comparisons constitutes a match for linkage.
+775    :return: A list of 2-tuples of the form (i,j), where i,j give the indices
+776      in the block of data of records deemed to match.
+777    """
+778    match_pairs = []
+779
+780    # Dynamic programming table: order doesn't matter, so only need to
+781    # check each combo of i,j once
+782    for i, record_i in enumerate(block):
+783        for j in range(i + 1, len(block)):
+784            record_j = block[j]
+785            feature_comps = [
+786                feature_funcs[feature_col](
+787                    record_i, record_j, feature_col, col_to_idx, **kwargs
+788                )
+789                for feature_col in feature_funcs
+790            ]
+791
+792            # If it's a match, store the result
+793            is_match = match_eval(feature_comps, **kwargs)
+794            if is_match:
+795                match_pairs.append((i, j))
+796
+797    return match_pairs
+
+ + +

Performs matching on all candidate pairs of records within a given block +of data. Actual partitioning of the data should be done outside this +function, as it compares all possible pairs within the provided partition. +Uses a given construction of feature comparison rules as well as a +match evaluation rule to determine the final verdict on whether two +records are indeed a match.

+ +

A feature function is of the form "feature_match_X" for some condition +X; it must accept two records (lists of data), an index i in which the +feature to compare is stored, and the parameter **kwargs. It must return +a boolean indicating whether the features "match" for whatever definition +of match the function uses (i.e. this allows modular logic to apply to +different features in the compared records). Note that not all features +in a record need a comparison function defined.

+ +

A match evaluation rule is a function of the form "eval_X" for some +condition X. It accepts as input a list of booleans, one for each feature +that was compared with feature funcs, and determines whether the +comparisons constitute a match according to X.

+ +
Parameters
+ +
    +
  • block: A list of records to check for matches. Each record in +the list is itself a list of features. The first feature of the +record must be an "id" for the record.
    • +
  • feature_funcs: A dictionary mapping feature indices to functions +used to evaluate those features for a match.
    • +
  • col_to_idx: A dictionary mapping column names to the numeric index +in which they occur in order in the data.
    • +
  • match_eval: A function for determining whether a given set of +feature comparisons constitutes a match for linkage.
    • +
+ +
Returns
+ +
+

A list of 2-tuples of the form (i,j), where i,j give the indices + in the block of data of records deemed to match.

+
+
+ + +
+
+ +
+ + def + feature_match_exact( record_i: List, record_j: List, feature_col: str, col_to_idx: dict[str, int], **kwargs: dict) -> bool: + + + +
+ + 
364def feature_match_exact(
+365    record_i: List,
+366    record_j: List,
+367    feature_col: str,
+368    col_to_idx: dict[str, int],
+369    **kwargs: dict,
+370) -> bool:
+371    """
+372    Determines whether a single feature in a given pair of records
+373    constitutes an exact match (perfect equality).
+374
+375    :param record_i: One of the records in the candidate pair to evaluate.
+376    :param record_j: The second record in the candidate pair.
+377    :param feature_col: The name of the column being evaluated (e.g. "city").
+378    :param col_to_idx: A dictionary mapping column names to the numeric index
+379      in which they occur in order in the data.
+380    :return: A boolean indicating whether the features are an exact match.
+381    """
+382    idx = col_to_idx[feature_col]
+383    return record_i[idx] == record_j[idx]
+
+ + +

Determines whether a single feature in a given pair of records +constitutes an exact match (perfect equality).

+ +
Parameters
+ +
    +
  • record_i: One of the records in the candidate pair to evaluate.
    • +
  • record_j: The second record in the candidate pair.
    • +
  • feature_col: The name of the column being evaluated (e.g. "city").
    • +
  • col_to_idx: A dictionary mapping column names to the numeric index +in which they occur in order in the data.
    • +
+ +
Returns
+ +
+

A boolean indicating whether the features are an exact match.

+
+
+ + +
+
+ +
+ + def + feature_match_fuzzy_string( record_i: List, record_j: List, feature_col: str, col_to_idx: dict[str, int], **kwargs: dict) -> bool: + + + +
+ + 
410def feature_match_fuzzy_string(
+411    record_i: List,
+412    record_j: List,
+413    feature_col: str,
+414    col_to_idx: dict[str, int],
+415    **kwargs: dict,
+416) -> bool:
+417    """
+418    Determines whether two strings in a given pair of records are close
+419    enough to constitute a partial match. The exact nature of the match
+420    is determined by the specified string comparison function (see
+421    harmonization/utils/compare_strings for more details) as well as a
+422    scoring threshold the comparison must meet or exceed.
+423
+424    :param record_i: One of the records in the candidate pair to evaluate.
+425    :param record_j: The second record in the candidate pair.
+426    :param feature_col: The name of the column being evaluated (e.g. "city").
+427    :param col_to_idx: A dictionary mapping column names to the numeric index
+428      in which they occur in order in the data.
+429    :param **kwargs: Optionally, a dictionary including specifications for
+430      the string comparison metric to use, as well as the cutoff score
+431      beyond which to classify the strings as a partial match.
+432    :return: A boolean indicating whether the features are a fuzzy match.
+433    """
+434    idx = col_to_idx[feature_col]
+435
+436    # Convert datetime obj to str using helper function
+437    if feature_col == "birthdate":
+438        record_i[idx] = datetime_to_str(record_i[idx])
+439        record_j[idx] = datetime_to_str(record_j[idx])
+440
+441    # Special case for two empty strings, since we don't want vacuous
+442    # equality (or in-) to penalize the score
+443    if record_i[idx] == "" and record_j[idx] == "":
+444        return True
+445    if record_i[idx] is None and record_j[idx] is None:
+446        return True
+447
+448    similarity_measure = "JaroWinkler"
+449    if "similarity_measure" in kwargs:
+450        similarity_measure = kwargs["similarity_measure"]
+451    threshold = 0.7
+452    if "threshold" in kwargs:
+453        threshold = kwargs["threshold"]
+454    score = compare_strings(record_i[idx], record_j[idx], similarity_measure)
+455    return score >= threshold
+
+ + +

Determines whether two strings in a given pair of records are close +enough to constitute a partial match. The exact nature of the match +is determined by the specified string comparison function (see +harmonization/utils/compare_strings for more details) as well as a +scoring threshold the comparison must meet or exceed.

+ +
Parameters
+ +
    +
  • record_i: One of the records in the candidate pair to evaluate.
    • +
  • record_j: The second record in the candidate pair.
    • +
  • feature_col: The name of the column being evaluated (e.g. "city").
    • +
  • col_to_idx: A dictionary mapping column names to the numeric index +in which they occur in order in the data.
    • +
  • **kwargs: Optionally, a dictionary including specifications for +the string comparison metric to use, as well as the cutoff score +beyond which to classify the strings as a partial match.
    • +
+ +
Returns
+ +
+

A boolean indicating whether the features are a fuzzy match.

+
+
+ + +
+
+ +
+ + def + eval_perfect_match(feature_comparisons: List, **kwargs) -> bool: + + + +
+ + 
245def eval_perfect_match(feature_comparisons: List, **kwargs) -> bool:
+246    """
+247    Determines whether a given set of feature comparisons represent a
+248    'perfect' match (i.e. whether all features that were compared match
+249    in whatever criteria was specified for them).
+250
+251    :param feature_comparisons: A list of 1s and 0s, one for each feature
+252      that was compared during the match algorithm.
+253    :return: The evaluation of whether the given features all match.
+254    """
+255    return sum(feature_comparisons) == len(feature_comparisons)
+
+ + +

Determines whether a given set of feature comparisons represent a +'perfect' match (i.e. whether all features that were compared match +in whatever criteria was specified for them).

+ +
Parameters
+ +
    +
  • feature_comparisons: A list of 1s and 0s, one for each feature +that was compared during the match algorithm.
    • +
+ +
Returns
+ +
+

The evaluation of whether the given features all match.

+
+
+ + +
+
+ +
+ + def + compile_match_lists(match_lists: List[dict], cluster_mode: bool = False): + + + +
+ + 
207def compile_match_lists(match_lists: List[dict], cluster_mode: bool = False):
+208    """
+209    Turns a list of matches of either clusters or candidate pairs found
+210    during linkage into a single unified structure holding all found matches
+211    across all rules passes. E.g. if a single pass of a linkage algorithm
+212    uses three rules, hence generates three dictionaries of matches, this
+213    function will aggregate the results of those three separate dicts into
+214    a single unified and deduplicated dictionary. For consistency during
+215    statistical evaluation, the returned dictionary is always indexed by
+216    the lower ID of the records in a given pair.
+217
+218    :param match_lists: A list of the dictionaries obtained during a run
+219      of the linkage algorithm, one dictionary per rule used in the run.
+220    :param cluster_mode: An optional boolean indicating whether the linkage
+221      algorithm was run in cluster mode. Default is False.
+222    :return: The aggregated dictionary of unified matches.
+223    """
+224    matches = {}
+225    for matches_from_rule in match_lists:
+226        for matches_within_blocks in matches_from_rule.values():
+227            for candidate_set in matches_within_blocks:
+228                # Always index the aggregate by the lowest valued ID
+229                # for statistical consistency and deduplication
+230                root_record = min(candidate_set)
+231                if root_record not in matches:
+232                    matches[root_record] = set()
+233
+234                # For clustering, need to add all other records in the cluster
+235                if cluster_mode:
+236                    for clustered_record in candidate_set:
+237                        if clustered_record != root_record:
+238                            matches[root_record].add(clustered_record)
+239                else:
+240                    matched_record = max(candidate_set)
+241                    matches[root_record].add(matched_record)
+242    return matches
+
+ + +

Turns a list of matches of either clusters or candidate pairs found +during linkage into a single unified structure holding all found matches +across all rules passes. E.g. if a single pass of a linkage algorithm +uses three rules, hence generates three dictionaries of matches, this +function will aggregate the results of those three separate dicts into +a single unified and deduplicated dictionary. For consistency during +statistical evaluation, the returned dictionary is always indexed by +the lower ID of the records in a given pair.

+ +
Parameters
+ +
    +
  • match_lists: A list of the dictionaries obtained during a run +of the linkage algorithm, one dictionary per rule used in the run.
    • +
  • cluster_mode: An optional boolean indicating whether the linkage +algorithm was run in cluster mode. Default is False.
    • +
+ +
Returns
+ +
+

The aggregated dictionary of unified matches.

+
+
+ + +
+
+ +
+ + def + feature_match_four_char( record_i: List, record_j: List, feature_col: str, col_to_idx: dict[str, int], **kwargs: dict) -> bool: + + + +
+ + 
386def feature_match_four_char(
+387    record_i: List,
+388    record_j: List,
+389    feature_col: str,
+390    col_to_idx: dict[str, int],
+391    **kwargs: dict,
+392) -> bool:
+393    """
+394    Determines whether a string feature in a pair of records exactly matches
+395    on the first four characters.
+396
+397    :param record_i: One of the records in the candidate pair to evaluate.
+398    :param record_j: The second record in the candidate pair.
+399    :param feature_col: The name of the column being evaluated (e.g. "city").
+400    :param col_to_idx: A dictionary mapping column names to the numeric index
+401      in which they occur in order in the data.
+402    :return: A boolean indicating whether the features are a match.
+403    """
+404    idx = col_to_idx[feature_col]
+405    first_four_i = record_i[idx][: min(4, len(record_i[idx]))]
+406    first_four_j = record_j[idx][: min(4, len(record_j[idx]))]
+407    return first_four_i == first_four_j
+
+ + +

Determines whether a string feature in a pair of records exactly matches +on the first four characters.

+ +
Parameters
+ +
    +
  • record_i: One of the records in the candidate pair to evaluate.
    • +
  • record_j: The second record in the candidate pair.
    • +
  • feature_col: The name of the column being evaluated (e.g. "city").
    • +
  • col_to_idx: A dictionary mapping column names to the numeric index +in which they occur in order in the data.
    • +
+ +
Returns
+ +
+

A boolean indicating whether the features are a match.

+
+
+ + +
+
+ +
+ + def + perform_linkage_pass( data: pandas.core.frame.DataFrame, blocks: List, feature_funcs: dict[str, typing.Callable], matching_rule: Callable, cluster_ratio: Optional[float] = None, **kwargs) -> dict: + + + +
+ + 
804def perform_linkage_pass(
+805    data: pd.DataFrame,
+806    blocks: List,
+807    feature_funcs: dict[str, Callable],
+808    matching_rule: Callable,
+809    cluster_ratio: Union[float, None] = None,
+810    **kwargs,
+811) -> dict:
+812    """
+813    Performs a partial run of a linkage algorithm using a single rule.
+814    Each rule in an algorithm is associated with its own pass through the
+815    data.
+816
+817    :param data: Currently, a pandas dataframe of records to link. When we
+818      move out of testing, this should become a LoL.
+819    :param blocks: A list of column headers to use as blocking assignments
+820      by which to partition the data.
+821    :param feature_funcs: A dictionary mapping feature indices to functions
+822      used to evaluate those features for a match.
+823    :param matching_rule: A function for determining whether a given set of
+824      feature comparisons constitutes a match for linkage.
+825    :param cluster_ratio: An optional parameter indicating, if using the
+826      algorithm in cluster mode, the required membership percentage a record
+827      must score with an existing cluster in order to join.
+828    :return: A dictionary mapping each block found in the pass to the matches
+829      discovered within that block.
+830    """
+831    # Retrieve indices of columns
+832    cols = list(data.columns.values)
+833    col_to_idx = dict(zip(cols, range(len(cols))))
+834
+835    blocked_data = block_data(data, blocks)
+836    matches = {}
+837    for block in blocked_data:
+838        if cluster_ratio:
+839            matches_in_block = _match_within_block_cluster_ratio(
+840                blocked_data[block],
+841                cluster_ratio,
+842                feature_funcs,
+843                col_to_idx,
+844                matching_rule,
+845                **kwargs,
+846            )
+847        else:
+848            matches_in_block = match_within_block(
+849                blocked_data[block], feature_funcs, col_to_idx, matching_rule, **kwargs
+850            )
+851        matches_in_block = _map_matches_to_record_ids(
+852            matches_in_block, blocked_data[block], cluster_ratio is not None
+853        )
+854        matches[block] = matches_in_block
+855    return matches
+
+ + +

Performs a partial run of a linkage algorithm using a single rule. +Each rule in an algorithm is associated with its own pass through the +data.

+ +
Parameters
+ +
    +
  • data: Currently, a pandas dataframe of records to link. When we +move out of testing, this should become a LoL.
    • +
  • blocks: A list of column headers to use as blocking assignments +by which to partition the data.
    • +
  • feature_funcs: A dictionary mapping feature indices to functions +used to evaluate those features for a match.
    • +
  • matching_rule: A function for determining whether a given set of +feature comparisons constitutes a match for linkage.
    • +
  • cluster_ratio: An optional parameter indicating, if using the +algorithm in cluster mode, the required membership percentage a record +must score with an existing cluster in order to join.
    • +
+ +
Returns
+ +
+

A dictionary mapping each block found in the pass to the matches + discovered within that block.

+
+
+ + +
+
+ +
+ + def + score_linkage_vs_truth( found_matches: dict[typing.Union[int, str], set], true_matches: dict[typing.Union[int, str], set], records_in_dataset: int, expand_clusters_pairwise: bool = False) -> tuple: + + + +
+ + 
 995def score_linkage_vs_truth(
+ 996    found_matches: dict[Union[int, str], set],
+ 997    true_matches: dict[Union[int, str], set],
+ 998    records_in_dataset: int,
+ 999    expand_clusters_pairwise: bool = False,
+1000) -> tuple:
+1001    """
+1002    Compute the statistical qualities of a run of record linkage against
+1003    known true results. This function assumes that matches have already
+1004    been determined by the algorithm, and further assumes that true
+1005    matches have already been identified in the data.
+1006
+1007    :param found_matches: A dictionary mapping IDs of records to sets of
+1008      other records which were determined to be a match.
+1009    :param true_matches: A dictionary mapping IDs of records to sets of
+1010      other records which are _known_ to be a true match.
+1011    :param records_in_dataset: The number of records in the original data
+1012      set to-link.
+1013    :param expand_clusters_pairwise: Optionally, whether we need to take
+1014      the cross-product of members within the sets of the match list. This
+1015      parameter only needs to be used if the linkage algorithm was run in
+1016      cluster mode. Default is False.
+1017    :return: A tuple reporting the sensitivity/precision, specificity/recall,
+1018      positive prediction value, and F1 score of the linkage algorithm.
+1019    """
+1020
+1021    # If cluster mode was used, only the "master" patient's set will exist
+1022    # Need to expand other permutations for accurate statistics
+1023    if expand_clusters_pairwise:
+1024        new_found_matches = {}
+1025        for root_rec in found_matches:
+1026            if root_rec not in new_found_matches:
+1027                new_found_matches[root_rec] = found_matches[root_rec]
+1028            for paired_record in found_matches[root_rec]:
+1029                if paired_record not in new_found_matches:
+1030                    new_found_matches[paired_record] = set()
+1031                for other_record in found_matches[root_rec]:
+1032                    if other_record > paired_record:
+1033                        new_found_matches[paired_record].add(other_record)
+1034        found_matches = new_found_matches
+1035
+1036    # Need division by 2 because ordering is irrelevant, matches are symmetric
+1037    total_possible_matches = (records_in_dataset * (records_in_dataset - 1)) / 2.0
+1038    true_positives = 0.0
+1039    false_positives = 0.0
+1040    false_negatives = 0.0
+1041
+1042    for root_record in true_matches:
+1043        if root_record in found_matches:
+1044            true_positives += len(
+1045                true_matches[root_record].intersection(found_matches[root_record])
+1046            )
+1047            false_positives += len(
+1048                found_matches[root_record].difference(true_matches[root_record])
+1049            )
+1050            false_negatives += len(
+1051                true_matches[root_record].difference(found_matches[root_record])
+1052            )
+1053        else:
+1054            false_negatives += len(true_matches[root_record])
+1055    for record in set(set(found_matches.keys()).difference(true_matches.keys())):
+1056        false_positives += len(found_matches[record])
+1057
+1058    true_negatives = (
+1059        total_possible_matches - true_positives - false_positives - false_negatives
+1060    )
+1061
+1062    print("True Positives:", true_positives)
+1063    print("False Positives:", false_positives)
+1064    print("False Negatives:", false_negatives)
+1065
+1066    sensitivity = round(true_positives / (true_positives + false_negatives), 3)
+1067    specificity = round(true_negatives / (true_negatives + false_positives), 3)
+1068    ppv = round(true_positives / (true_positives + false_positives), 3)
+1069    f1 = round(
+1070        (2 * true_positives) / (2 * true_positives + false_negatives + false_positives),
+1071        3,
+1072    )
+1073    return (sensitivity, specificity, ppv, f1)
+
+ + +

Compute the statistical qualities of a run of record linkage against +known true results. This function assumes that matches have already +been determined by the algorithm, and further assumes that true +matches have already been identified in the data.

+ +
Parameters
+ +
    +
  • found_matches: A dictionary mapping IDs of records to sets of +other records which were determined to be a match.
    • +
  • true_matches: A dictionary mapping IDs of records to sets of +other records which are _known_ to be a true match.
    • +
  • records_in_dataset: The number of records in the original data +set to-link.
    • +
  • expand_clusters_pairwise: Optionally, whether we need to take +the cross-product of members within the sets of the match list. This +parameter only needs to be used if the linkage algorithm was run in +cluster mode. Default is False.
    • +
+ +
Returns
+ +
+

A tuple reporting the sensitivity/precision, specificity/recall, + positive prediction value, and F1 score of the linkage algorithm.

+
+
+ + +
+
+ +
+ + def + calculate_m_probs( data: pandas.core.frame.DataFrame, true_matches: dict, cols: Optional[List[str]] = None, file_to_write: Optional[pathlib.Path] = None): + + + +
+ + 
 93def calculate_m_probs(
+ 94    data: pd.DataFrame,
+ 95    true_matches: dict,
+ 96    cols: Union[List[str], None] = None,
+ 97    file_to_write: Union[pathlib.Path, None] = None,
+ 98):
+ 99    """
+100    For a given set of patient records, calculate the per-field
+101    m-probability. The m-probability for field X is defined as the
+102    probability that a pair of records A and B have the same value in
+103    X, given that A and B are a true matching pair. This function
+104    incorporates LaPlacian Smoothing to account for unseen data and
+105    to resolve future logarithms against 0.
+106
+107    :param data: A pandas dataframe of patient records to compute
+108      probabilities for.
+109    :param true_matches: A dictionary holding the IDs of record pairs
+110      that are true matches in the data set. The format of the dictionary
+111      should be such that the IDs of the "lower numbered" records in each
+112      match pair are the keys, and the values are sets of the "higher
+113      numbered" records in each pair.
+114    :param cols: Optionally, a list of columns to compute probabilities
+115      for. If not supplied, computes probabilities across all fields.
+116      Default is None.
+117    :param file_to_write: Optionally, a destination filepath at which to
+118      write the probabilities in JSON format. Default is None.
+119    """
+120    if cols is None:
+121        cols = data.columns
+122    m_probs = {c: 1.0 for c in cols}
+123    total_pairs = 1.0
+124    for root_record, paired_records in true_matches.items():
+125        total_pairs += len(paired_records)
+126        for pr in paired_records:
+127            for c in cols:
+128                if data[c].iloc[root_record] == data[c].iloc[pr]:
+129                    m_probs[c] += 1
+130    for c in cols:
+131        m_probs[c] /= total_pairs
+132
+133    _write_prob_file(m_probs, file_to_write)
+134    return m_probs
+
+ + +

For a given set of patient records, calculate the per-field +m-probability. The m-probability for field X is defined as the +probability that a pair of records A and B have the same value in +X, given that A and B are a true matching pair. This function +incorporates LaPlacian Smoothing to account for unseen data and +to resolve future logarithms against 0.

+ +
Parameters
+ +
    +
  • data: A pandas dataframe of patient records to compute +probabilities for.
    • +
  • true_matches: A dictionary holding the IDs of record pairs +that are true matches in the data set. The format of the dictionary +should be such that the IDs of the "lower numbered" records in each +match pair are the keys, and the values are sets of the "higher +numbered" records in each pair.
    • +
  • cols: Optionally, a list of columns to compute probabilities +for. If not supplied, computes probabilities across all fields. +Default is None.
    • +
  • file_to_write: Optionally, a destination filepath at which to +write the probabilities in JSON format. Default is None.
    • +
+
+ + +
+
+ +
+ + def + calculate_u_probs( data: pandas.core.frame.DataFrame, true_matches: dict, n_samples: Optional[int] = None, cols: Optional[List] = None, file_to_write: Optional[pathlib.Path] = None): + + + +
+ + 
141def calculate_u_probs(
+142    data: pd.DataFrame,
+143    true_matches: dict,
+144    n_samples: Union[int, None] = None,
+145    cols: Union[List, None] = None,
+146    file_to_write: Union[pathlib.Path, None] = None,
+147):
+148    """
+149    For a given set of patient records, calculate the per-field
+150    u-probability. The u-probability for field X is defined as the
+151    probability that a pair of records A and B have the same value in
+152    X, given that A and B are not a true matching pair. This function
+153    incorporates LaPlacian Smoothing to account for unseen data and
+154    to handle future logarithms against 0.
+155
+156    Note: This function can be slow to compute for large data sets.
+157    It is recommended to pass only a representative subsample of the
+158    data to the function (we recommend sampling ~25k candidate pairs
+159    from a sub-sample of ~25k records), even if the sample operation
+160    is used.
+161
+162    :param data: A pandas dataframe of patient records to compute
+163      probabilities for.
+164    :param true_matches: A dictionary holding the IDs of record pairs
+165      that are true matches in the data set. The format of the dictionary
+166      should be such that the IDs of the "lower numbered" records in each
+167      match pair are the keys, and the values are sets of the "higher
+168      numbered" records in each pair.
+169    :param n_samples: Optionally, a number of samples to take from the
+170      list of possible pairs to compute probabilities over.
+171    :param cols: Optionally, a list of columns to compute probabilities
+172      for. If not supplied, computes probabilities across all fields.
+173      Default is None.
+174    :param file_to_write: Optionally, a destination filepath at which to
+175      write the probabilities in JSON format. Default is None.
+176    """
+177    if cols is None:
+178        cols = data.columns
+179
+180    u_probs = {c: 1.0 for c in cols}
+181
+182    # Want only the pairs of candidates that aren't true matches
+183    base_pairs = list(combinations(data.index, 2))
+184    neg_pairs = [
+185        x
+186        for x in base_pairs
+187        if x[0] not in true_matches or x[1] not in true_matches[x[0]]
+188    ]
+189
+190    if n_samples is not None and n_samples < len(neg_pairs):
+191        neg_pairs = sample(neg_pairs, n_samples)
+192    for index in neg_pairs:
+193        for c in cols:
+194            if data[c].iloc[index[0]] == data[c].iloc[index[1]]:
+195                u_probs[c] += 1.0
+196
+197    for c in cols:
+198        if n_samples is not None and n_samples < len(neg_pairs):
+199            u_probs[c] = u_probs[c] / (n_samples + 1.0)
+200        else:
+201            u_probs[c] = u_probs[c] / (len(neg_pairs) + 1.0)
+202
+203    _write_prob_file(u_probs, file_to_write)
+204    return u_probs
+
+ + +

For a given set of patient records, calculate the per-field +u-probability. The u-probability for field X is defined as the +probability that a pair of records A and B have the same value in +X, given that A and B are not a true matching pair. This function +incorporates LaPlacian Smoothing to account for unseen data and +to handle future logarithms against 0.

+ +

Note: This function can be slow to compute for large data sets. +It is recommended to pass only a representative subsample of the +data to the function (we recommend sampling ~25k candidate pairs +from a sub-sample of ~25k records), even if the sample operation +is used.

+ +
Parameters
+ +
    +
  • data: A pandas dataframe of patient records to compute +probabilities for.
    • +
  • true_matches: A dictionary holding the IDs of record pairs +that are true matches in the data set. The format of the dictionary +should be such that the IDs of the "lower numbered" records in each +match pair are the keys, and the values are sets of the "higher +numbered" records in each pair.
    • +
  • n_samples: Optionally, a number of samples to take from the +list of possible pairs to compute probabilities over.
    • +
  • cols: Optionally, a list of columns to compute probabilities +for. If not supplied, computes probabilities across all fields. +Default is None.
    • +
  • file_to_write: Optionally, a destination filepath at which to +write the probabilities in JSON format. Default is None.
    • +
+
+ + +
+
+ +
+ + def + load_json_probs(path: pathlib.Path): + + + +
+ + 
712def load_json_probs(path: pathlib.Path):
+713    """
+714    Load a dictionary of probabilities from a JSON-formatted file.
+715    The probabilities correspond to previously computed m-, u-, or
+716    log-odds probabilities derived from patient records, with one
+717    score for each field (column) appearing in the data.
+718
+719    :param path: The file path to load the data from.
+720    :return: A dictionary of probability scores, one for each field
+721      in the data set on which they were computed.
+722    :raises FileNotFoundError: If a file does not exist at the given
+723      path.
+724    :raises JSONDecodeError: If the file cannot be read as valid JSON.
+725    """
+726    try:
+727        with open(path, "r") as file:
+728            prob_dict = json.load(file)
+729        return prob_dict
+730    except FileNotFoundError:
+731        raise FileNotFoundError(f"The specified file does not exist at {path}.")
+732    except json.decoder.JSONDecodeError as e:
+733        raise json.decoder.JSONDecodeError(
+734            "The specified file is not valid JSON.", e.doc, e.pos
+735        )
+
+ + +

Load a dictionary of probabilities from a JSON-formatted file. +The probabilities correspond to previously computed m-, u-, or +log-odds probabilities derived from patient records, with one +score for each field (column) appearing in the data.

+ +
Parameters
+ +
    +
  • path: The file path to load the data from.
    • +
+ +
Returns
+ +
+

A dictionary of probability scores, one for each field + in the data set on which they were computed.

+
+ +
Raises
+ +
    +
  • FileNotFoundError: If a file does not exist at the given +path.
    • +
  • JSONDecodeError: If the file cannot be read as valid JSON.
    • +
+
+ + +
+
+ +
+ + def + calculate_log_odds( m_probs: dict, u_probs: dict, file_to_write: Optional[pathlib.Path] = None): + + + +
+ + 
60def calculate_log_odds(
+61    m_probs: dict,
+62    u_probs: dict,
+63    file_to_write: Union[pathlib.Path, None] = None,
+64):
+65    """
+66    Calculate the per-field log odds ratio score that two records will
+67    match in a given field. Measures the likelihood that two records
+68    match on a column due to being a true match as opposed to random
+69    chance.
+70
+71    :param m_probs: A dictionary of m-probabilities computed per field.
+72    :param u_probs: A dictionary of u_probabilities computed per field.
+73    :param file_to_write: Optionally, a destination filepath at which
+74      to write the probabilities in JSON format. Default is None.
+75    :raises ValueError: If the supplied m- and u- probability dictionaries
+76      do not share an equal key set.
+77    """
+78    if m_probs.keys() != u_probs.keys():
+79        raise ValueError(
+80            "m- and u- probability dictionaries must contain the same set of keys"
+81        )
+82    log_odds = {}
+83    for k in m_probs:
+84        log_odds[k] = log(m_probs[k]) - log(u_probs[k])
+85    _write_prob_file(log_odds, file_to_write)
+86    return log_odds
+
+ + +

Calculate the per-field log odds ratio score that two records will +match in a given field. Measures the likelihood that two records +match on a column due to being a true match as opposed to random +chance.

+ +
Parameters
+ +
    +
  • m_probs: A dictionary of m-probabilities computed per field.
    • +
  • u_probs: A dictionary of u_probabilities computed per field.
    • +
  • file_to_write: Optionally, a destination filepath at which +to write the probabilities in JSON format. Default is None.
    • +
+ +
Raises
+ +
    +
  • ValueError: If the supplied m- and u- probability dictionaries +do not share an equal key set.
    • +
+
+ + +
+
+ +
+ + def + feature_match_log_odds_exact( record_i: List, record_j: List, feature_col: str, col_to_idx: dict[str, int], **kwargs: dict) -> float: + + + +
+ + 
458def feature_match_log_odds_exact(
+459    record_i: List,
+460    record_j: List,
+461    feature_col: str,
+462    col_to_idx: dict[str, int],
+463    **kwargs: dict,
+464) -> float:
+465    """
+466    Determines whether two feature values in two records should earn the full
+467    log-odds similarity score (i.e. they match exactly) or whether they
+468    should earn no weight (they differ). Used for fields for which fuzzy
+469    comparisons are inappropriate, such as sex.
+470
+471    :param record_i: One of the records in the candidate pair to evaluate.
+472    :param record_j: The second record in the candidate pair.
+473    :param feature_col: The name of the column being evaluated (e.g. "city").
+474    :param col_to_idx: A dictionary mapping column names to the numeric index
+475      in which they occur in order in the data.
+476    :return: A float of the score the feature comparison earned.
+477    """
+478    if "log_odds" not in kwargs:
+479        raise KeyError("Mapping of columns to m/u log-odds must be provided.")
+480    col_odds = kwargs["log_odds"][feature_col]
+481    idx = col_to_idx[feature_col]
+482    if record_i[idx] == record_j[idx]:
+483        return col_odds
+484    else:
+485        return 0.0
+
+ + +

Determines whether two feature values in two records should earn the full +log-odds similarity score (i.e. they match exactly) or whether they +should earn no weight (they differ). Used for fields for which fuzzy +comparisons are inappropriate, such as sex.

+ +
Parameters
+ +
    +
  • record_i: One of the records in the candidate pair to evaluate.
    • +
  • record_j: The second record in the candidate pair.
    • +
  • feature_col: The name of the column being evaluated (e.g. "city").
    • +
  • col_to_idx: A dictionary mapping column names to the numeric index +in which they occur in order in the data.
    • +
+ +
Returns
+ +
+

A float of the score the feature comparison earned.

+
+
+ + +
+
+ +
+ + def + feature_match_log_odds_fuzzy_compare( record_i: List, record_j: List, feature_col: str, col_to_idx: dict[str, int], **kwargs: dict) -> float: + + + +
+ + 
488def feature_match_log_odds_fuzzy_compare(
+489    record_i: List,
+490    record_j: List,
+491    feature_col: str,
+492    col_to_idx: dict[str, int],
+493    **kwargs: dict,
+494) -> float:
+495    """
+496    Determines the weighted string-odds similarly score earned by two
+497    feature values in two records, as a function of the pre-computed
+498    log-odds weights and the string similarity between the two features.
+499    This scales the full score that would be earned from a perfect
+500    match to a degree of partial weight appropriate to how similar the
+501    two strings are.
+502
+503    :param record_i: One of the records in the candidate pair to evaluate.
+504    :param record_j: The second record in the candidate pair.
+505    :param feature_col: The name of the column being evaluated (e.g. "city").
+506    :param col_to_idx: A dictionary mapping column names to the numeric index
+507      in which they occur in order in the data.
+508    :return: A float of the score the feature comparison earned.
+509    """
+510    if "log_odds" not in kwargs:
+511        raise KeyError("Mapping of columns to m/u log-odds must be provided.")
+512    threshold = 0.7
+513    if "threshold" in kwargs:
+514        threshold = kwargs["threshold"]
+515    col_odds = kwargs["log_odds"][feature_col]
+516    idx = col_to_idx[feature_col]
+517
+518    # Convert datetime obj to str using helper function
+519    if feature_col == "birthdate":
+520        record_i[idx] = datetime_to_str(record_i[idx])
+521        record_j[idx] = datetime_to_str(record_j[idx])
+522
+523    score = compare_strings(record_i[idx], record_j[idx], "JaroWinkler")
+524    if score < threshold:
+525        score = 0.0
+526    return score * col_odds
+
+ + +

Determines the weighted string-odds similarly score earned by two +feature values in two records, as a function of the pre-computed +log-odds weights and the string similarity between the two features. +This scales the full score that would be earned from a perfect +match to a degree of partial weight appropriate to how similar the +two strings are.

+ +
Parameters
+ +
    +
  • record_i: One of the records in the candidate pair to evaluate.
    • +
  • record_j: The second record in the candidate pair.
    • +
  • feature_col: The name of the column being evaluated (e.g. "city").
    • +
  • col_to_idx: A dictionary mapping column names to the numeric index +in which they occur in order in the data.
    • +
+ +
Returns
+ +
+

A float of the score the feature comparison earned.

+
+
+ + +
+
+ +
+ + def + profile_log_odds( data: pandas.core.frame.DataFrame, true_matches: dict, log_odds: dict, exact_cols: List, fuzzy_cols: List, idx_to_col: dict, neg_samples: int = 50000) -> None: + + + +
+ + 
862def profile_log_odds(
+863    data: pd.DataFrame,
+864    true_matches: dict,
+865    log_odds: dict,
+866    exact_cols: List,
+867    fuzzy_cols: List,
+868    idx_to_col: dict,
+869    neg_samples: int = 50000,
+870) -> None:  # pragma: no cover
+871    """
+872    Basic graphical profiler for log-odds histogram analysis. Using the
+873    raw data and previously known true matches, the function computes one
+874    list of log-odds scores that that would be earned by true matches under
+875    a given linkage rule, and another list of scores that would be earned
+876    by a random sampling of non-matches under the same linkage rule. These
+877    lists are used to plot bimodal histograms so that the cutoff threshold
+878    between non-matchces and true matches can be visually determined.
+879
+880    :param data: A pandas data frame holding the raw patient record data.
+881    :param true_matches: A dictionary of known true matches in the data.
+882    :param log_odds: A dictionary whose keys are the column fields of data
+883      and whose values are the log-odds scores that two values match relative
+884      to random chance.
+885    :param exact_cols: A list of columns to be evaluated using equality
+886      comparisons.
+887    :param fuzzy_cols: A list of columns to be evaluated using fuzzy weighted
+888      comparisons.
+889    :param idx_to_col: A dictionary mapping the number of a column in a list
+890      representation of the data, to the name of the column in a pandas
+891      representation.
+892    :param neg_samples: Optionally, how many non-match samples to compute a
+893      score for when generating the histogram.
+894    """
+895    base_pairs = list(combinations(data.index, 2))
+896    neg_pairs = [
+897        x
+898        for x in base_pairs
+899        if x[0] not in true_matches or x[1] not in true_matches[x[0]]
+900    ]
+901    if neg_samples < len(neg_pairs):
+902        neg_pairs = sample(neg_pairs, neg_samples)
+903
+904    data = data.values.tolist()
+905    cols_to_idx = {}
+906    for idx in idx_to_col:
+907        cols_to_idx[idx_to_col[idx]] = idx
+908
+909    true_match_scores = []
+910    for root_record, paired_records in true_matches.items():
+911        for pr in paired_records:
+912            score = 0.0
+913            for c in exact_cols:
+914                score += feature_match_log_odds_exact(
+915                    data[root_record],
+916                    data[pr],
+917                    cols_to_idx[c],
+918                    idx_to_col=idx_to_col,
+919                    log_odds=log_odds,
+920                )
+921            for c in fuzzy_cols:
+922                score += feature_match_log_odds_fuzzy_compare(
+923                    data[root_record],
+924                    data[pr],
+925                    cols_to_idx[c],
+926                    idx_to_col=idx_to_col,
+927                    log_odds=log_odds,
+928                )
+929            true_match_scores.append(score)
+930
+931    non_match_scores = []
+932    for record_1, record_2 in neg_pairs:
+933        score = 0.0
+934        for c in exact_cols:
+935            score += feature_match_log_odds_exact(
+936                data[record_1],
+937                data[record_2],
+938                cols_to_idx[c],
+939                idx_to_col=idx_to_col,
+940                log_odds=log_odds,
+941            )
+942        for c in fuzzy_cols:
+943            score += feature_match_log_odds_fuzzy_compare(
+944                data[record_1],
+945                data[record_2],
+946                cols_to_idx[c],
+947                idx_to_col=idx_to_col,
+948                log_odds=log_odds,
+949            )
+950            non_match_scores.append(score)
+951
+952    min_length = min(len(true_match_scores), len(non_match_scores))
+953    true_match_scores = true_match_scores[:min_length]
+954    non_match_scores = non_match_scores[:min_length]
+955
+956    _, bins, _ = plt.hist(true_match_scores, bins=75, range=[0, 25])
+957    _ = plt.hist(non_match_scores, bins=bins, alpha=0.5)
+958    plt.show()
+
+ + +

Basic graphical profiler for log-odds histogram analysis. Using the +raw data and previously known true matches, the function computes one +list of log-odds scores that that would be earned by true matches under +a given linkage rule, and another list of scores that would be earned +by a random sampling of non-matches under the same linkage rule. These +lists are used to plot bimodal histograms so that the cutoff threshold +between non-matchces and true matches can be visually determined.

+ +
Parameters
+ +
    +
  • data: A pandas data frame holding the raw patient record data.
    • +
  • true_matches: A dictionary of known true matches in the data.
    • +
  • log_odds: A dictionary whose keys are the column fields of data +and whose values are the log-odds scores that two values match relative +to random chance.
    • +
  • exact_cols: A list of columns to be evaluated using equality +comparisons.
    • +
  • fuzzy_cols: A list of columns to be evaluated using fuzzy weighted +comparisons.
    • +
  • idx_to_col: A dictionary mapping the number of a column in a list +representation of the data, to the name of the column in a pandas +representation.
    • +
  • neg_samples: Optionally, how many non-match samples to compute a +score for when generating the histogram.
    • +
+
+ + +
+
+ +
+ + def + eval_log_odds_cutoff(feature_comparisons: List, **kwargs) -> bool: + + + +
+ + 
258def eval_log_odds_cutoff(feature_comparisons: List, **kwargs) -> bool:
+259    """
+260    Determines whether a given set of feature comparisons matches enough
+261    to be the result of a true patient link instead of just random chance.
+262    This is represented using previously computed log-odds ratios.
+263
+264    :param feature_comparisons: A list of floats representing the log-odds
+265      score of each field computed on.
+266    :return: Whether the feature comparisons score well enough to be
+267      considered a match.
+268    """
+269    if "true_match_threshold" not in kwargs:
+270        raise KeyError("Cutoff threshold for true matches must be passed.")
+271    return sum(feature_comparisons) >= kwargs["true_match_threshold"]
+
+ + +

Determines whether a given set of feature comparisons matches enough +to be the result of a true patient link instead of just random chance. +This is represented using previously computed log-odds ratios.

+ +
Parameters
+ +
    +
  • feature_comparisons: A list of floats representing the log-odds +score of each field computed on.
    • +
+ +
Returns
+ +
+

Whether the feature comparisons score well enough to be + considered a match.

+
+
+ + +
+
+ +
+ + class + BaseMPIConnectorClient(abc.ABC): + + + +
+ + 
 9class BaseMPIConnectorClient(ABC):
+10    """
+11    Represents a vendor-agnostic Master Patient Index (MPI) connector client. Requires
+12    implementing classes to define methods to retrive blocks of data from the MPI.
+13    Callers should use the provided interface functions (e.g., block_data)
+14    to interact with the underlying vendor-specific client property.
+15    """
+16
+17    @abstractmethod
+18    def get_block_data() -> List[list]:
+19        """
+20        Returns a list of lists containing records from the MPI database that
+21        match on the incoming record's block criteria and values. If blocking
+22        on 'ZIP' and the incoming record's zip code is '90210', the resulting
+23        block of data would contain records that all
+24        have the same zip code of 90210.
+25
+26        """
+27        pass  # pragma: no cover
+28
+29    @abstractmethod
+30    def insert_matched_patient() -> None:
+31        """
+32        If a matching person ID has been found in the MPI, inserts a new patient into
+33        the patient table and all other subsequent MPI tables, including the
+34        matched person id, to link the new patient and matched person ID;
+35        else inserts a new patient into the patient table, as well as all other
+36        subsequent MPI tables, and inserts a new person into the person table
+37        linking the new person to the new patient.
+38        """
+39        pass  # pragma: no cover
+40
+41    @abstractmethod
+42    def _generate_block_query(self, block_critieria: dict) -> Select:
+43        """
+44         Generates a query for selecting a block of data from the MPI tables per the
+45        block field criteria.  The block field criteria should be a dictionary
+46        organized by MPI table name, with the ORM table object, and the blocking
+47        criteria.
+48        """
+49        pass  # pragma: no cover
+
+ + +

Represents a vendor-agnostic Master Patient Index (MPI) connector client. Requires +implementing classes to define methods to retrive blocks of data from the MPI. +Callers should use the provided interface functions (e.g., block_data) +to interact with the underlying vendor-specific client property.

+
+ + +
+ +
+
@abstractmethod
+ + def + get_block_data() -> List[list]: + + + +
+ + 
17    @abstractmethod
+18    def get_block_data() -> List[list]:
+19        """
+20        Returns a list of lists containing records from the MPI database that
+21        match on the incoming record's block criteria and values. If blocking
+22        on 'ZIP' and the incoming record's zip code is '90210', the resulting
+23        block of data would contain records that all
+24        have the same zip code of 90210.
+25
+26        """
+27        pass  # pragma: no cover
+
+ + +

Returns a list of lists containing records from the MPI database that +match on the incoming record's block criteria and values. If blocking +on 'ZIP' and the incoming record's zip code is '90210', the resulting +block of data would contain records that all +have the same zip code of 90210.

+
+ + +
+
+ +
+
@abstractmethod
+ + def + insert_matched_patient() -> None: + + + +
+ + 
29    @abstractmethod
+30    def insert_matched_patient() -> None:
+31        """
+32        If a matching person ID has been found in the MPI, inserts a new patient into
+33        the patient table and all other subsequent MPI tables, including the
+34        matched person id, to link the new patient and matched person ID;
+35        else inserts a new patient into the patient table, as well as all other
+36        subsequent MPI tables, and inserts a new person into the person table
+37        linking the new person to the new patient.
+38        """
+39        pass  # pragma: no cover
+
+ + +

If a matching person ID has been found in the MPI, inserts a new patient into +the patient table and all other subsequent MPI tables, including the +matched person id, to link the new patient and matched person ID; +else inserts a new patient into the patient table, as well as all other +subsequent MPI tables, and inserts a new person into the person table +linking the new person to the new patient.

+
+ + +
+
+
+ +
+ + def + extract_blocking_values_from_record(record: dict, blocking_fields: List[dict]) -> dict: + + + +
+ + 
274def extract_blocking_values_from_record(
+275    record: dict, blocking_fields: List[dict]
+276) -> dict:
+277    """
+278    Extracts values from a given patient record for eventual use in database
+279    record linkage blocking. A list of fields to block on, as well as a mapping
+280    of those fields to any desired transformations of their extracted values,
+281    is used to fhir-path parse the value out of the incoming patient record.
+282
+283    Currently supported blocking fields:
+284    - first_name
+285    - last_name
+286    - birthdate
+287    - address
+288    - city
+289    - state
+290    - zip
+291    - sex
+292    - mrn
+293
+294    Currently supported transformations on extracted fields:
+295    - first4: the first four characters of the value
+296    - last4: the last four characters of the value
+297
+298    :param record: A FHIR-formatted Patient record.
+299    :param blocking_fields: A List of dictionaries giving the blocking
+300      fields and any transformations that should be applied to them. Each
+301      dictionary in the list should include a "value" key with one of the
+302      supported blocking fields above, and may also optionally contain a
+303      "transformation" key whose value is one of our supported transforms.
+304    """
+305
+306    transform_funcs = {
+307        "first4": lambda x: x[:4] if len(x) >= 4 else x,
+308        "last4": lambda x: x[-4:] if len(x) >= 4 else x,
+309    }
+310
+311    for block_dict in blocking_fields:
+312        if "value" not in block_dict:
+313            raise KeyError(
+314                f"Input dictionary for block {block_dict} must contain a 'value' key."
+315            )
+316
+317    block_vals = dict.fromkeys([b.get("value") for b in blocking_fields], "")
+318    transform_blocks = [b for b in blocking_fields if "transformation" in b]
+319    transformations = dict(
+320        zip(
+321            [b.get("value") for b in transform_blocks],
+322            [b.get("transformation") for b in transform_blocks],
+323        )
+324    )
+325    for block_dict in blocking_fields:
+326        block = block_dict.get("value")
+327        try:
+328            # Apply utility extractor for safe parsing
+329            value = extract_value_with_resource_path(
+330                record,
+331                LINKING_FIELDS_TO_FHIRPATHS[block],
+332                selection_criteria="first",
+333            )
+334            if value:
+335                if block in transformations:
+336                    try:
+337                        value = transform_funcs[transformations[block]](value)
+338                    except KeyError:
+339                        raise ValueError(
+340                            f"Transformation {transformations[block]} is not valid."
+341                        )
+342                    block_vals[block] = {
+343                        "value": value,
+344                        "transformation": transformations[block],
+345                    }
+346                else:
+347                    block_vals[block] = {"value": value}
+348
+349        except KeyError:
+350            raise ValueError(f"Field {block} is not a supported extraction field.")
+351
+352    # Account for any incoming FHIR resources that return no data
+353    # for a field--don't count this against records to-block
+354    keys_to_pop = []
+355    for field in block_vals:
+356        if _is_empty_extraction_field(block_vals, field):
+357            keys_to_pop.append(field)
+358    for k in keys_to_pop:
+359        block_vals.pop(k)
+360
+361    return block_vals
+
+ + +

Extracts values from a given patient record for eventual use in database +record linkage blocking. A list of fields to block on, as well as a mapping +of those fields to any desired transformations of their extracted values, +is used to fhir-path parse the value out of the incoming patient record.

+ +

Currently supported blocking fields:

+ +
    +
  • first_name
    • +
  • last_name
    • +
  • birthdate
    • +
  • address
    • +
  • city
    • +
  • state
    • +
  • zip
    • +
  • sex
    • +
  • mrn
    • +
+ +

Currently supported transformations on extracted fields:

+ +
    +
  • first4: the first four characters of the value
    • +
  • last4: the last four characters of the value
    • +
+ +
Parameters
+ +
    +
  • record: A FHIR-formatted Patient record.
    • +
  • blocking_fields: A List of dictionaries giving the blocking +fields and any transformations that should be applied to them. Each +dictionary in the list should include a "value" key with one of the +supported blocking fields above, and may also optionally contain a +"transformation" key whose value is one of our supported transforms.
    • +
+
+ + +
+
+ +
+ + def + write_linkage_config(linkage_algo: List[dict], file_to_write: pathlib.Path) -> None: + + + +
+ + 
1076def write_linkage_config(linkage_algo: List[dict], file_to_write: pathlib.Path) -> None:
+1077    """
+1078    Save a provided algorithm description as a JSON dictionary at the provided
+1079    filepath location. Algorithm descriptions are lists of dictionaries, one
+1080    for each pass of the algorithm, whose keys are parameter values for a
+1081    linkage pass (drawn from the list `"funcs"`, `"blocks"`, `"matching_rule"`,
+1082    and optionally `"cluster_ratio"` and `"kwargs"`) and whose values are
+1083    as follows:
+1084
+1085    - `"funcs"` should map to a dictionary mapping column index to the
+1086    name of a function in the DIBBS linkage module (such as
+1087    `feature_match_fuzzy_string`)--note that these are the actual
+1088    functions, not string names of the functions
+1089    - `"blocks"` should map to a list of columns to block on (e.g.
+1090    ["MRN4", "ADDRESS4"])
+1091    - `"matching_rule"` should map to one of the evaluation rule functions
+1092    in the DIBBS linkage module (i.e. `eval_perfect_match`)
+1093    - `"cluster_ratio"` should map to a float, if provided
+1094    - `"kwargs"` should map to a dictionary of keyword arguments and their
+1095    associated values, if provided
+1096
+1097    Here's an example of a simple single-pass linkage algorithm that blocks
+1098    on zip code, then matches on exact first name, exact last name, and
+1099    fuzzy date of birth (using, say, Levenshtein similarity with a score
+1100    threshold of 0.8) in dictionary descriptor form (for the sake of the
+1101    example, let's assume the data has the column order first, last, DOB):
+1102
+1103    [{
+1104        "funcs": {
+1105            0: feature_match_exact,
+1106            1: feature_match_exact,
+1107            2: feature_match_fuzzy_string,
+1108            3: feature_match_fuzzy_string,
+1109        },
+1110        "blocks": ["ZIP"],
+1111        "matching_rule": eval_perfect_match,
+1112        "kwargs": {
+1113            "similarity-measure": "Levenshtein",
+1114            "threshold": 0.8
+1115        }
+1116    }]
+1117
+1118    :param linkage_algo: A list of dictionaries whose key-value pairs correspond
+1119      to the rules above.
+1120    :param file_to_write: The path to the destination JSON file to write.
+1121    """
+1122    algo_json = []
+1123    for rl_pass in linkage_algo:
+1124        pass_json = {}
+1125        pass_json["funcs"] = {col: f.__name__ for (col, f) in rl_pass["funcs"].items()}
+1126        pass_json["blocks"] = rl_pass["blocks"]
+1127        pass_json["matching_rule"] = rl_pass["matching_rule"].__name__
+1128        if rl_pass.get("cluster_ratio", None) is not None:
+1129            pass_json["cluster_ratio"] = rl_pass["cluster_ratio"]
+1130        if rl_pass.get("kwargs", None) is not None:
+1131            pass_json["kwargs"] = {
+1132                kwarg: val for (kwarg, val) in rl_pass.get("kwargs", {}).items()
+1133            }
+1134        algo_json.append(pass_json)
+1135    linkage_json = {"algorithm": algo_json}
+1136    with open(file_to_write, "w") as out:
+1137        out.write(json.dumps(linkage_json))
+
+ + +

Save a provided algorithm description as a JSON dictionary at the provided +filepath location. Algorithm descriptions are lists of dictionaries, one +for each pass of the algorithm, whose keys are parameter values for a +linkage pass (drawn from the list "funcs", "blocks", "matching_rule", +and optionally "cluster_ratio" and "kwargs") and whose values are +as follows:

+ +
    +
  • "funcs" should map to a dictionary mapping column index to the +name of a function in the DIBBS linkage module (such as +feature_match_fuzzy_string)--note that these are the actual +functions, not string names of the functions
    • +
  • "blocks" should map to a list of columns to block on (e.g. +["MRN4", "ADDRESS4"])
    • +
  • "matching_rule" should map to one of the evaluation rule functions +in the DIBBS linkage module (i.e. eval_perfect_match)
    • +
  • "cluster_ratio" should map to a float, if provided
    • +
  • "kwargs" should map to a dictionary of keyword arguments and their +associated values, if provided
    • +
+ +

Here's an example of a simple single-pass linkage algorithm that blocks +on zip code, then matches on exact first name, exact last name, and +fuzzy date of birth (using, say, Levenshtein similarity with a score +threshold of 0.8) in dictionary descriptor form (for the sake of the +example, let's assume the data has the column order first, last, DOB):

+ +

[{ + "funcs": { + 0: feature_match_exact, + 1: feature_match_exact, + 2: feature_match_fuzzy_string, + 3: feature_match_fuzzy_string, + }, + "blocks": ["ZIP"], + "matching_rule": eval_perfect_match, + "kwargs": { + "similarity-measure": "Levenshtein", + "threshold": 0.8 + } +}]

+ +
Parameters
+ +
    +
  • linkage_algo: A list of dictionaries whose key-value pairs correspond +to the rules above.
    • +
  • file_to_write: The path to the destination JSON file to write.
    • +
+
+ + +
+
+ +
+ + def + read_linkage_config(config_file: pathlib.Path) -> List[dict]: + + + +
+ + 
961def read_linkage_config(config_file: pathlib.Path) -> List[dict]:
+962    """
+963    Reads and generates a record linkage algorithm configuration list from
+964    the provided filepath, which should point to a JSON file. A record
+965    linkage configuration list is a list of dictionaries--one for each
+966    pass in the algorithm it describes--containing information on the
+967    blocking fields, functions, cluster thresholds, and keyword arguments
+968    for that pass of the linkage algorithm. For a full example of all the
+969    components involved in a linkage description structure, see the doc
+970    string for `write_linkage_config`.
+971
+972    :param config_file: A `pathlib.Path` string pointing to a JSON file
+973      that describes the algorithm to decode.
+974    :return: A list of dictionaries whose values can be passed to the
+975      various parts of linkage pass function.
+976    """
+977    try:
+978        with open(config_file) as f:
+979            algo_config = json.load(f)
+980            # Need to convert function keys back to column indices, since
+981            # JSON serializes dict keys as strings
+982            for rl_pass in algo_config.get("algorithm"):
+983                rl_pass["funcs"] = {
+984                    int(col): f for (col, f) in rl_pass["funcs"].items()
+985                }
+986            return algo_config.get("algorithm", [])
+987    except FileNotFoundError:
+988        raise FileNotFoundError(f"No file exists at path {config_file}.")
+989    except json.decoder.JSONDecodeError as e:
+990        raise json.decoder.JSONDecodeError(
+991            "The specified file is not valid JSON.", e.doc, e.pos
+992        )
+
+ + +

Reads and generates a record linkage algorithm configuration list from +the provided filepath, which should point to a JSON file. A record +linkage configuration list is a list of dictionaries--one for each +pass in the algorithm it describes--containing information on the +blocking fields, functions, cluster thresholds, and keyword arguments +for that pass of the linkage algorithm. For a full example of all the +components involved in a linkage description structure, see the doc +string for write_linkage_config.

+ +
Parameters
+ +
    +
  • config_file: A pathlib.Path string pointing to a JSON file +that describes the algorithm to decode.
    • +
+ +
Returns
+ +
+

A list of dictionaries whose values can be passed to the + various parts of linkage pass function.

+
+
+ + +
+ +
+ +
+ + def + add_person_resource( person_id: str, patient_id: str, bundle: dict = FieldInfo(default=PydanticUndefined, description='A FHIR bundle', extra={})) -> dict: + + + +
+ + 
1516def add_person_resource(
+1517    person_id: str, patient_id: str, bundle: dict = Field(description="A FHIR bundle")
+1518) -> dict:
+1519    """
+1520    Adds a simplified person resource to a bundle if the patient resource in the bundle
+1521    matches an existing record in the Master Patient Index. Returns the bundle with
+1522    the newly added person resource.
+1523
+1524    :param person_id: _description_
+1525    :param patient_id: _description_
+1526    :param bundle: _description_, defaults to Field(description="A FHIR bundle")
+1527    :return: _description_
+1528    """
+1529    person_resource = {
+1530        "fullUrl": f"urn:uuid:{person_id}",
+1531        "resource": {
+1532            "resourceType": "Person",
+1533            "id": f"{person_id}",
+1534            "link": [{"target": {"reference": f"Patient/{patient_id}"}}],
+1535        },
+1536        "request": {
+1537            "method": "PUT",
+1538            "url": f"Person/{person_id}",
+1539        },
+1540    }
+1541
+1542    bundle.get("entry", []).append(person_resource)
+1543
+1544    return bundle
+
+ + +

Adds a simplified person resource to a bundle if the patient resource in the bundle +matches an existing record in the Master Patient Index. Returns the bundle with +the newly added person resource.

+ +
Parameters
+ +
    +
  • person_id: _description_
    • +
  • patient_id: _description_
    • +
  • bundle: _description_, defaults to Field(description="A FHIR bundle")
    • +
+ +
Returns
+ +
+

_description_

+
+
+ + +
+
+
+ _compare_address_elements + + +
+ + + + +
+
+
+ _compare_name_elements + + +
+ + + + +
+
+ +
+ + def + convert_to_patient_fhir_resources(data: Dict) -> Tuple: + + + +
+ + 
 37def convert_to_patient_fhir_resources(data: Dict) -> Tuple:
+ 38    """
+ 39    Converts and returns a row of patient data into patient resource in a FHIR-formatted
+ 40    patient resouce with a newly generated patient id as well as the
+ 41    `external_person_id`.
+ 42
+ 43    :param data: Dictionary of patient data that optionionally includes the following
+ 44      fields: mrn, ssn, first_name, middle_name, last_name, home_phone, cell-phone, sex,
+ 45      birthdate, address, city, state, zip.
+ 46    :return: Tuple of the `external_person_id` and FHIR-formatted patient resource.
+ 47    """
+ 48
+ 49    patient_id = str(uuid.uuid4())
+ 50
+ 51    # Iterate through each patient and convert patient data to FHIR resource
+ 52    patient_resource = {
+ 53        "resourceType": "Patient",
+ 54        "id": f"{patient_id}",
+ 55        "identifier": [
+ 56            {
+ 57                "type": {
+ 58                    "coding": [
+ 59                        {
+ 60                            "system": "http://terminology.hl7.org/CodeSystem/v2-0203",
+ 61                            "code": "MR",
+ 62                        }
+ 63                    ]
+ 64                },
+ 65                "value": f"{data.get('mrn', None)}",
+ 66            },
+ 67            {
+ 68                "type": {
+ 69                    "coding": [
+ 70                        {
+ 71                            "system": "http://terminology.hl7.org/CodeSystem/v2-0203",
+ 72                            "code": "SS",
+ 73                        }
+ 74                    ]
+ 75                },
+ 76                "value": f"{data.get('ssn', None)}",
+ 77            },
+ 78        ],
+ 79        "name": [
+ 80            {
+ 81                "family": f"{data.get('last_name', None)}",
+ 82                "given": extract_given_name(data),
+ 83            }
+ 84        ],
+ 85        "telecom": [
+ 86            {
+ 87                "system": "phone",
+ 88                "value": f"{data.get('home_phone', None)}",
+ 89                "use": "home",
+ 90            },
+ 91            {
+ 92                "system": "phone",
+ 93                "value": f"{data.get('cell_phone', None)}",
+ 94                "use": "mobile",
+ 95            },
+ 96            {"value": f"{data.get('email', None)}", "system": "email"},
+ 97        ],
+ 98        "gender": f"{data.get('sex', None)}",
+ 99        "birthDate": adjust_birthdate(data),
+100        "address": [
+101            {
+102                "use": "home",
+103                "line": [f"{data.get('address', None)}"],
+104                "city": f"{data.get('city', None)}",
+105                "state": f"{data.get('state', None)}",
+106                "postalCode": f"{data.get('zip', None)}",
+107            }
+108        ],
+109    }
+110
+111    fhir_bundle = {
+112        "resourceType": "Bundle",
+113        "type": "batch",
+114        "id": str(uuid.uuid4()),
+115        "entry": [
+116            {
+117                "fullUrl": f"urn:uuid:{patient_id}",
+118                "resource": patient_resource,
+119                "request": {"method": "PUT", "url": f"Patient/{patient_id}"},
+120            },
+121        ],
+122    }
+123
+124    external_person_id = data.get("person_id", None)
+125    return (external_person_id, fhir_bundle)
+
+ + +

Converts and returns a row of patient data into patient resource in a FHIR-formatted +patient resouce with a newly generated patient id as well as the +external_person_id.

+ +
Parameters
+ +
    +
  • data: Dictionary of patient data that optionionally includes the following +fields: mrn, ssn, first_name, middle_name, last_name, home_phone, cell-phone, sex, +birthdate, address, city, state, zip.
    • +
+ +
Returns
+ +
+

Tuple of the external_person_id and FHIR-formatted patient resource.

+
+
+ + +
+
+ +
+ + class + DIBBsMPIConnectorClient(phdi.linkage.BaseMPIConnectorClient): + + + +
+ + 
 22class DIBBsMPIConnectorClient(BaseMPIConnectorClient):
+ 23    """
+ 24    Represents a Postgres-specific Master Patient Index (MPI) connector
+ 25    client for the DIBBs implementation of the record linkage building
+ 26    block. Callers should use the provided interface functions (e.g.,
+ 27    block_vals) to interact with the underlying vendor-specific client
+ 28    property.
+ 29
+ 30    """
+ 31
+ 32    def __init__(self, pool_size: int = 5, max_overflow: int = 10):
+ 33        """
+ 34        Initialize the MPI connector client with the MPI database.
+ 35        :param pool_size: The number of connections to keep open to the database.
+ 36        :param max_overflow: The number of connections to allow in connection pool.
+ 37        """
+ 38        dbsettings = load_mpi_env_vars_os()
+ 39        dbuser = dbsettings.get("user")
+ 40        dbname = dbsettings.get("dbname")
+ 41        dbpwd = dbsettings.get("password")
+ 42        dbhost = dbsettings.get("host")
+ 43        dbport = dbsettings.get("port")
+ 44        self.dal = DataAccessLayer()
+ 45        self.dal.get_connection(
+ 46            engine_url=f"postgresql+psycopg2://{dbuser}:"
+ 47            + f"{dbpwd}@{dbhost}:{dbport}/{dbname}",
+ 48            pool_size=pool_size,
+ 49            max_overflow=max_overflow,
+ 50        )
+ 51        self.dal.initialize_schema()
+ 52        self.column_to_fhirpaths = {
+ 53            "patient": {
+ 54                "root_path": "Patient",
+ 55                "fields": {
+ 56                    "patient_id": "id",
+ 57                    "person_id": "person",
+ 58                    "dob": "birthDate",
+ 59                    "sex": "gender",
+ 60                    "race": """
+ 61                        extension.where(url =
+ 62                         'http://hl7.org/fhir/us/core/StructureDefinition/us-core-race')
+ 63                        .extension.valueCoding.display""",
+ 64                    "ethnicity": """
+ 65                    extension.where(url =
+ 66                    'http://hl7.org/fhir/us/core/StructureDefinition/us-core-ethnicity')
+ 67                    .extension.valueCoding.display""",
+ 68                },
+ 69            },
+ 70            "name": {
+ 71                "root_path": "Patient.name",
+ 72                "fields": {
+ 73                    "last_name": "family",
+ 74                    "given_name": "given",
+ 75                    "type": "use",
+ 76                },
+ 77            },
+ 78            "phone_number": {
+ 79                "root_path": "Patient.telecom.where(system='phone')",
+ 80                "fields": {
+ 81                    "phone_number": "value",
+ 82                    "start_date": "period.start",
+ 83                    "end_date": "period.end",
+ 84                    "type": "use",
+ 85                },
+ 86            },
+ 87            "address": {
+ 88                "root_path": "Patient.address",
+ 89                "fields": {
+ 90                    "line_1": "line[0]",
+ 91                    "line_2": "line[1]",
+ 92                    "city": "city",
+ 93                    "state": "state",
+ 94                    "zip_code": "postalCode",
+ 95                    "country": "country",
+ 96                    "latitude": """
+ 97                        extension.where(url =
+ 98                          'http://hl7.org/fhir/StructureDefinition/geolocation')
+ 99                        .extension.where(url = 'latitude').valueDecimal""",
+100                    "longitude": """extension.where(url =
+101                          'http://hl7.org/fhir/StructureDefinition/geolocation')
+102                          .extension.where(url = 'longitude').valueDecimal""",
+103                    "type": "use",
+104                    "start_date": "period.start",
+105                    "end_date": "period.end",
+106                },
+107            },
+108            "identifier": {
+109                "root_path": "Patient.identifier",
+110                "fields": {
+111                    "patient_identifier": "value",
+112                    "type_code": "type.coding[0].code",
+113                    "type_display": "type.coding[0].display",
+114                    "type_system": "type.coding[0].system",
+115                },
+116            },
+117        }
+118
+119    def get_block_data(self, block_criteria: Dict) -> List[list]:
+120        """
+121        Returns a list of lists containing records from the MPI database that
+122        match on the incoming record's block criteria and values. If blocking
+123        on 'ZIP' and the incoming record's ip code is '90210', the resulting
+124        block of data would contain records that all
+125        have the same zip code of 90210.
+126
+127        :param block_criteria: Dictionary containing key value pairs
+128            for the column name for blocking and the data for the
+129            incoming record as well as any transformations,
+130          e.g., {"ZIP": {"value": "90210"}} or
+131          {"ZIP": {"value": "90210",}, "transformation":"first4"}.
+132        :return: A list of records that are within the block, e.g.,
+133            records that all have 90210 as their ZIP.
+134        """
+135        logging.info("In get_block_data")
+136        if len(block_criteria) == 0:
+137            raise ValueError("`block_vals` cannot be empty.")
+138
+139        # Get the base query that will select all necessary
+140        # columns for linkage with some basic filtering
+141        logging.info(
+142            f"Starting _get_base_query at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+143        )
+144        query = self._get_base_query()
+145        logging.info(
+146            f"Done with _get_base_query at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+147        )
+148
+149        # now get the criteria organized by table so the
+150        # CTE queries can be constructed and then added
+151        # to the base query
+152        logging.info(
+153            f"Starting _organize_block_criteria at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+154        )
+155        organized_block_vals = self._organize_block_criteria(block_criteria)
+156        logging.info(
+157            f"Done with _organize_block_criteria at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}",  # noqa
+158        )
+159
+160        # now tack on the where criteria using the block_vals
+161        # while ensuring they exist in the table structure ORM
+162        logging.info(
+163            f"Starting _generate_block_query at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+164        )
+165        query_w_ctes = self._generate_block_query(
+166            organized_block_criteria=organized_block_vals, query=query
+167        )
+168        logging.info(
+169            f"Done with _generate_block_query at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+170        )
+171        logging.info(
+172            f"Starting dal.select_results at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+173        )
+174        blocked_data = self.dal.select_results(
+175            select_statement=query_w_ctes, include_col_header=True
+176        )
+177        logging.info(
+178            f"Done with dal.select_results at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+179        )
+180
+181        return blocked_data
+182
+183    def insert_matched_patient(
+184        self,
+185        patient_resource: Dict,
+186        person_id=None,
+187        external_person_id=None,
+188    ) -> str:
+189        """
+190        If a matching person ID has been found in the MPI, inserts a new patient into
+191        the patient table and all other subsequent MPI tables, including the
+192        matched person id, to link the new patient and matched person ID;
+193        else inserts a new patient into the patient table, as well as all other
+194        subsequent MPI tables, and inserts a new person into the person table
+195        linking the new person to the new patient.
+196
+197        :param patient_resource: A FHIR patient resource.
+198        :param person_id: The person ID matching the patient record if a match has been
+199          found in the MPI, defaults to None.
+200        :param external_person_id: The external person id for the person that matches
+201          the patient record if a match has been found in the MPI, defaults to None.
+202        """
+203        logging.info(
+204            f"Starting insert_matched_patient at {datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+205        )
+206
+207        try:
+208            if person_id is None:
+209                logging.info(
+210                    f"person_id was None; starting _insert_person at: {datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+211                )
+212                person_id = self._insert_person()
+213                logging.info(
+214                    f"person_id was None; done with _insert_person at: {datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+215                )
+216            patient_resource["person"] = person_id
+217            logging.info(
+218                f"Starting _get_mpi_records at: {datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+219            )
+220            mpi_records = self._get_mpi_records(patient_resource)
+221            logging.info(
+222                f"Done with _get_mpi_records at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+223            )
+224            logging.info(
+225                f"Starting dal.bulk_insert_dict at: {datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+226            )
+227            self.dal.bulk_insert_dict(
+228                records_with_table=mpi_records, return_primary_keys=False
+229            )
+230            logging.info(
+231                f"Done with dal.bulk_insert_dict at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+232            )
+233
+234            if external_person_id is not None:
+235                logging.info(
+236                    f"""external_person_id was not None;
+237                      starting _insert_external_person_id at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"""  # noqa
+238                )
+239                self._insert_external_person_id(person_id, external_person_id)
+240                logging.info(
+241                    f"""external_person_id was not None;
+242                      done with _insert_external_person_id at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"""  # noqa
+243                )
+244        except Exception as error:  # pragma: no cover
+245            raise ValueError(f"{error}")
+246
+247        return person_id
+248
+249    def _generate_where_criteria(self, block_criteria: dict, table_name: str) -> list:
+250        """
+251        Generates a list of where criteria leveraging the blocking criteria,
+252        including transformations such as 'first 4' or 'last 4'.  This
+253        function leverages the ORM to determine the table and columns.
+254
+255        :param block_criteria: a dictionary that contains the blocking criteria.
+256        :return: A list of where criteria used to append to the end of a query.
+257
+258        """
+259        where_criteria = []
+260        for key, value in block_criteria.items():
+261            criteria_value = value["value"]
+262            criteria_transform = value.get("transformation", None)
+263
+264            if criteria_transform is None:
+265                where_criteria.append(f"{table_name}.{key} = '{criteria_value}'")
+266            else:
+267                if criteria_transform == "first4":
+268                    where_criteria.append(
+269                        f"LEFT({table_name}.{key},4) = '{criteria_value}'"
+270                    )
+271                elif criteria_transform == "last4":
+272                    where_criteria.append(
+273                        f"RIGHT({table_name}.{key},4) = '{criteria_value}'"
+274                    )
+275        return where_criteria
+276
+277    def _generate_block_query(
+278        self, organized_block_criteria: dict, query: Select
+279    ) -> Select:
+280        """
+281        Generates a query for selecting a block of data from the MPI tables per the
+282        block field criteria.  The block field criteria should be a dictionary
+283        organized by MPI table name, with the ORM table object, and the blocking
+284        criteria.
+285
+286        :param organized_block_vals: a dictionary organized by MPI table name,
+287            with the ORM table object, and the blocking criteria.
+288        :return: A 'Select' statement built by the sqlalchemy ORM utilizing
+289            the blocking criteria.
+290
+291        """
+292        new_query = query
+293
+294        for table_key, table_info in organized_block_criteria.items():
+295            query_criteria = None
+296            cte_query = None
+297            sub_query = None
+298
+299            cte_query_table = table_info["table"]
+300            query_criteria = self._generate_where_criteria(
+301                table_info["criteria"], table_key
+302            )
+303
+304            if query_criteria is not None and len(query_criteria) > 0:
+305                if self.dal.does_table_have_column(cte_query_table, "patient_id"):
+306                    cte_query = (
+307                        select(cte_query_table.c.patient_id.label("patient_id"))
+308                        .where(text(" AND ".join(query_criteria)))
+309                        .cte(f"{table_key}_cte")
+310                    )
+311                else:
+312                    fk_query_table = copy.deepcopy(cte_query_table)
+313                    fk_info = fk_query_table.foreign_keys.pop()
+314                    fk_column = fk_info.column
+315                    fk_table = fk_info.column.table
+316                    sub_query = (
+317                        select(cte_query_table)
+318                        .where(text(" AND ".join(query_criteria)))
+319                        .subquery(f"{cte_query_table.name}_cte_subq")
+320                    )
+321                    cte_query = (
+322                        select(fk_table.c.patient_id).join(
+323                            sub_query,
+324                            text(
+325                                f"{fk_table.name}.{fk_column.name} = "
+326                                + f"{sub_query.name}.{fk_column.name}"
+327                            ),
+328                        )
+329                    ).cte(f"{table_key}_cte")
+330            if cte_query is not None:
+331                new_query = new_query.join(
+332                    cte_query,
+333                    and_(cte_query.c.patient_id == self.dal.PATIENT_TABLE.c.patient_id),
+334                )
+335
+336        return new_query
+337
+338    def _organize_block_criteria(self, block_fields: dict) -> dict:
+339        """
+340        Creates a dictionary with the MPI Table Names as keys
+341        that also stores the ORM Table Object, for each table,
+342        as well as the blocking criteria for each of the tables.
+343        The Table is discovered based upon the blocking columns.
+344        There is some transformation that occurs between certain
+345        blocking column criteria and the actual column names.
+346        Accepted blocking fields include: first_name, last_name,
+347        birthdate, address line 1, city, state, zip, mrn, and sex.
+348
+349        :param block_fields: A dictionary that contains the
+350            configured block fields along with the criteria
+351            and values for blocking.
+352        :return: A dictionary organized by table name that
+353            has the ORM Table Object and all blocking
+354            criteria and values.
+355        """
+356        # Accepted blocking fields include: first_name, last_name,
+357        # birthdate, address line 1, city, state, zip, mrn, and sex.
+358        organized_block_vals = {}
+359        for block_key, block_value in block_fields.items():
+360            sub_dict = {}
+361            # TODO: we may find a better way to handle this, but for now
+362            # just convert the known fields into their proper column counterparts
+363            if block_key == "address":
+364                sub_dict["line_1"] = block_value
+365                table_orm = self.dal.get_table_by_column("line_1")
+366            elif block_key == "zip":
+367                sub_dict["zip_code"] = block_value
+368                table_orm = self.dal.get_table_by_column("zip_code")
+369            elif block_key == "first_name":
+370                sub_dict["given_name"] = block_value
+371                table_orm = self.dal.get_table_by_column("given_name")
+372            elif block_key == "birthdate":
+373                sub_dict["dob"] = block_value
+374                table_orm = self.dal.get_table_by_column("dob")
+375            elif block_key == "mrn":
+376                sub_dict["patient_identifier"] = block_value
+377                # mrn specific criteria
+378                sub_dict["type_code"] = {"value": "MR"}
+379                table_orm = self.dal.get_table_by_column("patient_identifier")
+380            else:
+381                sub_dict[block_key] = block_value
+382                table_orm = self.dal.get_table_by_column(block_key)
+383            if table_orm is not None:
+384                if table_orm.name in organized_block_vals.keys():
+385                    organized_block_vals[table_orm.name]["criteria"].update(sub_dict)
+386                else:
+387                    organized_block_vals[table_orm.name] = {
+388                        "table": table_orm,
+389                        "criteria": sub_dict,
+390                    }
+391            else:
+392                continue
+393        return organized_block_vals
+394
+395    def _get_base_query(self) -> Select:
+396        """
+397        Generates a select query that pulls all the relevant
+398        MPI records from the MPI tables, using an ORM, for
+399        Patient Matching/Blocking.
+400
+401        :return: A single select statement queries all relevant
+402            blocking columns and tables from the MPI.
+403        """
+404
+405        id_sub_query = (
+406            select(
+407                self.dal.ID_TABLE.c.patient_identifier.label("mrn"),
+408                self.dal.ID_TABLE.c.patient_id.label("patient_id"),
+409            )
+410            .where(self.dal.ID_TABLE.c.type_code == "MR")
+411            .subquery("ident_subq")
+412        )
+413
+414        # TODO: keeping this here for the time
+415        # when we decide to add phone numbers into
+416        # the blocking data
+417        #
+418        #  phone_sub_query = (
+419        #     select(
+420        #         self.dal.PHONE_TABLE.c.phone_number.label("phone_number"),
+421        #         self.dal.PHONE_TABLE.c.type.label("phone_type"),
+422        #         self.dal.PHONE_TABLE.c.patient_id.label("patient_id"),
+423        #     )
+424        #     .where(self.dal.PHONE_TABLE.c.type.in_(["home", "cell"]))
+425        #     .subquery()
+426        # )
+427
+428        query = (
+429            select(
+430                self.dal.PATIENT_TABLE.c.patient_id,
+431                self.dal.PATIENT_TABLE.c.person_id,
+432                self.dal.PATIENT_TABLE.c.dob.label("birthdate"),
+433                self.dal.PATIENT_TABLE.c.sex,
+434                id_sub_query.c.mrn,
+435                self.dal.NAME_TABLE.c.last_name,
+436                self.dal.GIVEN_NAME_TABLE.c.given_name,
+437                self.dal.GIVEN_NAME_TABLE.c.given_name_index,
+438                self.dal.GIVEN_NAME_TABLE.c.name_id,
+439                # TODO: keeping this here for the time
+440                # when we decide to add phone numbers into
+441                # the blocking data
+442                #
+443                # phone_sub_query.c.phone_number,
+444                # phone_sub_query.c.phone_type,
+445                self.dal.ADDRESS_TABLE.c.line_1.label("address"),
+446                self.dal.ADDRESS_TABLE.c.zip_code.label("zip"),
+447                self.dal.ADDRESS_TABLE.c.city,
+448                self.dal.ADDRESS_TABLE.c.state,
+449            )
+450            .outerjoin(
+451                id_sub_query,
+452            )
+453            .outerjoin(self.dal.NAME_TABLE)
+454            .outerjoin(self.dal.GIVEN_NAME_TABLE)
+455            # TODO: keeping this here for the time
+456            # when we decide to add phone numbers into
+457            # the blocking data
+458            #
+459            # .outerjoin(phone_sub_query)
+460            .outerjoin(self.dal.ADDRESS_TABLE)
+461        )
+462        return query
+463
+464    def _get_mpi_records(self, patient_resource: dict) -> dict:
+465        """
+466        Generates a dictionary with the different MPI Table
+467        Name as keys along with the records for each of the
+468        MPI Tables, based upon the FHIR Patient Resource data
+469        passed in.
+470        There are cases where a direct insert occurs to get
+471        the primary key, that will be used as a foreign key
+472        in another MPI Table record.  ie. patient_id is used
+473        in almost every table, so a patient insert must occur
+474        first to get the Patient primary key for the other
+475        MPI table foreign keys.
+476
+477
+478        :param patient_resource: The FHIR Patient Resource that
+479            contains patient data to create new MPI records.
+480        :return: A dictionary of MPI Table names and records.
+481        """
+482        records = {}
+483        if patient_resource["resourceType"] != "Patient":
+484            return records
+485
+486        # Check if patient_id exists
+487        if patient_resource.get("id", None) is None:
+488            patient_id = uuid.uuid4()
+489            patient_resource["id"] = patient_id
+490        else:
+491            patient_id = patient_resource.get("id")
+492
+493        for table in self.column_to_fhirpaths.keys():
+494            table_dict = self.column_to_fhirpaths.get(table)
+495            table_fields = table_dict.get("fields")
+496
+497            # Parse root path
+498            root = extract_value_with_resource_path(
+499                patient_resource, table_dict.get("root_path"), selection_criteria="all"
+500            )
+501            # Parse fields
+502            table_records = []
+503            if root is not None:
+504                for element in root:
+505                    record = {"patient_id": patient_id}
+506                    if table == "name":
+507                        name_id = uuid.uuid4()
+508                        record["name_id"] = name_id
+509                    for field in table_fields.keys():
+510                        selection_criteria = "first"
+511                        if field == "given_name":
+512                            selection_criteria = "all"
+513
+514                        value = extract_value_with_resource_path(
+515                            element,
+516                            table_fields.get(field),
+517                            selection_criteria=selection_criteria,
+518                        )
+519                        # Create given_name table in records
+520                        if field == "given_name":
+521                            given_name_table_records = self._extract_given_names(
+522                                value, name_id
+523                            )
+524                            if field not in records.keys():
+525                                records[field] = given_name_table_records
+526                            else:
+527                                for given_name_table_record in given_name_table_records:
+528                                    records[field].append(given_name_table_record)
+529                            continue
+530                        record[field] = value
+531
+532                    table_records.append(record)
+533
+534            records[table] = table_records
+535
+536        return records
+537
+538    def _extract_given_names(self, given_names: list, name_id: uuid) -> dict:
+539        """
+540        Separates given_name into it's own table and creates the given_name_index
+541        ahead of inserting the table into the MPI.
+542
+543        :param given_names: List of given names.
+544        :return: List of dictionaries containing entries for the given_name table with
+545            1 given name and index per row as well as an associated given_name_id.
+546        """
+547        table_records = []
+548        if given_names is not None:
+549            for idx, name in enumerate(given_names):
+550                record = {
+551                    "name_id": name_id,
+552                    "given_name": name,
+553                    "given_name_index": idx,
+554                }
+555                table_records.append(record)
+556        else:
+557            record = {
+558                "name_id": name_id,
+559                "given_name": None,
+560                "given_name_index": 0,
+561            }
+562            table_records.append(record)
+563        return table_records
+564
+565    def _insert_external_person_id(
+566        self,
+567        person_id: str,
+568        external_person_id: str,
+569    ):
+570        """
+571        Inserts a new external person id record into the MPI if the external_person_id
+572        does not already exist in the MPI.
+573
+574        :param person_id: The person_id matching the patient record if a match has been
+575            found in the MPI.
+576        :param external_person_id: The external_person_id for the patient record if it
+577            exists.
+578
+579        """
+580        if person_id is None or external_person_id is None:  # pragma: no cover
+581            raise ValueError("person_id and external_person_id must be provided.")
+582
+583        external_source_id = self._get_external_source_id("IRIS")
+584
+585        if external_source_id is not None:
+586            query = select(self.dal.EXTERNAL_PERSON_TABLE).where(
+587                text(
+588                    f"{self.dal.EXTERNAL_PERSON_TABLE.name}.external_person_id"
+589                    + f" = '{external_person_id}' AND "
+590                    + f"{self.dal.EXTERNAL_PERSON_TABLE.name}.person_id = '{person_id}'"
+591                    + f" AND {self.dal.EXTERNAL_PERSON_TABLE.name}.external_source_id "
+592                    + f" = '{external_source_id}'"
+593                )
+594            )
+595            external_person_record = self.dal.select_results(query, False)
+596
+597            if len(external_person_record) == 0:
+598                new_external_person_record = {
+599                    "person_id": person_id,
+600                    "external_person_id": external_person_id,
+601                    "external_source_id": external_source_id,
+602                }
+603                self.dal.bulk_insert_list(
+604                    self.dal.EXTERNAL_PERSON_TABLE, [new_external_person_record], False
+605                )
+606
+607    @cache
+608    def _get_external_source_id(self, external_source_name: str) -> Literal[str, None]:
+609        """
+610        Gets the external source id for the external source name provided.
+611        :param external_source_name: The external source name.
+612        :return: The external source id if found, otherwise None.
+613        """
+614
+615        external_source_id_query = select(self.dal.EXTERNAL_SOURCE_TABLE).where(
+616            text(
+617                f"{self.dal.EXTERNAL_SOURCE_TABLE.name}.external_source_name"
+618                + f" = '{external_source_name}'"
+619            )
+620        )
+621        external_source_record = self.dal.select_results(
+622            external_source_id_query, False
+623        )
+624
+625        external_source_id = None
+626        if len(external_source_record) > 0:
+627            external_source_id = external_source_record[0][0]
+628
+629        return external_source_id
+630
+631    def _generate_dict_record_from_results(
+632        self, results_list: List[list]
+633    ) -> List[dict]:
+634        """
+635        Converts a list of list of records into a
+636        dictionary using the column name header, in the
+637        first row (first list) along with the values in
+638        the rest of the rows (lists).
+639
+640
+641        :param results_list: a list of list containing mpi
+642            records.
+643        :return: A dictionary that has the key value pairs
+644            of the results list.
+645        """
+646        return_records = []
+647        # we must ensure that there is a header AND at least
+648        # one record or there is much of a point in moving forward
+649        if len(results_list) > 1 and len(results_list[0]) > 0:
+650            for row_index, record in enumerate(results_list):
+651                if row_index > 0:
+652                    columns_and_values = {}
+653                    for col_index, row_header in enumerate(results_list[0]):
+654                        columns_and_values[row_header] = record[col_index]
+655                    return_records.append(columns_and_values)
+656        return return_records
+657
+658    def _insert_person(self) -> str:
+659        """
+660        Simple insert of a new person record, which contains
+661        a new id (pk)
+662
+663        :return: The newly created person id.
+664        """
+665        person_record = {}
+666        person_id = self.dal.bulk_insert_list(
+667            self.dal.PERSON_TABLE, [person_record], True
+668        )
+669        return person_id[0]
+
+ + +

Represents a Postgres-specific Master Patient Index (MPI) connector +client for the DIBBs implementation of the record linkage building +block. Callers should use the provided interface functions (e.g., +block_vals) to interact with the underlying vendor-specific client +property.

+
+ + +
+ +
+ + DIBBsMPIConnectorClient(pool_size: int = 5, max_overflow: int = 10) + + + +
+ + 
 32    def __init__(self, pool_size: int = 5, max_overflow: int = 10):
+ 33        """
+ 34        Initialize the MPI connector client with the MPI database.
+ 35        :param pool_size: The number of connections to keep open to the database.
+ 36        :param max_overflow: The number of connections to allow in connection pool.
+ 37        """
+ 38        dbsettings = load_mpi_env_vars_os()
+ 39        dbuser = dbsettings.get("user")
+ 40        dbname = dbsettings.get("dbname")
+ 41        dbpwd = dbsettings.get("password")
+ 42        dbhost = dbsettings.get("host")
+ 43        dbport = dbsettings.get("port")
+ 44        self.dal = DataAccessLayer()
+ 45        self.dal.get_connection(
+ 46            engine_url=f"postgresql+psycopg2://{dbuser}:"
+ 47            + f"{dbpwd}@{dbhost}:{dbport}/{dbname}",
+ 48            pool_size=pool_size,
+ 49            max_overflow=max_overflow,
+ 50        )
+ 51        self.dal.initialize_schema()
+ 52        self.column_to_fhirpaths = {
+ 53            "patient": {
+ 54                "root_path": "Patient",
+ 55                "fields": {
+ 56                    "patient_id": "id",
+ 57                    "person_id": "person",
+ 58                    "dob": "birthDate",
+ 59                    "sex": "gender",
+ 60                    "race": """
+ 61                        extension.where(url =
+ 62                         'http://hl7.org/fhir/us/core/StructureDefinition/us-core-race')
+ 63                        .extension.valueCoding.display""",
+ 64                    "ethnicity": """
+ 65                    extension.where(url =
+ 66                    'http://hl7.org/fhir/us/core/StructureDefinition/us-core-ethnicity')
+ 67                    .extension.valueCoding.display""",
+ 68                },
+ 69            },
+ 70            "name": {
+ 71                "root_path": "Patient.name",
+ 72                "fields": {
+ 73                    "last_name": "family",
+ 74                    "given_name": "given",
+ 75                    "type": "use",
+ 76                },
+ 77            },
+ 78            "phone_number": {
+ 79                "root_path": "Patient.telecom.where(system='phone')",
+ 80                "fields": {
+ 81                    "phone_number": "value",
+ 82                    "start_date": "period.start",
+ 83                    "end_date": "period.end",
+ 84                    "type": "use",
+ 85                },
+ 86            },
+ 87            "address": {
+ 88                "root_path": "Patient.address",
+ 89                "fields": {
+ 90                    "line_1": "line[0]",
+ 91                    "line_2": "line[1]",
+ 92                    "city": "city",
+ 93                    "state": "state",
+ 94                    "zip_code": "postalCode",
+ 95                    "country": "country",
+ 96                    "latitude": """
+ 97                        extension.where(url =
+ 98                          'http://hl7.org/fhir/StructureDefinition/geolocation')
+ 99                        .extension.where(url = 'latitude').valueDecimal""",
+100                    "longitude": """extension.where(url =
+101                          'http://hl7.org/fhir/StructureDefinition/geolocation')
+102                          .extension.where(url = 'longitude').valueDecimal""",
+103                    "type": "use",
+104                    "start_date": "period.start",
+105                    "end_date": "period.end",
+106                },
+107            },
+108            "identifier": {
+109                "root_path": "Patient.identifier",
+110                "fields": {
+111                    "patient_identifier": "value",
+112                    "type_code": "type.coding[0].code",
+113                    "type_display": "type.coding[0].display",
+114                    "type_system": "type.coding[0].system",
+115                },
+116            },
+117        }
+
+ + +

Initialize the MPI connector client with the MPI database.

+ +
Parameters
+ +
    +
  • pool_size: The number of connections to keep open to the database.
    • +
  • max_overflow: The number of connections to allow in connection pool.
    • +
+
+ + +
+
+ +
+ + def + get_block_data(self, block_criteria: Dict) -> List[list]: + + + +
+ + 
119    def get_block_data(self, block_criteria: Dict) -> List[list]:
+120        """
+121        Returns a list of lists containing records from the MPI database that
+122        match on the incoming record's block criteria and values. If blocking
+123        on 'ZIP' and the incoming record's ip code is '90210', the resulting
+124        block of data would contain records that all
+125        have the same zip code of 90210.
+126
+127        :param block_criteria: Dictionary containing key value pairs
+128            for the column name for blocking and the data for the
+129            incoming record as well as any transformations,
+130          e.g., {"ZIP": {"value": "90210"}} or
+131          {"ZIP": {"value": "90210",}, "transformation":"first4"}.
+132        :return: A list of records that are within the block, e.g.,
+133            records that all have 90210 as their ZIP.
+134        """
+135        logging.info("In get_block_data")
+136        if len(block_criteria) == 0:
+137            raise ValueError("`block_vals` cannot be empty.")
+138
+139        # Get the base query that will select all necessary
+140        # columns for linkage with some basic filtering
+141        logging.info(
+142            f"Starting _get_base_query at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+143        )
+144        query = self._get_base_query()
+145        logging.info(
+146            f"Done with _get_base_query at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+147        )
+148
+149        # now get the criteria organized by table so the
+150        # CTE queries can be constructed and then added
+151        # to the base query
+152        logging.info(
+153            f"Starting _organize_block_criteria at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+154        )
+155        organized_block_vals = self._organize_block_criteria(block_criteria)
+156        logging.info(
+157            f"Done with _organize_block_criteria at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}",  # noqa
+158        )
+159
+160        # now tack on the where criteria using the block_vals
+161        # while ensuring they exist in the table structure ORM
+162        logging.info(
+163            f"Starting _generate_block_query at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+164        )
+165        query_w_ctes = self._generate_block_query(
+166            organized_block_criteria=organized_block_vals, query=query
+167        )
+168        logging.info(
+169            f"Done with _generate_block_query at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+170        )
+171        logging.info(
+172            f"Starting dal.select_results at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+173        )
+174        blocked_data = self.dal.select_results(
+175            select_statement=query_w_ctes, include_col_header=True
+176        )
+177        logging.info(
+178            f"Done with dal.select_results at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+179        )
+180
+181        return blocked_data
+
+ + +

Returns a list of lists containing records from the MPI database that +match on the incoming record's block criteria and values. If blocking +on 'ZIP' and the incoming record's ip code is '90210', the resulting +block of data would contain records that all +have the same zip code of 90210.

+ +
Parameters
+ +
    +
  • block_criteria: Dictionary containing key value pairs + for the column name for blocking and the data for the + incoming record as well as any transformations, +e.g., {"ZIP": {"value": "90210"}} or +{"ZIP": {"value": "90210",}, "transformation":"first4"}.
    • +
+ +
Returns
+ +
+

A list of records that are within the block, e.g., + records that all have 90210 as their ZIP.

+
+
+ + +
+
+ +
+ + def + insert_matched_patient( self, patient_resource: Dict, person_id=None, external_person_id=None) -> str: + + + +
+ + 
183    def insert_matched_patient(
+184        self,
+185        patient_resource: Dict,
+186        person_id=None,
+187        external_person_id=None,
+188    ) -> str:
+189        """
+190        If a matching person ID has been found in the MPI, inserts a new patient into
+191        the patient table and all other subsequent MPI tables, including the
+192        matched person id, to link the new patient and matched person ID;
+193        else inserts a new patient into the patient table, as well as all other
+194        subsequent MPI tables, and inserts a new person into the person table
+195        linking the new person to the new patient.
+196
+197        :param patient_resource: A FHIR patient resource.
+198        :param person_id: The person ID matching the patient record if a match has been
+199          found in the MPI, defaults to None.
+200        :param external_person_id: The external person id for the person that matches
+201          the patient record if a match has been found in the MPI, defaults to None.
+202        """
+203        logging.info(
+204            f"Starting insert_matched_patient at {datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+205        )
+206
+207        try:
+208            if person_id is None:
+209                logging.info(
+210                    f"person_id was None; starting _insert_person at: {datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+211                )
+212                person_id = self._insert_person()
+213                logging.info(
+214                    f"person_id was None; done with _insert_person at: {datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+215                )
+216            patient_resource["person"] = person_id
+217            logging.info(
+218                f"Starting _get_mpi_records at: {datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+219            )
+220            mpi_records = self._get_mpi_records(patient_resource)
+221            logging.info(
+222                f"Done with _get_mpi_records at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+223            )
+224            logging.info(
+225                f"Starting dal.bulk_insert_dict at: {datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+226            )
+227            self.dal.bulk_insert_dict(
+228                records_with_table=mpi_records, return_primary_keys=False
+229            )
+230            logging.info(
+231                f"Done with dal.bulk_insert_dict at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"  # noqa
+232            )
+233
+234            if external_person_id is not None:
+235                logging.info(
+236                    f"""external_person_id was not None;
+237                      starting _insert_external_person_id at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"""  # noqa
+238                )
+239                self._insert_external_person_id(person_id, external_person_id)
+240                logging.info(
+241                    f"""external_person_id was not None;
+242                      done with _insert_external_person_id at:{datetime.datetime.now().strftime('%m-%d-%yT%H:%M:%S.%f')}"""  # noqa
+243                )
+244        except Exception as error:  # pragma: no cover
+245            raise ValueError(f"{error}")
+246
+247        return person_id
+
+ + +

If a matching person ID has been found in the MPI, inserts a new patient into +the patient table and all other subsequent MPI tables, including the +matched person id, to link the new patient and matched person ID; +else inserts a new patient into the patient table, as well as all other +subsequent MPI tables, and inserts a new person into the person table +linking the new person to the new patient.

+ +
Parameters
+ +
    +
  • patient_resource: A FHIR patient resource.
    • +
  • person_id: The person ID matching the patient record if a match has been +found in the MPI, defaults to None.
    • +
  • external_person_id: The external person id for the person that matches +the patient record if a match has been found in the MPI, defaults to None.
    • +
+
+ + +
+
+
+ +
+ + def + datetime_to_str( input_date: Union[str, datetime.date, datetime.datetime], include_time: bool = False) -> str: + + + +
+ + 
50def datetime_to_str(
+51    input_date: Union[str, date, datetime], include_time: bool = False
+52) -> str:
+53    """
+54    Convert a date or datetime object to a string; if a string is provided,
+55    check that it follows the appropriate format. If unable to perform actions,
+56    return input as string rather than failing loudly.
+57
+58    :param input_date: The input date to convert, which prefers types of
+59        datetime.date, datetime.datetime, or str.
+60    :param include_time: Whether to include the time in the output string.
+61    :return: The formatted date as a string. If include_time is True, the
+62        format is 'YYYY-MM-DD HH:MM:SS', otherwise it's 'YYYY-MM-DD'. If
+63        empty or None, return empty or None.
+64    """
+65    # Handle None or empty string
+66    if input_date is None or input_date == "":
+67        return input_date
+68
+69    # if input is str try to check that it follows the expected format
+70    if isinstance(input_date, str):
+71        try:
+72            expected_format = "%Y-%m-%d %H:%M:%S" if include_time else "%Y-%m-%d"
+73            datetime.strptime(input_date, expected_format)
+74            return input_date
+75        except ValueError:
+76            # rather than break loudly, allow str to pass
+77            return input_date
+78
+79    # if input is a date or datetime then convert in the expected format
+80    elif isinstance(input_date, (date, datetime)):
+81        if include_time:
+82            return input_date.strftime("%Y-%m-%d %H:%M:%S")
+83        else:
+84            return input_date.strftime("%Y-%m-%d")
+85    # if input isn't any of the accepted formats, then return a type error
+86    else:
+87        try:
+88            return str(input_date)
+89        except TypeError:
+90            raise TypeError(
+91                f"Input date {input_date} is not of type date, datetime, "
+92                "or str; or, it can't be converted or returned safely."
+93            )
+
+ + +

Convert a date or datetime object to a string; if a string is provided, +check that it follows the appropriate format. If unable to perform actions, +return input as string rather than failing loudly.

+ +
Parameters
+ +
    +
  • input_date: The input date to convert, which prefers types of +datetime.date, datetime.datetime, or str.
    • +
  • include_time: Whether to include the time in the output string.
    • +
+ +
Returns
+ +
+

The formatted date as a string. If include_time is True, the + format is 'YYYY-MM-DD HH:MM:SS', otherwise it's 'YYYY-MM-DD'. If + empty or None, return empty or None.

+
+
+ + +
+
+ +
+ + def + aggregate_given_names_for_linkage(data: list[list]): + + + +
+ + 
1547def aggregate_given_names_for_linkage(data: list[list]):
+1548    """
+1549    Aggregates the given names in the return block data into appropriate format for
+1550    record linkage, i.e., one row of data for each patient with all of the given names
+1551    in a space-delimited string, e.g., John Tiberius
+1552
+1553    :param data: List of lists block data.
+1554    :return: List of lists with aggregated given names.
+1555    """
+1556    # Convert LoL to pandas dataframe
+1557    raw_data = pd.DataFrame(data[1:], columns=data[0])
+1558
+1559    # Aggregate given names
+1560    given_names = (
+1561        raw_data.sort_values(["name_id", "given_name_index"])
+1562        .groupby(["name_id"])["given_name"]
+1563        .apply(lambda x: " ".join(x))
+1564        .reset_index()
+1565    )
+1566    given_names.rename(columns={"given_name": "first_name"}, inplace=True)
+1567
+1568    # Merge aggregated given names into original data
+1569    df = raw_data.merge(given_names, on="name_id")
+1570
+1571    # Return only necessary columns
+1572    # TODO: remove hard coding of necessary columns
+1573    necessary_columns = [
+1574        "patient_id",
+1575        "person_id",
+1576        "birthdate",
+1577        "sex",
+1578        "mrn",
+1579        "last_name",
+1580        "first_name",
+1581        "address",
+1582        "zip",
+1583        "city",
+1584        "state",
+1585    ]
+1586    df = df[necessary_columns]
+1587    df = df.drop_duplicates()
+1588
+1589    # Convert dataframe to list of lists for record linkage
+1590    lol = df.values.tolist()
+1591    lol.insert(0, necessary_columns)
+1592    return lol
+
+ + +

Aggregates the given names in the return block data into appropriate format for +record linkage, i.e., one row of data for each patient with all of the given names +in a space-delimited string, e.g., John Tiberius

+ +
Parameters
+ +
    +
  • data: List of lists block data.
    • +
+ +
Returns
+ +
+

List of lists with aggregated given names.

+
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/tabulation.html b/docs/v1.2.7/sdk/phdi/tabulation.html new file mode 100644 index 0000000000..b508c1fb0b --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/tabulation.html @@ -0,0 +1,545 @@ + + + + + + + phdi.tabulation API documentation + + + + + + + + + +
+
+

+phdi.tabulation

+ + + + + + + 
1from phdi.tabulation.tables import load_schema
+2from phdi.tabulation.tables import validate_schema
+3from phdi.tabulation.tables import write_data
+4
+5__all__ = ("load_schema", "validate_schema", write_data)
+
+ + +
+
+ +
+ + def + load_schema(path: pathlib.Path) -> dict: + + + +
+ + 
18def load_schema(path: pathlib.Path) -> dict:
+19    """
+20    Given the path to a local YAML or JSON file containing a schema,
+21    loads the file and return the resulting schema as a dictionary.
+22    If the file can't be found, raises an error.
+23
+24    :param path: The file path to a YAML file holding a schema.
+25    :raises ValueError: If the provided path points to an unsupported file type.
+26    :raises FileNotFoundError: If the file to be loaded could not be found.
+27    :raises JSONDecodeError: If a JSON file is provided with invalid JSON.
+28    :return: A dict representing a schema read from the given path.
+29    """
+30    try:
+31        with open(path, "r") as file:
+32            if path.suffix == ".yaml":
+33                schema = yaml.safe_load(file)
+34            elif path.suffix == ".json":
+35                schema = json.load(file)
+36            else:
+37                ftype = path.suffix.replace(".", "").upper()
+38                raise ValueError(f"Unsupported file type provided: {ftype}")
+39        validate_schema(schema)
+40        return schema
+41    except FileNotFoundError:
+42        raise FileNotFoundError(
+43            "The specified file does not exist at the path provided."
+44        )
+45    except json.decoder.JSONDecodeError as e:
+46        raise json.decoder.JSONDecodeError(
+47            "The specified file is not valid JSON.", e.doc, e.pos
+48        )
+
+ + +

Given the path to a local YAML or JSON file containing a schema, +loads the file and return the resulting schema as a dictionary. +If the file can't be found, raises an error.

+ +
Parameters
+ +
    +
  • path: The file path to a YAML file holding a schema.
    • +
+ +
Raises
+ +
    +
  • ValueError: If the provided path points to an unsupported file type.
    • +
  • FileNotFoundError: If the file to be loaded could not be found.
    • +
  • JSONDecodeError: If a JSON file is provided with invalid JSON.
    • +
+ +
Returns
+ +
+

A dict representing a schema read from the given path.

+
+
+ + +
+
+ +
+ + def + validate_schema(schema: dict): + + + +
+ + 
51def validate_schema(schema: dict):
+52    """
+53    Validates the schema structure, ensuring all required schema elements are present
+54    and all schema elements are of the expected data type.
+55
+56    :param schema: A declarative, user-defined specification, for one or more tables,
+57        that defines the metadata, properties, and columns of those tables as they
+58        relate to FHIR resources.
+59    :raises jsonschema.exception.ValidationError: If the schema is invalid.
+60    """
+61    # Load validation schema
+62    with importlib.resources.open_text(
+63        "phdi.tabulation", "validation_schema.json"
+64    ) as file:
+65        validation_schema = json.load(file)
+66
+67    validate(schema=validation_schema, instance=schema)
+
+ + +

Validates the schema structure, ensuring all required schema elements are present +and all schema elements are of the expected data type.

+ +
Parameters
+ +
    +
  • schema: A declarative, user-defined specification, for one or more tables, +that defines the metadata, properties, and columns of those tables as they +relate to FHIR resources.
    • +
+ +
Raises
+ +
    +
  • jsonschema.exception.ValidationError: If the schema is invalid.
    • +
+
+ + +
+
+ +
+ + def + write_data( tabulated_data: List[List], directory: str, output_type: Literal['csv', 'parquet', 'sql'], filename: str = None, db_file: str = None, db_tablename: str = None, pq_writer: pyarrow.parquet.core.ParquetWriter = None, schema: dict = None, table_name: str = None) -> Optional[pyarrow.parquet.core.ParquetWriter]: + + + +
+ + 
 70def write_data(
+ 71    tabulated_data: List[List],
+ 72    directory: str,
+ 73    output_type: Literal["csv", "parquet", "sql"],
+ 74    filename: str = None,
+ 75    db_file: str = None,
+ 76    db_tablename: str = None,
+ 77    pq_writer: pq.ParquetWriter = None,
+ 78    schema: dict = None,
+ 79    table_name: str = None,
+ 80) -> Union[None, pq.ParquetWriter]:
+ 81    """
+ 82    Writes a set of tabulated data to a particular output format on disk
+ 83    (one of CSV, Parquet, or SQL). For CSV and Parquet writing, a filename
+ 84    must be provided to write output to. In the case of the SQL format,
+ 85    a database file (if one exists and is being modified) must be specified
+ 86    along with a table name in place of a filename. Creates new data files
+ 87    if the given options specify a file that doesn't exist, and appends
+ 88    data to already-present files if they do.
+ 89
+ 90    :param tabulated_data: A list of lists in which the first element
+ 91      is the headers for the table-to-write and subsequent elements
+ 92      are rows in the table.
+ 93    :param directory: The directory in which to write the output data
+ 94      (if `output_type` is CSV or Parquet), or the directory in which
+ 95      the `db_file` is stored (if a database already exists) or should
+ 96      be created in (if a database does not already exist).
+ 97    :param output_type: The format the data should be written to.
+ 98    :param filename: The name of the CSV or Parquet file data should be
+ 99      written to. Omit if `output_type` is SQL. Default: `None`.
+100    :param db_file: The name of the database file to either create or
+101      access when writing to a SQL format. Omit if `output_type` is not
+102      SQL. Default: `None`.
+103    :param db_tablename: The name of the table in the database to create
+104      or write data to. Omit if `output_type` is not SQL. Default: `None`.
+105    :param pq_writer: A pre-existing `ParquetWriter` object that can be
+106      used to append data to a parquet format. Used in cases where
+107      incremental writing to a parquet destination is desired. Omit if
+108      `output_type` is not Parquet. Default: `None`.
+109    """
+110    # some elements may themselves contain lists, if selection_criteria = all is used
+111    for i in range(1, len(tabulated_data)):
+112        table_list = tabulated_data[i]
+113        for row, elt in enumerate(table_list):
+114            if isinstance(elt, list):
+115                tabulated_data[i][row] = _convert_list_to_string(elt)
+116            if isinstance(elt, dict):
+117                tabulated_data[i][row] = str(elt)
+118
+119    if output_type == "csv":
+120        write_headers = (
+121            False if os.path.isfile(os.path.join(directory, filename)) else True
+122        )
+123        with open(os.path.join(directory, filename), "a", newline="") as fp:
+124            writer = csv.writer(fp, dialect="excel")
+125            if write_headers:
+126                writer.writerow(tabulated_data[0])
+127            writer.writerows(tabulated_data[1:])
+128
+129    if output_type == "parquet":
+130        if schema and table_name:
+131            # Create the parquet schema based on the config file
+132            pq_schema = _create_pa_schema_from_table_schema(
+133                schema, tabulated_data[0], table_name
+134            )
+135        else:
+136            pq_schema = None
+137        # Rearrange data so that it is column, not row based as parquet needs
+138        parquet_data = _create_parquet_data(tabulated_data, pq_schema)
+139        if pq_schema:
+140            table = pa.Table.from_arrays(
+141                _create_from_arrays_data(parquet_data[1:]), schema=pq_schema
+142            )
+143        else:
+144            # If no schema file is provided, use the names field
+145            table = pa.Table.from_arrays(
+146                _create_from_arrays_data(parquet_data[1:]), names=tabulated_data[0]
+147            )
+148        if pq_writer is None:
+149            pq_writer = pq.ParquetWriter(
+150                os.path.join(directory, filename), table.schema
+151            )
+152        pq_writer.write_table(table=table)
+153        return pq_writer
+154
+155    # @TODO:
+156    # 1. support username and passwords for database access
+157    # 2. figure out a more intelligent way to serialize data that's being
+158    # written to the SQL DB; there's the possibility that we need to write
+159    # list data to the table if an anchor has multiple reverse references,
+160    # but SQL can't write native python lists, so we need to either
+161    # stringify them, json.dumps serialize them, or binarize them
+162    if output_type == "sql":
+163        # We need a file-space cursor to operate on a connected table
+164        conn = sql.connect(os.path.join(directory, db_file))
+165        cursor = conn.cursor()
+166
+167        # Create requested table if it's not already in the database
+168        headers = tuple(tabulated_data[0])
+169        cursor.execute(f"CREATE TABLE IF NOT EXISTS {db_tablename} {headers};")
+170
+171        # Format the programmatic values correctly by number of cols
+172        # Need this ugly construction so that the binding placeholder qmarks
+173        # don't have quotes around them individually when parsed by the SQL
+174        # engine
+175        hdr_placeholder = "({})".format(", ".join("?" * len(tabulated_data[0])))
+176        tuple_data = [tuple([str(x) for x in row]) for row in tabulated_data[1:]]
+177        # Have to do a format string this way to avoid an empty f-string error
+178        print(tuple_data)
+179        cursor.executemany(
+180            "INSERT INTO {} {} VALUES {};".format(
+181                db_tablename, headers, hdr_placeholder
+182            ),
+183            tuple_data,
+184        )
+185
+186        conn.commit()
+187        conn.close()
+
+ + +

Writes a set of tabulated data to a particular output format on disk +(one of CSV, Parquet, or SQL). For CSV and Parquet writing, a filename +must be provided to write output to. In the case of the SQL format, +a database file (if one exists and is being modified) must be specified +along with a table name in place of a filename. Creates new data files +if the given options specify a file that doesn't exist, and appends +data to already-present files if they do.

+ +
Parameters
+ +
    +
  • tabulated_data: A list of lists in which the first element +is the headers for the table-to-write and subsequent elements +are rows in the table.
    • +
  • directory: The directory in which to write the output data +(if output_type is CSV or Parquet), or the directory in which +the db_file is stored (if a database already exists) or should +be created in (if a database does not already exist).
    • +
  • output_type: The format the data should be written to.
    • +
  • filename: The name of the CSV or Parquet file data should be +written to. Omit if output_type is SQL. Default: None.
    • +
  • db_file: The name of the database file to either create or +access when writing to a SQL format. Omit if output_type is not +SQL. Default: None.
    • +
  • db_tablename: The name of the table in the database to create +or write data to. Omit if output_type is not SQL. Default: None.
    • +
  • pq_writer: A pre-existing ParquetWriter object that can be +used to append data to a parquet format. Used in cases where +incremental writing to a parquet destination is desired. Omit if +output_type is not Parquet. Default: None.
    • +
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/transport.html b/docs/v1.2.7/sdk/phdi/transport.html new file mode 100644 index 0000000000..3224a74b89 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/transport.html @@ -0,0 +1,358 @@ + + + + + + + phdi.transport API documentation + + + + + + + + + +
+
+

+phdi.transport

+ + + + + + + 
1from .http import http_request_with_retry
+2
+3__all__ = ["http_request_with_retry"]
+
+ + +
+
+ +
+ + def + http_request_with_retry( url: str, retry_count: int, request_type: Literal['GET', 'POST'], allowed_methods: List[str], headers: dict, data: dict = None) -> requests.models.Response: + + + +
+ + 
10def http_request_with_retry(
+11    url: str,
+12    retry_count: int,
+13    request_type: Literal["GET", "POST"],
+14    allowed_methods: List[str],
+15    headers: dict,
+16    data: dict = None,
+17) -> requests.Response:
+18    """
+19    Executes an HTTP request, retrying the request if the returned HTTP status code
+20    is one of a specified list of codes.
+21
+22    :param url: The url at which to make the HTTP request.
+23    :param retry_count: The number of times to retry the request, if the
+24      first attempt fails.
+25    :param request_type: The type of request to be made. Currently supports
+26      GET and POST.
+27    :param allowed_methods: The list of allowed HTTP request methods (i.e.,
+28      POST, PUT) for the specific URL and query.
+29    :param headers: JSON-type dictionary of headers to make the request with,
+30      including Authorization and content-type.
+31    :param data: The data as a JSON-formatted dictionary, used when the request
+32      requires data to be posted. Default: `None`
+33    :raises ValueError: An unsupported HTTP method (e.g., PATCH, DELETE) was passed
+34      to the request_type parameter.
+35    :return: A HTTP request response.
+36    """
+37
+38    request_type = request_type.upper()
+39    if request_type not in ["GET", "POST"]:
+40        raise ValueError(
+41            f"The HTTP '{request_type}' method is not currently supported."
+42        )
+43
+44    # Configure the settings of the 'requests' session we'll make
+45    # the API call with
+46    retry_strategy = Retry(
+47        total=retry_count,
+48        status_forcelist=[429, 500, 502, 503, 504],
+49        allowed_methods=allowed_methods,
+50    )
+51    adapter = HTTPAdapter(max_retries=retry_strategy)
+52    http = requests.Session()
+53    http.mount("http://", adapter)
+54    http.mount("https://", adapter)
+55
+56    # Now, actually try to complete the API request
+57    # TODO: Condense this down to make a single call using
+58    # http.request(method=request_type, url=url, headers=headers, json=data)
+59    if request_type == "POST":
+60        response = http.post(
+61            url=url,
+62            headers=headers,
+63            json=data,
+64        )
+65    elif request_type == "GET":
+66        response = http.get(
+67            url=url,
+68            headers=headers,
+69        )
+70
+71    return response
+
+ + +

Executes an HTTP request, retrying the request if the returned HTTP status code +is one of a specified list of codes.

+ +
Parameters
+ +
    +
  • url: The url at which to make the HTTP request.
    • +
  • retry_count: The number of times to retry the request, if the +first attempt fails.
    • +
  • request_type: The type of request to be made. Currently supports +GET and POST.
    • +
  • allowed_methods: The list of allowed HTTP request methods (i.e., +POST, PUT) for the specific URL and query.
    • +
  • headers: JSON-type dictionary of headers to make the request with, +including Authorization and content-type.
    • +
  • data: The data as a JSON-formatted dictionary, used when the request +requires data to be posted. Default: None
    • +
+ +
Raises
+ +
    +
  • ValueError: An unsupported HTTP method (e.g., PATCH, DELETE) was passed +to the request_type parameter.
    • +
+ +
Returns
+ +
+

A HTTP request response.

+
+
+ + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/phdi/validation.html b/docs/v1.2.7/sdk/phdi/validation.html new file mode 100644 index 0000000000..bbad140f39 --- /dev/null +++ b/docs/v1.2.7/sdk/phdi/validation.html @@ -0,0 +1,1453 @@ + + + + + + + phdi.validation API documentation + + + + + + + + + +
+
+

+phdi.validation

+ + + + + + + 
 1from phdi.validation.validation import _add_message_ids
+ 2from phdi.validation.validation import _append_error_message
+ 3from phdi.validation.validation import _clear_all_errors_and_ids
+ 4from phdi.validation.validation import _organize_error_messages
+ 5from phdi.validation.validation import _response_builder
+ 6from phdi.validation.validation import validate_ecr
+ 7from phdi.validation.xml_utils import _check_xml_names_and_attribs_exist
+ 8from phdi.validation.xml_utils import _get_ecr_custom_message
+ 9from phdi.validation.xml_utils import _get_xml_attributes
+10from phdi.validation.xml_utils import _get_xml_message_id
+11from phdi.validation.xml_utils import _get_xml_relative_iterator
+12from phdi.validation.xml_utils import _get_xml_relatives_details
+13from phdi.validation.xml_utils import _validate_xml_related_element
+14from phdi.validation.xml_utils import _validate_xml_relatives
+15from phdi.validation.xml_utils import ECR_NAMESPACES
+16from phdi.validation.xml_utils import get_ecr_message_ids
+17from phdi.validation.xml_utils import get_xml_element_details
+18from phdi.validation.xml_utils import validate_xml_attributes
+19from phdi.validation.xml_utils import validate_xml_elements
+20from phdi.validation.xml_utils import validate_xml_value
+21
+22__all__ = [
+23    "validate_ecr",
+24    "_organize_error_messages",
+25    "_response_builder",
+26    "_append_error_message",
+27    "_add_message_ids",
+28    "_clear_all_errors_and_ids",
+29    "get_ecr_message_ids",
+30    "_check_xml_names_and_attribs_exist",
+31    "_get_ecr_custom_message",
+32    "_get_xml_message_id",
+33    "get_xml_element_details",
+34    "_get_xml_attributes",
+35    "_get_xml_relative_iterator",
+36    "validate_xml_elements",
+37    "validate_xml_attributes",
+38    "_validate_xml_related_element",
+39    "_validate_xml_relatives",
+40    "validate_xml_value",
+41    "_get_xml_relatives_details",
+42    "ECR_NAMESPACES",
+43]
+
+ + +
+
+ +
+ + def + validate_ecr(ecr_message: str, config: dict, include_error_types: list) -> dict: + + + +
+ + 
 21def validate_ecr(ecr_message: str, config: dict, include_error_types: list) -> dict:
+ 22    """
+ 23    Receives an ecr message (a combined RR and eICR), a configuration of
+ 24    what fields are to be validated and how they are to be validated, as
+ 25    well as a list of error message types to include (default is all fatal
+ 26    errors, basic errors, warnings, and information).  The result of
+ 27    validation is returned in a dictionary that also contains a boolean
+ 28    if the ecr message is valid or not.
+ 29
+ 30    :param ecr_message: A eCR message that contains both eICR and RR fields.
+ 31    :param config: A dictionary of the requirements for validation of the
+ 32      eCR message.
+ 33    :param include_error_types: A list of error message types to include
+ 34        in the final validation response.  Default (fatal, errors,
+ 35        warnings, information)
+ 36    :return: A dictionary containing bool message_valid as well as a
+ 37        dictionary containing the validation results/errors.
+ 38    """
+ 39    _clear_all_errors_and_ids()
+ 40    # encoding ecr_message to allow it to be
+ 41    #  parsed and organized as an lxml Element Tree Object
+ 42    xml = ecr_message.encode("utf-8")
+ 43    parser = etree.XMLParser(ns_clean=True, recover=True, encoding="utf-8")
+ 44
+ 45    # we need a try-catch around this to ensure that the ecr message
+ 46    # passed in is proper XML - also ensure it's a clinical document
+ 47    try:
+ 48        parsed_ecr = etree.fromstring(xml, parser=parser)
+ 49        parsed_ecr.xpath("//hl7:ClinicalDocument", namespaces=ECR_NAMESPACES)
+ 50
+ 51    except AttributeError:
+ 52        _append_error_message(
+ 53            error_message_type="fatal", message="eCR Message is not valid XML!"
+ 54        )
+ 55        return _response_builder(include_error_types=include_error_types)
+ 56
+ 57    _add_message_ids(get_ecr_message_ids(parsed_ecr=parsed_ecr))
+ 58
+ 59    for field in config.get("fields"):
+ 60        # extract the specific information from the configuration
+ 61        # for the different fields
+ 62        cda_path = field.get("cdaPath")
+ 63
+ 64        # get a list of XML elements that match the field configuration
+ 65        matched_xml_elements = validate_xml_elements(
+ 66            xml_elements=parsed_ecr.xpath(cda_path, namespaces=ECR_NAMESPACES),
+ 67            config_field=field,
+ 68        )
+ 69        error_message_type = (
+ 70            field.get("errorType")
+ 71            if field.get("errorType") in ERROR_MESSAGES.keys()
+ 72            else "errors"
+ 73        )
+ 74        # if there are no xml elements that were valid for
+ 75        # the configuration then store an error for that based
+ 76        # upon the configured error message type
+ 77        if not matched_xml_elements:
+ 78            error_message = "Could not find field. " + get_xml_element_details(
+ 79                None, field
+ 80            )
+ 81            _append_error_message(
+ 82                error_message_type=error_message_type, message=error_message
+ 83            )
+ 84            continue
+ 85        # continue the validation steps for xml attributes and values
+ 86        attribute_errors = []
+ 87        value_errors = []
+ 88        for xml_element in matched_xml_elements:
+ 89            attribute_errors += validate_xml_attributes(xml_element, field)
+ 90            value_errors += validate_xml_value(xml_element, field)
+ 91        # this handles a specific case where just ONE xml element
+ 92        # must meet the attribute or xml value criteria - otherwise
+ 93        # you wil want to include an error.
+ 94        if not (
+ 95            field.get("validateOne")
+ 96            and len(attribute_errors) < len(matched_xml_elements)
+ 97            and len(value_errors) < len(matched_xml_elements)
+ 98        ):
+ 99            for attribute_error in attribute_errors:
+100                _append_error_message(
+101                    error_message_type=error_message_type, message=attribute_error
+102                )
+103            for value_error in value_errors:
+104                _append_error_message(
+105                    error_message_type=error_message_type, message=value_error
+106                )
+107    response = _response_builder(include_error_types=include_error_types)
+108    return response
+
+ + +

Receives an ecr message (a combined RR and eICR), a configuration of +what fields are to be validated and how they are to be validated, as +well as a list of error message types to include (default is all fatal +errors, basic errors, warnings, and information). The result of +validation is returned in a dictionary that also contains a boolean +if the ecr message is valid or not.

+ +
Parameters
+ +
    +
  • ecr_message: A eCR message that contains both eICR and RR fields.
    • +
  • config: A dictionary of the requirements for validation of the +eCR message.
    • +
  • include_error_types: A list of error message types to include +in the final validation response. Default (fatal, errors, +warnings, information)
    • +
+ +
Returns
+ +
+

A dictionary containing bool message_valid as well as a + dictionary containing the validation results/errors.

+
+
+ + +
+
+ +
+ + def + _organize_error_messages(include_error_types: list) -> None: + + + +
+ + 
111def _organize_error_messages(include_error_types: list) -> None:
+112    # utilize the error_types to filter out the different error message
+113    # types as well as specify the difference between the different error types
+114    # during the validation process
+115
+116    # fatal warnings cannot be filtered and will be automatically included!
+117    # also, let's not wipe out the message_ids dictionary
+118    for error_type in ERROR_MESSAGES.keys():
+119        if (
+120            error_type not in ("fatal", "message_ids")
+121            and error_type not in include_error_types
+122        ):
+123            ERROR_MESSAGES[error_type] = []
+
+ + + + +
+
+ +
+ + def + _response_builder(include_error_types: list) -> dict: + + + +
+ + 
126def _response_builder(include_error_types: list) -> dict:
+127    if ERROR_MESSAGES.get("fatal") != []:
+128        valid = False
+129    else:
+130        valid = True
+131        _append_error_message(
+132            error_message_type="information",
+133            message="Validation completed with no fatal errors!",
+134        )
+135    _organize_error_messages(include_error_types=include_error_types)
+136
+137    return {"message_valid": valid, "validation_results": ERROR_MESSAGES}
+
+ + + + +
+
+ +
+ + def + _append_error_message(error_message_type: str, message: str) -> None: + + + +
+ + 
140def _append_error_message(error_message_type: str, message: str) -> None:
+141    if error_message_type in ERROR_MESSAGES.keys():
+142        if isinstance(message, list):
+143            for msg in message:
+144                if msg is not None and msg.strip() != "":
+145                    ERROR_MESSAGES[error_message_type].append(msg.strip())
+146        elif message is not None and message.strip() != "":
+147            ERROR_MESSAGES[error_message_type].append(message.strip())
+
+ + + + +
+
+ +
+ + def + _add_message_ids(ids: dict) -> None: + + + +
+ + 
150def _add_message_ids(ids: dict) -> None:
+151    if ids:
+152        ERROR_MESSAGES["message_ids"] = ids
+153    else:
+154        ERROR_MESSAGES["message_ids"] = {}
+
+ + + + +
+
+ +
+ + def + _clear_all_errors_and_ids() -> None: + + + +
+ + 
157def _clear_all_errors_and_ids() -> None:
+158    ERROR_MESSAGES["fatal"] = []
+159    ERROR_MESSAGES["errors"] = []
+160    ERROR_MESSAGES["information"] = []
+161    ERROR_MESSAGES["warnings"] = []
+162    ERROR_MESSAGES["message_ids"] = {}
+
+ + + + +
+
+ +
+ + def + get_ecr_message_ids(parsed_ecr) -> dict: + + + +
+ + 
34def get_ecr_message_ids(parsed_ecr) -> dict:
+35    # get the message ids for the eicr and the rr
+36    xml_eicr_id = _get_xml_message_id(
+37        parsed_ecr.xpath(EICR_MSG_ID_XPATH, namespaces=ECR_NAMESPACES)
+38    )
+39    xml_rr_id = _get_xml_message_id(
+40        parsed_ecr.xpath(RR_MSG_ID_XPATH, namespaces=ECR_NAMESPACES)
+41    )
+42
+43    return {"eicr": xml_eicr_id, "rr": xml_rr_id}
+
+ + + + +
+
+ +
+ + def + _check_xml_names_and_attribs_exist(xml_element, config_field) -> bool: + + + +
+ + 
 99def _check_xml_names_and_attribs_exist(xml_element, config_field) -> bool:
+100    """
+101    Confirms that the xml element name and attributes specified in
+102    the configuration actually exist.
+103
+104    :param xml_element: The key xml element that is being evaluated.
+105    :param config_field: A dictionary of the requirements for validating
+106        the key xml elements name and attributes
+107    :return: Bool - True if the name and attributes exist in the passed in
+108        xml element, otherwise false.
+109    """
+110    # If the configuration specified field name doesn't match the xml elements
+111    # tag name, then return false to go to the next xml element
+112    field_name = re.search(r"(?!\:)[a-zA-z]+\w$", config_field.get("cdaPath")).group(0)
+113
+114    if field_name.lower() not in xml_element.tag.lower():
+115        return False
+116
+117    # Don't try to evaluate matches for the xml element's attributes
+118    # if we are validating all fields as indicated in the configuration
+119    # for the field/xml element
+120    match_attributes = False if config_field.get("validateAll") == "True" else True
+121    if not match_attributes:
+122        return True
+123
+124    # Check if the xml element passed in has the right attributes
+125    #  and if the values of the attribute correspond to the
+126    #  requirements in the configuration
+127    field_attributes = config_field.get("attributes")
+128    if field_attributes:
+129        for attribute in field_attributes:
+130            # If field is supposed to have an attribute and doesn't,
+131            # return that the field has failed validation for that
+132            # attribute.
+133            if not xml_element.get(attribute.get("attributeName")):
+134                return False
+135    else:
+136        # If there are not specified attributes to validate within the
+137        # configuration, but there are attributes in the xml element
+138        # then return a False/Fail
+139        # TODO: is this how this should be working??
+140        if xml_element.attrib:
+141            return False
+142    return True
+
+ + +

Confirms that the xml element name and attributes specified in +the configuration actually exist.

+ +
Parameters
+ +
    +
  • xml_element: The key xml element that is being evaluated.
    • +
  • config_field: A dictionary of the requirements for validating +the key xml elements name and attributes
    • +
+ +
Returns
+ +
+

Bool - True if the name and attributes exist in the passed in + xml element, otherwise false.

+
+
+ + +
+
+ +
+ + def + _get_ecr_custom_message(config_field, default_message): + + + +
+ + 
308def _get_ecr_custom_message(config_field, default_message):
+309    message = default_message
+310    if config_field.get("customMessage"):
+311        message = config_field.get("customMessage")
+312    return message
+
+ + + + +
+
+ +
+ + def + _get_xml_message_id(id_xml_tag: <cyfunction Element>) -> dict: + + + +
+ + 
21def _get_xml_message_id(id_xml_tag: etree.Element) -> dict:
+22    # extracts the message id from the root and extension
+23    # attributes from the specified xml tag and returns
+24    # the results in a dictionary
+25
+26    if id_xml_tag == []:
+27        return {}
+28    id_root = id_xml_tag[0].get("root")
+29    id_extension = id_xml_tag[0].get("extension")
+30    message_id = {"root": id_root, "extension": id_extension}
+31    return message_id
+
+ + + + +
+
+ +
+ + def + get_xml_element_details(xml_element, config_field) -> str: + + + +
+ + 
315def get_xml_element_details(xml_element, config_field) -> str:
+316    """
+317    Gets the name, value, of the xml element referenced as well
+318    as the details of any configured relative xml elements for
+319    the referenced xml element and formats this information into
+320    a single string for use in the validation messages.
+321
+322    :param xml_element: The key xml element.
+323    :param config_field: A dictionary of the configured requirements
+324        for the xml element.
+325    :return: A single string containing the information about the
+326        key xml element and its attribute(s).
+327    """
+328    if config_field is None or config_field == {}:
+329        return ""
+330    name = [f"Field name: '{config_field.get('fieldName')}'"]
+331    config_attributes = config_field.get("attributes")
+332    attributes = (
+333        ["Attributes:"] + _get_xml_attributes(xml_element, config_attributes)
+334        if config_attributes
+335        else []
+336    )
+337    relative_string = _get_xml_relatives_details(config_field.get("relatives"))
+338    value = (
+339        [f"value: '{''.join(xml_element.itertext())}'"]
+340        if (
+341            config_field.get("textRequired")
+342            and xml_element is not None
+343            and "".join(xml_element.itertext()) != ""
+344        )
+345        else []
+346    )
+347    return " ".join(name + value + attributes + relative_string)
+
+ + +

Gets the name, value, of the xml element referenced as well +as the details of any configured relative xml elements for +the referenced xml element and formats this information into +a single string for use in the validation messages.

+ +
Parameters
+ +
    +
  • xml_element: The key xml element.
    • +
  • config_field: A dictionary of the configured requirements +for the xml element.
    • +
+ +
Returns
+ +
+

A single string containing the information about the + key xml element and its attribute(s).

+
+
+ + +
+
+ +
+ + def + _get_xml_attributes(xml_element, config_attributes) -> list: + + + +
+ + 
383def _get_xml_attributes(xml_element, config_attributes) -> list:
+384    """
+385    Takes the xml element, along with its configuration to create
+386    a list of strings that include attribute name, required
+387    patterns, and the actual value of said attribute.
+388
+389    :param xml_element: The key xml element.
+390    :param config_attributes: A dictionary of the configured requirements
+391        for the attributes for the key xml element.
+392    :return: A single string containing the information about the
+393        key xml elements attribute(s).
+394    """
+395    attrs = []
+396    if config_attributes is None or config_attributes == "":
+397        return attrs
+398    for attribute in config_attributes:
+399        attr_index = len(attrs) + 1
+400        attribute_name = attribute.get("attributeName")
+401        reg_ex = attribute.get("regEx")
+402        reg_ex_string = (
+403            f" with the required value pattern: '{reg_ex}'" if reg_ex else ""
+404        )
+405
+406        if xml_element is not None and xml_element.get(attribute_name):
+407            attribute_value = f" actual value: '{xml_element.get(attribute_name)}'"
+408        else:
+409            attribute_value = ""
+410
+411        attrs.append(
+412            f"attribute #{attr_index}: "
+413            + f"'{attribute_name}'{reg_ex_string}{attribute_value}"
+414        )
+415    return [", ".join(attrs)]
+
+ + +

Takes the xml element, along with its configuration to create +a list of strings that include attribute name, required +patterns, and the actual value of said attribute.

+ +
Parameters
+ +
    +
  • xml_element: The key xml element.
    • +
  • config_attributes: A dictionary of the configured requirements +for the attributes for the key xml element.
    • +
+ +
Returns
+ +
+

A single string containing the information about the + key xml elements attribute(s).

+
+
+ + +
+
+ +
+ + def + _get_xml_relative_iterator(cda_path, relative_cda_path, xml_element) -> list: + + + +
+ + 
214def _get_xml_relative_iterator(cda_path, relative_cda_path, xml_element) -> list:
+215    """
+216    Gets an iterator, basically a list of xml elements, based on the key
+217    xml element's path and the relative xml element's path being
+218    searched for.
+219
+220    :param cda_path: A string representing the location of the key xml element.
+221    :param relative_cda_path: A string representing the path of the relative
+222        xml element to be searched for.
+223    :param xml_element: The key xml element.
+224    :return: An lxml defined iterator of the relative xml elements
+225        based on the key xml element.
+226    """
+227    if xml_element is None:
+228        return None
+229    # get the difference of the number of '/' between the key cda_path and the
+230    # relative_cda_path
+231    diff = len(cda_path.split(XML_PATH_DELIMITER)) - len(
+232        relative_cda_path.split(XML_PATH_DELIMITER)
+233    )
+234    # element is on the same level of the main element
+235    if diff == 0:
+236        iter = []
+237        iter_forward = xml_element.itersiblings()
+238        iter_reverse = xml_element.itersiblings(preceding=True)
+239        for e in iter_forward:
+240            iter.append(e)
+241        for e in iter_reverse:
+242            iter.append(e)
+243        return iter
+244    # element is an acestor to the main element
+245    elif diff > 0:
+246        # get all the ancestors and put them into a list
+247        # and then get the one that is at the level
+248        # equal to the diff -1 (to account for array numbering)
+249
+250        if len(list(xml_element.iterancestors())) < diff - 1:
+251            return None
+252        xml_relative_element = list(xml_element.iterancestors())[diff - 1]
+253        return xml_relative_element
+254    # element is a child of the main element
+255    elif diff == -1:
+256        return list(xml_element.iterchildren())
+257    # if diff is < -1 then it's a descendant and it's
+258    # going to have to return all tags under the base
+259    # xml element
+260    else:
+261        return list(xml_element.iterdescendants())
+
+ + +

Gets an iterator, basically a list of xml elements, based on the key +xml element's path and the relative xml element's path being +searched for.

+ +
Parameters
+ +
    +
  • cda_path: A string representing the location of the key xml element.
    • +
  • relative_cda_path: A string representing the path of the relative +xml element to be searched for.
    • +
  • xml_element: The key xml element.
    • +
+ +
Returns
+ +
+

An lxml defined iterator of the relative xml elements + based on the key xml element.

+
+
+ + +
+
+ +
+ + def + validate_xml_elements(xml_elements, config_field) -> list: + + + +
+ + 
46def validate_xml_elements(xml_elements, config_field) -> list:
+47    """
+48    Matches the xml_elements to the config field requirements for
+49    values, attributes, and relative xml element requirements for
+50    values, and attributes. Returns list of matching fields.
+51
+52    :param xml_elements: A list of xml elements
+53    :param config_field: A dictionary of the requirements of the field.
+54    :return: A list of matched xml elemnts
+55    """
+56    if not xml_elements:
+57        return []
+58    validated_elements = []
+59    for xml_element in xml_elements:
+60        if not _validate_xml_relatives(xml_element, config_field):
+61            continue
+62        found = _check_xml_names_and_attribs_exist(xml_element, config_field)
+63        if found:
+64            validated_elements.append(xml_element)
+65    return validated_elements
+
+ + +

Matches the xml_elements to the config field requirements for +values, attributes, and relative xml element requirements for +values, and attributes. Returns list of matching fields.

+ +
Parameters
+ +
    +
  • xml_elements: A list of xml elements
    • +
  • config_field: A dictionary of the requirements of the field.
    • +
+ +
Returns
+ +
+

A list of matched xml elemnts

+
+
+ + +
+
+ +
+ + def + validate_xml_attributes(xml_element, config_field) -> list: + + + +
+ + 
264def validate_xml_attributes(xml_element, config_field) -> list:
+265    """
+266    Validates an xml element by checking if the configured attribute(s) exist
+267    and match the configured regex pattern for the value of the attribute.
+268    If the xml element, and it's subsequent attribute(s), do not pass the checks,
+269    based upon what is in the configuration, then an error message is added to
+270    the validation results.
+271
+272    :param xml_element: The xml element that will have its attributes validated.
+273    :param config_field: A dictionary that contains the configuration that
+274        specifies what the attribute(s) for the xml element should be named
+275        and how the values should be patterned.
+276    :return: A list of errors or an empty list.  If the list is empty then
+277        the validation was successful.
+278    """
+279    config_attribs = config_field.get("attributes")
+280    if not config_attribs:
+281        return []
+282
+283    error_messages = []
+284    for attribute in config_attribs:
+285        if "attributeName" in attribute:
+286            attribute_name = attribute.get("attributeName")
+287            attribute_value = xml_element.get(attribute_name)
+288            if not attribute_value:
+289                message = _get_ecr_custom_message(
+290                    config_field,
+291                    f"Could not find attribute '{attribute_name}'. "
+292                    + f"{get_xml_element_details(xml_element, config_field)}",
+293                )
+294                error_messages.append(message)
+295        if "regEx" in attribute:
+296            pattern = re.compile(attribute.get("regEx"))
+297            if (not attribute_value) or (not pattern.match(attribute_value)):
+298                message = _get_ecr_custom_message(
+299                    config_field,
+300                    f"Attribute: '{attribute_name}'"
+301                    + " not in expected format. "
+302                    + f"{get_xml_element_details(xml_element, config_field)}",
+303                )
+304                error_messages.append(message)
+305    return error_messages
+
+ + +

Validates an xml element by checking if the configured attribute(s) exist +and match the configured regex pattern for the value of the attribute. +If the xml element, and it's subsequent attribute(s), do not pass the checks, +based upon what is in the configuration, then an error message is added to +the validation results.

+ +
Parameters
+ +
    +
  • xml_element: The xml element that will have its attributes validated.
    • +
  • config_field: A dictionary that contains the configuration that +specifies what the attribute(s) for the xml element should be named +and how the values should be patterned.
    • +
+ +
Returns
+ +
+

A list of errors or an empty list. If the list is empty then + the validation was successful.

+
+
+ + +
+
+ +
+ + def + _validate_xml_related_element(xml_element, cda_path, relative_config) -> str: + + + +
+ + 
145def _validate_xml_related_element(xml_element, cda_path, relative_config) -> str:
+146    """
+147    Validates a related xml element, to the key xml element,
+148    against the configured rules for the related element's
+149    location to the key element and the existence of values
+150    and attributes for the related xml element.  If the relative
+151    xml element meets all the configured criteria, then the xml
+152    element will be returned, otherwise None.
+153
+154    :param xml_element: The key xml element.
+155    :param cda_path: A string representing the location of the key xml element.
+156    :param config_field: A dictionary of the requirements for the related xml element.
+157    :return: A related xml element if the related xml element meets the configured
+158        criteria, otherwise return None.
+159    """
+160    if xml_element is None:
+161        return None
+162    relative_cda_path = relative_config.get("cdaPath")
+163    relative_tag_name = re.search(
+164        r"(?!\:)[a-zA-z]+\w$", relative_config.get("cdaPath")
+165    ).group(0)
+166
+167    xml_iterator = _get_xml_relative_iterator(cda_path, relative_cda_path, xml_element)
+168
+169    # if there are no related xml elements based upon the
+170    # specified cda paths then just return None
+171    if xml_iterator is None or len(xml_iterator) == 0:
+172        return None
+173
+174    # sibling, descendant, child iterators
+175    # are of different type than ancestors
+176    # It's not clear why, but this prevents errors
+177    # and ensures that we have the correct element tag
+178    # and related element
+179    try:
+180        related_xml_element_tag = xml_iterator.tag
+181        related_xml_element = xml_iterator
+182    except Exception as e:
+183        print(e)
+184        related_xml_element = None
+185        related_xml_element_tag = None
+186
+187    for xi in xml_iterator:
+188        # loop through iterator - unless it's
+189        # a ancestor - if that is the case then
+190        # the iterator itself IS the proper related
+191        # element and we want to use that - otherwise
+192        # loop through the list of elements in the list
+193        if related_xml_element_tag is None:
+194            related_xml_element = xi
+195            related_xml_element_tag = related_xml_element.tag
+196
+197        if relative_tag_name in related_xml_element_tag:
+198            relative_validated = _check_xml_names_and_attribs_exist(
+199                xml_element=related_xml_element, config_field=relative_config
+200            )
+201            relative_attributes_validated = validate_xml_attributes(
+202                related_xml_element, relative_config
+203            )
+204
+205            if not relative_validated or len(relative_attributes_validated) != 0:
+206                return None
+207            else:
+208                return related_xml_element
+209        else:
+210            related_xml_element = None
+211            related_xml_element_tag = None
+
+ + +

Validates a related xml element, to the key xml element, +against the configured rules for the related element's +location to the key element and the existence of values +and attributes for the related xml element. If the relative +xml element meets all the configured criteria, then the xml +element will be returned, otherwise None.

+ +
Parameters
+ +
    +
  • xml_element: The key xml element.
    • +
  • cda_path: A string representing the location of the key xml element.
    • +
  • config_field: A dictionary of the requirements for the related xml element.
    • +
+ +
Returns
+ +
+

A related xml element if the related xml element meets the configured + criteria, otherwise return None.

+
+
+ + +
+
+ +
+ + def + _validate_xml_relatives(xml_element, config_field) -> bool: + + + +
+ + 
68def _validate_xml_relatives(xml_element, config_field) -> bool:
+69    """
+70    Gets the 'relatives' portion of the configuration for a particular
+71    field and validates that the required attributes and values in the
+72    relative xml paths are present.
+73
+74    :param xml_element: The key xml element that is being evaluated as
+75        well as its relative xml elements.
+76    :param config_field: A dictionary of the requirements for validating
+77        the key xml elements relative xml elements.
+78    :return: Bool - True if all relative xml elements match the criteria
+79        specified in the configuration, otherwise false.
+80    """
+81    relatives_valid = True
+82    relatives = config_field.get("relatives")
+83    if relatives is None:
+84        return relatives_valid
+85    for relative_config in relatives:
+86        base_cda_path = config_field.get("cdaPath")
+87        if (
+88            _validate_xml_related_element(
+89                xml_element=xml_element,
+90                cda_path=base_cda_path,
+91                relative_config=relative_config,
+92            )
+93            is None
+94        ):
+95            relatives_valid = False
+96    return relatives_valid
+
+ + +

Gets the 'relatives' portion of the configuration for a particular +field and validates that the required attributes and values in the +relative xml paths are present.

+ +
Parameters
+ +
    +
  • xml_element: The key xml element that is being evaluated as +well as its relative xml elements.
    • +
  • config_field: A dictionary of the requirements for validating +the key xml elements relative xml elements.
    • +
+ +
Returns
+ +
+

Bool - True if all relative xml elements match the criteria + specified in the configuration, otherwise false.

+
+
+ + +
+
+ +
+ + def + validate_xml_value(xml_element, config_field) -> list: + + + +
+ + 
418def validate_xml_value(xml_element, config_field) -> list:
+419    """
+420    Validates the value of an xml element (ie... between the tags) based upon
+421    validating the xml element exists within the relative xml element location
+422    based upon the configuration of the parent of the xml element.
+423    Then it validates that the value of xml element matches the value pattern
+424    listed in the config.
+425
+426    :param xml_element: The key xml element being evaluated.
+427    :param config_field: A dictionary that contains the configuration information
+428        necessary to validate the location and value of the key xml element
+429    :return: A list of error messages if validation fails, otherwise an
+430        empty list.
+431    """
+432    # If value for xml element is not required return empty list
+433    if not config_field.get("textRequired"):
+434        return []
+435
+436    value = "".join(xml_element.itertext())
+437    config_regex = config_field.get("regEx")
+438    # first check if the value matches the regex from the config
+439    if config_regex is not None:
+440        pattern = re.compile(config_regex)
+441        if pattern.match(value) is None:
+442            message = _get_ecr_custom_message(
+443                config_field,
+444                "The field value does not exist or "
+445                + "doesn't match the following pattern: '"
+446                + config_regex
+447                + f"'. For the {get_xml_element_details(xml_element, config_field)}",
+448            )
+449            return [message]
+450        else:
+451            return []
+452    # otherwise just verify that a value is present
+453    else:
+454        if value is not None and value != "":
+455            return []
+456        else:
+457            message = _get_ecr_custom_message(
+458                config_field,
+459                "Field does not have a value. "
+460                + f"{get_xml_element_details(xml_element, config_field)}",
+461            )
+462            return [message]
+
+ + +

Validates the value of an xml element (ie... between the tags) based upon +validating the xml element exists within the relative xml element location +based upon the configuration of the parent of the xml element. +Then it validates that the value of xml element matches the value pattern +listed in the config.

+ +
Parameters
+ +
    +
  • xml_element: The key xml element being evaluated.
    • +
  • config_field: A dictionary that contains the configuration information +necessary to validate the location and value of the key xml element
    • +
+ +
Returns
+ +
+

A list of error messages if validation fails, otherwise an + empty list.

+
+
+ + +
+
+ +
+ + def + _get_xml_relatives_details(relatives_config: dict) -> list: + + + +
+ + 
350def _get_xml_relatives_details(relatives_config: dict) -> list:
+351    """
+352    Gets the name and configured attribute information for
+353    any relative xml elements based upon the relative config
+354    section passed in and formats this information into
+355    a single string for use in the validation messages.
+356
+357    :param relatives_config: A dictionary of the configured requirements
+358        for the relative xml element.
+359    :return: A single string, in a list, containing the information about the
+360        relative xml element and its attribute(s).
+361    """
+362    relative_string = []
+363    if relatives_config:
+364        relative_string.append("Related elements:")
+365        for rel_config in relatives_config:
+366            relative_field_name = rel_config.get("name")
+367            relative_name = (
+368                ["Field name: '" + relative_field_name + "'"]
+369                if relative_field_name
+370                else []
+371            )
+372            config_related_attributes = rel_config.get("attributes")
+373            relative_attributes = (
+374                ["Attributes:"] + _get_xml_attributes(None, config_related_attributes)
+375                if config_related_attributes
+376                else []
+377            )
+378            relative_string += relative_name
+379            relative_string += relative_attributes
+380    return relative_string
+
+ + +

Gets the name and configured attribute information for +any relative xml elements based upon the relative config +section passed in and formats this information into +a single string for use in the validation messages.

+ +
Parameters
+ +
    +
  • relatives_config: A dictionary of the configured requirements +for the relative xml element.
    • +
+ +
Returns
+ +
+

A single string, in a list, containing the information about the + relative xml element and its attribute(s).

+
+
+ + +
+
+
+ ECR_NAMESPACES = + + {'hl7': 'urn:hl7-org:v3', 'xsi': 'http://www.w3.org/2005/Atom', 'cda': 'urn:hl7-org:v3', 'sdtc': 'urn:hl7-org:sdtc', 'voc': 'http://www.lantanagroup.com/voc'} + + +
+ + + + +
+
+ + \ No newline at end of file diff --git a/docs/v1.2.7/sdk/search.js b/docs/v1.2.7/sdk/search.js new file mode 100644 index 0000000000..adc25f1f81 --- /dev/null +++ b/docs/v1.2.7/sdk/search.js @@ -0,0 +1,46 @@ +window.pdocSearch = (function(){ +/** elasticlunr - http://weixsong.github.io * Copyright (C) 2017 Oliver Nightingale * Copyright (C) 2017 Wei Song * MIT Licensed */!function(){function e(e){if(null===e||"object"!=typeof e)return e;var t=e.constructor();for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n]);return t}var t=function(e){var n=new t.Index;return n.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),e&&e.call(n,n),n};t.version="0.9.5",lunr=t,t.utils={},t.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),t.utils.toString=function(e){return void 0===e||null===e?"":e.toString()},t.EventEmitter=function(){this.events={}},t.EventEmitter.prototype.addListener=function(){var e=Array.prototype.slice.call(arguments),t=e.pop(),n=e;if("function"!=typeof t)throw new TypeError("last argument must be a function");n.forEach(function(e){this.hasHandler(e)||(this.events[e]=[]),this.events[e].push(t)},this)},t.EventEmitter.prototype.removeListener=function(e,t){if(this.hasHandler(e)){var n=this.events[e].indexOf(t);-1!==n&&(this.events[e].splice(n,1),0==this.events[e].length&&delete this.events[e])}},t.EventEmitter.prototype.emit=function(e){if(this.hasHandler(e)){var t=Array.prototype.slice.call(arguments,1);this.events[e].forEach(function(e){e.apply(void 0,t)},this)}},t.EventEmitter.prototype.hasHandler=function(e){return e in this.events},t.tokenizer=function(e){if(!arguments.length||null===e||void 0===e)return[];if(Array.isArray(e)){var n=e.filter(function(e){return null===e||void 0===e?!1:!0});n=n.map(function(e){return t.utils.toString(e).toLowerCase()});var i=[];return n.forEach(function(e){var n=e.split(t.tokenizer.seperator);i=i.concat(n)},this),i}return e.toString().trim().toLowerCase().split(t.tokenizer.seperator)},t.tokenizer.defaultSeperator=/[\s\-]+/,t.tokenizer.seperator=t.tokenizer.defaultSeperator,t.tokenizer.setSeperator=function(e){null!==e&&void 0!==e&&"object"==typeof e&&(t.tokenizer.seperator=e)},t.tokenizer.resetSeperator=function(){t.tokenizer.seperator=t.tokenizer.defaultSeperator},t.tokenizer.getSeperator=function(){return t.tokenizer.seperator},t.Pipeline=function(){this._queue=[]},t.Pipeline.registeredFunctions={},t.Pipeline.registerFunction=function(e,n){n in t.Pipeline.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+n),e.label=n,t.Pipeline.registeredFunctions[n]=e},t.Pipeline.getRegisteredFunction=function(e){return e in t.Pipeline.registeredFunctions!=!0?null:t.Pipeline.registeredFunctions[e]},t.Pipeline.warnIfFunctionNotRegistered=function(e){var n=e.label&&e.label in this.registeredFunctions;n||t.utils.warn("Function is not registered with pipeline. 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e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();o

\n"}, "phdi.cloud": {"fullname": "phdi.cloud", "modulename": "phdi.cloud", "kind": "module", "doc": "

\n"}, "phdi.cloud.azure": {"fullname": "phdi.cloud.azure", "modulename": "phdi.cloud.azure", "kind": "module", "doc": "

\n"}, "phdi.cloud.azure.AzureCredentialManager": {"fullname": "phdi.cloud.azure.AzureCredentialManager", "modulename": "phdi.cloud.azure", "qualname": "AzureCredentialManager", "kind": "class", "doc": "

Defines a credential manager used for connecting to Azure.

\n", "bases": "phdi.cloud.core.BaseCredentialManager"}, "phdi.cloud.azure.AzureCredentialManager.__init__": {"fullname": "phdi.cloud.azure.AzureCredentialManager.__init__", "modulename": "phdi.cloud.azure", "qualname": "AzureCredentialManager.__init__", "kind": "function", "doc": "

Creates a new AzureCredentialManager object.

\n\n
Parameters
\n\n
    \n
  • resource_location: The URL or other location of the requested resource.
    • \n
  • scope: A space-delimited list of scopes to limit access to resource.\nDefault: None
    • \n
\n", "signature": "(resource_location: str = None, scope: str = None)"}, "phdi.cloud.azure.AzureCredentialManager.get_credential_object": {"fullname": "phdi.cloud.azure.AzureCredentialManager.get_credential_object", "modulename": "phdi.cloud.azure", "qualname": "AzureCredentialManager.get_credential_object", "kind": "function", "doc": "

Gets an Azure-specific credential object.

\n\n
Returns
\n\n
\n

An instance of one of the *Credential objects from the\n azure.identity package.

\n
\n", "signature": "(self) -> object:", "funcdef": "def"}, "phdi.cloud.azure.AzureCredentialManager.get_access_token": {"fullname": "phdi.cloud.azure.AzureCredentialManager.get_access_token", "modulename": "phdi.cloud.azure", "qualname": "AzureCredentialManager.get_access_token", "kind": "function", "doc": "

Obtains an access token from the Azure identity provider. Returns the\naccess token string, refreshed if expired or force_refresh is specified.

\n\n
Parameters
\n\n
    \n
  • force_refresh: True if a new token should be requested, regardless\nof expiration timestamp. False otherwise. Default: False
    • \n
\n\n
Returns
\n\n
\n

An Azure access token.

\n
\n", "signature": "(self, force_refresh: bool = False) -> str:", "funcdef": "def"}, "phdi.cloud.azure.AzureCredentialManager.get_secret": {"fullname": "phdi.cloud.azure.AzureCredentialManager.get_secret", "modulename": "phdi.cloud.azure", "qualname": "AzureCredentialManager.get_secret", "kind": "function", "doc": "

Get the value of a secret from an Azure key vault given the names of the vault\nand the secret.

\n\n
Parameters
\n\n
    \n
  • secret_name: The name of the secret whose value should be retrieved from\nthe key vault.
    • \n
  • key_vault_name: The name of the key vault where the secret is stored.
    • \n
\n\n
Returns
\n\n
\n

The value of the secret specified by secret_name.

\n
\n", "signature": "(self, secret_name: str, key_vault_name: str) -> str:", "funcdef": "def"}, "phdi.cloud.azure.AzureCloudContainerConnection": {"fullname": "phdi.cloud.azure.AzureCloudContainerConnection", "modulename": "phdi.cloud.azure", "qualname": "AzureCloudContainerConnection", "kind": "class", "doc": "

Defines a connection used for interacting with cloud storage in Azure.

\n", "bases": "phdi.cloud.core.BaseCloudStorageConnection"}, "phdi.cloud.azure.AzureCloudContainerConnection.__init__": {"fullname": "phdi.cloud.azure.AzureCloudContainerConnection.__init__", "modulename": "phdi.cloud.azure", "qualname": "AzureCloudContainerConnection.__init__", "kind": "function", "doc": "

Creates a new AzureCloudContainerConnection object.

\n\n
Parameters
\n\n
    \n
  • storage_account_url: The storage account location of the requested\nresource.
    • \n
  • cred_manager: The credential manager used to authenticate to the\nFHIR server.
    • \n
\n", "signature": "(\tstorage_account_url: str,\tcred_manager: phdi.cloud.azure.AzureCredentialManager)"}, "phdi.cloud.azure.AzureCloudContainerConnection.download_object": {"fullname": "phdi.cloud.azure.AzureCloudContainerConnection.download_object", "modulename": "phdi.cloud.azure", "qualname": "AzureCloudContainerConnection.download_object", "kind": "function", "doc": "

Downloads a blob from storage and returns it as a string or bytes.

\n\n
Parameters
\n\n
    \n
  • container_name: The name of the container containing object to download.
    • \n
  • filename: The location of the file within Azure blob storage.
    • \n
  • encoding: The encoding applied to the downloaded content. If set to None\nthen the blob contents will be returned as bytes. Default: UTF-8
    • \n
\n\n
Returns
\n\n
\n

A character blob as a string from the given container and filename.

\n
\n", "signature": "(\tself,\tcontainer_name: str,\tfilename: str,\tencoding: Literal[None, str] = 'UTF-8') -> Literal[str, bytes]:", "funcdef": "def"}, "phdi.cloud.azure.AzureCloudContainerConnection.upload_object": {"fullname": "phdi.cloud.azure.AzureCloudContainerConnection.upload_object", "modulename": "phdi.cloud.azure", "qualname": "AzureCloudContainerConnection.upload_object", "kind": "function", "doc": "

Uploads the content of a given message to Azure blob storage.\nThe message can be passed either as a raw string or as JSON.

\n\n
Parameters
\n\n
    \n
  • message: The contents of a message, encoded either as a\nstring or a JSON-formatted dictionary.
    • \n
  • container_name: The name of the target container for upload.
    • \n
  • filename: The location of file to upload within Azure blob storage.
    • \n
\n", "signature": "(\tself,\tmessage: Union[str, dict],\tcontainer_name: str,\tfilename: str) -> None:", "funcdef": "def"}, "phdi.cloud.azure.AzureCloudContainerConnection.list_containers": {"fullname": "phdi.cloud.azure.AzureCloudContainerConnection.list_containers", "modulename": "phdi.cloud.azure", "qualname": "AzureCloudContainerConnection.list_containers", "kind": "function", "doc": "

Lists names for this CloudContainerConnection's containers.

\n\n
Returns
\n\n
\n

A list of container names.

\n
\n", "signature": "(self) -> List[str]:", "funcdef": "def"}, "phdi.cloud.azure.AzureCloudContainerConnection.list_objects": {"fullname": "phdi.cloud.azure.AzureCloudContainerConnection.list_objects", "modulename": "phdi.cloud.azure", "qualname": "AzureCloudContainerConnection.list_objects", "kind": "function", "doc": "

Lists names for objects within a container.

\n\n
Parameters
\n\n
    \n
  • container_name: The name of the container to look for objects.
    • \n
  • prefix: Filter the objects returned to filenames beginning\nwith this value.
    • \n
\n\n
Returns
\n\n
\n

A list of names for objects in given container.

\n
\n", "signature": "(self, container_name: str, prefix: str = '') -> List[str]:", "funcdef": "def"}, "phdi.cloud.azure.AzureCloudContainerConnection.blob_exists": {"fullname": "phdi.cloud.azure.AzureCloudContainerConnection.blob_exists", "modulename": "phdi.cloud.azure", "qualname": "AzureCloudContainerConnection.blob_exists", "kind": "function", "doc": "

Check if a blob exists within a container given its name and the name of the\ncontainer.

\n\n
Parameters
\n\n
    \n
  • container_name: The name of the container to look for the blob in.
    • \n
  • filename: The name of the blob to check the existence of.
    • \n
  • prefix: Filter the objects returned to filenames beginning\nwith this value.
    • \n
\n\n
Returns
\n\n
\n

A boolean of true if the file exists and false if it does not.

\n
\n", "signature": "(self, container_name: str, filename: str) -> bool:", "funcdef": "def"}, "phdi.cloud.core": {"fullname": "phdi.cloud.core", "modulename": "phdi.cloud.core", "kind": "module", "doc": "

\n"}, "phdi.cloud.core.BaseCredentialManager": {"fullname": "phdi.cloud.core.BaseCredentialManager", "modulename": "phdi.cloud.core", "qualname": "BaseCredentialManager", "kind": "class", "doc": "

Provides a common interface for managing service credentials.

\n", "bases": "abc.ABC"}, "phdi.cloud.core.BaseCredentialManager.get_credential_object": {"fullname": "phdi.cloud.core.BaseCredentialManager.get_credential_object", "modulename": "phdi.cloud.core", "qualname": "BaseCredentialManager.get_credential_object", "kind": "function", "doc": "

Gets a cloud-specific credential object.

\n\n
Returns
\n\n
\n

A credential object.

\n
\n", "signature": "(self) -> object:", "funcdef": "def"}, "phdi.cloud.core.BaseCredentialManager.get_access_token": {"fullname": "phdi.cloud.core.BaseCredentialManager.get_access_token", "modulename": "phdi.cloud.core", "qualname": "BaseCredentialManager.get_access_token", "kind": "function", "doc": "

Gets an access token using the managed credentials.

\n\n
Returns
\n\n
\n

An access token.

\n
\n", "signature": "(self) -> str:", "funcdef": "def"}, "phdi.cloud.core.BaseCloudStorageConnection": {"fullname": "phdi.cloud.core.BaseCloudStorageConnection", "modulename": "phdi.cloud.core", "qualname": "BaseCloudStorageConnection", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "phdi.cloud.core.BaseCloudStorageConnection.download_object": {"fullname": "phdi.cloud.core.BaseCloudStorageConnection.download_object", "modulename": "phdi.cloud.core", "qualname": "BaseCloudStorageConnection.download_object", "kind": "function", "doc": "

Downloads a blob from storage.

\n\n
Parameters
\n\n
    \n
  • container_name: The name of the container containing object to download.
    • \n
  • filename: The location of file within storage.
    • \n
  • encoding: The character encoding applied to the downloaded content.
    • \n
\n\n
Returns
\n\n
\n

The stream parameter, if supplied. Otherwise a new stream object\n containing blob content.

\n
\n", "signature": "(self, container_name: str, filename: str, encoding: str = 'utf-8') -> str:", "funcdef": "def"}, "phdi.cloud.core.BaseCloudStorageConnection.upload_object": {"fullname": "phdi.cloud.core.BaseCloudStorageConnection.upload_object", "modulename": "phdi.cloud.core", "qualname": "BaseCloudStorageConnection.upload_object", "kind": "function", "doc": "

Uploads the content of a given message to blob storage.\nThe message can be passed either as a raw string or as JSON.

\n\n
Parameters
\n\n
    \n
  • message: The contents of a message, encoded either as a\nstring or in a JSON format.
    • \n
  • container_name: The name of the target container for upload.
    • \n
  • filename: The location of file within storage container.
    • \n
\n", "signature": "(\tself,\tmessage: Union[str, dict],\tcontainer_name: str,\tfilename: str) -> None:", "funcdef": "def"}, "phdi.cloud.core.BaseCloudStorageConnection.list_containers": {"fullname": "phdi.cloud.core.BaseCloudStorageConnection.list_containers", "modulename": "phdi.cloud.core", "qualname": "BaseCloudStorageConnection.list_containers", "kind": "function", "doc": "

Lists names for this CloudContainerConnection's containers.

\n\n
Returns
\n\n
\n

A list of container names.

\n
\n", "signature": "(self) -> List[str]:", "funcdef": "def"}, "phdi.cloud.core.BaseCloudStorageConnection.list_objects": {"fullname": "phdi.cloud.core.BaseCloudStorageConnection.list_objects", "modulename": "phdi.cloud.core", "qualname": "BaseCloudStorageConnection.list_objects", "kind": "function", "doc": "

Lists names for objects within a container.

\n\n
Parameters
\n\n
    \n
  • container_name: The name of the container to look for objects.
    • \n
  • prefix: Filter the objects returned to filenames beginning\nwith this value.
    • \n
\n\n
Returns
\n\n
\n

A list of objects within a container.

\n
\n", "signature": "(self, container_name: str, prefix: str) -> List[str]:", "funcdef": "def"}, "phdi.cloud.gcp": {"fullname": "phdi.cloud.gcp", "modulename": "phdi.cloud.gcp", "kind": "module", "doc": "

\n"}, "phdi.cloud.gcp.GcpCredentialManager": {"fullname": "phdi.cloud.gcp.GcpCredentialManager", "modulename": "phdi.cloud.gcp", "qualname": "GcpCredentialManager", "kind": "class", "doc": "

Provides a GCP-specific credential manager.

\n", "bases": "phdi.cloud.core.BaseCredentialManager"}, "phdi.cloud.gcp.GcpCredentialManager.__init__": {"fullname": "phdi.cloud.gcp.GcpCredentialManager.__init__", "modulename": "phdi.cloud.gcp", "qualname": "GcpCredentialManager.__init__", "kind": "function", "doc": "

Creates a new GcpCredentialManager object.

\n\n
Parameters
\n\n
    \n
  • scope: A list of scopes to limit access to resource.
    • \n
\n", "signature": "(scope: list = None)"}, "phdi.cloud.gcp.GcpCredentialManager.get_credential_object": {"fullname": "phdi.cloud.gcp.GcpCredentialManager.get_credential_object", "modulename": "phdi.cloud.gcp", "qualname": "GcpCredentialManager.get_credential_object", "kind": "function", "doc": "

Gets a GCP-specific credential object.

\n\n
Returns
\n\n
\n

A scoped instance of the Credentials class from google.auth\n package, refreshed if necessary.

\n
\n", "signature": "(self) -> google.auth.credentials.Credentials:", "funcdef": "def"}, "phdi.cloud.gcp.GcpCredentialManager.get_project_id": {"fullname": "phdi.cloud.gcp.GcpCredentialManager.get_project_id", "modulename": "phdi.cloud.gcp", "qualname": "GcpCredentialManager.get_project_id", "kind": "function", "doc": "

Gets the ID of the current GCP project.

\n\n
Returns
\n\n
\n

The current GCP project ID.

\n
\n", "signature": "(self) -> str:", "funcdef": "def"}, "phdi.cloud.gcp.GcpCredentialManager.get_access_token": {"fullname": "phdi.cloud.gcp.GcpCredentialManager.get_access_token", "modulename": "phdi.cloud.gcp", "qualname": "GcpCredentialManager.get_access_token", "kind": "function", "doc": "

Obtains an access token from GCP.

\n\n
Returns
\n\n
\n

The access token, refreshed if necessary.

\n
\n", "signature": "(self) -> str:", "funcdef": "def"}, "phdi.cloud.gcp.GcpCloudStorageConnection": {"fullname": "phdi.cloud.gcp.GcpCloudStorageConnection", "modulename": "phdi.cloud.gcp", "qualname": "GcpCloudStorageConnection", "kind": "class", "doc": "

Defines a connection used for interacting with cloud storage in GCP.

\n", "bases": "phdi.cloud.core.BaseCloudStorageConnection"}, "phdi.cloud.gcp.GcpCloudStorageConnection.__init__": {"fullname": "phdi.cloud.gcp.GcpCloudStorageConnection.__init__", "modulename": "phdi.cloud.gcp", "qualname": "GcpCloudStorageConnection.__init__", "kind": "function", "doc": "

Creates a new GcpCloudContainerConnection object.

\n", "signature": "()"}, "phdi.cloud.gcp.GcpCloudStorageConnection.download_object": {"fullname": "phdi.cloud.gcp.GcpCloudStorageConnection.download_object", "modulename": "phdi.cloud.gcp", "qualname": "GcpCloudStorageConnection.download_object", "kind": "function", "doc": "

Downloads a character blob from storage and returns it as a string.

\n\n
Parameters
\n\n
    \n
  • container_name: The name of the bucket containing object to download.
    • \n
  • filename: The location of file within GCP blob storage.
    • \n
  • encoding: The encoding applied to the downloaded content.
    • \n
\n\n
Returns
\n\n
\n

A character blob (as a string) from given bucket and filename.

\n
\n", "signature": "(self, container_name: str, filename: str, encoding: str = 'utf-8') -> str:", "funcdef": "def"}, "phdi.cloud.gcp.GcpCloudStorageConnection.upload_object": {"fullname": "phdi.cloud.gcp.GcpCloudStorageConnection.upload_object", "modulename": "phdi.cloud.gcp", "qualname": "GcpCloudStorageConnection.upload_object", "kind": "function", "doc": "

Uploads the content of a given message to GCP blob storage.\nThe message can be passed either as a raw string or as JSON.

\n\n
Parameters
\n\n
    \n
  • message: The contents of a message, encoded either as a\nstring or in a JSON-formatted dictionary.
    • \n
  • container_name: The name of the target bucket for upload.
    • \n
  • filename: The location of file within GCP blob storage.
    • \n
\n", "signature": "(\tself,\tmessage: Union[str, dict],\tcontainer_name: str,\tfilename: str,\tcontent_type='application/json') -> None:", "funcdef": "def"}, "phdi.cloud.gcp.GcpCloudStorageConnection.list_containers": {"fullname": "phdi.cloud.gcp.GcpCloudStorageConnection.list_containers", "modulename": "phdi.cloud.gcp", "qualname": "GcpCloudStorageConnection.list_containers", "kind": "function", "doc": "

Lists bucket names in storage.

\n\n
Returns
\n\n
\n

A list of bucket names in storage.

\n
\n", "signature": "(self) -> List[str]:", "funcdef": "def"}, "phdi.cloud.gcp.GcpCloudStorageConnection.list_objects": {"fullname": "phdi.cloud.gcp.GcpCloudStorageConnection.list_objects", "modulename": "phdi.cloud.gcp", "qualname": "GcpCloudStorageConnection.list_objects", "kind": "function", "doc": "

Lists names for objects within a bucket.

\n\n
Parameters
\n\n
    \n
  • container_name: The name of the bucket to look for objects.
    • \n
  • prefix: Filter the objects returned to filenames beginning\nwith this value.
    • \n
\n\n
Returns
\n\n
\n

A list of names for objects in given bucket.

\n
\n", "signature": "(self, container_name: str, prefix: str = '') -> List[str]:", "funcdef": "def"}, "phdi.containers": {"fullname": "phdi.containers", "modulename": "phdi.containers", "kind": "module", "doc": "

\n"}, "phdi.containers.base_service": {"fullname": "phdi.containers.base_service", "modulename": "phdi.containers.base_service", "kind": "module", "doc": "

\n"}, "phdi.containers.base_service.StatusResponse": {"fullname": "phdi.containers.base_service.StatusResponse", "modulename": "phdi.containers.base_service", "qualname": "StatusResponse", "kind": "class", "doc": "

The schema for the response from the health check endpoint.

\n", "bases": "pydantic.main.BaseModel"}, "phdi.containers.base_service.BaseService": {"fullname": "phdi.containers.base_service.BaseService", "modulename": "phdi.containers.base_service", "qualname": "BaseService", "kind": "class", "doc": "

\n"}, "phdi.containers.base_service.BaseService.__init__": {"fullname": "phdi.containers.base_service.BaseService.__init__", "modulename": "phdi.containers.base_service", "qualname": "BaseService.__init__", "kind": "function", "doc": "

Initialize a BaseService instance.

\n\n
Parameters
\n\n
    \n
  • service_name: The name of the service.
    • \n
  • service_path: The path to used to access the service from a gateway.
    • \n
  • description_path: The path to a markdown file containing a description of\nthe service.
    • \n
  • include_health_check_endpoint: If True, the standard DIBBs health check\nendpoint will be added.
    • \n
  • license_info: If empty, the standard DIBBs Creative Commons Zero v1.0\nUniversal license will be used. The other available option is to use the\nMIT license.
    • \n
\n", "signature": "(\tservice_name: str,\tservice_path: str,\tdescription_path: str,\tinclude_health_check_endpoint: bool = True,\tlicense_info: Literal['CreativeCommonsZero', 'MIT'] = 'CreativeCommonsZero')"}, "phdi.containers.base_service.BaseService.add_path_rewrite_middleware": {"fullname": "phdi.containers.base_service.BaseService.add_path_rewrite_middleware", "modulename": "phdi.containers.base_service", "qualname": "BaseService.add_path_rewrite_middleware", "kind": "function", "doc": "

Add middleware to the FastAPI instance to strip the service_path\nfrom the URL path if it is present. This is useful when the service\nis behind a gateway that is using a path-based routing strategy.

\n", "signature": "(self):", "funcdef": "def"}, "phdi.containers.base_service.BaseService.add_health_check_endpoint": {"fullname": "phdi.containers.base_service.BaseService.add_health_check_endpoint", "modulename": "phdi.containers.base_service", "qualname": "BaseService.add_health_check_endpoint", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.containers.base_service.BaseService.start": {"fullname": "phdi.containers.base_service.BaseService.start", "modulename": "phdi.containers.base_service", "qualname": "BaseService.start", "kind": "function", "doc": "

Return a FastAPI instance with DIBBs metadata set. If\ninclude_health_check_endpoint is True, then the health check endpoint\nwill be added.

\n\n
Returns
\n\n
\n

The FastAPI instance.

\n
\n", "signature": "(self) -> fastapi.applications.FastAPI:", "funcdef": "def"}, "phdi.fhir": {"fullname": "phdi.fhir", "modulename": "phdi.fhir", "kind": "module", "doc": "

\n"}, "phdi.fhir.cloud": {"fullname": "phdi.fhir.cloud", "modulename": "phdi.fhir.cloud", "kind": "module", "doc": "

\n"}, "phdi.fhir.cloud.download_from_fhir_export_response": {"fullname": "phdi.fhir.cloud.download_from_fhir_export_response", "modulename": "phdi.fhir.cloud", "qualname": "download_from_fhir_export_response", "kind": "function", "doc": "

Accepts the export response content as specified here:\nhttps://hl7.org/fhir/uv/bulkdata/export/index.html#response---complete-status

\n\n

Loops through the \"output\" array and yields the resource_type (e.g., Patient)\nalong with TextIO wrapping ndjson content.

\n\n
Parameters
\n\n
    \n
  • export_response: A dictionary holding the final export response.
    • \n
  • cred_manager: The credential manager used to authenticate to the\nstorage account.
    • \n
\n\n
Returns
\n\n
\n

An iterator of tuples. Each tuple is comprised of:

\n \n
    \n
  • FHIR resource type (str)
    • \n
  • Export file content (io.TextIO)
    • \n
\n
\n", "signature": "(\texport_response: dict,\tcred_manager: phdi.cloud.azure.AzureCredentialManager) -> Iterator[Tuple[str, TextIO]]:", "funcdef": "def"}, "phdi.fhir.conversion": {"fullname": "phdi.fhir.conversion", "modulename": "phdi.fhir.conversion", "kind": "module", "doc": "

\n"}, "phdi.fhir.conversion.add_rr_data_to_eicr": {"fullname": "phdi.fhir.conversion.add_rr_data_to_eicr", "modulename": "phdi.fhir.conversion", "qualname": "add_rr_data_to_eicr", "kind": "function", "doc": "

Extracts relevant fields from an RR document, and inserts them into a\ngiven eICR document. Ensures that the eICR contains properly formatted\nRR fields, including templateId, id, code, title, effectiveTime,\nconfidentialityCode, and corresponding entries; and required format tags.

\n\n
Parameters
\n\n
    \n
  • rr: A serialized xml format reportability response (RR) document.
    • \n
  • ecr: A serialized xml format electronic initial case report (eICR) document.
    • \n
\n\n
Returns
\n\n
\n

An xml format eICR document with additional fields extracted from the RR.

\n
\n", "signature": "(rr, ecr):", "funcdef": "def"}, "phdi.fhir.conversion.convert_to_fhir": {"fullname": "phdi.fhir.conversion.convert_to_fhir", "modulename": "phdi.fhir.conversion", "qualname": "convert_to_fhir", "kind": "function", "doc": "

Converts a given message from either HL7 v2 (pipe-delimited flat file) or CCDA (XML)\ninto FHIR format (JSON) for further processing using the FHIR server. Standardizes\ndatetimes in HL7v2 messages before conversion.

\n\n

This function uses a containerized version of the\nAzure FHIR Converter.

\n\n

If conversion succeeds, a requests.Response object will be returned with the\nconversion response. Otherwise, a ConversionError is raised, with the\nrequests.Response available as a property for troubleshooting and reporting\npurposes.

\n\n
Parameters
\n\n
    \n
  • message: The raw message that needs to be converted to\nFHIR. Currently, only HL7v2 or CCDA are supported.
    • \n
  • url: A URL that points to the location of the converter API.
    • \n
  • cred_manager: Service used to get an access token used to\nmake a request.
    • \n
  • headers: JSON-type dictionary of headers to make the request with.
    • \n
  • use_default_ccda: Whether to default to the\nbase \"CCD\" root template if a resource's LOINC code doesn't\nmap to a specific supported template (Optional, default is No)
    • \n
\n\n
Raises
\n\n
    \n
  • requests.HttpError: If the HTTP request was unsuccessful.
    • \n
  • ConversionError: If the message could not be converted.
    • \n
\n\n
Returns
\n\n
\n

A requests.Response object

\n
\n", "signature": "(\tmessage: str,\turl: str,\tcred_manager: phdi.cloud.core.BaseCredentialManager = None,\theaders: dict = {},\tuse_default_ccda=False):", "funcdef": "def"}, "phdi.fhir.geospatial": {"fullname": "phdi.fhir.geospatial", "modulename": "phdi.fhir.geospatial", "kind": "module", "doc": "

\n"}, "phdi.fhir.geospatial.BaseFhirGeocodeClient": {"fullname": "phdi.fhir.geospatial.BaseFhirGeocodeClient", "modulename": "phdi.fhir.geospatial", "qualname": "BaseFhirGeocodeClient", "kind": "class", "doc": "

Represents a vendor-agnostic geocoder client designed to process\nFHIR-based data. Implementing classes should define methods to\ngeocode from both bundles and resources. Callers should use the\nprovided interface functions (e.g., geocode_resource) to interact with\nthe underlying vendor-specific client property.

\n", "bases": "abc.ABC"}, "phdi.fhir.geospatial.BaseFhirGeocodeClient.geocode_resource": {"fullname": "phdi.fhir.geospatial.BaseFhirGeocodeClient.geocode_resource", "modulename": "phdi.fhir.geospatial", "qualname": "BaseFhirGeocodeClient.geocode_resource", "kind": "function", "doc": "

Performs geocoding, using the implementing client, on the provided resource,\nwhich is passed in as a dictionary.

\n\n
Parameters
\n\n
    \n
  • resource: A FHIR resource to be geocoded.
    • \n
  • overwrite: If true, resource is modified in-place;\nif false, a copy of resource modified and returned. Default: True
    • \n
\n\n
Returns
\n\n
\n

The geocoded resource as a dict.

\n
\n", "signature": "(self, resource: dict, overwrite=True) -> dict:", "funcdef": "def"}, "phdi.fhir.geospatial.BaseFhirGeocodeClient.geocode_bundle": {"fullname": "phdi.fhir.geospatial.BaseFhirGeocodeClient.geocode_bundle", "modulename": "phdi.fhir.geospatial", "qualname": "BaseFhirGeocodeClient.geocode_bundle", "kind": "function", "doc": "

Performs geocoding, using the implementing client, on all supported resources in\nthe provided FHIR bundle which is passed in as a dictionary.

\n\n
Parameters
\n\n
    \n
  • bundle: A bundle of FHIR resources.
    • \n
  • overwrite: If true, bundle is modified in-place;\nif false, a copy of bundle modified and returned. Default: True
    • \n
\n\n
Returns
\n\n
\n

The geocoded FHIR bundle as a dict.

\n
\n", "signature": "(self, bundle: dict, overwrite=True) -> dict:", "funcdef": "def"}, "phdi.fhir.geospatial.SmartyFhirGeocodeClient": {"fullname": "phdi.fhir.geospatial.SmartyFhirGeocodeClient", "modulename": "phdi.fhir.geospatial", "qualname": "SmartyFhirGeocodeClient", "kind": "class", "doc": "

Implementation of a geocoding client designed to handle FHIR-\nformatted data using the SmartyStreets API.\nRequires an authorization ID as well as an authentication token\nin order to build a street lookup client.

\n", "bases": "phdi.fhir.geospatial.core.BaseFhirGeocodeClient"}, "phdi.fhir.geospatial.SmartyFhirGeocodeClient.__init__": {"fullname": "phdi.fhir.geospatial.SmartyFhirGeocodeClient.__init__", "modulename": "phdi.fhir.geospatial", "qualname": "SmartyFhirGeocodeClient.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsmarty_auth_id: str,\tsmarty_auth_token: str,\tlicenses: list[str] = ['us-standard-cloud'])"}, "phdi.fhir.geospatial.SmartyFhirGeocodeClient.geocode_client": {"fullname": "phdi.fhir.geospatial.SmartyFhirGeocodeClient.geocode_client", "modulename": "phdi.fhir.geospatial", "qualname": "SmartyFhirGeocodeClient.geocode_client", "kind": "variable", "doc": "

An instance of the underlying Smarty client.\nAllows the FHIR wrapper to access a SmartyStreets-\nspecific connection client without instantiating its own\ncopy. Provides access to the respective geocode_from_str\nand geocode_from_dict methods if they're desired.

\n", "annotation": ": smartystreets_python_sdk.us_street.client.Client"}, "phdi.fhir.geospatial.SmartyFhirGeocodeClient.geocode_resource": {"fullname": "phdi.fhir.geospatial.SmartyFhirGeocodeClient.geocode_resource", "modulename": "phdi.fhir.geospatial", "qualname": "SmartyFhirGeocodeClient.geocode_resource", "kind": "function", "doc": "

Performs geocoding on one or more addresses in a given FHIR\nresource and returns either the result or a copy thereof.\nCurrently supported resource types are:

\n\n
    \n
  • Patient
    • \n
\n\n
Parameters
\n\n
    \n
  • resource: The resource whose addresses should be geocoded.
    • \n
  • overwrite: If true, resource is modified in-place;\nif false, a copy of resource modified and returned. Default: True
    • \n
\n\n
Returns
\n\n
\n

The geocoded resource as a dict.

\n
\n", "signature": "(self, resource: dict, overwrite=True) -> dict:", "funcdef": "def"}, "phdi.fhir.geospatial.SmartyFhirGeocodeClient.geocode_bundle": {"fullname": "phdi.fhir.geospatial.SmartyFhirGeocodeClient.geocode_bundle", "modulename": "phdi.fhir.geospatial", "qualname": "SmartyFhirGeocodeClient.geocode_bundle", "kind": "function", "doc": "

Geocodes on all resources in a given FHIR bundle whose\nresource type is among those supported by the PHDI SDK. Currently,\nthis includes:

\n\n
    \n
  • Patient
    • \n
\n\n
Parameters
\n\n
    \n
  • bundle: A bundle of FHIR resources.
    • \n
  • overwrite: If true, bundle is modified in-place;\nif false, a copy of bundle modified and returned. Default: True
    • \n
\n\n
Returns
\n\n
\n

The FHIR bundle with geocoded address(es).

\n
\n", "signature": "(self, bundle: dict, overwrite=True) -> dict:", "funcdef": "def"}, "phdi.fhir.geospatial.CensusFhirGeocodeClient": {"fullname": "phdi.fhir.geospatial.CensusFhirGeocodeClient", "modulename": "phdi.fhir.geospatial", "qualname": "CensusFhirGeocodeClient", "kind": "class", "doc": "

Implementation of a geocoding client designed to handle FHIR-\nformatted data using the Census API.

\n", "bases": "phdi.fhir.geospatial.core.BaseFhirGeocodeClient"}, "phdi.fhir.geospatial.CensusFhirGeocodeClient.geocode_resource": {"fullname": "phdi.fhir.geospatial.CensusFhirGeocodeClient.geocode_resource", "modulename": "phdi.fhir.geospatial", "qualname": "CensusFhirGeocodeClient.geocode_resource", "kind": "function", "doc": "

Performs geocoding on one or more addresses in a given FHIR\nresource and returns either the result or a copy thereof. The original street\nname, number, and any secondary address line information are returned in the\noriginal form.\nCurrently supported resource types are:

\n\n
- Patient\n
\n\n
Parameters
\n\n
    \n
  • resource: The resource whose addresses should be geocoded.
    • \n
  • overwrite: Whether to save the geocoding information over\nthe raw data, or to create a copy of the given data and write\nover that instead. Defaults to True (write over given data).
    • \n
\n\n
Returns
\n\n
\n

Geocoded resource as a dict.

\n
\n", "signature": "(self, resource: dict, overwrite=True) -> dict:", "funcdef": "def"}, "phdi.fhir.geospatial.CensusFhirGeocodeClient.geocode_bundle": {"fullname": "phdi.fhir.geospatial.CensusFhirGeocodeClient.geocode_bundle", "modulename": "phdi.fhir.geospatial", "qualname": "CensusFhirGeocodeClient.geocode_bundle", "kind": "function", "doc": "

Performs geocoding on all resources in a given FHIR bundle whose\nresource type is among those supported by the PHDI SDK. Currently,\nthis includes:

\n\n
- Patient\n
\n\n
Parameters
\n\n
    \n
  • bundle: A bundle of fhir resources.
    • \n
  • overwrite: Whether to overwrite the address data in the given\nbundle's resources (True), or whether to create a copy of the bundle\nand overwrite that instead (False). Defaults to True.
    • \n
\n\n
Returns
\n\n
\n

A FHIR bundle with geocoded address(es).

\n
\n", "signature": "(self, bundle: dict, overwrite=True) -> dict:", "funcdef": "def"}, "phdi.fhir.harmonization": {"fullname": "phdi.fhir.harmonization", "modulename": "phdi.fhir.harmonization", "kind": "module", "doc": "

\n"}, "phdi.fhir.harmonization.double_metaphone_bundle": {"fullname": "phdi.fhir.harmonization.double_metaphone_bundle", "modulename": "phdi.fhir.harmonization", "qualname": "double_metaphone_bundle", "kind": "function", "doc": "

Performs the double metaphone algorithm on each name of each patient in a\ngiven FHIR bundle.

\n\n
Parameters
\n\n
    \n
  • bundle: A FHIR bundle of data containing one or more patient\nresources.
    • \n
  • overwrite: If true, data is modified in-place; if false, a\ncopy of data modified and returned. Default: True.
    • \n
\n\n
Returns
\n\n
\n

A dictionary mapping the FHIR IDs of patients in the bundle\n to lists holding the double metaphone representations of their\n names for each FHIR use case their resource includes.

\n
\n", "signature": "(bundle: dict, overwrite=True) -> dict:", "funcdef": "def"}, "phdi.fhir.harmonization.double_metaphone_patient": {"fullname": "phdi.fhir.harmonization.double_metaphone_patient", "modulename": "phdi.fhir.harmonization", "qualname": "double_metaphone_patient", "kind": "function", "doc": "

Performs the double metaphone algorithm for each name in a given patient\nresource. The algorithm is performed on each component of the name (first,\nmiddle, last), and the resulting representations are ordered in a list\nsuch that the first element is first name, the last element is last name,\nand all other elements are one or more middle names in the order of\nname presentation. These lists of phonetic representations are stored as\nthe values of dictionaries whose keys are the FHIR uses of the name in\nthe patient resource (e.g. \"official\"), and all such dictionaries are\nreturned to the caller in a list ordered the same as the names within\nthe given resource.

\n\n
Parameters
\n\n
    \n
  • patient: A FHIR-formatted JSON dictionary representing a patient\nresource.
    • \n
  • dmeta: An optional existing instantiation of a double metaphone\nobject for use in bulk processing.
    • \n
  • overwrite: If true, data is modified in-place; if false, a\ncopy of data modified and returned. Default: True.
    • \n
\n\n
Returns
\n\n
\n

A list of dictionaries mapping FHIR uses to the phonetic\n representations of names associated with those uses, in presentation\n order (first, middle, last).

\n
\n", "signature": "(patient: dict, dmeta=None, overwrite=True) -> dict:", "funcdef": "def"}, "phdi.fhir.harmonization.standardize_names": {"fullname": "phdi.fhir.harmonization.standardize_names", "modulename": "phdi.fhir.harmonization", "qualname": "standardize_names", "kind": "function", "doc": "

Standardizes all names contained in a given FHIR bundle or a FHIR resource. The\ndefault standardization behavior is our defined non-numeric, space-trimming, full\ncapitalization standardization, but other modes may be specified.

\n\n
Parameters
\n\n
    \n
  • data: A FHIR-formatted JSON dict.
    • \n
  • trim: Whether leading/trailing whitespace should be removed. Default: True
    • \n
  • case: The type of casing that should be used. Default: upper
    • \n
  • remove_numbers: If true, delete numeric characters; if false leave numbers\nin place. Default: True
    • \n
  • overwrite: If true, data is modified in-place;\nif false, a copy of data modified and returned. Default: True
    • \n
\n\n
Returns
\n\n
\n

The bundle or resource with names appropriately standardized.

\n
\n", "signature": "(\tdata: dict,\ttrim: bool = True,\tcase: Literal['upper', 'lower', 'title'] = 'upper',\tremove_numbers: bool = True,\toverwrite: bool = True) -> dict:", "funcdef": "def"}, "phdi.fhir.harmonization.standardize_phones": {"fullname": "phdi.fhir.harmonization.standardize_phones", "modulename": "phdi.fhir.harmonization", "qualname": "standardize_phones", "kind": "function", "doc": "

Standardizes all phone numbers in a given FHIR bundle or a FHIR resource.\nStandardization is done according to the underlying standardize_phone\nfunction in phdi.harmonization.

\n\n
Parameters
\n\n
    \n
  • data: A FHIR bundle or FHIR-formatted JSON dict.
    • \n
  • overwrite: If true, data is modified in-place;\nif false, a copy of data modified and returned. Default: True
    • \n
\n\n
Returns
\n\n
\n

The bundle or resource with phones appropriately standardized.

\n
\n", "signature": "(data: dict, overwrite=True) -> dict:", "funcdef": "def"}, "phdi.fhir.harmonization.standardize_dob": {"fullname": "phdi.fhir.harmonization.standardize_dob", "modulename": "phdi.fhir.harmonization", "qualname": "standardize_dob", "kind": "function", "doc": "

Standardizes all birth dates in a given FHIR bundle or a FHIR resource.\nStandardization is done according to the underlying standardize_dob function in\nphdi.harmonization. The final birthDate will follow the FHIR STu3/R4 format\nof YYYY-MM-DD which will be stored in the Patient resource.

\n\n
Parameters
\n\n
    \n
  • data: A FHIR bundle or FHIR-formatted JSON dict.
    • \n
  • format: A python DateTime format used to parse the birthDate within\nthe Patient resource. Default: %Y-%m-%d (also known as YYYY-MM-DD)
    • \n
  • overwrite: If true, data is modified in-place;\nif false, a copy of data modified and returned. Default: True
    • \n
\n\n
Returns
\n\n
\n

The bundle or resource with bith dates appropriately standardized.

\n
\n", "signature": "(data: dict, format: str = '%Y-%m-%d', overwrite=True) -> dict:", "funcdef": "def"}, "phdi.fhir.linkage": {"fullname": "phdi.fhir.linkage", "modulename": "phdi.fhir.linkage", "kind": "module", "doc": "

\n"}, "phdi.fhir.linkage.add_patient_identifier_in_bundle": {"fullname": "phdi.fhir.linkage.add_patient_identifier_in_bundle", "modulename": "phdi.fhir.linkage", "qualname": "add_patient_identifier_in_bundle", "kind": "function", "doc": "

Given a FHIR resource bundle:

\n\n
    \n
  • Identifies all patient resource(s) in the bundle
    • \n
  • Adds the hash string to the list of identifiers held in that patient resource
    • \n
\n\n
Parameters
\n\n
    \n
  • bundle: The FHIR bundle for whose patients to add a linking identifier.
    • \n
  • salt_str: The salt to use with the hash. This is intended to prevent\nreverse engineering of the PII used to create the hash.
    • \n
  • overwrite: If true, bundle is modified in-place;\nif false, a copy of bundle modified and returned. Default: True
    • \n
\n\n
Returns
\n\n
\n

The bundle, resources updated with additional patient identifier.

\n
\n", "signature": "(bundle: dict, salt_str: str, overwrite: bool = True) -> dict:", "funcdef": "def"}, "phdi.fhir.linkage.add_patient_identifier": {"fullname": "phdi.fhir.linkage.add_patient_identifier", "modulename": "phdi.fhir.linkage", "qualname": "add_patient_identifier", "kind": "function", "doc": "

Given a FHIR Patient resource:

\n\n
    \n
  • Extracts name, DOB, and address information
    • \n
  • Computes a unique hash string based on these fields
    • \n
  • Adds the hash string to resource
    • \n
\n\n
Parameters
\n\n
    \n
  • patient_resource: The FHIR patient resource to add a linking identifier.
    • \n
  • salt_str: The salt to use with the hash. This is intended to prevent\nreverse engineering of the PII used to create the hash.
    • \n
  • overwrite: If true, patient_resource is modified in-place;\nif false, a copy of patient_resource modified and returned. Default: True
    • \n
\n\n
Returns
\n\n
\n

The resource updated with additional patient identifier.

\n
\n", "signature": "(patient_resource: dict, salt_str: str, overwrite: bool = True):", "funcdef": "def"}, "phdi.fhir.tabulation": {"fullname": "phdi.fhir.tabulation", "modulename": "phdi.fhir.tabulation", "kind": "module", "doc": "

\n"}, "phdi.fhir.tabulation.drop_invalid": {"fullname": "phdi.fhir.tabulation.drop_invalid", "modulename": "phdi.fhir.tabulation", "qualname": "drop_invalid", "kind": "function", "doc": "

Removes resources from tabulated data if the resource contains an invalid value, as\nspecified in the invalid_values field in a user-defined schema. Users may provide\ninvalid values as a list, including empty string values (\"\") and\nNone/null values (null).

\n\n
Parameters
\n\n
    \n
  • data: A list of lists containing data for a table. The first list in\nthe data value is a list of headers serving as the columns, and all subsequent\nlists are rows in the table.
    • \n
  • schema: A declarative, user-defined specification, for one or more tables,\nthat defines the metadata, properties, and columns of those tables as they\nrelate to FHIR resources.
    • \n
  • table_name: Name of the table to drop invalid values.
    • \n
  • return: A list of lists, without rows of data derived from the FHIR\nresources and elements that contained invalid values.\nThe first list in the data value is a list of headers serving as the\ncolumns, and all subsequent lists are rows in the table.
    • \n
\n", "signature": "(data: List[list], schema: Dict, table_name: str) -> List[list]:", "funcdef": "def"}, "phdi.fhir.tabulation.extract_data_from_fhir_search": {"fullname": "phdi.fhir.tabulation.extract_data_from_fhir_search", "modulename": "phdi.fhir.tabulation", "qualname": "extract_data_from_fhir_search", "kind": "function", "doc": "

Performs a FHIR search, continuously using the \"next\" url to perform\nsearch continuations until no additional search results are available.\nReturns a dictionary containing the data from all search responses.

\n\n
Parameters
\n\n
    \n
  • search_url: The URL to a FHIR server with search criteria.
    • \n
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • \n
\n\n
Raises
\n\n
    \n
  • KeyError: If the query returns no data from the FHIR server.
    • \n
\n\n
Returns
\n\n
\n

A list of FHIR resources returned from the search.

\n
\n", "signature": "(\tsearch_url: str,\tcred_manager: phdi.cloud.core.BaseCredentialManager = None) -> List[dict]:", "funcdef": "def"}, "phdi.fhir.tabulation.extract_data_from_fhir_search_incremental": {"fullname": "phdi.fhir.tabulation.extract_data_from_fhir_search_incremental", "modulename": "phdi.fhir.tabulation", "qualname": "extract_data_from_fhir_search_incremental", "kind": "function", "doc": "

Performs a FHIR search for a single page of data and returns a dictionary containing\nthe data and a next URL. If there is no next URL (this is the last page of data),\nthen return None as the next URL.

\n\n
Parameters
\n\n
    \n
  • search_url: The URL to a FHIR server with search criteria.
    • \n
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • \n
\n\n
Raises
\n\n
    \n
  • requests.HttpError: If the HTTP request was unsuccessful.
    • \n
\n\n
Returns
\n\n
\n

Tuple containing single page of data as a list of dictionaries and the next\n URL.

\n
\n", "signature": "(\tsearch_url: str,\tcred_manager: phdi.cloud.core.BaseCredentialManager = None) -> Tuple[List[dict], str]:", "funcdef": "def"}, "phdi.fhir.tabulation.extract_data_from_schema": {"fullname": "phdi.fhir.tabulation.extract_data_from_schema", "modulename": "phdi.fhir.tabulation", "qualname": "extract_data_from_schema", "kind": "function", "doc": "

Performs a full FHIR search for each table in the specified schema,\nand returns a dictionary mapping the table name to corresponding search results.

\n\n
Parameters
\n\n
    \n
  • schema: A declarative, user-defined specification, for one or more tables,\nthat defines the metadata, properties, and columns of those tables as they\nrelate to FHIR resources.
    • \n
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • \n
\n\n
Returns
\n\n
\n

A dict containing the mapping of a table and its columns, grouped by\n table name, to a list of FHIR resource element results returned from\n the search for each subsequent table name.

\n
\n", "signature": "(\tschema: dict,\tfhir_url: str,\tcred_manager: phdi.cloud.core.BaseCredentialManager = None) -> Dict[str, List[dict]]:", "funcdef": "def"}, "phdi.fhir.tabulation.tabulate_data": {"fullname": "phdi.fhir.tabulation.tabulate_data", "modulename": "phdi.fhir.tabulation", "qualname": "tabulate_data", "kind": "function", "doc": "

Transforms a list of FHIR bundle resource entries into a tabular\nformat (given by a list of lists) using a user-defined schema.\nTabulation works using a two-pass procedure. First, resources\nthat are associated with one another in the provided schema\n(identified by the presence of a reference_location field in\none of the schema's columns) are grouped together. For each\ntable, one type of resource serves as the \"anchor\", which\ndefines the number of rows in the table, while referenced\nresources are either \"forwards\" or \"reverse\" references,\ndepending on their relationship to the anchor type. Second,\nthe aggregated resources are parsed for value extraction using\nthe schema's columns, and the results are stored in a list of\nlists for that table. The first entry in this list are the headers\nof the data, taken from the schema. This functions performs the\nabove procedure on one table from the schema, specified by a\ntable name.

\n\n
Parameters
\n\n
    \n
  • data: A list of FHIR bundle resource entries to tabulate.
    • \n
  • schema: A declarative, user-defined specification, for one or more tables,\nthat defines the metadata, properties, and columns of those tables as they\nrelate to FHIR resources.
    • \n
  • table_name: A string specifying the name of a table defined\nin the given schema.
    • \n
\n\n
Raises
\n\n
    \n
  • KeyError: If the given table_name does not occur in the\nprovided schema.
    • \n
\n\n
Returns
\n\n
\n

A list of lists denoting the tabulated form of the data.\n The first list is a list of headers serving as the columns,\n and all subsequent lists are rows in the table.

\n
\n", "signature": "(data: List[dict], schema: dict, table_name: str) -> List[list]:", "funcdef": "def"}, "phdi.fhir.transport": {"fullname": "phdi.fhir.transport", "modulename": "phdi.fhir.transport", "kind": "module", "doc": "

\n"}, "phdi.fhir.transport.http_request_with_reauth": {"fullname": "phdi.fhir.transport.http_request_with_reauth", "modulename": "phdi.fhir.transport", "qualname": "http_request_with_reauth", "kind": "function", "doc": "

First, calls phdi.transport.http.http_request_with_retry(). If the first call\nfails with an authorization error (HTTP status 401), obtains a new token using the\ncred_manager. If the original request had an Authorization header, replaces\nit with the new token and re-initiates\nphdi.transport.http.http_request_with_retry().

\n\n
Parameters
\n\n
    \n
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • \n
  • url: The url at which to make the HTTP request.
    • \n
  • retry_count: The number of times to retry the request, if the\nfirst attempt fails.
    • \n
  • request_type: The type of request to be made.
    • \n
  • allowed_methods: The list of allowed HTTP request methods (i.e.,\nPOST, PUT, etc.) for the specific URL and query.
    • \n
  • headers: JSON-type dictionary of headers to make the request with,\nincluding Authorization and content-type.
    • \n
  • data: JSON data in the case that the request requires data to be\nposted. Default: None
    • \n
\n\n
Returns
\n\n
\n

A requests.Request object containing the response from the FHIR server.

\n
\n", "signature": "(\tcred_manager: phdi.cloud.core.BaseCredentialManager,\turl: str,\tretry_count: int,\trequest_type: Literal['GET', 'POST'],\tallowed_methods: List[str],\theaders: dict,\tdata: dict = None) -> requests.models.Response:", "funcdef": "def"}, "phdi.fhir.transport.fhir_server_get": {"fullname": "phdi.fhir.transport.fhir_server_get", "modulename": "phdi.fhir.transport", "qualname": "fhir_server_get", "kind": "function", "doc": "

Submits a GET request to a FHIR server given a url and access token for\nauthentication.

\n\n
Parameters
\n\n
    \n
  • url: A URL specifying a GET request on a FHIR server.
    • \n
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • \n
\n\n
Returns
\n\n
\n

A requests.Request object containing the response from the FHIR server.

\n
\n", "signature": "(\turl: str,\tcred_manager: phdi.cloud.core.BaseCredentialManager) -> requests.models.Response:", "funcdef": "def"}, "phdi.fhir.transport.upload_bundle_to_fhir_server": {"fullname": "phdi.fhir.transport.upload_bundle_to_fhir_server", "modulename": "phdi.fhir.transport", "qualname": "upload_bundle_to_fhir_server", "kind": "function", "doc": "

Uploads a FHIR resource bundle to the FHIR server.

\n\n
Parameters
\n\n
    \n
  • bundle: A FHIR bundle (type \"batch\" or \"transaction\") to post. Each entry in\nthe bundle must contain a request element in addition to a resource.\nThe FHIR API provides additional details on creating\nFHIR-conformant batch/transaction\nbundles.
    • \n
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • \n
  • fhir_url: The url of the FHIR server to upload to.
    • \n
  • max_bundle_size: The maximum number of resources per bundle to upload to\nthe FHIR server.
    • \n
\n\n
Returns
\n\n
\n

A requests.Response object containing the response from the FHIR server.

\n
\n", "signature": "(\tbundle: dict,\tcred_manager: phdi.cloud.core.BaseCredentialManager,\tfhir_url: str,\tmax_bundle_size: int = 500) -> list[requests.models.Response]:", "funcdef": "def"}, "phdi.fhir.transport.export_from_fhir_server": {"fullname": "phdi.fhir.transport.export_from_fhir_server", "modulename": "phdi.fhir.transport", "qualname": "export_from_fhir_server", "kind": "function", "doc": "

Initiates a FHIR $export operation, polls until it completes, and returns the\nsuccessful result.

\n\n
Parameters
\n\n
    \n
  • cred_manager: The credential manager used to authenticate to the FHIR server.
    • \n
  • fhir_url: The FHIR server base URL.
    • \n
  • export_scope: Either Patient or Group/[id] as specified in the FHIR spec\n(https://hl7.org/fhir/uv/bulkdata/export/index.html#bulk-data-kick-off-request).
    • \n
  • since: A FHIR instant (https: //build.fhir.org/datatypes.html#instant)\ninstructing the export to include only resources created or modified after the\nspecified instant.
    • \n
  • resource_type: A comma-delimited list of FHIR resource types to include\nin exported files.
    • \n
  • container: The name of the storage container used to store exported files.
    • \n
  • poll_step: The number of seconds to wait between poll requests, waiting\nfor export files to be generated.
    • \n
  • poll_timeout: The maximum number of seconds to wait for export files to\nbe generated.
    • \n
\n\n
Raises
\n\n
    \n
  • polling.TimeoutException: If the FHIR server continually returns a 202\nstatus indicating in progress until the timeout is reached.
    • \n
\n\n
Returns
\n\n
\n

The JSON-formatted HTTP response of a completed export operation\n as a dictionary.

\n
\n", "signature": "(\tcred_manager: phdi.cloud.core.BaseCredentialManager,\tfhir_url: str,\texport_scope: str = '',\tsince: str = '',\tresource_type: str = '',\tcontainer: str = '',\tpoll_step: float = 30,\tpoll_timeout: float = 300) -> dict:", "funcdef": "def"}, "phdi.fhir.utils": {"fullname": "phdi.fhir.utils", "modulename": "phdi.fhir.utils", "kind": "module", "doc": "

\n"}, "phdi.fhir.utils.apply_selection_criteria": {"fullname": "phdi.fhir.utils.apply_selection_criteria", "modulename": "phdi.fhir.utils", "qualname": "apply_selection_criteria", "kind": "function", "doc": "

Returns value(s), according to the selection criteria, from a given list of values\nparsed from a FHIR resource. A single string value is returned - if the selected\nvalue is a complex structure (list or dict), it is converted to a string.

\n\n
Parameters
\n\n
    \n
  • value: A list containing the values parsed from a FHIR resource.
    • \n
  • selection_criteria: A string indicating which element(s) of a list to select.
    • \n
\n\n
Returns
\n\n
\n

Value(s) parsed from a FHIR resource that conform to the selection\n criteria.

\n
\n", "signature": "(\tvalue: List[Any],\tselection_criteria: Literal['first', 'last', 'random', 'all']) -> Union[str, List]:", "funcdef": "def"}, "phdi.fhir.utils.extract_value_with_resource_path": {"fullname": "phdi.fhir.utils.extract_value_with_resource_path", "modulename": "phdi.fhir.utils", "qualname": "extract_value_with_resource_path", "kind": "function", "doc": "

Yields a single value from a resource based on a provided fhir_path.\nIf the path doesn't map to an extant value in the first, returns\nNone instead.

\n\n
Parameters
\n\n
    \n
  • resource: The FHIR resource to extract a value from.
    • \n
  • path: The fhir_path at which the value can be found in the\nresource.
    • \n
  • selection_criteria: A string dictating which value to extract,\nif multiple values exist at the path location.
    • \n
\n\n
Returns
\n\n
\n

The extracted value, or None if the value doesn't exist.

\n
\n", "signature": "(\tresource: dict,\tpath: str,\tselection_criteria: Literal['first', 'last', 'random', 'all'] = 'first') -> Optional[Any]:", "funcdef": "def"}, "phdi.fhir.utils.find_entries_by_resource_type": {"fullname": "phdi.fhir.utils.find_entries_by_resource_type", "modulename": "phdi.fhir.utils", "qualname": "find_entries_by_resource_type", "kind": "function", "doc": "

Collect all entries of a specific type in a bundle of FHIR data and\nreturn references to them in a list.

\n\n
Parameters
\n\n
    \n
  • bundle: The FHIR bundle to search for resource entries.
    • \n
  • resource_type: The type of FHIR resource to find.
    • \n
\n\n
Returns
\n\n
\n

A list holding all entries of the requested resource type that were\n found in the input bundle.

\n
\n", "signature": "(bundle: dict, resource_type: str) -> List[dict]:", "funcdef": "def"}, "phdi.fhir.utils.get_field": {"fullname": "phdi.fhir.utils.get_field", "modulename": "phdi.fhir.utils", "qualname": "get_field", "kind": "function", "doc": "

Finds an instance of the specified field in a given FHIR- formatted JSON dictionary.\nOptionally, a particular \"use\" of a field can be provided such that only instances\nwith that purpose are considered. For example, find the name for a patient that has\na \"use\" of \"official\". \"Use\" here refers to the FHIR-based usage of classifying a\nvalue's purpose. If no instance of a field with the requested use case can be found,\ninstead return a specified default value for the field.

\n\n
Parameters
\n\n
    \n
  • resource: A FHIR-formatted resource.
    • \n
  • field: The field to extract.
    • \n
  • index: The nth element of the field to return. If the index is greater than\nthe number of elements in the field, the last element will be returned. If the\nindex is less than 1, the first element will be returned. Default: 1.
    • \n
  • use: The 'use' the field must have to qualify for selection. Default: None.
    • \n
  • require_use: If True and no elements of the specified field have that\nuse, none will be returned. If False and no elements of the specified field have\nthat use, the nth element as indicated by the index parameter will be returned.\nThis parameter is ignored if no use is specified. Default: True.
    • \n
\n\n
Returns
\n\n
\n

The first instance of the field value matching the desired\n use, or a default field value if a match couldn't be found.

\n
\n", "signature": "(\tresource: dict,\tfield: str,\tindex: int = 1,\tuse: str = None,\trequire_use: bool = True) -> Any:", "funcdef": "def"}, "phdi.fhir.utils.get_fhirpathpy_parser": {"fullname": "phdi.fhir.utils.get_fhirpathpy_parser", "modulename": "phdi.fhir.utils", "qualname": "get_fhirpathpy_parser", "kind": "function", "doc": "

Accepts a FHIRPath expression, and returns a callable function\nwhich returns the evaluated value at fhirpath_expression for\na specified FHIR resource.

\n\n
Parameters
\n\n
    \n
  • fhirpath_expression: The FHIRPath expression to evaluate.
    • \n
\n\n
Returns
\n\n
\n

A function that, when called passing in a FHIR resource,\n will return value at fhirpath_expression.

\n
\n", "signature": "(fhirpath_expression: str) -> Callable:", "funcdef": "def"}, "phdi.fhir.utils.get_one_line_address": {"fullname": "phdi.fhir.utils.get_one_line_address", "modulename": "phdi.fhir.utils", "qualname": "get_one_line_address", "kind": "function", "doc": "

Extracts a one-line string representation of an address from a\nJSON dictionary holding address information.

\n\n
Parameters
\n\n
    \n
  • address: The FHIR-formatted address.
    • \n
\n\n
Returns
\n\n
\n

A one-line string representation of an address.

\n
\n", "signature": "(address: dict) -> str:", "funcdef": "def"}, "phdi.geospatial": {"fullname": "phdi.geospatial", "modulename": "phdi.geospatial", "kind": "module", "doc": "

\n"}, "phdi.geospatial.GeocodeResult": {"fullname": "phdi.geospatial.GeocodeResult", "modulename": "phdi.geospatial", "qualname": "GeocodeResult", "kind": "class", "doc": "

Represents a successful geocoding response.\nBased on the field nomenclature of a FHIR address, specified at\nhttps://www.hl7.org/fhir/datatypes.html#Address.

\n"}, "phdi.geospatial.GeocodeResult.__init__": {"fullname": "phdi.geospatial.GeocodeResult.__init__", "modulename": "phdi.geospatial", "qualname": "GeocodeResult.__init__", "kind": "function", "doc": "

\n", "signature": "(\tline: List[str],\tcity: str,\tstate: str,\tpostal_code: str,\tcounty_fips: str,\tlat: float,\tlng: float,\tdistrict: Optional[str] = None,\tcountry: Optional[str] = None,\tcounty_name: Optional[str] = None,\tprecision: Optional[str] = None,\tgeoid: Optional[str] = None,\tcensus_tract: Optional[str] = None,\tcensus_block: Optional[str] = None)"}, "phdi.geospatial.BaseGeocodeClient": {"fullname": "phdi.geospatial.BaseGeocodeClient", "modulename": "phdi.geospatial", "qualname": "BaseGeocodeClient", "kind": "class", "doc": "

Represents a vendor-agnostic geocoder client. Requires implementing\nclasses to define methods to geocode from both strings and dictionaries.\nCallers should use the provided interface functions (e.g., geocode_from_str)\nto interact with the underlying vendor-specific client property.

\n", "bases": "abc.ABC"}, "phdi.geospatial.BaseGeocodeClient.geocode_from_str": {"fullname": "phdi.geospatial.BaseGeocodeClient.geocode_from_str", "modulename": "phdi.geospatial", "qualname": "BaseGeocodeClient.geocode_from_str", "kind": "function", "doc": "

Geocodes the provided address, which is formatted as a string.

\n\n
Parameters
\n\n
    \n
  • address: The address to geocode, given as a string.
    • \n
  • overwrite: If true, resource is modified in-place;\nif false, a copy of resource modified and returned. Default: True
    • \n
\n\n
Returns
\n\n
\n

A geocoded address (if valid result) or None (if no valid result).

\n
\n", "signature": "(self, address: str) -> Optional[phdi.geospatial.core.GeocodeResult]:", "funcdef": "def"}, "phdi.geospatial.BaseGeocodeClient.geocode_from_dict": {"fullname": "phdi.geospatial.BaseGeocodeClient.geocode_from_dict", "modulename": "phdi.geospatial", "qualname": "BaseGeocodeClient.geocode_from_dict", "kind": "function", "doc": "

Geocodes the provided address, which is formatted as a dictionary.

\n\n

The given dictionary should conform to standard nomenclature around address\nfields, including:

\n\n
    \n
  • street: the number and street address
    • \n
  • street2: additional street level information (if needed)
    • \n
  • apartment: apartment or suite number (if needed)
    • \n
  • city: city to geocode
    • \n
  • state: state to geocode
    • \n
  • postal_code: the postal code to use
    • \n
  • urbanization: urbanization code for area, sector, or regional
    • \n
  • development: (only used for Puerto Rican addresses)
    • \n
\n\n

There is no minimum number of fields that must be specified to use this\nfunction; however, a minimum of street, city, and state are suggested\nfor the best matches.

\n\n
Parameters
\n\n
    \n
  • address: A dictionary with fields outlined above.
    • \n
\n\n
Returns
\n\n
\n

A geocoded address (if valid result) or None (if no valid result).

\n
\n", "signature": "(self, address: dict) -> Optional[phdi.geospatial.core.GeocodeResult]:", "funcdef": "def"}, "phdi.geospatial.SmartyGeocodeClient": {"fullname": "phdi.geospatial.SmartyGeocodeClient", "modulename": "phdi.geospatial", "qualname": "SmartyGeocodeClient", "kind": "class", "doc": "

Represents a PHDI-supplied geocoding client using the Smarty API.\nRequires an authorization ID as well as an authentication token\nin order to build a street lookup client.

\n", "bases": "phdi.geospatial.core.BaseGeocodeClient"}, "phdi.geospatial.SmartyGeocodeClient.__init__": {"fullname": "phdi.geospatial.SmartyGeocodeClient.__init__", "modulename": "phdi.geospatial", "qualname": "SmartyGeocodeClient.__init__", "kind": "function", "doc": "

\n", "signature": "(\tsmarty_auth_id: str,\tsmarty_auth_token: str,\tlicenses: list[str] = ['us-standard-cloud'])"}, "phdi.geospatial.SmartyGeocodeClient.client": {"fullname": "phdi.geospatial.SmartyGeocodeClient.client", "modulename": "phdi.geospatial", "qualname": "SmartyGeocodeClient.client", "kind": "variable", "doc": "

This property:

\n\n
    \n
  1. defines a private instance variable __client
    2. \n
  2. makes it accessible through the use of .client()
    3. \n
\n\n

This property holds a Smarty-specific connection client that\nallows a user to geocode without directly referencing the\nunderlying vendor service client.

\n", "annotation": ": smartystreets_python_sdk.us_street.client.Client"}, "phdi.geospatial.SmartyGeocodeClient.geocode_from_str": {"fullname": "phdi.geospatial.SmartyGeocodeClient.geocode_from_str", "modulename": "phdi.geospatial", "qualname": "SmartyGeocodeClient.geocode_from_str", "kind": "function", "doc": "

Geocodes the provided address, which is formatted as a string. If the\nresult cannot be latitude- or longitude-located, then Smarty failed\nto precisely geocode the address, so no result is returned. Raises\nan error if the provided address is empty.

\n\n
Parameters
\n\n
    \n
  • address: The address to geocode, given as a string.
    • \n
\n\n
Raises
\n\n
    \n
  • ValueError: When the address does not include street number and name.
    • \n
\n\n
Returns
\n\n
\n

A geocoded address (if valid result) or None (if no valid result).

\n
\n", "signature": "(self, address: str) -> Optional[phdi.geospatial.core.GeocodeResult]:", "funcdef": "def"}, "phdi.geospatial.SmartyGeocodeClient.geocode_from_dict": {"fullname": "phdi.geospatial.SmartyGeocodeClient.geocode_from_dict", "modulename": "phdi.geospatial", "qualname": "SmartyGeocodeClient.geocode_from_dict", "kind": "function", "doc": "

Geocodes the provided address, which is formatted as a dictionary.

\n\n

The given dictionary should conform to standard nomenclature around address\nfields, including:

\n\n
    \n
  • street: the number and street address
    • \n
  • street2: additional street level information (if needed)
    • \n
  • apartment: apartment or suite number (if needed)
    • \n
  • city: city to geocode
    • \n
  • state: state to geocode
    • \n
  • postal_code: the postal code to use
    • \n
  • urbanization: urbanization code for area, sector, or regional
    • \n
  • development: (only used for Puerto Rican addresses)
    • \n
\n\n

There is no minimum number of fields that must be specified to use this\nfunction; however, a minimum of street, city, and state are suggested\nfor the best matches.

\n\n
Parameters
\n\n
    \n
  • address: A dictionary with fields outlined above.
    • \n
\n\n
Raises
\n\n
    \n
  • Exception: When the address street is an empty string.
    • \n
\n\n
Returns
\n\n
\n

A geocoded address (if valid result) or None (if no valid result).

\n
\n", "signature": "(self, address: dict) -> Optional[phdi.geospatial.core.GeocodeResult]:", "funcdef": "def"}, "phdi.geospatial.CensusGeocodeClient": {"fullname": "phdi.geospatial.CensusGeocodeClient", "modulename": "phdi.geospatial", "qualname": "CensusGeocodeClient", "kind": "class", "doc": "

Implementation of a geocoding client using the Census API.

\n", "bases": "phdi.geospatial.core.BaseGeocodeClient"}, "phdi.geospatial.CensusGeocodeClient.geocode_from_str": {"fullname": "phdi.geospatial.CensusGeocodeClient.geocode_from_str", "modulename": "phdi.geospatial", "qualname": "CensusGeocodeClient.geocode_from_str", "kind": "function", "doc": "

Geocodes a string-formatted address using Census API with searchtype =\n\"onelineaddress\". If a result is found, encodes as a GeocodeResult object and\nreturn, otherwise the return None.

\n\n
Parameters
\n\n
    \n
  • address: The address to geocode, given as a string.
    • \n
  • searchtype: onelineaddress OR address # doesn't yet support coordinates.
    • \n
\n\n
Raises
\n\n
    \n
  • ValueError: If address does not include street number and name.
    • \n
\n\n
Returns
\n\n
\n

A standardized address enriched with lat, lon, census tract, and more.\n Returns None if no valid result.

\n
\n", "signature": "(self, address: str) -> Optional[phdi.geospatial.core.GeocodeResult]:", "funcdef": "def"}, "phdi.geospatial.CensusGeocodeClient.geocode_from_dict": {"fullname": "phdi.geospatial.CensusGeocodeClient.geocode_from_dict", "modulename": "phdi.geospatial", "qualname": "CensusGeocodeClient.geocode_from_dict", "kind": "function", "doc": "

Geocodes the provided address, which is formatted as a dictionary.\nusing the Census API with searchtype = \"address\". If a result is found, encodes\nas a GeocodeResult object and return, otherwise returns None.

\n\n

The given dictionary should conform to standard nomenclature around address\nfields, including:

\n\n
    \n
  • street: the number and street address
    • \n
  • street2: additional street level information (if needed)
    • \n
  • apartment: apartment or suite number (if needed)
    • \n
  • city: city to geocode
    • \n
  • state: state to geocode
    • \n
  • postal_code: the postal code to use
    • \n
  • urbanization: urbanization code for area, sector, or regional
    • \n
  • development: (only used for Puerto Rican addresses)
    • \n
\n\n

Street must be included to use this function; however, a minimum of street,\ncity, and state are suggested for the best matches.

\n\n
Parameters
\n\n
    \n
  • address: A dictionary with fields outlined above.
    • \n
\n\n
Raises
\n\n
    \n
  • ValueError: If address does not include street number and name.
    • \n
\n\n
Returns
\n\n
\n

A standardized address enriched with lat, lon, census tract, and more.\n Returns None if no valid result.

\n
\n", "signature": "(self, address: dict) -> Optional[phdi.geospatial.core.GeocodeResult]:", "funcdef": "def"}, "phdi.harmonization": {"fullname": "phdi.harmonization", "modulename": "phdi.harmonization", "kind": "module", "doc": "

\n"}, "phdi.harmonization.standardize_hl7_datetimes": {"fullname": "phdi.harmonization.standardize_hl7_datetimes", "modulename": "phdi.harmonization", "qualname": "standardize_hl7_datetimes", "kind": "function", "doc": "

Prepares an HL7 message for conversion by normalizing / sanitizing\nfields that are known to contain datetime data in problematic formats. This\nfunction helps messages conform to expectations.

\n\n

This function accepts either segments terminated by \\r or \\n, but always\nreturns data with \\n as the segment terminator.

\n\n
Parameters
\n\n
    \n
  • message: The raw HL7 message to sanitize.
    • \n
\n\n
Returns
\n\n
\n

The HL7 message with potential problem formats resolved. If the function\n is unable to parse a date, the original value is retained.

\n
\n", "signature": "(message: str) -> str:", "funcdef": "def"}, "phdi.harmonization.normalize_hl7_datetime_segment": {"fullname": "phdi.harmonization.normalize_hl7_datetime_segment", "modulename": "phdi.harmonization", "qualname": "normalize_hl7_datetime_segment", "kind": "function", "doc": "

Applies datetime normalization to multiple fields in a segment,\noverwriting values in the input segment as necessary.

\n\n
Parameters
\n\n
    \n
  • message: The HL7 message, represented as a list\nof indexable component strings (which is how the HL7 library\nprocesses and returns messages).
    • \n
  • segment_id: The segment type (MSH, PID, etc) of the field to replace.
    • \n
  • field_num: The field number to replace in the segment named by segment_id.
    • \n
  • field_list: The list of field numbers to replace in the segment named\nby segement_id.
    • \n
\n", "signature": "(\tmessage: hl7.containers.Message,\tsegment_id: str,\tfield_list: list) -> None:", "funcdef": "def"}, "phdi.harmonization.normalize_hl7_datetime": {"fullname": "phdi.harmonization.normalize_hl7_datetime", "modulename": "phdi.harmonization", "qualname": "normalize_hl7_datetime", "kind": "function", "doc": "

Splits HL7 datetime-formatted fields into the following parts:\n[.][+/-]

\n\n

Each group of integers is truncated to conform to the HL7\nspecification:

\n\n
    \n
  • first integer group: max 14 digits
    • \n
  • following decimal point: max 4 digits
    • \n
  • following +/- (timezone): 4 digits
    • \n
\n\n

This normalization facilitates downstream processing using\ncloud providers that have particular requirements for dates.

\n\n
Parameters
\n\n
    \n
  • hl7_datetime: The raw datetime string to clean.
    • \n
\n\n
Returns
\n\n
\n

The datetime string with normalizing substitutions\n performed, or the original HL7 datetime if no matching\n format could be found.

\n
\n", "signature": "(hl7_datetime: str) -> str:", "funcdef": "def"}, "phdi.harmonization.default_hl7_value": {"fullname": "phdi.harmonization.default_hl7_value", "modulename": "phdi.harmonization", "qualname": "default_hl7_value", "kind": "function", "doc": "

Defaults a field value in an HL7 message.

\n\n

This function accepts either segments terminated by \\r or \\n, but always\nreturns data with \\n as the segment terminator.

\n\n
Parameters
\n\n
    \n
  • message: A string representing the HL7 message used to modify\na value.
    • \n
  • segment_id: The segment type (MSH, PID, etc) of the field to replace.
    • \n
  • field_num: The field number to replace in the segment named by segment_id.
    • \n
  • default_value: If the selected field is blank, set the\nfield's value to this value.
    • \n
\n\n
Returns
\n\n
\n

The HL7 message with default value inserted at the\n specified segment location, if possible. If not, then the\n original message.

\n
\n", "signature": "(message: str, segment_id: str, field_num: int, default_value: str):", "funcdef": "def"}, "phdi.harmonization.convert_hl7_batch_messages_to_list": {"fullname": "phdi.harmonization.convert_hl7_batch_messages_to_list", "modulename": "phdi.harmonization", "qualname": "convert_hl7_batch_messages_to_list", "kind": "function", "doc": "

Converts a batch file of messages into a list of strings\nrepresenting parts of the message. This function is based\non the following header/tail segments:

\n\n
    \n
  • FHS is a \"File Header Segment,\" which is used to head a file\n(group of batches)
    • \n
  • FTS is a \"File Trailer Segment,\" which defines the end of a file
    • \n
  • BHS is \"Batch Header Segment,\" which defines the start of a batch
    • \n
  • BTS is \"Batch Trailer Segment,\" which defines the end of a batch
    • \n
\n\n

The structure of an HL7 Batch looks like this:\n[FHS] (file header segment) { [BHS] (batch header segment)\n{ [MSH (zero or more HL7 messages)\n....\n....\n....\n] }\n[BTS] (batch trailer segment)\n}\n[FTS] (file trailer segment)

\n\n

Ignores lines that start with these header/tail segments since we don't want to\ninclude them in a message.

\n\n
Parameters
\n\n
    \n
  • content: The batch content to turn into a list.
    • \n
  • delimiter: The character delimiting messages in the batch.
    • \n
\n\n
Returns
\n\n
\n

A list of separated, cleaned HL7 messages.

\n
\n", "signature": "(content: str, delimiter: str = '\\n') -> List[str]:", "funcdef": "def"}, "phdi.harmonization.standardize_country_code": {"fullname": "phdi.harmonization.standardize_country_code", "modulename": "phdi.harmonization", "qualname": "standardize_country_code", "kind": "function", "doc": "

Identifies the country represented and generates the desired type of the ISO\n3611 standardized country identifier for a given string representation of a country\n(whether a full name such as \"United States,\" or an abbreviation such as \"US\"\nor \"USA\"). If the country identifier cannot be determined, returns None.

\n\n

Example: If raw_country = \"United States of America,\" then

\n\n
    \n
  • alpha_2 would be \"US\"
    • \n
  • alpha_3 would be \"USA\"
    • \n
  • numeric would be \"840\"
    • \n
\n\n
Parameters
\n\n
    \n
  • raw_country: The string representation of the country to be\nput in ISO 3611 standardized form.
    • \n
  • code_type: One of 'alpha_2', 'alpha_3', or 'numeric'; the\ndesired identifier type to generate.
    • \n
\n\n
Returns
\n\n
\n

The standardized country identifier found in the resource's addresses.

\n
\n", "signature": "(\traw_country: str,\tcode_type: Literal['alpha_2', 'alpha_3', 'numeric'] = 'alpha_2') -> str:", "funcdef": "def"}, "phdi.harmonization.standardize_phone": {"fullname": "phdi.harmonization.standardize_phone", "modulename": "phdi.harmonization", "qualname": "standardize_phone", "kind": "function", "doc": "

Parses phone number and generates its standardized ISO E.164 international format\nfor each given phone number and optional list of associated countries. If an input\nphone number can't be parsed, that number returns the empty string. Attempts\nto parse the inputs using the first successful strategy out of the following:

\n\n
    \n
  1. parses the phone number on its own
    2. \n
  2. parses the phone number using the provided list of possible\nassociated countries
    3. \n
  3. parses the phone number using the US as country
    4. \n
\n\n
Parameters
\n\n
    \n
  • raw_phone: One or more raw phone number(s) to standardize.
    • \n
  • countries: An optional list containing 2 letter ISO codes\nassociated with the phone numbers, signifying to which countries\nthe phone numbers might belong.
    • \n
\n\n
Returns
\n\n
\n

Either a string or a list of strings, depending on the\n input of raw_phone, holding the standardized phone number(s).

\n
\n", "signature": "(\traw_phone: Union[str, List[str]],\tcountries: List = [None, 'US']) -> Union[str, List[str]]:", "funcdef": "def"}, "phdi.harmonization.standardize_name": {"fullname": "phdi.harmonization.standardize_name", "modulename": "phdi.harmonization", "qualname": "standardize_name", "kind": "function", "doc": "

Performs basic standardization (described below) on each given name. Removes\npunctuation characters and performs a variety of additional cleaning operations.\nOther options can be toggled on or off using the relevant parameter.

\n\n

All options specified will be applied uniformly to each input name,\ni.e., specifying case = \"lower\" will make all given names lower case.

\n\n
Parameters
\n\n
    \n
  • raw_name: Either a single string name or a list of strings,\neach representing a name.
    • \n
  • trim: If true, strips leading/trailing whitespace;\nif false, retains whitespace. Default: True
    • \n

  • case: What case to enforce on each name.

    \n\n
      \n
    • upper: All upper case
      • \n
    • lower: All lower case
      • \n
    • title: Title case
      • \n
    \n\n

    Default: upper\n:remove_numbers: If true, removes numeric characters from inputs;\nif false, retains numeric characters. Default True

    • \n
\n\n
Returns
\n\n
\n

Either a string or a list of strings, depending on the\n input of raw_name, holding the cleaned name(s).

\n
\n", "signature": "(\traw_name: Union[str, List[str]],\ttrim: bool = True,\tcase: Literal['upper', 'lower', 'title'] = 'upper',\tremove_numbers: bool = True) -> Union[str, List[str]]:", "funcdef": "def"}, "phdi.harmonization.double_metaphone_string": {"fullname": "phdi.harmonization.double_metaphone_string", "modulename": "phdi.harmonization", "qualname": "double_metaphone_string", "kind": "function", "doc": "

Performs the double metaphone phonetic encoding algorithm on the given\nstring. Returns a list holding the primary and secondary phonetic\nrepresentations of the string (including None if there is no valid\nsecondary encoding). This function expects basic text cleaning (e.g.\nremoval of numeric characters, trimming of spaces, etc.) to already\nhave been performed.

\n\n
Parameters
\n\n
    \n
  • string: The string to phonetically encode.
    • \n
  • dmeta: An optional existing double metaphone object, in the case\none has already been instantiated for bulk processing.
    • \n
\n\n
Returns
\n\n
\n

A list of the primary and secondary encodings of the given\n string.

\n
\n", "signature": "(string: str, dmeta=None) -> List[Optional[str]]:", "funcdef": "def"}, "phdi.harmonization.compare_strings": {"fullname": "phdi.harmonization.compare_strings", "modulename": "phdi.harmonization", "qualname": "compare_strings", "kind": "function", "doc": "

Returns the normalized similarity measure between string1 and string2, as\ndetermined by the similarlity measure. The higher the normalized similarity measure\n(up to 1.0), the more similar string1 and string2 are. A normalized similarity\nmeasure of 0.0 means string1 and string 2 are not at all similar. This function\nexpects basic text cleaning (e.g. removal of numeric characters, trimming of spaces,\netc.) to already have been performed on the input strings.

\n\n
Parameters
\n\n
    \n
  • string1: First string for comparison.
    • \n
  • string2: Second string for comparison.
    • \n
  • similarity_measure: The method used to measure the similarity between two\nstrings, defaults to \"JaroWinkler\".
    • \n
  • JaroWinkler: a ratio of matching characters and transpositions needed to\ntransform string1 into string2.
    • \n
  • Levenshtein: the number of edits (excluding transpositions) needed to transform\nstring1 into string2.
    • \n
  • DamerauLevenshtein: the number of edits (including transpositions) needed to\ntransform string1 into string2.
    • \n
\n\n
Returns
\n\n
\n

The normalized similarity between string1 and string2, with 0 representing\n no similarity between string1 and string2, and 1 meaning string1 and string2 are\n dentical words.

\n
\n", "signature": "(\tstring1: str,\tstring2: str,\tsimilarity_measure: Literal['JaroWinkler', 'Levenshtein', 'DamerauLevenshtein'] = 'JaroWinkler') -> float:", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone": {"fullname": "phdi.harmonization.DoubleMetaphone", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone", "kind": "class", "doc": "

A Double Metaphone parsing object capable of performing the double\ncoding algorithm on a given input string.

\n"}, "phdi.harmonization.DoubleMetaphone.check_word_start": {"fullname": "phdi.harmonization.DoubleMetaphone.check_word_start", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.check_word_start", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_vowel": {"fullname": "phdi.harmonization.DoubleMetaphone.process_vowel", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_vowel", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_b": {"fullname": "phdi.harmonization.DoubleMetaphone.process_b", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_b", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_c": {"fullname": "phdi.harmonization.DoubleMetaphone.process_c", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_c", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_d": {"fullname": "phdi.harmonization.DoubleMetaphone.process_d", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_d", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_f": {"fullname": "phdi.harmonization.DoubleMetaphone.process_f", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_f", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_g": {"fullname": "phdi.harmonization.DoubleMetaphone.process_g", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_g", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_h": {"fullname": "phdi.harmonization.DoubleMetaphone.process_h", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_h", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_j": {"fullname": "phdi.harmonization.DoubleMetaphone.process_j", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_j", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_k": {"fullname": "phdi.harmonization.DoubleMetaphone.process_k", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_k", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_l": {"fullname": "phdi.harmonization.DoubleMetaphone.process_l", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_l", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_m": {"fullname": "phdi.harmonization.DoubleMetaphone.process_m", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_m", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_n": {"fullname": "phdi.harmonization.DoubleMetaphone.process_n", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_n", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_p": {"fullname": "phdi.harmonization.DoubleMetaphone.process_p", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_p", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_q": {"fullname": "phdi.harmonization.DoubleMetaphone.process_q", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_q", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_r": {"fullname": "phdi.harmonization.DoubleMetaphone.process_r", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_r", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_s": {"fullname": "phdi.harmonization.DoubleMetaphone.process_s", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_s", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_t": {"fullname": "phdi.harmonization.DoubleMetaphone.process_t", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_t", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_v": {"fullname": "phdi.harmonization.DoubleMetaphone.process_v", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_v", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_w": {"fullname": "phdi.harmonization.DoubleMetaphone.process_w", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_w", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_x": {"fullname": "phdi.harmonization.DoubleMetaphone.process_x", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_x", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.process_z": {"fullname": "phdi.harmonization.DoubleMetaphone.process_z", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.process_z", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "phdi.harmonization.DoubleMetaphone.parse": {"fullname": "phdi.harmonization.DoubleMetaphone.parse", "modulename": "phdi.harmonization", "qualname": "DoubleMetaphone.parse", "kind": "function", "doc": "

\n", "signature": "(self, input):", "funcdef": "def"}, "phdi.harmonization.standardize_birth_date": {"fullname": "phdi.harmonization.standardize_birth_date", "modulename": "phdi.harmonization", "qualname": "standardize_birth_date", "kind": "function", "doc": "

Validates and standardizes a date of birth string into YYYY-MM-DD format.

\n\n
Parameters
\n\n
    \n
  • raw_dob: One date of birth (dob) to standardize.
    • \n
  • existing_format: A python DateTime format used to parse the date of\nbirth within the Patient resource. Default: %Y-%m-%d (YYYY-MM-DD).
    • \n
\n\n
Returns
\n\n
\n

Date of birth as a string in YYYY-MM-DD format\n or None if date of birth is invalid.

\n
\n", "signature": "(raw_dob: str, existing_format: str = '%Y-%m-%d') -> str:", "funcdef": "def"}, "phdi.linkage": {"fullname": "phdi.linkage", "modulename": "phdi.linkage", "kind": "module", "doc": "

\n"}, "phdi.linkage.generate_hash_str": {"fullname": "phdi.linkage.generate_hash_str", "modulename": "phdi.linkage", "qualname": "generate_hash_str", "kind": "function", "doc": "

Generates a hash for a given string of concatenated patient information. The hash\nserves as a \"unique\" identifier for the patient.

\n\n
Parameters
\n\n
    \n
  • linking_identifier: The value to be hashed. For example, the concatenation\nof a patient's name, address, and date of birth, delimited by dashes.
    • \n
  • salt_str: The salt to use with the hash. This is intended to prevent\nreverse engineering of the PII used to create the hash.
    • \n
\n\n
Returns
\n\n
\n

The hash of the linking_identifier string.

\n
\n", "signature": "(linking_identifier: str, salt_str: str) -> str:", "funcdef": "def"}, "phdi.linkage.block_data": {"fullname": "phdi.linkage.block_data", "modulename": "phdi.linkage", "qualname": "block_data", "kind": "function", "doc": "

Generates dictionary of blocked data where each key is a block\nand each value is a distinct list of lists containing the data\nfor a given block.

\n\n
Parameters
\n\n
    \n
  • data: A pandas dataframe of records to be linked.
    • \n
  • blocks: List of columns to be used in blocks.
    • \n
\n\n
Returns
\n\n
\n

A dictionary of with the keys as the blocks and the\n values as the data within each block, stored as a list of\n lists.

\n
\n", "signature": "(data: pandas.core.frame.DataFrame, blocks: List) -> dict:", "funcdef": "def"}, "phdi.linkage.match_within_block": {"fullname": "phdi.linkage.match_within_block", "modulename": "phdi.linkage", "qualname": "match_within_block", "kind": "function", "doc": "

Performs matching on all candidate pairs of records within a given block\nof data. Actual partitioning of the data should be done outside this\nfunction, as it compares all possible pairs within the provided partition.\nUses a given construction of feature comparison rules as well as a\nmatch evaluation rule to determine the final verdict on whether two\nrecords are indeed a match.

\n\n

A feature function is of the form \"feature_match_X\" for some condition\nX; it must accept two records (lists of data), an index i in which the\nfeature to compare is stored, and the parameter **kwargs. It must return\na boolean indicating whether the features \"match\" for whatever definition\nof match the function uses (i.e. this allows modular logic to apply to\ndifferent features in the compared records). Note that not all features\nin a record need a comparison function defined.

\n\n

A match evaluation rule is a function of the form \"eval_X\" for some\ncondition X. It accepts as input a list of booleans, one for each feature\nthat was compared with feature funcs, and determines whether the\ncomparisons constitute a match according to X.

\n\n
Parameters
\n\n
    \n
  • block: A list of records to check for matches. Each record in\nthe list is itself a list of features. The first feature of the\nrecord must be an \"id\" for the record.
    • \n
  • feature_funcs: A dictionary mapping feature indices to functions\nused to evaluate those features for a match.
    • \n
  • col_to_idx: A dictionary mapping column names to the numeric index\nin which they occur in order in the data.
    • \n
  • match_eval: A function for determining whether a given set of\nfeature comparisons constitutes a match for linkage.
    • \n
\n\n
Returns
\n\n
\n

A list of 2-tuples of the form (i,j), where i,j give the indices\n in the block of data of records deemed to match.

\n
\n", "signature": "(\tblock: List[List],\tfeature_funcs: dict[str, typing.Callable],\tcol_to_idx: dict[str, int],\tmatch_eval: Callable,\t**kwargs) -> List[tuple]:", "funcdef": "def"}, "phdi.linkage.feature_match_exact": {"fullname": "phdi.linkage.feature_match_exact", "modulename": "phdi.linkage", "qualname": "feature_match_exact", "kind": "function", "doc": "

Determines whether a single feature in a given pair of records\nconstitutes an exact match (perfect equality).

\n\n
Parameters
\n\n
    \n
  • record_i: One of the records in the candidate pair to evaluate.
    • \n
  • record_j: The second record in the candidate pair.
    • \n
  • feature_col: The name of the column being evaluated (e.g. \"city\").
    • \n
  • col_to_idx: A dictionary mapping column names to the numeric index\nin which they occur in order in the data.
    • \n
\n\n
Returns
\n\n
\n

A boolean indicating whether the features are an exact match.

\n
\n", "signature": "(\trecord_i: List,\trecord_j: List,\tfeature_col: str,\tcol_to_idx: dict[str, int],\t**kwargs: dict) -> bool:", "funcdef": "def"}, "phdi.linkage.feature_match_fuzzy_string": {"fullname": "phdi.linkage.feature_match_fuzzy_string", "modulename": "phdi.linkage", "qualname": "feature_match_fuzzy_string", "kind": "function", "doc": "

Determines whether two strings in a given pair of records are close\nenough to constitute a partial match. The exact nature of the match\nis determined by the specified string comparison function (see\nharmonization/utils/compare_strings for more details) as well as a\nscoring threshold the comparison must meet or exceed.

\n\n
Parameters
\n\n
    \n
  • record_i: One of the records in the candidate pair to evaluate.
    • \n
  • record_j: The second record in the candidate pair.
    • \n
  • feature_col: The name of the column being evaluated (e.g. \"city\").
    • \n
  • col_to_idx: A dictionary mapping column names to the numeric index\nin which they occur in order in the data.
    • \n
  • **kwargs: Optionally, a dictionary including specifications for\nthe string comparison metric to use, as well as the cutoff score\nbeyond which to classify the strings as a partial match.
    • \n
\n\n
Returns
\n\n
\n

A boolean indicating whether the features are a fuzzy match.

\n
\n", "signature": "(\trecord_i: List,\trecord_j: List,\tfeature_col: str,\tcol_to_idx: dict[str, int],\t**kwargs: dict) -> bool:", "funcdef": "def"}, "phdi.linkage.eval_perfect_match": {"fullname": "phdi.linkage.eval_perfect_match", "modulename": "phdi.linkage", "qualname": "eval_perfect_match", "kind": "function", "doc": "

Determines whether a given set of feature comparisons represent a\n'perfect' match (i.e. whether all features that were compared match\nin whatever criteria was specified for them).

\n\n
Parameters
\n\n
    \n
  • feature_comparisons: A list of 1s and 0s, one for each feature\nthat was compared during the match algorithm.
    • \n
\n\n
Returns
\n\n
\n

The evaluation of whether the given features all match.

\n
\n", "signature": "(feature_comparisons: List, **kwargs) -> bool:", "funcdef": "def"}, "phdi.linkage.compile_match_lists": {"fullname": "phdi.linkage.compile_match_lists", "modulename": "phdi.linkage", "qualname": "compile_match_lists", "kind": "function", "doc": "

Turns a list of matches of either clusters or candidate pairs found\nduring linkage into a single unified structure holding all found matches\nacross all rules passes. E.g. if a single pass of a linkage algorithm\nuses three rules, hence generates three dictionaries of matches, this\nfunction will aggregate the results of those three separate dicts into\na single unified and deduplicated dictionary. For consistency during\nstatistical evaluation, the returned dictionary is always indexed by\nthe lower ID of the records in a given pair.

\n\n
Parameters
\n\n
    \n
  • match_lists: A list of the dictionaries obtained during a run\nof the linkage algorithm, one dictionary per rule used in the run.
    • \n
  • cluster_mode: An optional boolean indicating whether the linkage\nalgorithm was run in cluster mode. Default is False.
    • \n
\n\n
Returns
\n\n
\n

The aggregated dictionary of unified matches.

\n
\n", "signature": "(match_lists: List[dict], cluster_mode: bool = False):", "funcdef": "def"}, "phdi.linkage.feature_match_four_char": {"fullname": "phdi.linkage.feature_match_four_char", "modulename": "phdi.linkage", "qualname": "feature_match_four_char", "kind": "function", "doc": "

Determines whether a string feature in a pair of records exactly matches\non the first four characters.

\n\n
Parameters
\n\n
    \n
  • record_i: One of the records in the candidate pair to evaluate.
    • \n
  • record_j: The second record in the candidate pair.
    • \n
  • feature_col: The name of the column being evaluated (e.g. \"city\").
    • \n
  • col_to_idx: A dictionary mapping column names to the numeric index\nin which they occur in order in the data.
    • \n
\n\n
Returns
\n\n
\n

A boolean indicating whether the features are a match.

\n
\n", "signature": "(\trecord_i: List,\trecord_j: List,\tfeature_col: str,\tcol_to_idx: dict[str, int],\t**kwargs: dict) -> bool:", "funcdef": "def"}, "phdi.linkage.perform_linkage_pass": {"fullname": "phdi.linkage.perform_linkage_pass", "modulename": "phdi.linkage", "qualname": "perform_linkage_pass", "kind": "function", "doc": "

Performs a partial run of a linkage algorithm using a single rule.\nEach rule in an algorithm is associated with its own pass through the\ndata.

\n\n
Parameters
\n\n
    \n
  • data: Currently, a pandas dataframe of records to link. When we\nmove out of testing, this should become a LoL.
    • \n
  • blocks: A list of column headers to use as blocking assignments\nby which to partition the data.
    • \n
  • feature_funcs: A dictionary mapping feature indices to functions\nused to evaluate those features for a match.
    • \n
  • matching_rule: A function for determining whether a given set of\nfeature comparisons constitutes a match for linkage.
    • \n
  • cluster_ratio: An optional parameter indicating, if using the\nalgorithm in cluster mode, the required membership percentage a record\nmust score with an existing cluster in order to join.
    • \n
\n\n
Returns
\n\n
\n

A dictionary mapping each block found in the pass to the matches\n discovered within that block.

\n
\n", "signature": "(\tdata: pandas.core.frame.DataFrame,\tblocks: List,\tfeature_funcs: dict[str, typing.Callable],\tmatching_rule: Callable,\tcluster_ratio: Optional[float] = None,\t**kwargs) -> dict:", "funcdef": "def"}, "phdi.linkage.score_linkage_vs_truth": {"fullname": "phdi.linkage.score_linkage_vs_truth", "modulename": "phdi.linkage", "qualname": "score_linkage_vs_truth", "kind": "function", "doc": "

Compute the statistical qualities of a run of record linkage against\nknown true results. This function assumes that matches have already\nbeen determined by the algorithm, and further assumes that true\nmatches have already been identified in the data.

\n\n
Parameters
\n\n
    \n
  • found_matches: A dictionary mapping IDs of records to sets of\nother records which were determined to be a match.
    • \n
  • true_matches: A dictionary mapping IDs of records to sets of\nother records which are _known_ to be a true match.
    • \n
  • records_in_dataset: The number of records in the original data\nset to-link.
    • \n
  • expand_clusters_pairwise: Optionally, whether we need to take\nthe cross-product of members within the sets of the match list. This\nparameter only needs to be used if the linkage algorithm was run in\ncluster mode. Default is False.
    • \n
\n\n
Returns
\n\n
\n

A tuple reporting the sensitivity/precision, specificity/recall,\n positive prediction value, and F1 score of the linkage algorithm.

\n
\n", "signature": "(\tfound_matches: dict[typing.Union[int, str], set],\ttrue_matches: dict[typing.Union[int, str], set],\trecords_in_dataset: int,\texpand_clusters_pairwise: bool = False) -> tuple:", "funcdef": "def"}, "phdi.linkage.calculate_m_probs": {"fullname": "phdi.linkage.calculate_m_probs", "modulename": "phdi.linkage", "qualname": "calculate_m_probs", "kind": "function", "doc": "

For a given set of patient records, calculate the per-field\nm-probability. The m-probability for field X is defined as the\nprobability that a pair of records A and B have the same value in\nX, given that A and B are a true matching pair. This function\nincorporates LaPlacian Smoothing to account for unseen data and\nto resolve future logarithms against 0.

\n\n
Parameters
\n\n
    \n
  • data: A pandas dataframe of patient records to compute\nprobabilities for.
    • \n
  • true_matches: A dictionary holding the IDs of record pairs\nthat are true matches in the data set. The format of the dictionary\nshould be such that the IDs of the \"lower numbered\" records in each\nmatch pair are the keys, and the values are sets of the \"higher\nnumbered\" records in each pair.
    • \n
  • cols: Optionally, a list of columns to compute probabilities\nfor. If not supplied, computes probabilities across all fields.\nDefault is None.
    • \n
  • file_to_write: Optionally, a destination filepath at which to\nwrite the probabilities in JSON format. Default is None.
    • \n
\n", "signature": "(\tdata: pandas.core.frame.DataFrame,\ttrue_matches: dict,\tcols: Optional[List[str]] = None,\tfile_to_write: Optional[pathlib.Path] = None):", "funcdef": "def"}, "phdi.linkage.calculate_u_probs": {"fullname": "phdi.linkage.calculate_u_probs", "modulename": "phdi.linkage", "qualname": "calculate_u_probs", "kind": "function", "doc": "

For a given set of patient records, calculate the per-field\nu-probability. The u-probability for field X is defined as the\nprobability that a pair of records A and B have the same value in\nX, given that A and B are not a true matching pair. This function\nincorporates LaPlacian Smoothing to account for unseen data and\nto handle future logarithms against 0.

\n\n

Note: This function can be slow to compute for large data sets.\nIt is recommended to pass only a representative subsample of the\ndata to the function (we recommend sampling ~25k candidate pairs\nfrom a sub-sample of ~25k records), even if the sample operation\nis used.

\n\n
Parameters
\n\n
    \n
  • data: A pandas dataframe of patient records to compute\nprobabilities for.
    • \n
  • true_matches: A dictionary holding the IDs of record pairs\nthat are true matches in the data set. The format of the dictionary\nshould be such that the IDs of the \"lower numbered\" records in each\nmatch pair are the keys, and the values are sets of the \"higher\nnumbered\" records in each pair.
    • \n
  • n_samples: Optionally, a number of samples to take from the\nlist of possible pairs to compute probabilities over.
    • \n
  • cols: Optionally, a list of columns to compute probabilities\nfor. If not supplied, computes probabilities across all fields.\nDefault is None.
    • \n
  • file_to_write: Optionally, a destination filepath at which to\nwrite the probabilities in JSON format. Default is None.
    • \n
\n", "signature": "(\tdata: pandas.core.frame.DataFrame,\ttrue_matches: dict,\tn_samples: Optional[int] = None,\tcols: Optional[List] = None,\tfile_to_write: Optional[pathlib.Path] = None):", "funcdef": "def"}, "phdi.linkage.load_json_probs": {"fullname": "phdi.linkage.load_json_probs", "modulename": "phdi.linkage", "qualname": "load_json_probs", "kind": "function", "doc": "

Load a dictionary of probabilities from a JSON-formatted file.\nThe probabilities correspond to previously computed m-, u-, or\nlog-odds probabilities derived from patient records, with one\nscore for each field (column) appearing in the data.

\n\n
Parameters
\n\n
    \n
  • path: The file path to load the data from.
    • \n
\n\n
Returns
\n\n
\n

A dictionary of probability scores, one for each field\n in the data set on which they were computed.

\n
\n\n
Raises
\n\n
    \n
  • FileNotFoundError: If a file does not exist at the given\npath.
    • \n
  • JSONDecodeError: If the file cannot be read as valid JSON.
    • \n
\n", "signature": "(path: pathlib.Path):", "funcdef": "def"}, "phdi.linkage.calculate_log_odds": {"fullname": "phdi.linkage.calculate_log_odds", "modulename": "phdi.linkage", "qualname": "calculate_log_odds", "kind": "function", "doc": "

Calculate the per-field log odds ratio score that two records will\nmatch in a given field. Measures the likelihood that two records\nmatch on a column due to being a true match as opposed to random\nchance.

\n\n
Parameters
\n\n
    \n
  • m_probs: A dictionary of m-probabilities computed per field.
    • \n
  • u_probs: A dictionary of u_probabilities computed per field.
    • \n
  • file_to_write: Optionally, a destination filepath at which\nto write the probabilities in JSON format. Default is None.
    • \n
\n\n
Raises
\n\n
    \n
  • ValueError: If the supplied m- and u- probability dictionaries\ndo not share an equal key set.
    • \n
\n", "signature": "(\tm_probs: dict,\tu_probs: dict,\tfile_to_write: Optional[pathlib.Path] = None):", "funcdef": "def"}, "phdi.linkage.feature_match_log_odds_exact": {"fullname": "phdi.linkage.feature_match_log_odds_exact", "modulename": "phdi.linkage", "qualname": "feature_match_log_odds_exact", "kind": "function", "doc": "

Determines whether two feature values in two records should earn the full\nlog-odds similarity score (i.e. they match exactly) or whether they\nshould earn no weight (they differ). Used for fields for which fuzzy\ncomparisons are inappropriate, such as sex.

\n\n
Parameters
\n\n
    \n
  • record_i: One of the records in the candidate pair to evaluate.
    • \n
  • record_j: The second record in the candidate pair.
    • \n
  • feature_col: The name of the column being evaluated (e.g. \"city\").
    • \n
  • col_to_idx: A dictionary mapping column names to the numeric index\nin which they occur in order in the data.
    • \n
\n\n
Returns
\n\n
\n

A float of the score the feature comparison earned.

\n
\n", "signature": "(\trecord_i: List,\trecord_j: List,\tfeature_col: str,\tcol_to_idx: dict[str, int],\t**kwargs: dict) -> float:", "funcdef": "def"}, "phdi.linkage.feature_match_log_odds_fuzzy_compare": {"fullname": "phdi.linkage.feature_match_log_odds_fuzzy_compare", "modulename": "phdi.linkage", "qualname": "feature_match_log_odds_fuzzy_compare", "kind": "function", "doc": "

Determines the weighted string-odds similarly score earned by two\nfeature values in two records, as a function of the pre-computed\nlog-odds weights and the string similarity between the two features.\nThis scales the full score that would be earned from a perfect\nmatch to a degree of partial weight appropriate to how similar the\ntwo strings are.

\n\n
Parameters
\n\n
    \n
  • record_i: One of the records in the candidate pair to evaluate.
    • \n
  • record_j: The second record in the candidate pair.
    • \n
  • feature_col: The name of the column being evaluated (e.g. \"city\").
    • \n
  • col_to_idx: A dictionary mapping column names to the numeric index\nin which they occur in order in the data.
    • \n
\n\n
Returns
\n\n
\n

A float of the score the feature comparison earned.

\n
\n", "signature": "(\trecord_i: List,\trecord_j: List,\tfeature_col: str,\tcol_to_idx: dict[str, int],\t**kwargs: dict) -> float:", "funcdef": "def"}, "phdi.linkage.profile_log_odds": {"fullname": "phdi.linkage.profile_log_odds", "modulename": "phdi.linkage", "qualname": "profile_log_odds", "kind": "function", "doc": "

Basic graphical profiler for log-odds histogram analysis. Using the\nraw data and previously known true matches, the function computes one\nlist of log-odds scores that that would be earned by true matches under\na given linkage rule, and another list of scores that would be earned\nby a random sampling of non-matches under the same linkage rule. These\nlists are used to plot bimodal histograms so that the cutoff threshold\nbetween non-matchces and true matches can be visually determined.

\n\n
Parameters
\n\n
    \n
  • data: A pandas data frame holding the raw patient record data.
    • \n
  • true_matches: A dictionary of known true matches in the data.
    • \n
  • log_odds: A dictionary whose keys are the column fields of data\nand whose values are the log-odds scores that two values match relative\nto random chance.
    • \n
  • exact_cols: A list of columns to be evaluated using equality\ncomparisons.
    • \n
  • fuzzy_cols: A list of columns to be evaluated using fuzzy weighted\ncomparisons.
    • \n
  • idx_to_col: A dictionary mapping the number of a column in a list\nrepresentation of the data, to the name of the column in a pandas\nrepresentation.
    • \n
  • neg_samples: Optionally, how many non-match samples to compute a\nscore for when generating the histogram.
    • \n
\n", "signature": "(\tdata: pandas.core.frame.DataFrame,\ttrue_matches: dict,\tlog_odds: dict,\texact_cols: List,\tfuzzy_cols: List,\tidx_to_col: dict,\tneg_samples: int = 50000) -> None:", "funcdef": "def"}, "phdi.linkage.eval_log_odds_cutoff": {"fullname": "phdi.linkage.eval_log_odds_cutoff", "modulename": "phdi.linkage", "qualname": "eval_log_odds_cutoff", "kind": "function", "doc": "

Determines whether a given set of feature comparisons matches enough\nto be the result of a true patient link instead of just random chance.\nThis is represented using previously computed log-odds ratios.

\n\n
Parameters
\n\n
    \n
  • feature_comparisons: A list of floats representing the log-odds\nscore of each field computed on.
    • \n
\n\n
Returns
\n\n
\n

Whether the feature comparisons score well enough to be\n considered a match.

\n
\n", "signature": "(feature_comparisons: List, **kwargs) -> bool:", "funcdef": "def"}, "phdi.linkage.BaseMPIConnectorClient": {"fullname": "phdi.linkage.BaseMPIConnectorClient", "modulename": "phdi.linkage", "qualname": "BaseMPIConnectorClient", "kind": "class", "doc": "

Represents a vendor-agnostic Master Patient Index (MPI) connector client. Requires\nimplementing classes to define methods to retrive blocks of data from the MPI.\nCallers should use the provided interface functions (e.g., block_data)\nto interact with the underlying vendor-specific client property.

\n", "bases": "abc.ABC"}, "phdi.linkage.BaseMPIConnectorClient.get_block_data": {"fullname": "phdi.linkage.BaseMPIConnectorClient.get_block_data", "modulename": "phdi.linkage", "qualname": "BaseMPIConnectorClient.get_block_data", "kind": "function", "doc": "

Returns a list of lists containing records from the MPI database that\nmatch on the incoming record's block criteria and values. If blocking\non 'ZIP' and the incoming record's zip code is '90210', the resulting\nblock of data would contain records that all\nhave the same zip code of 90210.

\n", "signature": "() -> List[list]:", "funcdef": "def"}, "phdi.linkage.BaseMPIConnectorClient.insert_matched_patient": {"fullname": "phdi.linkage.BaseMPIConnectorClient.insert_matched_patient", "modulename": "phdi.linkage", "qualname": "BaseMPIConnectorClient.insert_matched_patient", "kind": "function", "doc": "

If a matching person ID has been found in the MPI, inserts a new patient into\nthe patient table and all other subsequent MPI tables, including the\nmatched person id, to link the new patient and matched person ID;\nelse inserts a new patient into the patient table, as well as all other\nsubsequent MPI tables, and inserts a new person into the person table\nlinking the new person to the new patient.

\n", "signature": "() -> None:", "funcdef": "def"}, "phdi.linkage.extract_blocking_values_from_record": {"fullname": "phdi.linkage.extract_blocking_values_from_record", "modulename": "phdi.linkage", "qualname": "extract_blocking_values_from_record", "kind": "function", "doc": "

Extracts values from a given patient record for eventual use in database\nrecord linkage blocking. A list of fields to block on, as well as a mapping\nof those fields to any desired transformations of their extracted values,\nis used to fhir-path parse the value out of the incoming patient record.

\n\n

Currently supported blocking fields:

\n\n
    \n
  • first_name
    • \n
  • last_name
    • \n
  • birthdate
    • \n
  • address
    • \n
  • city
    • \n
  • state
    • \n
  • zip
    • \n
  • sex
    • \n
  • mrn
    • \n
\n\n

Currently supported transformations on extracted fields:

\n\n
    \n
  • first4: the first four characters of the value
    • \n
  • last4: the last four characters of the value
    • \n
\n\n
Parameters
\n\n
    \n
  • record: A FHIR-formatted Patient record.
    • \n
  • blocking_fields: A List of dictionaries giving the blocking\nfields and any transformations that should be applied to them. Each\ndictionary in the list should include a \"value\" key with one of the\nsupported blocking fields above, and may also optionally contain a\n\"transformation\" key whose value is one of our supported transforms.
    • \n
\n", "signature": "(record: dict, blocking_fields: List[dict]) -> dict:", "funcdef": "def"}, "phdi.linkage.write_linkage_config": {"fullname": "phdi.linkage.write_linkage_config", "modulename": "phdi.linkage", "qualname": "write_linkage_config", "kind": "function", "doc": "

Save a provided algorithm description as a JSON dictionary at the provided\nfilepath location. Algorithm descriptions are lists of dictionaries, one\nfor each pass of the algorithm, whose keys are parameter values for a\nlinkage pass (drawn from the list \"funcs\", \"blocks\", \"matching_rule\",\nand optionally \"cluster_ratio\" and \"kwargs\") and whose values are\nas follows:

\n\n
    \n
  • \"funcs\" should map to a dictionary mapping column index to the\nname of a function in the DIBBS linkage module (such as\nfeature_match_fuzzy_string)--note that these are the actual\nfunctions, not string names of the functions
    • \n
  • \"blocks\" should map to a list of columns to block on (e.g.\n[\"MRN4\", \"ADDRESS4\"])
    • \n
  • \"matching_rule\" should map to one of the evaluation rule functions\nin the DIBBS linkage module (i.e. eval_perfect_match)
    • \n
  • \"cluster_ratio\" should map to a float, if provided
    • \n
  • \"kwargs\" should map to a dictionary of keyword arguments and their\nassociated values, if provided
    • \n
\n\n

Here's an example of a simple single-pass linkage algorithm that blocks\non zip code, then matches on exact first name, exact last name, and\nfuzzy date of birth (using, say, Levenshtein similarity with a score\nthreshold of 0.8) in dictionary descriptor form (for the sake of the\nexample, let's assume the data has the column order first, last, DOB):

\n\n

[{\n \"funcs\": {\n 0: feature_match_exact,\n 1: feature_match_exact,\n 2: feature_match_fuzzy_string,\n 3: feature_match_fuzzy_string,\n },\n \"blocks\": [\"ZIP\"],\n \"matching_rule\": eval_perfect_match,\n \"kwargs\": {\n \"similarity-measure\": \"Levenshtein\",\n \"threshold\": 0.8\n }\n}]

\n\n
Parameters
\n\n
    \n
  • linkage_algo: A list of dictionaries whose key-value pairs correspond\nto the rules above.
    • \n
  • file_to_write: The path to the destination JSON file to write.
    • \n
\n", "signature": "(linkage_algo: List[dict], file_to_write: pathlib.Path) -> None:", "funcdef": "def"}, "phdi.linkage.read_linkage_config": {"fullname": "phdi.linkage.read_linkage_config", "modulename": "phdi.linkage", "qualname": "read_linkage_config", "kind": "function", "doc": "

Reads and generates a record linkage algorithm configuration list from\nthe provided filepath, which should point to a JSON file. A record\nlinkage configuration list is a list of dictionaries--one for each\npass in the algorithm it describes--containing information on the\nblocking fields, functions, cluster thresholds, and keyword arguments\nfor that pass of the linkage algorithm. For a full example of all the\ncomponents involved in a linkage description structure, see the doc\nstring for write_linkage_config.

\n\n
Parameters
\n\n
    \n
  • config_file: A pathlib.Path string pointing to a JSON file\nthat describes the algorithm to decode.
    • \n
\n\n
Returns
\n\n
\n

A list of dictionaries whose values can be passed to the\n various parts of linkage pass function.

\n
\n", "signature": "(config_file: pathlib.Path) -> List[dict]:", "funcdef": "def"}, "phdi.linkage.link_record_against_mpi": {"fullname": "phdi.linkage.link_record_against_mpi", "modulename": "phdi.linkage", "qualname": "link_record_against_mpi", "kind": "function", "doc": "

Runs record linkage on a single incoming record (extracted from a FHIR\nbundle) using an existing database as an MPI. Uses a flexible algorithm\nconfiguration to allow customization of the exact kind of linkage to\nrun. Linkage is assumed to run using cluster membership (i.e. the new\nrecord must match a certain proportion of existing records all assigned\nto a person in order to match), and if multiple persons are matched,\nthe new record is linked to the person with the strongest membership\npercentage.

\n\n
Parameters
\n\n
    \n
  • record: The FHIR-formatted patient resource to try to match to\nother records in the MPI.
    • \n
  • algo_config: An algorithm configuration consisting of a list\nof dictionaries describing the algorithm to run. See\nread_linkage_config and write_linkage_config for more details.\n:returns: A tuple consisting of a boolean indicating whether a match\nwas found for the new record in the MPI, followed by the ID of the\nPerson entity now associated with the incoming patient (either a\nnew Person ID or the ID of an existing matched Person).
    • \n
\n", "signature": "(\trecord: dict,\talgo_config: List[dict],\texternal_person_id: str = None,\tmpi_client: phdi.linkage.core.BaseMPIConnectorClient = None) -> tuple[bool, str]:", "funcdef": "def"}, "phdi.linkage.add_person_resource": {"fullname": "phdi.linkage.add_person_resource", "modulename": "phdi.linkage", "qualname": "add_person_resource", "kind": "function", "doc": "

Adds a simplified person resource to a bundle if the patient resource in the bundle\nmatches an existing record in the Master Patient Index. Returns the bundle with\nthe newly added person resource.

\n\n
Parameters
\n\n
    \n
  • person_id: _description_
    • \n
  • patient_id: _description_
    • \n
  • bundle: _description_, defaults to Field(description=\"A FHIR bundle\")
    • \n
\n\n
Returns
\n\n
\n

_description_

\n
\n", "signature": "(\tperson_id: str,\tpatient_id: str,\tbundle: dict = FieldInfo(default=PydanticUndefined, description='A FHIR bundle', extra={})) -> dict:", "funcdef": "def"}, "phdi.linkage.convert_to_patient_fhir_resources": {"fullname": "phdi.linkage.convert_to_patient_fhir_resources", "modulename": "phdi.linkage", "qualname": "convert_to_patient_fhir_resources", "kind": "function", "doc": "

Converts and returns a row of patient data into patient resource in a FHIR-formatted\npatient resouce with a newly generated patient id as well as the\nexternal_person_id.

\n\n
Parameters
\n\n
    \n
  • data: Dictionary of patient data that optionionally includes the following\nfields: mrn, ssn, first_name, middle_name, last_name, home_phone, cell-phone, sex,\nbirthdate, address, city, state, zip.
    • \n
\n\n
Returns
\n\n
\n

Tuple of the external_person_id and FHIR-formatted patient resource.

\n
\n", "signature": "(data: Dict) -> Tuple:", "funcdef": "def"}, "phdi.linkage.DIBBsMPIConnectorClient": {"fullname": "phdi.linkage.DIBBsMPIConnectorClient", "modulename": "phdi.linkage", "qualname": "DIBBsMPIConnectorClient", "kind": "class", "doc": "

Represents a Postgres-specific Master Patient Index (MPI) connector\nclient for the DIBBs implementation of the record linkage building\nblock. Callers should use the provided interface functions (e.g.,\nblock_vals) to interact with the underlying vendor-specific client\nproperty.

\n", "bases": "phdi.linkage.core.BaseMPIConnectorClient"}, "phdi.linkage.DIBBsMPIConnectorClient.__init__": {"fullname": "phdi.linkage.DIBBsMPIConnectorClient.__init__", "modulename": "phdi.linkage", "qualname": "DIBBsMPIConnectorClient.__init__", "kind": "function", "doc": "

Initialize the MPI connector client with the MPI database.

\n\n
Parameters
\n\n
    \n
  • pool_size: The number of connections to keep open to the database.
    • \n
  • max_overflow: The number of connections to allow in connection pool.
    • \n
\n", "signature": "(pool_size: int = 5, max_overflow: int = 10)"}, "phdi.linkage.DIBBsMPIConnectorClient.get_block_data": {"fullname": "phdi.linkage.DIBBsMPIConnectorClient.get_block_data", "modulename": "phdi.linkage", "qualname": "DIBBsMPIConnectorClient.get_block_data", "kind": "function", "doc": "

Returns a list of lists containing records from the MPI database that\nmatch on the incoming record's block criteria and values. If blocking\non 'ZIP' and the incoming record's ip code is '90210', the resulting\nblock of data would contain records that all\nhave the same zip code of 90210.

\n\n
Parameters
\n\n
    \n
  • block_criteria: Dictionary containing key value pairs\n for the column name for blocking and the data for the\n incoming record as well as any transformations,\ne.g., {\"ZIP\": {\"value\": \"90210\"}} or\n{\"ZIP\": {\"value\": \"90210\",}, \"transformation\":\"first4\"}.
    • \n
\n\n
Returns
\n\n
\n

A list of records that are within the block, e.g.,\n records that all have 90210 as their ZIP.

\n
\n", "signature": "(self, block_criteria: Dict) -> List[list]:", "funcdef": "def"}, "phdi.linkage.DIBBsMPIConnectorClient.insert_matched_patient": {"fullname": "phdi.linkage.DIBBsMPIConnectorClient.insert_matched_patient", "modulename": "phdi.linkage", "qualname": "DIBBsMPIConnectorClient.insert_matched_patient", "kind": "function", "doc": "

If a matching person ID has been found in the MPI, inserts a new patient into\nthe patient table and all other subsequent MPI tables, including the\nmatched person id, to link the new patient and matched person ID;\nelse inserts a new patient into the patient table, as well as all other\nsubsequent MPI tables, and inserts a new person into the person table\nlinking the new person to the new patient.

\n\n
Parameters
\n\n
    \n
  • patient_resource: A FHIR patient resource.
    • \n
  • person_id: The person ID matching the patient record if a match has been\nfound in the MPI, defaults to None.
    • \n
  • external_person_id: The external person id for the person that matches\nthe patient record if a match has been found in the MPI, defaults to None.
    • \n
\n", "signature": "(\tself,\tpatient_resource: Dict,\tperson_id=None,\texternal_person_id=None) -> str:", "funcdef": "def"}, "phdi.linkage.datetime_to_str": {"fullname": "phdi.linkage.datetime_to_str", "modulename": "phdi.linkage", "qualname": "datetime_to_str", "kind": "function", "doc": "

Convert a date or datetime object to a string; if a string is provided,\ncheck that it follows the appropriate format. If unable to perform actions,\nreturn input as string rather than failing loudly.

\n\n
Parameters
\n\n
    \n
  • input_date: The input date to convert, which prefers types of\ndatetime.date, datetime.datetime, or str.
    • \n
  • include_time: Whether to include the time in the output string.
    • \n
\n\n
Returns
\n\n
\n

The formatted date as a string. If include_time is True, the\n format is 'YYYY-MM-DD HH:MM:SS', otherwise it's 'YYYY-MM-DD'. If\n empty or None, return empty or None.

\n
\n", "signature": "(\tinput_date: Union[str, datetime.date, datetime.datetime],\tinclude_time: bool = False) -> str:", "funcdef": "def"}, "phdi.linkage.aggregate_given_names_for_linkage": {"fullname": "phdi.linkage.aggregate_given_names_for_linkage", "modulename": "phdi.linkage", "qualname": "aggregate_given_names_for_linkage", "kind": "function", "doc": "

Aggregates the given names in the return block data into appropriate format for\nrecord linkage, i.e., one row of data for each patient with all of the given names\nin a space-delimited string, e.g., John Tiberius

\n\n
Parameters
\n\n
    \n
  • data: List of lists block data.
    • \n
\n\n
Returns
\n\n
\n

List of lists with aggregated given names.

\n
\n", "signature": "(data: list[list]):", "funcdef": "def"}, "phdi.tabulation": {"fullname": "phdi.tabulation", "modulename": "phdi.tabulation", "kind": "module", "doc": "

\n"}, "phdi.tabulation.load_schema": {"fullname": "phdi.tabulation.load_schema", "modulename": "phdi.tabulation", "qualname": "load_schema", "kind": "function", "doc": "

Given the path to a local YAML or JSON file containing a schema,\nloads the file and return the resulting schema as a dictionary.\nIf the file can't be found, raises an error.

\n\n
Parameters
\n\n
    \n
  • path: The file path to a YAML file holding a schema.
    • \n
\n\n
Raises
\n\n
    \n
  • ValueError: If the provided path points to an unsupported file type.
    • \n
  • FileNotFoundError: If the file to be loaded could not be found.
    • \n
  • JSONDecodeError: If a JSON file is provided with invalid JSON.
    • \n
\n\n
Returns
\n\n
\n

A dict representing a schema read from the given path.

\n
\n", "signature": "(path: pathlib.Path) -> dict:", "funcdef": "def"}, "phdi.tabulation.validate_schema": {"fullname": "phdi.tabulation.validate_schema", "modulename": "phdi.tabulation", "qualname": "validate_schema", "kind": "function", "doc": "

Validates the schema structure, ensuring all required schema elements are present\nand all schema elements are of the expected data type.

\n\n
Parameters
\n\n
    \n
  • schema: A declarative, user-defined specification, for one or more tables,\nthat defines the metadata, properties, and columns of those tables as they\nrelate to FHIR resources.
    • \n
\n\n
Raises
\n\n
    \n
  • jsonschema.exception.ValidationError: If the schema is invalid.
    • \n
\n", "signature": "(schema: dict):", "funcdef": "def"}, "phdi.tabulation.write_data": {"fullname": "phdi.tabulation.write_data", "modulename": "phdi.tabulation", "qualname": "write_data", "kind": "function", "doc": "

Writes a set of tabulated data to a particular output format on disk\n(one of CSV, Parquet, or SQL). For CSV and Parquet writing, a filename\nmust be provided to write output to. In the case of the SQL format,\na database file (if one exists and is being modified) must be specified\nalong with a table name in place of a filename. Creates new data files\nif the given options specify a file that doesn't exist, and appends\ndata to already-present files if they do.

\n\n
Parameters
\n\n
    \n
  • tabulated_data: A list of lists in which the first element\nis the headers for the table-to-write and subsequent elements\nare rows in the table.
    • \n
  • directory: The directory in which to write the output data\n(if output_type is CSV or Parquet), or the directory in which\nthe db_file is stored (if a database already exists) or should\nbe created in (if a database does not already exist).
    • \n
  • output_type: The format the data should be written to.
    • \n
  • filename: The name of the CSV or Parquet file data should be\nwritten to. Omit if output_type is SQL. Default: None.
    • \n
  • db_file: The name of the database file to either create or\naccess when writing to a SQL format. Omit if output_type is not\nSQL. Default: None.
    • \n
  • db_tablename: The name of the table in the database to create\nor write data to. Omit if output_type is not SQL. Default: None.
    • \n
  • pq_writer: A pre-existing ParquetWriter object that can be\nused to append data to a parquet format. Used in cases where\nincremental writing to a parquet destination is desired. Omit if\noutput_type is not Parquet. Default: None.
    • \n
\n", "signature": "(\ttabulated_data: List[List],\tdirectory: str,\toutput_type: Literal['csv', 'parquet', 'sql'],\tfilename: str = None,\tdb_file: str = None,\tdb_tablename: str = None,\tpq_writer: pyarrow.parquet.core.ParquetWriter = None,\tschema: dict = None,\ttable_name: str = None) -> Optional[pyarrow.parquet.core.ParquetWriter]:", "funcdef": "def"}, "phdi.transport": {"fullname": "phdi.transport", "modulename": "phdi.transport", "kind": "module", "doc": "

\n"}, "phdi.transport.http_request_with_retry": {"fullname": "phdi.transport.http_request_with_retry", "modulename": "phdi.transport", "qualname": "http_request_with_retry", "kind": "function", "doc": "

Executes an HTTP request, retrying the request if the returned HTTP status code\nis one of a specified list of codes.

\n\n
Parameters
\n\n
    \n
  • url: The url at which to make the HTTP request.
    • \n
  • retry_count: The number of times to retry the request, if the\nfirst attempt fails.
    • \n
  • request_type: The type of request to be made. Currently supports\nGET and POST.
    • \n
  • allowed_methods: The list of allowed HTTP request methods (i.e.,\nPOST, PUT) for the specific URL and query.
    • \n
  • headers: JSON-type dictionary of headers to make the request with,\nincluding Authorization and content-type.
    • \n
  • data: The data as a JSON-formatted dictionary, used when the request\nrequires data to be posted. Default: None
    • \n
\n\n
Raises
\n\n
    \n
  • ValueError: An unsupported HTTP method (e.g., PATCH, DELETE) was passed\nto the request_type parameter.
    • \n
\n\n
Returns
\n\n
\n

A HTTP request response.

\n
\n", "signature": "(\turl: str,\tretry_count: int,\trequest_type: Literal['GET', 'POST'],\tallowed_methods: List[str],\theaders: dict,\tdata: dict = None) -> requests.models.Response:", "funcdef": "def"}, "phdi.validation": {"fullname": "phdi.validation", "modulename": "phdi.validation", "kind": "module", "doc": "

\n"}, "phdi.validation.validate_ecr": {"fullname": "phdi.validation.validate_ecr", "modulename": "phdi.validation", "qualname": "validate_ecr", "kind": "function", "doc": "

Receives an ecr message (a combined RR and eICR), a configuration of\nwhat fields are to be validated and how they are to be validated, as\nwell as a list of error message types to include (default is all fatal\nerrors, basic errors, warnings, and information). The result of\nvalidation is returned in a dictionary that also contains a boolean\nif the ecr message is valid or not.

\n\n
Parameters
\n\n
    \n
  • ecr_message: A eCR message that contains both eICR and RR fields.
    • \n
  • config: A dictionary of the requirements for validation of the\neCR message.
    • \n
  • include_error_types: A list of error message types to include\nin the final validation response. Default (fatal, errors,\nwarnings, information)
    • \n
\n\n
Returns
\n\n
\n

A dictionary containing bool message_valid as well as a\n dictionary containing the validation results/errors.

\n
\n", "signature": "(ecr_message: str, config: dict, include_error_types: list) -> dict:", "funcdef": "def"}, "phdi.validation.get_ecr_message_ids": {"fullname": "phdi.validation.get_ecr_message_ids", "modulename": "phdi.validation", "qualname": "get_ecr_message_ids", "kind": "function", "doc": "

\n", "signature": "(parsed_ecr) -> dict:", "funcdef": "def"}, "phdi.validation.get_xml_element_details": {"fullname": "phdi.validation.get_xml_element_details", "modulename": "phdi.validation", "qualname": "get_xml_element_details", "kind": "function", "doc": "

Gets the name, value, of the xml element referenced as well\nas the details of any configured relative xml elements for\nthe referenced xml element and formats this information into\na single string for use in the validation messages.

\n\n
Parameters
\n\n
    \n
  • xml_element: The key xml element.
    • \n
  • config_field: A dictionary of the configured requirements\nfor the xml element.
    • \n
\n\n
Returns
\n\n
\n

A single string containing the information about the\n key xml element and its attribute(s).

\n
\n", "signature": "(xml_element, config_field) -> str:", "funcdef": "def"}, "phdi.validation.validate_xml_elements": {"fullname": "phdi.validation.validate_xml_elements", "modulename": "phdi.validation", "qualname": "validate_xml_elements", "kind": "function", "doc": "

Matches the xml_elements to the config field requirements for\nvalues, attributes, and relative xml element requirements for\nvalues, and attributes. Returns list of matching fields.

\n\n
Parameters
\n\n
    \n
  • xml_elements: A list of xml elements
    • \n
  • config_field: A dictionary of the requirements of the field.
    • \n
\n\n
Returns
\n\n
\n

A list of matched xml elemnts

\n
\n", "signature": "(xml_elements, config_field) -> list:", "funcdef": "def"}, "phdi.validation.validate_xml_attributes": {"fullname": "phdi.validation.validate_xml_attributes", "modulename": "phdi.validation", "qualname": "validate_xml_attributes", "kind": "function", "doc": "

Validates an xml element by checking if the configured attribute(s) exist\nand match the configured regex pattern for the value of the attribute.\nIf the xml element, and it's subsequent attribute(s), do not pass the checks,\nbased upon what is in the configuration, then an error message is added to\nthe validation results.

\n\n
Parameters
\n\n
    \n
  • xml_element: The xml element that will have its attributes validated.
    • \n
  • config_field: A dictionary that contains the configuration that\nspecifies what the attribute(s) for the xml element should be named\nand how the values should be patterned.
    • \n
\n\n
Returns
\n\n
\n

A list of errors or an empty list. If the list is empty then\n the validation was successful.

\n
\n", "signature": "(xml_element, config_field) -> list:", "funcdef": "def"}, "phdi.validation.validate_xml_value": {"fullname": "phdi.validation.validate_xml_value", "modulename": "phdi.validation", "qualname": "validate_xml_value", "kind": "function", "doc": "

Validates the value of an xml element (ie... between the tags) based upon\nvalidating the xml element exists within the relative xml element location\nbased upon the configuration of the parent of the xml element.\nThen it validates that the value of xml element matches the value pattern\nlisted in the config.

\n\n
Parameters
\n\n
    \n
  • xml_element: The key xml element being evaluated.
    • \n
  • config_field: A dictionary that contains the configuration information\nnecessary to validate the location and value of the key xml element
    • \n
\n\n
Returns
\n\n
\n

A list of error messages if validation fails, otherwise an\n empty list.

\n
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{"docs": {}, "df": 0, "i": {"docs": {}, "df": 0, "f": {"docs": {}, "df": 0, "y": {"docs": {"phdi.fhir.utils.get_field": {"tf": 1}}, "df": 1}}, "t": {"docs": {}, "df": 0, "i": {"docs": {}, "df": 0, "e": {"docs": {}, "df": 0, "s": {"docs": {"phdi.linkage.score_linkage_vs_truth": {"tf": 1}}, "df": 1}}}}}}}}}}}}, "pipeline": ["trimmer"], "_isPrebuiltIndex": true}; + + // mirrored in build-search-index.js (part 1) + // Also split on html tags. this is a cheap heuristic, but good enough. + elasticlunr.tokenizer.setSeperator(/[\s\-.;&_'"=,()]+|<[^>]*>/); + + let searchIndex; + if (docs._isPrebuiltIndex) { + console.info("using precompiled search index"); + searchIndex = elasticlunr.Index.load(docs); + } else { + console.time("building search index"); + // mirrored in build-search-index.js (part 2) + searchIndex = elasticlunr(function () { + this.pipeline.remove(elasticlunr.stemmer); + this.pipeline.remove(elasticlunr.stopWordFilter); + this.addField("qualname"); + this.addField("fullname"); + this.addField("annotation"); + this.addField("default_value"); + this.addField("signature"); + this.addField("bases"); + this.addField("doc"); + this.setRef("fullname"); + }); + for (let doc of docs) { + searchIndex.addDoc(doc); + } + console.timeEnd("building search index"); + } + + return (term) => searchIndex.search(term, { + fields: { + qualname: {boost: 4}, + fullname: {boost: 2}, + annotation: {boost: 2}, + default_value: {boost: 2}, + signature: {boost: 2}, + bases: {boost: 2}, + doc: {boost: 1}, + }, + expand: true + }); +})(); \ No newline at end of file