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chore(Documentation): Adding of class diagram templates.
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33 changes: 33 additions & 0 deletions .docs/design.class.md
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[<< Back](./design.md)

# Class Diagrams & ERDs
![Class Diagram](./designs/root.class.drawio.png)
## Managers
### IExampleManager
A description of the example manager.

**+ ExamplePublicFunc<type>(someVariable: string): returnType**

A description for the example public function.

## Engines
### IExampleEngine
A description of the example engine.

**+ ExamplePublicFunc<type>(someVariable: string): returnType**

A description for the example public function.

## Data Access
### IExampleDataAccess
A description of the example data access.

**+ ExamplePublicFunc<type>(someVariable: string): returnType**

A description for the example public function.

## Models
### Model1
Model 1 description

[<< Back](./design.md)
29 changes: 16 additions & 13 deletions .docs/design.md
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The software architecture diagram(s) and design(s).

### Introduction
The basic problem statmement that this project is to resolve.
TODO: Project architecture high-level description goes here.

### Architecture
#### Use Cases
Below is an example diagram drawn with the VS Code draw.io extension.

![Example Design](./designs/use_cases.drawio.png)

#### Class Diagrams & ERDs

#### Sequence Diagrams

### Performance Considerations

### Security Considerations
The architecture of the solution is a layered one. Specifically 3 layers deep. These layers are also only allowed to depend on components adjacent of itself or down (never up - e.g. Engines shouldn't depend on managers). All components should be color coded correctly based on the description below for ease of reading.
| Layer | Description |
| --- | --- |
| Managers (Green) | These components orchestrate other code paths and often fascilitate use cases and as such would be the entry point to the application. |
| Engines (Orange) | These components perform complex operations exclusively. |
| Data Access (Grey) | These components perform IO operations exclusively. |
| Models (Purple) | These are simple data structures (DTOs) / models and occasionally enums. |

### Design Documentation
| Content | Description
| -- | -- |
| [Use Cases](./design.use_cases.md) | Use case diagram(s).
| [High-Level](./design.high_level.md) | High-level system components.
| [Class Diagrams](./design.class.md) | Class diagram(s).
| [Sequence Diagrams](./design.sequence.md) | Sequence diagram(s).

[<< Back](../README.md)
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27 changes: 0 additions & 27 deletions .docs/docker_support.md

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37 changes: 25 additions & 12 deletions src/environments/README.md → .docs/getting_started.md
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# environments
[<< Back](../README.md)

# Getting Started
## Description
This page describes how to set up Windows and Mac environments for working with this repo.

In addition, this directory provides various conda environments that can be used cross-platform to work with various libraries and versioning restrictions that may come with them. For this you can refer to the [conda](./conda/README.md) page.

## Getting Started
### Local
- Python >= 3.7 required.
- [Setup your environment.](./environments/README.md)

To build the Python package locally, from the root of the project, run `python -m build` (Legacy way: `python setup.py sdist bdist_wheel`).
### PIP Installation
```
pip install -U --no-cache-dir frostaura
````
#### Example Usage (See [all the examples here](https://github.com/faGH/fa.intelligence.notebooks/tree/main/examples).)
```
from frostaura import (models,
data_access,
engines,
managers)

html_data_access = data_access.HtmlDataAccess()
engine = engines.FinvizAssetValuationEngine(html_data_access=html_data_access)

vars(engine.valuate(symbol='AAPL', company_name='Apple Inc.'))
```
### MiniForge (conda)
#### Windows
- Install Miniforge from [their GitHub page](https://github.com/conda-forge/miniforge). In our case [Miniforge3-Windows-x86_64](https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Windows-x86_64.exe).
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- [Run this notebook to check library versions post-setup](./scripts/check_version.ipynb).
- Now you can run any notebooks just like you did the above. Remember to choose your environment that you registered in the setup stage, as your Python interpreter of choice.
## Contribute
In order to contribute, simply fork the repository, make changes and create a pull request.

## Support
If you enjoy FrostAura open-source content and would like to support us in continuous delivery, please consider a donation via a platform of your choice.

| Supported Platforms | Link |
| ------------------- | ---- |
| PayPal | [Donate via Paypal](https://www.paypal.com/donate/?hosted_button_id=SVEXJC9HFBJ72) |

For any queries, contact [email protected].
[<< Back](../README.md)
21 changes: 3 additions & 18 deletions .docs/support_contribute.md
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[<< Back](../README.md)

## Cleanup Required After Forking the Template
### Text Replacements
Replace all instances of the following strings across all files with your specifications.

| Phrase | Description |
| -- | -- |
| \<DIVISION> | The division of the company. E.g. 'intelligence'.
| \<APPLICATION> | The name or namespace of the application. E.g. clients.pointskeeper.
| fa.templates | The name of the template at the top of the README.md file.

### Adding Environment Variables
| Variable | Description |
| -- | -- |
| DOCKER_USERNAME | The Docker Hub username to use to publish the Docker image after a build.
| DOCKER_PASSWORD | The Docker Hub password to use to publish the Docker image after a build.
| PROJECT_IDENTITY | The name or namespace of the application. E.g. clients.pointskeeper.
| PROJECT_DESCRIPTION | A brief description for the software.

## Contribute
To contribute, simply fork the repository, make changes and create a pull request.

## Credits
- [Jeff Heaton's GitHub](https://github.com/jeffheaton/t81_558_deep_learning/blob/master/)

## Support
To support me in publishing and optimizing strategies, please use my referral link below it won't cost you anything but will help me lots :)

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13 changes: 9 additions & 4 deletions README.md
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# fa.templates
# fa.intelligence.notebooks
## Description
This is an empty template repository that can be forked for any new projects that should follow FrostAura repository standards.
FrostAura Intelligence provides a range of open-source notebooks for Python-based machine learning solutions like:
- Utilities
- Environments
- Labs
- Experiments

## Status
| Project | Status | Platform
| --- | --- | --- |
| \<APPLICATION> | [![Containerization Workflow](https://github.com/faGH/fa.templates/actions/workflows/containerization_workflow.yml/badge.svg)](https://github.com/faGH/fa.templates/actions/workflows/containerization_workflow.yml) | GitHub Actions
| FrostAura Components PIP Package | [![Package FrostAura Components Workflow](https://github.com/faGH/fa.intelligence.notebooks/actions/workflows/package_components_workflow.yml/badge.svg)](https://github.com/faGH/fa.intelligence.notebooks/actions/workflows/package_components_workflow.yml) | GitHub Actions

## Documentation
| Content | Description
| -- | -- |
| [Repo Structure](.docs/repo_structure.md) | The structuring of the repo.
| [Getting Started](.docs/getting_started.md) | Start using the repo.
| [Design](.docs/design.md) | The software architecture diagram(s) and design(s).
| [Workflow](.docs/workflow.md) | The software automated software pipeline(s).
| [Docker Support](.docs/docker_support.md) | Details about how docker is set up for this repo.
| [Support & Contribute](.docs/support_contribute.md) | Basic queries, constributing to the repo and supporting the team(s) working on this open-source repo.
45 changes: 0 additions & 45 deletions README.old.md

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