Automated creation of EntitySets from relational data stored in SQL databases

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The featuretools_sql library allows you to directly import your relational data into Featuretools to run automated feature engineering.

Installation

Install with pip:

python -m pip install "featuretools[sql]"

or from the Conda-forge channel on conda:

conda install -c conda-forge featuretools

Example

Simply pass in the database connection information:

from featuretools_sql.connector import DBConnector

sql_connector = DBConnector(
    system_name = "mysql",
    host = "127.0.0.1:3306"
    user = "root",
    password = "password",
    database = "db"
) 
entityset = sql_connector.get_entityset()

The entityset object will have the relationships and DataFrames already populated, allowing you to call featuretools.DFS and run automated feature generation.

import featuretools as ft

feature_defs, feature_matrix = ft.dfs(
    entityset=entityset,
    target_entity='target_table_name'
)

We currently supports importing data from the following relational database systems:

• MySQL
• PostgreSQL
• Snowflake

Support

The Featuretools community is happy to provide support to users. Project support can be found in four places depending on the type of question:

1. For usage questions, use Stack Overflow with the featuretools tag.
2. For bugs, issues, or feature requests start a Github issue.
3. For discussion regarding development, use Slack.
4. For everything else, the core developers can be reached by email at [email protected]

Built at Alteryx

featuretools_sql is an open source project maintained by Alteryx. To see the other open source projects we’re working on, visit Alteryx Open Source. If building impactful data science pipelines is important to you or your business, please get in touch.