Awesome
<div align="left"> <a href="https://join.slack.com/t/substra-workspace/shared_invite/zt-1fqnk0nw6-xoPwuLJ8dAPXThfyldX8yA"><img src="https://img.shields.io/badge/chat-on%20slack-blue?logo=slack" /></a> <a href="https://docs.substra.org/"><img src="https://img.shields.io/badge/read-docs-purple?logo=mdbook" /></a> <br /><br /></div> <div align="center"> <picture> <object-position: center> <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/substra/substra/main/Substra-logo-white.svg"> <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/substra/substra/main/Substra-logo-colour.svg"> <img alt="Substra" src="https://raw.githubusercontent.com/substra/substra/main/Substra-logo-colour.svg" width="500"> </picture> </div> <br> <br>Substra is an open source federated learning (FL) software. It enables the training and validation of machine learning models on distributed datasets. It provides a flexible Python interface and a web application to run federated learning training at scale. This specific repository is the low-level Python library used to interact with a Substra network.
Substra's main usage is in production environments. It has already been deployed and used by hospitals and biotech companies (see the MELLODDY project for instance). Substra can also be used on a single machine to perform FL simulations and debug code.
Substra was originally developed by Owkin and is now hosted by the Linux Foundation for AI and Data. Today Owkin is the main contributor to Substra.
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To start using Substra
Have a look at our documentation.
Try out our MNIST example.
Support
If you need support, please either raise an issue on Github or ask on Slack.
Contributing
Substra warmly welcomes any contribution. Feel free to fork the repo and create a pull request.
Setup
To setup the project in development mode, run:
pip install -e ".[dev]"
To run all tests, use the following command:
make test
Some of the tests require Docker running on your machine before running them.
Code formatting
You can opt into auto-formatting of code on pre-commit using Black.
This relies on hooks managed by pre-commit, which you can set up as follows.
Install pre-commit, then run:
pre-commit install
Documentation generation
To generate the command line interface documentation, sdk and schemas documentation, the python version
must be 3.8. Run the following command:
make doc
Documentation will be available in the references/ directory.
Changelog generation
The changelog is managed with towncrier.
To add a new entry in the changelog, add a file in the changes folder. The file name should have the following structure:
<unique_id>.<change_type>.
The unique_id is a unique identifier, we currently use the PR number.
The change_type can be of the following types: added, changed, removed, fixed.
To generate the changelog (for example during a release), use the following command (you must have the dev dependencies installed):
towncrier build --version=<x.y.z>
You can use the --draft option to see what would be generated without actually writing to the changelog (and without removing the fragments).