https://github.com/Substra/substra

Low-level Python library used to interact with a Substra network
https://github.com/Substra/substra

federated-learning federated-learning-framework

Last synced: 2 months ago
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Low-level Python library used to interact with a Substra network

• Host: GitHub
• URL: https://github.com/Substra/substra
• Owner: Substra
• License: apache-2.0
• Created: 2019-10-25T09:22:58.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2024-03-22T10:01:39.000Z (2 months ago)
• Last Synced: 2024-03-22T10:53:48.644Z (2 months ago)
• Topics: federated-learning, federated-learning-framework
• Language: Python
• Homepage: https://docs.substra.org
• Size: 5.35 MB
• Stars: 266
• Watchers: 9
• Forks: 35
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Codeowners: .github/CODEOWNERS

Lists

• awesome-production-machine-learning - Substra - Substra is an open-source framework for privacy-preserving, traceable and collaborative Machine Learning. (Privacy Preserving ML)
• Awesome-FL - substra - commit/Substra/substra) | | [Substra](https://github.com/Substra) | | | [[DOC](https://doc.substra.ai/index.html)] | (federated learning framework / table)

README

        


 









  

  

  

  









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](https://www.melloddy.eu/) 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](https://owkin.com/) and is now hosted by the [Linux Foundation for AI and Data](https://lfaidata.foundation/). Today Owkin is the main contributor to Substra.

Join the discussion on [Slack](https://join.slack.com/t/substra-workspace/shared_invite/zt-1fqnk0nw6-xoPwuLJ8dAPXThfyldX8yA) and [subscribe here](https://lists.lfaidata.foundation/g/substra-announce/join) to our newsletter.

## To start using Substra

Have a look at our [documentation](https://docs.substra.org/).

Try out our [MNIST example](https://docs.substra.org/en/stable/substrafl_doc/examples/index.html#example-to-get-started-using-the-pytorch-interface).

## Support

If you need support, please either raise an issue on Github or ask on [Slack](https://join.slack.com/t/substra-workspace/shared_invite/zt-1fqnk0nw6-xoPwuLJ8dAPXThfyldX8yA).

## 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:

```sh

pip install -e ".[dev]"

```

To run all tests, use the following command:

```sh

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](https://github.com/psf/black).

This relies on hooks managed by [pre-commit](https://pre-commit.com/), which you can set up as follows.

Install [pre-commit](https://pre-commit.com/), then run:

```sh

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:

```sh

make doc

```

Documentation will be available in the *references/* directory.