Everything you need to know to contribute efficiently to the project.

Whatever the way you wish to contribute to the project, please respect the code of conduct.

• torchscan - The actual torchscan library
• tests - Python unit tests
• docs - Sphinx documentation building
• scripts - Example and utilities scripts

This project uses the following integrations to ensure proper codebase maintenance:

• Github Worklow - run jobs for package build and coverage
• Codacy - analyzes commits for code quality
• Codecov - reports back coverage results

As a contributor, you will only have to ensure coverage of your code by adding appropriate unit testing of your code.

Whether you encountered a problem, or you have a feature suggestion, your input has value and can be used by contributors to reference it in their developments. For this purpose, we advise you to use Github issues.

First, check whether the topic wasn't already covered in an open / closed issue. If not, feel free to open a new one! When doing so, use issue templates whenever possible and provide enough information for other contributors to jump in.

If you are wondering how to do something with TorchScan, or a more general question, you should consider checking out Github discussions. See it as a Q&A forum, or the TorchScan-specific StackOverflow!

1 - Fork this repository by clicking on the "Fork" button at the top right of the page. This will create a copy of the project under your GitHub account (cf. Fork a repo).

2 - Clone your fork to your local disk and set the upstream to this repo

git clone git@github.com:<YOUR_GITHUB_ACCOUNT>/torch-scan.git
cd torch-scan
git remote add upstream https://github.com/frgfm/torch-scan.git

3 - You should not work on the main branch, so let's create a new one

git checkout -b a-short-description

4 - You only have to set your development environment now. First uninstall any existing installation of the library with pip uninstall torch-scan, then:

pip install -e ".[dev]"
pre-commit install

• Code: ensure to provide docstrings to your Python code. In doing so, please follow Google-style so it can ease the process of documentation later.
• Commit message: please follow Udacity guide

In order to run the same unit tests as the CI workflows, you can run unittests locally:

make test

The CI will also run some sanity checks (header format, dependency consistency, etc.), which you can run as follows:

make quality

This will read pyproject.toml and run:

• lint checking, formatting (ruff)
• type annotation checking (mypy)

You can apply automatic fix to most of those by running:

make style

Push your last modifications to your remote branch

git push -u origin a-short-description

Then open a Pull Request from your fork's branch. Follow the instructions of the Pull Request template and then click on "Create a pull request".