How can I contribute to FastSK?¶

We welcome contributions from all members of the community– and there are lots of ways to help without editing the code! Answering questions, helping others, reaching out and improving the documentations are immensely valuable to the community.

It also helps us if you spread the word: reference the library from blog posts on the awesome projects it made possible, shout out on Twitter every time it has helped you, or simply star the repo to say “thank you”.

Ways to contribute¶

There are lots of ways you can contribute to FastSK:

Submitting issues on Github to report bugs or make feature requests
Fixing outstanding issues with the existing code
Implementing new features
Adding support for new models and datasets
Contributing to the examples or to the documentation

All are equally valuable to the community.

Submitting a new issue or feature request¶

Do your best to follow these guidelines when submitting an issue or a feature request. It will make it easier for us to come back to you quickly and with good feedback.

Found a bug?¶

FastSK can remain robust and reliable thanks to users who notify us of the problems they encounter. So thank you for reporting an issue.

We also have a suite of tests intended to detect bugs before they enter the codebase. That said, they still happen (Turing completeness and all) so it’s up to you to report the bugs you find! We would really appreciate it if you could make sure the bug was not already reported (use the search bar on Github under Issues).

To help us fix your issue quickly, please follow these steps:

Include your OS type and version, the versions of Python, PyTorch and Tensorflow when applicable;
A short, self-contained, code snippet that allows us to reproduce the bug in less than 30s;
Provide the full traceback if an exception is raised.

Do you want a new feature: a component, a recipe, or something else?¶

A world-class feature request addresses the following points:

Motivation first:

Is it related to a problem/frustration with the library? If so, please explain why. Providing a code snippet that demonstrates the problem is best.
Is it related to something you would need for a project? We’d love to hear about it!
Is it something you worked on and think could benefit the community? Awesome! Tell us what problem it solved for you.

Write a full paragraph describing the feature;
Provide a code snippet that demonstrates its future use;
In case this is related to a paper, please attach a link;
Attach any additional information (drawings, screenshots, etc.) you think may help.

Start contributing! (Pull Requests)¶

Before writing code, we strongly advise you to search through the exising PRs or issues to make sure that nobody is already working on the same thing. If you are unsure, it is always a good idea to open an issue to get some feedback.

You will need basic git proficiency to be able to contribute to FastSK. git is not the easiest tool to use but it has the greatest manual. Type git --help in a shell and enjoy. If you prefer books, Pro Git is a very good reference.

Follow these steps to start contributing:

Fork the repository by clicking on the ‘Fork’ button on the repository’s page. This creates a copy of the code under your GitHub user account.

Clone your fork to your local disk, and add the base repository as a remote:

$ git clone git@github.com:<your Github handle>/FastSK.git
$ cd FastSK
$ git remote add upstream https://github.com/QData/FastSK

Create a new branch to hold your development changes:
```
$ git checkout -b a-descriptive-name-for-my-changes
```
do not work on the master branch.
Set up a development environment by running the following commands in a virtual environment:
```
$ cd FastSK
$ pip install -e . ".[dev]"
$ pip install black isort pytest pytest-xdist
```
This will install FastSK in editable mode and install black and isort, packages we use for code formatting.

(If FastSK was already installed in the virtual environment, remove it with pip uninstall FastSK before reinstalling it in editable mode with the -e flag.)
Develop the features on your branch.

As you work on the features, you should make sure that the test suite passes:
```
$ make test
```
(or just simply pytest.)

Tip: if you’re fixing just one or two tests, you can run only the last tests that failed using pytest --lf.

FastSK relies on black and isort to format its source code consistently. After you make changes, format them with:
```
$ make format
```
You can run quality checks to make sure your code is formatted properly using this command:
```
$ make lint
```
Once you’re happy with your changes, add changed files using git add and make a commit with git commit to record your changes locally:
```
$ git add modified_file.py
$ git commit
```
Please write good commit messages.

It is a good idea to sync your copy of the code with the original repository regularly. This way you can quickly account for changes:
```
$ git fetch upstream
$ git rebase upstream/master
```
Push the changes to your account using:
```
$ git push -u origin a-descriptive-name-for-my-changes
```
Add documentation.

Our docs are in the docs/ folder. Thanks to sphinx-automodule, adding documentation for a new code file should just be two lines. Our docs will automatically generate from the comments you added to your code. If you’re adding an attack recipe, add a reference in attack_recipes.rst. If you’re adding a transformation, add a reference in transformation.rst, etc.

You can build the docs and view the updates using make docs. If you’re adding a tutorial or something where you want to update the docs multiple times, you can run make docs-auto. This will run a server using sphinx-autobuild that should automatically reload whenever you change a file.
Once you are satisfied (and the checklist below is happy too), go to the webpage of your fork on GitHub. Click on ‘Pull request’ to send your changes to the project maintainers for review.
It’s ok if maintainers ask you for changes. It happens to core contributors too! So everyone can see the changes in the Pull request, work in your local branch and push the changes to your fork. They will automatically appear in the pull request.

Checklist¶

The title of your pull request should be a summary of its contribution.
If your pull request adresses an issue, please mention the issue number in the pull request description to make sure they are linked (and people consulting the issue know you are working on it);
To indicate a work in progress please mark it as a draft on Github.
Make sure existing tests pass.
Add relevant tests. No quality testing = no merge.
All public methods must have informative docstrings that work nicely with sphinx.

Tests¶

You can run FastSK tests with pytest. Just type make test.