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How to contribute

We'd love to accept your patches and contributions to this project. There are just a few small guidelines you need to follow.

Getting started

Before we can work on the code, we need to get a copy of it and setup some local environment and tools.

First, fork the code to your user and clone your fork. This gives you a private playground where you can do any edits you'd like. For this guide, we'll use the GitHub gh tool (Linux install). (More advanced users may prefer the GitHub UI and raw git commands).

gh repo fork bazelbuild/rules_python --clone --remote

Next, make sure you have a new enough version of Python installed that supports the various code formatters and other devtools. For a quick start, install pyenv and at least Python 3.9.15:

curl https://pyenv.run | bash
pyenv install 3.9.15
pyenv shell 3.9.15

Development workflow

It's suggested that you create what is called a "feature/topic branch" in your fork when you begin working on code you want to eventually send or code review.

git checkout main # Start our branch from the latest code
git checkout -b my-feature # Create and switch to our feature branch
git push origin my-feature # Cause the branch to be created in your fork.

From here, you then edit code and commit to your local branch. If you want to save your work to github, you use git push to do so:

git push origin my-feature

Once the code is in your github repo, you can then turn it into a Pull Request to the actual rules_python project and begin the code review process.

Running tests

Running tests is particularly easy thanks to Bazel, simply run:

bazel test //...

And it will run all the tests it can find. The first time you do this, it will probably take long time because various dependencies will need to be downloaded and setup. Subsequent runs will be faster, but there are many tests, and some of them are slow. If you're working on a particular area of code, you can run just the tests in those directories instead, which can speed up your edit-run cycle.

Updating tool dependencies

It's suggested to routinely update the tool versions within our repo - some of the tools are using requirement files compiled by uv and others use other means. In order to have everything self-documented, we have a special target - //private:requirements.update, which uses rules_multirun to run in sequence all of the requirement updating scripts in one go. This can be done once per release as we prepare for releases.

Formatting

Starlark files should be formatted by buildifier. Otherwise the Buildkite CI will fail with formatting/linting violations. We suggest using a pre-commit hook to automate this. First install pre-commit, then run

pre-commit install

Running buildifer manually

You can also run buildifier manually. To do this, install buildifier, and run the following command:

$ buildifier --lint=fix --warnings=native-py -warnings=all WORKSPACE

Replace the argument "WORKSPACE" with the file that you are linting.

Contributor License Agreement

Contributions to this project must be accompanied by a Contributor License Agreement. You (or your employer) retain the copyright to your contribution, this simply gives us permission to use and redistribute your contributions as part of the project. Head over to https://cla.developers.google.com/ to see your current agreements on file or to sign a new one.

You generally only need to submit a CLA once, so if you've already submitted one (even if it was for a different project), you probably don't need to do it again.

Code reviews

All submissions, including submissions by project members, require review. We use GitHub pull requests for this purpose. Consult GitHub Help for more information on using pull requests.

Commit messages

Commit messages (upon merging) and PR messages should follow the Conventional Commits style:

type(scope)!: <summary>

<body>

BREAKING CHANGE: <summary>

Where (scope) is optional, and ! is only required if there is a breaking change. If a breaking change is introduced, then BREAKING CHANGE: is required; see the Breaking Changes section for how to introduce breaking changes.

Common types:

  • build: means it affects the building or development workflow.
  • docs: means only documentation is being added, updated, or fixed.
  • feat: means a user-visible feature is being added.
  • fix: means a user-visible behavior is being fixed.
  • refactor: means some sort of code cleanup that doesn't change user-visible behavior.
  • revert: means a prior change is being reverted in some way.
  • test: means only tests are being added.

For the full details of types, see Conventional Commits.

Generated files

Some checked-in files are generated and need to be updated when a new PR is merged:

  • requirements lock files: These are usually generated by a compile_pip_requirements update target, which is usually in the same directory. e.g. bazel run //docs:requirements.update

Core rules

The bulk of this repo is owned and maintained by the Bazel Python community. However, since the core Python rules (py_binary and friends) are still bundled with Bazel itself, the Bazel team retains ownership of their stubs in this repository. This will be the case at least until the Python rules are fully migrated to Starlark code.

Practically, this means that a Bazel team member should approve any PR concerning the core Python logic. This includes everything under the python/ directory except for pip.bzl and requirements.txt.

Issues should be triaged as follows:

  • Anything concerning the way Bazel implements the core Python rules should be filed under bazelbuild/bazel, using the label team-Rules-python.

  • If the issue specifically concerns the rules_python stubs, it should be filed here in this repository and use the label core-rules.

  • Anything else, such as feature requests not related to existing core rules functionality, should also be filed in this repository but without the core-rules label.

(breaking-changes)=

Breaking Changes

Breaking changes are generally permitted, but we follow a 3-step process for introducing them. The intent behind this process is to balance the difficulty of version upgrades for users, maintaining multiple code paths, and being able to introduce modern functionality.

The general process is:

  1. In version N, introduce the new behavior, but it must be disabled by default. Users can opt into the new functionality when they upgrade to version N, which lets them try it and verify functionality.
  2. In version N+1, the new behavior can be enabled by default. Users can opt out if necessary, but doing so causes a warning to be issued.
  3. In version N+2, the new behavior is always enabled and cannot be opted out of. The API for the control mechanism can be removed in this release.

Note that the +1 and +2 releases are just examples; the steps are not required to happen in immediately subsequent releases.

Once The first major version is released, the process will be:

  1. In N.M.0 we introduce the new behaviour, but it is disabled by a feature flag.
  2. In N.M+1.0 we may choose the behaviour to become the default if it is not too disruptive.
  3. In N+1.0.0 we get rid of the old behaviour.

How to control breaking changes

The details of the control mechanism will depend on the situation. Below is a summary of some different options.

  • Environment variables are best for repository rule behavior. Environment variables can be propagated to rules and macros using the generated @rules_python_internal//:config.bzl file.
  • Attributes are applicable to macros and regular rules, especially when the behavior is likely to vary on a per-target basis.
  • User defined build settings (aka custom build flags) are applicable for rules when the behavior change generally wouldn't vary on a per-target basis. They also have the benefit that an entire code base can have them easily enabled by a bazel command line flag.
  • Allowlists allow a project to centrally control if something is enabled/disabled. Under the hood, they are basically a specialized custom build flag.

Note that attributes and flags can seamlessly interoperate by having the default controlled by a flag, and an attribute can override the flag setting. This allows a project to enable the new behavior by default while they work to fix problematic cases to prepare for the next upgrade.

What is considered a breaking change?

Precisely defining what constitutes a breaking change is hard because it's easy for someone, somewhere to depend on some observable behavior, despite our best efforts to thoroughly document what is or isn't supported and hiding any internal details.

In general, something is considered a breaking change when it changes the direct behavior of a supported public API. Simply being able to observe a behavior change doesn't necessarily mean it's a breaking change.

Long standing undocumented behavior is a large grey area and really depends on how load-bearing it has become and what sort of reasonable expectation of behavior there is.

Here's some examples of what would or wouldn't be considered a breaking change.

Breaking changes:

  • Renaming an function argument for public functions.
  • Enforcing stricter validation than was previously required when there's a sensible reason users would run afoul of it.
  • Changing the name of a public rule.

Not breaking changes:

  • Upgrading dependencies
  • Changing internal details, such as renaming an internal file.
  • Changing a rule to a macro.

FAQ

Installation errors when during git commit

If you did pre-commit install, various tools are run when you do git commit. This might show as an error such as:

[INFO] Installing environment for https://github.com/psf/black.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
An unexpected error has occurred: CalledProcessError: command: ...

To fix, you'll need to figure out what command is failing and why. Because these are tools that run locally, its likely you'll need to fix something with your environment or the installation of the tools. For Python tools (e.g. black or isort), you can try using a different Python version in your shell by using tools such as pyenv.