Contribution Guide#

Getting Started#

Supported Python Versions#

The lowest currently supported version is Python 3.8. At a minimum you will need Python 3.8 for code changes and 3.12 if you plan on doing documentation building / changes.

You can use various tools to manage multiple Python versions on your system including:

We use the lowest supported version in our type-checking CI, this ensures that the changes you made are backward compatible.

Setting up the environment#

Tip

We maintain a Makefile with several commands to help with common tasks. You can run make help to see a list of available commands.

If you are utilizing GitHub Codespaces, the environment will bootstrap itself automatically. The steps below are for local development.

  1. Install PDM:

    Using our Make target to install PDM#
    make install-pdm
    Using pipx#
    pipx install pdm
    Using Homebrew#
    brew install pdm

  2. Run make install to create a virtual environment and install the required development dependencies or run the PDM installation command manually:

    Installing the documentation dependencies#
    pdm install

  3. If you’re working on the documentation and need to build it locally, install the extra dependencies with make docs-install or:

    Installing the documentation dependencies#
    pdm install -G:docs

  4. Install pre-commit:

    Using pip#
    python3 -m pip install pre-commit
    Using pipx#
    pipx install pre-commit
    Using Homebrew#
    brew install pre-commit

  5. Install our pre-commit hooks. by running make install or:

    Installing pre-commit hooks#
    pre-commit install --install-hooks

Tip

Many modern IDEs like PyCharm or VS Code will enable the PDM-managed virtualenv that is created in step 2 for you automatically. If your IDE / editor does not offer this functionality, then you will need to manually activate the virtualenv yourself. Otherwise you may encounter errors or unexpected behaviour when trying to run the commands referenced within this document.

To activate the virtualenv manually, please consult PDM’s documentation on working with virtual environments. A simpler alternative is using the PDM plugin pdm-shell.

The rest of this document will assume this environment is active wherever commands are referenced.

Code contributions#

Workflow#

  1. Fork the Litestar repository

  2. Clone your fork locally with git

  3. Set up the environment

  4. Make your changes

  5. (Optional) Run pre-commit run --all-files to run linters and formatters. This step is optional and will be executed automatically by git before you make a commit, but you may want to run it manually in order to apply fixes

  6. Commit your changes to git. We follow conventional commits which are enforced using a pre-commit hook.

  7. Push the changes to your fork

  8. Open a pull request. Give the pull request a descriptive title indicating what it changes. The style of the PR title should also follow conventional commits, and this is enforced using a GitHub action.

  9. Add yourself as a contributor using the all-contributors bot

Guidelines for writing code#

  • Code should be Pythonic and zen

  • All code should be fully typed. This is enforced via mypy and Pyright

    • When requiring complex types, use a type alias. Check types if a type alias for your use case already exists

    • If something cannot be typed correctly due to a limitation of the type checkers, you may use typing.cast() to rectify the situation. However, you should only use this as a last resort if you’ve exhausted all other options of type narrowing, such as isinstance() checks and type guards.

    • You may use a properly scoped type: ignore if you ensured that a line is correct, but mypy / pyright has issues with it.

      Properly scoped meaning do not use blank type: ignore, instead supply the specific error code, e.g., type: ignore[attr-defined]

  • If you are adding or modifying existing code, ensure that it’s fully tested. 100% test coverage is mandatory, and will be checked on the PR using SonarCloud and Codecov

  • All functions, methods, classes, and attributes should be documented with a docstring. We use the Google docstring style. If you come across a function or method that doesn’t conform to this standard, please update it as you go

  • When adding a new public interface, it has to be included in the reference documentation located in docs/reference. If applicable, add or modify examples in the docs related to the new functionality implemented, following the guidelines established in Adding examples.

Writing and running tests#

Tests are contained within the tests directory, and follow the same directory structure as the litestar module. If you are adding a test case, it should be located within the correct submodule of tests. E.g., tests for litestar/utils/sync.py reside in tests/utils/test_sync.py.

The Makefile includes several commands for running tests:

  • make test to run tests located in tests

  • make test-examples to run tests located in docs/examples/tests

  • make test-all to run all tests

  • make coverage to run tests with coverage and generate an html report

The tests make use of pytest-xdist to speed up test runs. These are enabled by default when running make test, make test-all or make coverage. Due to the nature of pytest-xdist, attaching a debugger isn’t as straightforward. For debugging, it’s recommended to run the tests individually with pytest <test name> or via an IDE, which will skip pytest-xdist.

Running type checkers#

We use mypy and pyright to enforce type safety. You can run them with:

  • make mypy

  • make pyright

  • make type-check to run both

  • make lint to run pre-commit hooks and type checkers.

Our type checkers are run on Python 3.8 in CI, so you should make sure to run them on the same version locally as well.

Project documentation#

The documentation is located in the /docs directory and is written in reStructuredText with the Sphinx. library. If you’re unfamiliar with any of those, reStructuredText primer and Sphinx quickstart are recommended reads.

Docs theme and appearance#

We welcome contributions that enhance / improve the appearance and usability of the docs. We use the excellent PyData Sphinx Theme theme, which comes with a lot of options out of the box. If you wish to contribute to the docs style / setup, or static site generation, you should consult the theme docs as a first step.

Running the docs locally#

To run or build the docs locally, you need to first install the required dependencies:

Installing the documentation dependencies#
pdm install -G:docs

Then you can serve the documentation with our helpful Makefile targets:

Serving the documentation locally#
make docs-serve

Writing and editing docs#

We welcome contributions that enhance / improve the content of the docs. Feel free to add examples, clarify text, restructure the docs, etc., but make sure to follow these guidelines:

  • Write text in idiomatic English, using simple language

  • Do not use contractions for ease of reading for non-native English speakers

  • Opt for Oxford commas when listing a series of terms

  • Keep examples simple and self contained (see Adding examples). This is to ensure they are tested alongside the rest of the test suite and properly type checked and linted.

  • Provide links where applicable.

  • Use intersphinx wherever possible when referencing external libraries

  • Provide diagrams using Mermaid where applicable and possible

Adding examples#

The examples from the docs are located in their own modules inside the /docs/examples folder. This makes it easier to test them alongside the rest of the test suite, ensuring they do not become stale as Litestar evolves.

Please follow the next guidelines when adding a new example:

  • Add the example in the corresponding module directory in /docs/examples or create a new one if necessary

  • Create a suite for the module in /tests/examples that tests the aspects of the example that it demonstrates

  • Reference the example in the rst file with an external reference code block, e.g.

An example of how to use literal includes of external files#
.. literalinclude:: /examples/test_thing.py
   :caption: All includes should have a descriptive caption

Automatically execute examples#

Our docs include a Sphinx extension that can automatically run requests against example apps and include their result in the documentation page when its being built. This only requires 2 steps:

  1. Create an example file with an app object in it, which is an instance of Litestar

  2. Add a comment in the form of # run: /hello to the example file

When building the docs (or serving them locally), a process serving the app instance will be launched, and the requests specified in the comments will be run against it. The comments will be stripped from the result, and the output of the curl invocation inserted after the example code-block.

The # run: syntax is nothing special; everything after the colon will be passed to the curl command that’s being invoked. The URL is built automatically, so the specified path can just be a path relative to the app.

In practice, this looks like the following:

An example of how to use the automatic example runner#
from typing import Dict

from litestar import Litestar, get


@get("/")
def hello_world() -> Dict[str, str]:
    """Handler function that returns a greeting dictionary."""
    return {"hello": "world"}


app = Litestar(route_handlers=[hello_world])

# run: /

This is equivalent to:

An example of how to use the automatic example runner#
   from typing import Dict

   from litestar import Litestar, get


   @get("/")
   def hello_world() -> Dict[str, str]:
       """Handler function that returns a greeting dictionary."""
       return {"hello": "world"}


   app = Litestar(route_handlers=[hello_world])

Run it

> curl http://127.0.0.1:8000/
{"hello": "world"}

Creating a New Release#

  1. Checkout the main branch:

    Checking out the main branch of the litestar repository#
    git checkout main

  2. Run the release preparation script:

    Preparing a new release#
    python tools/prepare_release.py <new version number> --update-version --create-draft-release

    Replace <new version number> with the desired version number following the versioning scheme.

    This script will:

    • Update the version in pyproject.toml

    • Generate a changelog entry in 2.x Changelog

    • Create a draft release on GitHub

  3. Review the generated changelog entry in 2.x Changelog to ensure it looks correct.

  4. Commit the changes to main:

    Committing the changes to the main branch#
    git commit -am "chore(release): prepare release vX.Y.Z"

    Replace vX.Y.Z with the actual version number.

  5. Create a new branch for the release:

    Creating a new branch for the release#
    git checkout -b vX.Y.Z

  6. Push the changes to a vX.Y.Z branch:

    Pushing the changes to the vX.Y.Z branch#
    git push origin vX.Y.Z

  7. Open a pull request from the vX.Y.Z branch to main.

  8. Once the pull request is approved, go to the draft release on GitHub (the release preparation script will provide a link).

  9. Review the release notes in the draft release to ensure they look correct.

  10. If everything looks good, click “Publish release” to make the release official.

  11. Go to the Release Action and approve the release workflow if necessary.

  12. Check that the release workflow runs successfully.

Note

The version number should follow semantic versioning and PEP 440.