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We'd love you to contribute to Pydantic!


Questions, feature requests and bug reports are all welcome as discussions or issues. However, to report a security vulnerability, please see our security policy.

To make it as simple as possible for us to help you, please include the output of the following call in your issue:

python -c "import pydantic.version; print(pydantic.version.version_info())"
If you're using Pydantic prior to v2.0 please use:
python -c "import pydantic.utils; print(pydantic.utils.version_info())"
If you're using Pydantic prior to v1.3 (when version_info() was added), please manually include OS, Python version and pydantic version.

Please try to always include the above unless you're unable to install Pydantic or know it's not relevant to your question or feature request.

Pull Requests

It should be extremely simple to get started and create a Pull Request. Pydantic is released regularly so you should see your improvements release in a matter of days or weeks 🚀.

Unless your change is trivial (typo, docs tweak etc.), please create an issue to discuss the change before creating a pull request.

Pydantic V1 is in maintenance mode

Pydantic v1 is in maintenance mode, meaning that only bug fixes and security fixes will be accepted. New features should be targeted at Pydantic v2.

To submit a fix to Pydantic v1, use the 1.10.X-fixes branch.

If you're looking for something to get your teeth into, check out the "help wanted" label on github.

To make contributing as easy and fast as possible, you'll want to run tests and linting locally. Luckily, Pydantic has few dependencies, doesn't require compiling and tests don't need access to databases, etc. Because of this, setting up and running the tests should be very simple.


tl;dr: use make format to fix formatting, make to run tests and linting & make docs to build the docs.


You'll need the following prerequisites:

  • Any Python version between Python 3.8 and 3.11
  • virtualenv or other virtual environment tool
  • git
  • make
  • PDM

Installation and setup

Fork the repository on GitHub and clone your fork locally.

# Clone your fork and cd into the repo directory
git clone [email protected]:<your username>/pydantic.git
cd pydantic

# Install PDM and pre-commit
# We use pipx here, for other options see:
# To get pipx itself:
pipx install pdm
pipx install pre-commit

# Install pydantic, dependencies, test dependencies and doc dependencies
make install

Check out a new branch and make your changes

Create a new branch for your changes.

# Checkout a new branch and make your changes
git checkout -b my-new-feature-branch
# Make your changes...

Run tests and linting

Run tests and linting locally to make sure everything is working as expected.

# Run automated code formatting and linting
make format
# Pydantic uses ruff, an awesome Python linter written in rust

# Run tests and linting
# There are a few sub-commands in Makefile like `test`, `testcov` and `lint`
# which you might want to use, but generally just `make` should be all you need.
# You can run `make help` to see more options.

Build documentation

If you've made any changes to the documentation (including changes to function signatures, class definitions, or docstrings that will appear in the API documentation), make sure it builds successfully.

# Build documentation
make docs
# If you have changed the documentation, make sure it builds successfully.
# You can also use `pdm run mkdocs serve` to serve the documentation at localhost:8000

Commit and push your changes

Commit your changes, push your branch to GitHub, and create a pull request.

Please follow the pull request template and fill in as much information as possible. Link to any relevant issues and include a description of your changes.

When your pull request is ready for review, add a comment with the message "please review" and we'll take a look as soon as we can.

Code style and requirements


Documentation style

Documentation is written in Markdown and built using Material for MkDocs. API documentation is build from docstrings using mkdocstrings.

Code documentation

When contributing to Pydantic, please make sure that all code is well documented. The following should be documented using properly formatted docstrings:

  • Modules
  • Class definitions
  • Function definitions
  • Module-level variables

Pydantic uses Google-style docstrings formatted according to PEP 257 guidelines. (See Example Google Style Python Docstrings for further examples.)

pydocstyle is used for linting docstrings. You can run make format to check your docstrings.

Where this is a conflict between Google-style docstrings and pydocstyle linting, follow the pydocstyle linting hints.

Class attributes and function arguments should be documented in the format "name: description." When applicable, a return type should be documented with just a description. Types are inferred from the signature.

class Foo:
    """A class docstring.

        bar: A description of bar. Defaults to "bar".

    bar: str = 'bar'
def bar(self, baz: int) -> str:
    """A function docstring.

        baz: A description of `baz`.

        A description of the return value.

    return 'bar'

You may include example code in docstrings. This code should be complete, self-contained, and runnable. Docstring examples are tested using doctest, so make sure they are correct and complete. See FieldInfo.from_annotated_attribute() for an example.

Class and instance attributes

Class attributes should be documented in the class docstring.

Instance attributes should be documented as "Args" in the __init__ docstring.

Documentation Style

In general, documentation should be written in a friendly, approachable style. It should be easy to read and understand, and should be as concise as possible while still being complete.

Code examples are encouraged, but should be kept short and simple. However, every code example should be complete, self-contained, and runnable. (If you're not sure how to do this, ask for help!) We prefer print output to naked asserts, but if you're testing something that doesn't have a useful print output, asserts are fine.

Pydantic's unit test will test all code examples in the documentation, so it's important that they are correct and complete. When adding a new code example, use the following to test examples and update their formatting and output:

# Run tests and update code examples
pytest tests/ --update-examples

Debugging Python and Rust

If you're working with pydantic and pydantic-core, you might find it helpful to debug Python and Rust code together. Here's a quick guide on how to do that. This tutorial is done in VSCode, but you can use similar steps in other IDEs.


Pydantic v1 Pydantic v2

Pydantic has a badge that you can use to show that your project uses Pydantic. You can use this badge in your

With Markdown

[![Pydantic v1](](

[![Pydantic v2](](

With reStructuredText

.. image::
    :alt: Pydantic

.. image::
    :alt: Pydantic


<a href=""><img src="" alt="Pydantic Version 1" style="max-width:100%;"></a>

<a href=""><img src="" alt="Pydantic Version 2" style="max-width:100%;"></a>