Python Rules for Bazel

This repository is the home of the core Python rules -- py_library, py_binary, py_test, and related symbols that provide the basis for Python support in Bazel. It also contains packaging rules for integrating with PyPI (pip). Documentation lives in the docs/ directory and in the Bazel Build Encyclopedia.

Currently the core rules are bundled with Bazel itself, and the symbols in this repository are simple aliases. However, in the future the rules will be migrated to Starlark and debundled from Bazel. Therefore, the future-proof way to depend on Python rules is via this repository. SeeMigrating from the Bundled Rules below.

The core rules are stable. Their implementation in Bazel is subject to Bazel's backward compatibility policy. Once they are fully migrated to rules_python, they may evolve at a different rate, but this repository will still follow semantic versioning.

The packaging rules (pip_install, etc.) are less stable. We may make breaking changes as they evolve. There are no guarantees for rules underneath the experimental/ directory.

This repository is maintained by the Bazel community. Neither Google, nor the Bazel team, provides support for the code. However, this repository is part of the test suite used to vet new Bazel releases. See the How to contribute page for information on our development workflow.

Getting started

To import rules_python in your project, you first need to add it to your WORKSPACE file:

load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
    name = "rules_python",
    url = "",
    sha256 = "778197e26c5fbeb07ac2a2c5ae405b30f6cb7ad1f5510ea6fdac03bded96cc6f",

To depend on a particular unreleased version (not recommended), you can do:

load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

rules_python_version = "c8c79aae9aa1b61d199ad03d5fe06338febd0774" # Latest @ 2020-10-15

    name = "rules_python",
    sha256 = "5be9610a959772697f57ec66bb58c8132970686ed7fb0f1cf81b22ddf12f5368",
    strip_prefix = "rules_python-{}".format(rules_python_version),
    url = "{}.zip".format(rules_python_version),

Once you've imported the rule set into your WORKSPACE using any of these methods, you can then load the core rules in your BUILD files with:

load("@rules_python//python:defs.bzl", "py_binary")

  name = "main",
  srcs = [""],

Using the packaging rules

The packaging rules create two kinds of repositories: A central repo that holds downloaded wheel files, and individual repos for each wheel's extracted contents. Users only need to interact with the central repo; the wheel repos are essentially an implementation detail. The central repo provides a WORKSPACE macro to create the wheel repos, as well as a function to call in BUILD files to translate a pip package name into the label of a py_library target in the appropriate wheel repo.

Importing pip dependencies

To add pip dependencies to your WORKSPACE load the pip_install function, and call it to create the individual wheel repos.

load("@rules_python//python:pip.bzl", "pip_install")

# Create a central repo that knows about the dependencies needed for
# requirements.txt.
   name = "my_deps",
   requirements = "//path/to:requirements.txt",

Note that since pip is executed at WORKSPACE-evaluation time, Bazel has no information about the Python toolchain and cannot enforce that the interpreter used to invoke pip matches the interpreter used to run py_binary targets. By default, pip_install uses the system command "python3". This can be overridden by passing the python_interpreter attribute or python_interpreter_target attribute to pip_install.

You can have multiple pip_installs in the same workspace, e.g. for Python 2 and Python 3. This will create multiple central repos that have no relation to one another, and may result in downloading the same wheels multiple times.

As with any repository rule, if you would like to ensure that pip_install is re-executed in order to pick up a non-hermetic change to your environment (e.g., updating your system python interpreter), you can completely flush out your repo cache with bazel clean --expunge.

Fetch pip dependencies lazily (experimental)

One pain point with pip_install is the need to download all dependencies resolved by your requirements.txt before the bazel analysis phase can start. For large python monorepos this can take a long time, especially on slow connections.

pip_parse provides a solution to this problem. If you can provide a lock file of all your python dependencies pip_parse will translate each requirement into its own external repository. Bazel will only fetch/build wheels for the requirements in the subgraph of your build target.

There are API differences between pip_parse and pip_install:

  1. pip_parse requires a fully resolved lock file of your python dependencies. You can generate this using pip-compile, or a virtualenv and pip freeze. pip_parse uses a label argument called requirements_lock instead of requirements to make this distinction clear.

  2. pip_parse translates your requirements into a starlark macro called install_deps. You must call this macro in your WORKSPACE to declare your dependencies.

    load("@rules_python//python:pip.bzl", "pip_parse")

    Create a central repo that knows about the dependencies needed from


    name = "my_deps",
    requirements_lock = "//path/to:requirements_lock.txt",

    Load the starlark macro which will define your dependencies.

    load("@my_deps//:requirements.bzl", "install_deps")

    Call it to define repos for your requirements.


Importing pip dependencies with pip_import (legacy)

The deprecated pip_import can still be used if needed.

load("@rules_python//python/legacy_pip_import:pip.bzl", "pip_import", "pip_repositories")

# Create a central repo that knows about the dependencies needed for requirements.txt.
pip_import(   # or pip3_import
   name = "my_deps",
   requirements = "//path/to:requirements.txt",

# Load the central repo's install function from its `//:requirements.bzl` file, and call it.
load("@my_deps//:requirements.bzl", "pip_install")

An example can be found in examples/legacy_pip_import.

Consuming pip dependencies

Each extracted wheel repo contains a py_library target representing the wheel's contents. Rather than depend on this target's label directly -- which would require hardcoding the wheel repo's mangled name into your BUILD files -- you should instead use the requirement() function defined in the central repo's //:requirements.bzl file. This function maps a pip package name to a label.

load("@my_deps//:requirements.bzl", "requirement")

    name = "mylib",
    srcs = [""],
    deps = [

For reference, the wheel repos are canonically named following the pattern: @{central_repo_name}_pypi__{distribution}_{version}. Characters in the distribution and version that are illegal in Bazel label names (e.g. -, .) are replaced with _. While this naming pattern doesn't change often, it is not guaranted to remain stable, so use of the requirement() function is recommended.

'Extras' requirement consumption

When using the legacy pip_import, you must specify the extra in the argument to the requirement macro. For example:

    name = "mylib",
    srcs = [""],
    deps = [

If using pip_install or pip_parse, any extras specified in the requirements file will be automatically linked as a dependency of the package so that you don't need to specify the extra. In the example above, you'd just put requirement("useful_dep").

Consuming Wheel Dists Directly

If you need to depend on the wheel dists themselves, for instance to pass them to some other packaging tool, you can get a handle to them with the whl_requirement macro. For example:

    name = "whl_files",	
    data = [	

Migrating from the bundled rules

The core rules are currently available in Bazel as built-in symbols, but this form is deprecated. Instead, you should depend on rules_python in your WORKSPACE file and load the Python rules from @rules_python//python:defs.bzl.

A buildifier fix is available to automatically migrate BUILD and .bzl files to add the appropriate load() statements and rewrite uses of native.py_*.

# Also consider using the -r flag to modify an entire workspace.
buildifier --lint=fix --warnings=native-py <files>

Currently the WORKSPACE file needs to be updated manually as per Getting started above.

Note that Starlark-defined bundled symbols underneath @bazel_tools//tools/python are also deprecated. These are not yet rewritten by buildifier.