This repository is the home of the core Python rules -- py_library
,
py_binary
, py_test
, py_proto_library
, and related symbols that provide the basis for Python
support in Bazel. It also contains package installation rules for integrating with PyPI and other package indices. 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 package installation rules (pip_install
, pip_parse
etc.) are less stable. We may make breaking
changes as they evolve.
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.
- Status: Beta
- Full Feature Parity: No
See Bzlmod support for more details.
The next two sections cover using rules_python
with bzlmod and
the older way of configuring bazel with a WORKSPACE
file.
To import rules_python in your project, you first need to add it to your
MODULE.bazel
file, using the snippet provided in the
release you choose.
To register a hermetic Python toolchain rather than rely on a system-installed interpreter for runtime execution, you can add to the MODULE.bazel
file:
# Find the latest version number here: https://github.com/bazelbuild/rules_python/releases
# and change the version number if needed in the line below.
bazel_dep(name = "rules_python", version = "0.20.0")
# You do not have to use pip for the toolchain, but most people
# will use it for the dependency management.
pip = use_extension("@rules_python//python:extensions.bzl", "pip")
pip.parse(
name = "pip",
requirements_lock = "//:requirements_lock.txt",
)
use_repo(pip, "pip")
# Register a specific python toolchain instead of using the host version
python = use_extension("@rules_python//python:extensions.bzl", "python")
use_repo(python, "python3_10_toolchains")
register_toolchains(
"@python3_10_toolchains//:all",
)
To import rules_python in your project, you first need to add it to your
WORKSPACE
file, using the snippet provided in the
release you choose
To depend on a particular unreleased version, you can do:
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
rules_python_version = "740825b7f74930c62f44af95c9a4c1bd428d2c53" # Latest @ 2021-06-23
http_archive(
name = "rules_python",
# Bazel will print the proper value to add here during the first build.
# sha256 = "FIXME",
strip_prefix = "rules_python-{}".format(rules_python_version),
url = "https://github.com/bazelbuild/rules_python/archive/{}.zip".format(rules_python_version),
)
To register a hermetic Python toolchain rather than rely on a system-installed interpreter for runtime execution, you can add to the WORKSPACE
file:
load("@rules_python//python:repositories.bzl", "python_register_toolchains")
python_register_toolchains(
name = "python3_9",
# Available versions are listed in @rules_python//python:versions.bzl.
# We recommend using the same version your team is already standardized on.
python_version = "3.9",
)
load("@python3_9//:defs.bzl", "interpreter")
load("@rules_python//python:pip.bzl", "pip_parse")
pip_parse(
...
python_interpreter_target = interpreter,
...
)
After registration, your Python targets will use the toolchain's interpreter during execution, but a system-installed interpreter is still used to 'bootstrap' Python targets (see bazelbuild#691). You may also find some quirks while using this toolchain. Please refer to python-build-standalone documentation's Quirks section for details.
Python toolchains can be utilised in other bazel rules, such as genrule()
, by adding the toolchains=["@rules_python//python:current_py_toolchain"]
attribute. The path to the python interpreter can be obtained by using the $(PYTHON2)
and $(PYTHON3)
"Make" Variables. See the test_current_py_toolchain
target for an example.
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")
py_binary(
name = "main",
srcs = ["main.py"],
)
Usage of the packaging rules involves two main steps.
The package installation rules create two kinds of repositories: A central external repo that holds
downloaded wheel files, and individual external repos for each wheel's extracted
contents. Users only need to interact with the central external repo; the wheel repos
are essentially an implementation detail. The central external repo provides a
WORKSPACE
macro to create the wheel repos, as well as a function, requirement()
, for use in
BUILD
files that translates a pip package name into the label of a py_library
target in the appropriate wheel repo.
To add pip dependencies to your MODULE.bazel
file, use the pip.parse
extension, and call it to create the
central external repo and individual wheel external repos.
pip.parse(
name = "my_deps",
requirements_lock = "//:requirements_lock.txt",
)
use_repo(pip, "my_deps")
To add pip dependencies to your WORKSPACE
, load the pip_parse
function, and call it to create the
central external repo and individual wheel external repos.
load("@rules_python//python:pip.bzl", "pip_parse")
# Create a central repo that knows about the dependencies needed from
# requirements_lock.txt.
pip_parse(
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.
install_deps()
Note that since pip_parse
is a repository rule and therefore executes pip 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_parse
uses the system command "python3"
. This can be overridden by passing the
python_interpreter
attribute or python_interpreter_target
attribute to pip_parse
.
You can have multiple pip_parse
s in the same workspace. This will create multiple external 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_parse
is
re-executed in order to pick up a non-hermetic change to your environment (e.g.,
updating your system python
interpreter), you can force it to re-execute by running
bazel sync --only [pip_parse name]
.
Note: The pip_install
rule is deprecated. pip_parse
offers identical functionality and both pip_install
and pip_parse
now have the same implementation. The name pip_install
may be removed in a future version of the rules.
The maintainers have taken all reasonable efforts to faciliate a smooth transition, but some users of pip_install
will
need to replace their existing requirements.txt
with a fully resolved set of dependencies using a tool such as
pip-tools
or the compile_pip_requirements
repository rule.
Each extracted wheel repo contains a py_library
target representing
the wheel's contents. There are two ways to access this library. The
first is using 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")
py_library(
name = "mylib",
srcs = ["mylib.py"],
deps = [
":myotherlib",
requirement("some_pip_dep"),
requirement("another_pip_dep"),
]
)
The reason requirement()
exists is that the pattern for the labels,
while not expected to change frequently, is not guaranteed to be
stable. Using requirement()
ensures that you do not have to refactor
your BUILD
files if the pattern changes.
On the other hand, using requirement()
has several drawbacks; see
this issue for an enumeration. If you don't
want to use requirement()
then you can instead use the library
labels directly. For pip_parse
the labels are of the form
@{name}_{package}//:pkg
Here name
is the name
attribute that was passed to pip_parse
and
package
is the pip package name with characters that are illegal in
Bazel label names (e.g. -
, .
) replaced with _
. If you need to
update name
from "old" to "new", then you can run the following
buildozer command:
buildozer 'substitute deps @old_([^/]+)//:pkg @new_${1}//:pkg' //...:*
For pip_install
the labels are instead of the form
@{name}//pypi__{package}
Any 'extras' specified in the requirements lock-file will be automatically added as transitive dependencies of the
package. In the example above, you'd just put requirement("useful_dep")
.
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:
filegroup(
name = "whl_files",
data = [
whl_requirement("boto3"),
]
)
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.