README.md - platform/external/bazelbuild-rules_python - Git at Google

 # Python Rules for Bazel

 [![Build status](https://badge.buildkite.com/1bcfe58b6f5741aacb09b12485969ba7a1205955a45b53e854.svg?branch=main)](https://buildkite.com/bazel/python-rules-python-postsubmit)

 ## Overview

 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 indices.

 Documentation for rules_python  lives in the
 [`docs/`](https://github.com/bazelbuild/rules_python/tree/main/docs)
 directory and in the
 [Bazel Build Encyclopedia](https://docs.bazel.build/versions/master/be/python.html).

 Examples live in the [examples](examples) directory.

 Currently, the core rules build into the Bazel binary, and the symbols in this
 repository are simple aliases. However, we are migrating the rules to Starlark and removing them from the Bazel binary. Therefore, the future-proof way to depend on Python rules is via this repository. See[`Migrating from the Bundled Rules`](#Migrating-from-the-bundled-rules) below.

 The core rules are stable. Their implementation in Bazel is subject to Bazel's
 [backward compatibility policy](https://docs.bazel.build/versions/master/backward-compatibility.html).
 Once migrated to rules_python, they may evolve at a different
 rate, but this repository will still follow [semantic versioning](https://semver.org).

 The Bazel community maintains this repository. 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 [How to contribute](CONTRIBUTING.md) page for information on our development workflow.

 ## Bzlmod support

 - Status: Beta
 - Full Feature Parity: No

 See [Bzlmod support](BZLMOD_SUPPORT.md) for more details.

 ## Getting started

 The following two sections cover using `rules_python` with bzlmod and
 the older way of configuring bazel with a `WORKSPACE` file.

 ### Using bzlmod

 **IMPORTANT: bzlmod support is still in Beta; APIs are subject to change.**

 The first step to using rules_python with bzlmod is to add the dependency to
 your MODULE.bazel file:

 ```starlark
 # Update the version "0.0.0" to the release found here:
 # https://github.com/bazelbuild/rules_python/releases.
 bazel_dep(name = "rules_python", version = "0.0.0")
 ```

 Once added, you can load the rules and use them:

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

 py_binary(...)
 ```

 Depending on what you're doing, you likely want to do some additional
 configuration to control what Python version is used; read the following
 sections for how to do that.

 #### Toolchain registration with bzlmod

 A default toolchain is automatically configured depending on
 `rules_python`. Note, however, the version used tracks the most recent Python
 release and will change often.

 If you want to use a specific Python version for your programs, then how
 to do so depends on if you're configuring the root module or not. The root
 module is special because it can set the *default* Python version, which
 is used by the version-unaware rules (e.g. `//python:py_binary.bzl` et al). For
 submodules, it's recommended to use the version-aware rules to pin your programs
 to a specific Python version so they don't accidentally run with a different
 version configured by the root module.

 ##### Configuring and using the default Python version

 To specify what the default Python version is, set `is_default = True` when
 calling `python.toolchain()`. This can only be done by the root module; it is
 silently ignored if a submodule does it. Similarly, using the version-unaware
 rules (which always use the default Python version) should only be done by the
 root module. If submodules use them, then they may run with a different Python
 version than they expect.

 ```starlark
 python = use_extension("@rules_python//python/extensions:python.bzl", "python")

 python.toolchain(
     python_version = "3.11",
     is_default = True,
 )
 ```

 Then use the base rules from e.g. `//python:py_binary.bzl`.

 ##### Pinning to a Python version

 Pinning to a version allows targets to force that a specific Python version is
 used, even if the root module configures a different version as a default. This
 is most useful for two cases:

 1. For submodules to ensure they run with the appropriate Python version
 2. To allow incremental, per-target, upgrading to newer Python versions,
    typically in a mono-repo situation.

 To configure a submodule with the version-aware rules, request the particular
 version you need, then use the `@python_versions` repo to use the rules that
 force specific versions:

 ```starlark
 python = use_extension("@rules_python//python/extensions:python.bzl", "python")

 python.toolchain(
     python_version = "3.11",
 )
 use_repo(python, "python_versions")
 ```

 Then use e.g. `load("@python_versions//3.11:defs.bzl", "py_binary")` to use
 the rules that force that particular version. Multiple versions can be specified
 and use within a single build.

 For more documentation, see the bzlmod examples under the [examples](examples) folder.  Look for the examples that contain a `MODULE.bazel` file.

 ##### Other toolchain details

 The `python.toolchain()` call makes its contents available under a repo named
 `python_X_Y`, where X and Y are the major and minor versions. For example,
 `python.toolchain(python_version="3.11")` creates the repo `@python_3_11`.
 Remember to call `use_repo()` to make repos visible to your module:
 `use_repo(python, "python_3_11")`

 ### Using a WORKSPACE file

 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](https://github.com/bazelbuild/rules_python/releases)

 To depend on a particular unreleased version, you can do the following:

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


 # Update the SHA and VERSION to the lastest version available here:
 # https://github.com/bazelbuild/rules_python/releases.

 SHA="84aec9e21cc56fbc7f1335035a71c850d1b9b5cc6ff497306f84cced9a769841"

 VERSION="0.23.1"

 http_archive(
     name = "rules_python",
     sha256 = SHA,
     strip_prefix = "rules_python-{}".format(VERSION),
     url = "https://github.com/bazelbuild/rules_python/releases/download/{}/rules_python-{}.tar.gz".format(VERSION,VERSION),
 )

 load("@rules_python//python:repositories.bzl", "py_repositories")

 py_repositories()
 ```

 #### Toolchain registration

 To register a hermetic Python toolchain rather than rely on a system-installed interpreter for runtime execution, you can add to the `WORKSPACE` file:

 ```starlark
 load("@rules_python//python:repositories.bzl", "python_register_toolchains")

 python_register_toolchains(
     name = "python_3_11",
     # Available versions are listed in @rules_python//python:versions.bzl.
     # We recommend using the same version your team is already standardized on.
     python_version = "3.11",
 )

 load("@python_3_11//: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 https://github.com/bazelbuild/rules_python/issues/691).
 You may also find some quirks while using this toolchain. Please refer to [python-build-standalone documentation's _Quirks_ section](https://python-build-standalone.readthedocs.io/en/latest/quirks.html).

 ### Toolchain usage in other rules

 Python toolchains can be utilized in other bazel rules, such as `genrule()`, by adding the `toolchains=["@rules_python//python:current_py_toolchain"]` attribute. You can obtain the path to the Python interpreter using the `$(PYTHON2)` and `$(PYTHON3)` ["Make" Variables](https://bazel.build/reference/be/make-variables). See the [`test_current_py_toolchain`](tests/load_from_macro/BUILD.bazel) target for an example.

 ### "Hello World"

 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 the following:

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

 py_binary(
   name = "main",
   srcs = ["main.py"],
 )
 ```

 ## Using dependencies from PyPI

 Using PyPI packages (aka "pip install") involves two main steps.

 1. [Installing third_party packages](#installing-third_party-packages)
 2. [Using third_party packages as dependencies](#using-third_party-packages-as-dependencies

 ### Installing third_party packages

 #### Using bzlmod

 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. Include in the `MODULE.bazel` the toolchain extension as shown in the first bzlmod example above.

 ```starlark
 pip = use_extension("@rules_python//python/extensions:pip.bzl", "pip")
 pip.parse(
     hub_name = "my_deps",
     python_version = "3.11",
     requirements_lock = "//:requirements_lock_3_11.txt",
 )
 use_repo(pip, "my_deps")
 ```
 For more documentation, including how the rules can update/create a requirements file, see the bzlmod examples under the [examples](examples) folder.

 #### Using a WORKSPACE file

 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.

 ```starlark
 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()
 ```

 #### pip rules

 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"`. To override this, pass in the
 `python_interpreter` attribute or `python_interpreter_target` attribute to `pip_parse`.

 You can have multiple `pip_parse`s in the same workspace.  Or use the pip extension multiple times when using bzlmod.
 This configuration will create multiple external repos that have no relation to one another
 and may result in downloading the same wheels numerous times.

 As with any repository rule, if you would like to ensure that `pip_parse` is
 re-executed 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 made all reasonable efforts to facilitate a smooth transition. Still, 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.

 ### Using third_party packages as dependencies

 Each extracted wheel repo contains a `py_library` target representing
 the wheel's contents. There are two ways to access this library. The
 first uses the `requirement()` function defined in the central
 repo's `//:requirements.bzl` file. This function maps a pip package
 name to a label:

 ```starlark
 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 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][requirements-drawbacks] for an enumeration. If you don't
 want to use `requirement()`, you can use the library
 labels directly instead. For `pip_parse`, the labels are of the following form:

 ```starlark
 @{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:

 ```shell
 buildozer 'substitute deps @old_([^/]+)//:pkg @new_${1}//:pkg' //...:*
 ```

 For `pip_install`, the labels are instead of the form:

 ```starlark
 @{name}//pypi__{package}
 ```

 [requirements-drawbacks]: https://github.com/bazelbuild/rules_python/issues/414

 #### 'Extras' dependencies

 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")`.

 ### 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:

 ```starlark
 filegroup(
     name = "whl_files",
     data = [
         whl_requirement("boto3"),
     ]
 )
 ```
 # Python Gazelle plugin

 [Gazelle](https://github.com/bazelbuild/bazel-gazelle)
 is a build file generator for Bazel projects. It can create new `BUILD.bazel` files for a project that follows language conventions and update existing build files to include new sources, dependencies, and options.

 Bazel may run Gazelle using the Gazelle rule, or it may be installed and run as a command line tool.

 See the documentation for Gazelle with rules_python [here](gazelle).

 ## 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](https://github.com/bazelbuild/buildtools/blob/master/buildifier/README.md)
 fix is available to automatically migrate `BUILD` and `.bzl` files to add the
 appropriate `load()` statements and rewrite uses of `native.py_*`.

 ```sh
 # 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](#Getting-started) above.

 Note that Starlark-defined bundled symbols underneath
 `@bazel_tools//tools/python` are also deprecated. These are not yet rewritten
 by buildifier.
	# Python Rules for Bazel

	[![Build status](https://badge.buildkite.com/1bcfe58b6f5741aacb09b12485969ba7a1205955a45b53e854.svg?branch=main)](https://buildkite.com/bazel/python-rules-python-postsubmit)

	## Overview

	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 indices.

	Documentation for rules_python lives in the
	[`docs/`](https://github.com/bazelbuild/rules_python/tree/main/docs)
	directory and in the
	[Bazel Build Encyclopedia](https://docs.bazel.build/versions/master/be/python.html).

	Examples live in the [examples](examples) directory.

	Currently, the core rules build into the Bazel binary, and the symbols in this
	repository are simple aliases. However, we are migrating the rules to Starlark and removing them from the Bazel binary. Therefore, the future-proof way to depend on Python rules is via this repository. See[`Migrating from the Bundled Rules`](#Migrating-from-the-bundled-rules) below.

	The core rules are stable. Their implementation in Bazel is subject to Bazel's
	[backward compatibility policy](https://docs.bazel.build/versions/master/backward-compatibility.html).
	Once migrated to rules_python, they may evolve at a different
	rate, but this repository will still follow [semantic versioning](https://semver.org).

	The Bazel community maintains this repository. 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 [How to contribute](CONTRIBUTING.md) page for information on our development workflow.

	## Bzlmod support

	- Status: Beta
	- Full Feature Parity: No

	See [Bzlmod support](BZLMOD_SUPPORT.md) for more details.

	## Getting started

	The following two sections cover using `rules_python` with bzlmod and
	the older way of configuring bazel with a `WORKSPACE` file.

	### Using bzlmod

	IMPORTANT: bzlmod support is still in Beta; APIs are subject to change.

	The first step to using rules_python with bzlmod is to add the dependency to
	your MODULE.bazel file:

	```starlark
	# Update the version "0.0.0" to the release found here:
	# https://github.com/bazelbuild/rules_python/releases.
	bazel_dep(name = "rules_python", version = "0.0.0")
	```

	Once added, you can load the rules and use them:

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

	py_binary(...)
	```

	Depending on what you're doing, you likely want to do some additional
	configuration to control what Python version is used; read the following
	sections for how to do that.

	#### Toolchain registration with bzlmod

	A default toolchain is automatically configured depending on
	`rules_python`. Note, however, the version used tracks the most recent Python
	release and will change often.

	If you want to use a specific Python version for your programs, then how
	to do so depends on if you're configuring the root module or not. The root
	module is special because it can set the default Python version, which
	is used by the version-unaware rules (e.g. `//python:py_binary.bzl` et al). For
	submodules, it's recommended to use the version-aware rules to pin your programs
	to a specific Python version so they don't accidentally run with a different
	version configured by the root module.

	##### Configuring and using the default Python version

	To specify what the default Python version is, set `is_default = True` when
	calling `python.toolchain()`. This can only be done by the root module; it is
	silently ignored if a submodule does it. Similarly, using the version-unaware
	rules (which always use the default Python version) should only be done by the
	root module. If submodules use them, then they may run with a different Python
	version than they expect.

	```starlark
	python = use_extension("@rules_python//python/extensions:python.bzl", "python")

	python.toolchain(
	python_version = "3.11",
	is_default = True,
	)
	```

	Then use the base rules from e.g. `//python:py_binary.bzl`.

	##### Pinning to a Python version

	Pinning to a version allows targets to force that a specific Python version is
	used, even if the root module configures a different version as a default. This
	is most useful for two cases:

	1. For submodules to ensure they run with the appropriate Python version
	2. To allow incremental, per-target, upgrading to newer Python versions,
	typically in a mono-repo situation.

	To configure a submodule with the version-aware rules, request the particular
	version you need, then use the `@python_versions` repo to use the rules that
	force specific versions:

	```starlark
	python = use_extension("@rules_python//python/extensions:python.bzl", "python")

	python.toolchain(
	python_version = "3.11",
	)
	use_repo(python, "python_versions")
	```

	Then use e.g. `load("@python_versions//3.11:defs.bzl", "py_binary")` to use
	the rules that force that particular version. Multiple versions can be specified
	and use within a single build.

	For more documentation, see the bzlmod examples under the [examples](examples) folder. Look for the examples that contain a `MODULE.bazel` file.

	##### Other toolchain details

	The `python.toolchain()` call makes its contents available under a repo named
	`python_X_Y`, where X and Y are the major and minor versions. For example,
	`python.toolchain(python_version="3.11")` creates the repo `@python_3_11`.
	Remember to call `use_repo()` to make repos visible to your module:
	`use_repo(python, "python_3_11")`

	### Using a WORKSPACE file

	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](https://github.com/bazelbuild/rules_python/releases)

	To depend on a particular unreleased version, you can do the following:

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


	# Update the SHA and VERSION to the lastest version available here:
	# https://github.com/bazelbuild/rules_python/releases.

	SHA="84aec9e21cc56fbc7f1335035a71c850d1b9b5cc6ff497306f84cced9a769841"

	VERSION="0.23.1"

	http_archive(
	name = "rules_python",
	sha256 = SHA,
	strip_prefix = "rules_python-{}".format(VERSION),
	url = "https://github.com/bazelbuild/rules_python/releases/download/{}/rules_python-{}.tar.gz".format(VERSION,VERSION),
	)

	load("@rules_python//python:repositories.bzl", "py_repositories")

	py_repositories()
	```

	#### Toolchain registration

	To register a hermetic Python toolchain rather than rely on a system-installed interpreter for runtime execution, you can add to the `WORKSPACE` file:

	```starlark
	load("@rules_python//python:repositories.bzl", "python_register_toolchains")

	python_register_toolchains(
	name = "python_3_11",
	# Available versions are listed in @rules_python//python:versions.bzl.
	# We recommend using the same version your team is already standardized on.
	python_version = "3.11",
	)

	load("@python_3_11//: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 https://github.com/bazelbuild/rules_python/issues/691).
	You may also find some quirks while using this toolchain. Please refer to [python-build-standalone documentation's _Quirks_ section](https://python-build-standalone.readthedocs.io/en/latest/quirks.html).

	### Toolchain usage in other rules

	Python toolchains can be utilized in other bazel rules, such as `genrule()`, by adding the `toolchains=["@rules_python//python:current_py_toolchain"]` attribute. You can obtain the path to the Python interpreter using the `$(PYTHON2)` and `$(PYTHON3)` ["Make" Variables](https://bazel.build/reference/be/make-variables). See the [`test_current_py_toolchain`](tests/load_from_macro/BUILD.bazel) target for an example.

	### "Hello World"

	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 the following:

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

	py_binary(
	name = "main",
	srcs = ["main.py"],
	)
	```

	## Using dependencies from PyPI

	Using PyPI packages (aka "pip install") involves two main steps.

	1. [Installing third_party packages](#installing-third_party-packages)
	2. [Using third_party packages as dependencies](#using-third_party-packages-as-dependencies

	### Installing third_party packages

	#### Using bzlmod

	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. Include in the `MODULE.bazel` the toolchain extension as shown in the first bzlmod example above.

	```starlark
	pip = use_extension("@rules_python//python/extensions:pip.bzl", "pip")
	pip.parse(
	hub_name = "my_deps",
	python_version = "3.11",
	requirements_lock = "//:requirements_lock_3_11.txt",
	)
	use_repo(pip, "my_deps")
	```
	For more documentation, including how the rules can update/create a requirements file, see the bzlmod examples under the [examples](examples) folder.

	#### Using a WORKSPACE file

	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.

	```starlark
	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()
	```

	#### pip rules

	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"`. To override this, pass in the
	`python_interpreter` attribute or `python_interpreter_target` attribute to `pip_parse`.

	You can have multiple `pip_parse`s in the same workspace. Or use the pip extension multiple times when using bzlmod.
	This configuration will create multiple external repos that have no relation to one another
	and may result in downloading the same wheels numerous times.

	As with any repository rule, if you would like to ensure that `pip_parse` is
	re-executed 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 made all reasonable efforts to facilitate a smooth transition. Still, 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.

	### Using third_party packages as dependencies

	Each extracted wheel repo contains a `py_library` target representing
	the wheel's contents. There are two ways to access this library. The
	first uses the `requirement()` function defined in the central
	repo's `//:requirements.bzl` file. This function maps a pip package
	name to a label:

	```starlark
	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 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][requirements-drawbacks] for an enumeration. If you don't
	want to use `requirement()`, you can use the library
	labels directly instead. For `pip_parse`, the labels are of the following form:

	```starlark
	@{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:

	```shell
	buildozer 'substitute deps @old_([^/]+)//:pkg @new_${1}//:pkg' //...:*
	```

	For `pip_install`, the labels are instead of the form:

	```starlark
	@{name}//pypi__{package}
	```

	[requirements-drawbacks]: https://github.com/bazelbuild/rules_python/issues/414

	#### 'Extras' dependencies

	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")`.

	### 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:

	```starlark
	filegroup(
	name = "whl_files",
	data = [
	whl_requirement("boto3"),
	]
	)
	```
	# Python Gazelle plugin

	[Gazelle](https://github.com/bazelbuild/bazel-gazelle)
	is a build file generator for Bazel projects. It can create new `BUILD.bazel` files for a project that follows language conventions and update existing build files to include new sources, dependencies, and options.

	Bazel may run Gazelle using the Gazelle rule, or it may be installed and run as a command line tool.

	See the documentation for Gazelle with rules_python [here](gazelle).

	## 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](https://github.com/bazelbuild/buildtools/blob/master/buildifier/README.md)
	fix is available to automatically migrate `BUILD` and `.bzl` files to add the
	appropriate `load()` statements and rewrite uses of `native.py_*`.

	```sh
	# 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](#Getting-started) above.

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