Bazel rules to install Python dependencies with Poetry

Overview

rules_python_poetry

Bazel rules to install Python dependencies from a Poetry project. Works with native Python rules for Bazel.

Getting started

Add the following to your WORKSPACE file:

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

http_archive(
    name = "rules_python",
    url = "https://github.com/bazelbuild/rules_python/releases/download/0.1.0/rules_python-0.1.0.tar.gz",
    sha256 = "b6d46438523a3ec0f3cead544190ee13223a52f6a6765a29eae7b7cc24cc83a0",
)

http_archive(
    name = "rules_python_poetry",
    url = "https://github.com/martinxsliu/rules_python_poetry/archive/v0.1.0.tar.gz",
    sha256 = "8f0abc58a8fcf75341b4615c6b7d9bb254119577629f45c2b1bb60f60f31b301",
    strip_prefix = "rules_python_poetry-0.1.0"
)

load("@rules_python_poetry//:defs.bzl", "poetry_install_toolchain", "poetry_install")

# Optional, if you want to use a specific version of Poetry (1.0.10 is the default).
poetry_install_toolchain(poetry_version = "1.1.4")

poetry_install(
    name = "my_deps",
    pyproject_toml = "//path/to:pyproject.toml",
    poetry_lock = "//path/to:poetry.lock",
    dev = True,  # Optional
)

Under the hood, poetry_install uses Poetry to export a requirements.txt file which is then passed to rule_python's pip_install repository rule. You can consume dependencies the same way as you would with pip_install, e.g.:

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

py_library(
    name = "my_lib",
    srcs = ["my_lib.py"],
    deps = [
        ":my_other_lib",
        requirement("some_pip_dep"),
        requirement("another_pip_dep[some_extra]"),
    ],
)

Poetry dependencies

Poetry allows you to specify dependencies from different types of sources that are not automatically fetched and installed by the poetry_install rule. You will have to manually declare these dependencies.

See tests/multi/app for examples.

Local directory dependency

A dependency on a local directory, for example if you have multiple projects within a monorepo that depend on each other.

[tool.poetry.dependencies]
foo = {path = "../libs/foo"}

If the local dependency has a py_library target, you can include it in the deps attribute.

py_library(
    name = "my_lib",
    srcs = ["my_lib.py"],
    deps = [
        "//path/to/libs:foo",
    ],
)

Local file dependency

A dependency on a local tarball, for example if you have vendored packages.

[tool.poetry.dependencies]
foo = {path = "../vendor/foo-1.2.3.tar.gz"}

There are some options available. The first is to extract the archive and vendor the extracted files. Then add a py_library that can be included as a deps, like the local directory dependency.

The second is to use the py_archive repository rule to declare the archive as an external repository in your WORKSPACE file, e.g.:

load("@rules_python_poetry//:defs.bzl", "py_archive")

py_archive(
    name = "foo",
    archive = "//path/to/vendor:foo-1.2.3.tar.gz",
    strip_prefix = "foo-1.2.3",
)

The py_archive rule defines a target named :py_library that can be referenced like so:

py_library(
    name = "my_lib",
    srcs = ["my_lib.py"],
    deps = [
        "@foo//:py_library",
    ],
)

URL dependency

A dependency on a remote archive.

[tool.poetry.dependencies]
foo = {url = "https://example.com/packages/foo-1.2.3.tar.gz"}

You can use the py_archive repository rule to declare the remote archive as an external repository in your WORKSPACE file, e.g.:

load("@rules_python_poetry//:defs.bzl", "py_archive")

py_archive(
    name = "foo",
    url = "https://example.com/packages/foo-1.2.3.tar.gz",
    sha256 = "...",
    strip_prefix = "foo-1.2.3",
)

The py_archive rule defines a target named :py_library that can be referenced like so:

py_library(
    name = "my_lib",
    srcs = ["my_lib.py"],
    deps = [
        "@foo//:py_library",
    ],
)

Git dependency

Git dependencies are not currently supported. You can work around this by using a URL dependency instead of a git key.

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Comments
  • Reference python3 instead of python in hashbang

    Reference python3 instead of python in hashbang

    This fixes a build error on Ubuntu 20.04:

    ERROR: /workspace/WORKSPACE:41:15: fetching poetry_export rule //external:py_deps_export: Traceback (most recent call last):
            File "/workspace/out/external/rules_python_poetry/internal/export.bzl", line 19, column 17, in _poetry_export_impl
                    fail("Poetry strip dependencies failed:\n%s\n%s" % (result.stdout, result.stderr))
    

    Not all distros have python pointing to python3 by default yet. It's possible to resolve the issue by installing python-is-python3 but IMO explicitly specifying the version is better since it avoids this build error without needing to modify the host machine.

    A future improvement could be to allow specifying a Bazel target which points to the Python target to use.

    opened by bduffany 0
  • How can I have a py_test target use this poetry toolchain?

    How can I have a py_test target use this poetry toolchain?

    my BUILD file is:

    load("@rules_python//python:defs.bzl", "py_test")
    
    py_test(
        name = "test_example",
        srcs = ["test_example.py"],
    )
    

    but when running test, it is still using the system python instead of the poetry venv, is this possible and if so can you update the README?

    opened by ruidc 0
Releases(v0.1.0)
  • v0.1.0(Nov 16, 2020)

Owner
Martin Liu
Martin Liu
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