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Python Enhancement Proposals

PEP 711 – PyBI: a standard format for distributing Python Binaries

Nathaniel J. Smith <njs at>
Discourse thread
Standards Track

Table of Contents


“Like wheels, but instead of a pre-built python package, it’s a pre-built python interpreter”


End goal: has pre-built packages for all Python versions on all popular platforms, so automated tools can easily grab any of them and set it up. It becomes quick and easy to try Python prereleases, pin Python versions in CI, make a temporary environment to reproduce a bug report that only happens on a specific Python point release, etc.

First step (this PEP): define a standard packaging file format to hold pre-built Python interpreters, that reuses existing Python packaging standards as much as possible.


Example pybi builds are available at They’re zip files, so you can unpack them and poke around inside if you want to get a feel for how they’re laid out.

You can also look at the tooling I used to create them.



Filename: {distribution}-{version}[-{build tag}]-{platform tag}.pybi

This matches the wheel file format defined in PEP 427, except dropping the {python tag} and {abi tag} and changing the extension from .whl.pybi.

For example:

  • cpython-3.9.3-manylinux_2014.pybi
  • cpython-3.10b2-win_amd64.pybi

Just like for wheels, if a pybi supports multiple platforms, you can separate them by dots to make a “compressed tag set”:

  • cpython-3.9.5-macosx_11_0_x86_64.macosx_11_0_arm64.pybi

(Though in practice this probably won’t be used much, e.g. the above filename is more idiomatically written as cpython-3.9.5-macosx_11_0_universal2.pybi.)

File contents

A .pybi file is a zip file, that can be unpacked directly into an arbitrary location and then used as a self-contained Python environment. There’s no .data directory or install scheme keys, because the Python environment knows which install scheme it’s using, so it can just put things in the right places to start with.

The “arbitrary location” part is important: the pybi can’t contain any hardcoded absolute paths. In particular, any preinstalled scripts MUST NOT embed absolute paths in their shebang lines.

Similar to wheels’ <package>-<version>.dist-info directory, the pybi archive must contain a top-level directory named pybi-info/. (Rationale: calling it pybi-info instead dist-info makes sure that tools don’t get confused about which kind of metadata they’re looking at; leaving off the {name}-{version} part is fine because only one pybi can be installed into a given directory.) The pybi-info/ directory contains at least the following files:

  • .../PYBI: metadata about the archive itself, in the same RFC822-ish format as METADATA and WHEEL files:
    Pybi-Version: 1.0
    Generator: {name} {version}
    Tag: {platform tag}
    Tag: {another platform tag}
    Tag: {...and so on...}
    Build: 1   # optional
  • .../RECORD: same as in wheels, except see the note about symlinks, below.
  • .../METADATA: In the same format as described in the current core metadata spec, except that the following keys are forbidden because they don’t make sense:
    • Requires-Dist
    • Provides-Extra
    • Requires-Python

    And also there are some new, required keys described below.

Pybi-specific core metadata

Here’s an example of the new METADATA fields, before we give the full details:

Pybi-Environment-Marker-Variables: {"implementation_name": "cpython", "implementation_version": "3.10.8", "os_name": "posix", "platform_machine": "x86_64", "platform_system": "Linux", "python_full_version": "3.10.8", "platform_python_implementation": "CPython", "python_version": "3.10", "sys_platform": "linux"}
Pybi-Paths: {"stdlib": "lib/python3.10", "platstdlib": "lib/python3.10", "purelib": "lib/python3.10/site-packages", "platlib": "lib/python3.10/site-packages", "include": "include/python3.10", "platinclude": "include/python3.10", "scripts": "bin", "data": "."}
Pybi-Wheel-Tag: cp310-cp310-PLATFORM
Pybi-Wheel-Tag: cp310-abi3-PLATFORM
Pybi-Wheel-Tag: cp310-none-PLATFORM
Pybi-Wheel-Tag: cp39-abi3-PLATFORM
Pybi-Wheel-Tag: cp38-abi3-PLATFORM
Pybi-Wheel-Tag: cp37-abi3-PLATFORM
Pybi-Wheel-Tag: cp36-abi3-PLATFORM
Pybi-Wheel-Tag: cp35-abi3-PLATFORM
Pybi-Wheel-Tag: cp34-abi3-PLATFORM
Pybi-Wheel-Tag: cp33-abi3-PLATFORM
Pybi-Wheel-Tag: cp32-abi3-PLATFORM
Pybi-Wheel-Tag: py310-none-PLATFORM
Pybi-Wheel-Tag: py3-none-PLATFORM
Pybi-Wheel-Tag: py39-none-PLATFORM
Pybi-Wheel-Tag: py38-none-PLATFORM
Pybi-Wheel-Tag: py37-none-PLATFORM
Pybi-Wheel-Tag: py36-none-PLATFORM
Pybi-Wheel-Tag: py35-none-PLATFORM
Pybi-Wheel-Tag: py34-none-PLATFORM
Pybi-Wheel-Tag: py33-none-PLATFORM
Pybi-Wheel-Tag: py32-none-PLATFORM
Pybi-Wheel-Tag: py31-none-PLATFORM
Pybi-Wheel-Tag: py30-none-PLATFORM
Pybi-Wheel-Tag: py310-none-any
Pybi-Wheel-Tag: py3-none-any
Pybi-Wheel-Tag: py39-none-any
Pybi-Wheel-Tag: py38-none-any
Pybi-Wheel-Tag: py37-none-any
Pybi-Wheel-Tag: py36-none-any
Pybi-Wheel-Tag: py35-none-any
Pybi-Wheel-Tag: py34-none-any
Pybi-Wheel-Tag: py33-none-any
Pybi-Wheel-Tag: py32-none-any
Pybi-Wheel-Tag: py31-none-any
Pybi-Wheel-Tag: py30-none-any


  • Pybi-Environment-Marker-Variables: The value of all PEP 508 environment marker variables that are static across installs of this Pybi, as a JSON dict. So for example:
    • python_version will always be present, because a Python 3.10 package always has python_version == "3.10".
    • platform_version will generally not be present, because it gives detailed information about the OS where Python is running, for example:
      #60-Ubuntu SMP Thu May 6 07:46:32 UTC 2021

      platform_release has similar issues.

    • platform_machine will usually be present, except for macOS universal2 pybis: these can potentially be run in either x86-64 or arm64 mode, and we don’t know which until the interpreter is actually invoked, so we can’t record it in static metadata.

    Rationale: In many cases, this should allow a resolver running on Linux to compute package pins for a Python environment on Windows, or vice-versa, so long as the resolver has access to the target platform’s .pybi file. (Note that Requires-Python constraints can be checked by using the python_full_version value.) While we have to leave out a few keys sometimes, they’re either fairly useless (platform_version, platform_release) or can be reconstructed by the resolver (platform_machine).

    The markers are also just generally useful information to have accessible. For example, if you have a pypy3-7.3.2 pybi, and you want to know what version of the Python language that supports, then that’s recorded in the python_version marker.

    (Note: we may want to deprecate/remove platform_version and platform_release? They’re problematic and I can’t figure out any cases where they’re useful. But that’s out of scope of this particular PEP.)

  • Pybi-Paths: The install paths needed to install wheels (same keys as sysconfig.get_paths()), as relative paths starting at the root of the zip file, as a JSON dict.

    These paths MUST be written in Unix format, using forward slashes as a separator, not backslashes.

    It must be possible to invoke the Python interpreter by running {paths["scripts"]}/python. If there are alternative interpreter entry points (e.g. pythonw for Windows GUI apps), then they should also be in that directory under their conventional names, with no version number attached. (You can also have a python3.11 symlink if you want; there’s no rule against that. It’s just that python has to exist and work.)

    Rationale: Pybi-Paths and Pybi-Wheel-Tags (see below) are together enough to let an installer choose wheels and install them into an unpacked pybi environment, without invoking Python. Besides, we need to write down the interpreter location somewhere, so it’s two birds with one stone.

  • Pybi-Wheel-Tag: The wheel tags supported by this interpreter, in preference order (most-preferred first, least-preferred last), except that the special platform tag PLATFORM should replace any platform tags that depend on the final installation system.

    Discussion: It would be nice™ if installers could compute a pybi’s corresponding wheel tags ahead of time, so that they could install wheels into the unpacked pybi without needing to actually invoke the python interpreter to query its tags – both for efficiency and to allow for more exotic use cases like setting up a Windows environment from a Linux host.

    But unfortunately, it’s impossible to compute the full set of platform tags supported by a Python installation ahead of time, because they can depend on the final system:

    • A pybi tagged manylinux_2_12_x86_64 can always use wheels tagged as manylinux_2_12_x86_64. It also might be able to use wheels tagged manylinux_2_17_x86_64, but only if the final installation system has glibc 2.17+.
    • A pybi tagged macosx_11_0_universal2 (= x86-64 + arm64 support in the same binary) might be able to use wheels tagged as macosx_11_0_arm64, but only if it’s installed on an “Apple Silicon” machine and running in arm64 mode.

    In these two cases, an installation tool can still work out the appropriate set of wheel tags by computing the local platform tags, taking the wheel tag templates from Pybi-Wheel-Tag, and swapping in the actual supported platforms in place of the magic PLATFORM string.

    However, there are other cases that are even more complicated:

    • You can (usually) run both 32- and 64-bit apps on 64-bit Windows. So a pybi
      installer might compute the set of allowable pybi tags on the current platform as [win32, win_amd64]. But you can’t then just take that set and swap it into the pybi’s wheel tag template or you get nonsense:

      To handle this, the installer needs to somehow understand that a manylinux_2_12_x86_64 pybi can use a manylinux_2_17_x86_64 wheel as long as those are both valid tags on the current machine, but a win32 pybi can’t use a win_amd64 wheel, even if those are both valid tags on the current machine.

    • A pybi tagged macosx_11_0_universal2 might be able to use wheels tagged as macosx_11_0_x86_64, but only if it’s installed on an x86-64 machine or it’s installed on an ARM machine and the interpreter is invoked with the magic incantation that tells macOS to run a binary in x86-64 mode. So how the installer plans to invoke the pybi matters too!

    So actually using Pybi-Wheel-Tag values is less trivial than it might seem, and they’re probably only useful with fairly sophisticated tooling. But, smart pybi installers will already have to understand a lot of these platform compatibility issues in order to select a working pybi, and for the cross-platform pinning/environment building case, users can potentially provide whatever information is needed to disambiguate exactly what platform they’re targeting. So, it’s still useful enough to include in the PyBI metadata – tools that don’t find it useful can simply ignore it.

You can probably generate these metadata values by running this script on the built interpreter:

import packaging.markers
import packaging.tags
import sysconfig
import os.path
import json
import sys

marker_vars = packaging.markers.default_environment()
# Delete any keys that depend on the final installation
del marker_vars["platform_release"]
del marker_vars["platform_version"]
# Darwin binaries are often multi-arch, so play it safe and
# delete the architecture marker. (Better would be to only
# do this if the pybi actually is multi-arch.)
if marker_vars["sys_platform"] == "darwin":
    del marker_vars["platform_machine"]

# Copied and tweaked version of packaging.tags.sys_tags
tags = []
interp_name = packaging.tags.interpreter_name()
if interp_name == "cp":
    tags += list(packaging.tags.cpython_tags(platforms=["xyzzy"]))
    tags += list(packaging.tags.generic_tags(platforms=["xyzzy"]))

tags += list(packaging.tags.compatible_tags(platforms=["xyzzy"]))

# Gross hack: packaging.tags normalizes platforms by lowercasing them,
# so we generate the tags with a unique string and then replace it
# with our special uppercase placeholder.
str_tags = [str(t).replace("xyzzy", "PLATFORM") for t in tags]

(base_path,) = sysconfig.get_config_vars("installed_base")
# For some reason, macOS framework builds report their
# installed_base as a directory deep inside the framework.
while "Python.framework" in base_path:
    base_path = os.path.dirname(base_path)
paths = {key: os.path.relpath(path, base_path).replace("\\", "/") for (key, path) in sysconfig.get_paths().items()}

json.dump({"marker_vars": marker_vars, "tags": str_tags, "paths": paths}, sys.stdout)

This emits a JSON dict on stdout with separate entries for each set of pybi-specific tags.

Non-normative comments

Why not just use conda?

This isn’t really in the scope of this PEP, but since conda is a popular way to distribute binary Python interpreters, it’s a natural question.

The simple answer is: conda is great! But, there are lots of python users who aren’t conda users, and they deserve nice things too. This PEP just gives them another option.

The deeper answer is: the maintainers who upload packages to PyPI are the backbone of the Python ecosystem. They’re the first audience for Python packaging tools. And one thing they want is to upload a package once, and have it be accessible across all the different ways Python is deployed: in Debian and Fedora and Homebrew and FreeBSD, in Conda environments, in big companies’ monorepos, in Nix, in Blender plugins, in RenPy games, ….. you get the idea.

All of these environments have their own tooling and strategies for managing packages and dependencies. So what’s special about PyPI and wheels is that they’re designed to describe dependencies in a standard, abstract way, that all these downstream systems can consume and convert into their local conventions. That’s why package maintainers use Python-specific metadata and upload to PyPI: because it lets them address all of those systems simultaneously. Every time you build a Python package for conda, there’s an intermediate wheel that’s generated, because wheels are the common language that Python package build systems and conda can use to talk to each other.

But then, if you’re a maintainer releasing an sdist+wheels, then you naturally want to test what you’re releasing, which may depend on arbitrary PyPI packages and versions. So you need tools that build Python environments directly from PyPI, and conda is fundamentally not designed to do that. So conda and pip are both necessary for different cases, and this proposal happens to be targeting the pip side of that equation.

Sdists (or not)

It might be cool to have an “sdist” equivalent for pybis, i.e., some kind of format for a Python source release that’s structured-enough to let tools automatically fetch and build it into a pybi, for platforms where prebuilt pybis aren’t available. But, this isn’t necessary for the MVP and opens a can of worms, so let’s worry about it later.

What packages should be bundled inside a pybi?

Pybi builders have the power to pick and choose what exactly goes inside. For example, you could include some preinstalled packages in the pybi’s site-packages directory, or prune out bits of the stdlib that you don’t want. We can’t stop you! Though if you do preinstall packages, then it’s strongly recommended to also include the correct metadata (.dist-info etc.), so that it’s possible for Pip or other tools to understand out what’s going on.

For my prototype “general purpose” pybi’s, what I chose is:

  • Make sure site-packages is empty.

    Rationale: for traditional standalone python installers that are targeted at end-users, you probably want to include at least pip, to avoid bootstrapping issues (PEP 453). But pybis are different: they’re designed to be installed by “smart” tooling, that consume the pybi as part of some kind of larger automated deployment process. It’s easier for these installers to start from a blank slate and then add whatever they need, than for them to start with some preinstalled packages that they may or may not want. (And besides, you can still run python -m ensurepip.)

  • Include the full stdlib, except for test.

    Rationale: the top-level test module contains CPython’s own test suite. It’s huge (CPython without test is ~37 MB, then test adds another ~25 MB on top of that!), and essentially never used by regular user code. Also, as precedent, the official nuget packages, the official manylinux images, and multiple Linux distributions all leave it out, and this hasn’t caused any major problems.

    So this seems like the best way to balance broad compatibility with reasonable download/install sizes.

  • I’m not shipping any .pyc files. They take up space in the download, can be generated on the final system at minimal cost, and dropping them removes a source of location-dependence. (.pyc files store the absolute path of the corresponding .py file and include it in tracebacks; but, pybis are relocatable, so the correct path isn’t known until after install.)

Backwards Compatibility

No backwards compatibility considerations.

Security Implications

No security implications, beyond the fact that anyone who takes it upon themselves to distribute binaries has to come up with a plan to manage their security (e.g., whether they roll a new build after an OpenSSL CVE drops). But collectively, we core Python folks are already maintaining binary builds for all major platforms (macOS + Windows through, and Linux builds through the official manylinux image), so even if we do start releasing official CPython builds on PyPI it doesn’t really raise any new security issues.

How to Teach This

This isn’t targeted at end-users; their experience will simply be that e.g. their pyenv or tox invocation magically gets faster and more reliable (if those projects’ maintainers decide to take advantage of this PEP).


Last modified: 2023-09-09 17:39:29 GMT