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PEP 517 -- A build-system independent format for source trees

PEP: 517
Title: A build-system independent format for source trees
Author: Nathaniel J. Smith <njs at pobox.com>, Thomas Kluyver <thomas at kluyver.me.uk>
BDFL-Delegate: Nick Coghlan < ncoghlan@gmail.com >
Discussions-To: < distutils-sig at python.org >
Status: Draft
Type: Standards Track
Created: 30-Sep-2015
Post-History: 1 Oct 2015, 25 Oct 2015

Abstract

While distutils / setuptools have taken us a long way, they suffer from three serious problems: (a) they're missing important features like usable build-time dependency declaration, autoconfiguration, and even basic ergonomic niceties like DRY -compliant version number management, and (b) extending them is difficult, so while there do exist various solutions to the above problems, they're often quirky, fragile, and expensive to maintain, and yet (c) it's very difficult to use anything else, because distutils/setuptools provide the standard interface for installing packages expected by both users and installation tools like pip .

Previous efforts (e.g. distutils2 or setuptools itself) have attempted to solve problems (a) and/or (b). This proposal aims to solve (c).

The goal of this PEP is get distutils-sig out of the business of being a gatekeeper for Python build systems. If you want to use distutils, great; if you want to use something else, then that should be easy to do using standardized methods. The difficulty of interfacing with distutils means that there aren't many such systems right now, but to give a sense of what we're thinking about see flit or bento . Fortunately, wheels have now solved many of the hard problems here -- e.g. it's no longer necessary that a build system also know about every possible installation configuration -- so pretty much all we really need from a build system is that it have some way to spit out standard-compliant wheels and sdists.

We therefore propose a new, relatively minimal interface for installation tools like pip to interact with package source trees and source distributions.

Terminology and goals

A source tree is something like a VCS checkout. We need a standard interface for installing from this format, to support usages like pip install some-directory/ .

A source distribution is a static snapshot representing a particular release of some source code, like lxml-3.4.4.zip . Source distributions serve many purposes: they form an archival record of releases, they provide a stupid-simple de facto standard for tools that want to ingest and process large corpora of code, possibly written in many languages (e.g. code search), they act as the input to downstream packaging systems like Debian/Fedora/Conda/..., and so forth. In the Python ecosystem they additionally have a particularly important role to play, because packaging tools like pip are able to use source distributions to fulfill binary dependencies, e.g. if there is a distribution foo.whl which declares a dependency on bar , then we need to support the case where pip install bar or pip install foo automatically locates the sdist for bar , downloads it, builds it, and installs the resulting package.

Source distributions are also known as sdists for short.

A build frontend is a tool that users might run that takes arbitrary source trees or source distributions and builds wheels from them. The actual building is done by each source tree's build backend . In a command like pip wheel some-directory/ , pip is acting as a build frontend.

An integration frontend is a tool that users might run that takes a set of package requirements (e.g. a requirements.txt file) and attempts to update a working environment to satisfy those requirements. This may require locating, building, and installing a combination of wheels and sdists. In a command like pip install lxml==2.4.0 , pip is acting as an integration frontend.

Source trees

There is an existing, legacy source tree format involving setup.py . We don't try to specify it further; its de facto specification is encoded in the source code and documentation of distutils , setuptools , pip , and other tools. We'll refer to it as the setup.py -style.

Here we define a new style of source tree based around the pyproject.toml file defined in PEP 518 , extending the [build-system] table in that file with one additional key, build-backend . Here's an example of how it would look:

[build-system]
# Defined by PEP 518:
requires = ["flit"]
# Defined by this PEP:
build-backend = "flit.api:main"

build-backend is a string naming a Python object that will be used to perform the build (see below for details). This is formatted following the same module:object syntax as a setuptools entry point. For instance, if the string is "flit.api:main" as in the example above, this object would be looked up by executing the equivalent of:

import flit.api
backend = flit.api.main

It's also legal to leave out the :object part, e.g.

build-backend = "flit.api"

which acts like:

import flit.api
backend = flit.api

Formally, the string should satisfy this grammar:

identifier = (letter | '_') (letter | '_' | digit)*
module_path = identifier ('.' identifier)*
object_path = identifier ('.' identifier)*
entry_point = module_path (':' object_path)?

And we import module_path and then lookup module_path.object_path (or just module_path if object_path is missing).

If the pyproject.toml file is absent, or the build-backend key is missing, the source tree is not using this specification, and tools should fall back to running setup.py .

Where the build-backend key exists, it takes precedence over setup.py , and source trees need not include setup.py at all. Projects may still wish to include a setup.py for compatibility with tools that do not use this spec.

Build backend interface

The build backend object is expected to have attributes which provide some or all of the following hooks. The common config_settings argument is described after the individual hooks:

def get_build_requires(config_settings):
    ...

This hook MUST return an additional list of strings containing PEP 508 dependency specifications, above and beyond those specified in the pyproject.toml file. Example:

def get_build_requires(config_settings):
    return ["wheel >= 0.25", "setuptools"]

Optional. If not defined, the default implementation is equivalent to return [] .

def get_wheel_metadata(metadata_directory, config_settings):
    ...

Must create a .dist-info directory containing wheel metadata inside the specified metadata_directory (i.e., creates a directory like {metadata_directory}/{package}-{version}.dist-info/ . This directory MUST be a valid .dist-info directory as defined in the wheel specification, except that it need not contain RECORD or signatures. The hook MAY also create other files inside this directory, and a build frontend MUST ignore such files; the intention here is that in cases where the metadata depends on build-time decisions, the build backend may need to record these decisions in some convenient format for re-use by the actual wheel-building step.

Return value is ignored.

Optional. If a build frontend needs this information and the method is not defined, it should call build_wheel and look at the resulting metadata directly.

def build_wheel(wheel_directory, config_settings, metadata_directory=None):
    ...

Must build a .whl file, and place it in the specified wheel_directory .

If the build frontend has previously called get_wheel_metadata and depends on the wheel resulting from this call to have metadata matching this earlier call, then it should provide the path to the previous metadata_directory as an argument. If this argument is provided, then build_wheel MUST produce a wheel with identical metadata. The directory passed in by the build frontend MUST be identical to the directory created by get_wheel_metadata , including any unrecognized files it created.

Mandatory.

Note

Editable installs

This PEP originally specified a fourth hook, install_editable , to do an editable install (as with pip install -e ). It was removed due to the complexity of the topic, but may be specified in a later PEP.

Briefly, the questions to be answered include: what reasonable ways existing of implementing an 'editable install'? Should the backend or the frontend pick how to make an editable install? And if the frontend does, what does it need from the backend to do so.

config_settings

This argument, which is passed to all hooks, is an arbitrary dictionary provided as an "escape hatch" for users to pass ad-hoc configuration into individual package builds. Build backends MAY assign any semantics they like to this dictionary. Build frontends SHOULD provide some mechanism for users to specify arbitrary string-key/string-value pairs to be placed in this dictionary. For example, they might support some syntax like --package-config CC=gcc . Build frontends MAY also provide arbitrary other mechanisms for users to place entries in this dictionary. For example, pip might choose to map a mix of modern and legacy command line arguments like:

pip install                                           \
  --package-config CC=gcc                             \
  --global-option="--some-global-option"              \
  --build-option="--build-option1"                    \
  --build-option="--build-option2"

into a config_settings dictionary like:

{
 "CC": "gcc",
 "--global-option": ["--some-global-option"],
 "--build-option": ["--build-option1", "--build-option2"],
}

Of course, it's up to users to make sure that they pass options which make sense for the particular build backend and package that they are building.

All hooks are run with working directory set to the root of the source tree, and MAY print arbitrary informational text on stdout and stderr. They MUST NOT read from stdin, and the build frontend MAY close stdin before invoking the hooks.

If a hook raises an exception, or causes the process to terminate, then this indicates an error.

Build environment

One of the responsibilities of a build frontend is to set up the Python environment in which the build backend will run.

We do not require that any particular "virtual environment" mechanism be used; a build frontend might use virtualenv, or venv, or no special mechanism at all. But whatever mechanism is used MUST meet the following criteria:

  • All requirements specified by the project's build-requirements must be available for import from Python. In particular:

    • The get_build_requires hook is executed in an environment which contains the bootstrap requirements specified in the pyproject.toml file.
    • All other hooks are executed in an environment which contains both the bootstrap requirements specified in the pyproject.toml hook and those specified by the get_build_requires hook.
  • This must remain true even for new Python subprocesses spawned by the build environment, e.g. code like:

    import sys, subprocess
    subprocess.check_call([sys.executable, ...])
    

    must spawn a Python process which has access to all the project's build-requirements. This is necessary e.g. for build backends that want to run legacy setup.py scripts in a subprocess.

  • All command-line scripts provided by the build-required packages must be present in the build environment's PATH. For example, if a project declares a build-requirement on flit , then the following must work as a mechanism for running the flit command-line tool:

    import subprocess
    subprocess.check_call(["flit", ...])
    

A build backend MUST be prepared to function in any environment which meets the above criteria. In particular, it MUST NOT assume that it has access to any packages except those that are present in the stdlib, or that are explicitly declared as build-requirements.

Recommendations for build frontends (non-normative)

A build frontend MAY use any mechanism for setting up a build environment that meets the above criteria. For example, simply installing all build-requirements into the global environment would be sufficient to build any compliant package -- but this would be sub-optimal for a number of reasons. This section contains non-normative advice to frontend implementors.

A build frontend SHOULD, by default, create an isolated environment for each build, containing only the standard library and any explicitly requested build-dependencies. This has two benefits:

  • It allows for a single installation run to build multiple packages that have contradictory build-requirements. E.g. if package1 build-requires pbr==1.8.1, and package2 build-requires pbr==1.7.2, then these cannot both be installed simultaneously into the global environment -- which is a problem when the user requests pip install package1 package2 . Or if the user already has pbr==1.8.1 installed in their global environment, and a package build-requires pbr==1.7.2, then downgrading the user's version would be rather rude.
  • It acts as a kind of public health measure to maximize the number of packages that actually do declare accurate build-dependencies. We can write all the strongly worded admonitions to package authors we want, but if build frontends don't enforce isolation by default, then we'll inevitably end up with lots of packages on PyPI that build fine on the original author's machine and nowhere else, which is a headache that no-one needs.

However, there will also be situations where build-requirements are problematic in various ways. For example, a package author might accidentally leave off some crucial requirement despite our best efforts; or, a package might declare a build-requirement on foo >= 1.0 which worked great when 1.0 was the latest version, but now 1.1 is out and it has a showstopper bug; or, the user might decide to build a package against numpy==1.7 -- overriding the package's preferred numpy==1.8 -- to guarantee that the resulting build will be compatible at the C ABI level with an older version of numpy (even if this means the resulting build is unsupported upstream). Therefore, build frontends SHOULD provide some mechanism for users to override the above defaults. For example, a build frontend could have a --build-with-system-site-packages option that causes the --system-site-packages option to be passed to virtualenv-or-equivalent when creating build environments, or a --build-requirements-override=my-requirements.txt option that overrides the project's normal build-requirements.

The general principle here is that we want to enforce hygiene on package authors , while still allowing end-users to open up the hood and apply duct tape when necessary.

Source distributions

For now, we continue with the legacy sdist format which is mostly undefined, but basically comes down to: a file named {NAME}-{VERSION}.{EXT} , which unpacks into a buildable source tree called {NAME}-{VERSION}/ . Traditionally these have always contained setup.py -style source trees; we now allow them to also contain pyproject.toml -style source trees.

Integration frontends require that an sdist named {NAME}-{VERSION}.{EXT} will generate a wheel named {NAME}-{VERSION}-{COMPAT-INFO}.whl .

Comparison to competing proposals

The primary difference between this and competing proposals (in particular, PEP 516 ) is that our build backend is defined via a Python hook-based interface rather than a command-line based interface.

We do not expect that this will, by itself, intrinsically reduce the complexity calling into the backend, because build frontends will in any case want to run hooks inside a child -- this is important to isolate the build frontend itself from the backend code and to better control the build backends execution environment. So under both proposals, there will need to be some code in pip to spawn a subprocess and talk to some kind of command-line/IPC interface, and there will need to be some code in the subprocess that knows how to parse these command line arguments and call the actual build backend implementation. So this diagram applies to all proposals equally:

+-----------+          +---------------+           +----------------+
| frontend  | -spawn-> | child cmdline | -Python-> |    backend     |
|   (pip)   |          |   interface   |           | implementation |
+-----------+          +---------------+           +----------------+

The key difference between the two approaches is how these interface boundaries map onto project structure:

.-= This PEP =-.

+-----------+          +---------------+    |      +----------------+
| frontend  | -spawn-> | child cmdline | -Python-> |    backend     |
|   (pip)   |          |   interface   |    |      | implementation |
+-----------+          +---------------+    |      +----------------+
                                            |
|______________________________________|    |
   Owned by pip, updated in lockstep        |
                                            |
                                            |
                                 PEP-defined interface boundary
                               Changes here require distutils-sig


.-= Alternative =-.

+-----------+    |     +---------------+           +----------------+
| frontend  | -spawn-> | child cmdline | -Python-> |    backend     |
|   (pip)   |    |     |   interface   |           | implementation |
+-----------+    |     +---------------+           +----------------+
                 |
                 |     |____________________________________________|
                 |      Owned by build backend, updated in lockstep
                 |
    PEP-defined interface boundary
  Changes here require distutils-sig

By moving the PEP-defined interface boundary into Python code, we gain three key advantages.

First , because there will likely be only a small number of build frontends ( pip , and... maybe a few others?), while there will likely be a long tail of custom build backends (since these are chosen separately by each package to match their particular build requirements), the actual diagrams probably look more like:

.-= This PEP =-.

+-----------+          +---------------+           +----------------+
| frontend  | -spawn-> | child cmdline | -Python+> |    backend     |
|   (pip)   |          |   interface   |        |  | implementation |
+-----------+          +---------------+        |  +----------------+
                                                |
                                                |  +----------------+
                                                +> |    backend     |
                                                |  | implementation |
                                                |  +----------------+
                                                :
                                                :

.-= Alternative =-.

+-----------+          +---------------+           +----------------+
| frontend  | -spawn+> | child cmdline | -Python-> |    backend     |
|   (pip)   |       |  |   interface   |           | implementation |
+-----------+       |  +---------------+           +----------------+
                    |
                    |  +---------------+           +----------------+
                    +> | child cmdline | -Python-> |    backend     |
                    |  |   interface   |           | implementation |
                    |  +---------------+           +----------------+
                    :
                    :

That is, this PEP leads to less total code in the overall ecosystem. And in particular, it reduces the barrier to entry of making a new build system. For example, this is a complete, working build backend:

# mypackage_custom_build_backend.py
import os.path

def get_build_requires(config_settings, config_directory):
    return ["wheel"]

def build_wheel(wheel_directory, config_settings, config_directory=None):
    from wheel.archive import archive_wheelfile
    path = os.path.join(wheel_directory,
                        "mypackage-0.1-py2.py3-none-any")
    archive_wheelfile(path, "src/")

Of course, this is a terrible build backend: it requires the user to have manually set up the wheel metadata in src/mypackage-0.1.dist-info/ ; when the version number changes it must be manually updated in multiple places; it doesn't implement the metadata or develop hooks, ... but it works, and these features can be added incrementally. Much experience suggests that large successful projects often originate as quick hacks (e.g., Linux -- "just a hobby, won't be big and professional"; IPython/Jupyter -- a grad student's ``$PYTHONSTARTUP` file < http://blog.fperez.org/2012/01/ipython-notebook-historical.html >`_), so if our goal is to encourage the growth of a vibrant ecosystem of good build tools, it's important to minimize the barrier to entry.

Second , because Python provides a simpler yet richer structure for describing interfaces, we remove unnecessary complexity from the specification -- and specifications are the worst place for complexity, because changing specifications requires painful consensus-building across many stakeholders. In the command-line interface approach, we have to come up with ad hoc ways to map multiple different kinds of inputs into a single linear command line (e.g. how do we avoid collisions between user-specified configuration arguments and PEP-defined arguments? how do we specify optional arguments? when working with a Python interface these questions have simple, obvious answers). When spawning and managing subprocesses, there are many fiddly details that must be gotten right, subtle cross-platform differences, and some of the most obvious approaches -- e.g., using stdout to return data for the build_requires operation -- can create unexpected pitfalls (e.g., what happens when computing the build requirements requires spawning some child processes, and these children occasionally print an error message to stdout? obviously a careful build backend author can avoid this problem, but the most obvious way of defining a Python interface removes this possibility entirely, because the hook return value is clearly demarcated).

In general, the need to isolate build backends into their own process means that we can't remove IPC complexity entirely -- but by placing both sides of the IPC channel under the control of a single project, we make it much cheaper to fix bugs in the IPC interface than if fixing bugs requires coordinated agreement and coordinated changes across the ecosystem.

Third , and most crucially, the Python hook approach gives us much more powerful options for evolving this specification in the future.

For concreteness, imagine that next year we add a new get_wheel_metadata2 hook, which replaces the current get_wheel_metadata hook with something that produces more data, or a different metadata format. In order to manage the transition, we want it to be possible for build frontends to transparently use get_wheel_metadata2 when available and fall back onto get_wheel_metadata otherwise; and we want it to be possible for build backends to define both methods, for compatibility with both old and new build frontends.

Furthermore, our mechanism should also fulfill two more goals: (a) If new versions of e.g. pip and flit are both updated to support the new interface, then this should be sufficient for it to be used; in particular, it should not be necessary for every project that uses flit to update its individual pyproject.toml file. (b) We do not want to have to spawn extra processes just to perform this negotiation, because process spawns can easily become a bottleneck when deploying large multi-package stacks on some platforms (Windows).

In the interface described here, all of these goals are easy to achieve. Because pip controls the code that runs inside the child process, it can easily write it to do something like:

command, backend, args = parse_command_line_args(...)
if command == "get_wheel_metadata":
   if hasattr(backend, "get_wheel_metadata2"):
       backend.get_wheel_metadata2(...)
   elif hasattr(backend, "get_wheel_metadata"):
       backend.get_wheel_metadata(...)
   else:
       # error handling

In the alternative where the public interface boundary is placed at the subprocess call, this is not possible -- either we need to spawn an extra process just to query what interfaces are supported (as was included in an earlier draft of PEP 516 , an alternative to this), or else we give up on autonegotiation entirely (as in the current version of that PEP), meaning that any changes in the interface will require N individual packages to update their pyproject.toml files before any change can go live, and that any changes will necessarily be restricted to new releases.

One specific consequence of this is that in this PEP, we're able to make the get_wheel_metadata command optional. In our design, this can easily be worked around by a tool like pip , which can put code in its subprocess runner like:

def get_wheel_metadata(output_dir, config_settings):
     if hasattr(backend, "get_wheel_metadata"):
         backend.get_wheel_metadata(output_dir, config_settings)
     else:
         backend.build_wheel(output_dir, config_settings)
         touch(output_dir / "PIP_ALREADY_BUILT_WHEELS")
         unzip_metadata(output_dir/*.whl)

def build_wheel(output_dir, config_settings, metadata_dir):
     if os.path.exists(metadata_dir / "PIP_ALREADY_BUILT_WHEELS"):
         copy(metadata_dir / *.whl, output_dir)
     else:
         backend.build_wheel(output_dir, config_settings, metadata_dir)

and thus expose a totally uniform interface to the rest of pip , with no extra subprocess calls, no duplicated builds, etc. But obviously this is the kind of code that you only want to write as part of a private, within-project interface.

(And, of course, making the metadata command optional is one piece of lowering the barrier to entry, as discussed above.)

Other differences

Besides the key command line versus Python hook difference described above, there are a few other differences in this proposal:

  • Metadata command is optional (as described above).
  • We return metadata as a directory, rather than a single METADATA file. This aligns better with the way that in practice wheel metadata is distributed across multiple files (e.g. entry points), and gives us more options in the future. (For example, instead of following the PEP 426 proposal of switching the format of METADATA to JSON, we might decide to keep the existing METADATA the way it is for backcompat, while adding new extensions as JSON "sidecar" files inside the same directory. Or maybe not; the point is it keeps our options more open.)
  • We provide a mechanism for passing information between the metadata step and the wheel building step. I guess everyone probably will agree this is a good idea?
  • We provide more detailed recommendations about the build environment, but these aren't normative anyway.

Evolutionary notes

A goal here is to make it as simple as possible to convert old-style sdists to new-style sdists. (E.g., this is one motivation for supporting dynamic build requirements.) The ideal would be that there would be a single static pyproject.toml that could be dropped into any "version 0" VCS checkout to convert it to the new shiny. This is probably not 100% possible, but we can get close, and it's important to keep track of how close we are... hence this section.

A rough plan would be: Create a build system package ( setuptools_pypackage or whatever) that knows how to speak whatever hook language we come up with, and convert them into calls to setup.py . This will probably require some sort of hooking or monkeypatching to setuptools to provide a way to extract the setup_requires= argument when needed, and to provide a new version of the sdist command that generates the new-style format. This all seems doable and sufficient for a large proportion of packages (though obviously we'll want to prototype such a system before we finalize anything here). (Alternatively, these changes could be made to setuptools itself rather than going into a separate package.)

But there remain two obstacles that mean we probably won't be able to automatically upgrade packages to the new format:

  1. There currently exist packages which insist on particular packages being available in their environment before setup.py is executed. This means that if we decide to execute build scripts in an isolated virtualenv-like environment, then projects will need to check whether they do this, and if so then when upgrading to the new system they will have to start explicitly declaring these dependencies (either via setup_requires= or via static declaration in pyproject.toml ).
  2. There currently exist packages which do not declare consistent metadata (e.g. egg_info and bdist_wheel might get different install_requires= ). When upgrading to the new system, projects will have to evaluate whether this applies to them, and if so they will need to stop doing that.
Source: https://github.com/python/peps/blob/master/pep-0517.txt