python-peps/peps/pep-0723.rst

PEP: 723
Title: Inline script metadata
Author: Ofek Lev <ofekmeister@gmail.com>
Sponsor: Adam Turner <python@quite.org.uk>
PEP-Delegate: Brett Cannon <brett@python.org>
Discussions-To: https://discuss.python.org/t/31151
Status: Final
Type: Standards Track
Topic: Packaging
Created: 04-Aug-2023
Post-History: `04-Aug-2023 <https://discuss.python.org/t/30979>`__,
              `06-Aug-2023 <https://discuss.python.org/t/31151>`__,
              `23-Aug-2023 <https://discuss.python.org/t/32149>`__,
              `06-Dec-2023 <https://discuss.python.org/t/40418>`__,
Replaces: 722
Resolution: https://discuss.python.org/t/40418/82

.. canonical-pypa-spec:: :ref:`packaging:inline-script-metadata`

Abstract
========

This PEP specifies a metadata format that can be embedded in single-file Python
scripts to assist launchers, IDEs and other external tools which may need to
interact with such scripts.


Motivation
==========

Python is routinely used as a scripting language, with Python scripts as a
(better) alternative to shell scripts, batch files, etc. When Python code is
structured as a script, it is usually stored as a single file and does not
expect the availability of any other local code that may be used for imports.
As such, it is possible to share with others over arbitrary text-based means
such as email, a URL to the script, or even a chat window. Code that is
structured like this may live as a single file forever, never becoming a
full-fledged project with its own directory and ``pyproject.toml`` file.

An issue that users encounter with this approach is that there is no standard
mechanism to define metadata for tools whose job it is to execute such scripts.
For example, a tool that runs a script may need to know which dependencies are
required or the supported version(s) of Python.

There is currently no standard tool that addresses this issue, and this PEP
does *not* attempt to define one. However, any tool that *does* address this
issue will need to know what the runtime requirements of scripts are. By
defining a standard format for storing such metadata, existing tools, as well
as any future tools, will be able to obtain that information without requiring
users to include tool-specific metadata in their scripts.


Rationale
=========

This PEP defines a mechanism for embedding metadata *within the script itself*,
and not in an external file.

The metadata format is designed to be similar to the layout of data in the
``pyproject.toml`` file of a Python project directory, to provide a familiar
experience for users who have experience writing Python projects. By using a
similar format, we avoid unnecessary inconsistency between packaging tools,
a common frustration expressed by users in the recent
`packaging survey <https://discuss.python.org/t/22420>`__.

The following are some of the use cases that this PEP wishes to support:

* A user facing CLI that is capable of executing scripts. If we take Hatch as
  an example, the interface would be simply
  ``hatch run /path/to/script.py [args]`` and Hatch will manage the
  environment for that script. Such tools could be used as shebang lines on
  non-Windows systems e.g. ``#!/usr/bin/env hatch run``.
* A script that desires to transition to a directory-type project. A user may
  be rapidly prototyping locally or in a remote REPL environment and then
  decide to transition to a more formal project layout if their idea works
  out. Being able to define dependencies in the script would be very useful to
  have fully reproducible bug reports.
* Users that wish to avoid manual dependency management. For example, package
  managers that have commands to add/remove dependencies or dependency update
  automation in CI that triggers based on new versions or in response to
  CVEs [1]_.


Specification
=============

This PEP defines a metadata comment block format loosely inspired [2]_ by
`reStructuredText Directives`__.

__ https://docutils.sourceforge.io/docs/ref/rst/directives.html

Any Python script may have top-level comment blocks that MUST start with the
line ``# /// TYPE`` where ``TYPE`` determines how to process the content. That
is: a single ``#``, followed by a single space, followed by three forward
slashes, followed by a single space, followed by the type of metadata. Block
MUST end with the line ``# ///``. That is: a single ``#``, followed by a single
space, followed by three forward slashes. The ``TYPE`` MUST only consist of
ASCII letters, numbers and hyphens.

Every line between these two lines (``# /// TYPE`` and ``# ///``) MUST be a
comment starting with ``#``. If there are characters after the ``#`` then the
first character MUST be a space. The embedded content is formed by taking away
the first two characters of each line if the second character is a space,
otherwise just the first character (which means the line consists of only a
single ``#``).

Precedence for an ending line ``# ///`` is given when the next line is not
a valid embedded content line as described above. For example, the following
is a single fully valid block:

.. code:: python

    # /// some-toml
    # embedded-csharp = """
    # /// <summary>
    # /// text
    # ///
    # /// </summary>
    # public class MyClass { }
    # """
    # ///

A starting line MUST NOT be placed between another starting line and its ending
line. In such cases tools MAY produce an error. Unclosed blocks MUST be ignored.

When there are multiple comment blocks of the same ``TYPE`` defined, tools MUST
produce an error.

Tools reading embedded metadata MAY respect the standard Python encoding
declaration. If they choose not to do so, they MUST process the file as UTF-8.

This is the canonical regular expression that MAY be used to parse the
metadata:

.. code:: text

    (?m)^# /// (?P<type>[a-zA-Z0-9-]+)$\s(?P<content>(^#(| .*)$\s)+)^# ///$

In circumstances where there is a discrepancy between the text specification
and the regular expression, the text specification takes precedence.

Tools MUST NOT read from metadata blocks with types that have not been
standardized by this PEP or future ones.

script type
-----------

The first type of metadata block is named ``script`` which contains script
metadata (dependency data and tool configuration).

This document MAY include top-level fields ``dependencies`` and ``requires-python``,
and MAY optionally include a ``[tool]`` table.

The ``[tool]`` table MAY be used by any tool, script runner or otherwise, to configure
behavior. It has the same semantics as the :pep:`tool table <518#tool-table>` in
``pyproject.toml``.

The top-level fields are:

* ``dependencies``: A list of strings that specifies the runtime dependencies
  of the script. Each entry MUST be a valid :pep:`508` dependency.
* ``requires-python``: A string that specifies the Python version(s) with which
  the script is compatible. The value of this field MUST be a valid
  :pep:`version specifier <440#version-specifiers>`.

Script runners MUST error if the specified ``dependencies`` cannot be provided.
Script runners SHOULD error if no version of Python that satisfies the specified
``requires-python`` can be provided.

Example
-------

The following is an example of a script with embedded metadata:

.. code:: python

    # /// script
    # requires-python = ">=3.11"
    # dependencies = [
    #   "requests<3",
    #   "rich",
    # ]
    # ///

    import requests
    from rich.pretty import pprint

    resp = requests.get("https://peps.python.org/api/peps.json")
    data = resp.json()
    pprint([(k, v["title"]) for k, v in data.items()][:10])

Reference Implementation
========================

The following is an example of how to read the metadata on Python 3.11 or
higher.

.. code:: python

   import re
   import tomllib

   REGEX = r'(?m)^# /// (?P<type>[a-zA-Z0-9-]+)$\s(?P<content>(^#(| .*)$\s)+)^# ///$'

   def read(script: str) -> dict | None:
       name = 'script'
       matches = list(
           filter(lambda m: m.group('type') == name, re.finditer(REGEX, script))
       )
       if len(matches) > 1:
           raise ValueError(f'Multiple {name} blocks found')
       elif len(matches) == 1:
           content = ''.join(
               line[2:] if line.startswith('# ') else line[1:]
               for line in matches[0].group('content').splitlines(keepends=True)
           )
           return tomllib.loads(content)
       else:
           return None

Often tools will edit dependencies like package managers or dependency update
automation in CI. The following is a crude example of modifying the content
using the ``tomlkit`` library__.

__ https://tomlkit.readthedocs.io/en/latest/

.. code:: python

   import re

   import tomlkit

   REGEX = r'(?m)^# /// (?P<type>[a-zA-Z0-9-]+)$\s(?P<content>(^#(| .*)$\s)+)^# ///$'

   def add(script: str, dependency: str) -> str:
       match = re.search(REGEX, script)
       content = ''.join(
           line[2:] if line.startswith('# ') else line[1:]
           for line in match.group('content').splitlines(keepends=True)
       )

       config = tomlkit.parse(content)
       config['dependencies'].append(dependency)
       new_content = ''.join(
           f'# {line}' if line.strip() else f'#{line}'
           for line in tomlkit.dumps(config).splitlines(keepends=True)
       )

       start, end = match.span('content')
       return script[:start] + new_content + script[end:]

Note that this example used a library that preserves TOML formatting. This is
not a requirement for editing by any means but rather is a "nice to have"
feature.

The following is an example of how to read a stream of arbitrary metadata
blocks.

.. code:: python

   import re
   from typing import Iterator

   REGEX = r'(?m)^# /// (?P<type>[a-zA-Z0-9-]+)$\s(?P<content>(^#(| .*)$\s)+)^# ///$'

   def stream(script: str) -> Iterator[tuple[str, str]]:
       for match in re.finditer(REGEX, script):
           yield match.group('type'), ''.join(
               line[2:] if line.startswith('# ') else line[1:]
               for line in match.group('content').splitlines(keepends=True)
           )


Backwards Compatibility
=======================

At the time of writing, the ``# /// script`` block comment starter does not
appear in any Python files `on GitHub`__. Therefore, there is little risk of existing
scripts being broken by this PEP.

__ https://github.com/search?q=%22%23+%2F%2F%2F+script%22&type=code


Security Implications
=====================

If a script containing embedded metadata is run using a tool that automatically
installs dependencies, this could cause arbitrary code to be downloaded and
installed in the user's environment.

The risk here is part of the functionality of the tool being used to run the
script, and as such should already be addressed by the tool itself. The only
additional risk introduced by this PEP is if an untrusted script with embedded
metadata is run, when a potentially malicious dependency or transitive
dependency might be installed.

This risk is addressed by the normal good practice of reviewing code
before running it. Additionally, tools may be able to provide
`locking functionality <723-tool-configuration_>`__ to ameliorate this risk.


How to Teach This
=================

To embed metadata in a script, define a comment block that starts with the
line ``# /// script`` and ends with the line ``# ///``. Every line between
those two lines must be a comment and the full content is derived by removing
the first two characters.

.. code:: python

    # /// script
    # dependencies = [
    #   "requests<3",
    #   "rich",
    # ]
    # requires-python = ">=3.11"
    # ///

The allowed fields are described in the following table:

.. list-table::

   * - Field
     - Description
     - Tool behavior

   * - ``dependencies``
     - A list of strings that specifies the runtime dependencies of the script.
       Each entry must be a valid :pep:`508` dependency.
     - Tools will error if the specified dependencies cannot be provided.

   * - ``requires-python``
     - A string that specifies the Python version(s)
       with which the script is compatible.
       The value of this field must be a valid
       :pep:`version specifier <440#version-specifiers>`.
     - Tools might error if no version of Python that satisfies
       the constraint can be executed.

In addition, a ``[tool]`` table is allowed. Details of what is permitted are similar
to what is permitted in ``pyproject.toml``, but precise information must be included
in the documentation of the relevant tool.

It is up to individual tools whether or not their behavior is altered based on
the embedded metadata. For example, every script runner may not be able to
provide an environment for specific Python versions as defined by the
``requires-python`` field.

The :pep:`tool table <518#tool-table>` may be used by any tool, script runner
or otherwise, to configure behavior.


Recommendations
===============

Tools that support managing different versions of Python should attempt to use
the highest available version of Python that is compatible with the script's
``requires-python`` metadata, if defined.


Tooling buy-in
==============

The following is a list of tools that have expressed support for this PEP or
have committed to implementing support should it be accepted:

* `Pantsbuild and Pex <https://discuss.python.org/t/31151/15>`__:  expressed
  support for any way to define dependencies and also features that this PEP
  considers as valid use cases such as building packages from scripts and
  embedding tool configuration
* `Mypy <https://discuss.python.org/t/31151/16>`__ and
  `Ruff <https://discuss.python.org/t/31151/42>`__: strongly expressed support
  for embedding tool configuration as it would solve existing pain points for
  users
* `Hatch <https://discuss.python.org/t/31151/53>`__: (author of this PEP)
  expressed support for all aspects of this PEP, and will be one of the first
  tools to support running scripts with specifically configured Python versions


Rejected Ideas
==============

.. _723-comment-block:

Why not use a comment block resembling requirements.txt?
--------------------------------------------------------

This PEP considers there to be different types of users for whom Python code
would live as single-file scripts:

* Non-programmers who are just using Python as a scripting language to achieve
  a specific task. These users are unlikely to be familiar with concepts of
  operating systems like shebang lines or the ``PATH`` environment variable.
  Some examples:

  * The average person, perhaps at a workplace, who wants to write a script to
    automate something for efficiency or to reduce tedium
  * Someone doing data science or machine learning in industry or academia who
    wants to write a script to analyze some data or for research purposes.
    These users are special in that, although they have limited programming
    knowledge, they learn from sources like StackOverflow and blogs that have a
    programming bent and are increasingly likely to be part of communities that
    share knowledge and code. Therefore, a non-trivial number of these users
    will have some familiarity with things like Git(Hub), Jupyter, HuggingFace,
    etc.
* Non-programmers who manage operating systems e.g. a sysadmin. These users are
  able to set up ``PATH``, for example, but are unlikely to be familiar with
  Python concepts like virtual environments. These users often operate in
  isolation and have limited need to gain exposure to tools intended for
  sharing like Git.
* Programmers who manage operating systems/infrastructure e.g. SREs. These
  users are not very likely to be familiar with Python concepts like virtual
  environments, but are likely to be familiar with Git and most often use it
  to version control everything required to manage infrastructure like Python
  scripts and Kubernetes config.
* Programmers who write scripts primarily for themselves. These users over time
  accumulate a great number of scripts in various languages that they use to
  automate their workflow and often store them in a single directory, that is
  potentially version controlled for persistence. Non-Windows users may set
  up each Python script with a shebang line pointing to the desired Python
  executable or script runner.

This PEP argues that the proposed TOML-based metadata format is the best for
each category of user and that the requirements-like block comment is only
approachable for those who have familiarity with ``requirements.txt``, which
represents a small subset of users.

* For the average person automating a task or the data scientist, they are
  already starting with zero context and are unlikely to be familiar with
  TOML nor ``requirements.txt``. These users will very likely rely on
  snippets found online via a search engine or utilize AI in the form
  of a chat bot or direct code completion software. The similarity with
  dependency information stored in ``pyproject.toml`` will provide useful
  search results relatively quickly, and while the ``pyproject.toml`` format
  and the script metadata format are not the same, any resulting discrepancies
  are unlikely to be difficult for the intended users to resolve.

  Additionally, these users are most susceptible to formatting quirks and
  syntax errors. TOML is a well-defined format with existing online
  validators that features assignment that is compatible with Python
  expressions and has no strict indenting rules. The block comment format
  on the other hand could be easily malformed by forgetting the colon, for
  example, and debugging why it's not working with a search engine would be
  a difficult task for such a user.
* For the sysadmin types, they are equally unlikely as the previously described
  users to be familiar with TOML or ``requirements.txt``. For either format
  they would have to read documentation. They would likely be more comfortable
  with TOML since they are used to structured data formats and there would be
  less perceived magic in their systems.

  Additionally, for maintenance of their systems ``/// script`` would be
  much easier to search for from a shell than a block comment with potentially
  numerous extensions over time.
* For the SRE types, they are likely to be familiar with TOML already from
  other projects that they might have to work with like configuring the
  `GitLab Runner`__ or `Cloud Native Buildpacks`__.

  __ https://docs.gitlab.com/runner/configuration/advanced-configuration.html
  __ https://buildpacks.io/docs/reference/config/

  These users are responsible for the security of their systems and most likely
  have security scanners set up to automatically open PRs to update versions
  of dependencies. Such automated tools like Dependabot would have a much
  easier time using existing TOML libraries than writing their own custom
  parser for a block comment format.
* For the programmer types, they are more likely to be familiar with TOML
  than they have ever seen a ``requirements.txt`` file, unless they are a
  Python programmer who has had previous experience with writing applications.
  In the case of experience with the requirements format, it necessarily means
  that they are at least somewhat familiar with the ecosystem and therefore
  it is safe to assume they know what TOML is.

  Another benefit of this PEP to these users is that their IDEs like Visual
  Studio Code would be able to provide TOML syntax highlighting much more
  easily than each writing custom logic for this feature.

Additionally, since the original block comment alternative format (double
``#``) went against the recommendation of :pep:`8` and as a result linters
and IDE auto-formatters that respected the recommendation would
`fail by default <https://discuss.python.org/t/29905/247>`__, the final
proposal uses standard comments starting with a single ``#`` character without
any obvious start nor end sequence.

The concept of regular comments that do not appear to be intended for machines
(i.e. `encoding declarations`__) affecting behavior would not be customary to
users of Python and goes directly against the "explicit is better than
implicit" foundational principle.

__ https://docs.python.org/3/reference/lexical_analysis.html#encoding-declarations

Users typing what to them looks like prose could alter runtime behavior. This
PEP takes the view that the possibility of that happening, even when a tool
has been set up as such (maybe by a sysadmin), is unfriendly to users.

Finally, and critically, the alternatives to this PEP like :pep:`722` do not
satisfy the use cases enumerated herein, such as setting the supported Python
versions, the eventual building of scripts into packages, and the ability to
have machines edit metadata on behalf of users. It is very likely that the
requests for such features persist and conceivable that another PEP in the
future would allow for the embedding of such metadata. At that point there
would be multiple ways to achieve the same thing which goes against our
foundational principle of "there should be one - and preferably only one -
obvious way to do it".

Why not use a multi-line string?
--------------------------------

A previous version of this PEP proposed that the metadata be stored as follows:

.. code:: python

    __pyproject__ = """
    ...
    """

The most significant problem with this proposal is that the embedded TOML would
be limited in the following ways:

* It would not be possible to use multi-line double-quoted strings in the TOML
  as that would conflict with the Python string containing the document. Many
  TOML writers do not preserve style and may potentially produce output that
  would be malformed.
* The way in which character escaping works in Python strings is not quite the
  way it works in TOML strings. It would be possible to preserve a one-to-one
  character mapping by enforcing raw strings, but this ``r`` prefix requirement
  may be potentially confusing to users.

Why not reuse core metadata fields?
-----------------------------------

A previous version of this PEP proposed to reuse the existing
`metadata standard <pyproject metadata_>`_ that is used to describe projects.

There are two significant problems with this proposal:

* The ``name`` and ``version`` fields are required and changing that would
  require its own PEP
* Reusing the data is `fundamentally a misuse of it`__

  __ https://snarky.ca/differentiating-between-writing-down-dependencies-to-use-packages-and-for-packages-themselves/

Why not limit to specific metadata fields?
------------------------------------------

By limiting the metadata to just ``dependencies``, we would prevent the known
use case of tools that support managing Python installations, which would
allows users to target specific versions of Python for new syntax or standard
library functionality.

.. _723-tool-configuration:

Why not limit tool configuration?
---------------------------------

By not allowing the ``[tool]`` table, we would prevent known functionality
that would benefit users. For example:

* A script runner may support injecting of dependency resolution data for an
  embedded lock file (this is what Go's ``gorun`` can do).
* A script runner may support configuration instructing to run scripts in
  containers for situations in which there is no cross-platform support for a
  dependency or if the setup is too complex for the average user like when
  requiring Nvidia drivers. Situations like this would allow users to proceed
  with what they want to do whereas otherwise they may stop at that point
  altogether.
* Tools may wish to experiment with features to ease development burden for
  users such as the building of single-file scripts into packages. We received
  `feedback <https://discuss.python.org/t/31151/9>`__ stating that there are
  already tools that exist in the wild that build wheels and source
  distributions from single files.

  The author of the Rust RFC for embedding metadata
  `mentioned to us <https://discuss.python.org/t/29905/179>`__ that they are
  actively looking into that as well based on user feedback saying that there
  is unnecessary friction with managing small projects.

  There has been `a commitment <https://discuss.python.org/t/31151/15>`__ to
  support this by at least one major build system.

Why not limit tool behavior?
----------------------------

A previous version of this PEP proposed that non-script running tools SHOULD
NOT modify their behavior when the script is not the sole input to the tool.
For example, if a linter is invoked with the path to a directory, it SHOULD
behave the same as if zero files had embedded metadata.

This was done as a precaution to avoid tool behavior confusion and generating
various feature requests for tools to support this PEP. However, during
discussion we received `feedback <https://discuss.python.org/t/31151/16>`__
from maintainers of tools that this would be undesirable and potentially
confusing to users. Additionally, this may allow for a universally easier
way to configure tools in certain circumstances and solve existing issues.

Why not just set up a Python project with a ``pyproject.toml``?
---------------------------------------------------------------

Again, a key issue here is that the target audience for this proposal is people
writing scripts which aren't intended for distribution. Sometimes scripts will
be "shared", but this is far more informal than "distribution" - it typically
involves sending a script via an email with some written instructions on how to
run it, or passing someone a link to a GitHub gist.

Expecting such users to learn the complexities of Python packaging is a
significant step up in complexity, and would almost certainly give the
impression that "Python is too hard for scripts".

In addition, if the expectation here is that the ``pyproject.toml`` will
somehow be designed for running scripts in place, that's a new feature of the
standard that doesn't currently exist. At a minimum, this isn't a reasonable
suggestion until the `current discussion on Discourse
<pyproject without wheels_>`_ about using ``pyproject.toml`` for projects that
won't be distributed as wheels is resolved. And even then, it doesn't address
the "sending someone a script in a gist or email" use case.

Why not infer the requirements from import statements?
------------------------------------------------------

The idea would be to automatically recognize ``import`` statements in the source
file and turn them into a list of requirements.

However, this is infeasible for several reasons. First, the points above about
the necessity to keep the syntax easily parsable, for all Python versions, also
by tools written in other languages, apply equally here.

Second, PyPI and other package repositories conforming to the Simple Repository
API do not provide a mechanism to resolve package names from the module names
that are imported (see also `this related discussion`__).

__ https://discuss.python.org/t/record-the-top-level-names-of-a-wheel-in-metadata/29494

Third, even if repositories did offer this information, the same import name may
correspond to several packages on PyPI. One might object that disambiguating
which package is wanted would only be needed if there are several projects
providing the same import name. However, this would make it easy for anyone to
unintentionally or malevolently break working scripts, by uploading a package to
PyPI providing an import name that is the same as an existing project. The
alternative where, among the candidates, the first package to have been
registered on the index is chosen, would be confusing in case a popular package
is developed with the same import name as an existing obscure package, and even
harmful if the existing package is malware intentionally uploaded with a
sufficiently generic import name that has a high probability of being reused.

A related idea would be to attach the requirements as comments to the import
statements instead of gathering them in a block, with a syntax such as::

  import numpy as np # requires: numpy
  import rich # requires: rich

This still suffers from parsing difficulties. Also, where to place the comment
in the case of multiline imports is ambiguous and may look ugly::

   from PyQt5.QtWidgets import (
       QCheckBox, QComboBox, QDialog, QDialogButtonBox,
       QGridLayout, QLabel, QSpinBox, QTextEdit
   ) # requires: PyQt5

Furthermore, this syntax cannot behave as might be intuitively expected
in all situations. Consider::

  import platform
  if platform.system() == "Windows":
      import pywin32 # requires: pywin32

Here, the user's intent is that the package is only required on Windows, but
this cannot be understood by the script runner (the correct way to write
it would be ``requires: pywin32 ; sys_platform == 'win32'``).

(Thanks to Jean Abou-Samra for the clear discussion of this point)

Why not use a requirements file for dependencies?
-------------------------------------------------

Putting your requirements in a requirements file, doesn't require a PEP. You
can do that right now, and in fact it's quite likely that many adhoc solutions
do this. However, without a standard, there's no way of knowing how to locate a
script's dependency data. And furthermore, the requirements file format is
pip-specific, so tools relying on it are depending on a pip implementation
detail.

So in order to make a standard, two things would be required:

1. A standardised replacement for the requirements file format.
2. A standard for how to locate the requirements file for a given script.

The first item is a significant undertaking. It has been discussed on a number
of occasions, but so far no-one has attempted to actually do it. The most
likely approach would be for standards to be developed for individual use cases
currently addressed with requirements files. One option here would be for this
PEP to simply define a new file format which is simply a text file containing
:pep:`508` requirements, one per line. That would just leave the question of
how to locate that file.

The "obvious" solution here would be to do something like name the file the
same as the script, but with a ``.reqs`` extension (or something similar).
However, this still requires *two* files, where currently only a single file is
needed, and as such, does not match the "better batch file" model (shell
scripts and batch files are typically self-contained). It requires the
developer to remember to keep the two files together, and this may not always
be possible. For example, system administration policies may require that *all*
files in a certain directory are executable (the Linux filesystem standards
require this of ``/usr/bin``, for example). And some methods of sharing a
script (for example, publishing it on a text file sharing service like Github's
gist, or a corporate intranet) may not allow for deriving the location of an
associated requirements file from the script's location (tools like ``pipx``
support running a script directly from a URL, so "download and unpack a zip of
the script and its dependencies" may not be an appropriate requirement).

Essentially, though, the issue here is that there is an explicitly stated
requirement that the format supports storing dependency data *in the script
file itself*. Solutions that don't do that are simply ignoring that
requirement.

Why not use (possibly restricted) Python syntax?
------------------------------------------------

This would typically involve storing metadata as multiple special variables,
such as the following.

.. code:: python

    __requires_python__ = ">=3.11"
    __dependencies__ = [
        "requests",
        "click",
    ]

The most significant problem with this proposal is that it requires all
consumers of the dependency data to implement a Python parser. Even if the
syntax is restricted, the *rest* of the script will use the full Python syntax,
and trying to define a syntax which can be successfully parsed in isolation
from the surrounding code is likely to be extremely difficult and error-prone.

Furthermore, Python's syntax changes in every release. If extracting dependency
data needs a Python parser, the parser will need to know which version of
Python the script is written for, and the overhead for a generic tool of having
a parser that can handle *multiple* versions of Python is unsustainable.

With this approach there is the potential to clutter scripts with many
variables as new extensions get added. Additionally, intuiting which metadata
fields correspond to which variable names would cause confusion for users.

It is worth noting, though, that the ``pip-run`` utility does implement (an
extended form of) this approach. `Further discussion <pip-run issue_>`_ of
the ``pip-run`` design is available on the project's issue tracker.

What about local dependencies?
------------------------------

These can be handled without needing special metadata and tooling, simply by
adding the location of the dependencies to ``sys.path``. This PEP simply isn't
needed for this case. If, on the other hand, the "local dependencies" are
actual distributions which are published locally, they can be specified as
usual with a :pep:`508` requirement, and the local package index specified when
running a tool by using the tool's UI for that.

Open Issues
===========

None at this point.


References
==========

.. _pyproject metadata: https://packaging.python.org/en/latest/specifications/declaring-project-metadata/
.. _pip-run issue: https://github.com/jaraco/pip-run/issues/44
.. _pyproject without wheels: https://discuss.python.org/t/projects-that-arent-meant-to-generate-a-wheel-and-pyproject-toml/29684


Footnotes
=========

.. [1] A large number of users use scripts that are version controlled. For
   example, `the SREs that were mentioned <723-comment-block_>`_ or
   projects that require special maintenance like the
   `AWS CLI <https://github.com/aws/aws-cli/tree/4393dcdf044a5275000c9c193d1933c07a08fdf1/scripts>`__
   or `Calibre <https://github.com/kovidgoyal/calibre/tree/master/setup>`__.
.. [2] The syntax is taken directly from the final resolution of the
   `Blocks extension`__ to `Python Markdown`__.

   __ https://github.com/facelessuser/pymdown-extensions/discussions/1973
   __ https://github.com/Python-Markdown/markdown



Copyright
=========

This document is placed in the public domain or under the
CC0-1.0-Universal license, whichever is more permissive.