604 lines
23 KiB
ReStructuredText
604 lines
23 KiB
ReStructuredText
PEP: 620
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Title: Hide implementation details from the C API
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Author: Victor Stinner <vstinner@python.org>
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Status: Draft
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Type: Standards Track
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Content-Type: text/x-rst
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Created: 19-June-2020
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Python-Version: 3.10
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Abstract
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========
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Introduce C API incompatible changes to hide implementation details.
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Once most implementation details will be hidden, evolution of CPython
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internals would be less limited by C API backward compatibility issues.
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It will be way easier to add new features.
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It becomes possible to experiment with more advanced optimizations in
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CPython than just micro-optimizations, like tagged pointers.
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Define a process to reduce the number of broken C extensions.
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The implementation of this PEP is expected to be done carefully over
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multiple Python versions. It already started in Python 3.7 and most
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changes are already completed. The `Process to reduce the number of
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broken C extensions`_ dictates the rhythm.
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Motivation
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==========
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The C API blocks CPython evolutions
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-----------------------------------
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Adding or removing members of C structures is causing multiple backward
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compatibility issues.
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Adding a new member breaks the stable ABI (PEP 384), especially for
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types declared statically (e.g. ``static PyTypeObject MyType =
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{...};``). In Python 3.4, the PEP 442 "Safe object finalization" added
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the ``tp_finalize`` member at the end of the ``PyTypeObject`` structure.
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For ABI backward compatibility, a new ``Py_TPFLAGS_HAVE_FINALIZE`` type
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flag was required to announce if the type structure contains the
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``tp_finalize`` member. The flag was removed in Python 3.8 (`bpo-32388
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<https://bugs.python.org/issue32388>`_).
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The ``PyTypeObject.tp_print`` member, deprecated since Python 3.0
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released in 2009, has been removed in the Python 3.8 development cycle.
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But the change broke too many C extensions and had to be reverted before
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3.8 final release. Finally, the member was removed again in Python 3.9.
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C extensions rely on the ability to access structure members,
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indirectly through the C API, or even directly. Modifying structures
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like ``PyListObject`` cannot be even considered.
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The ``PyTypeObject`` structure is the one which evolved the most, simply
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because there was no other way to evolve CPython than modifying it.
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A C extension can technically dereference a ``PyObject*`` pointer and
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access ``PyObject`` members. This prevents experiments like tagged
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pointers (storing small values as ``PyObject*`` which does not point to
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a valid ``PyObject`` structure).
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Replacing Python garbage collector with a tracing garbage collector
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would also need to remove ``PyObject.ob_refcnt`` reference counter,
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whereas currently ``Py_INCREF()`` and ``Py_DECREF()`` macros access
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directly to ``PyObject.ob_refcnt``.
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Same CPython design since 1990: structures and reference counting
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-----------------------------------------------------------------
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When the CPython project was created, it was written with one principle:
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keep the implementation simple enough so it can be maintained by a
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single developer. CPython complexity grew a lot and many
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micro-optimizations have been implemented, but CPython core design has
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not changed.
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Members of ``PyObject`` and ``PyTupleObject`` structures have not
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changed since the "Initial revision" commit (1990)::
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#define OB_HEAD \
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unsigned int ob_refcnt; \
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struct _typeobject *ob_type;
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typedef struct _object {
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OB_HEAD
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} object;
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typedef struct {
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OB_VARHEAD
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object *ob_item[1];
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} tupleobject;
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Only names changed: ``object`` was renamed to ``PyObject`` and
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``tupleobject`` was renamed to ``PyTupleObject``.
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CPython still tracks Python objects lifetime using reference counting
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internally and for third party C extensions (through the Python C API).
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All Python objects must be allocated on the heap and cannot be moved.
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Why is PyPy more efficient than CPython?
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----------------------------------------
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The PyPy project is a Python implementation which is 4.2x faster than
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CPython on average. PyPy developers chose to not fork CPython, but start
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from scratch to have more freedom in terms of optimization choices.
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PyPy does not use reference counting, but a tracing garbage collector
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which moves objects. Objects can be allocated on the stack (or even not
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at all), rather than always having to be allocated on the heap.
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Objects layouts are designed with performance in mind. For example, a
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list strategy stores integers directly as integers, rather than objects.
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Moreover, PyPy also has a JIT compiler which emits fast code thanks to
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the efficient PyPy design.
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PyPy bottleneck: the Python C API
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---------------------------------
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While PyPy is way more efficient than CPython to run pure Python code,
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it is as efficient or slower than CPython to run C extensions.
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Since the C API requires ``PyObject*`` and allows to access directly
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structure members, PyPy has to associate a CPython object to PyPy
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objects and maintain both consistent. Converting a PyPy object to a
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CPython object is inefficient. Moreover, reference counting also has to
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be implemented on top of PyPy tracing garbage collector.
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These conversions are required because the Python C API is too close to
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the CPython implementation: there is no high-level abstraction.
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For example, structures members are part of the public C API and nothing
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prevents a C extension to get or set directly
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``PyTupleObject.ob_item[0]`` (the first item of a tuple).
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See `Inside cpyext: Why emulating CPython C API is so Hard
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<https://morepypy.blogspot.com/2018/09/inside-cpyext-why-emulating-cpython-c.html>`_
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(Sept 2018) by Antonio Cuni for more details.
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Rationale
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=========
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Hide implementation details
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---------------------------
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Hiding implementation details from the C API has multiple advantages:
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* It becomes possible to experiment with more advanced optimizations in
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CPython than just micro-optimizations. For example, tagged pointers,
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and replace the garbage collector with a tracing garbage collector
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which can move objects.
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* Adding new features in CPython becomes easier.
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* PyPy should be able to avoid conversions to CPython objects in more
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cases: keep efficient PyPy objects.
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* It becomes easier to implement the C API for a new Python
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implementation.
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* More C extensions will be compatible with Python implementations other
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than CPython.
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Relationship with the limited C API
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-----------------------------------
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The PEP 384 "Defining a Stable ABI" is in Python 3.4. It introduces the
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"limited C API": a subset of the C API. When the limited C API is used,
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it becomes possible to build a C extension only once and use it on
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multiple Python versions: that's the stable ABI.
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The main limitation of the PEP 384 is that C extensions have to opt-in
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for the limited C API. Only very few projects made this choice,
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usually to ease distribution of binaries, especially on Windows.
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This PEP moves the C API towards the limited C API.
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Ideally, the C API will become the limited C API and all C extensions
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will use the stable ABI, but this is out of this PEP scope.
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Specification
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=============
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Summary
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-------
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* (**Completed**) Reorganize the C API header files: create ``Include/cpython/`` and
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``Include/internal/`` subdirectories.
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* (**Completed**) Move private functions exposing implementation details to the internal
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C API.
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* (**Completed**) Convert macros to static inline functions.
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* (**Completed**) Add new functions ``Py_SET_TYPE()``, ``Py_SET_REFCNT()`` and
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``Py_SET_SIZE()``. The ``Py_TYPE()``, ``Py_REFCNT()`` and
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``Py_SIZE()`` macros become functions which cannot be used as l-value.
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* (**Completed**) New C API functions must not return borrowed
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references.
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* (**In Progress**) Provide ``pythoncapi_compat.h`` header file.
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* (**In Progress**) Make structures opaque, add getter and setter
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functions.
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* (**Not Started**) Deprecate ``PySequence_Fast_ITEMS()``.
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* (**Not Started**) Convert ``PyTuple_GET_ITEM()`` and
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``PyList_GET_ITEM()`` macros to static inline functions.
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Reorganize the C API header files
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---------------------------------
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The first consumer of the C API was Python itself. There is no clear
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separation between APIs which must not be used outside Python, and API
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which are public on purpose.
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Header files must be reorganized in 3 API:
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* ``Include/`` directory is the limited C API: no implementation
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details, structures are opaque. C extensions using it get a stable
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ABI.
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* ``Include/cpython/`` directory is the CPython C API: less "portable"
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API, depends more on the Python version, expose some implementation
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details, few incompatible changes can happen.
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* ``Include/internal/`` directory is the internal C API: implementation
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details, incompatible changes are likely at each Python release.
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The creation of the ``Include/cpython/`` directory is fully backward
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compatible. ``Include/cpython/`` header files cannot be included
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directly and are included automatically by ``Include/`` header files
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when the ``Py_LIMITED_API`` macro is not defined.
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The internal C API is installed and can be used for specific usage like
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debuggers and profilers which must access structures members without
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executing code. C extensions using the internal C API are tightly
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coupled to a Python version and must be recompiled at each Python
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version.
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**STATUS**: Completed (in Python 3.8)
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The reorganization of header files started in Python 3.7 and was
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completed in Python 3.8:
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* `bpo-35134 <https://bugs.python.org/issue35134>`_: Add a new
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Include/cpython/ subdirectory for the "CPython API" with
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implementation details.
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* `bpo-35081 <https://bugs.python.org/issue35081>`_: Move internal
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headers to ``Include/internal/``
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Move private functions to the internal C API
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--------------------------------------------
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Private functions which expose implementation details must be moved to
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the internal C API.
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If a C extension relies on a CPython private function which exposes
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CPython implementation details, other Python implementations have to
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re-implement this private function to support this C extension.
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**STATUS**: Completed (in Python 3.9)
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Private functions moved to the internal C API in Python 3.8:
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* ``_PyObject_GC_TRACK()``, ``_PyObject_GC_UNTRACK()``
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Macros and functions excluded from the limited C API in Python 3.9:
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* ``_PyObject_SIZE()``, ``_PyObject_VAR_SIZE()``
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* ``PyThreadState_DeleteCurrent()``
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* ``PyFPE_START_PROTECT()``, ``PyFPE_END_PROTECT()``
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* ``_Py_NewReference()``, ``_Py_ForgetReference()``
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* ``_PyTraceMalloc_NewReference()``
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* ``_Py_GetRefTotal()``
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Private functions moved to the internal C API in Python 3.9:
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* GC functions like ``_Py_AS_GC()``, ``_PyObject_GC_IS_TRACKED()``
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and ``_PyGCHead_NEXT()``
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* ``_Py_AddToAllObjects()`` (not exported)
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* ``_PyDebug_PrintTotalRefs()``, ``_Py_PrintReferences()``,
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``_Py_PrintReferenceAddresses()`` (not exported)
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Public "clear free list" functions moved to the internal C API and
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renamed to private functions in Python 3.9:
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* ``PyAsyncGen_ClearFreeLists()``
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* ``PyContext_ClearFreeList()``
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* ``PyDict_ClearFreeList()``
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* ``PyFloat_ClearFreeList()``
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* ``PyFrame_ClearFreeList()``
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* ``PyList_ClearFreeList()``
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* ``PyTuple_ClearFreeList()``
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* Functions simply removed:
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* ``PyMethod_ClearFreeList()`` and ``PyCFunction_ClearFreeList()``:
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bound method free list removed in Python 3.9.
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* ``PySet_ClearFreeList()``: set free list removed in Python 3.4.
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* ``PyUnicode_ClearFreeList()``: Unicode free list removed
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in Python 3.3.
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Convert macros to static inline functions
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-----------------------------------------
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Converting macros to static inline functions has multiple advantages:
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* Functions have well defined parameter types and return type.
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* Functions can use variables with a well defined scope (the function).
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* Debugger can be put breakpoints on functions and profilers can display
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the function name in the call stacks. In most cases, it works even
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when a static inline function is inlined.
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* Functions don't have `macros pitfalls
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<https://gcc.gnu.org/onlinedocs/cpp/Macro-Pitfalls.html>`_.
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Converting macros to static inline functions should only impact very few
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C extensions that use macros in unusual ways.
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For backward compatibility, functions must continue to accept any type,
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not only ``PyObject*``, to avoid compiler warnings, since most macros
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cast their parameters to ``PyObject*``.
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Python 3.6 requires C compilers to support static inline functions: the
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PEP 7 requires a subset of C99.
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**STATUS**: Completed (in Python 3.9)
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Macros converted to static inline functions in Python 3.8:
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* ``Py_INCREF()``, ``Py_DECREF()``
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* ``Py_XINCREF()``, ``Py_XDECREF()``
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* ``PyObject_INIT()``, ``PyObject_INIT_VAR()``
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* ``_PyObject_GC_TRACK()``, ``_PyObject_GC_UNTRACK()``, ``_Py_Dealloc()``
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Macros converted to regular functions in Python 3.9:
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* ``Py_EnterRecursiveCall()``, ``Py_LeaveRecursiveCall()``
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(added to the limited C API)
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* ``PyObject_INIT()``, ``PyObject_INIT_VAR()``
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* ``PyObject_GET_WEAKREFS_LISTPTR()``
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* ``PyObject_CheckBuffer()``
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* ``PyIndex_Check()``
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* ``PyObject_IS_GC()``
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* ``PyObject_NEW()`` (alias to ``PyObject_New()``),
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``PyObject_NEW_VAR()`` (alias to ``PyObject_NewVar()``)
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* ``PyType_HasFeature()`` (always call ``PyType_GetFlags()``)
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* ``Py_TRASHCAN_BEGIN_CONDITION()`` and ``Py_TRASHCAN_END()`` macros
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now call functions which hide implementation details, rather than
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accessing directly members of the ``PyThreadState`` structure.
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Make structures opaque
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----------------------
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The following structures of the C API become opaque:
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* ``PyInterpreterState``
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* ``PyThreadState``
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* ``PyGC_Head``
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* ``PyTypeObject``
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* ``PyObject`` and ``PyVarObject``
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* ``PyTypeObject``
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* All types which inherit from ``PyObject`` or ``PyVarObject``
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C extensions must use getter or setter functions to get or set structure
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members. For example, ``tuple->ob_item[0]`` must be replaced with
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``PyTuple_GET_ITEM(tuple, 0)``.
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To be able to move away from reference counting, ``PyObject`` must
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become opaque. Currently, the reference counter ``PyObject.ob_refcnt``
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is exposed in the C API. All structures must become opaque, since they
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"inherit" from PyObject. For, ``PyFloatObject`` inherits from
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``PyObject``::
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typedef struct {
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PyObject ob_base;
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double ob_fval;
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} PyFloatObject;
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Making ``PyObject`` fully opaque requires converting ``Py_INCREF()`` and
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``Py_DECREF()`` macros to function calls. This change has an impact on
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performance. It is likely to be one of the very last changes when making
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structures opaque.
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Making ``PyTypeObject`` structure opaque breaks C extensions declaring
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types statically (e.g. ``static PyTypeObject MyType = {...};``). C
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extensions must use ``PyType_FromSpec()`` to allocate types on the heap
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instead. Using heap types has other advantages like being compatible
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with subinterpreters. Combined with PEP 489 "Multi-phase extension
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module initialization", it makes a C extension behavior closer to a
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Python module, like allowing to create more than one module instance.
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Making ``PyThreadState`` structure opaque requires adding getter and
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setter functions for members used by C extensions.
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**STATUS**: In Progress (started in Python 3.8)
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The ``PyInterpreterState`` structure was made opaque in Python 3.8
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(`bpo-35886 <https://bugs.python.org/issue35886>`_) and the
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``PyGC_Head`` structure (`bpo-40241
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<https://bugs.python.org/issue40241>`_) was made opaque in Python 3.9.
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Issues tracking the work to prepare the C API to make following
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structures opaque:
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* ``PyObject``: `bpo-39573 <https://bugs.python.org/issue39573>`_
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* ``PyTypeObject``: `bpo-40170 <https://bugs.python.org/issue40170>`_
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* ``PyFrameObject``: `bpo-40421 <https://bugs.python.org/issue40421>`_
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* Python 3.9 adds ``PyFrame_GetCode()`` and ``PyFrame_GetBack()``
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getter functions, and moves ``PyFrame_GetLineNumber`` to the limited
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C API.
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* ``PyThreadState``: `bpo-39947 <https://bugs.python.org/issue39947>`_
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* Python 3.9 adds 3 getter functions: ``PyThreadState_GetFrame()``,
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``PyThreadState_GetID()``, ``PyThreadState_GetInterpreter()``.
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Disallow using Py_TYPE() as l-value
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-----------------------------------
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The ``Py_TYPE()`` function gets an object type, its ``PyObject.ob_type``
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member. It is implemented as a macro which can be used as an l-value to
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set the type: ``Py_TYPE(obj) = new_type``. This code relies on the
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assumption that ``PyObject.ob_type`` can be modified directly. It
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prevents making the ``PyObject`` structure opaque.
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New setter functions ``Py_SET_TYPE()``, ``Py_SET_REFCNT()`` and
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``Py_SET_SIZE()`` are added and must be used instead.
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The ``Py_TYPE()``, ``Py_REFCNT()`` and ``Py_SIZE()`` macros must be
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converted to static inline functions which can not be used as l-value.
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For example, the ``Py_TYPE()`` macro::
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#define Py_TYPE(ob) (((PyObject*)(ob))->ob_type)
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becomes::
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#define _PyObject_CAST_CONST(op) ((const PyObject*)(op))
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static inline PyTypeObject* _Py_TYPE(const PyObject *ob) {
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return ob->ob_type;
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}
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#define Py_TYPE(ob) _Py_TYPE(_PyObject_CAST_CONST(ob))
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**STATUS**: Completed (in Python 3.10)
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New functions ``Py_SET_TYPE()``, ``Py_SET_REFCNT()`` and
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``Py_SET_SIZE()`` were added to Python 3.9.
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In Python 3.10, ``Py_TYPE()``, ``Py_REFCNT()`` and ``Py_SIZE()`` can no
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longer be used as l-value and the new setter functions must be used
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instead.
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New C API functions must not return borrowed references
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-------------------------------------------------------
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When a function returns a borrowed reference, Python cannot track when
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the caller stops using this reference.
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For example, if the Python ``list`` type is specialized for small
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integers, store directly "raw" numbers rather than Python objects,
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``PyList_GetItem()`` has to create a temporary Python object. The
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problem is to decide when it is safe to delete the temporary object.
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The general guidelines is to avoid returning borrowed references for new
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C API functions.
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No function returning borrowed references is scheduled for removal by
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this PEP.
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**STATUS**: Completed (in Python 3.9)
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In Python 3.9, new C API functions returning Python objects only return
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strong references:
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* ``PyFrame_GetBack()``
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* ``PyFrame_GetCode()``
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* ``PyObject_CallNoArgs()``
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* ``PyObject_CallOneArg()``
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* ``PyThreadState_GetFrame()``
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Avoid functions returning PyObject**
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------------------------------------
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The ``PySequence_Fast_ITEMS()`` function gives a direct access to an
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array of ``PyObject*`` objects. The function is deprecated in favor of
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``PyTuple_GetItem()`` and ``PyList_GetItem()``.
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``PyTuple_GET_ITEM()`` can be abused to access directly the
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``PyTupleObject.ob_item`` member::
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PyObject **items = &PyTuple_GET_ITEM(0);
|
|
|
|
The ``PyTuple_GET_ITEM()`` and ``PyList_GET_ITEM()`` macros are
|
|
converted to static inline functions to disallow that.
|
|
|
|
**STATUS**: Not Started
|
|
|
|
New pythoncapi_compat.h header file
|
|
-----------------------------------
|
|
|
|
Making structures opaque requires modifying C extensions to
|
|
use getter and setter functions. The practical issue is how to keep
|
|
support for old Python versions which don't have these functions.
|
|
|
|
For example, in Python 3.10, it is no longer possible to use
|
|
``Py_TYPE()`` as an l-value. The new ``Py_SET_TYPE()`` function must be
|
|
used instead::
|
|
|
|
#if PY_VERSION_HEX >= 0x030900A4
|
|
Py_SET_TYPE(&MyType, &PyType_Type);
|
|
#else
|
|
Py_TYPE(&MyType) = &PyType_Type;
|
|
#endif
|
|
|
|
This code may ring a bell to developers who ported their Python code
|
|
base from Python 2 to Python 3.
|
|
|
|
Python will distribute a new ``pythoncapi_compat.h`` header file which
|
|
provides new C API functions to old Python versions. Example::
|
|
|
|
#if PY_VERSION_HEX < 0x030900A4
|
|
static inline void
|
|
_Py_SET_TYPE(PyObject *ob, PyTypeObject *type)
|
|
{
|
|
ob->ob_type = type;
|
|
}
|
|
#define Py_SET_TYPE(ob, type) _Py_SET_TYPE((PyObject*)(ob), type)
|
|
#endif // PY_VERSION_HEX < 0x030900A4
|
|
|
|
Using this header file, ``Py_SET_TYPE()`` can be used on old Python
|
|
versions as well.
|
|
|
|
Developers can copy this file in their project, or even to only
|
|
copy/paste the few functions needed by their C extension.
|
|
|
|
**STATUS**: In Progress (implemented but not distributed by CPython yet)
|
|
|
|
The ``pythoncapi_compat.h`` header file is currently developer at:
|
|
https://github.com/pythoncapi/pythoncapi_compat
|
|
|
|
Process to reduce the number of broken C extensions
|
|
===================================================
|
|
|
|
Process to reduce the number of broken C extensions when introducing C
|
|
API incompatible changes listed in this PEP:
|
|
|
|
* Estimate how many popular C extensions are affected by the
|
|
incompatible change.
|
|
* Coordinate with maintainers of broken C extensions to prepare their
|
|
code for the future incompatible change.
|
|
* Introduce the incompatible changes in Python. The documentation must
|
|
explain how to port existing code. It is recommended to merge such
|
|
changes at the beginning of a development cycle to have more time for
|
|
tests.
|
|
* Changes which are the most likely to break a large number of C
|
|
extensions should be announced on the capi-sig mailing list to notify
|
|
C extensions maintainers to prepare their project for the next Python.
|
|
* If the change breaks too many projects, reverting the change should be
|
|
discussed, taking in account the number of broken packages, their
|
|
importance in the Python community, and the importance of the change.
|
|
|
|
The coordination usually means reporting issues to the projects, or even
|
|
proposing changes. It does not require waiting for a new release including
|
|
fixes for every broken project.
|
|
|
|
Since more and more C extensions are written using Cython, rather
|
|
directly using the C API, it is important to ensure that Cython is
|
|
prepared in advance for incompatible changes. It gives more time for C
|
|
extension maintainers to release a new version with code generated with
|
|
the updated Cython (for C extensions distributing the code generated by
|
|
Cython).
|
|
|
|
Future incompatible changes can be announced by deprecating a function
|
|
in the documentation and by annotating the function with
|
|
``Py_DEPRECATED()``. But making a structure opaque and preventing the
|
|
usage of a macro as l-value cannot be deprecated with
|
|
``Py_DEPRECATED()``.
|
|
|
|
The important part is coordination and finding a balance between CPython
|
|
evolutions and backward compatibility. For example, breaking a random,
|
|
old, obscure and unmaintained C extension on PyPI is less severe than
|
|
breaking numpy.
|
|
|
|
If a change is reverted, we move back to the coordination step to better
|
|
prepare the change. Once more C extensions are ready, the incompatible
|
|
change can be reconsidered.
|
|
|
|
|
|
Version History
|
|
===============
|
|
|
|
* Version 3, June 2020: PEP rewritten from scratch. Python now
|
|
distributes a new ``pythoncapi_compat.h`` header and a process is
|
|
defined to reduce the number of broken C extensions when introducing C
|
|
API incompatible changes listed in this PEP.
|
|
* Version 2, April 2020:
|
|
`PEP: Modify the C API to hide implementation details
|
|
<https://mail.python.org/archives/list/python-dev@python.org/thread/HKM774XKU7DPJNLUTYHUB5U6VR6EQMJF/#TKHNENOXP6H34E73XGFOL2KKXSM4Z6T2>`_.
|
|
* Version 1, July 2017:
|
|
`PEP: Hide implementation details in the C API
|
|
<https://mail.python.org/archives/list/python-ideas@python.org/thread/6XATDGWK4VBUQPRHCRLKQECTJIPBVNJQ/#HFBGCWVLSM47JEP6SO67MRFT7Y3EOC44>`_
|
|
sent to python-ideas
|
|
|
|
|
|
Copyright
|
|
=========
|
|
|
|
This document has been placed in the public domain.
|