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‎.github/CODEOWNERS

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@@ -28,14 +28,18 @@ Objects/type* @markshannon
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Objects/codeobject.c @markshannon
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Objects/frameobject.c @markshannon
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Objects/call.c @markshannon
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Python/ceval.c @markshannon
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Python/ceval*.c @markshannon @gvanrossum
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Python/ceval*.h @markshannon @gvanrossum
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Python/compile.c @markshannon @iritkatriel
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Python/assemble.c @markshannon @iritkatriel
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Python/flowgraph.c @markshannon @iritkatriel
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Python/ast_opt.c @isidentical
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Python/bytecodes.c @markshannon @gvanrossum
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Python/optimizer*.c @markshannon @gvanrossum
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Lib/test/test_patma.py @brandtbucher
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Lib/test/test_peepholer.py @brandtbucher
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Lib/test/test_type_*.py @JelleZijlstra
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Lib/test/test_capi/test_misc.py @markshannon @gvanrossum
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# Exceptions
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Lib/traceback.py @iritkatriel
@@ -102,6 +106,9 @@ Include/internal/pycore_time.h @pganssle @abalkin
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/Lib/tokenize.py @pablogsal @lysnikolaou
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/Lib/test/test_tokenize.py @pablogsal @lysnikolaou
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# Code generator
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/Tools/cases_generator/ @gvanrossum
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# AST
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Python/ast.c @isidentical
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Parser/asdl.py @isidentical
@@ -151,7 +158,7 @@ Doc/c-api/stable.rst @encukou
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**/*idlelib* @terryjreedy
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**/*typing* @gvanrossum @JelleZijlstra @AlexWaygood
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**/*typing* @JelleZijlstra @AlexWaygood
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**/*ftplib @giampaolo
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**/*shutil @giampaolo

‎.github/workflows/build.yml

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@@ -120,7 +120,9 @@ jobs:
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check_generated_files:
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name: 'Check if generated files are up to date'
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runs-on: ubuntu-latest
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# Don't use ubuntu-latest but a specific version to make the job
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# reproducible: to get the same tools versions (autoconf, aclocal, ...)
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runs-on: ubuntu-22.04
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timeout-minutes: 60
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needs: check_source
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if: needs.check_source.outputs.run_tests == 'true'
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- name: Check Autoconf and aclocal versions
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run: |
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grep "Generated by GNU Autoconf 2.71" configure
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grep "aclocal 1.16.4" aclocal.m4
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grep "aclocal 1.16.5" aclocal.m4
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grep -q "runstatedir" configure
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grep -q "PKG_PROG_PKG_CONFIG" aclocal.m4
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- name: Configure CPython
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run: |
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# Build Python with the libpython dynamic library
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./configure --config-cache --with-pydebug --enable-shared
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- name: Regenerate autoconf files with container image
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run: make regen-configure
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- name: Regenerate autoconf files
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# Same command used by Tools/build/regen-configure.sh ($AUTORECONF)
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run: autoreconf -ivf -Werror
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- name: Build CPython
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run: |
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make -j4 regen-all

‎.github/workflows/posix-deps-apt.sh

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#!/bin/sh
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apt-get update
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# autoconf-archive is needed by autoreconf (check_generated_files job)
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apt-get -yq install \
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build-essential \
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pkg-config \
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autoconf-archive \
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ccache \
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gdb \
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lcov \

‎Doc/c-api/bool.rst

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.. c:var:: PyObject* Py_False
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The Python ``False`` object. This object has no methods and is
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`immortal <https://peps.python.org/pep-0683/>`_.
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:term:`immortal`.
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.. versionchanged:: 3.12
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:c:data:`Py_False` is immortal.
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.. versionchanged:: 3.12
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:c:data:`Py_False` is :term:`immortal`.
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.. c:var:: PyObject* Py_True
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The Python ``True`` object. This object has no methods and is
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`immortal <https://peps.python.org/pep-0683/>`_.
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:term:`immortal`.
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.. versionchanged:: 3.12
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:c:data:`Py_True` is immortal.
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.. versionchanged:: 3.12
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:c:data:`Py_True` is :term:`immortal`.
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.. c:macro:: Py_RETURN_FALSE

‎Doc/c-api/init.rst

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@@ -1485,7 +1485,7 @@ otherwise immutable (e.g. ``None``, ``(1, 5)``) can't normally be shared
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because of the refcount. One simple but less-efficient approach around
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this is to use a global lock around all use of some state (or object).
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Alternately, effectively immutable objects (like integers or strings)
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can be made safe in spite of their refcounts by making them "immortal".
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can be made safe in spite of their refcounts by making them :term:`immortal`.
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In fact, this has been done for the builtin singletons, small integers,
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and a number of other builtin objects.
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‎Doc/c-api/init_config.rst

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.. c:member:: int show_ref_count
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Show total reference count at exit (excluding immortal objects)?
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Show total reference count at exit (excluding :term:`immortal` objects)?
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Set to ``1`` by :option:`-X showrefcount <-X>` command line option.
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‎Doc/c-api/none.rst

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.. c:var:: PyObject* Py_None
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The Python ``None`` object, denoting lack of value. This object has no methods
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and is `immortal <https://peps.python.org/pep-0683/>`_.
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and is :term:`immortal`.
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.. versionchanged:: 3.12
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:c:data:`Py_None` is immortal.
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.. versionchanged:: 3.12
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:c:data:`Py_None` is :term:`immortal`.
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.. c:macro:: Py_RETURN_NONE
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‎Doc/c-api/refcounting.rst

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@@ -17,7 +17,7 @@ of Python objects.
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Note that the returned value may not actually reflect how many
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references to the object are actually held. For example, some
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objects are "immortal" and have a very high refcount that does not
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objects are :term:`immortal` and have a very high refcount that does not
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reflect the actual number of references. Consequently, do not rely
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on the returned value to be accurate, other than a value of 0 or 1.
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Set the object *o* reference counter to *refcnt*.
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Note that this function has no effect on
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`immortal <https://peps.python.org/pep-0683/>`_
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objects.
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This function has no effect on :term:`immortal` objects.
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.. versionadded:: 3.9
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Indicate taking a new :term:`strong reference` to object *o*,
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indicating it is in use and should not be destroyed.
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This function has no effect on :term:`immortal` objects.
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This function is usually used to convert a :term:`borrowed reference` to a
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:term:`strong reference` in-place. The :c:func:`Py_NewRef` function can be
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used to create a new :term:`strong reference`.
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Release a :term:`strong reference` to object *o*, indicating the
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reference is no longer used.
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This function has no effect on :term:`immortal` objects.
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Once the last :term:`strong reference` is released
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(i.e. the object's reference count reaches 0),
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the object's type's deallocation

‎Doc/c-api/slice.rst

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.. c:var:: PyObject *Py_Ellipsis
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The Python ``Ellipsis`` object. This object has no methods. Like
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:c:data:`Py_None`, it is an `immortal <https://peps.python.org/pep-0683/>`_.
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singleton object.
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:c:data:`Py_None`, it is an :term:`immortal` singleton object.
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.. versionchanged:: 3.12
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:c:data:`Py_Ellipsis` is immortal.

‎Doc/glossary.rst

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:ref:`idle` is a basic editor and interpreter environment
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which ships with the standard distribution of Python.
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immortal
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If an object is immortal, its reference count is never modified, and
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therefore it is never deallocated.
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Built-in strings and singletons are immortal objects. For example,
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:const:`True` and :const:`None` singletons are immmortal.
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See `PEP 683 – Immortal Objects, Using a Fixed Refcount
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<https://peps.python.org/pep-0683/>`_ for more information.
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immutable
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An object with a fixed value. Immutable objects include numbers, strings and
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tuples. Such an object cannot be altered. A new object has to
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reference count
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The number of references to an object. When the reference count of an
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object drops to zero, it is deallocated. Some objects are
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"immortal" and have reference counts that are never modified, and
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:term:`immortal` and have reference counts that are never modified, and
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therefore the objects are never deallocated. Reference counting is
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generally not visible to Python code, but it is a key element of the
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:term:`CPython` implementation. Programmers can call the

‎Doc/howto/isolating-extensions.rst

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- Define a traverse function using ``Py_tp_traverse``, which
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visits the type (e.g. using :c:expr:`Py_VISIT(Py_TYPE(self))`).
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Please refer to the :ref:`the documentation <type-structs>` of
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Please refer to the the documentation of
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:c:macro:`Py_TPFLAGS_HAVE_GC` and :c:member:`~PyTypeObject.tp_traverse`
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for additional considerations.
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If your traverse function delegates to the ``tp_traverse`` of its base class
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(or another type), ensure that ``Py_TYPE(self)`` is visited only once.
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The API for defining heap types grew organically, leaving it
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somewhat awkward to use in its current state.
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The following sections will guide you through common issues.
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``tp_traverse`` in Python 3.8 and lower
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.......................................
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The requirement to visit the type from ``tp_traverse`` was added in Python 3.9.
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If you support Python 3.8 and lower, the traverse function must *not*
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visit the type, so it must be more complicated::
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static int my_traverse(PyObject *self, visitproc visit, void *arg)
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{
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if (Py_Version >= 0x03090000) {
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Py_VISIT(Py_TYPE(self));
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}
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return 0;
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}
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Unfortunately, :c:data:`Py_Version` was only added in Python 3.11.
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As a replacement, use:
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* :c:macro:`PY_VERSION_HEX`, if not using the stable ABI, or
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* :py:data:`sys.version_info` (via :c:func:`PySys_GetObject` and
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:c:func:`PyArg_ParseTuple`).
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Delegating ``tp_traverse``
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..........................
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If your traverse function delegates to the :c:member:`~PyTypeObject.tp_traverse`
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of its base class (or another type), ensure that ``Py_TYPE(self)`` is visited
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only once.
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if (base->tp_flags & Py_TPFLAGS_HEAPTYPE) {
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} else {
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Py_VISIT(Py_TYPE(self));
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if (Py_Version >= 0x03090000) {
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Py_VISIT(Py_TYPE(self));
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}
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}
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It is not necessary to handle the type's reference count in ``tp_new``
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and ``tp_clear``.
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It is not necessary to handle the type's reference count in
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:c:member:`~PyTypeObject.tp_new` and :c:member:`~PyTypeObject.tp_clear`.
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Defining ``tp_dealloc``
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.......................
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If your type has a custom :c:member:`~PyTypeObject.tp_dealloc` function,
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it needs to:
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- call :c:func:`PyObject_GC_UnTrack` before any fields are invalidated, and
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- decrement the reference count of the type.
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To keep the type valid while ``tp_free`` is called, the type's refcount needs
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to be decremented *after* the instance is deallocated. For example::
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static void my_dealloc(PyObject *self)
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{
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PyObject_GC_UnTrack(self);
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...
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PyTypeObject *type = Py_TYPE(self);
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type->tp_free(self);
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Py_DECREF(type);
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}
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The default ``tp_dealloc`` function does this, so
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if your type does *not* override
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``tp_dealloc`` you don't need to add it.
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Not overriding ``tp_free``
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..........................
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The :c:member:`~PyTypeObject.tp_free` slot of a heap type must be set to
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:c:func:`PyObject_GC_Del`.
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This is the default; do not override it.
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Avoiding ``PyObject_New``
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.........................
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GC-tracked objects need to be allocated using GC-aware functions.
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If you use use :c:func:`PyObject_New` or :c:func:`PyObject_NewVar`:
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- Get and call type's :c:member:`~PyTypeObject.tp_alloc` slot, if possible.
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That is, replace ``TYPE *o = PyObject_New(TYPE, typeobj)`` with::
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TYPE *o = typeobj->tp_alloc(typeobj, 0);
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Replace ``o = PyObject_NewVar(TYPE, typeobj, size)`` with the same,
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but use size instead of the 0.
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- If the above is not possible (e.g. inside a custom ``tp_alloc``),
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call :c:func:`PyObject_GC_New` or :c:func:`PyObject_GC_NewVar`::
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TYPE *o = PyObject_GC_New(TYPE, typeobj);
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TYPE *o = PyObject_GC_NewVar(TYPE, typeobj, size);
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Module State Access from Classes

‎Doc/library/__main__.rst

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import sys
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student_name = sys.argv[2] if len(sys.argv) >= 2 else ''
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student_name = sys.argv[1] if len(sys.argv) >= 2 else ''
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print(f'Found student: {search_students(student_name)}')
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Note that ``from .student import search_students`` is an example of a relative

‎Doc/library/importlib.metadata.rst

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and one top-level *import package*
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may map to multiple *distribution packages*
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if it is a namespace package.
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You can use :ref:`package_distributions() <package-distributions>`
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You can use :ref:`packages_distributions() <package-distributions>`
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By default, distribution metadata can live on the file system

‎Doc/library/profile.rst

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The first line indicates that 214 calls were monitored. Of those calls, 207
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next line: ``Ordered by: cumulative time``, indicates that the text string in the
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far right column was used to sort the output. The column headings include:
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next line: ``Ordered by: cumulative time`` indicates the output is sorted
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by the ``cumtime`` values. The column headings include:
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ncalls
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for the number of calls.

‎Doc/library/subprocess.rst

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.. note::
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The function is implemented using a busy loop (non-blocking call and
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short sleeps). Use the :mod:`asyncio` module for an asynchronous wait:
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see :class:`asyncio.create_subprocess_exec`.
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When the ``timeout`` parameter is not ``None``, then (on POSIX) the
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function is implemented using a busy loop (non-blocking call and short
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sleeps). Use the :mod:`asyncio` module for an asynchronous wait: see
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:class:`asyncio.create_subprocess_exec`.
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.. versionchanged:: 3.3
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*timeout* was added.

‎Doc/library/sys.rst

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Note that the returned value may not actually reflect how many
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objects are "immortal" and have a very high refcount that does not
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objects are :term:`immortal` and have a very high refcount that does not
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reflect the actual number of references. Consequently, do not rely
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names used in Python programs are automatically interned, and the dictionaries
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1185-
Interned strings are not immortal; you must keep a reference to the return
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value of :func:`intern` around to benefit from it.
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Interned strings are not :term:`immortal`; you must keep a reference to the
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return value of :func:`intern` around to benefit from it.
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.. function:: is_finalizing()

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