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‎.github/workflows/reusable-context.yml

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run: python Tools/build/compute-changes.py
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env:
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GITHUB_DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
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CCF_TARGET_REF: ${{ github.base_ref || github.event.repository.default_branch }}
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CCF_HEAD_REF: ${{ github.event.pull_request.head.sha || github.sha }}
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- name: Compute hash for config cache key
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id: config-hash

‎Doc/deprecations/index.rst

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.. include:: pending-removal-in-3.17.rst
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.. include:: pending-removal-in-3.19.rst
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.. include:: pending-removal-in-future.rst
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C API deprecations

‎Doc/deprecations/pending-removal-in-3.19.rst

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Pending removal in Python 3.19
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------------------------------
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* :mod:`ctypes`:
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* Implicitly switching to the MSVC-compatible struct layout by setting
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:attr:`~ctypes.Structure._pack_` but not :attr:`~ctypes.Structure._layout_`
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on non-Windows platforms.

‎Doc/library/asyncio-eventloop.rst

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.. versionadded:: 3.5.2
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.. method:: loop.create_task(coro, *, name=None, context=None)
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.. method:: loop.create_task(coro, *, name=None, context=None, eager_start=None)
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Schedule the execution of :ref:`coroutine <coroutine>` *coro*.
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Return a :class:`Task` object.
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custom :class:`contextvars.Context` for the *coro* to run in.
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The current context copy is created when no *context* is provided.
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An optional keyword-only *eager_start* argument allows specifying
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if the task should execute eagerly during the call to create_task,
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or be scheduled later. If *eager_start* is not passed the mode set
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by :meth:`loop.set_task_factory` will be used.
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.. versionchanged:: 3.8
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Added the *name* parameter.
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.. versionchanged:: 3.11
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Added the *context* parameter.
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.. versionchanged:: next
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Added the *eager_start* parameter.
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.. method:: loop.set_task_factory(factory)
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Set a task factory that will be used by

‎Doc/library/ctypes.rst

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when :attr:`_fields_` is assigned, otherwise it will have no effect.
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Setting this attribute to 0 is the same as not setting it at all.
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This is only implemented for the MSVC-compatible memory layout.
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.. deprecated-removed:: next 3.19
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For historical reasons, if :attr:`!_pack_` is non-zero,
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the MSVC-compatible layout will be used by default.
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On non-Windows platforms, this default is deprecated and is slated to
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become an error in Python 3.19.
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If it is intended, set :attr:`~Structure._layout_` to ``'ms'``
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explicitly.
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.. attribute:: _align_
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Currently the default will be:
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- On Windows: ``"ms"``
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- When :attr:`~Structure._pack_` is specified: ``"ms"``
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- When :attr:`~Structure._pack_` is specified: ``"ms"``.
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(This is deprecated; see :attr:`~Structure._pack_` documentation.)
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- Otherwise: ``"gcc-sysv"``
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:attr:`!_layout_` must already be defined when
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:attr:`~Structure._fields_` is assigned, otherwise it will have no effect.
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.. versionadded:: next
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.. attribute:: _anonymous_
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An optional sequence that lists the names of unnamed (anonymous) fields.

‎Doc/library/heapq.rst

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This module provides an implementation of the heap queue algorithm, also known
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as the priority queue algorithm.
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Heaps are binary trees for which every parent node has a value less than or
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equal to any of its children. We refer to this condition as the heap invariant.
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Min-heaps are binary trees for which every parent node has a value less than
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or equal to any of its children.
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We refer to this condition as the heap invariant.
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This implementation uses arrays for which
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``heap[k] <= heap[2*k+1]`` and ``heap[k] <= heap[2*k+2]`` for all *k*, counting
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elements from zero. For the sake of comparison, non-existing elements are
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considered to be infinite. The interesting property of a heap is that its
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smallest element is always the root, ``heap[0]``.
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For min-heaps, this implementation uses lists for which
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``heap[k] <= heap[2*k+1]`` and ``heap[k] <= heap[2*k+2]`` for all *k* for which
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the compared elements exist. Elements are counted from zero. The interesting
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property of a min-heap is that its smallest element is always the root,
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``heap[0]``.
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The API below differs from textbook heap algorithms in two aspects: (a) We use
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zero-based indexing. This makes the relationship between the index for a node
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and the indexes for its children slightly less obvious, but is more suitable
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since Python uses zero-based indexing. (b) Our pop method returns the smallest
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item, not the largest (called a "min heap" in textbooks; a "max heap" is more
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common in texts because of its suitability for in-place sorting).
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Max-heaps satisfy the reverse invariant: every parent node has a value
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*greater* than any of its children. These are implemented as lists for which
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``maxheap[2*k+1] <= maxheap[k]`` and ``maxheap[2*k+2] <= maxheap[k]`` for all
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*k* for which the compared elements exist.
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The root, ``maxheap[0]``, contains the *largest* element;
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``heap.sort(reverse=True)`` maintains the max-heap invariant.
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These two make it possible to view the heap as a regular Python list without
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surprises: ``heap[0]`` is the smallest item, and ``heap.sort()`` maintains the
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heap invariant!
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The :mod:`!heapq` API differs from textbook heap algorithms in two aspects: (a)
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We use zero-based indexing. This makes the relationship between the index for
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a node and the indexes for its children slightly less obvious, but is more
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suitable since Python uses zero-based indexing. (b) Textbooks often focus on
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max-heaps, due to their suitability for in-place sorting. Our implementation
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favors min-heaps as they better correspond to Python :class:`lists <list>`.
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To create a heap, use a list initialized to ``[]``, or you can transform a
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populated list into a heap via function :func:`heapify`.
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These two aspects make it possible to view the heap as a regular Python list
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without surprises: ``heap[0]`` is the smallest item, and ``heap.sort()``
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maintains the heap invariant!
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The following functions are provided:
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Like :meth:`list.sort`, this implementation uses only the ``<`` operator
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for comparisons, for both min-heaps and max-heaps.
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In the API below, and in this documentation, the unqualified term *heap*
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generally refers to a min-heap.
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The API for max-heaps is named using a ``_max`` suffix.
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To create a heap, use a list initialized as ``[]``, or transform an existing list
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into a min-heap or max-heap using the :func:`heapify` or :func:`heapify_max`
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functions, respectively.
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The following functions are provided for min-heaps:
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.. function:: heappush(heap, item)
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Push the value *item* onto the *heap*, maintaining the heap invariant.
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Push the value *item* onto the *heap*, maintaining the min-heap invariant.
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.. function:: heappop(heap)
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Pop and return the smallest item from the *heap*, maintaining the heap
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Pop and return the smallest item from the *heap*, maintaining the min-heap
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invariant. If the heap is empty, :exc:`IndexError` is raised. To access the
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smallest item without popping it, use ``heap[0]``.
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.. function:: heapify(x)
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Transform list *x* into a heap, in-place, in linear time.
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Transform list *x* into a min-heap, in-place, in linear time.
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.. function:: heapreplace(heap, item)
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on the heap.
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For max-heaps, the following functions are provided:
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.. function:: heapify_max(x)
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Transform list *x* into a max-heap, in-place, in linear time.
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.. versionadded:: next
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.. function:: heappush_max(heap, item)
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Push the value *item* onto the max-heap *heap*, maintaining the max-heap
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invariant.
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.. versionadded:: next
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.. function:: heappop_max(heap)
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Pop and return the largest item from the max-heap *heap*, maintaining the
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max-heap invariant. If the max-heap is empty, :exc:`IndexError` is raised.
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To access the largest item without popping it, use ``maxheap[0]``.
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.. versionadded:: next
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.. function:: heappushpop_max(heap, item)
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Push *item* on the max-heap *heap*, then pop and return the largest item
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from *heap*.
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The combined action runs more efficiently than :func:`heappush_max`
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followed by a separate call to :func:`heappop_max`.
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.. versionadded:: next
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.. function:: heapreplace_max(heap, item)
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Pop and return the largest item from the max-heap *heap* and also push the
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new *item*.
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The max-heap size doesn't change. If the max-heap is empty,
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:exc:`IndexError` is raised.
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The value returned may be smaller than the *item* added. Refer to the
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analogous function :func:`heapreplace` for detailed usage notes.
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.. versionadded:: next
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The module also offers three general purpose functions based on heaps.
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‎Doc/library/pdb.rst

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access further features, you have to do this yourself:
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.. class:: Pdb(completekey='tab', stdin=None, stdout=None, skip=None, \
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nosigint=False, readrc=True, mode=None, backend=None)
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nosigint=False, readrc=True, mode=None, backend=None, colorize=False)
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:class:`Pdb` is the debugger class.
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is passed, the default backend will be used. See :func:`set_default_backend`.
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The *colorize* argument, if set to ``True``, will enable colorized output in the
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debugger, if color is supported. This will highlight source code displayed in pdb.
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.. versionadded:: 3.14
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.. versionchanged:: 3.14
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Inline breakpoints like :func:`breakpoint` or :func:`pdb.set_trace` will
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‎Doc/library/subprocess.rst

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Notes
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-----
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.. _subprocess-timeout-behavior:
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Timeout Behavior
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^^^^^^^^^^^^^^^^
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When using the ``timeout`` parameter in functions like :func:`run`,
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:meth:`Popen.wait`, or :meth:`Popen.communicate`,
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users should be aware of the following behaviors:
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1. **Process Creation Delay**: The initial process creation itself cannot be interrupted
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on many platform APIs. This means that even when specifying a timeout, you are not
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guaranteed to see a timeout exception until at least after however long process
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creation takes.
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2. **Extremely Small Timeout Values**: Setting very small timeout values (such as a few
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milliseconds) may result in almost immediate :exc:`TimeoutExpired` exceptions because
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process creation and system scheduling inherently require time.
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.. _converting-argument-sequence:
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Converting an argument sequence to a string on Windows

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