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‎Doc/c-api/arg.rst

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@@ -113,18 +113,14 @@ There are three ways strings and buffers can be converted to C:
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``z`` (:class:`str` or ``None``) [const char \*]
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Like ``s``, but the Python object may also be ``None``, in which case the C
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pointer is set to ``NULL``.
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It is the same as ``s?`` with the C pointer was initialized to ``NULL``.
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``z*`` (:class:`str`, :term:`bytes-like object` or ``None``) [Py_buffer]
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Like ``s*``, but the Python object may also be ``None``, in which case the
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``buf`` member of the :c:type:`Py_buffer` structure is set to ``NULL``.
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It is the same as ``s*?`` with the ``buf`` member of the :c:type:`Py_buffer`
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structure was initialized to ``NULL``.
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``z#`` (:class:`str`, read-only :term:`bytes-like object` or ``None``) [const char \*, :c:type:`Py_ssize_t`]
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Like ``s#``, but the Python object may also be ``None``, in which case the C
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pointer is set to ``NULL``.
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It is the same as ``s#?`` with the C pointer was initialized to ``NULL``.
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``y`` (read-only :term:`bytes-like object`) [const char \*]
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This format converts a bytes-like object to a C pointer to a
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Non-tuple sequences are deprecated if *items* contains format units
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which store a borrowed buffer or a borrowed reference.
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``unit?`` (anything or ``None``) [*matching-variable(s)*]
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``?`` modifies the behavior of the preceding format unit.
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The C variable(s) corresponding to that parameter should be initialized
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to their default value --- when the argument is ``None``,
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:c:func:`PyArg_ParseTuple` does not touch the contents of the corresponding
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C variable(s).
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If the argument is not ``None``, it is parsed according to the specified
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format unit.
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.. versionadded:: 3.14
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A few other characters have a meaning in a format string. These may not occur
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inside nested parentheses. They are:
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‎Doc/c-api/init.rst

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@@ -2287,7 +2287,7 @@ The C-API provides a basic mutual exclusion lock.
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should not be used to make concurrency control decisions, as the lock
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state may change immediately after the check.
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.. versionadded:: next
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.. versionadded:: 3.14
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.. _python-critical-section-api:
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@@ -2372,7 +2372,7 @@ code triggered by the finalizer blocks and calls :c:func:`PyEval_SaveThread`.
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On the default build, this macro expands to ``{``.
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.. versionadded:: next
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.. versionadded:: 3.14
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.. c:macro:: Py_END_CRITICAL_SECTION()
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@@ -2418,7 +2418,7 @@ code triggered by the finalizer blocks and calls :c:func:`PyEval_SaveThread`.
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On the default build, this macro expands to ``{``.
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.. versionadded:: next
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.. versionadded:: 3.14
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.. c:macro:: Py_END_CRITICAL_SECTION2()
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‎Doc/c-api/perfmaps.rst

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Support for Perf Maps
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----------------------
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On supported platforms (as of this writing, only Linux), the runtime can take
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On supported platforms (Linux and macOS), the runtime can take
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advantage of *perf map files* to make Python functions visible to an external
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profiling tool (such as `perf <https://perf.wiki.kernel.org/index.php/Main_Page>`_).
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A running process may create a file in the ``/tmp`` directory, which contains entries
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that can map a section of executable code to a name. This interface is described in the
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profiling tool (such as `perf <https://perf.wiki.kernel.org/index.php/Main_Page>`_ or
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`samply <https://github.com/mstange/samply/>`_). A running process may create a
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file in the ``/tmp`` directory, which contains entries that can map a section
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of executable code to a name. This interface is described in the
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`documentation of the Linux Perf tool <https://git.kernel.org/pub/scm/linux/
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kernel/git/torvalds/linux.git/tree/tools/perf/Documentation/jit-interface.txt>`_.
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‎Doc/extending/extending.rst

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@@ -214,7 +214,7 @@ and initialize it by calling :c:func:`PyErr_NewException` in the module's
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SpamError = PyErr_NewException("spam.error", NULL, NULL);
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Since :c:data:`!SpamError` is a global variable, it will be overwitten every time
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Since :c:data:`!SpamError` is a global variable, it will be overwritten every time
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the module is reinitialized, when the :c:data:`Py_mod_exec` function is called.
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For now, let's avoid the issue: we will block repeated initialization by raising an

‎Doc/glossary.rst

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core and with user code.
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f-string
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String literals prefixed with ``'f'`` or ``'F'`` are commonly called
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String literals prefixed with ``f`` or ``F`` are commonly called
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"f-strings" which is short for
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:ref:`formatted string literals <f-strings>`. See also :pep:`498`.
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See also :term:`borrowed reference`.
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t-string
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String literals prefixed with ``t`` or ``T`` are commonly called
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"t-strings" which is short for
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:ref:`template string literals <t-strings>`.
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text encoding
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A string in Python is a sequence of Unicode code points (in range
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``U+0000``--``U+10FFFF``). To store or transfer a string, it needs to be

‎Doc/howto/free-threading-extensions.rst

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+===================================+===================================+
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| :c:func:`PyList_GetItem` | :c:func:`PyList_GetItemRef` |
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+-----------------------------------+-----------------------------------+
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| :c:func:`PyList_GET_ITEM` | :c:func:`PyList_GetItemRef` |
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+-----------------------------------+-----------------------------------+
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| :c:func:`PyDict_GetItem` | :c:func:`PyDict_GetItemRef` |
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+-----------------------------------+-----------------------------------+
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| :c:func:`PyDict_GetItemWithError` | :c:func:`PyDict_GetItemRef` |

‎Doc/howto/perf_profiling.rst

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.. _perf_profiling:
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==============================================
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Python support for the Linux ``perf`` profiler
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==============================================
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========================================================
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Python support for the ``perf map`` compatible profilers
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========================================================
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:author: Pablo Galindo
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`The Linux perf profiler <https://perf.wiki.kernel.org>`_
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is a very powerful tool that allows you to profile and obtain
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information about the performance of your application.
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``perf`` also has a very vibrant ecosystem of tools
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that aid with the analysis of the data that it produces.
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`The Linux perf profiler <https://perf.wiki.kernel.org>`_ and
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`samply <https://github.com/mstange/samply>`_ are powerful tools that allow you to
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profile and obtain information about the performance of your application.
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Both tools have vibrant ecosystems that aid with the analysis of the data they produce.
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The main problem with using the ``perf`` profiler with Python applications is that
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``perf`` only gets information about native symbols, that is, the names of
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The main problem with using these profilers with Python applications is that
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they only get information about native symbols, that is, the names of
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functions and procedures written in C. This means that the names and file names
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of Python functions in your code will not appear in the output of ``perf``.
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of Python functions in your code will not appear in the profiler output.
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Since Python 3.12, the interpreter can run in a special mode that allows Python
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functions to appear in the output of the ``perf`` profiler. When this mode is
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functions to appear in the output of compatible profilers. When this mode is
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enabled, the interpreter will interpose a small piece of code compiled on the
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fly before the execution of every Python function and it will teach ``perf`` the
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fly before the execution of every Python function and it will teach the profiler the
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relationship between this piece of code and the associated Python function using
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:doc:`perf map files <../c-api/perfmaps>`.
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.. note::
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Support for the ``perf`` profiler is currently only available for Linux on
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select architectures. Check the output of the ``configure`` build step or
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Support for profiling is available on Linux and macOS on select architectures.
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Perf is available on Linux, while samply can be used on both Linux and macOS.
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samply support on macOS is available starting from Python 3.15.
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Check the output of the ``configure`` build step or
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check the output of ``python -m sysconfig | grep HAVE_PERF_TRAMPOLINE``
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to see if your system is supported.
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Using the samply profiler
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-------------------------
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samply is a modern profiler that can be used as an alternative to perf.
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It uses the same perf map files that Python generates, making it compatible
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with Python's profiling support. samply is particularly useful on macOS
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where perf is not available.
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To use samply with Python, first install it following the instructions at
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https://github.com/mstange/samply, then run::
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$ samply record PYTHONPERFSUPPORT=1 python my_script.py
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This will open a web interface where you can analyze the profiling data
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interactively. The advantage of samply is that it provides a modern
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web-based interface for analyzing profiling data and works on both Linux
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and macOS.
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On macOS, samply support requires Python 3.15 or later. Also on macOS, samply
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can't profile signed Python executables due to restrictions by macOS. You can
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profile with Python binaries that you've compiled yourself, or which are
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unsigned or locally-signed (such as anything installed by Homebrew). In
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order to attach to running processes on macOS, run ``samply setup`` once (and
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every time samply is updated) to self-sign the samply binary.
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How to enable ``perf`` profiling support
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----------------------------------------
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‎Doc/library/annotationlib.rst

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>>> def f(x: (1).__class__.__base__.__subclasses__()[-1].__init__.__builtins__["print"]("Hello world")): pass
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...
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>>> annotationlib.get_annotations(f, format=annotationlib.Format.SOURCE)
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>>> annotationlib.get_annotations(f, format=annotationlib.Format.STRING)
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Hello world
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{'x': 'None'}
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‎Doc/library/array.rst

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+-----------+--------------------+-------------------+-----------------------+-------+
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| ``'u'`` | wchar_t | Unicode character | 2 | \(1) |
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+-----------+--------------------+-------------------+-----------------------+-------+
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| ``'w'`` | Py_UCS4 | Unicode character | 4 | |
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| ``'w'`` | Py_UCS4 | Unicode character | 4 | \(2) |
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+-----------+--------------------+-------------------+-----------------------+-------+
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| ``'h'`` | signed short | int | 2 | |
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+-----------+--------------------+-------------------+-----------------------+-------+
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.. deprecated-removed:: 3.3 3.16
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Please migrate to ``'w'`` typecode.
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(2)
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.. versionadded:: 3.13
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The actual representation of values is determined by the machine architecture
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(strictly speaking, by the C implementation). The actual size can be accessed

‎Doc/library/ast.rst

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* ``conversion`` is an integer:
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* -1: no formatting
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* 115: ``!s`` string formatting
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* 114: ``!r`` repr formatting
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* 97: ``!a`` ascii formatting
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* 115 (``ord('s')``): ``!s`` string formatting
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* 114 (``ord('r')``): ``!r`` repr formatting
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* 97 (``ord('a')``): ``!a`` ASCII formatting
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* ``format_spec`` is a :class:`JoinedStr` node representing the formatting
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of the value, or ``None`` if no format was specified. Both
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Constant(value='.3')]))]))
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.. class:: TemplateStr(values)
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A t-string, comprising a series of :class:`Interpolation` and :class:`Constant`
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nodes.
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.. doctest::
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>>> print(ast.dump(ast.parse('t"{name} finished {place:ordinal}"', mode='eval'), indent=4))
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Expression(
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body=TemplateStr(
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values=[
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Interpolation(
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value=Name(id='name'),
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str='name',
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conversion=-1),
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Constant(value=' finished '),
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Interpolation(
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value=Name(id='place'),
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str='place',
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conversion=-1,
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format_spec=JoinedStr(
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values=[
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Constant(value='ordinal')]))]))
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.. versionadded:: 3.14
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.. class:: Interpolation(value, str, conversion, format_spec)
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Node representing a single interpolation field in a t-string.
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* ``value`` is any expression node (such as a literal, a variable, or a
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function call).
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* ``str`` is a constant containing the text of the interpolation expression.
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* ``conversion`` is an integer:
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* -1: no conversion
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* 115: ``!s`` string conversion
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* 114: ``!r`` repr conversion
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* 97: ``!a`` ascii conversion
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* ``format_spec`` is a :class:`JoinedStr` node representing the formatting
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of the value, or ``None`` if no format was specified. Both
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``conversion`` and ``format_spec`` can be set at the same time.
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.. versionadded:: 3.14
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.. class:: List(elts, ctx)
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Tuple(elts, ctx)
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