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.. _freethreading-python-howto: | ||||||||||
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Python experimental support for free threading | ||||||||||
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Starting with the 3.13 release, CPython has experimental support for a build of Python | ||||||||||
called :term:`free threading` where the :term:`global interpreter lock` (GIL) is disabled. This document describes the implications of | ||||||||||
free threading for Python code. See :ref:`freethreading-extensions-howto` for | ||||||||||
information on how to write C extensions that support the free-threaded build. | ||||||||||
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I wonder if we could add a quick snapshot of the overall plan: if everything works out, eventually free threading will be the only build, etc. Also, maybe a statement about how most programmer won't need to be concerned with this, we're doing a lot to keep everyday Python programs behaving the same, etc. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I would perhaps add a note in the seealso block that refers to the PEP and adds 1 or 2 highlights:
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.. seealso:: | ||||||||||
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:pep:`703` – Making the Global Interpreter Lock Optional in CPython for an | ||||||||||
overall description of free-threaded Python. | ||||||||||
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Installation | ||||||||||
============ | ||||||||||
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Starting with Python 3.13, the official macOS and Windows installers | ||||||||||
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optionally support installing free-threaded Python binaries. The installers | ||||||||||
are available at https://www.python.org/downloads/. | ||||||||||
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.. seealso:: | ||||||||||
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`Installing a Free-Threaded Python | ||||||||||
<https://py-free-threading.github.io/installing_cpython/>`_: | ||||||||||
A community-maintained installation guide for installing free-threaded | ||||||||||
Python. | ||||||||||
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Identifying free-threaded Python | ||||||||||
================================ | ||||||||||
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The free-threaded build of CPython can optionally run with the global | ||||||||||
interpreter lock enabled, such as when :envvar:`PYTHON_GIL` is set to ``1``, | ||||||||||
or automatically when importing an extension module that requires the GIL. | ||||||||||
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The :func:`sys._is_gil_enabled` function will return ``False`` if the global | ||||||||||
interpreter lock is currently disabled. This is the recommended mechanism for | ||||||||||
decisions like whether to use multithreading or multiprocessing. | ||||||||||
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The ``sysconfig.get_config_var("Py_GIL_DISABLED")`` configuration variable can | ||||||||||
be used to determine whether the build supports free threading. If the variable | ||||||||||
is set to ``1``, then the build supports free threading. This is the recommended | ||||||||||
mechanism for decisions related to the build configuration. | ||||||||||
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Thread safety | ||||||||||
============= | ||||||||||
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The free-threaded build of CPython aims to provide similar thread-safety | ||||||||||
behavior at the Python level to the default GIL-enabled build. Built-in | ||||||||||
types like :class:`dict`, :class:`list`, and :class:`set` use internal locks | ||||||||||
to protect against concurrent modifications in ways that behave similarly to | ||||||||||
the GIL. However, Python has not historically guaranteed specific behavior for | ||||||||||
concurrent modifications to these built-in types, so this should be treated | ||||||||||
as a description of the current implementation, not a guarantee of current or future | ||||||||||
behavior. | ||||||||||
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.. note:: | ||||||||||
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It's recommended to use the :class:`threading.Lock` or other synchronization | ||||||||||
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primitives instead of relying on the internal locks of built-in types, when | ||||||||||
possible. | ||||||||||
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Known limitations | ||||||||||
================= | ||||||||||
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This section describes known limitations of the free-threaded CPython build. | ||||||||||
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Immortalization | ||||||||||
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The free-threaded build of the 3.13 release makes some objects :term:`immortal` | ||||||||||
in order to avoid reference count contention that would prevent efficient | ||||||||||
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in order to avoid reference count contention that would prevent efficient | |
which have reference counts that are never modified. Since the immortal object is guaranteed not to be | |
deallocated, efficient multi-threading scaling is possible by avoiding reference count contention between | |
threads. |
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I've reworked this a bit. Would you please take another look at it? As you wrote, immortalization means reference counts are not modified and objects are not guaranteed not to be deallocated. I wanted to get across that:
- Reference counts not being modified enables efficient multi-threaded scaling.
- Objects not being deallocated is a potential problem because some applications may leak memory. That's being addressed in 3.14. We don't expect this to be a problem for most applications, but it's something to watch out for if you run your application with refleak checks.
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"addressed" how? That makes it sound like immortal objects are a problem. Are they?
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It's probably worth noting somewhere in here that these objects (and immortalization itself) are implementation details, and very much subject to change.
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After reading about immortalization, I don't understand the implications for me as a Python programmer. Why do I care that they are now immortal? These all sound like things that would have never been deallocated anyway. Are there unusual circumstances that I should be considering?
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Hopefully most people won't care, but some programs create these sorts of things in a loop.
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Is the possible crashing of the interpreter expected to be addressed in 3.14?
As a consequence of iterators not being thread safe, some modules are not safe either (e g. json
, itertools
). Should this be mentioned somewhere?
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less of an impact. This overhead is expected to be reduced in Python | |
3.14. We are aiming for an overhead of 10% or less on the pyperformance | |
less of an impact. This overhead is expected to be reduced in Python | |
3.14 by implementing more efficient reference counting and garbage collection. We are aiming for an overhead of 10% or less on the pyperformance |
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We expect that the biggest source of improvement will be reenabling the specializing adaptive interpreter in 3.14. It's currently disabled in the 3.13 free-threaded build. Is that worth mentioning here?
I don't expect any big performance impact for reference counting and garbage collection changes in 3.14
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We seem to switch between "free threading" and "free-threaded" kind of randomly. I can't decide if this is OK or if we should choose one and stick with it.
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I think it's fine. We also say both "multithreaded" and "multithreading" depending on the context.