C API Extension Support for Free Threading
******************************************

Starting with the 3.13 release, CPython has experimental support for
running with the *global interpreter lock* (GIL) disabled in a
configuration called *free threading*.  This document describes how to
adapt C API extensions to support free threading.


Identifying the Free-Threaded Build in C
========================================

The CPython C API exposes the "Py_GIL_DISABLED" macro: in the free-
threaded build it's defined to "1", and in the regular build it's not
defined. You can use it to enable code that only runs under the free-
threaded build:

   #ifdef Py_GIL_DISABLED
   /* code that only runs in the free-threaded build */
   #endif


Module Initialization
=====================

Extension modules need to explicitly indicate that they support
running with the GIL disabled; otherwise importing the extension will
raise a warning and enable the GIL at runtime.

There are two ways to indicate that an extension module supports
running with the GIL disabled depending on whether the extension uses
multi-phase or single-phase initialization.


Multi-Phase Initialization
--------------------------

Extensions that use multi-phase initialization (i.e.,
"PyModuleDef_Init()") should add a "Py_mod_gil" slot in the module
definition.  If your extension supports older versions of CPython, you
should guard the slot with a "PY_VERSION_HEX" check.

   static struct PyModuleDef_Slot module_slots[] = {
       ...
   #if PY_VERSION_HEX >= 0x030D0000
       {Py_mod_gil, Py_MOD_GIL_NOT_USED},
   #endif
       {0, NULL}
   };

   static struct PyModuleDef moduledef = {
       PyModuleDef_HEAD_INIT,
       .m_slots = module_slots,
       ...
   };


Single-Phase Initialization
---------------------------

Extensions that use single-phase initialization (i.e.,
"PyModule_Create()") should call "PyUnstable_Module_SetGIL()" to
indicate that they support running with the GIL disabled.  The
function is only defined in the free-threaded build, so you should
guard the call with "#ifdef Py_GIL_DISABLED" to avoid compilation
errors in the regular build.

   static struct PyModuleDef moduledef = {
       PyModuleDef_HEAD_INIT,
       ...
   };

   PyMODINIT_FUNC
   PyInit_mymodule(void)
   {
       PyObject *m = PyModule_Create(&moduledef);
       if (m == NULL) {
           return NULL;
       }
   #ifdef Py_GIL_DISABLED
       PyUnstable_Module_SetGIL(m, Py_MOD_GIL_NOT_USED);
   #endif
       return m;
   }


General API Guidelines
======================

Most of the C API is thread-safe, but there are some exceptions.

* **Struct Fields**: Accessing fields in Python C API objects or
  structs directly is not thread-safe if the field may be concurrently
  modified.

* **Macros**: Accessor macros like "PyList_GET_ITEM" and
  "PyList_SET_ITEM" do not perform any error checking or locking.
  These macros are not thread-safe if the container object may be
  modified concurrently.

* **Borrowed References**: C API functions that return *borrowed
  references* may not be thread-safe if the containing object is
  modified concurrently.  See the section on borrowed references for
  more information.


Container Thread Safety
-----------------------

Containers like "PyListObject", "PyDictObject", and "PySetObject"
perform internal locking in the free-threaded build.  For example, the
"PyList_Append()" will lock the list before appending an item.


"PyDict_Next"
~~~~~~~~~~~~~

A notable exception is "PyDict_Next()", which does not lock the
dictionary.  You should use "Py_BEGIN_CRITICAL_SECTION" to protect the
dictionary while iterating over it if the dictionary may be
concurrently modified:

   Py_BEGIN_CRITICAL_SECTION(dict);
   PyObject *key, *value;
   Py_ssize_t pos = 0;
   while (PyDict_Next(dict, &pos, &key, &value)) {
       ...
   }
   Py_END_CRITICAL_SECTION();


Borrowed References
===================

Some C API functions return *borrowed references*. These APIs are not
thread-safe if the containing object is modified concurrently.  For
example, it's not safe to use "PyList_GetItem()" if the list may be
modified concurrently.

The following table lists some borrowed reference APIs and their
replacements that return *strong references*.

+-------------------------------------+-------------------------------------+
| Borrowed reference API              | Strong reference API                |
|=====================================|=====================================|
| "PyList_GetItem()"                  | "PyList_GetItemRef()"               |
+-------------------------------------+-------------------------------------+
| "PyDict_GetItem()"                  | "PyDict_GetItemRef()"               |
+-------------------------------------+-------------------------------------+
| "PyDict_GetItemWithError()"         | "PyDict_GetItemRef()"               |
+-------------------------------------+-------------------------------------+
| "PyDict_GetItemString()"            | "PyDict_GetItemStringRef()"         |
+-------------------------------------+-------------------------------------+
| "PyDict_SetDefault()"               | "PyDict_SetDefaultRef()"            |
+-------------------------------------+-------------------------------------+
| "PyDict_Next()"                     | none (see PyDict_Next)              |
+-------------------------------------+-------------------------------------+
| "PyWeakref_GetObject()"             | "PyWeakref_GetRef()"                |
+-------------------------------------+-------------------------------------+
| "PyWeakref_GET_OBJECT()"            | "PyWeakref_GetRef()"                |
+-------------------------------------+-------------------------------------+
| "PyImport_AddModule()"              | "PyImport_AddModuleRef()"           |
+-------------------------------------+-------------------------------------+

Not all APIs that return borrowed references are problematic.  For
example, "PyTuple_GetItem()" is safe because tuples are immutable.
Similarly, not all uses of the above APIs are problematic.  For
example, "PyDict_GetItem()" is often used for parsing keyword argument
dictionaries in function calls; those keyword argument dictionaries
are effectively private (not accessible by other threads), so using
borrowed references in that context is safe.

Some of these functions were added in Python 3.13.  You can use the
pythoncapi-compat package to provide implementations of these
functions for older Python versions.


Memory Allocation APIs
======================

Python's memory management C API provides functions in three different
allocation domains: "raw", "mem", and "object". For thread-safety, the
free-threaded build requires that only Python objects are allocated
using the object domain, and that all Python object are allocated
using that domain.  This differs from the prior Python versions, where
this was only a best practice and not a hard requirement.

Not:

  Search for uses of "PyObject_Malloc()" in your extension and check
  that the allocated memory is used for Python objects. Use
  "PyMem_Malloc()" to allocate buffers instead of "PyObject_Malloc()".


Thread State and GIL APIs
=========================

Python provides a set of functions and macros to manage thread state
and the GIL, such as:

* "PyGILState_Ensure()" and "PyGILState_Release()"

* "PyEval_SaveThread()" and "PyEval_RestoreThread()"

* "Py_BEGIN_ALLOW_THREADS" and "Py_END_ALLOW_THREADS"

These functions should still be used in the free-threaded build to
manage thread state even when the *GIL* is disabled.  For example, if
you create a thread outside of Python, you must call
"PyGILState_Ensure()" before calling into the Python API to ensure
that the thread has a valid Python thread state.

You should continue to call "PyEval_SaveThread()" or
"Py_BEGIN_ALLOW_THREADS" around blocking operations, such as I/O or
lock acquisitions, to allow other threads to run the *cyclic garbage
collector*.


Protecting Internal Extension State
===================================

Your extension may have internal state that was previously protected
by the GIL.  You may need to add locking to protect this state.  The
approach will depend on your extension, but some common patterns
include:

* **Caches**: global caches are a common source of shared state.
  Consider using a lock to protect the cache or disabling it in the
  free-threaded build if the cache is not critical for performance.

* **Global State**: global state may need to be protected by a lock or
  moved to thread local storage. C11 and C++11 provide the
  "thread_local" or "_Thread_local" for thread-local storage.


Building Extensions for the Free-Threaded Build
===============================================

C API extensions need to be built specifically for the free-threaded
build. The wheels, shared libraries, and binaries are indicated by a
"t" suffix.

* pypa/manylinux supports the free-threaded build, with the "t"
  suffix, such as "python3.13t".

* pypa/cibuildwheel supports the free-threaded build if you set
  CIBW_FREE_THREADED_SUPPORT.


Limited C API and Stable ABI
----------------------------

The free-threaded build does not currently support the Limited C API
or the stable ABI.  If you use setuptools to build your extension and
currently set "py_limited_api=True" you can use "py_limited_api=not
sysconfig.get_config_var("Py_GIL_DISABLED")" to opt out of the limited
API when building with the free-threaded build.

Not:

  You will need to build separate wheels specifically for the free-
  threaded build.  If you currently use the stable ABI, you can
  continue to build a single wheel for multiple non-free-threaded
  Python versions.


Windows
-------

Due to a limitation of the official Windows installer, you will need
to manually define "Py_GIL_DISABLED=1" when building extensions from
source.

Ayrıca bakınız:

  Porting Extension Modules to Support Free-Threading: A community-
  maintained porting guide for extension authors.
