..highlight::c

.. _freethreading-extensions-howto:

C API Extension Support for Free Threading

Starting with the 3.13 release, CPython has experimental support for running

with the:term:`global interpreter lock` (GIL) disabled in a configuration

called:term:`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::

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.,

:c:func:`PyModuleDef_Init`) should add a:c:data:`Py_mod_gil` slot in the

module definition. If your extension supports older versions of CPython,

you should guard the slot with a:c:data:`PY_VERSION_HEX` check.

::

Single-Phase Initialization

Extensions that use single-phase initialization (i.e.,

:c:func:`PyModule_Create`) should call:c:func:`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.

::

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:c:macro:`PyList_GET_ITEM` and

:c:macro:`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

:term:`borrowed references <borrowed reference>` may not be thread-safe if

the containing object is modified concurrently. See the section on

:ref:`borrowed references<borrowed-references>` for more information.

Container Thread Safety

Containers like:c:struct:`PyListObject`,

:c:struct:`PyDictObject`, and:c:struct:`PySetObject` perform internal locking

in the free-threaded build. For example, the:c:func:`PyList_Append` will

lock the list before appending an item.

Borrowed References

.. _borrowed-references:

Some C API functions return:term:`borrowed references <borrowed reference>`.

These APIs are not thread-safe if the containing object is modified

concurrently. For example, it's not safe to use:c:func:`PyList_GetItem`

if the list may be modified concurrently.

The following table lists some borrowed reference APIs and their replacements

that return:term:`strong references <strong reference>`.

| Borrowed reference API| Strong reference API|

|:c:func:`PyList_GetItem`|:c:func:`PyList_GetItemRef`|

|:c:func:`PyDict_GetItem`|:c:func:`PyDict_GetItemRef`|

|:c:func:`PyDict_GetItemWithError`|:c:func:`PyDict_GetItemRef`|

|:c:func:`PyDict_GetItemString`|:c:func:`PyDict_GetItemStringRef`|

|:c:func:`PyDict_SetDefault`|:c:func:`PyDict_SetDefaultRef`|

|:c:func:`PyDict_Next`| no direct replacement|

|:c:func:`PyWeakref_GetObject`|:c:func:`PyWeakref_GetRef`|

|:c:func:`PyWeakref_GET_OBJECT`|:c:func:`PyWeakref_GetRef`|

|:c:func:`PyImport_AddModule`|:c:func:`PyImport_AddModuleRef`|

Not all APIs that return borrowed references are problematic. For

example,:c:func:`PyTuple_GetItem` is safe because tuples are immutable.

Similarly, not all uses of the above APIs are problematic. For example,

:c:func:`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<https://github.com/python/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

:ref:`allocation domains<allocator-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 differes from the prior Python versions,

where this was only a best practice and not a hard requirement.

..note::

Search for uses of:c:func:`PyObject_Malloc` in your

extension and check that the allocated memory is used for Python objects.

Use:c:func:`PyMem_Malloc` to allocate buffers instead of

:c:func:`PyObject_Malloc`.

Thread State and GIL APIs

Python provides a set of functions and macros to manage thread state and the

GIL, such as:

*:c:func:`PyGILState_Ensure` and:c:func:`PyGILState_Release`

*:c:func:`PyEval_SaveThread` and:c:func:`PyEval_RestoreThread`

*:c:macro:`Py_BEGIN_ALLOW_THREADS` and:c:macro:`Py_END_ALLOW_THREADS`

These functions should still be used in the free-threaded build to manage

thread state even when the:term:`GIL` is disabled. For example, if you

create a thread outside of Python, you must call:c:func:`PyGILState_Ensure`

before calling into the Python API to ensure that the thread has a valid

Python thread state.

You should continue to call:c:func:`PyEval_SaveThread` or

:c:macro:`Py_BEGIN_ALLOW_THREADS` around blocking operations, such as I/O or

lock acquisitions, to allow other threads to run the

:term:`cyclic garbage collector <garbage collection>`.

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<https://en.cppreference.com/w/c/language/storage_duration>`_.

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<https://github.com/pypa/manylinux>`_ supports the

free-threaded build, with the ``t`` suffix, such as ``python3.13t``.

* `pypa/cibuildwheel<https://github.com/pypa/cibuildwheel>`_ supports the

free-threaded build if you set

`CIBW_FREE_THREADED_SUPPORT<https://cibuildwheel.pypa.io/en/stable/options/#free-threaded-support>`_.

Limited C API and Stable ABI

The free-threaded build does not currently support the

:ref:`Limited C API<limited-c-api>` or the stable ABI. If you use

`setuptools<https://setuptools.pypa.io/en/latest/setuptools.html>`_ 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.

..note::

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.

General: