PEP: 311 Title: Simplified Global Interpreter Lock Acquisition for
Extensions Version: $Revision$ Last-Modified: $Date$ Author: Mark
Hammond <mhammond@skippinet.com.au> Status: Final Type: Standards Track
Content-Type: text/x-rst Created: 05-Feb-2003 Python-Version: 2.3
Post-History: 05-Feb-2003, 14-Feb-2003, 19-Apr-2003

Abstract

This PEP proposes a simplified API for access to the Global Interpreter
Lock (GIL) for Python extension modules. Specifically, it provides a
solution for authors of complex multi-threaded extensions, where the
current state of Python (i.e., the state of the GIL is unknown.

This PEP proposes a new API, for platforms built with threading support,
to manage the Python thread state. An implementation strategy is
proposed, along with an initial, platform independent implementation.

Rationale

The current Python interpreter state API is suitable for simple,
single-threaded extensions, but quickly becomes incredibly complex for
non-trivial, multi-threaded extensions.

Currently Python provides two mechanisms for dealing with the GIL:

-   Py_BEGIN_ALLOW_THREADS and Py_END_ALLOW_THREADS macros. These macros
    are provided primarily to allow a simple Python extension that
    already owns the GIL to temporarily release it while making an
    "external" (ie, non-Python), generally expensive, call. Any existing
    Python threads that are blocked waiting for the GIL are then free to
    run. While this is fine for extensions making calls from Python into
    the outside world, it is no help for extensions that need to make
    calls into Python when the thread state is unknown.
-   PyThreadState and PyInterpreterState APIs. These API functions allow
    an extension/embedded application to acquire the GIL, but suffer
    from a serious boot-strapping problem - they require you to know the
    state of the Python interpreter and of the GIL before they can be
    used. One particular problem is for extension authors that need to
    deal with threads never before seen by Python, but need to call
    Python from this thread. It is very difficult, delicate and error
    prone to author an extension where these "new" threads always know
    the exact state of the GIL, and therefore can reliably interact with
    this API.

For these reasons, the question of how such extensions should interact
with Python is quickly becoming a FAQ. The main impetus for this PEP, a
thread on python-dev[1], immediately identified the following projects
with this exact issue:

-   The win32all extensions
-   Boost
-   ctypes
-   Python-GTK bindings
-   Uno
-   PyObjC
-   Mac toolbox
-   PyXPCOM

Currently, there is no reasonable, portable solution to this problem,
forcing each extension author to implement their own hand-rolled
version. Further, the problem is complex, meaning many implementations
are likely to be incorrect, leading to a variety of problems that will
often manifest simply as "Python has hung".

While the biggest problem in the existing thread-state API is the lack
of the ability to query the current state of the lock, it is felt that a
more complete, simplified solution should be offered to extension
authors. Such a solution should encourage authors to provide error-free,
complex extension modules that take full advantage of Python's threading
mechanisms.

Limitations and Exclusions

This proposal identifies a solution for extension authors with complex
multi-threaded requirements, but that only require a single
"PyInterpreterState". There is no attempt to cater for extensions that
require multiple interpreter states. At the time of writing, no
extension has been identified that requires multiple
PyInterpreterStates, and indeed it is not clear if that facility works
correctly in Python itself.

This API will not perform automatic initialization of Python, or
initialize Python for multi-threaded operation. Extension authors must
continue to call Py_Initialize(), and for multi-threaded applications,
PyEval_InitThreads(). The reason for this is that the first thread to
call PyEval_InitThreads() is nominated as the "main thread" by Python,
and so forcing the extension author to specify the main thread (by
requiring them to make this first call) removes ambiguity. As
Py_Initialize() must be called before PyEval_InitThreads(), and as both
of these functions currently support being called multiple times, the
burden this places on extension authors is considered reasonable.

It is intended that this API be all that is necessary to acquire the
Python GIL. Apart from the existing, standard Py_BEGIN_ALLOW_THREADS and
Py_END_ALLOW_THREADS macros, it is assumed that no additional thread
state API functions will be used by the extension. Extensions with such
complicated requirements are free to continue to use the existing thread
state API.

Proposal

This proposal recommends a new API be added to Python to simplify the
management of the GIL. This API will be available on all platforms built
with WITH_THREAD defined.

The intent is that assuming Python has correctly been initialized, an
extension author be able to use a small, well-defined "prologue dance",
at any time and on any thread, which will ensure Python is ready to be
used on that thread. After the extension has finished with Python, it
must also perform an "epilogue dance" to release any resources
previously acquired. Ideally, these dances can be expressed in a single
line.

Specifically, the following new APIs are proposed:

    /* Ensure that the current thread is ready to call the Python
       C API, regardless of the current state of Python, or of its
       thread lock.  This may be called as many times as desired
       by a thread so long as each call is matched with a call to
       PyGILState_Release().  In general, other thread-state APIs may
       be used between _Ensure() and _Release() calls, so long as the
       thread-state is restored to its previous state before the Release().
       For example, normal use of the Py_BEGIN_ALLOW_THREADS/
       Py_END_ALLOW_THREADS macros are acceptable.

       The return value is an opaque "handle" to the thread state when
       PyGILState_Acquire() was called, and must be passed to
       PyGILState_Release() to ensure Python is left in the same state. Even
       though recursive calls are allowed, these handles can *not* be
       shared - each unique call to PyGILState_Ensure must save the handle
       for its call to PyGILState_Release.

       When the function returns, the current thread will hold the GIL.

       Failure is a fatal error.
    */
    PyAPI_FUNC(PyGILState_STATE) PyGILState_Ensure(void);

    /* Release any resources previously acquired.  After this call, Python's
       state will be the same as it was prior to the corresponding
       PyGILState_Acquire call (but generally this state will be unknown to
       the caller, hence the use of the GILState API.)

       Every call to PyGILState_Ensure must be matched by a call to
       PyGILState_Release on the same thread.
    */
    PyAPI_FUNC(void) PyGILState_Release(PyGILState_STATE);

Common usage will be:

    void SomeCFunction(void)
    {
        /* ensure we hold the lock */
        PyGILState_STATE state = PyGILState_Ensure();
        /* Use the Python API */
        ...
        /* Restore the state of Python */
        PyGILState_Release(state);
    }

Design and Implementation

The general operation of PyGILState_Ensure() will be:

-   assert Python is initialized.
-   Get a PyThreadState for the current thread, creating and saving if
    necessary.
-   remember the current state of the lock (owned/not owned)
-   If the current state does not own the GIL, acquire it.
-   Increment a counter for how many calls to PyGILState_Ensure have
    been made on the current thread.
-   return

The general operation of PyGILState_Release() will be:

-   assert our thread currently holds the lock.
-   If old state indicates lock was previously unlocked, release GIL.
-   Decrement the PyGILState_Ensure counter for the thread.
-   If counter == 0:
    -   release and delete the PyThreadState.
    -   forget the ThreadState as being owned by the thread.
-   return

It is assumed that it is an error if two discrete PyThreadStates are
used for a single thread. Comments in pystate.h ("State unique per
thread") support this view, although it is never directly stated. Thus,
this will require some implementation of Thread Local Storage.
Fortunately, a platform independent implementation of Thread Local
Storage already exists in the Python source tree, in the SGI threading
port. This code will be integrated into the platform independent Python
core, but in such a way that platforms can provide a more optimal
implementation if desired.

Implementation

An implementation of this proposal can be found at
https://bugs.python.org/issue684256

References

Copyright

This document has been placed in the public domain.

[1] David Abrahams, Extension modules, Threading, and the GIL
https://mail.python.org/pipermail/python-dev/2002-December/031424.html