Initialization, Finalization, and Threads — Python v3.1.3 documentation (original) (raw)

Thread State and the Global Interpreter Lock¶

The Python interpreter is not fully thread-safe. In order to support multi-threaded Python programs, there’s a global lock, called the global interpreter lock or GIL, that must be held by the current thread before it can safely access Python objects. Without the lock, even the simplest operations could cause problems in a multi-threaded program: for example, when two threads simultaneously increment the reference count of the same object, the reference count could end up being incremented only once instead of twice.

Therefore, the rule exists that only the thread that has acquired the global interpreter lock may operate on Python objects or call Python/C API functions. In order to support multi-threaded Python programs, the interpreter regularly releases and reacquires the lock — by default, every 100 bytecode instructions (this can be changed with sys.setcheckinterval()). The lock is also released and reacquired around potentially blocking I/O operations like reading or writing a file, so that other threads can run while the thread that requests the I/O is waiting for the I/O operation to complete.

The Python interpreter needs to keep some bookkeeping information separate per thread — for this it uses a data structure called PyThreadState. There’s one global variable, however: the pointer to the currentPyThreadState structure. Before the addition of thread-local storage (TLS) the current thread state had to be manipulated explicitly.

This is easy enough in most cases. Most code manipulating the global interpreter lock has the following simple structure:

Save the thread state in a local variable. Release the global interpreter lock. ...Do some blocking I/O operation... Reacquire the global interpreter lock. Restore the thread state from the local variable.

This is so common that a pair of macros exists to simplify it:

Py_BEGIN_ALLOW_THREADS ...Do some blocking I/O operation... Py_END_ALLOW_THREADS

The Py_BEGIN_ALLOW_THREADS macro opens a new block and declares a hidden local variable; the Py_END_ALLOW_THREADS macro closes the block. Another advantage of using these two macros is that when Python is compiled without thread support, they are defined empty, thus saving the thread state and GIL manipulations.

When thread support is enabled, the block above expands to the following code:

PyThreadState *_save;

_save = PyEval_SaveThread(); ...Do some blocking I/O operation... PyEval_RestoreThread(_save);

Using even lower level primitives, we can get roughly the same effect as follows:

PyThreadState *_save;

_save = PyThreadState_Swap(NULL); PyEval_ReleaseLock(); ...Do some blocking I/O operation... PyEval_AcquireLock(); PyThreadState_Swap(_save);

There are some subtle differences; in particular, PyEval_RestoreThread()saves and restores the value of the global variable errno, since the lock manipulation does not guarantee that errno is left alone. Also, when thread support is disabled, PyEval_SaveThread() andPyEval_RestoreThread() don’t manipulate the GIL; in this case,PyEval_ReleaseLock() and PyEval_AcquireLock() are not available. This is done so that dynamically loaded extensions compiled with thread support enabled can be loaded by an interpreter that was compiled with disabled thread support.

The global interpreter lock is used to protect the pointer to the current thread state. When releasing the lock and saving the thread state, the current thread state pointer must be retrieved before the lock is released (since another thread could immediately acquire the lock and store its own thread state in the global variable). Conversely, when acquiring the lock and restoring the thread state, the lock must be acquired before storing the thread state pointer.

It is important to note that when threads are created from C, they don’t have the global interpreter lock, nor is there a thread state data structure for them. Such threads must bootstrap themselves into existence, by first creating a thread state data structure, then acquiring the lock, and finally storing their thread state pointer, before they can start using the Python/C API. When they are done, they should reset the thread state pointer, release the lock, and finally free their thread state data structure.

Threads can take advantage of the PyGILState_*() functions to do all of the above automatically. The typical idiom for calling into Python from a C thread is now:

PyGILState_STATE gstate; gstate = PyGILState_Ensure();

/* Perform Python actions here. / result = CallSomeFunction(); / evaluate result */

/* Release the thread. No Python API allowed beyond this point. */ PyGILState_Release(gstate);

Note that the PyGILState_*() functions assume there is only one global interpreter (created automatically by Py_Initialize()). Python still supports the creation of additional interpreters (usingPy_NewInterpreter()), but mixing multiple interpreters and thePyGILState_*() API is unsupported.

Another important thing to note about threads is their behaviour in the face of the C fork() call. On most systems with fork(), after a process forks only the thread that issued the fork will exist. That also means any locks held by other threads will never be released. Python solves this for os.fork() by acquiring the locks it uses internally before the fork, and releasing them afterwards. In addition, it resets anyLock Objects in the child. When extending or embedding Python, there is no way to inform Python of additional (non-Python) locks that need to be acquired before or reset after a fork. OS facilities such asposix_atfork() would need to be used to accomplish the same thing. Additionally, when extending or embedding Python, calling fork()directly rather than through os.fork() (and returning to or calling into Python) may result in a deadlock by one of Python’s internal locks being held by a thread that is defunct after the fork.PyOS_AfterFork() tries to reset the necessary locks, but is not always able to.

PyInterpreterState¶

This data structure represents the state shared by a number of cooperating threads. Threads belonging to the same interpreter share their module administration and a few other internal items. There are no public members in this structure.

Threads belonging to different interpreters initially share nothing, except process state like available memory, open file descriptors and such. The global interpreter lock is also shared by all threads, regardless of to which interpreter they belong.

PyThreadState¶

This data structure represents the state of a single thread. The only public data member is PyInterpreterState *interp, which points to this thread’s interpreter state.

void PyEval_InitThreads()¶

Initialize and acquire the global interpreter lock. It should be called in the main thread before creating a second thread or engaging in any other thread operations such as PyEval_ReleaseLock() orPyEval_ReleaseThread(tstate). It is not needed before callingPyEval_SaveThread() or PyEval_RestoreThread().

This is a no-op when called for a second time. It is safe to call this function before calling Py_Initialize().

When only the main thread exists, no GIL operations are needed. This is a common situation (most Python programs do not use threads), and the lock operations slow the interpreter down a bit. Therefore, the lock is not created initially. This situation is equivalent to having acquired the lock: when there is only a single thread, all object accesses are safe. Therefore, when this function initializes the global interpreter lock, it also acquires it. Before the Python _thread module creates a new thread, knowing that either it has the lock or the lock hasn’t been created yet, it callsPyEval_InitThreads(). When this call returns, it is guaranteed that the lock has been created and that the calling thread has acquired it.

It is not safe to call this function when it is unknown which thread (if any) currently has the global interpreter lock.

This function is not available when thread support is disabled at compile time.

int PyEval_ThreadsInitialized()¶

Returns a non-zero value if PyEval_InitThreads() has been called. This function can be called without holding the GIL, and therefore can be used to avoid calls to the locking API when running single-threaded. This function is not available when thread support is disabled at compile time.

void PyEval_AcquireLock()¶

Acquire the global interpreter lock. The lock must have been created earlier. If this thread already has the lock, a deadlock ensues. This function is not available when thread support is disabled at compile time.

void PyEval_ReleaseLock()¶

Release the global interpreter lock. The lock must have been created earlier. This function is not available when thread support is disabled at compile time.

void PyEval_AcquireThread(PyThreadState *tstate)¶

Acquire the global interpreter lock and set the current thread state to_tstate_, which should not be NULL. The lock must have been created earlier. If this thread already has the lock, deadlock ensues. This function is not available when thread support is disabled at compile time.

void PyEval_ReleaseThread(PyThreadState *tstate)¶

Reset the current thread state to NULL and release the global interpreter lock. The lock must have been created earlier and must be held by the current thread. The tstate argument, which must not be NULL, is only used to check that it represents the current thread state — if it isn’t, a fatal error is reported. This function is not available when thread support is disabled at compile time.

PyThreadState* PyEval_SaveThread()¶

Release the global interpreter lock (if it has been created and thread support is enabled) and reset the thread state to NULL, returning the previous thread state (which is not NULL). If the lock has been created, the current thread must have acquired it. (This function is available even when thread support is disabled at compile time.)

void PyEval_RestoreThread(PyThreadState *tstate)¶

Acquire the global interpreter lock (if it has been created and thread support is enabled) and set the thread state to tstate, which must not be_NULL_. If the lock has been created, the current thread must not have acquired it, otherwise deadlock ensues. (This function is available even when thread support is disabled at compile time.)

void PyEval_ReInitThreads()¶

This function is called from PyOS_AfterFork() to ensure that newly created child processes don’t hold locks referring to threads which are not running in the child process.

The following macros are normally used without a trailing semicolon; look for example usage in the Python source distribution.

Py_BEGIN_ALLOW_THREADS¶

This macro expands to { PyThreadState *_save; _save = PyEval_SaveThread();. Note that it contains an opening brace; it must be matched with a followingPy_END_ALLOW_THREADS macro. See above for further discussion of this macro. It is a no-op when thread support is disabled at compile time.

Py_END_ALLOW_THREADS¶

This macro expands to PyEval_RestoreThread(_save); }. Note that it contains a closing brace; it must be matched with an earlierPy_BEGIN_ALLOW_THREADS macro. See above for further discussion of this macro. It is a no-op when thread support is disabled at compile time.

Py_BLOCK_THREADS¶

This macro expands to PyEval_RestoreThread(_save);: it is equivalent toPy_END_ALLOW_THREADS without the closing brace. It is a no-op when thread support is disabled at compile time.

Py_UNBLOCK_THREADS¶

This macro expands to _save = PyEval_SaveThread();: it is equivalent toPy_BEGIN_ALLOW_THREADS without the opening brace and variable declaration. It is a no-op when thread support is disabled at compile time.

All of the following functions are only available when thread support is enabled at compile time, and must be called only when the global interpreter lock has been created.

PyInterpreterState* PyInterpreterState_New()¶

Create a new interpreter state object. The global interpreter lock need not be held, but may be held if it is necessary to serialize calls to this function.

void PyInterpreterState_Clear(PyInterpreterState *interp)¶

Reset all information in an interpreter state object. The global interpreter lock must be held.

void PyInterpreterState_Delete(PyInterpreterState *interp)¶

Destroy an interpreter state object. The global interpreter lock need not be held. The interpreter state must have been reset with a previous call toPyInterpreterState_Clear().

PyThreadState* PyThreadState_New(PyInterpreterState *interp)¶

Create a new thread state object belonging to the given interpreter object. The global interpreter lock need not be held, but may be held if it is necessary to serialize calls to this function.

void PyThreadState_Clear(PyThreadState *tstate)¶

Reset all information in a thread state object. The global interpreter lock must be held.

void PyThreadState_Delete(PyThreadState *tstate)¶

Destroy a thread state object. The global interpreter lock need not be held. The thread state must have been reset with a previous call toPyThreadState_Clear().

PyThreadState* PyThreadState_Get()¶

Return the current thread state. The global interpreter lock must be held. When the current thread state is NULL, this issues a fatal error (so that the caller needn’t check for NULL).

PyThreadState* PyThreadState_Swap(PyThreadState *tstate)¶

Swap the current thread state with the thread state given by the argument_tstate_, which may be NULL. The global interpreter lock must be held.

PyObject* PyThreadState_GetDict()¶

Return value: Borrowed reference.

Return a dictionary in which extensions can store thread-specific state information. Each extension should use a unique key to use to store state in the dictionary. It is okay to call this function when no current thread state is available. If this function returns NULL, no exception has been raised and the caller should assume no current thread state is available.

int PyThreadState_SetAsyncExc(long id, PyObject *exc)¶

Asynchronously raise an exception in a thread. The id argument is the thread id of the target thread; exc is the exception object to be raised. This function does not steal any references to exc. To prevent naive misuse, you must write your own C extension to call this. Must be called with the GIL held. Returns the number of thread states modified; this is normally one, but will be zero if the thread id isn’t found. If exc is NULL, the pending exception (if any) for the thread is cleared. This raises no exceptions.

PyGILState_STATE PyGILState_Ensure()¶

Ensure that the current thread is ready to call the Python C API regardless of the current state of Python, or of the global interpreter lock. This may be called as many times as desired by a thread as long as each call is matched with a call to PyGILState_Release(). In general, other thread-related APIs may be used between PyGILState_Ensure() andPyGILState_Release() calls as long as the thread state is restored to its previous state before the Release(). For example, normal usage of thePy_BEGIN_ALLOW_THREADS and Py_END_ALLOW_THREADS macros is acceptable.

The return value is an opaque “handle” to the thread state whenPyGILState_Ensure() was called, and must be passed toPyGILState_Release() to ensure Python is left in the same state. Even though recursive calls are allowed, these handles cannot 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.

void PyGILState_Release(PyGILState_STATE)¶

Release any resources previously acquired. After this call, Python’s state will be the same as it was prior to the corresponding PyGILState_Ensure() 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 toPyGILState_Release() on the same thread.

Asynchronous Notifications¶

A mechanism is provided to make asynchronous notifications to the main interpreter thread. These notifications take the form of a function pointer and a void argument.

Every check interval, when the global interpreter lock is released and reacquired, Python will also call any such provided functions. This can be used for example by asynchronous IO handlers. The notification can be scheduled from a worker thread and the actual call than made at the earliest convenience by the main thread where it has possession of the global interpreter lock and can perform any Python API calls.

void Py_AddPendingCall(int (*func)(void *, void *arg))¶

Post a notification to the Python main thread. If successful, func will be called with the argument arg at the earliest convenience. func will be called having the global interpreter lock held and can thus use the full Python API and can take any action such as setting object attributes to signal IO completion. It must return 0 on success, or -1 signalling an exception. The notification function won’t be interrupted to perform another asynchronous notification recursively, but it can still be interrupted to switch threads if the global interpreter lock is released, for example, if it calls back into Python code.

This function returns 0 on success in which case the notification has been scheduled. Otherwise, for example if the notification buffer is full, it returns -1 without setting any exception.

This function can be called on any thread, be it a Python thread or some other system thread. If it is a Python thread, it doesn’t matter if it holds the global interpreter lock or not.

New in version 3.1.

Profiling and Tracing¶

The Python interpreter provides some low-level support for attaching profiling and execution tracing facilities. These are used for profiling, debugging, and coverage analysis tools.

This C interface allows the profiling or tracing code to avoid the overhead of calling through Python-level callable objects, making a direct C function call instead. The essential attributes of the facility have not changed; the interface allows trace functions to be installed per-thread, and the basic events reported to the trace function are the same as had been reported to the Python-level trace functions in previous versions.

int (*Py_tracefunc)(PyObject *obj, PyFrameObject *frame, int what, PyObject *arg)¶

The type of the trace function registered using PyEval_SetProfile() andPyEval_SetTrace(). The first parameter is the object passed to the registration function as obj, frame is the frame object to which the event pertains, what is one of the constants PyTrace_CALL,PyTrace_EXCEPTION, PyTrace_LINE, PyTrace_RETURN,PyTrace_C_CALL, PyTrace_C_EXCEPTION, orPyTrace_C_RETURN, and arg depends on the value of what:

int PyTrace_CALL¶

The value of the what parameter to a Py_tracefunc function when a new call to a function or method is being reported, or a new entry into a generator. Note that the creation of the iterator for a generator function is not reported as there is no control transfer to the Python bytecode in the corresponding frame.

int PyTrace_EXCEPTION¶

The value of the what parameter to a Py_tracefunc function when an exception has been raised. The callback function is called with this value for_what_ when after any bytecode is processed after which the exception becomes set within the frame being executed. The effect of this is that as exception propagation causes the Python stack to unwind, the callback is called upon return to each frame as the exception propagates. Only trace functions receives these events; they are not needed by the profiler.

int PyTrace_LINE¶

The value passed as the what parameter to a trace function (but not a profiling function) when a line-number event is being reported.

int PyTrace_RETURN¶

The value for the what parameter to Py_tracefunc functions when a call is returning without propagating an exception.

int PyTrace_C_CALL¶

The value for the what parameter to Py_tracefunc functions when a C function is about to be called.

int PyTrace_C_EXCEPTION¶

The value for the what parameter to Py_tracefunc functions when a C function has raised an exception.

int PyTrace_C_RETURN¶

The value for the what parameter to Py_tracefunc functions when a C function has returned.

void PyEval_SetProfile(Py_tracefunc func, PyObject *obj)¶

Set the profiler function to func. The obj parameter is passed to the function as its first parameter, and may be any Python object, or NULL. If the profile function needs to maintain state, using a different value for _obj_for each thread provides a convenient and thread-safe place to store it. The profile function is called for all monitored events except the line-number events.

void PyEval_SetTrace(Py_tracefunc func, PyObject *obj)¶

Set the tracing function to func. This is similar toPyEval_SetProfile(), except the tracing function does receive line-number events.

PyObject* PyEval_GetCallStats(PyObject *self)¶

Return a tuple of function call counts. There are constants defined for the positions within the tuple:

PCALL_FAST_FUNCTION means no argument tuple needs to be created.PCALL_FASTER_FUNCTION means that the fast-path frame setup code is used.

If there is a method call where the call can be optimized by changing the argument tuple and calling the function directly, it gets recorded twice.

This function is only present if Python is compiled with CALL_PROFILEdefined.

Advanced Debugger Support¶

These functions are only intended to be used by advanced debugging tools.

PyInterpreterState* PyInterpreterState_Head()¶

Return the interpreter state object at the head of the list of all such objects.

PyInterpreterState* PyInterpreterState_Next(PyInterpreterState *interp)¶

Return the next interpreter state object after interp from the list of all such objects.

PyThreadState * PyInterpreterState_ThreadHead(PyInterpreterState *interp)¶

Return the a pointer to the first PyThreadState object in the list of threads associated with the interpreter interp.

PyThreadState* PyThreadState_Next(PyThreadState *tstate)¶

Return the next thread state object after tstate from the list of all such objects belonging to the same PyInterpreterState object.