`threading` — Thread-based parallelism¶

This module constructs higher-level threading interfaces on top of the lower level _thread module.

Alterado na versão 3.7: Este módulo costumava ser opcional, agora está sempre disponível.

Ver também

concurrent.futures.ThreadPoolExecutor offers a higher level interface to push tasks to a background thread without blocking execution of the calling thread, while still being able to retrieve their results when needed.

queue provides a thread-safe interface for exchanging data between running threads.

asyncio offers an alternative approach to achieving task level concurrency without requiring the use of multiple operating system threads.

Nota

In the Python 2.x series, this module contained camelCase names for some methods and functions. These are deprecated as of Python 3.10, but they are still supported for compatibility with Python 2.5 and lower.

Detalhes da implementação do CPython: In CPython, due to the Global Interpreter Lock, only one thread can execute Python code at once (even though certain performance-oriented libraries might overcome this limitation). If you want your application to make better use of the computational resources of multi-core machines, you are advised to use multiprocessing or concurrent.futures.ProcessPoolExecutor. However, threading is still an appropriate model if you want to run multiple I/O-bound tasks simultaneously.

Availability: not WASI.

Este módulo não funciona ou não está disponível em WebAssembly. Veja Plataformas WebAssembly para mais informações.

Este módulo define as seguintes funções:

threading.active_count()¶

Retorna o número de objetos Thread atualmente ativos. A quantidade retornada é igual ao tamanho da lista retornada por enumerate().

The function activeCount is a deprecated alias for this function.

threading.current_thread()¶

Retorna o objeto Thread atual, correspondendo ao controle do chamador da thread. Se o controle do chamador da thread não foi criado através do módulo threading, um objeto thread vazio, com funcionalidade limitada, é retornado.

The function currentThread is a deprecated alias for this function.

threading.excepthook(args, /)¶

Handle uncaught exception raised by Thread.run().

O argumento args tem os seguintes atributos:

exc_type: Tipo de exceção..
exc_value: Valor da exceção, pode ser None.
exc_traceback: Pilha de execução da exceção, pode ser None.
thread: Thread que levantou a exceção, pode ser None.

Se exc_type é SystemExit, a exceção é silenciosamente ignorada. Caso contrário, a exceção é exibida em sys.stderr.

Se esta função levantar uma exceção, sys.excepthook() é chamada para tratá-la.

threading.excepthook() pode ser substituída para controlar como exceções não capturadas levantadas por Thread.run() são tratadas.

Storing exc_value using a custom hook can create a reference cycle. It should be cleared explicitly to break the reference cycle when the exception is no longer needed.

Storing thread using a custom hook can resurrect it if it is set to an object which is being finalized. Avoid storing thread after the custom hook completes to avoid resurrecting objects.

Ver também

sys.excepthook() trata exceções não capturadas.

Adicionado na versão 3.8.

threading.__excepthook__¶: Holds the original value of threading.excepthook(). It is saved so that the original value can be restored in case they happen to get replaced with broken or alternative objects.

Adicionado na versão 3.10.

threading.get_ident()¶: Retorna o ‘identificador de thread’ do thread atual. Este é um número inteiro diferente de zero. Seu valor não tem significado direto; pretende-se que seja um cookie mágico para ser usado, por exemplo, para indexar um dicionário de dados específicos do thread. identificadores de thread podem ser reciclados quando um thread sai e outro é criado.

Adicionado na versão 3.3.

threading.get_native_id()¶: Retorna a ID de thread integral nativa da thread atual atribuída pelo kernel. Este é um número inteiro não negativo. Seu valor pode ser usado para identificar exclusivamente essa thread específica em todo o sistema (até que a thread termine, após o que o valor poderá ser reciclado pelo sistema operacional).

Availability: Windows, FreeBSD, Linux, macOS, OpenBSD, NetBSD, AIX, DragonFlyBSD, GNU/kFreeBSD.

Adicionado na versão 3.8.

Alterado na versão 3.13: Adicionado suporte a GNU/kFreeBSD.

threading.enumerate()¶: Return a list of all Thread objects currently active. The list includes daemonic threads and dummy thread objects created by current_thread(). It excludes terminated threads and threads that have not yet been started. However, the main thread is always part of the result, even when terminated.

threading.main_thread()¶: Return the main Thread object. In normal conditions, the main thread is the thread from which the Python interpreter was started.

Adicionado na versão 3.4.

threading.settrace(func)¶: Set a trace function for all threads started from the threading module. The func will be passed to sys.settrace() for each thread, before its run() method is called.

threading.settrace_all_threads(func)¶

Set a trace function for all threads started from the threading module and all Python threads that are currently executing.

The func will be passed to sys.settrace() for each thread, before its run() method is called.

Adicionado na versão 3.12.

threading.gettrace()¶: Obtém a função trace conforme definido por settrace().

Adicionado na versão 3.10.

threading.setprofile(func)¶: Set a profile function for all threads started from the threading module. The func will be passed to sys.setprofile() for each thread, before its run() method is called.

threading.setprofile_all_threads(func)¶

Set a profile function for all threads started from the threading module and all Python threads that are currently executing.

The func will be passed to sys.setprofile() for each thread, before its run() method is called.

Adicionado na versão 3.12.

threading.getprofile()¶: Obtém a função do criador de perfil conforme definido por setprofile().

Adicionado na versão 3.10.

threading.stack_size([size])¶: Retorna o tamanho da pilha de threads usado ao criar novos threads. O argumento opcional size especifica o tamanho da pilha a ser usado para threads criados posteriormente e deve ser 0 (usar plataforma ou padrão configurado) ou um valor inteiro positivo de pelo menos 32.768 (32 KiB). Se size não for especificado, 0 será usado. Se a alteração do tamanho da pilha de threads não for suportada, uma RuntimeError será levantada. Se o tamanho da pilha especificado for inválido, uma ValueError será levantada e o tamanho da pilha não será modificado. Atualmente, 0 KiB é o valor mínimo de tamanho de pilha suportado para garantir espaço suficiente para o próprio interpretador. Observe que algumas plataformas podem ter restrições específicas sobre valores para o tamanho da pilha, como exigir um tamanho mínimo de pilha > 32 KiB ou exigir alocação em múltiplos do tamanho da página de memória do sistema – a documentação da plataforma deve ser consultada para obter mais informações (4 páginas KiB são comuns; usar múltiplos de 4096 para o tamanho da pilha é a abordagem sugerida na ausência de informações mais específicas).

Availability: Windows, pthreads.

Plataformas Unix com suporte a threads POSIX.

This module also defines the following constant:

threading.TIMEOUT_MAX¶: The maximum value allowed for the timeout parameter of blocking functions (Lock.acquire(), RLock.acquire(), Condition.wait(), etc.). Specifying a timeout greater than this value will raise an OverflowError.

Adicionado na versão 3.2.

This module defines a number of classes, which are detailed in the sections below.

The design of this module is loosely based on Java’s threading model. However, where Java makes locks and condition variables basic behavior of every object, they are separate objects in Python. Python’s Thread class supports a subset of the behavior of Java’s Thread class; currently, there are no priorities, no thread groups, and threads cannot be destroyed, stopped, suspended, resumed, or interrupted. The static methods of Java’s Thread class, when implemented, are mapped to module-level functions.

All of the methods described below are executed atomically.

Thread-Local Data¶

Thread-local data is data whose values are thread specific. To manage thread-local data, just create an instance of local (or a subclass) and store attributes on it:

mydata = threading.local()
mydata.x = 1

The instance’s values will be different for separate threads.

class threading.local¶

A class that represents thread-local data.

For more details and extensive examples, see the documentation string of the _threading_local module: Lib/_threading_local.py.

Thread Objects¶

The Thread class represents an activity that is run in a separate thread of control. There are two ways to specify the activity: by passing a callable object to the constructor, or by overriding the run() method in a subclass. No other methods (except for the constructor) should be overridden in a subclass. In other words, only override the __init__() and run() methods of this class.

Once a thread object is created, its activity must be started by calling the thread’s start() method. This invokes the run() method in a separate thread of control.

Once the thread’s activity is started, the thread is considered ‘alive’. It stops being alive when its run() method terminates – either normally, or by raising an unhandled exception. The is_alive() method tests whether the thread is alive.

Other threads can call a thread’s join() method. This blocks the calling thread until the thread whose join() method is called is terminated.

A thread has a name. The name can be passed to the constructor, and read or changed through the name attribute.

If the run() method raises an exception, threading.excepthook() is called to handle it. By default, threading.excepthook() ignores silently SystemExit.

A thread can be flagged as a “daemon thread”. The significance of this flag is that the entire Python program exits when only daemon threads are left. The initial value is inherited from the creating thread. The flag can be set through the daemon property or the daemon constructor argument.

Nota

Daemon threads are abruptly stopped at shutdown. Their resources (such as open files, database transactions, etc.) may not be released properly. If you want your threads to stop gracefully, make them non-daemonic and use a suitable signalling mechanism such as an Event.

There is a “main thread” object; this corresponds to the initial thread of control in the Python program. It is not a daemon thread.

There is the possibility that “dummy thread objects” are created. These are thread objects corresponding to “alien threads”, which are threads of control started outside the threading module, such as directly from C code. Dummy thread objects have limited functionality; they are always considered alive and daemonic, and cannot be joined. They are never deleted, since it is impossible to detect the termination of alien threads.

class threading.Thread(group=None, target=None, name=None, args=(), kwargs={}, *, daemon=None)¶

This constructor should always be called with keyword arguments. Arguments are:

group should be None; reserved for future extension when a ThreadGroup class is implemented.

target is the callable object to be invoked by the run() method. Defaults to None, meaning nothing is called.

name is the thread name. By default, a unique name is constructed of the form “Thread-N” where N is a small decimal number, or “Thread-N (target)” where “target” is target.__name__ if the target argument is specified.

args is a list or tuple of arguments for the target invocation. Defaults to ().

kwargs is a dictionary of keyword arguments for the target invocation. Defaults to {}.

If not None, daemon explicitly sets whether the thread is daemonic. If None (the default), the daemonic property is inherited from the current thread.

If the subclass overrides the constructor, it must make sure to invoke the base class constructor (Thread.__init__()) before doing anything else to the thread.

Alterado na versão 3.3: Adicionado o parâmetro daemon.

Alterado na versão 3.10: Use the target name if name argument is omitted.

start()¶

Start the thread’s activity.

It must be called at most once per thread object. It arranges for the object’s run() method to be invoked in a separate thread of control.

This method will raise a RuntimeError if called more than once on the same thread object.

run()¶

Method representing the thread’s activity.

You may override this method in a subclass. The standard run() method invokes the callable object passed to the object’s constructor as the target argument, if any, with positional and keyword arguments taken from the args and kwargs arguments, respectively.

Using list or tuple as the args argument which passed to the Thread could achieve the same effect.

Exemplo:

>>> from threading import Thread
>>> t = Thread(target=print, args=[1])
>>> t.run()
1
>>> t = Thread(target=print, args=(1,))
>>> t.run()
1

join(timeout=None)¶

Wait until the thread terminates. This blocks the calling thread until the thread whose join() method is called terminates – either normally or through an unhandled exception – or until the optional timeout occurs.

When the timeout argument is present and not None, it should be a floating-point number specifying a timeout for the operation in seconds (or fractions thereof). As join() always returns None, you must call is_alive() after join() to decide whether a timeout happened – if the thread is still alive, the join() call timed out.

When the timeout argument is not present or None, the operation will block until the thread terminates.

A thread can be joined many times.

join() raises a RuntimeError if an attempt is made to join the current thread as that would cause a deadlock. It is also an error to join() a thread before it has been started and attempts to do so raise the same exception.

name¶

A string used for identification purposes only. It has no semantics. Multiple threads may be given the same name. The initial name is set by the constructor.

On some platforms, the thread name is set at the operating system level when the thread starts, so that it is visible in task managers. This name may be truncated to fit in a system-specific limit (for example, 15 bytes on Linux or 63 bytes on macOS).

Changes to name are only reflected at the OS level when the currently running thread is renamed. (Setting the name attribute of a different thread only updates the Python Thread object.)

Alterado na versão 3.14: Set the operating system thread name.

getName()¶
setName()¶: Deprecated getter/setter API for name; use it directly as a property instead.

Obsoleto desde a versão 3.10.

ident¶: The ‘thread identifier’ of this thread or None if the thread has not been started. This is a nonzero integer. See the get_ident() function. Thread identifiers may be recycled when a thread exits and another thread is created. The identifier is available even after the thread has exited.

native_id¶: The Thread ID (TID) of this thread, as assigned by the OS (kernel). This is a non-negative integer, or None if the thread has not been started. See the get_native_id() function. This value may be used to uniquely identify this particular thread system-wide (until the thread terminates, after which the value may be recycled by the OS).

Nota

Similar to Process IDs, Thread IDs are only valid (guaranteed unique system-wide) from the time the thread is created until the thread has been terminated.

Availability: Windows, FreeBSD, Linux, macOS, OpenBSD, NetBSD, AIX, DragonFlyBSD.

Adicionado na versão 3.8.

is_alive()¶

Return whether the thread is alive.

This method returns True just before the run() method starts until just after the run() method terminates. The module function enumerate() returns a list of all alive threads.

daemon¶

A boolean value indicating whether this thread is a daemon thread (True) or not (False). This must be set before start() is called, otherwise RuntimeError is raised. Its initial value is inherited from the creating thread; the main thread is not a daemon thread and therefore all threads created in the main thread default to daemon = False.

The entire Python program exits when no alive non-daemon threads are left.

isDaemon()¶
setDaemon()¶: Deprecated getter/setter API for daemon; use it directly as a property instead.

Obsoleto desde a versão 3.10.

Lock Objects¶

A primitive lock is a synchronization primitive that is not owned by a particular thread when locked. In Python, it is currently the lowest level synchronization primitive available, implemented directly by the _thread extension module.

A primitive lock is in one of two states, “locked” or “unlocked”. It is created in the unlocked state. It has two basic methods, acquire() and release(). When the state is unlocked, acquire() changes the state to locked and returns immediately. When the state is locked, acquire() blocks until a call to release() in another thread changes it to unlocked, then the acquire() call resets it to locked and returns. The release() method should only be called in the locked state; it changes the state to unlocked and returns immediately. If an attempt is made to release an unlocked lock, a RuntimeError will be raised.

Locks also support the context management protocol.

When more than one thread is blocked in acquire() waiting for the state to turn to unlocked, only one thread proceeds when a release() call resets the state to unlocked; which one of the waiting threads proceeds is not defined, and may vary across implementations.

All methods are executed atomically.

class threading.Lock¶

The class implementing primitive lock objects. Once a thread has acquired a lock, subsequent attempts to acquire it block, until it is released; any thread may release it.

Alterado na versão 3.13: Lock is now a class. In earlier Pythons, Lock was a factory function which returned an instance of the underlying private lock type.

acquire(blocking=True, timeout=-1)¶

Adquire uma trava, bloqueante ou não.

When invoked with the blocking argument set to True (the default), block until the lock is unlocked, then set it to locked and return True.

When invoked with the blocking argument set to False, do not block. If a call with blocking set to True would block, return False immediately; otherwise, set the lock to locked and return True.

When invoked with the floating-point timeout argument set to a positive value, block for at most the number of seconds specified by timeout and as long as the lock cannot be acquired. A timeout argument of -1 specifies an unbounded wait. It is forbidden to specify a timeout when blocking is False.

The return value is True if the lock is acquired successfully, False if not (for example if the timeout expired).

Alterado na versão 3.2: O parâmetro timeout é novo.

Alterado na versão 3.2: Lock acquisition can now be interrupted by signals on POSIX if the underlying threading implementation supports it.

Alterado na versão 3.14: Lock acquisition can now be interrupted by signals on Windows.

release()¶

Release a lock. This can be called from any thread, not only the thread which has acquired the lock.

When the lock is locked, reset it to unlocked, and return. If any other threads are blocked waiting for the lock to become unlocked, allow exactly one of them to proceed.

When invoked on an unlocked lock, a RuntimeError is raised.

There is no return value.

locked()¶: Return True if the lock is acquired.

Objetos RLock¶

A reentrant lock is a synchronization primitive that may be acquired multiple times by the same thread. Internally, it uses the concepts of “owning thread” and “recursion level” in addition to the locked/unlocked state used by primitive locks. In the locked state, some thread owns the lock; in the unlocked state, no thread owns it.

Threads call a lock’s acquire() method to lock it, and its release() method to unlock it.

Nota

Reentrant locks support the context management protocol, so it is recommended to use with instead of manually calling acquire() and release() to handle acquiring and releasing the lock for a block of code.

RLock’s acquire()/release() call pairs may be nested, unlike Lock’s acquire()/release(). Only the final release() (the release() of the outermost pair) resets the lock to an unlocked state and allows another thread blocked in acquire() to proceed.

acquire()/release() must be used in pairs: each acquire must have a release in the thread that has acquired the lock. Failing to call release as many times the lock has been acquired can lead to deadlock.

class threading.RLock¶

This class implements reentrant lock objects. A reentrant lock must be released by the thread that acquired it. Once a thread has acquired a reentrant lock, the same thread may acquire it again without blocking; the thread must release it once for each time it has acquired it.

Note that RLock is actually a factory function which returns an instance of the most efficient version of the concrete RLock class that is supported by the platform.

acquire(blocking=True, timeout=-1)¶

Adquire uma trava, bloqueante ou não.

Ver também

Using RLock as a context manager: Recommended over manual acquire() and release() calls whenever practical.

When invoked with the blocking argument set to True (the default):

If no thread owns the lock, acquire the lock and return immediately.

If another thread owns the lock, block until we are able to acquire lock, or timeout, if set to a positive float value.

If the same thread owns the lock, acquire the lock again, and return immediately. This is the difference between Lock and RLock; Lock handles this case the same as the previous, blocking until the lock can be acquired.

When invoked with the blocking argument set to False:

If no thread owns the lock, acquire the lock and return immediately.

If another thread owns the lock, return immediately.

If the same thread owns the lock, acquire the lock again and return immediately.

In all cases, if the thread was able to acquire the lock, return True. If the thread was unable to acquire the lock (i.e. if not blocking or the timeout was reached) return False.

If called multiple times, failing to call release() as many times may lead to deadlock. Consider using RLock as a context manager rather than calling acquire/release directly.

Alterado na versão 3.2: O parâmetro timeout é novo.

release()¶

Release a lock, decrementing the recursion level. If after the decrement it is zero, reset the lock to unlocked (not owned by any thread), and if any other threads are blocked waiting for the lock to become unlocked, allow exactly one of them to proceed. If after the decrement the recursion level is still nonzero, the lock remains locked and owned by the calling thread.

Only call this method when the calling thread owns the lock. A RuntimeError is raised if this method is called when the lock is not acquired.

There is no return value.

Condition Objects¶

A condition variable is always associated with some kind of lock; this can be passed in or one will be created by default. Passing one in is useful when several condition variables must share the same lock. The lock is part of the condition object: you don’t have to track it separately.

A condition variable obeys the context management protocol: using the with statement acquires the associated lock for the duration of the enclosed block. The acquire() and release() methods also call the corresponding methods of the associated lock.

Other methods must be called with the associated lock held. The wait() method releases the lock, and then blocks until another thread awakens it by calling notify() or notify_all(). Once awakened, wait() re-acquires the lock and returns. It is also possible to specify a timeout.

The notify() method wakes up one of the threads waiting for the condition variable, if any are waiting. The notify_all() method wakes up all threads waiting for the condition variable.

Note: the notify() and notify_all() methods don’t release the lock; this means that the thread or threads awakened will not return from their wait() call immediately, but only when the thread that called notify() or notify_all() finally relinquishes ownership of the lock.

The typical programming style using condition variables uses the lock to synchronize access to some shared state; threads that are interested in a particular change of state call wait() repeatedly until they see the desired state, while threads that modify the state call notify() or notify_all() when they change the state in such a way that it could possibly be a desired state for one of the waiters. For example, the following code is a generic producer-consumer situation with unlimited buffer capacity:

# Consume one item
with cv:
    while not an_item_is_available():
        cv.wait()
    get_an_available_item()

# Produce one item
with cv:
    make_an_item_available()
    cv.notify()

The while loop checking for the application’s condition is necessary because wait() can return after an arbitrary long time, and the condition which prompted the notify() call may no longer hold true. This is inherent to multi-threaded programming. The wait_for() method can be used to automate the condition checking, and eases the computation of timeouts:

# Consume an item
with cv:
    cv.wait_for(an_item_is_available)
    get_an_available_item()

To choose between notify() and notify_all(), consider whether one state change can be interesting for only one or several waiting threads. E.g. in a typical producer-consumer situation, adding one item to the buffer only needs to wake up one consumer thread.

class threading.Condition(lock=None)¶

This class implements condition variable objects. A condition variable allows one or more threads to wait until they are notified by another thread.

If the lock argument is given and not None, it must be a Lock or RLock object, and it is used as the underlying lock. Otherwise, a new RLock object is created and used as the underlying lock.

Alterado na versão 3.3: changed from a factory function to a class.

acquire(*args)¶: Acquire the underlying lock. This method calls the corresponding method on the underlying lock; the return value is whatever that method returns.

release()¶: Release the underlying lock. This method calls the corresponding method on the underlying lock; there is no return value.

wait(timeout=None)¶

Wait until notified or until a timeout occurs. If the calling thread has not acquired the lock when this method is called, a RuntimeError is raised.

This method releases the underlying lock, and then blocks until it is awakened by a notify() or notify_all() call for the same condition variable in another thread, or until the optional timeout occurs. Once awakened or timed out, it re-acquires the lock and returns.

When the timeout argument is present and not None, it should be a floating-point number specifying a timeout for the operation in seconds (or fractions thereof).

When the underlying lock is an RLock, it is not released using its release() method, since this may not actually unlock the lock when it was acquired multiple times recursively. Instead, an internal interface of the RLock class is used, which really unlocks it even when it has been recursively acquired several times. Another internal interface is then used to restore the recursion level when the lock is reacquired.

The return value is True unless a given timeout expired, in which case it is False.

Alterado na versão 3.2: Previously, the method always returned None.

wait_for(predicate, timeout=None)¶

Wait until a condition evaluates to true. predicate should be a callable which result will be interpreted as a boolean value. A timeout may be provided giving the maximum time to wait.

This utility method may call wait() repeatedly until the predicate is satisfied, or until a timeout occurs. The return value is the last return value of the predicate and will evaluate to False if the method timed out.

Ignoring the timeout feature, calling this method is roughly equivalent to writing:

while not predicate():
    cv.wait()

Therefore, the same rules apply as with wait(): The lock must be held when called and is re-acquired on return. The predicate is evaluated with the lock held.

Adicionado na versão 3.2.

notify(n=1)¶

By default, wake up one thread waiting on this condition, if any. If the calling thread has not acquired the lock when this method is called, a RuntimeError is raised.

This method wakes up at most n of the threads waiting for the condition variable; it is a no-op if no threads are waiting.

The current implementation wakes up exactly n threads, if at least n threads are waiting. However, it’s not safe to rely on this behavior. A future, optimized implementation may occasionally wake up more than n threads.

Note: an awakened thread does not actually return from its wait() call until it can reacquire the lock. Since notify() does not release the lock, its caller should.

notify_all()¶

Wake up all threads waiting on this condition. This method acts like notify(), but wakes up all waiting threads instead of one. If the calling thread has not acquired the lock when this method is called, a RuntimeError is raised.

The method notifyAll is a deprecated alias for this method.

Semaphore Objects¶

This is one of the oldest synchronization primitives in the history of computer science, invented by the early Dutch computer scientist Edsger W. Dijkstra (he used the names P() and V() instead of acquire() and release()).

A semaphore manages an internal counter which is decremented by each acquire() call and incremented by each release() call. The counter can never go below zero; when acquire() finds that it is zero, it blocks, waiting until some other thread calls release().

Semaphores also support the context management protocol.

class threading.Semaphore(value=1)¶

This class implements semaphore objects. A semaphore manages an atomic counter representing the number of release() calls minus the number of acquire() calls, plus an initial value. The acquire() method blocks if necessary until it can return without making the counter negative. If not given, value defaults to 1.

The optional argument gives the initial value for the internal counter; it defaults to 1. If the value given is less than 0, ValueError is raised.

Alterado na versão 3.3: changed from a factory function to a class.

acquire(blocking=True, timeout=None)¶

Acquire a semaphore.

When invoked without arguments:

If the internal counter is larger than zero on entry, decrement it by one and return True immediately.
If the internal counter is zero on entry, block until awoken by a call to release(). Once awoken (and the counter is greater than 0), decrement the counter by 1 and return True. Exactly one thread will be awoken by each call to release(). The order in which threads are awoken should not be relied on.

When invoked with blocking set to False, do not block. If a call without an argument would block, return False immediately; otherwise, do the same thing as when called without arguments, and return True.

When invoked with a timeout other than None, it will block for at most timeout seconds. If acquire does not complete successfully in that interval, return False. Return True otherwise.

Alterado na versão 3.2: O parâmetro timeout é novo.

release(n=1)¶: Release a semaphore, incrementing the internal counter by n. When it was zero on entry and other threads are waiting for it to become larger than zero again, wake up n of those threads.

Alterado na versão 3.9: Added the n parameter to release multiple waiting threads at once.

class threading.BoundedSemaphore(value=1)¶: Class implementing bounded semaphore objects. A bounded semaphore checks to make sure its current value doesn’t exceed its initial value. If it does, ValueError is raised. In most situations semaphores are used to guard resources with limited capacity. If the semaphore is released too many times it’s a sign of a bug. If not given, value defaults to 1.

Alterado na versão 3.3: changed from a factory function to a class.

Exemplo `Semaphore`¶

Semaphores are often used to guard resources with limited capacity, for example, a database server. In any situation where the size of the resource is fixed, you should use a bounded semaphore. Before spawning any worker threads, your main thread would initialize the semaphore:

maxconnections = 5
# ...
pool_sema = BoundedSemaphore(value=maxconnections)

Once spawned, worker threads call the semaphore’s acquire and release methods when they need to connect to the server:

with pool_sema:
    conn = connectdb()
    try:
        # ... use connection ...
    finally:
        conn.close()

The use of a bounded semaphore reduces the chance that a programming error which causes the semaphore to be released more than it’s acquired will go undetected.

Event Objects¶

This is one of the simplest mechanisms for communication between threads: one thread signals an event and other threads wait for it.

An event object manages an internal flag that can be set to true with the set() method and reset to false with the clear() method. The wait() method blocks until the flag is true.

class threading.Event¶

Class implementing event objects. An event manages a flag that can be set to true with the set() method and reset to false with the clear() method. The wait() method blocks until the flag is true. The flag is initially false.

Alterado na versão 3.3: changed from a factory function to a class.

is_set()¶

Return True if and only if the internal flag is true.

The method isSet is a deprecated alias for this method.

set()¶: Set the internal flag to true. All threads waiting for it to become true are awakened. Threads that call wait() once the flag is true will not block at all.

clear()¶: Reset the internal flag to false. Subsequently, threads calling wait() will block until set() is called to set the internal flag to true again.

wait(timeout=None)¶

Block as long as the internal flag is false and the timeout, if given, has not expired. The return value represents the reason that this blocking method returned; True if returning because the internal flag is set to true, or False if a timeout is given and the internal flag did not become true within the given wait time.

When the timeout argument is present and not None, it should be a floating-point number specifying a timeout for the operation in seconds, or fractions thereof.

Alterado na versão 3.1: Previously, the method always returned None.

Objetos Timer¶

This class represents an action that should be run only after a certain amount of time has passed — a timer. Timer is a subclass of Thread and as such also functions as an example of creating custom threads.

Timers are started, as with threads, by calling their Timer.start method. The timer can be stopped (before its action has begun) by calling the cancel() method. The interval the timer will wait before executing its action may not be exactly the same as the interval specified by the user.

Por exemplo:

def hello():
    print("hello, world")

t = Timer(30.0, hello)
t.start()  # after 30 seconds, "hello, world" will be printed

class threading.Timer(interval, function, args=None, kwargs=None)¶

Create a timer that will run function with arguments args and keyword arguments kwargs, after interval seconds have passed. If args is None (the default) then an empty list will be used. If kwargs is None (the default) then an empty dict will be used.

Alterado na versão 3.3: changed from a factory function to a class.

cancel()¶: Stop the timer, and cancel the execution of the timer’s action. This will only work if the timer is still in its waiting stage.

Barrier Objects¶

Adicionado na versão 3.2.

This class provides a simple synchronization primitive for use by a fixed number of threads that need to wait for each other. Each of the threads tries to pass the barrier by calling the wait() method and will block until all of the threads have made their wait() calls. At this point, the threads are released simultaneously.

The barrier can be reused any number of times for the same number of threads.

As an example, here is a simple way to synchronize a client and server thread:

b = Barrier(2, timeout=5)

def server():
    start_server()
    b.wait()
    while True:
        connection = accept_connection()
        process_server_connection(connection)

def client():
    b.wait()
    while True:
        connection = make_connection()
        process_client_connection(connection)

class threading.Barrier(parties, action=None, timeout=None)¶

Create a barrier object for parties number of threads. An action, when provided, is a callable to be called by one of the threads when they are released. timeout is the default timeout value if none is specified for the wait() method.

wait(timeout=None)¶

Pass the barrier. When all the threads party to the barrier have called this function, they are all released simultaneously. If a timeout is provided, it is used in preference to any that was supplied to the class constructor.

The return value is an integer in the range 0 to parties – 1, different for each thread. This can be used to select a thread to do some special housekeeping, e.g.:

i = barrier.wait()
if i == 0:
    # Only one thread needs to print this
    print("passed the barrier")

If an action was provided to the constructor, one of the threads will have called it prior to being released. Should this call raise an error, the barrier is put into the broken state.

If the call times out, the barrier is put into the broken state.

This method may raise a BrokenBarrierError exception if the barrier is broken or reset while a thread is waiting.

reset()¶

Return the barrier to the default, empty state. Any threads waiting on it will receive the BrokenBarrierError exception.

Note that using this function may require some external synchronization if there are other threads whose state is unknown. If a barrier is broken it may be better to just leave it and create a new one.

abort()¶

Put the barrier into a broken state. This causes any active or future calls to wait() to fail with the BrokenBarrierError. Use this for example if one of the threads needs to abort, to avoid deadlocking the application.

It may be preferable to simply create the barrier with a sensible timeout value to automatically guard against one of the threads going awry.

parties¶: The number of threads required to pass the barrier.

n_waiting¶: The number of threads currently waiting in the barrier.

broken¶: A boolean that is True if the barrier is in the broken state.

exception threading.BrokenBarrierError¶: This exception, a subclass of RuntimeError, is raised when the Barrier object is reset or broken.

Using locks, conditions, and semaphores in the `with` statement¶

All of the objects provided by this module that have acquire and release methods can be used as context managers for a with statement. The acquire method will be called when the block is entered, and release will be called when the block is exited. Hence, the following snippet:

with some_lock:
    # do something...

é equivalente a:

some_lock.acquire()
try:
    # do something...
finally:
    some_lock.release()

Currently, Lock, RLock, Condition, Semaphore, and BoundedSemaphore objects may be used as with statement context managers.

`threading` — Thread-based parallelism¶

Thread-Local Data¶

Thread Objects¶

Lock Objects¶

Objetos RLock¶

Condition Objects¶

Semaphore Objects¶

Exemplo `Semaphore`¶

Event Objects¶

Objetos Timer¶

Barrier Objects¶

Using locks, conditions, and semaphores in the `with` statement¶

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threading — Thread-based parallelism¶

Thread-Local Data¶

Thread Objects¶

Lock Objects¶

Objetos RLock¶

Condition Objects¶

Semaphore Objects¶

Exemplo Semaphore¶

Event Objects¶

Objetos Timer¶

Barrier Objects¶

Using locks, conditions, and semaphores in the with statement¶

`threading` — Thread-based parallelism¶

Exemplo `Semaphore`¶

Using locks, conditions, and semaphores in the `with` statement¶