17.1. threading — Parallélisme basé sur les fils d’exécution (threads)

Code source: Lib/threading.py

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Ce module élabore des interfaces haut-niveau de fils d’exécutions multiples (threading) conçues en s’appuyant sur le module bas-niveau _thread. Voir aussi le module queue.

The dummy_threading module is provided for situations where threading cannot be used because _thread is missing.

Note

Bien qu’ils ne soient pas listés ci-dessous, ce module gère toujours les noms en camelCase utilisés pour certaines méthodes et fonctions de ce module dans la série Python 2.x.

Ce module définit les fonctions suivantes :

threading.active_count()

Renvoie le nombre d’objets Thread actuellement vivants. Le compte renvoyé est égal à la longueur de la liste renvoyée par enumerate().

threading.current_thread()

Renvoie l’objet Thread courant, correspondant au fil de contrôle de l’appelant. Si le fil de contrôle de l’appelant n’a pas été créé via le module Thread, un objet thread factice aux fonctionnalités limitées est renvoyé.

threading.get_ident()

Renvoie l“« identificateur de fil » du fil d’exécution courant. C’est un entier non nul. Sa valeur n’a pas de signification directe ; il est destiné à être utilisé comme valeur magique opaque, par exemple comme clef de dictionnaire de données pour chaque fil. Les identificateurs de fils peuvent être recyclés lorsqu’un fil se termine et qu’un autre fil est créé.

Nouveau dans la version 3.3.

threading.enumerate()

Renvoie une liste de tous les objets fil d’exécution Thread actuellement vivants. La liste inclut les fils démons, les fils factices créés par current_thread() et le fil principal. Elle exclut les fils terminés et les fils qui n’ont pas encore été lancés.

threading.main_thread()

Renvoie l’objet fil d’exécution Thread principal. Dans des conditions normales, le fil principal est le fil à partir duquel l’interpréteur Python a été lancé.

Nouveau dans la version 3.4.

threading.settrace(func)

Attache une fonction de traçage pour tous les fils d’exécution démarrés depuis le module Thread. La fonction func est passée à sys.settrace() pour chaque fil, avant que sa méthode run() soit appelée.

threading.setprofile(func)

Attache une fonction de profilage pour tous les fils d’exécution démarrés depuis le module Threading. La fonction func est passée à sys.setprofile() pour chaque fil, avant que sa méthode run() soit appelée.

threading.stack_size([size])

Return the thread stack size used when creating new threads. The optional size argument specifies the stack size to be used for subsequently created threads, and must be 0 (use platform or configured default) or a positive integer value of at least 32,768 (32 KiB). If size is not specified, 0 is used. If changing the thread stack size is unsupported, a RuntimeError is raised. If the specified stack size is invalid, a ValueError is raised and the stack size is unmodified. 32 KiB is currently the minimum supported stack size value to guarantee sufficient stack space for the interpreter itself. Note that some platforms may have particular restrictions on values for the stack size, such as requiring a minimum stack size > 32 KiB or requiring allocation in multiples of the system memory page size - platform documentation should be referred to for more information (4 KiB pages are common; using multiples of 4096 for the stack size is the suggested approach in the absence of more specific information). Availability: Windows, systems with POSIX threads.

Ce module définit également la constante suivante :

threading.TIMEOUT_MAX

La valeur maximale autorisée pour le paramètre timeout des fonctions bloquantes (Lock.acquire(), RLock.acquire(), Condition.wait(), etc.). Spécifier un délai d’attente supérieur à cette valeur lève une OverflowError.

Nouveau dans la version 3.2.

Ce module définit un certain nombre de classes, qui sont détaillées dans les sections ci-dessous.

La conception de ce module est librement basée sur le modèle des fils d’exécution de Java. Cependant, là où Java fait des verrous et des variables de condition le comportement de base de chaque objet, ils sont des objets séparés en Python. La classe Python Thread prend en charge un sous-ensemble du comportement de la classe Thread de Java ; actuellement, il n’y a aucune priorité, aucun groupe de fils d’exécution, et les fils ne peuvent être détruits, arrêtés, suspendus, repris ni interrompus. Les méthodes statiques de la classe Thread de Java, lorsqu’elles sont implémentées, correspondent à des fonctions au niveau du module.

Toutes les méthodes décrites ci-dessous sont exécutées de manière atomique.

17.1.1. Données locales au fil d’exécution

Les données locales au fil d’exécution (thread-local data) sont des données dont les valeurs sont propres à chaque fil. Pour gérer les données locales au fil, il suffit de créer une instance de local (ou une sous-classe) et d’y stocker des données :

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

Les valeurs dans l’instance sont différentes pour des threads différents.

class threading.local

Classe qui représente les données locales au fil d’exécution.

Pour plus de détails et de nombreux exemples, voir la chaîne de documentation du module _threading_local.

17.1.2. Objets Threads

La classe fil d’exécution Thread représente une activité qui est exécutée dans un fil d’exécution séparé. Il y a deux façons de spécifier l’activité : en passant un objet appelable au constructeur, ou en ré-implémentant la méthode run() dans une sous-classe. Aucune autre méthode (à l’exception du constructeur) ne doit être remplacée dans une sous-classe. En d’autres termes, réimplémentez seulement les méthodes __init__() et run() de cette classe.

Une fois qu’un objet fil d’exécution est créé, son activité doit être lancée en appelant la méthode start() du fil. Ceci invoque la méthode run() dans un fil d’exécution séparé.

Une fois que l’activité du fil d’exécution est lancée, le fil est considéré comme « vivant ». Il cesse d’être vivant lorsque sa méthode run() se termine – soit normalement, soit en levant une exception non gérée. La méthode is_alive() teste si le fil est vivant.

D’autres fils d’exécution peuvent appeler la méthode join() d’un fil. Ceci bloque le fil appelant jusqu’à ce que le fil dont la méthode join() est appelée soit terminé.

Un fil d’exécution a un nom. Le nom peut être passé au constructeur, et lu ou modifié via l’attribut name.

Un fil d’exécution peut être marqué comme « fil démon ». Un programme Python se termine quand il ne reste plus que des fils démons. La valeur initiale est héritée du fil d’exécution qui l’a créé. Cette option peut être définie par la propriété daemon ou par l’argument daemon du constructeur.

Note

Les fils d’exécution démons sont brusquement terminés à l’arrêt du programme Python. Leurs ressources (fichiers ouverts, transactions de base de données, etc.) peuvent ne pas être libérées correctement. Si vous voulez que vos fils s’arrêtent proprement, faites en sorte qu’ils ne soient pas démoniques et utilisez un mécanisme de signalisation approprié tel qu’un objet évènement Event.

Il y a un objet « fil principal », qui correspond au fil de contrôle initial dans le programme Python. Ce n’est pas un fil démon.

Il y a une possibilité que des objets fil d’exécution « fictifs » soient créés. Ce sont des objets correspondant à des fils d’exécution « étrangers », qui sont des fils de contrôle démarrés en dehors du module de threading, par exemple directement depuis du code C. Les objets fils d’exécution fictifs ont des fonctionnalités limitées ; ils sont toujours considérés comme vivants et démoniques, et ne peuvent pas être attendus via join(). Ils ne sont jamais supprimés, car il est impossible de détecter la fin des fils d’exécution étrangers.

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

Ce constructeur doit toujours être appelé avec des arguments nommés. Les arguments sont :

group doit être None ; cet argument est réservé pour une extension future lorsqu’une classe ThreadGroup sera implémentée.

target est l’objet appelable qui doit être invoqué par la méthode run(). La valeur par défaut est None, ce qui signifie que rien n’est appelé.

name est le nom du fil d’exécution. Par défaut, un nom unique est construit de la forme « Thread–N » où N est un petit nombre décimal.

args est le tuple d’arguments pour l’invocation de l’objet appelable. La valeur par défaut est ().

kwargs est un dictionnaire d’arguments nommés pour l’invocation de l’objet appelable. La valeur par défaut est {}.

S’il ne vaut pas None, daemon définit explicitement si le fil d’exécution est démonique ou pas. S’il vaut None (par défaut), la valeur est héritée du fil courant.

Si la sous-classe réimplémente le constructeur, elle doit s’assurer d’appeler le constructeur de la classe de base (Thread.__init__()) avant de faire autre chose au fil d’exécution.

Modifié dans la version 3.3: Ajout de l’argument daemon.

start()

Lance l’activité du fil d’exécution.

Elle ne doit être appelée qu’une fois par objet de fil. Elle fait en sorte que la méthode run() de l’objet soit invoquée dans un fil d’exécution.

Cette méthode lève une RuntimeError si elle est appelée plus d’une fois sur le même objet fil d’exécution.

run()

Méthode représentant l’activité du fil d’exécution.

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 sequential and keyword arguments taken from the args and kwargs arguments, respectively.

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.

Lorsque l’argument timeout est présent et ne vaut pas None, il doit être un nombre en virgule flottante spécifiant un délai pour l’opération en secondes (ou fractions de secondes). Comme join() renvoie toujours None, vous devez appeler is_alive() après join() pour déterminer si le délai a expiré – si le fil d’exécution est toujours vivant, c’est que l’appel à join() a expiré.

Lorsque l’argument timeout n’est pas présent ou vaut None, l’opération se bloque jusqu’à ce que le fil d’exécution se termine.

Un fil d’exécution peut être attendu via join() de nombreuses fois.

join() lève une RuntimeError si une tentative est faite pour attendre le fil d’exécution courant car cela conduirait à un interblocage (deadlock en anglais). Attendre via join() un fil d’exécution avant son lancement est aussi une erreur et, si vous tentez de le faire, lève la même exception.

name

Une chaîne de caractères utilisée à des fins d’identification seulement. Elle n’a pas de sémantique. Plusieurs fils d’exécution peuvent porter le même nom. Le nom initial est défini par le constructeur.

getName()

setName()

Anciens accesseur et mutateur pour name ; utilisez plutôt ce dernier directement.

ident

The “thread identifier” of this thread or None if the thread has not been started. This is a nonzero integer. See the _thread.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.

is_alive()

Renvoie si le fil d’exécution est vivant ou pas.

Cette méthode renvoie True depuis juste avant le démarrage de la méthode run() et jusqu’à juste après la terminaison de la méthode run(). La fonction enumerate() du module renvoie une liste de tous les fils d’exécution vivants.

daemon

Booléen indiquant si ce fil d’exécution est un fil démon (True) ou non (False). Celui-ci doit être défini avant que start() ne soit appelé, sinon RuntimeError est levée. Sa valeur initiale est héritée du fil d’exécution créateur ; le fil principal n’est pas un fil démon et donc tous les fils créés dans ce fil principal ont par défaut la valeur daemon = False.

Le programme Python se termine lorsqu’il ne reste plus de fils d’exécution non-démons vivants.

isDaemon()

setDaemon()

Anciens accesseur et mutateur pour daemon ; utilisez plutôt ce dernier directement.

En CPython, en raison du verrou global de l’interpréteur (Global Interpreter Lock), un seul fil d’exécution peut exécuter du code Python à la fois (même si certaines bibliothèques orientées performance peuvent surmonter cette limitation). Si vous voulez que votre application fasse un meilleur usage des ressources de calcul des machines multi-cœurs, nous vous conseillons d’utiliser multiprocessing ou concurrent.futures.ProcessPoolExecutor. Néanmoins, les fils d’exécutions multiples restent un modèle approprié si vous souhaitez exécuter simultanément plusieurs tâches limitées par les performances des entrées-sorties.

17.1.3. 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.

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

acquire(blocking=True, timeout=-1)

Acquiert un verrou, bloquant ou non bloquant.

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).

Modifié dans la version 3.2: Le paramètre timeout est nouveau.

Modifié dans la version 3.2: Le verrou acquis peut maintenant être interrompu par des signaux sur POSIX.

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.

Il n’y a pas de valeur de retour.

17.1.4. RLock Objects

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.

To lock the lock, a thread calls its acquire() method; this returns once the thread owns the lock. To unlock the lock, a thread calls its release() method. acquire()/release() call pairs may be nested; only the final release() (the release() of the outermost pair) resets the lock to unlocked and allows another thread blocked in acquire() to proceed.

Reentrant locks also support the context management protocol.

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)

Acquiert un verrou, bloquant ou non bloquant.

When invoked without arguments: if this thread already owns the lock, increment the recursion level by one, and return immediately. Otherwise, if another thread owns the lock, block until the lock is unlocked. Once the lock is unlocked (not owned by any thread), then grab ownership, set the recursion level to one, and return. If more than one thread is blocked waiting until the lock is unlocked, only one at a time will be able to grab ownership of the lock. There is no return value in this case.

When invoked with the blocking argument set to true, do the same thing as when called without arguments, and return true.

When invoked with the blocking argument 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 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. Return true if the lock has been acquired, false if the timeout has elapsed.

Modifié dans la version 3.2: Le paramètre timeout est nouveau.

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 unlocked.

Il n’y a pas de valeur de retour.

17.1.5. 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.

Modifié dans la version 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.

Modifié dans la version 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.

Nouveau dans la version 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.

17.1.6. 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 a 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.

Modifié dans la version 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 immediately. If it is zero on entry, block, waiting until some other thread has called release() to make it larger than zero. This is done with proper interlocking so that if multiple acquire() calls are blocked, release() will wake exactly one of them up. The implementation may pick one at random, so the order in which blocked threads are awakened should not be relied on. Returns true (or blocks indefinitely).

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.

Modifié dans la version 3.2: Le paramètre timeout est nouveau.

release()

Release a semaphore, incrementing the internal counter by one. When it was zero on entry and another thread is waiting for it to become larger than zero again, wake up that thread.

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.

Modifié dans la version 3.3: changed from a factory function to a class.

17.1.6.1. Semaphore Example

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.

17.1.7. 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.

Modifié dans la version 3.3: changed from a factory function to a class.

is_set()

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

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 until the internal flag is true. If the internal flag is true on entry, return immediately. Otherwise, block until another thread calls set() to set the flag to true, 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).

This method returns true if and only if the internal flag has been set to true, either before the wait call or after the wait starts, so it will always return True except if a timeout is given and the operation times out.

Modifié dans la version 3.1: Previously, the method always returned None.

17.1.8. Timer Objects

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 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.

Par exemple :

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.

Modifié dans la version 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.

17.1.9. Barrier Objects

Nouveau dans la version 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 the call. At this points, 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 can 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 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.

17.1.10. 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...

est équivalente à :

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.