threading --- Thread-based parallelism

Code source : Lib/threading.py

---

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

Modifié dans la version 3.7: Ce module était auparavant optionnel, il est maintenant toujours disponible.

Voir aussi

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.

Note

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.

Particularité de l'implémentation 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.

This module does not work or is not available on WebAssembly. See Plateformes WebAssembly for more information.

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().

The function activeCount is a deprecated alias for this function.

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.

The function currentThread is a deprecated alias for this function.

threading.excepthook(args, /)

Gère les exceptions non-attrapées levées par Thread.run().

L'argument arg a les attributs suivants :

• exc_type : le type de l'exception ;

• exc_value: la valeur de l'exception, peut être None ;

• exc_traceback : la pile d'appels pour cette exception, peut être None ;

• thread: le fil d'exécution ayant levé l'exception, peut être None.

Si exc_type est SystemExit, l'exception est ignorée silencieusement. Toutes les autres sont affichées sur sys.stderr.

Si cette fonction lève une exception, sys.excepthook() est appelée pour la gérer.

La fonction threading.excepthook() peut être surchargée afin de contrôler comment les exceptions non-attrapées levées par Thread.run() sont gérées.

Stocker exc_value en utilisant une fonction de rappel personnalisée peut créer un cycle de références. exc_value doit être nettoyée explicitement pour casser ce cycle lorsque l'exception n'est plus nécessaire.

Stocker thread en utilisant une fonction de rappel personnalisée peut le ressusciter, si c'est un objet en cours de finalisation. Évitez de stocker thread après la fin de la fonction de rappel, pour éviter de ressusciter des objets.

Voir aussi

sys.excepthook() gère les exceptions qui n'ont pas été attrapées.

Ajouté dans la version 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.

Ajouté dans la version 3.10.

threading.get_ident()

Renvoie l'« identifiant 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.

Ajouté dans la version 3.3.

threading.get_native_id()

Renvoie l'identifiant natif complet assigné par le noyau du fil d'exécution actuel. C'est un entier non négatif. Sa valeur peut uniquement être utilisée pour identifier ce fil d'exécution à l'échelle du système (jusqu'à ce que le fil d'exécution se termine, après quoi la valeur peut être recyclée par le système d'exploitation).

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

Ajouté dans la version 3.8.

Modifié dans la version 3.13: Added support for 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()

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.

Ajouté 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.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.

Ajouté dans la version 3.12.

threading.gettrace()

Renvoie la fonction de traçage tel que définie par settrace().

Ajouté dans la version 3.10.

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.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.

Ajouté dans la version 3.12.

threading.getprofile()

Renvoie la fonction de profilage tel que défini par setprofile().

Ajouté dans la version 3.10.

threading.stack_size([size])

Renvoie la taille de la pile d'exécution utilisée lors de la création de nouveaux fils d'exécution. L'argument optionnel size spécifie la taille de pile à utiliser pour les fils créés ultérieurement, et doit être 0 (pour utiliser la taille de la plate-forme ou la valeur configurée par défaut) ou un entier positif supérieur ou égal à 32 768 (32 Kio). Si size n'est pas spécifié, 0 est utilisé. Si la modification de la taille de la pile de fils n'est pas prise en charge, une RuntimeError est levée. Si la taille de pile spécifiée n'est pas valide, une ValueError est levée et la taille de pile n'est pas modifiée. 32 Kio est actuellement la valeur minimale de taille de pile prise en charge pour garantir un espace de pile suffisant pour l'interpréteur lui-même. Notez que certaines plates-formes peuvent avoir des restrictions particulières sur les valeurs de taille de la pile, telles que l'exigence d'une taille de pile minimale > 32 Kio ou d'une allocation en multiples de la taille de page de la mémoire du système – la documentation de la plate-forme devrait être consultée pour plus d'informations (4 Kio sont courantes ; en l'absence de renseignements plus spécifiques, l'approche proposée est l'utilisation de multiples de 4 096 pour la taille de la pile).

Availability: Windows, pthreads.

Unix platforms with POSIX threads support.

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.

Ajouté 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.

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.

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

Objets Threads

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.

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.

Si la méthode run() lève une exception, threading.excepthook() est appelée pour s'en occuper. Par défaut, threading.excepthook() ignore silencieusement SystemExit.

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.

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)

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

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

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 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 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: Added the daemon parameter.

Modifié dans la version 3.10: Use the target name if name argument is omitted.

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.

Vous pouvez remplacer cette méthode dans une sous-classe. La méthode standard run() invoque l'objet appelable passé au constructeur de l'objet en tant qu'argument target, le cas échéant, avec des arguments positionnels et des arguments nommés tirés respectivement des arguments args et kwargs.

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

Example:

>>> 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)

Attend que le fil d'exécution se termine. Ceci bloque le fil appelant jusqu'à ce que le fil dont la méthode join() est appelée se termine – soit normalement, soit par une exception non gérée – ou jusqu'à ce que le délai optionnel timeout soit atteint.

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.

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.

A thread can be joined many times.

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()

Deprecated getter/setter API for name; use it directly as a property instead.

Obsolète depuis la version 3.10.

ident

« L'identificateur de fil d'exécution » de ce fil ou None si le fil n'a pas été lancé. C'est un entier non nul. Voyez également la fonction get_ident(). Les identificateurs de fils peuvent être recyclés lorsqu'un fil se termine et qu'un autre fil est créé. L'identifiant est disponible même après que le fil ait terminé.

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).

Note

Tout comme pour les Process IDs, les Thread IDs ne sont valides (garantis uniques sur le système) uniquement du démarrage du fil à sa fin.

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

Ajouté dans la version 3.8.

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

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.

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

isDaemon()

setDaemon()

Deprecated getter/setter API for daemon; use it directly as a property instead.

Obsolète depuis la version 3.10.

Verrous

Un verrou primitif n'appartient pas à un fil d'exécution lorsqu'il est verrouillé. En Python, c'est actuellement la méthode de synchronisation la plus bas-niveau qui soit disponible, implémentée directement par le module d'extension _thread.

Un verrou primitif est soit « verrouillé » soit « déverrouillé ». Il est créé dans un état déverrouillé. Il a deux méthodes, acquire() et release(). Lorsque l'état est déverrouillé, acquire() verrouille et se termine immédiatement. Lorsque l'état est verrouillé, acquire() bloque jusqu'à ce qu'un appel à release() provenant d'un autre fil d'exécution le déverrouille. À ce moment acquire() le verrouille à nouveau et rend la main. La méthode release() ne doit être appelée que si le verrou est verrouillé, elle le déverrouille alors et se termine immédiatement. Déverrouiller un verrou qui n'est pas verrouillé provoque une RuntimeError.

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.

Modifié dans la version 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)

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

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.

Lorsqu'elle est invoquée sur un verrou déverrouillé, une RuntimeError est levée.

Il n'y a pas de valeur de retour.

locked()

Return True if the lock is acquired.

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.

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

Note

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)

Acquiert un verrou, bloquant ou non bloquant.

Voir aussi

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.

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 not acquired.

Il n'y a pas de valeur de retour.

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.

Ajouté 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.

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.

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

acquire(blocking=True, timeout=None)

Acquiert un sémaphore.

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.

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

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.

Modifié dans la version 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.

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

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.

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.

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.

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

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 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.

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.

Barrier Objects

Ajouté 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 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

Booléen qui vaut True si la barrière est rompue.

exception threading.BrokenBarrierError

Cette exception, une sous-classe de RuntimeError, est déclenchée lorsque l'objet Barrier est réinitialisé ou cassé.

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.