1. Nick Coghlan
  2. cpython_sandbox


cpython_sandbox / Doc / library / threading.rst

:mod:`threading` --- Thread-based parallelism

Source code: :source:`Lib/threading.py`

This module constructs higher-level threading interfaces on top of the lower level :mod:`_thread` module. See also the :mod:`queue` module.

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


While they are not listed below, the camelCase names used for some methods and functions in this module in the Python 2.x series are still supported by this module.

This module defines the following functions:

This module also defines the following constant:

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 :class:`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 :class:`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.

A class that represents thread-local data.

For more details and extensive examples, see the documentation string of the :mod:`_threading_local` module.

Thread Objects

The :class:`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 :meth:`~Thread.run` method in a subclass. No other methods (except for the constructor) should be overridden in a subclass. In other words, only override the :meth:`~Thread.__init__` and :meth:`~Thread.run` methods of this class.

Once a thread object is created, its activity must be started by calling the thread's :meth:`~Thread.start` method. This invokes the :meth:`~Thread.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 :meth:`~Thread.run` method terminates -- either normally, or by raising an unhandled exception. The :meth:`~Thread.is_alive` method tests whether the thread is alive.

Other threads can call a thread's :meth:`~Thread.join` method. This blocks the calling thread until the thread whose :meth:`~Thread.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 :attr:`~Thread.name` attribute.

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 :attr:`~Thread.daemon` property or the daemon constructor argument.


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 :class:`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 :meth:`~Thread.join`ed. They are never deleted, since it is impossible to detect the termination of alien threads.

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 :mod:`_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, :meth:`~Lock.acquire` and :meth:`~Lock.release`. When the state is unlocked, :meth:`~Lock.acquire` changes the state to locked and returns immediately. When the state is locked, :meth:`~Lock.acquire` blocks until a call to :meth:`~Lock.release` in another thread changes it to unlocked, then the :meth:`~Lock.acquire` call resets it to locked and returns. The :meth:`~Lock.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 :exc:`RuntimeError` will be raised.

Locks also support the :ref:`context manager protocol <with-locks>`.

When more than one thread is blocked in :meth:`~Lock.acquire` waiting for the state to turn to unlocked, only one thread proceeds when a :meth:`~Lock.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.

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.

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

Reentrant locks also support the :ref:`context manager protocol <with-locks>`.

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.

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 :ref:`context manager protocol <with-locks>`: using the with statement acquires the associated lock for the duration of the enclosed block. The :meth:`~Condition.acquire` and :meth:`~Condition.release` methods also call the corresponding methods of the associated lock.

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

The :meth:`~Condition.notify` method wakes up one of the threads waiting for the condition variable, if any are waiting. The :meth:`~Condition.notify_all` method wakes up all threads waiting for the condition variable.

Note: the :meth:`~Condition.notify` and :meth:`~Condition.notify_all` methods don't release the lock; this means that the thread or threads awakened will not return from their :meth:`~Condition.wait` call immediately, but only when the thread that called :meth:`~Condition.notify` or :meth:`~Condition.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 :meth:`~Condition.wait` repeatedly until they see the desired state, while threads that modify the state call :meth:`~Condition.notify` or :meth:`~Condition.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():

# Produce one item
with cv:

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

# Consume an item
with cv:

To choose between :meth:`~Condition.notify` and :meth:`~Condition.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.

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 :class:`Lock` or :class:`RLock` object, and it is used as the underlying lock. Otherwise, a new :class:`RLock` object is created and used as the underlying lock.

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 :meth:`~Semaphore.acquire` and :meth:`~Semaphore.release`).

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

Semaphores also support the :ref:`context manager protocol <with-locks>`.

This class implements semaphore objects. A semaphore manages a counter representing the number of :meth:`release` calls minus the number of :meth:`acquire` calls, plus an initial value. The :meth:`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, :exc:`ValueError` is raised.

Class implementing bounded semaphore objects. A bounded semaphore checks to make sure its current value doesn't exceed its initial value. If it does, :exc:`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.

: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()
        # ... use connection ...

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 :meth:`~Event.set` method and reset to false with the :meth:`~Event.clear` method. The :meth:`~Event.wait` method blocks until the flag is true.

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

Timer Objects

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

Timers are started, as with threads, by calling their :meth:`start` method. The timer can be stopped (before its action has begun) by calling the :meth:`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.

For example:

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

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

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.

Barrier Objects

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 :meth:`~Barrier.wait` method and will block until all of the threads have made the call. At this points, the threads are released simultanously.

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():
    while True:
        connection = accept_connection()

def client():
    while True:
        connection = make_connection()

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 :meth:`wait` method.

Using locks, conditions, and semaphores in the :keyword:`with` statement

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

with some_lock:
    # do something...

is equivalent to:

    # do something...

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