Doc/library/threading.rst

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

.. module:: threading
   :synopsis: 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.

.. include:: ../includes/wasm-notavail.rst

Introduction
------------

The :mod:`!threading` module provides a way to run multiple `threads
<https://en.wikipedia.org/wiki/Thread_(computing)>`_ (smaller
units of a process) concurrently within a single process. It allows for the
creation and management of threads, making it possible to execute tasks in
parallel, sharing memory space. Threads are particularly useful when tasks are
I/O bound, such as file operations or making network requests,
where much of the time is spent waiting for external resources.

A typical use case for :mod:`!threading` includes managing a pool of worker
threads that can process multiple tasks concurrently.  Here's a basic example of
creating and starting threads using :class:`~threading.Thread`::

   import threading
   import time

   def crawl(link, delay=3):
       print(f"crawl started for {link}")
       time.sleep(delay)  # Blocking I/O (simulating a network request)
       print(f"crawl ended for {link}")

   links = [
       "https://python.org",
       "https://docs.python.org",
       "https://peps.python.org",
   ]

   # Start threads for each link
   threads = []
   for link in links:
       # Using `args` to pass positional arguments and `kwargs` for keyword arguments
       t = threading.Thread(target=crawl, args=(link,), kwargs={"delay": 2})
       threads.append(t)

   # Start each thread
   for t in threads:
       t.start()

   # Wait for all threads to finish
   for t in threads:
       t.join()

.. versionchanged:: 3.7
   This module used to be optional, it is now always available.

.. seealso::

   :class:`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.

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

   :mod:`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.


.. impl-detail::

   In CPython, due to the :term:`Global Interpreter Lock
   <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
   :mod:`multiprocessing` or :class:`concurrent.futures.ProcessPoolExecutor`.
   However, threading is still an appropriate model if you want to run
   multiple I/O-bound tasks simultaneously.

GIL and performance considerations
----------------------------------

Unlike the :mod:`multiprocessing` module, which uses separate processes to
bypass the :term:`global interpreter lock` (GIL), the threading module operates
within a single process, meaning that all threads share the same memory space.
However, the GIL limits the performance gains of threading when it comes to
CPU-bound tasks, as only one thread can execute Python bytecode at a time.
Despite this, threads remain a useful tool for achieving concurrency in many
scenarios.

As of Python 3.13, :term:`free-threaded <free threading>` builds
can disable the GIL, enabling true parallel execution of threads, but this
feature is not available by default (see :pep:`703`).

.. TODO: At some point this feature will become available by default.

Reference
---------

This module defines the following functions:


.. function:: active_count()

   Return the number of :class:`Thread` objects currently alive.  The returned
   count is equal to the length of the list returned by :func:`.enumerate`.

   The function ``activeCount`` is a deprecated alias for this function.


.. function:: current_thread()

   Return the current :class:`Thread` object, corresponding to the caller's thread
   of control.  If the caller's thread of control was not created through the
   :mod:`!threading` module, a dummy thread object with limited functionality is
   returned.

   The function ``currentThread`` is a deprecated alias for this function.


.. function:: excepthook(args, /)

   Handle uncaught exception raised by :func:`Thread.run`.

   The *args* argument has the following attributes:

   * *exc_type*: Exception type.
   * *exc_value*: Exception value, can be ``None``.
   * *exc_traceback*: Exception traceback, can be ``None``.
   * *thread*: Thread which raised the exception, can be ``None``.

   If *exc_type* is :exc:`SystemExit`, the exception is silently ignored.
   Otherwise, the exception is printed out on :data:`sys.stderr`.

   If  this function raises an exception, :func:`sys.excepthook` is called to
   handle it.

   :func:`threading.excepthook` can be overridden to control how uncaught
   exceptions raised by :func:`Thread.run` are handled.

   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.

   .. seealso::
      :func:`sys.excepthook` handles uncaught exceptions.

   .. versionadded:: 3.8

.. data:: __excepthook__

   Holds the original value of :func:`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.

   .. versionadded:: 3.10

.. function:: get_ident()

   Return the 'thread identifier' of the current thread.  This is a nonzero
   integer.  Its value has no direct meaning; it is intended as a magic cookie
   to be used e.g. to index a dictionary of thread-specific data.  Thread
   identifiers may be recycled when a thread exits and another thread is
   created.

   .. versionadded:: 3.3


.. function:: get_native_id()

   Return the native integral Thread ID of the current thread assigned by the kernel.
   This is a non-negative integer.
   Its 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).

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

   .. versionadded:: 3.8

   .. versionchanged:: 3.13
      Added support for GNU/kFreeBSD.

   .. versionchanged:: 3.15
      Added support for Solaris.


.. function:: enumerate()

   Return a list of all :class:`Thread` objects currently active.  The list
   includes daemonic threads and dummy thread objects created by
   :func:`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.


.. function:: main_thread()

   Return the main :class:`Thread` object.  In normal conditions, the
   main thread is the thread from which the Python interpreter was
   started.

   .. versionadded:: 3.4


.. function:: settrace(func)

   .. index:: single: trace function

   Set a trace function for all threads started from the :mod:`!threading` module.
   The *func* will be passed to  :func:`sys.settrace` for each thread, before its
   :meth:`~Thread.run` method is called.

.. function:: settrace_all_threads(func)

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

   The *func* will be passed to  :func:`sys.settrace` for each thread, before its
   :meth:`~Thread.run` method is called.

   .. versionadded:: 3.12

.. function:: gettrace()

   .. index::
      single: trace function
      single: debugger

   Get the trace function as set by :func:`settrace`.

   .. versionadded:: 3.10


.. function:: setprofile(func)

   .. index:: single: profile function

   Set a profile function for all threads started from the :mod:`!threading` module.
   The *func* will be passed to  :func:`sys.setprofile` for each thread, before its
   :meth:`~Thread.run` method is called.

.. function:: setprofile_all_threads(func)

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

   The *func* will be passed to  :func:`sys.setprofile` for each thread, before its
   :meth:`~Thread.run` method is called.

   .. versionadded:: 3.12

.. function:: getprofile()

   .. index:: single: profile function

   Get the profiler function as set by :func:`setprofile`.

   .. versionadded:: 3.10


.. function:: 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 :exc:`RuntimeError` is raised.  If the specified stack size is
   invalid, a :exc:`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, pthreads.

      Unix platforms with POSIX threads support.


This module also defines the following constant:

.. data:: TIMEOUT_MAX

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

   .. versionadded:: 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 :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. If you
have data that you want to be local to a thread, create a
:class:`local` object and use its attributes::

   >>> mydata = local()
   >>> mydata.number = 42
   >>> mydata.number
   42

You can also access the :class:`local`-object's dictionary::

   >>> mydata.__dict__
   {'number': 42}
   >>> mydata.__dict__.setdefault('widgets', [])
   []
   >>> mydata.widgets
   []

If we access the data in a different thread::

   >>> log = []
   >>> def f():
   ...     items = sorted(mydata.__dict__.items())
   ...     log.append(items)
   ...     mydata.number = 11
   ...     log.append(mydata.number)

   >>> import threading
   >>> thread = threading.Thread(target=f)
   >>> thread.start()
   >>> thread.join()
   >>> log
   [[], 11]

we get different data.  Furthermore, changes made in the other thread
don't affect data seen in this thread::

   >>> mydata.number
   42

Of course, values you get from a :class:`local` object, including their
:attr:`~object.__dict__` attribute, are for whatever thread was current
at the time the attribute was read.  For that reason, you generally
don't want to save these values across threads, as they apply only to
the thread they came from.

You can create custom :class:`local` objects by subclassing the
:class:`local` class::

   >>> class MyLocal(local):
   ...     number = 2
   ...     def __init__(self, /, **kw):
   ...         self.__dict__.update(kw)
   ...     def squared(self):
   ...         return self.number ** 2

This can be useful to support default values, methods and
initialization.  Note that if you define an :py:meth:`~object.__init__`
method, it will be called each time the :class:`local` object is used
in a separate thread.  This is necessary to initialize each thread's
dictionary.

Now if we create a :class:`local` object::

   >>> mydata = MyLocal(color='red')

we have a default number::

   >>> mydata.number
   2

an initial color::

   >>> mydata.color
   'red'
   >>> del mydata.color

And a method that operates on the data::

   >>> mydata.squared()
   4

As before, we can access the data in a separate thread::

   >>> log = []
   >>> thread = threading.Thread(target=f)
   >>> thread.start()
   >>> thread.join()
   >>> log
   [[('color', 'red')], 11]

without affecting this thread's data::

   >>> mydata.number
   2
   >>> mydata.color
   Traceback (most recent call last):
   ...
   AttributeError: 'MyLocal' object has no attribute 'color'

Note that subclasses can define :term:`__slots__`, but they are not
thread local. They are shared across threads::

   >>> class MyLocal(local):
   ...     __slots__ = 'number'

   >>> mydata = MyLocal()
   >>> mydata.number = 42
   >>> mydata.color = 'red'

So, the separate thread::

   >>> thread = threading.Thread(target=f)
   >>> thread.start()
   >>> thread.join()

affects what we see::

   >>> mydata.number
   11


.. class:: local()

   A class that represents thread-local data.


.. _thread-objects:

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
``__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.

If the :meth:`~Thread.run` method raises an exception,
:func:`threading.excepthook` is called to handle it. By default,
:func:`threading.excepthook` ignores silently :exc:`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 :attr:`~Thread.daemon` property or the *daemon* constructor
argument.

.. note::
   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 :ref:`joined <meth-thread-join>`.  They are never deleted,
since it is impossible to detect the termination of alien threads.


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

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

   *group* must be ``None`` as it is reserved for future extension when a
   :class:`!ThreadGroup` class is implemented.

   *target* is the callable object to be invoked by the :meth:`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.

   *context* is the :class:`~contextvars.Context` value to use when starting
   the thread.  The default value is ``None`` which indicates that the
   :data:`sys.flags.thread_inherit_context` flag controls the behaviour.  If
   the flag is true, threads will start with a copy of the context of the
   caller of :meth:`~Thread.start`.  If false, they will start with an empty
   context.  To explicitly start with an empty context, pass a new instance of
   :class:`~contextvars.Context()`.  To explicitly start with a copy of the
   current context, pass the value from :func:`~contextvars.copy_context`. The
   flag defaults true on free-threaded builds and false otherwise.

   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.

   .. versionchanged:: 3.3
      Added the *daemon* parameter.

   .. versionchanged:: 3.10
      Use the *target* name if *name* argument is omitted.

   .. versionchanged:: 3.14
      Added the *context* parameter.

   .. method:: start()

      Start the thread's activity.

      It must be called at most once per thread object.  It arranges for the
      object's :meth:`~Thread.run` method to be invoked in a separate thread
      of control.

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

      If supported, set the operating system thread name to
      :attr:`threading.Thread.name`. The name can be truncated depending on the
      operating system thread name limits.

      .. versionchanged:: 3.14
         Set the operating system thread name.

   .. method:: run()

      Method representing the thread's activity.

      You may override this method in a subclass.  The standard :meth:`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 :class:`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

   .. _meth-thread-join:

   .. method:: join(timeout=None)

      Wait until the thread terminates. This blocks the calling thread until
      the thread whose :meth:`~Thread.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
      real number specifying a timeout for the operation in seconds
      (or fractions thereof). As :meth:`~Thread.join` always returns ``None``,
      you must call :meth:`~Thread.is_alive` after :meth:`~Thread.join` to
      decide whether a timeout happened -- if the thread is still alive, the
      :meth:`~Thread.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.

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

      If an attempt is made to join a running daemonic thread in late stages
      of :term:`Python finalization <interpreter shutdown>` :meth:`!join`
      raises a :exc:`PythonFinalizationError`.

      .. versionchanged:: 3.14

         May raise :exc:`PythonFinalizationError`.

      .. versionchanged:: 3.15
         Accepts any real number as *timeout*, not only integer or float.

   .. attribute:: 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.)

   .. method:: getName()
               setName()

      Deprecated getter/setter API for :attr:`~Thread.name`; use it directly as a
      property instead.

      .. deprecated:: 3.10

   .. attribute:: ident

      The 'thread identifier' of this thread or ``None`` if the thread has not
      been started.  This is a nonzero integer.  See the :func:`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.

   .. attribute:: 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 :func:`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::

         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.

      .. versionadded:: 3.8

   .. method:: is_alive()

      Return whether the thread is alive.

      This method returns ``True`` just before the :meth:`~Thread.run` method
      starts until just after the :meth:`~Thread.run` method terminates.  The
      module function :func:`.enumerate` returns a list of all alive threads.

   .. attribute:: daemon

      A boolean value indicating whether this thread is a daemon thread (``True``)
      or not (``False``).  This must be set before :meth:`~Thread.start` is called,
      otherwise :exc:`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
      :attr:`~Thread.daemon` = ``False``.

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

   .. method:: isDaemon()
               setDaemon()

      Deprecated getter/setter API for :attr:`~Thread.daemon`; use it directly as a
      property instead.

      .. deprecated:: 3.10


.. _lock-objects:

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 management 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.


.. class:: 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.

   .. versionchanged:: 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.


   .. method:: acquire(blocking=True, timeout=-1)

      Acquire a lock, blocking or non-blocking.

      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 *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).

      .. versionchanged:: 3.2
         The *timeout* parameter is new.

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

      .. versionchanged:: 3.14
         Lock acquisition can now be interrupted by signals on Windows.

      .. versionchanged:: 3.15
         Accepts any real number as *timeout*, not only integer or float.


   .. method:: 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 :exc:`RuntimeError` is raised.

      There is no return value.

   .. method:: locked()

      Return ``True`` if the lock is acquired.



.. _rlock-objects:

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 :meth:`~RLock.acquire` method to lock it,
and its :meth:`~Lock.release` method to unlock it.

.. note::

  Reentrant locks support the :ref:`context management protocol <with-locks>`,
  so it is recommended to use :keyword:`with` instead of manually calling
  :meth:`~RLock.acquire` and :meth:`~RLock.release`
  to handle acquiring and releasing the lock for a block of code.

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

:meth:`~RLock.acquire`/:meth:`~RLock.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:: 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.


   .. method:: acquire(blocking=True, timeout=-1)

      Acquire a lock, blocking or non-blocking.

      .. seealso::

         :ref:`Using RLock as a context manager <with-locks>`
            Recommended over manual :meth:`!acquire` and :meth:`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 value.

         * If the same thread owns the lock, acquire the lock again, and
           return immediately. This is the difference between :class:`Lock` and
           :class:`!RLock`; :class:`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 :meth:`~RLock.release` as many times
      may lead to deadlock. Consider using :class:`!RLock` as a context manager rather than
      calling acquire/release directly.

      .. versionchanged:: 3.2
         The *timeout* parameter is new.

      .. versionchanged:: 3.15
         Accepts any real number as *timeout*, not only integer or float.


   .. method:: 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
      :exc:`RuntimeError` is raised if this method is called when the lock is
      not acquired.

      There is no return value.


   .. method:: locked()

      Return a boolean indicating whether this object is locked right now.

      .. versionadded:: 3.14


.. _condition-objects:

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 management 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():
           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 :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:
       cv.wait_for(an_item_is_available)
       get_an_available_item()

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.


.. class:: 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 :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.

   .. versionchanged:: 3.3
      changed from a factory function to a class.

   .. method:: acquire(*args)

      Acquire the underlying lock. This method calls the corresponding method on
      the underlying lock; the return value is whatever that method returns.

   .. method:: release()

      Release the underlying lock. This method calls the corresponding method on
      the underlying lock; there is no return value.

   .. method:: locked()

      Return a boolean indicating whether this object is locked right now.

      .. versionadded:: 3.14

   .. method:: 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 :exc:`RuntimeError` is
      raised.

      This method releases the underlying lock, and then blocks until it is
      awakened by a :meth:`notify` or :meth:`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
      real number specifying a timeout for the operation in seconds
      (or fractions thereof).

      When the underlying lock is an :class:`RLock`, it is not released using
      its :meth:`release` method, since this may not actually unlock the lock
      when it was acquired multiple times recursively.  Instead, an internal
      interface of the :class:`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``.

      .. versionchanged:: 3.2
         Previously, the method always returned ``None``.

   .. method:: 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 :meth:`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 :meth:`wait`: The lock must be
      held when called and is re-acquired on return.  The predicate is evaluated
      with the lock held.

      .. versionadded:: 3.2

   .. method:: 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
      :exc:`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 :meth:`wait`
      call until it can reacquire the lock.  Since :meth:`notify` does not
      release the lock, its caller should.

   .. method:: notify_all()

      Wake up all threads waiting on this condition.  This method acts like
      :meth:`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
      :exc:`RuntimeError` is raised.

      The method ``notifyAll`` is a deprecated alias for this method.


.. _semaphore-objects:

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 management protocol <with-locks>`.


.. class:: Semaphore(value=1)

   This class implements semaphore objects.  A semaphore manages an atomic
   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.

   .. versionchanged:: 3.3
      changed from a factory function to a class.

   .. method:: 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
        :meth:`~Semaphore.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 :meth:`~Semaphore.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.

      .. versionchanged:: 3.2
         The *timeout* parameter is new.

      .. versionchanged:: 3.15
         Accepts any real number as *timeout*, not only integer or float.

   .. method:: 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.

      .. versionchanged:: 3.9
         Added the *n* parameter to release multiple waiting threads at once.


.. class:: 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,
   :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.

   .. versionchanged:: 3.3
      changed from a factory function to a class.


.. _semaphore-examples:

: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:

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:: Event()

   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.

   .. versionchanged:: 3.3
      changed from a factory function to a class.

   .. method:: is_set()

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

      The method ``isSet`` is a deprecated alias for this method.

   .. method:: set()

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

   .. method:: clear()

      Reset the internal flag to false. Subsequently, threads calling
      :meth:`wait` will block until :meth:`.set` is called to set the internal
      flag to true again.

   .. method:: 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
      real number specifying a timeout for the operation in seconds,
      or fractions thereof.

      .. versionchanged:: 3.1
         Previously, the method always returned ``None``.


.. _timer-objects:

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:`Timer.start <Thread.start>`
method.  The timer can be stopped (before its action has begun) by calling the
:meth:`~Timer.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


.. class:: 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.

   .. versionchanged:: 3.3
      changed from a factory function to a class.

   .. method:: 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
^^^^^^^^^^^^^^^

.. versionadded:: 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 :meth:`~Barrier.wait` method and will block until
all of the threads have made their :meth:`~Barrier.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:: 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 :meth:`wait` method.

   .. 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 :class:`BrokenBarrierError` exception if the
      barrier is broken or reset while a thread is waiting.

   .. method:: reset()

      Return the barrier to the default, empty state.  Any threads waiting on it
      will receive the :class:`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.

   .. method:: abort()

      Put the barrier into a broken state.  This causes any active or future
      calls to :meth:`wait` to fail with the :class:`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.

   .. attribute:: parties

      The number of threads required to pass the barrier.

   .. attribute:: n_waiting

      The number of threads currently waiting in the barrier.

   .. attribute:: broken

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


.. exception:: BrokenBarrierError

   This exception, a subclass of :exc:`RuntimeError`, is raised when the
   :class:`Barrier` object is reset or broken.


.. _with-locks:

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

All of the objects provided by this module that have ``acquire`` and
``release`` methods can be used as context managers for a :keyword:`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...

is equivalent to::

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

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


Iterator synchronization
------------------------

By default, Python iterators do not support concurrent access. Most iterators make
no guarantees when accessed simultaneously from multiple threads. Generator
iterators, for example, raise :exc:`ValueError` if one of their iterator methods
is called while the generator is already executing. The tools in this section
allow reliable concurrency support to be added to ordinary iterators and
iterator-producing callables.

The :class:`serialize_iterator` wrapper lets multiple threads share a single iterator and
take turns consuming from it. While one thread is running ``__next__()``, the
others block until the iterator becomes available. Each value produced by the
underlying iterator is delivered to exactly one caller.

The :func:`concurrent_tee` function lets multiple threads each receive the full
stream of values from one underlying iterator. It creates independent iterators
that all draw from the same source. Values are buffered until consumed by all
of the derived iterators.

.. class:: serialize_iterator(iterable)

   Return an iterator wrapper that serializes concurrent calls to
   :meth:`~iterator.__next__` using a lock.

   If the wrapped iterator also defines :meth:`~generator.send`,
   :meth:`~generator.throw`, or :meth:`~generator.close`, those calls
   are serialized as well.

   This makes it possible to share a single iterator, including a generator
   iterator, between multiple threads. A lock ensures that calls are handled
   one at a time. No values are duplicated or skipped by the wrapper itself.
   Each item from the underlying iterator is given to exactly one caller.

   This wrapper does not copy or buffer values. Threads that call
   :func:`next` while another thread is already advancing the iterator will
   block until the active call completes.

   Example:

   .. code-block:: python

      import threading

      def squares(n):
          for x in range(n):
              yield x * x

      def consume(name, iterable):
          for item in iterable:
              print(name, item)

      source = threading.serialize_iterator(squares(5))

      t1 = threading.Thread(target=consume, args=("left", source))
      t2 = threading.Thread(target=consume, args=("right", source))
      t1.start()
      t2.start()
      t1.join()
      t2.join()

   In this example, each number is printed exactly once, but the work is shared
   between the two threads.

   .. versionadded:: 3.15


.. function:: synchronized_iterator(func)

   Wrap an iterator-producing callable so that each iterator it returns is
   automatically passed through :class:`serialize_iterator`.

   This is especially useful as a :term:`decorator` for generator functions,
   allowing their generator-iterators to be consumed from multiple threads.

   Example:

   .. code-block:: python

      import threading

      @threading.synchronized_iterator
      def squares(n):
          for x in range(n):
              yield x * x

      def consume(name, iterable):
          for item in iterable:
              print(name, item)

      source = squares(5)

      t1 = threading.Thread(target=consume, args=("left", source))
      t2 = threading.Thread(target=consume, args=("right", source))
      t1.start()
      t2.start()
      t1.join()
      t2.join()

   The returned wrapper preserves the metadata of *func*, such as its name and
   wrapped function reference.

   .. versionadded:: 3.15


.. function:: concurrent_tee(iterable, n=2)

   Return *n* independent iterators from a single input *iterable*, with
   guaranteed behavior when the derived iterators are consumed concurrently.

   This function is similar to :func:`itertools.tee`, but is intended for cases
   where the source iterator may feed consumers running in different threads.
   Each returned iterator yields every value from the underlying iterable, in
   the same order.

   Internally, values are buffered until every derived iterator has consumed
   them.

   The returned iterators share the same underlying synchronization lock. Each
   individual derived iterator is intended to be consumed by one thread at a
   time. If a single derived iterator must itself be shared by multiple
   threads, wrap it with :class:`serialize_iterator`.

   If *n* is ``0``, return an empty tuple. If *n* is negative, raise
   :exc:`ValueError`.

   Example:

   .. code-block:: python

      import threading

      def squares(n):
          for x in range(n):
              yield x * x

      def consume(name, iterable):
          for item in iterable:
              print(name, item)

      source = squares(5)
      left, right = threading.concurrent_tee(source)

      t1 = threading.Thread(target=consume, args=("left", left))
      t2 = threading.Thread(target=consume, args=("right", right))
      t1.start()
      t2.start()
      t1.join()
      t2.join()

   In this example, both consumer threads see the full sequence of squares
   from a single generator expression.

   .. versionadded:: 3.15