17.1. "threading" — Thread-based parallelism
********************************************

**Source code:** Lib/threading.py

======================================================================

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

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

Note: 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:

threading.active_count()

   Return the number of "Thread" objects currently alive.  The
   returned count is equal to the length of the list returned by
   "enumerate()".

threading.current_thread()

   Return the current "Thread" object, corresponding to the caller’s
   thread of control.  If the caller’s thread of control was not
   created through the "threading" module, a dummy thread object with
   limited functionality is returned.

threading.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.

   New in version 3.3.

threading.enumerate()

   Return a list of all "Thread" objects currently alive.  The list
   includes daemonic threads, dummy thread objects created by
   "current_thread()", and the main thread.  It excludes terminated
   threads and threads that have not yet been started.

threading.main_thread()

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

   New in version 3.4.

threading.settrace(func)

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

threading.setprofile(func)

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

threading.stack_size([size])

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

This module also defines the following constant:

threading.TIMEOUT_MAX

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

   New in version 3.2.

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

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

All of the methods described below are executed atomically.


17.1.1. Thread-Local Data
=========================

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

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

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

class threading.local

   A class that represents thread-local data.

   For more details and extensive examples, see the documentation
   string of the "_threading_local" module.


17.1.2. Thread Objects
======================

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

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

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

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

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

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

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 "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 "join()"ed.  They are never deleted, since it is impossible
to detect the termination of alien threads.

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

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

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

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

   *name* is the thread name.  By default, a unique name is
   constructed of the form “Thread-*N*” where *N* is a small decimal
   number.

   *args* is the argument tuple for the target invocation.  Defaults
   to "()".

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

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

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

   Changed in version 3.3: Added the *daemon* argument.

   start()

      Start the thread’s activity.

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

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

   run()

      Method representing the thread’s activity.

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

   join(timeout=None)

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

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

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

      A thread can be "join()"ed many times.

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

   name

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

   getName()
   setName()

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

   ident

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

   is_alive()

      Return whether the thread is alive.

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

   daemon

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

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

   isDaemon()
   setDaemon()

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

**CPython implementation detail:** 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.


17.1.3. Lock Objects
====================

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

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

Locks also support the context management protocol.

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

All methods are executed atomically.

class threading.Lock

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

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

   acquire(blocking=True, timeout=-1)

      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 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).

      Changed in version 3.2: The *timeout* parameter is new.

      Changed in 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.

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

      There is no return value.


17.1.4. RLock Objects
=====================

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

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

Reentrant locks also support the context management protocol.

class threading.RLock

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

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

   acquire(blocking=True, timeout=-1)

      Acquire a lock, blocking or non-blocking.

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

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

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

      When invoked with the floating-point *timeout* argument set to a
      positive value, block for at most the number of seconds
      specified by *timeout* and as long as the lock cannot be
      acquired.  Return true if the lock has been acquired, false if
      the timeout has elapsed.

      Changed in version 3.2: The *timeout* parameter is new.

   release()

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

      Only call this method when the calling thread owns the lock. A
      "RuntimeError" is raised if this method is called when the lock
      is unlocked.

      There is no return value.


17.1.5. Condition Objects
=========================

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

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

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

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

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

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

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

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

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

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

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

class threading.Condition(lock=None)

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

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

   Changed in 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".

      Changed in 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.

      New in version 3.2.

   notify(n=1)

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

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

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

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

   notify_all()

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


17.1.6. Semaphore Objects
=========================

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

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

Semaphores also support the context management protocol.

class threading.Semaphore(value=1)

   This class implements semaphore objects.  A semaphore manages 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.

   Changed in version 3.3: changed from a factory function to a class.

   acquire(blocking=True, timeout=None)

      Acquire a semaphore.

      When invoked without arguments:

      * If the internal counter is larger than zero on entry,
        decrement it by one and return 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.

      Changed in version 3.2: The *timeout* parameter is new.

   release()

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

class threading.BoundedSemaphore(value=1)

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

   Changed in version 3.3: changed from a factory function to a class.


17.1.6.1. "Semaphore" Example
-----------------------------

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

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

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

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

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


17.1.7. Event Objects
=====================

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

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

class threading.Event

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

   Changed in version 3.3: changed from a factory function to a class.

   is_set()

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

   set()

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

   clear()

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

   wait(timeout=None)

      Block until the internal flag is true.  If the internal flag is
      true on entry, return immediately.  Otherwise, block until
      another thread calls "set()" to set the flag to true, or until
      the optional timeout occurs.

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

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

      Changed in version 3.1: Previously, the method always returned
      "None".


17.1.8. Timer Objects
=====================

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

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

For example:

   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.

   Changed in version 3.3: changed from a factory function to a class.

   cancel()

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


17.1.9. Barrier Objects
=======================

New in 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 can require some external
      synchronization if there are other threads whose state is
      unknown.  If a barrier is broken it may be better to just leave
      it and create a new one.

   abort()

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

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

   parties

      The number of threads required to pass the barrier.

   n_waiting

      The number of threads currently waiting in the barrier.

   broken

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

exception threading.BrokenBarrierError

   This exception, a subclass of "RuntimeError", is raised when the
   "Barrier" object is reset or broken.


17.1.10. Using locks, conditions, and semaphores in the "with" statement
========================================================================

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

   with some_lock:
       # do something...

is equivalent to:

   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.
