16.2. "threading" — Higher-level threading interface
****************************************************

**Código Fonte:** Lib/threading.py

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

This module constructs higher-level threading interfaces on top of the
lower level "thread" module. See also the "mutex" and "Queue" modules.

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

Nota: Starting with Python 2.6, this module provides **PEP 8**
  compliant aliases and properties to replace the "camelCase" names
  that were inspired by Java’s threading API. This updated API is
  compatible with that of the "multiprocessing" module. However, no
  schedule has been set for the deprecation of the "camelCase" names
  and they remain fully supported in both Python 2.x and 3.x.

Nota: Starting with Python 2.5, several Thread methods raise
  "RuntimeError" instead of "AssertionError" if called erroneously.

**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". However, threading is still an appropriate
model if you want to run multiple I/O-bound tasks simultaneously.

This module defines the following functions and objects:

threading.active_count()
threading.activeCount()

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

   Alterado na versão 2.6: Added "active_count()" spelling.

threading.Condition()

   A factory function that returns a new condition variable object. A
   condition variable allows one or more threads to wait until they
   are notified by another thread.

   See Condition Objects.

threading.current_thread()
threading.currentThread()

   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.

   Alterado na versão 2.6: Added "current_thread()" spelling.

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.Event()

   A factory function that returns a new event object.  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.

   See Event Objects.

class threading.local

   A class that represents thread-local data.  Thread-local data are
   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.

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

   Novo na versão 2.4.

threading.Lock()

   A factory function that returns a new primitive lock object.  Once
   a thread has acquired it, subsequent attempts to acquire it block,
   until it is released; any thread may release it.

   See Lock Objects.

threading.RLock()

   A factory function that returns a new reentrant lock object. 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.

   See RLock Objects.

threading.Semaphore([value])

   A factory function that returns a new semaphore object.  A
   semaphore manages a counter representing the number of "release()"
   calls minus the number of "acquire()" calls, plus an initial value.
   The "acquire()" method blocks if necessary until it can return
   without making the counter negative.  If not given, *value*
   defaults to 1.

   See Semaphore Objects.

threading.BoundedSemaphore([value])

   A factory function that returns a new bounded semaphore object.  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.

class threading.Thread

   A class that represents a thread of control.  This class can be
   safely subclassed in a limited fashion.

   See Thread Objects.

class threading.Timer

   A thread that executes a function after a specified interval has
   passed.

   See Timer Objects.

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.

   Novo na versão 2.3.

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.

   Novo na versão 2.3.

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 "ThreadError" is raised.  If
   the specified stack size is invalid, a "ValueError" is raised and
   the stack size is unmodified.  32kB 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 > 32kB or requiring allocation in
   multiples of the system memory page size - platform documentation
   should be referred to for more information (4kB 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.

   Novo na versão 2.5.

exception threading.ThreadError

   Raised for various threading-related errors as described below.
   Note that many interfaces use "RuntimeError" instead of
   "ThreadError".

Detailed interfaces for the objects are documented 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.


16.2.1. Thread Objects
======================

This 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.

Nota: 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={})

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

   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])

      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 "isAlive()" 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 raises 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.

      Novo na versão 2.6.

   getName()
   setName()

      Pre-2.6 API for "name".

   ident

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

      Novo na versão 2.6.

   is_alive()
   isAlive()

      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.

      Alterado na versão 2.6: Added "is_alive()" spelling.

   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.

      Novo na versão 2.6.

   isDaemon()
   setDaemon()

      Pre-2.6 API for "daemon".


16.2.2. 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
"ThreadError" will be raised.

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.

Lock.acquire([blocking])

   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".

Lock.release()

   Release a 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 "ThreadError" is raised.

   There is no return value.

   locked()
   Return true if the lock is acquired.


16.2.3. 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.

RLock.acquire([blocking=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.

RLock.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.


16.2.4. 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.)

A condition variable has "acquire()" and "release()" methods that call
the corresponding methods of the associated lock. It also has a
"wait()" method, and "notify()" and "notifyAll()" methods.  These
three must only be called when the calling thread has acquired the
lock, otherwise a "RuntimeError" is raised.

The "wait()" method releases the lock, and then blocks until it is
awakened by a "notify()" or "notifyAll()" call for the same condition
variable in another thread.  Once awakened, it 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 "notifyAll()" method
wakes up all threads waiting for the condition variable.

Note: the "notify()" and "notifyAll()" 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 "notifyAll()" finally relinquishes ownership of the
lock.

Tip: 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 "notifyAll()" 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
   cv.acquire()
   while not an_item_is_available():
       cv.wait()
   get_an_available_item()
   cv.release()

   # Produce one item
   cv.acquire()
   make_an_item_available()
   cv.notify()
   cv.release()

To choose between "notify()" and "notifyAll()", 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])

   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.

   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])

      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 "notifyAll()" 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.

   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()
   notifyAll()

      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.

      Alterado na versão 2.6: Added "notify_all()" spelling.


16.2.5. 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 "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()".

class threading.Semaphore([value])

   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.

   acquire([blocking])

      Acquire a semaphore.

      When invoked without arguments: if the internal counter is
      larger than zero on entry, decrement it by one and return
      immediately.  If it is zero on entry, block, waiting until some
      other thread has called "release()" to make it larger than zero.
      This is done with proper interlocking so that if multiple
      "acquire()" calls are blocked, "release()" will wake exactly one
      of them up.  The implementation may pick one at random, so the
      order in which blocked threads are awakened should not be relied
      on.  There is no return value in this case.

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

      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.

   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.


16.2.5.1. Exemplo "Semaphore"
-----------------------------

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:

   pool_sema.acquire()
   conn = connectdb()
   ... use connection ...
   conn.close()
   pool_sema.release()

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.


16.2.6. 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

   The internal flag is initially false.

   is_set()
   isSet()

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

      Alterado na versão 2.6: Added "is_set()" spelling.

   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])

      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 the internal flag on exit, so it will always
      return "True" except if a timeout is given and the operation
      times out.

      Alterado na versão 2.7: Previously, the method always returned
      "None".


16.2.7. 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.

Por exemplo:

   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=[], kwargs={})

   Create a timer that will run *function* with arguments *args* and
   keyword arguments *kwargs*, after *interval* seconds have passed.

   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.


16.2.8. 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.

Currently, "Lock", "RLock", "Condition", "Semaphore", and
"BoundedSemaphore" objects may be used as "with" statement context
managers.  For example:

   import threading

   some_rlock = threading.RLock()

   with some_rlock:
       print "some_rlock is locked while this executes"


16.2.9. Importing in threaded code
==================================

While the import machinery is thread-safe, there are two key
restrictions on threaded imports due to inherent limitations in the
way that thread-safety is provided:

* Firstly, other than in the main module, an import should not have
  the side effect of spawning a new thread and then waiting for that
  thread in any way. Failing to abide by this restriction can lead to
  a deadlock if the spawned thread directly or indirectly attempts to
  import a module.

* Secondly, all import attempts must be completed before the
  interpreter starts shutting itself down. This can be most easily
  achieved by only performing imports from non-daemon threads created
  through the threading module. Daemon threads and threads created
  directly with the thread module will require some other form of
  synchronization to ensure they do not attempt imports after system
  shutdown has commenced. Failure to abide by this restriction will
  lead to intermittent exceptions and crashes during interpreter
  shutdown (as the late imports attempt to access machinery which is
  no longer in a valid state).
