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<!DOCTYPE html>

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<title>concurrent.futures --- Launching parallel tasks — مستندات Python3.14.6</title><meta name="viewport" content="width=device-width, initial-scale=1.0">

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<li><a class="reference internal" href="#"><code class="xref py py-mod docutils literal notranslate">concurrent.futures</code> --- Launching parallel tasks</a><ul>

<li><a class="reference internal" href="#executor-objects">Executor Objects</a></li>

<li><a class="reference internal" href="#threadpoolexecutor">ThreadPoolExecutor</a><ul>

<li><a class="reference internal" href="#threadpoolexecutor-example">ThreadPoolExecutor Example</a></li>

</ul>

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<li><a class="reference internal" href="#interpreterpoolexecutor">InterpreterPoolExecutor</a></li>

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<li><a class="reference internal" href="#processpoolexecutor-example">ProcessPoolExecutor Example</a></li>

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<h1><code class="xref py py-mod docutils literal notranslate">concurrent.futures</code> --- Launching parallel tasks<a class="headerlink" href="#module-concurrent.futures" title="Link to this heading">¶</a></h1>

Added in version 3.2.

</div>

Source code: <a class="extlink-source reference external" href="https://github.com/python/cpython/tree/3.14/Lib/concurrent/futures/thread.py">Lib/concurrent/futures/thread.py</a>,

<a class="extlink-source reference external" href="https://github.com/python/cpython/tree/3.14/Lib/concurrent/futures/process.py">Lib/concurrent/futures/process.py</a>,

and <a class="extlink-source reference external" href="https://github.com/python/cpython/tree/3.14/Lib/concurrent/futures/interpreter.py">Lib/concurrent/futures/interpreter.py</a>

The <code class="xref py py-mod docutils literal notranslate">concurrent.futures</code> module provides a high-level interface for

asynchronously executing callables.

The asynchronous execution can be performed with threads, using

<a class="reference internal" href="#concurrent.futures.ThreadPoolExecutor" title="concurrent.futures.ThreadPoolExecutor"><code class="xref py py-class docutils literal notranslate">ThreadPoolExecutor</code></a> or <a class="reference internal" href="#concurrent.futures.InterpreterPoolExecutor" title="concurrent.futures.InterpreterPoolExecutor"><code class="xref py py-class docutils literal notranslate">InterpreterPoolExecutor</code></a>,

or separate processes, using <a class="reference internal" href="#concurrent.futures.ProcessPoolExecutor" title="concurrent.futures.ProcessPoolExecutor"><code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code></a>.

Each implements the same interface, which is defined

by the abstract <a class="reference internal" href="#concurrent.futures.Executor" title="concurrent.futures.Executor"><code class="xref py py-class docutils literal notranslate">Executor</code></a> class.

<a class="reference internal" href="#concurrent.futures.Future" title="concurrent.futures.Future"><code class="xref py py-class docutils literal notranslate">concurrent.futures.Future</code></a> must not be confused with

<a class="reference internal" href="asyncio-future.html#asyncio.Future" title="asyncio.Future"><code class="xref py py-class docutils literal notranslate">asyncio.Future</code></a>, which is designed for use with <a class="reference internal" href="asyncio.html#module-asyncio" title="asyncio: Asynchronous I/O."><code class="xref py py-mod docutils literal notranslate">asyncio</code></a>

tasks and coroutines. See the <a class="reference internal" href="asyncio-future.html">asyncio's Future</a>

documentation for a detailed comparison of the two.

<a class="reference internal" href="intro.html#availability">در دسترس بودن</a>: not WASI.

This module does not work or is not available on WebAssembly. See

<a class="reference internal" href="intro.html#wasm-availability">WebAssembly platforms</a> for more information.

</div>

<h2>Executor Objects<a class="headerlink" href="#executor-objects" title="Link to this heading">¶</a></h2>

<dd>An abstract class that provides methods to execute calls asynchronously. It

should not be used directly, but through its concrete subclasses.

submit(fn, <abbr title="Positional-only parameter separator (PEP 570)">/</abbr>, *args, **kwargs)<a class="headerlink" href="#concurrent.futures.Executor.submit" title="Link to this definition">¶</a></dt>

<dd>Schedules the callable, fn, to be executed as <code class="docutils literal notranslate">fn(*args, **kwargs)</code>

and returns a <a class="reference internal" href="#concurrent.futures.Future" title="concurrent.futures.Future"><code class="xref py py-class docutils literal notranslate">Future</code></a> object representing the execution of the

callable.

<div class="highlight-python3 notranslate"><div class="highlight"><pre>with ThreadPoolExecutor(max_workers=1) as executor:

future = executor.submit(pow, 323, 1235)

print(future.result())

</pre></div>

</div>

</dd></dl>

map(fn, *iterables, timeout=None, chunksize=1, buffersize=None)<a class="headerlink" href="#concurrent.futures.Executor.map" title="Link to this definition">¶</a></dt>

<dd>Similar to <a class="reference internal" href="functions.html#map" title="map"><code class="xref py py-func docutils literal notranslate">map(fn, *iterables)</code></a> except:

<li>The iterables are collected immediately rather than lazily, unless a

buffersize is specified to limit the number of submitted tasks whose

results have not yet been yielded. If the buffer is full, iteration over

the iterables pauses until a result is yielded from the buffer.</li>

<li>fn is executed asynchronously and several calls to

fn may be made concurrently.</li>

</ul>

The returned iterator raises a <a class="reference internal" href="exceptions.html#TimeoutError" title="TimeoutError"><code class="xref py py-exc docutils literal notranslate">TimeoutError</code></a>

if <a class="reference internal" href="stdtypes.html#iterator.__next__" title="iterator.__next__"><code class="xref py py-meth docutils literal notranslate">__next__()</code></a> is called and the result isn't available

after timeout seconds from the original call to <code class="xref py py-meth docutils literal notranslate">Executor.map()</code>.

timeout can be an int or a float. If timeout is not specified or

<code class="docutils literal notranslate">None</code>, there is no limit to the wait time.

If a fn call raises an exception, then that exception will be

raised when its value is retrieved from the iterator.

When using <a class="reference internal" href="#concurrent.futures.ProcessPoolExecutor" title="concurrent.futures.ProcessPoolExecutor"><code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code></a>, this method chops iterables

into a number of chunks which it submits to the pool as separate

tasks. The (approximate) size of these chunks can be specified by

setting chunksize to a positive integer. For very long iterables,

using a large value for chunksize can significantly improve

performance compared to the default size of 1. With

<a class="reference internal" href="#concurrent.futures.ThreadPoolExecutor" title="concurrent.futures.ThreadPoolExecutor"><code class="xref py py-class docutils literal notranslate">ThreadPoolExecutor</code></a> and <a class="reference internal" href="#concurrent.futures.InterpreterPoolExecutor" title="concurrent.futures.InterpreterPoolExecutor"><code class="xref py py-class docutils literal notranslate">InterpreterPoolExecutor</code></a>,

chunksize has no effect.

تغییر داده شده در نسخه 3.5: Added the chunksize parameter.

</div>

تغییر داده شده در نسخه 3.14: Added the buffersize parameter.

</div>

</dd></dl>

shutdown(wait=True, <abbr title="Keyword-only parameters separator (PEP 3102)">*</abbr>, cancel_futures=False)<a class="headerlink" href="#concurrent.futures.Executor.shutdown" title="Link to this definition">¶</a></dt>

<dd>Signal the executor that it should free any resources that it is using

when the currently pending futures are done executing. Calls to

<a class="reference internal" href="#concurrent.futures.Executor.submit" title="concurrent.futures.Executor.submit"><code class="xref py py-meth docutils literal notranslate">Executor.submit()</code></a> and <a class="reference internal" href="#concurrent.futures.Executor.map" title="concurrent.futures.Executor.map"><code class="xref py py-meth docutils literal notranslate">Executor.map()</code></a> made after shutdown will

raise <a class="reference internal" href="exceptions.html#RuntimeError" title="RuntimeError"><code class="xref py py-exc docutils literal notranslate">RuntimeError</code></a>.

If wait is <code class="docutils literal notranslate">True</code> then this method will not return until all the

pending futures are done executing and the resources associated with the

executor have been freed. If wait is <code class="docutils literal notranslate">False</code> then this method will

return immediately and the resources associated with the executor will be

freed when all pending futures are done executing. Regardless of the

value of wait, the entire Python program will not exit until all

pending futures are done executing.

If cancel_futures is <code class="docutils literal notranslate">True</code>, this method will cancel all pending

futures that the executor has not started running. Any futures that

are completed or running won't be cancelled, regardless of the value

of cancel_futures.

If both cancel_futures and wait are <code class="docutils literal notranslate">True</code>, all futures that the

executor has started running will be completed prior to this method

returning. The remaining futures are cancelled.

You can avoid having to call this method explicitly if you use the executor

as a <a class="reference internal" href="../glossary.html#term-context-manager">context manager</a> via the <a class="reference internal" href="../reference/compound_stmts.html#with"><code class="xref std std-keyword docutils literal notranslate">with</code></a> statement, which

will shutdown the <code class="xref py py-class docutils literal notranslate">Executor</code> (waiting as if <code class="xref py py-meth docutils literal notranslate">Executor.shutdown()</code>

were called with wait set to <code class="docutils literal notranslate">True</code>):

<div class="highlight-python3 notranslate"><div class="highlight"><pre>import shutil

with ThreadPoolExecutor(max_workers=4) as e:

e.submit(shutil.copy, 'src1.txt', 'dest1.txt')

e.submit(shutil.copy, 'src2.txt', 'dest2.txt')

e.submit(shutil.copy, 'src3.txt', 'dest3.txt')

e.submit(shutil.copy, 'src4.txt', 'dest4.txt')

</pre></div>

</div>

تغییر داده شده در نسخه 3.9: Added cancel_futures.

</div>

</dd></dl>

</section>

<h2>ThreadPoolExecutor<a class="headerlink" href="#threadpoolexecutor" title="Link to this heading">¶</a></h2>

<a class="reference internal" href="#concurrent.futures.ThreadPoolExecutor" title="concurrent.futures.ThreadPoolExecutor"><code class="xref py py-class docutils literal notranslate">ThreadPoolExecutor</code></a> is an <a class="reference internal" href="#concurrent.futures.Executor" title="concurrent.futures.Executor"><code class="xref py py-class docutils literal notranslate">Executor</code></a> subclass that uses a pool of

threads to execute calls asynchronously.

Deadlocks can occur when the callable associated with a <a class="reference internal" href="#concurrent.futures.Future" title="concurrent.futures.Future"><code class="xref py py-class docutils literal notranslate">Future</code></a> waits on

the results of another <code class="xref py py-class docutils literal notranslate">Future</code>. For example:

<div class="highlight-python3 notranslate"><div class="highlight"><pre>import time

def wait_on_b():

time.sleep(5)

print(b.result()) # b will never complete because it is waiting on a.

return 5

def wait_on_a():

time.sleep(5)

print(a.result()) # a will never complete because it is waiting on b.

return 6

executor = ThreadPoolExecutor(max_workers=2)

a = executor.submit(wait_on_b)

b = executor.submit(wait_on_a)

</pre></div>

</div>

And:

<div class="highlight-python3 notranslate"><div class="highlight"><pre>def wait_on_future():

f = executor.submit(pow, 5, 2)

# This will never complete because there is only one worker thread and

# it is executing this function.

print(f.result())

# Note: calling future.result() would also cause a deadlock because

# the single worker thread is already waiting for wait_on_future().

</pre></div>

</div>

class concurrent.futures.ThreadPoolExecutor(max_workers=None, thread_name_prefix='', initializer=None, initargs=())<a class="headerlink" href="#concurrent.futures.ThreadPoolExecutor" title="Link to this definition">¶</a></dt>

<dd>An <a class="reference internal" href="#concurrent.futures.Executor" title="concurrent.futures.Executor"><code class="xref py py-class docutils literal notranslate">Executor</code></a> subclass that uses a pool of at most max_workers

threads to execute calls asynchronously.

All threads enqueued to <code class="docutils literal notranslate">ThreadPoolExecutor</code> will be joined before the

interpreter can exit. Note that the exit handler which does this is

executed before any exit handlers added using <code class="docutils literal notranslate">atexit</code>. This means

exceptions in the main thread must be caught and handled in order to

signal threads to exit gracefully. For this reason, it is recommended

that <code class="docutils literal notranslate">ThreadPoolExecutor</code> not be used for long-running tasks.

initializer is an optional callable that is called at the start of

each worker thread; initargs is a tuple of arguments passed to the

initializer. Should initializer raise an exception, all currently

pending jobs will raise a <a class="reference internal" href="#concurrent.futures.thread.BrokenThreadPool" title="concurrent.futures.thread.BrokenThreadPool"><code class="xref py py-exc docutils literal notranslate">BrokenThreadPool</code></a>,

as well as any attempt to submit more jobs to the pool.

تغییر داده شده در نسخه 3.5: If max_workers is <code class="docutils literal notranslate">None</code> or

not given, it will default to the number of processors on the machine,

multiplied by <code class="docutils literal notranslate">5</code>, assuming that <code class="xref py py-class docutils literal notranslate">ThreadPoolExecutor</code> is often

used to overlap I/O instead of CPU work and the number of workers

should be higher than the number of workers

for <a class="reference internal" href="#concurrent.futures.ProcessPoolExecutor" title="concurrent.futures.ProcessPoolExecutor"><code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code></a>.

</div>

تغییر داده شده در نسخه 3.6: Added the thread_name_prefix parameter to allow users to

control the <a class="reference internal" href="threading.html#threading.Thread" title="threading.Thread"><code class="xref py py-class docutils literal notranslate">threading.Thread</code></a> names for worker threads created by

the pool for easier debugging.

</div>

تغییر داده شده در نسخه 3.7: Added the initializer and initargs arguments.

</div>

تغییر داده شده در نسخه 3.8: Default value of max_workers is changed to <code class="docutils literal notranslate">min(32, os.cpu_count() + 4)</code>.

This default value preserves at least 5 workers for I/O bound tasks.

It utilizes at most 32 CPU cores for CPU bound tasks which release the GIL.

And it avoids using very large resources implicitly on many-core machines.

ThreadPoolExecutor now reuses idle worker threads before starting

max_workers worker threads too.

</div>

تغییر داده شده در نسخه 3.13: Default value of max_workers is changed to

<code class="docutils literal notranslate">min(32, (os.process_cpu_count() or 1) + 4)</code>.

</div>

</dd></dl>

<h3>ThreadPoolExecutor Example<a class="headerlink" href="#threadpoolexecutor-example" title="Link to this heading">¶</a></h3>

<div class="highlight-python3 notranslate"><div class="highlight"><pre>import concurrent.futures

import urllib.request

URLS = ['http://www.foxnews.com/',

'http://www.cnn.com/',

'http://europe.wsj.com/',

'http://www.bbc.co.uk/',

'http://nonexistent-subdomain.python.org/']

# Retrieve a single page and report the URL and contents

def load_url(url, timeout):

with urllib.request.urlopen(url, timeout=timeout) as conn:

return conn.read()

# We can use a with statement to ensure threads are cleaned up promptly

with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:

# Start the load operations and mark each future with its URL

future_to_url = {executor.submit(load_url, url, 60): url for url in URLS}

for future in concurrent.futures.as_completed(future_to_url):

url = future_to_url[future]

try:

data = future.result()

except Exception as exc:

print('%r generated an exception: %s' % (url, exc))

else:

print('%r page is %d bytes' % (url, len(data)))

</pre></div>

</div>

</section>

<h2>InterpreterPoolExecutor<a class="headerlink" href="#interpreterpoolexecutor" title="Link to this heading">¶</a></h2>

Added in version 3.14.

</div>

The <a class="reference internal" href="#concurrent.futures.InterpreterPoolExecutor" title="concurrent.futures.InterpreterPoolExecutor"><code class="xref py py-class docutils literal notranslate">InterpreterPoolExecutor</code></a> class uses a pool of interpreters

to execute calls asynchronously. It is a <a class="reference internal" href="#concurrent.futures.ThreadPoolExecutor" title="concurrent.futures.ThreadPoolExecutor"><code class="xref py py-class docutils literal notranslate">ThreadPoolExecutor</code></a>

subclass, which means each worker is running in its own thread.

The difference here is that each worker has its own interpreter,

and runs each task using that interpreter.

The biggest benefit to using interpreters instead of only threads

is true multi-core parallelism. Each interpreter has its own

<a class="reference internal" href="../glossary.html#term-global-interpreter-lock">Global Interpreter Lock</a>, so code

running in one interpreter can run on one CPU core, while code in

another interpreter runs unblocked on a different core.

The tradeoff is that writing concurrent code for use with multiple

interpreters can take extra effort. However, this is because it

forces you to be deliberate about how and when interpreters interact,

and to be explicit about what data is shared between interpreters.

This results in several benefits that help balance the extra effort,

including true multi-core parallelism, For example, code written

this way can make it easier to reason about concurrency. Another

major benefit is that you don't have to deal with several of the

big pain points of using threads, like race conditions.

Each worker's interpreter is isolated from all the other interpreters.

"Isolated" means each interpreter has its own runtime state and

operates completely independently. For example, if you redirect

<a class="reference internal" href="sys.html#sys.stdout" title="sys.stdout"><code class="xref py py-data docutils literal notranslate">sys.stdout</code></a> in one interpreter, it will not be automatically

redirected to any other interpreter. If you import a module in one

interpreter, it is not automatically imported in any other. You

would need to import the module separately in interpreter where

you need it. In fact, each module imported in an interpreter is

a completely separate object from the same module in a different

interpreter, including <a class="reference internal" href="sys.html#module-sys" title="sys: Access system-specific parameters and functions."><code class="xref py py-mod docutils literal notranslate">sys</code></a>, <a class="reference internal" href="builtins.html#module-builtins" title="builtins: The module that provides the built-in namespace."><code class="xref py py-mod docutils literal notranslate">builtins</code></a>,

and even <code class="docutils literal notranslate">__main__</code>.

Isolation means a mutable object, or other data, cannot be used

by more than one interpreter at the same time. That effectively means

interpreters cannot actually share such objects or data. Instead,

each interpreter must have its own copy, and you will have to

synchronize any changes between the copies manually. Immutable

objects and data, like the builtin singletons, strings, and tuples

of immutable objects, don't have these limitations.

Communicating and synchronizing between interpreters is most effectively

done using dedicated tools, like those proposed in <a class="pep reference external" href="https://peps.python.org/pep-0734/">PEP 734</a>. One less

efficient alternative is to serialize with <a class="reference internal" href="pickle.html#module-pickle" title="pickle: Convert Python objects to streams of bytes and back."><code class="xref py py-mod docutils literal notranslate">pickle</code></a> and then send

the bytes over a shared <a class="reference internal" href="socket.html#module-socket" title="socket: Low-level networking interface."><code class="xref py py-mod docutils literal notranslate">socket</code></a> or

<a class="reference internal" href="os.html#os.pipe" title="os.pipe"><code class="xref py py-func docutils literal notranslate">pipe</code></a>.

class concurrent.futures.InterpreterPoolExecutor(max_workers=None, thread_name_prefix='', initializer=None, initargs=())<a class="headerlink" href="#concurrent.futures.InterpreterPoolExecutor" title="Link to this definition">¶</a></dt>

<dd>A <a class="reference internal" href="#concurrent.futures.ThreadPoolExecutor" title="concurrent.futures.ThreadPoolExecutor"><code class="xref py py-class docutils literal notranslate">ThreadPoolExecutor</code></a> subclass that executes calls asynchronously

using a pool of at most max_workers threads. Each thread runs

tasks in its own interpreter. The worker interpreters are isolated

from each other, which means each has its own runtime state and that

they can't share any mutable objects or other data. Each interpreter

has its own <a class="reference internal" href="../glossary.html#term-global-interpreter-lock">Global Interpreter Lock</a>,

which means code run with this executor has true multi-core parallelism.

The optional initializer and initargs arguments have the same

meaning as for <code class="xref py py-class docutils literal notranslate">ThreadPoolExecutor</code>: the initializer is run

when each worker is created, though in this case it is run in

the worker's interpreter. The executor serializes the initializer

and initargs using <a class="reference internal" href="pickle.html#module-pickle" title="pickle: Convert Python objects to streams of bytes and back."><code class="xref py py-mod docutils literal notranslate">pickle</code></a> when sending them to the worker's

interpreter.

توجه

The executor may replace uncaught exceptions from initializer

with <a class="reference internal" href="concurrent.interpreters.html#concurrent.interpreters.ExecutionFailed" title="concurrent.interpreters.ExecutionFailed"><code class="xref py py-class docutils literal notranslate">ExecutionFailed</code></a>.

</div>

Other caveats from parent <a class="reference internal" href="#concurrent.futures.ThreadPoolExecutor" title="concurrent.futures.ThreadPoolExecutor"><code class="xref py py-class docutils literal notranslate">ThreadPoolExecutor</code></a> apply here.

</dd></dl>

<a class="reference internal" href="#concurrent.futures.Executor.submit" title="concurrent.futures.Executor.submit"><code class="xref py py-meth docutils literal notranslate">submit()</code></a> and <a class="reference internal" href="#concurrent.futures.Executor.map" title="concurrent.futures.Executor.map"><code class="xref py py-meth docutils literal notranslate">map()</code></a> work like normal,

except the worker serializes the callable and arguments using

<a class="reference internal" href="pickle.html#module-pickle" title="pickle: Convert Python objects to streams of bytes and back."><code class="xref py py-mod docutils literal notranslate">pickle</code></a> when sending them to its interpreter. The worker

likewise serializes the return value when sending it back.

When a worker's current task raises an uncaught exception, the worker

always tries to preserve the exception as-is. If that is successful

then it also sets the <code class="docutils literal notranslate">__cause__</code> to a corresponding

<a class="reference internal" href="concurrent.interpreters.html#concurrent.interpreters.ExecutionFailed" title="concurrent.interpreters.ExecutionFailed"><code class="xref py py-class docutils literal notranslate">ExecutionFailed</code></a>

instance, which contains a summary of the original exception.

In the uncommon case that the worker is not able to preserve the

original as-is then it directly preserves the corresponding

<code class="xref py py-class docutils literal notranslate">ExecutionFailed</code>

instance instead.

</section>

<h2>ProcessPoolExecutor<a class="headerlink" href="#processpoolexecutor" title="Link to this heading">¶</a></h2>

The <a class="reference internal" href="#concurrent.futures.ProcessPoolExecutor" title="concurrent.futures.ProcessPoolExecutor"><code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code></a> class is an <a class="reference internal" href="#concurrent.futures.Executor" title="concurrent.futures.Executor"><code class="xref py py-class docutils literal notranslate">Executor</code></a> subclass that

uses a pool of processes to execute calls asynchronously.

<code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code> uses the <a class="reference internal" href="multiprocessing.html#module-multiprocessing" title="multiprocessing: Process-based parallelism."><code class="xref py py-mod docutils literal notranslate">multiprocessing</code></a> module, which

allows it to side-step the <a class="reference internal" href="../glossary.html#term-global-interpreter-lock">Global Interpreter Lock</a> but also means that

only picklable objects can be executed and returned.

The <code class="docutils literal notranslate">__main__</code> module must be importable by worker subprocesses. This means

that <a class="reference internal" href="#concurrent.futures.ProcessPoolExecutor" title="concurrent.futures.ProcessPoolExecutor"><code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code></a> will not work in the interactive interpreter.

Calling <a class="reference internal" href="#concurrent.futures.Executor" title="concurrent.futures.Executor"><code class="xref py py-class docutils literal notranslate">Executor</code></a> or <a class="reference internal" href="#concurrent.futures.Future" title="concurrent.futures.Future"><code class="xref py py-class docutils literal notranslate">Future</code></a> methods from a callable submitted

to a <a class="reference internal" href="#concurrent.futures.ProcessPoolExecutor" title="concurrent.futures.ProcessPoolExecutor"><code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code></a> will result in deadlock.

Note that the restrictions on functions and arguments needing to picklable as

per <a class="reference internal" href="multiprocessing.html#multiprocessing.Process" title="multiprocessing.Process"><code class="xref py py-class docutils literal notranslate">multiprocessing.Process</code></a> apply when using <a class="reference internal" href="#concurrent.futures.Executor.submit" title="concurrent.futures.Executor.submit"><code class="xref py py-meth docutils literal notranslate">submit()</code></a>

and <a class="reference internal" href="#concurrent.futures.Executor.map" title="concurrent.futures.Executor.map"><code class="xref py py-meth docutils literal notranslate">map()</code></a> on a <a class="reference internal" href="#concurrent.futures.ProcessPoolExecutor" title="concurrent.futures.ProcessPoolExecutor"><code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code></a>. A function defined

in a REPL or a lambda should not be expected to work.

class concurrent.futures.ProcessPoolExecutor(max_workers=None, mp_context=None, initializer=None, initargs=(), max_tasks_per_child=None)<a class="headerlink" href="#concurrent.futures.ProcessPoolExecutor" title="Link to this definition">¶</a></dt>

of at most max_workers processes. If max_workers is <code class="docutils literal notranslate">None</code> or not

given, it will default to <a class="reference internal" href="os.html#os.process_cpu_count" title="os.process_cpu_count"><code class="xref py py-func docutils literal notranslate">os.process_cpu_count()</code></a>.

If max_workers is less than or equal to <code class="docutils literal notranslate">0</code>, then a <a class="reference internal" href="exceptions.html#ValueError" title="ValueError"><code class="xref py py-exc docutils literal notranslate">ValueError</code></a>

will be raised.

On Windows, max_workers must be less than or equal to <code class="docutils literal notranslate">61</code>. If it is not

then <code class="xref py py-exc docutils literal notranslate">ValueError</code> will be raised. If max_workers is <code class="docutils literal notranslate">None</code>, then

the default chosen will be at most <code class="docutils literal notranslate">61</code>, even if more processors are

available.

mp_context can be a <a class="reference internal" href="multiprocessing.html#module-multiprocessing" title="multiprocessing: Process-based parallelism."><code class="xref py py-mod docutils literal notranslate">multiprocessing</code></a> context or <code class="docutils literal notranslate">None</code>. It will be

used to launch the workers. If mp_context is <code class="docutils literal notranslate">None</code> or not given, the

default <code class="xref py py-mod docutils literal notranslate">multiprocessing</code> context is used.

See <a class="reference internal" href="multiprocessing.html#multiprocessing-start-methods">Contexts and start methods</a>.

initializer is an optional callable that is called at the start of

each worker process; initargs is a tuple of arguments passed to the

initializer. Should initializer raise an exception, all currently

pending jobs will raise a <a class="reference internal" href="#concurrent.futures.process.BrokenProcessPool" title="concurrent.futures.process.BrokenProcessPool"><code class="xref py py-exc docutils literal notranslate">BrokenProcessPool</code></a>,

as well as any attempt to submit more jobs to the pool.

max_tasks_per_child is an optional argument that specifies the maximum

number of tasks a single process can execute before it will exit and be

replaced with a fresh worker process. By default max_tasks_per_child is

<code class="docutils literal notranslate">None</code> which means worker processes will live as long as the pool. When

a max is specified, the "spawn" multiprocessing start method will be used by

default in absence of a mp_context parameter. This feature is incompatible

with the "fork" start method.

توجه

Bugs have been reported when using the max_tasks_per_child feature that

can result in the <code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code> hanging in some

circumstances. Follow its eventual resolution in <a class="reference external" href="https://github.com/python/cpython/issues/115634">gh-115634</a>.

</div>

تغییر داده شده در نسخه 3.3: When one of the worker processes terminates abruptly, a

<a class="reference internal" href="#concurrent.futures.process.BrokenProcessPool" title="concurrent.futures.process.BrokenProcessPool"><code class="xref py py-exc docutils literal notranslate">BrokenProcessPool</code></a> error is now raised.

Previously, behaviour

was undefined but operations on the executor or its futures would often

freeze or deadlock.

</div>

تغییر داده شده در نسخه 3.7: The mp_context argument was added to allow users to control the

start_method for worker processes created by the pool.

Added the initializer and initargs arguments.

</div>

تغییر داده شده در نسخه 3.11: The max_tasks_per_child argument was added to allow users to

control the lifetime of workers in the pool.

</div>

تغییر داده شده در نسخه 3.12: On POSIX systems, if your application has multiple threads and the

<a class="reference internal" href="multiprocessing.html#module-multiprocessing" title="multiprocessing: Process-based parallelism."><code class="xref py py-mod docutils literal notranslate">multiprocessing</code></a> context uses the <code class="docutils literal notranslate">"fork"</code> start method:

The <a class="reference internal" href="os.html#os.fork" title="os.fork"><code class="xref py py-func docutils literal notranslate">os.fork()</code></a> function called internally to spawn workers may raise a

<a class="reference internal" href="exceptions.html#DeprecationWarning" title="DeprecationWarning"><code class="xref py py-exc docutils literal notranslate">DeprecationWarning</code></a>. Pass a mp_context configured to use a

different start method. See the <code class="xref py py-func docutils literal notranslate">os.fork()</code> documentation for

further explanation.

</div>

تغییر داده شده در نسخه 3.13: max_workers uses <a class="reference internal" href="os.html#os.process_cpu_count" title="os.process_cpu_count"><code class="xref py py-func docutils literal notranslate">os.process_cpu_count()</code></a> by default, instead of

<a class="reference internal" href="os.html#os.cpu_count" title="os.cpu_count"><code class="xref py py-func docutils literal notranslate">os.cpu_count()</code></a>.

</div>

تغییر داده شده در نسخه 3.14: The default process start method (see

<a class="reference internal" href="multiprocessing.html#multiprocessing-start-methods">Contexts and start methods</a>) changed away from fork. If you

require the fork start method for <code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code> you must

explicitly pass <code class="docutils literal notranslate">mp_context=multiprocessing.get_context("fork")</code>.

</div>

terminate_workers()<a class="headerlink" href="#concurrent.futures.ProcessPoolExecutor.terminate_workers" title="Link to this definition">¶</a></dt>

<dd>Attempt to terminate all living worker processes immediately by calling

<a class="reference internal" href="multiprocessing.html#multiprocessing.Process.terminate" title="multiprocessing.Process.terminate"><code class="xref py py-meth docutils literal notranslate">Process.terminate</code></a> on each of them.

Internally, it will also call <a class="reference internal" href="#concurrent.futures.Executor.shutdown" title="concurrent.futures.Executor.shutdown"><code class="xref py py-meth docutils literal notranslate">Executor.shutdown()</code></a> to ensure that all

other resources associated with the executor are freed.

After calling this method the caller should no longer submit tasks to the

executor.

Added in version 3.14.

</div>

</dd></dl>

kill_workers()<a class="headerlink" href="#concurrent.futures.ProcessPoolExecutor.kill_workers" title="Link to this definition">¶</a></dt>

<dd>Attempt to kill all living worker processes immediately by calling

<a class="reference internal" href="multiprocessing.html#multiprocessing.Process.kill" title="multiprocessing.Process.kill"><code class="xref py py-meth docutils literal notranslate">Process.kill</code></a> on each of them.

other resources associated with the executor are freed.

After calling this method the caller should no longer submit tasks to the

executor.

Added in version 3.14.

</div>

</dd></dl>

<h3>ProcessPoolExecutor Example<a class="headerlink" href="#processpoolexecutor-example" title="Link to this heading">¶</a></h3>

<div class="highlight-python3 notranslate"><div class="highlight"><pre>import concurrent.futures

import math

PRIMES = [

112272535095293,

112582705942171,

112272535095293,

115280095190773,

115797848077099,

1099726899285419]

def is_prime(n):

if n < 2:

return False

if n == 2:

return True

if n % 2 == 0:

return False

sqrt_n = int(math.floor(math.sqrt(n)))

for i in range(3, sqrt_n + 1, 2):

if n % i == 0:

return False

return True

def main():

with concurrent.futures.ProcessPoolExecutor() as executor:

for number, prime in zip(PRIMES, executor.map(is_prime, PRIMES)):

print('%d is prime: %s' % (number, prime))

if __name__ == '__main__':

main()

</pre></div>

</div>

</section>

<h2>Future Objects<a class="headerlink" href="#future-objects" title="Link to this heading">¶</a></h2>

The <a class="reference internal" href="#concurrent.futures.Future" title="concurrent.futures.Future"><code class="xref py py-class docutils literal notranslate">Future</code></a> class encapsulates the asynchronous execution of a callable.

<code class="xref py py-class docutils literal notranslate">Future</code> instances are created by <a class="reference internal" href="#concurrent.futures.Executor.submit" title="concurrent.futures.Executor.submit"><code class="xref py py-meth docutils literal notranslate">Executor.submit()</code></a>.

<dd>Encapsulates the asynchronous execution of a callable. <code class="xref py py-class docutils literal notranslate">Future</code>

instances are created by <a class="reference internal" href="#concurrent.futures.Executor.submit" title="concurrent.futures.Executor.submit"><code class="xref py py-meth docutils literal notranslate">Executor.submit()</code></a> and should not be created

directly except for testing.

cancel()<a class="headerlink" href="#concurrent.futures.Future.cancel" title="Link to this definition">¶</a></dt>

<dd>Attempt to cancel the call. If the call is currently being executed or

finished running and cannot be cancelled then the method will return

<code class="docutils literal notranslate">False</code>, otherwise the call will be cancelled and the method will

return <code class="docutils literal notranslate">True</code>.

</dd></dl>

cancelled()<a class="headerlink" href="#concurrent.futures.Future.cancelled" title="Link to this definition">¶</a></dt>

<dd>Return <code class="docutils literal notranslate">True</code> if the call was successfully cancelled.

</dd></dl>

running()<a class="headerlink" href="#concurrent.futures.Future.running" title="Link to this definition">¶</a></dt>

<dd>Return <code class="docutils literal notranslate">True</code> if the call is currently being executed and cannot be

cancelled.

</dd></dl>

done()<a class="headerlink" href="#concurrent.futures.Future.done" title="Link to this definition">¶</a></dt>

<dd>Return <code class="docutils literal notranslate">True</code> if the call was successfully cancelled or finished

running.

</dd></dl>

result(timeout=None)<a class="headerlink" href="#concurrent.futures.Future.result" title="Link to this definition">¶</a></dt>

<dd>Return the value returned by the call. If the call hasn't yet completed

then this method will wait up to timeout seconds. If the call hasn't

completed in timeout seconds, then a

<a class="reference internal" href="exceptions.html#TimeoutError" title="TimeoutError"><code class="xref py py-exc docutils literal notranslate">TimeoutError</code></a> will be raised. timeout can be

an int or float. If timeout is not specified or <code class="docutils literal notranslate">None</code>, there is no

limit to the wait time.

If the future is cancelled before completing then <a class="reference internal" href="#concurrent.futures.CancelledError" title="concurrent.futures.CancelledError"><code class="xref py py-exc docutils literal notranslate">CancelledError</code></a>

will be raised.

If the call raised an exception, this method will raise the same exception.

</dd></dl>

exception(timeout=None)<a class="headerlink" href="#concurrent.futures.Future.exception" title="Link to this definition">¶</a></dt>

<dd>Return the exception raised by the call. If the call hasn't yet

completed then this method will wait up to timeout seconds. If the

call hasn't completed in timeout seconds, then a

an int or float. If timeout is not specified or <code class="docutils literal notranslate">None</code>, there is no

limit to the wait time.

will be raised.

If the call completed without raising, <code class="docutils literal notranslate">None</code> is returned.

</dd></dl>

add_done_callback(fn)<a class="headerlink" href="#concurrent.futures.Future.add_done_callback" title="Link to this definition">¶</a></dt>

<dd>Attaches the callable fn to the future. fn will be called, with the

future as its only argument, when the future is cancelled or finishes

running.

Added callables are called in the order that they were added and are

always called in a thread belonging to the process that added them. If

the callable raises an <a class="reference internal" href="exceptions.html#Exception" title="Exception"><code class="xref py py-exc docutils literal notranslate">Exception</code></a> subclass, it will be logged and

ignored. If the callable raises a <a class="reference internal" href="exceptions.html#BaseException" title="BaseException"><code class="xref py py-exc docutils literal notranslate">BaseException</code></a> subclass, the

behavior is undefined.

If the future has already completed or been cancelled, fn will be

called immediately.

</dd></dl>

The following <code class="xref py py-class docutils literal notranslate">Future</code> methods are meant for use in unit tests and

<a class="reference internal" href="#concurrent.futures.Executor" title="concurrent.futures.Executor"><code class="xref py py-class docutils literal notranslate">Executor</code></a> implementations.

set_running_or_notify_cancel()<a class="headerlink" href="#concurrent.futures.Future.set_running_or_notify_cancel" title="Link to this definition">¶</a></dt>

<dd>This method should only be called by <a class="reference internal" href="#concurrent.futures.Executor" title="concurrent.futures.Executor"><code class="xref py py-class docutils literal notranslate">Executor</code></a> implementations

before executing the work associated with the <code class="xref py py-class docutils literal notranslate">Future</code> and by unit

tests.

If the method returns <code class="docutils literal notranslate">False</code> then the <code class="xref py py-class docutils literal notranslate">Future</code> was cancelled,

i.e. <a class="reference internal" href="#concurrent.futures.Future.cancel" title="concurrent.futures.Future.cancel"><code class="xref py py-meth docutils literal notranslate">Future.cancel()</code></a> was called and returned <code class="docutils literal notranslate">True</code>. Any threads

waiting on the <code class="xref py py-class docutils literal notranslate">Future</code> completing (i.e. through

<a class="reference internal" href="#concurrent.futures.as_completed" title="concurrent.futures.as_completed"><code class="xref py py-func docutils literal notranslate">as_completed()</code></a> or <a class="reference internal" href="#concurrent.futures.wait" title="concurrent.futures.wait"><code class="xref py py-func docutils literal notranslate">wait()</code></a>) will be woken up.

If the method returns <code class="docutils literal notranslate">True</code> then the <code class="xref py py-class docutils literal notranslate">Future</code> was not cancelled

and has been put in the running state, i.e. calls to

<a class="reference internal" href="#concurrent.futures.Future.running" title="concurrent.futures.Future.running"><code class="xref py py-meth docutils literal notranslate">Future.running()</code></a> will return <code class="docutils literal notranslate">True</code>.

This method can only be called once and cannot be called after

<a class="reference internal" href="#concurrent.futures.Future.set_result" title="concurrent.futures.Future.set_result"><code class="xref py py-meth docutils literal notranslate">Future.set_result()</code></a> or <a class="reference internal" href="#concurrent.futures.Future.set_exception" title="concurrent.futures.Future.set_exception"><code class="xref py py-meth docutils literal notranslate">Future.set_exception()</code></a> have been

called.

</dd></dl>

set_result(result)<a class="headerlink" href="#concurrent.futures.Future.set_result" title="Link to this definition">¶</a></dt>

<dd>Sets the result of the work associated with the <code class="xref py py-class docutils literal notranslate">Future</code> to

result.

This method should only be used by <a class="reference internal" href="#concurrent.futures.Executor" title="concurrent.futures.Executor"><code class="xref py py-class docutils literal notranslate">Executor</code></a> implementations and

unit tests.

تغییر داده شده در نسخه 3.8: This method raises

<a class="reference internal" href="#concurrent.futures.InvalidStateError" title="concurrent.futures.InvalidStateError"><code class="xref py py-exc docutils literal notranslate">concurrent.futures.InvalidStateError</code></a> if the <code class="xref py py-class docutils literal notranslate">Future</code> is

already done.

</div>

</dd></dl>

set_exception(exception)<a class="headerlink" href="#concurrent.futures.Future.set_exception" title="Link to this definition">¶</a></dt>

<dd>Sets the result of the work associated with the <code class="xref py py-class docutils literal notranslate">Future</code> to the

<a class="reference internal" href="exceptions.html#Exception" title="Exception"><code class="xref py py-class docutils literal notranslate">Exception</code></a> exception.

unit tests.

تغییر داده شده در نسخه 3.8: This method raises

already done.

</div>

</dd></dl>

</section>

<h2>Module Functions<a class="headerlink" href="#module-functions" title="Link to this heading">¶</a></h2>

concurrent.futures.wait(fs, timeout=None, return_when=ALL_COMPLETED)<a class="headerlink" href="#concurrent.futures.wait" title="Link to this definition">¶</a></dt>

<dd>Wait for the <a class="reference internal" href="#concurrent.futures.Future" title="concurrent.futures.Future"><code class="xref py py-class docutils literal notranslate">Future</code></a> instances (possibly created by different

given to fs are removed and will be returned only once. Returns a named

2-tuple of sets. The first set, named <code class="docutils literal notranslate">done</code>, contains the futures that

completed (finished or cancelled futures) before the wait completed. The

second set, named <code class="docutils literal notranslate">not_done</code>, contains the futures that did not complete

(pending or running futures).

timeout can be used to control the maximum number of seconds to wait before

returning. timeout can be an int or float. If timeout is not specified

or <code class="docutils literal notranslate">None</code>, there is no limit to the wait time.

return_when indicates when this function should return. It must be one of

the following constants:

<thead>

<tr class="row-odd"><th class="head">Constant</th>

<th class="head">Description</th>

</tr>

</thead>

<tbody>

concurrent.futures.FIRST_COMPLETED<a class="headerlink" href="#concurrent.futures.FIRST_COMPLETED" title="Link to this definition">¶</a></dt>

</td>

<td>The function will return when any future finishes or is cancelled.</td>

</tr>

concurrent.futures.FIRST_EXCEPTION<a class="headerlink" href="#concurrent.futures.FIRST_EXCEPTION" title="Link to this definition">¶</a></dt>

</td>

<td>The function will return when any future finishes by raising an

exception. If no future raises an exception

then it is equivalent to <a class="reference internal" href="#concurrent.futures.ALL_COMPLETED" title="concurrent.futures.ALL_COMPLETED"><code class="xref py py-const docutils literal notranslate">ALL_COMPLETED</code></a>.</td>

</tr>

concurrent.futures.ALL_COMPLETED<a class="headerlink" href="#concurrent.futures.ALL_COMPLETED" title="Link to this definition">¶</a></dt>

</td>

<td>The function will return when all futures finish or are cancelled.</td>

</tr>

</tbody>

</table>

</dd></dl>

concurrent.futures.as_completed(fs, timeout=None)<a class="headerlink" href="#concurrent.futures.as_completed" title="Link to this definition">¶</a></dt>

<dd>Returns an iterator over the <a class="reference internal" href="#concurrent.futures.Future" title="concurrent.futures.Future"><code class="xref py py-class docutils literal notranslate">Future</code></a> instances (possibly created by

different <a class="reference internal" href="#concurrent.futures.Executor" title="concurrent.futures.Executor"><code class="xref py py-class docutils literal notranslate">Executor</code></a> instances) given by fs that yields futures as

they complete (finished or cancelled futures). Any futures given by fs that

are duplicated will be returned once. Any futures that completed before

<code class="xref py py-func docutils literal notranslate">as_completed()</code> is called will be yielded first. The returned iterator

raises a <a class="reference internal" href="exceptions.html#TimeoutError" title="TimeoutError"><code class="xref py py-exc docutils literal notranslate">TimeoutError</code></a> if <a class="reference internal" href="stdtypes.html#iterator.__next__" title="iterator.__next__"><code class="xref py py-meth docutils literal notranslate">__next__()</code></a>

is called and the result isn't available after timeout seconds from the

original call to <code class="xref py py-func docutils literal notranslate">as_completed()</code>. timeout can be an int or float. If

timeout is not specified or <code class="docutils literal notranslate">None</code>, there is no limit to the wait time.

</dd></dl>

همچنین ملاحظه نمائید

<dt><a class="pep reference external" href="https://peps.python.org/pep-3148/">PEP 3148</a> -- futures - execute computations asynchronously</dt><dd>The proposal which described this feature for inclusion in the Python

standard library.

</dd>

</dl>

</div>

</section>

<h2>Exception classes<a class="headerlink" href="#exception-classes" title="Link to this heading">¶</a></h2>

exception concurrent.futures.CancelledError<a class="headerlink" href="#concurrent.futures.CancelledError" title="Link to this definition">¶</a></dt>

<dd>Raised when a future is cancelled.

</dd></dl>

exception concurrent.futures.TimeoutError<a class="headerlink" href="#concurrent.futures.TimeoutError" title="Link to this definition">¶</a></dt>

<dd>A deprecated alias of <code class="xref py py-exc docutils literal notranslate">TimeoutError</code>,

raised when a future operation exceeds the given timeout.

تغییر داده شده در نسخه 3.11: This class was made an alias of <code class="xref py py-exc docutils literal notranslate">TimeoutError</code>.

</div>

</dd></dl>

exception concurrent.futures.BrokenExecutor<a class="headerlink" href="#concurrent.futures.BrokenExecutor" title="Link to this definition">¶</a></dt>

<dd>Derived from <a class="reference internal" href="exceptions.html#RuntimeError" title="RuntimeError"><code class="xref py py-exc docutils literal notranslate">RuntimeError</code></a>, this exception class is raised

when an executor is broken for some reason, and cannot be used

to submit or execute new tasks.

Added in version 3.7.

</div>

</dd></dl>

exception concurrent.futures.InvalidStateError<a class="headerlink" href="#concurrent.futures.InvalidStateError" title="Link to this definition">¶</a></dt>

<dd>Raised when an operation is performed on a future that is not allowed

in the current state.

Added in version 3.8.

</div>

</dd></dl>

exception concurrent.futures.thread.BrokenThreadPool<a class="headerlink" href="#concurrent.futures.thread.BrokenThreadPool" title="Link to this definition">¶</a></dt>

<dd>Derived from <a class="reference internal" href="#concurrent.futures.BrokenExecutor" title="concurrent.futures.BrokenExecutor"><code class="xref py py-exc docutils literal notranslate">BrokenExecutor</code></a>, this exception

class is raised when one of the workers

of a <a class="reference internal" href="#concurrent.futures.ThreadPoolExecutor" title="concurrent.futures.ThreadPoolExecutor"><code class="xref py py-class docutils literal notranslate">ThreadPoolExecutor</code></a>

has failed initializing.

Added in version 3.7.

</div>

</dd></dl>

exception concurrent.futures.interpreter.BrokenInterpreterPool<a class="headerlink" href="#concurrent.futures.interpreter.BrokenInterpreterPool" title="Link to this definition">¶</a></dt>

<dd>Derived from <a class="reference internal" href="#concurrent.futures.thread.BrokenThreadPool" title="concurrent.futures.thread.BrokenThreadPool"><code class="xref py py-exc docutils literal notranslate">BrokenThreadPool</code></a>,

this exception class is raised when one of the workers

of a <a class="reference internal" href="#concurrent.futures.InterpreterPoolExecutor" title="concurrent.futures.InterpreterPoolExecutor"><code class="xref py py-class docutils literal notranslate">InterpreterPoolExecutor</code></a>

has failed initializing.

Added in version 3.14.

</div>

</dd></dl>

exception concurrent.futures.process.BrokenProcessPool<a class="headerlink" href="#concurrent.futures.process.BrokenProcessPool" title="Link to this definition">¶</a></dt>

<a class="reference internal" href="exceptions.html#RuntimeError" title="RuntimeError"><code class="xref py py-exc docutils literal notranslate">RuntimeError</code></a>), this exception class is raised when one of the

workers of a <a class="reference internal" href="#concurrent.futures.ProcessPoolExecutor" title="concurrent.futures.ProcessPoolExecutor"><code class="xref py py-class docutils literal notranslate">ProcessPoolExecutor</code></a>

has terminated in a non-clean

fashion (for example, if it was killed from the outside).

Added in version 3.3.

</div>

</dd></dl>

</section>

</div>

<div>

<h3><a href="../contents.html">فهرست عناوین</a></h3>

<ul>

<li><a class="reference internal" href="#"><code class="xref py py-mod docutils literal notranslate">concurrent.futures</code> --- Launching parallel tasks</a><ul>

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