Source code: Lib/concurrent/futures/thread.py
and Lib/concurrent/futures/process.py
The concurrent.futures module provides a high-level interface for
asynchronously executing callables.
The asynchronous execution can be performed with threads, using
ThreadPoolExecutor, or separate processes, using
ProcessPoolExecutor. Both implement the same interface, which is
defined by the abstract Executor class.
17.4.1. Executor Objects
-
class
concurrent.futures.Executor
An abstract class that provides methods to execute calls asynchronously. It
should not be used directly, but through its concrete subclasses.
-
submit(fn, *args, **kwargs)
Schedules the callable, fn, to be executed as fn(*args **kwargs)
and returns a Future object representing the execution of the
callable.
with ThreadPoolExecutor(max_workers=1) as executor:
future = executor.submit(pow, 323, 1235)
print(future.result())
-
map(func, *iterables, timeout=None, chunksize=1)
Similar to map(func, *iterables) except:
- the iterables are collected immediately rather than lazily;
- func is executed asynchronously and several calls to
func may be made concurrently.
The returned iterator raises a concurrent.futures.TimeoutError
if __next__() is called and the result isn’t available
after timeout seconds from the original call to Executor.map().
timeout can be an int or a float. If timeout is not specified or
None, there is no limit to the wait time.
If a func call raises an exception, then that exception will be
raised when its value is retrieved from the iterator.
When using ProcessPoolExecutor, 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
ThreadPoolExecutor, chunksize has no effect.
Changed in version 3.5: Added the chunksize argument.
-
shutdown(wait=True)
Signal the executor that it should free any resources that it is using
when the currently pending futures are done executing. Calls to
Executor.submit() and Executor.map() made after shutdown will
raise RuntimeError.
If wait is True 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 False 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.
You can avoid having to call this method explicitly if you use the
with statement, which will shutdown the Executor
(waiting as if Executor.shutdown() were called with wait set to
True):
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')
17.4.2. ThreadPoolExecutor
ThreadPoolExecutor is an Executor subclass that uses a pool of
threads to execute calls asynchronously.
Deadlocks can occur when the callable associated with a Future waits on
the results of another Future. For example:
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)
And:
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())
executor = ThreadPoolExecutor(max_workers=1)
executor.submit(wait_on_future)
-
class
concurrent.futures.ThreadPoolExecutor(max_workers=None, thread_name_prefix='')
An Executor subclass that uses a pool of at most max_workers
threads to execute calls asynchronously.
Changed in version 3.5: If max_workers is None or
not given, it will default to the number of processors on the machine,
multiplied by 5, assuming that ThreadPoolExecutor 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 ProcessPoolExecutor.
New in version 3.6: The thread_name_prefix argument was added to allow users to
control the threading.Thread names for worker threads created by
the pool for easier debugging.
17.4.2.1. ThreadPoolExecutor Example
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://some-made-up-domain.com/']
# 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)))
17.4.3. ProcessPoolExecutor
The ProcessPoolExecutor class is an Executor subclass that
uses a pool of processes to execute calls asynchronously.
ProcessPoolExecutor uses the multiprocessing module, which
allows it to side-step the Global Interpreter Lock but also means that
only picklable objects can be executed and returned.
The __main__ module must be importable by worker subprocesses. This means
that ProcessPoolExecutor will not work in the interactive interpreter.
Calling Executor or Future methods from a callable submitted
to a ProcessPoolExecutor will result in deadlock.
-
class
concurrent.futures.ProcessPoolExecutor(max_workers=None)
An Executor subclass that executes calls asynchronously using a pool
of at most max_workers processes. If max_workers is None or not
given, it will default to the number of processors on the machine.
If max_workers is lower or equal to 0, then a ValueError
will be raised.
Changed in version 3.3: When one of the worker processes terminates abruptly, a
BrokenProcessPool error is now raised. Previously, behaviour
was undefined but operations on the executor or its futures would often
freeze or deadlock.
17.4.3.1. ProcessPoolExecutor Example
import concurrent.futures
import math
PRIMES = [
112272535095293,
112582705942171,
112272535095293,
115280095190773,
115797848077099,
1099726899285419]
def is_prime(n):
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()
17.4.4. Future Objects
The Future class encapsulates the asynchronous execution of a callable.
Future instances are created by Executor.submit().
-
class
concurrent.futures.Future
Encapsulates the asynchronous execution of a callable. Future
instances are created by Executor.submit() and should not be created
directly except for testing.
-
cancel()
Attempt to cancel the call. If the call is currently being executed and
cannot be cancelled then the method will return False, otherwise the
call will be cancelled and the method will return True.
-
cancelled()
Return True if the call was successfully cancelled.
-
running()
Return True if the call is currently being executed and cannot be
cancelled.
-
done()
Return True if the call was successfully cancelled or finished
running.
-
result(timeout=None)
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
concurrent.futures.TimeoutError will be raised. timeout can be
an int or float. If timeout is not specified or None, there is no
limit to the wait time.
If the future is cancelled before completing then CancelledError
will be raised.
If the call raised, this method will raise the same exception.
-
exception(timeout=None)
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
concurrent.futures.TimeoutError will be raised. timeout can be
an int or float. If timeout is not specified or None, there is no
limit to the wait time.
If the future is cancelled before completing then CancelledError
will be raised.
If the call completed without raising, None is returned.
-
add_done_callback(fn)
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 Exception subclass, it will be logged and
ignored. If the callable raises a BaseException subclass, the
behavior is undefined.
If the future has already completed or been cancelled, fn will be
called immediately.
The following Future methods are meant for use in unit tests and
Executor implementations.
-
set_running_or_notify_cancel()
This method should only be called by Executor implementations
before executing the work associated with the Future and by unit
tests.
If the method returns False then the Future was cancelled,
i.e. Future.cancel() was called and returned True. Any threads
waiting on the Future completing (i.e. through
as_completed() or wait()) will be woken up.
If the method returns True then the Future was not cancelled
and has been put in the running state, i.e. calls to
Future.running() will return True.
This method can only be called once and cannot be called after
Future.set_result() or Future.set_exception() have been
called.
-
set_result(result)
Sets the result of the work associated with the Future to
result.
This method should only be used by Executor implementations and
unit tests.
-
set_exception(exception)
Sets the result of the work associated with the Future to the
Exception exception.
This method should only be used by Executor implementations and
unit tests.
17.4.5. Module Functions
-
concurrent.futures.wait(fs, timeout=None, return_when=ALL_COMPLETED)
Wait for the Future instances (possibly created by different
Executor instances) given by fs to complete. Returns a named
2-tuple of sets. The first set, named done, contains the futures that
completed (finished or were cancelled) before the wait completed. The second
set, named not_done, contains uncompleted 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 None, there is no limit to the wait time.
return_when indicates when this function should return. It must be one of
the following constants:
| Constant |
Description |
FIRST_COMPLETED |
The function will return when any
future finishes or is cancelled. |
FIRST_EXCEPTION |
The function will return when any
future finishes by raising an
exception. If no future raises an
exception then it is equivalent to
ALL_COMPLETED. |
ALL_COMPLETED |
The function will return when all
futures finish or are cancelled. |
-
concurrent.futures.as_completed(fs, timeout=None)
Returns an iterator over the Future instances (possibly created by
different Executor instances) given by fs that yields futures as
they complete (finished or were cancelled). Any futures given by fs that
are duplicated will be returned once. Any futures that completed before
as_completed() is called will be yielded first. The returned iterator
raises a concurrent.futures.TimeoutError if __next__()
is called and the result isn’t available after timeout seconds from the
original call to as_completed(). timeout can be an int or float. If
timeout is not specified or None, there is no limit to the wait time.
See also
- PEP 3148 – futures - execute computations asynchronously
- The proposal which described this feature for inclusion in the Python
standard library.
17.4.6. Exception classes
-
exception
concurrent.futures.CancelledError
Raised when a future is cancelled.
-
exception
concurrent.futures.TimeoutError
Raised when a future operation exceeds the given timeout.
-
exception
concurrent.futures.process.BrokenProcessPool
Derived from RuntimeError, this exception class is raised when
one of the workers of a ProcessPoolExecutor has terminated
in a non-clean fashion (for example, if it was killed from the outside).