terminate() Stops the worker processes immediately without completing outstanding work. When the pool object is garbage collected terminate() will be called immediately.

multiprocessing.pool.Pool.starmap_async()

starmap_async(func, iterable[, chunksize[, callback[, error_back]]]) A combination of starmap() and map_async() that iterates over iterable of iterables and calls func with the iterables unpacked. Returns a result object. New in version 3.3.

multiprocessing.pool.Pool.starmap()

starmap(func, iterable[, chunksize]) Like map() except that the elements of the iterable are expected to be iterables that are unpacked as arguments. Hence an iterable of [(1,2), (3, 4)] results in [func(1,2), func(3,4)]. New in version 3.3.

multiprocessing.pool.Pool.map_async()

map_async(func, iterable[, chunksize[, callback[, error_callback]]]) A variant of the map() method which returns a result object. If callback is specified then it should be a callable which accepts a single argument. When the result becomes ready callback is applied to it, that is unless the call failed, in which case the error_callback is applied instead. If error_callback is specified then it should be a callable which accepts a single argument. If the target function fails, then the error

multiprocessing.pool.Pool.map()

map(func, iterable[, chunksize]) A parallel equivalent of the map() built-in function (it supports only one iterable argument though). It blocks until the result is ready. This method chops the iterable into a number of chunks which it submits to the process pool as separate tasks. The (approximate) size of these chunks can be specified by setting chunksize to a positive integer.

multiprocessing.pool.Pool.join()

join() Wait for the worker processes to exit. One must call close() or terminate() before using join().

multiprocessing.pool.Pool.imap_unordered()

imap_unordered(func, iterable[, chunksize]) The same as imap() except that the ordering of the results from the returned iterator should be considered arbitrary. (Only when there is only one worker process is the order guaranteed to be “correct”.)

multiprocessing.pool.Pool.imap()

imap(func, iterable[, chunksize]) A lazier version of map(). The chunksize argument is the same as the one used by the map() method. For very long iterables using a large value for chunksize can make the job complete much faster than using the default value of 1. Also if chunksize is 1 then the next() method of the iterator returned by the imap() method has an optional timeout parameter: next(timeout) will raise multiprocessing.TimeoutError if the result cannot be returned within timeout sec

multiprocessing.pool.Pool.close()

close() Prevents any more tasks from being submitted to the pool. Once all the tasks have been completed the worker processes will exit.

multiprocessing.pool.Pool.apply_async()

apply_async(func[, args[, kwds[, callback[, error_callback]]]]) A variant of the apply() method which returns a result object. If callback is specified then it should be a callable which accepts a single argument. When the result becomes ready callback is applied to it, that is unless the call failed, in which case the error_callback is applied instead. If error_callback is specified then it should be a callable which accepts a single argument. If the target function fails, then the error_ca