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-rw-r--r--Lib/multiprocessing/pool.py32
1 files changed, 30 insertions, 2 deletions
diff --git a/Lib/multiprocessing/pool.py b/Lib/multiprocessing/pool.py
index 0c29e64..7039d16 100644
--- a/Lib/multiprocessing/pool.py
+++ b/Lib/multiprocessing/pool.py
@@ -64,6 +64,9 @@ job_counter = itertools.count()
def mapstar(args):
return list(map(*args))
+def starmapstar(args):
+ return list(itertools.starmap(args[0], args[1]))
+
#
# Code run by worker processes
#
@@ -248,7 +251,25 @@ class Pool(object):
in a list that is returned.
'''
assert self._state == RUN
- return self.map_async(func, iterable, chunksize).get()
+ return self._map_async(func, iterable, mapstar, chunksize).get()
+
+ def starmap(self, func, iterable, chunksize=None):
+ '''
+ Like `map()` method but the elements of the `iterable` are expected to
+ be iterables as well and will be unpacked as arguments. Hence
+ `func` and (a, b) becomes func(a, b).
+ '''
+ assert self._state == RUN
+ return self._map_async(func, iterable, starmapstar, chunksize).get()
+
+ def starmap_async(self, func, iterable, chunksize=None, callback=None,
+ error_callback=None):
+ '''
+ Asynchronous version of `starmap()` method.
+ '''
+ assert self._state == RUN
+ return self._map_async(func, iterable, starmapstar, chunksize,
+ callback, error_callback)
def imap(self, func, iterable, chunksize=1):
'''
@@ -302,6 +323,13 @@ class Pool(object):
Asynchronous version of `map()` method.
'''
assert self._state == RUN
+ return self._map_async(func, iterable, mapstar, chunksize)
+
+ def _map_async(self, func, iterable, mapper, chunksize=None, callback=None,
+ error_callback=None):
+ '''
+ Helper function to implement map, starmap and their async counterparts.
+ '''
if not hasattr(iterable, '__len__'):
iterable = list(iterable)
@@ -315,7 +343,7 @@ class Pool(object):
task_batches = Pool._get_tasks(func, iterable, chunksize)
result = MapResult(self._cache, chunksize, len(iterable), callback,
error_callback=error_callback)
- self._taskqueue.put((((result._job, i, mapstar, (x,), {})
+ self._taskqueue.put((((result._job, i, mapper, (x,), {})
for i, x in enumerate(task_batches)), None))
return result