本文整理汇总了Python中multiprocess.Pool.map_async方法的典型用法代码示例。如果您正苦于以下问题：Python Pool.map_async方法的具体用法？Python Pool.map_async怎么用？Python Pool.map_async使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类multiprocess.Pool的用法示例。
在下文中一共展示了Pool.map_async方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: fmultiprocess
# 需要导入模块: from multiprocess import Pool [as 别名]
# 或者: from multiprocess.Pool import map_async [as 别名]
def fmultiprocess(
log,
function,
inputArray,
poolSize=False,
timeout=3600,
**kwargs):
"""multiprocess pool
**Key Arguments:**
- ``log`` -- logger
- ``function`` -- the function to multiprocess
- ``inputArray`` -- the array to be iterated over
- ``poolSize`` -- limit the number of CPU that are used in multiprocess job
- ``timeout`` -- time in sec after which to raise a timeout error if the processes have not completed
**Return:**
- ``resultArray`` -- the array of results
**Usage:**
.. code-block:: python
from fundamentals import multiprocess
# DEFINE AN INPUT ARRAY
inputArray = range(10000)
results = multiprocess(log=log, function=functionName, poolSize=10, timeout=300,
inputArray=inputArray, otherFunctionKeyword="cheese")
"""
log.debug('starting the ``multiprocess`` function')
# DEFINTE POOL SIZE - NUMBER OF CPU CORES TO USE (BEST = ALL - 1)
if not poolSize:
poolSize = psutil.cpu_count()
if poolSize:
p = Pool(processes=poolSize)
else:
p = Pool()
cpuCount = psutil.cpu_count()
chunksize = int((len(inputArray) + 1) / (cpuCount * 3))
if chunksize == 0:
chunksize = 1
# MAP-REDUCE THE WORK OVER MULTIPLE CPU CORES
if "log" in inspect.getargspec(function)[0]:
mapfunc = partial(function, log=log, **kwargs)
resultArray = p.map_async(mapfunc, inputArray, chunksize=chunksize)
else:
mapfunc = partial(function, **kwargs)
resultArray = p.map_async(mapfunc, inputArray, chunksize=chunksize)
resultArray = resultArray.get(timeout=timeout)
p.close()
p.terminate()
log.debug('completed the ``multiprocess`` function')
return resultArray示例2: test
# 需要导入模块: from multiprocess import Pool [as 别名]
# 或者: from multiprocess.Pool import map_async [as 别名]
#.........这里部分代码省略.........
try:
sys.stdout.write('\n\t%s' % res.get(0.02))
break
except TimeoutError:
sys.stdout.write('.')
print()
print()
print('Testing IMapIterator.next() with timeout:', end='')
it = pool.imap(calculatestar, TASKS)
while 1:
sys.stdout.flush()
try:
sys.stdout.write('\n\t%s' % it.next(0.02))
except StopIteration:
break
except TimeoutError:
sys.stdout.write('.')
print()
print()
#
# Testing callback
#
print('Testing callback:')
A = []
B = [56, 0, 1, 8, 27, 64, 125, 216, 343, 512, 729]
r = pool.apply_async(mul, (7, 8), callback=A.append)
r.wait()
r = pool.map_async(pow3, range(10), callback=A.extend)
r.wait()
if A == B:
print('\tcallbacks succeeded\n')
else:
print('\t*** callbacks failed\n\t\t%s != %s\n' % (A, B))
#
# Check there are no outstanding tasks
#
assert not pool._cache, 'cache = %r' % pool._cache
#
# Check close() methods
#
print('Testing close():')
for worker in pool._pool:
assert worker.is_alive()
result = pool.apply_async(time.sleep, [0.5])
pool.close()
pool.join()
assert result.get() is None
for worker in pool._pool:
assert not worker.is_alive()
print('\tclose() succeeded\n')