Quickstart
from concurrent import futures
def fib(n):
if n == 0 or n == 1:
return 1
return fib(n-1) + fib(n-2)
# base
with futures.ThreadPoolExecutor() as executor:
f1 = executor.submit(fib, 4) # return future
f2 = executor.submit(fib, 5)
print(f1.result())
print(f2.result())
FIBS = [3, 7, 10, 20]
# advance
with futures.ThreadPoolExecutor(max_workers=5) as executor:
future_to_num = {executor.submit(fib, num): num for num in FIBS}
for future in futures.as_completed(future_to_num):
print(future.result(), future_to_num[future])
# map
with futures.ThreadPoolExecutor(max_workers=5) as executor:
for num, res in zip(FIBS, executor.map(fib, FIBS)):
print(num, res)
HOW-TO
通過(guò)改變max_workers 來(lái)提速
通過(guò)改變chunksize 來(lái)加速
chunksize表示每個(gè)進(jìn)程完成多少次函數(shù)計(jì)算之后 會(huì)被殺死掉 默認(rèn)是1個(gè)
FIBS = [1, 3, 5, 7] * 5
def do_calculate(chunksize=1):
with futures.ProcessPoolExecutor(max_workers=5) as executor:
for num, ret in zip(FIBS, executor.map(fib, FIBS, chunksize=chunksize)):
pass
def main():
for num in FIBS:
fib(num)
(3.6) ~/Documents/code/zhangyu/learn_python/test_concurrent master ● python -m perf timeit 'from concur import do_calculate,main;do_calculate(5)' --quiet
Mean +- std dev: 28.4 ms +- 0.8 ms
(3.6) ~/Documents/code/zhangyu/learn_python/test_concurrent master ● python -m perf timeit 'from concur import do_calculate,main;do_calculate(1)' --quiet
Mean +- std dev: 19.1 ms +- 1.3 ms
(3.6) ~/Documents/code/zhangyu/learn_python/test_concurrent master ● python -m perf timeit 'from concur import do_calculate,main;do_calculate(3)' --quiet
Mean +- std dev: 15.2 ms +- 0.7 ms
(3.6) ~/Documents/code/zhangyu/learn_python/test_concurrent master ● python -m perf timeit 'from concur import do_calculate,main;do_calculate(30)' --quiet
Mean +- std dev: 13.8 ms +- 0.6 ms
(3.6) ~/Documents/code/zhangyu/learn_python/test_concurrent master ● python -m perf timeit 'from concur import do_calculate,main;main()' --quiet
Mean +- std dev: 64.9 us +- 1.6 us
