我有以下功能
from multiprocessing import Pool
def do_comparison(tupl):
x, y = tupl # unpack arguments
return compare_clusters(x, y)
def distance_matrix(clusters, condensed=False):
pool = Pool()
values = pool.map_async(do_comparison, itertools.combinations(clusters, 2)).get()
do stuff
是否可以打印pool.map_async(do_comparison, itertools.combinations(clusters, 2)).get()
的进度?
我通过像这样向 do_comparison 添加计数来尝试
count = 0
def do_comparison(tupl):
global count
count += 1
if count % 1000 == 0:
print count
x, y = tupl # unpack arguments
return compare_clusters(x, y)
但除了它看起来不是一个好的解决方案之外,数字直到脚本结束才会打印。有什么好的方法吗?
最佳答案
我按如下方式跟踪进度:
import multiprocessing
import time
class PoolProgress:
def __init__(self,pool,update_interval=3):
self.pool = pool
self.update_interval = update_interval
def track(self, job):
task = self.pool._cache[job._job]
while task._number_left>0:
print("Tasks remaining = {0}".format(task._number_left*task._chunksize))
time.sleep(self.update_interval)
def hi(x): #This must be defined before `p` if we are to use in the interpreter
time.sleep(x//2)
return x
a = list(range(50))
p = multiprocessing.Pool()
pp = PoolProgress(p)
res = p.map_async(hi,a)
pp.track(res)
关于python - pool.map_async 的打印进度,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/19562916/