python-pool

The different performance of Python multiprocessing.Pool on MacOS and Linux systems

由 生来就可爱ヽ(ⅴ＜●) 提交于 2021-02-19 07:53:07
问题 I'm a beginner in Python. I used multiprocessing.Pool in my project to imporve performance. Here's a snippet of code I use the multiprocessing.Pool. I build the pool at the starting of my resident server, and use the Pool.apply_async method every time when the server get a request : # build pool when server started mp.set_start_method('forkserver') self._driver_pool = Pool(processes=10) self._executor_pool = Pool(processes=30) # use pool every time get a request driver = driver_class(driver

The different performance of Python multiprocessing.Pool on MacOS and Linux systems

由 时光毁灭记忆、已成空白 提交于 2021-02-19 07:53:02
问题 I'm a beginner in Python. I used multiprocessing.Pool in my project to imporve performance. Here's a snippet of code I use the multiprocessing.Pool. I build the pool at the starting of my resident server, and use the Pool.apply_async method every time when the server get a request : # build pool when server started mp.set_start_method('forkserver') self._driver_pool = Pool(processes=10) self._executor_pool = Pool(processes=30) # use pool every time get a request driver = driver_class(driver

Python Using List/Multiple Arguments in Pool Map

由 隐身守侯 提交于 2019-12-12 08:45:42
问题 I am trying to pass a list as a parameter to the pool.map(co_refresh, input_list) . However, pool.map didn't trigger the function co_refresh . And also no error returned. It looks like the process hung in there. Original Code: from multiprocessing import Pool import pandas as pd import os account='xxx' password='xxx' threads=5 co_links='file.csv' input_list=[] pool = Pool(processes=threads) def co_refresh(url, account, password, outputfile): print(url + ' : ' + account + ' : ' + password + '

Python Using List/Multiple Arguments in Pool Map

由 与世无争的帅哥 提交于 2019-12-04 04:41:26
I am trying to pass a list as a parameter to the pool.map(co_refresh, input_list) . However, pool.map didn't trigger the function co_refresh . And also no error returned. It looks like the process hung in there. Original Code: from multiprocessing import Pool import pandas as pd import os account='xxx' password='xxx' threads=5 co_links='file.csv' input_list=[] pool = Pool(processes=threads) def co_refresh(url, account, password, outputfile): print(url + ' : ' + account + ' : ' + password + ' : ' + outputfile) return; link_pool = pd.read_csv(co_links, skipinitialspace = True) for i, row in link
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