[issue26418] multiprocessing.pool.ThreadPool eats up memories

2017-03-20 Thread renlifeng
renlifeng added the comment: I confirm that 3.5.3 and 2.7.13 have fixed this problem. Now the memory usage will stop growing after using 28% of physical memory. In other words, this problem can not be reproduced with the latest version of python, Thanks. It's OK for me to set it to any

[issue26418] multiprocessing.pool.ThreadPool eats up memories

2016-02-23 Thread renlifeng
New submission from renlifeng: If func creates lots objects and appends them to a list, and runs over and over, pool.map(func...) will eventually eat up all memories. Cleaning the list at the end of func does not help. One can reproduce by running the attached file. By contrast, after