imap_unordered
... same numbers in arbitrary order for i in pool.imap_unordered(f, range(10)): print i # evaluate "f(20)" asynchronously res = pool.apply_async(f, ..., Using pool.imap_unordered instead of pool.imap will not have a large effect on the total running time of your code. It might be a little faster, but ...,... 81]" print(pool.map(f, range(10))) # print same numbers in arbitrary order for i in pool.imap_unordered(f, range(10)): print(i) # evaluate "f(20)" asynchronously ... ,... 81]" print(pool.map(f, range(10))) # print same numbers in arbitrary order for i in pool.imap_unordered(f, range(10)): print(i) # evaluate "f(20)" asynchronously ... , Since processing is fast, but writing is slow, it sounds like your problem is I/O-bound. Therefore there might not be much to be gained from using ..., 展开. 很简单的使用代码：. from multiprocess import Pool. pool = Pool(args.n_cpus). # eg: f_list = [a, b, c]. for a in pool.imap_unordered(f, f_list):., map 直接返回列表，而 i 开头的两个函数返回的是迭代器； imap_unordered 返回的是无序的。 当计算时间比较长的时候，我们可能想要加上一个 ..., 6、imap_unordered(func, iterable[, chunksize]) 同imap一致，只不过其并不保证返回结果与迭代传入的顺序一致。 7、close() 关闭pool，使其不再 ..., imap_unordered()不保证返回的结果顺序与进程添加的顺序一致。 怎么取得进程的结果？ 阻塞式函数： Pool.apply()直接返回结果. Pool.map() 直接 ..., Using pool.imap_unordered instead of pool.imap will not have a large effect on the total running time of your code. It might be a little faster, but ...
| 相關軟體 Processing 資訊 | |
|---|---|
 imap_unordered 相關參考資料
16.6. multiprocessing — Process-based “threading” interface ...
... same numbers in arbitrary order for i in pool.imap_unordered(f, range(10)): print i # evaluate "f(20)" asynchronously res = pool.apply_async(f, ... https://docs.python.org In what situation do we need to use `multiprocessing.Pool ...
Using pool.imap_unordered instead of pool.imap will not have a large effect on the total running time of your code. It might be a little faster, but ... https://stackoverflow.com multiprocessing --- 基于进程的并行— Python 3.8.2 文档
... 81]" print(pool.map(f, range(10))) # print same numbers in arbitrary order for i in pool.imap_unordered(f, range(10)): print(i) # evaluate "f(20)" asynchronously ... https://docs.python.org multiprocessing — Process-based parallelism — Python 3.8.2 ...
... 81]" print(pool.map(f, range(10))) # print same numbers in arbitrary order for i in pool.imap_unordered(f, range(10)): print(i) # evaluate "f(20)" asynchronously ... https://docs.python.org multiprocessing.Pool.imap_unordered with fixed queue size or ...
Since processing is fast, but writing is slow, it sounds like your problem is I/O-bound. Therefore there might not be much to be gained from using ... https://stackoverflow.com pool.imap_unordered()多进程模块使用_Python_ccbrid的博客 ...
展开. 很简单的使用代码：. from multiprocess import Pool. pool = Pool(args.n_cpus). # eg: f_list = [a, b, c]. for a in pool.imap_unordered(f, f_list):. https://blog.csdn.net Python 多核并行计算 - Lequn Chen
map 直接返回列表，而 i 开头的两个函数返回的是迭代器； imap_unordered 返回的是无序的。 当计算时间比较长的时候，我们可能想要加上一个 ... https://abcdabcd987.com python 进程池2 - Pool相关函数- congbo - 博客园
6、imap_unordered(func, iterable[, chunksize]) 同imap一致，只不过其并不保证返回结果与迭代传入的顺序一致。 7、close() 关闭pool，使其不再 ... https://www.cnblogs.com Python中实现多进程- 知乎
imap_unordered()不保证返回的结果顺序与进程添加的顺序一致。 怎么取得进程的结果？ 阻塞式函数： Pool.apply()直接返回结果. Pool.map() 直接 ... https://zhuanlan.zhihu.com `multiprocessing.Pool.imap_unordered`? - Stack Overflow
Using pool.imap_unordered instead of pool.imap will not have a large effect on the total running time of your code. It might be a little faster, but ... https://stackoverflow.com |