Python的threading和multiprocessing
Python的threading
基础用法, 通过 threading.Thread() 创建线程, 然后 start() 和 join()
import time import threading def do_something(seconds): print('Sleeping...') time.sleep(seconds) print('Done') start = time.perf_counter() threads = [] for _ in range(10): t = threading.Thread(target = do_something, args=[1]) t.start() threads.append(t) for t in threads: t.join() finish = time.perf_counter() print('Total: {}'.format(round(finish - start, 2)))
使用线程池. 使用as_completed, 可以阻塞并按完成顺序输出结果, 而直接用executor.map()会将结果收集完成后一起返回.
import time import threading from concurrent import futures def do_something(seconds): print('Sleeping...') time.sleep(seconds) return 'Done ' + str(seconds) start = time.perf_counter() with futures.ThreadPoolExecutor(max_workers=3) as executor: secs = [3, 2.5, 2, 2.2, 0.5] results = [executor.submit(do_something, sec) for sec in secs] for f in futures.as_completed(results): print(f.result()) # 注意区别 with futures.ThreadPoolExecutor() as executor: secs = [3, 2.5, 2, 2.2, 0.5] # 下面这行实际是阻塞的 results = executor.map(do_something, secs) for result in results: print(result) finish = time.perf_counter() print('Total: {}'.format(round(finish - start, 2)))
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Python的multiprocessing
.在使用multiprocessing时, 子进程里的print()是会滞后打印的.
import time import multiprocessing import logging def do_something(seconds): print('Sleeping...', seconds) time.sleep(seconds) return 'Done ' + str(seconds) if __name__ == '__main__': multiprocessing.log_to_stderr() logger = multiprocessing.get_logger() logger.setLevel(logging.INFO) start = time.perf_counter() secs = [3.1, 3.5, 3.1, 3.2, 3.5, 3.3] processes = [] for sec in secs: p = multiprocessing.Process(target=do_something, args=(sec,)) p.start() processes.append(p) for p in processes: p.join() finish = time.perf_counter() print('Total: {}'.format(round(finish - start, 2))) print() pool = multiprocessing.Pool(processes=3) print(pool.map(do_something, secs)) finish = time.perf_counter() print('Total: {}'.format(round(finish - start, 2)))
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