python中多线程与非线程的执行性能对比-白红宇

此对比说明了一件事：

如果是IO型应用，多线程有优势，

如果是CPU计算型应用，多线程没必要，还有实现锁呢。

#!/usr/bin/env python# -*- coding: utf-8 -*-from threading import Threadclass threads_object(Thread):    def run(self):        function_to_run()class nothreads_object(object):    def run(self):        function_to_run()def non_threaded(num_iter):    funcs = []    for i in range(int(num_iter)):        funcs.append(nothreads_object())    for i in funcs:        i.run()def threaded(num_threads):    funcs = []    for i in range(int(num_threads)):        funcs.append(threads_object())    for i in funcs:        i.start()    for i in funcs:        i.join()def function_to_run():    a, b = 0, 1    for i in range(10000):        a, b = b, a + b    '''    import requests    for i in range(10):        requests.get("http://10.25.174.41/")    '''def show_results(func_name, results):    print("%-23s %4.6f seconds" % (func_name, results))if __name__ == "__main__":    import sys    from timeit import Timer    repeat = 100    number = 1    number_threads = [1, 2, 4, 8]    print('Starting tests')    for i in number_threads:        t = Timer("non_threaded(%s)" \                  % i, "from __main__ import non_threaded")        best_result =\                    min(t.repeat(repeat=repeat, number=number))        show_results("non_threaded (%s iters) "\                     %i, best_result)        t = Timer("threaded(%s)" \                  % i, "from __main__ import threaded")        best_result =\                    min(t.repeat(repeat=repeat, number=number))        show_results("threaded (%s iters) "\                     %i, best_result)    print ('Iterations complete')