等待循环内pool.apply

尝试将整个 for 循环放在条件套件中。...if __name__ == '__main__':    for val in range(10):        buffer.append(val)        print(f'Added value: {val}')        if len(buffer) == 5:            pool = mp.Pool()            res = [pool.apply_async(fun, args = (x,x)) for x in buffer]            # wait til they are ALL done ?            for r in res:                r.wait()            # get the return values            res = [r.get() for r in res]            print(f'Results: {res}')            buffer = []            pool.close()            pool.join()这是您的原件，经过一些额外的检查。我仍然不知道为什么，但似乎不知何故，for循环中的行在多个python进程中运行。import multiprocessing as mpimport pickledef fun(x, y, pid=None):    print(f"here pid:{pid}",file=sys.stderr)    return (x+y,pid)buffer = []stuff = []with open(r'c:\pyProjects\stuff.pkl','wb') as f:    pickle.dump(stuff,f)for val in range(10):    buffer.append(val)    pid = os.getpid()    print(f'Added value: {val}.   pid={pid}')    d = {'val':val,'pid':pid}    with open(r'c:\pyProjects\stuff.pkl','rb') as f:        try:            stuff = pickle.load(f)            stuff.append(d)        except EOFError as e:            s = '\n'.join(f'\t\t\t\t{item}' for item in stuff)            print(f'\t\t\tEOFError {d}\n\t\t\tstuff:\n{s}\n')    with open(r'c:\pyProjects\stuff.pkl','wb') as f:        pickle.dump(stuff,f)    if len(buffer) == 5:        print(buffer)        #It is my understanding, this is necessary on Windows        if __name__ == "__main__":            pool = mp.Pool()            res = [pool.apply_async(fun, args = (x,x,pid)) for x in buffer]            res = [r.get() for r in res]            print(f'\t\t\tResults: {res}')            buffer = []            pool.close()            pool.join()完成后，您可以加载并仔细阅读腌制文件>>> import pickle>>> from pprint import pprint>>> with open(r'c:\pyProjects\stuff.pkl','rb') as f:...     a = pickle.load(f)>>> a.sort(key=lambda x: x['pid'])>>> pprint(a)

等待循环内pool.apply_async

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