Python多处理ThreadPool

Question

我尝试使用python中的多处理读取文件。这里是一个小例子：

import multiprocessing 
from time import * 

class class1(): 
    def function(self, datasheetname): 
     #here i start reading my datasheet 

if __name__ == '__main__': 
    #Test with multiprosessing 
    pool = multiprocessing.Pool(processes=4) 
    pool.map(class1("Datasheetname")) 
    pool.close() 

现在我得到以下错误：

TypeError: map() missing 1 required positional argument: 'iterable'

在这个板上的其他线程我得到了暗示与线程池要做到这一点，但我不无怎么做。有任何想法吗？

Answer 1

Pool.map：

map(func, iterable[, chunksize])

A parallel equivalent of the map() built-in function (it supports only one iterable argument though). It blocks until the result is ready.

This method chops the iterable into a number of chunks which it submits to the process pool as separate tasks. The (approximate) size of these chunks can be specified by setting chunksize to a positive integer.

您必须通过其中的每个元素被传递给目标func作为每个过程参数可迭代。

例子：

def function(sheet): 
    # do something with sheet 
    return "foo" 

pool = Pool(processes=4) 
result = pool.map(function, ['sheet1', 'sheet2', 'sheet3', 'sheet4']) 
# result will be ['foo', 'foo', 'foo', 'foo']