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Python?multiprocessing?共享對象的示例代碼

更新時(shí)間：2023年07月07日 09:08:10 作者：跡憶客

在 Python 中使用 multiprocessing，一個(gè)新的進(jìn)程可以獨(dú)立運(yùn)行并擁有自己的內(nèi)存空間，下面通過示例代碼講解Python multiprocessing共享對象的相關(guān)知識，感興趣的朋友跟隨小編一起看看吧

在多進(jìn)程中使用 Python 共享內(nèi)存對象

在 Python 中使用 multiprocessing，一個(gè)新的進(jìn)程可以獨(dú)立運(yùn)行并擁有自己的內(nèi)存空間。通過查看下面的示例，讓我們詳細(xì)了解使用 Python 的共享對象多處理。

示例代碼：

import multiprocessing
#an empty array globally declared
answer = []
def square_numbers(mynumbers):
#for squaring array elements, a function has been used
    global answer
    #appending square numbers to a global array
    for n in mynumbers:
        answer.append(n * n)
    #print a global array for generating an answer
    print("Answer using first process: {}".format(answer))
if __name__ == "__main__":
    #input array
    mynumbers = [5,10,15]
    #new process has been created
    p = multiprocessing.Process(target=square_numbers, args=(mynumbers,))
    #process begins here
    p.start()
    #wait unless a process is completed
    p.join()
    #print a global array for generating an answer
    print("Answer using main program: {}".format(answer))

輸出:

Answer using first process: [25, 100, 225]
Answer using main program: []

我們使用上面的例子在兩個(gè)地方打印了全局?jǐn)?shù)組答案。

進(jìn)程 p 調(diào)用 square_numbers 函數(shù)，以便在內(nèi)存空間中為進(jìn)程 p 更改數(shù)組元素。

主程序在進(jìn)程 p 完成后運(yùn)行，我們將在內(nèi)存空間中得到一個(gè)空數(shù)組作為答案。

Python 中的多處理提供了值對象和一個(gè)數(shù)組，用于在多個(gè)進(jìn)程之間共享數(shù)據(jù)。

示例代碼：

import multiprocessing
def square_data(mydata, answer, square_sum):
  #a function has been made for squaring of given data
    #appending squares of mydata to the given array
    for ix, n in enumerate(mydata):
        answer[ix] = n * n
    #sum the square values
    square_sum.value = sum(answer)
    #print array of squared values for process p
    print("Answer in process p: {}".format(answer[:]))
    # print the sum of squared values for process p
    print("Sum of squares values in process p: {}".format(square_sum.value))
if __name__ == "__main__":
    #here, we input the data
    mydata = [1,2,3]
    #an array has been created for the int data type for three integers
    answer = multiprocessing.Array('i', 3)
    #value has been created for int data type
    square_sum = multiprocessing.Value('i')
    #new process has been created
    p = multiprocessing.Process(target=square_data, args=(mydata, answer, square_sum))
    #process begins from here
    p.start()
    #wait unless the process is completed
    p.join()
    # print an array of squared values for the main program
    print("Answer in main program: {}".format(answer[:]))
    # print the sum of squared values for the main program
    print("Sum of square values in main program: {}".format(square_sum.value))

輸出: