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Python多線程多進程實例對比解析

更新時間：2020年03月12日 12:43:18 作者：我太難了008

這篇文章主要介紹了Python多線程多進程實例對比解析,文中通過示例代碼介紹的非常詳細，對大家的學習或者工作具有一定的參考學習價值,需要的朋友可以參考下

多線程適合于多io操作

多進程適合于耗cpu(計算)的操作

# 多進程編程
# 耗cpu的操作,用多進程編程, 對于io操作來說,使用多線程編程
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
from concurrent.futures import ProcessPoolExecutor


def fib(n):
  if n <= 2:
    return 1
  return fib(n - 2) + fib(n - 1)

if __name__ == '__main__':

  # 1. 對于耗cpu操作,多進程優(yōu)于多線程

  # with ThreadPoolExecutor(3) as executor:
  #   all_task = [executor.submit(fib, num) for num in range(25, 35)]
  #   start_time = time.time()
  #   for future in as_completed(all_task):
  #     data = future.result()
  #     print(data)
  #   print("last time :{}".format(time.time() - start_time)) # 3.905290126800537

  # 多進程 ,在window環(huán)境 下必須放在main方法中執(zhí)行,否則拋異常
  with ProcessPoolExecutor(3) as executor:
    all_task = [executor.submit(fib, num) for num in range(25, 35)]
    start_time = time.time()
    for future in as_completed(all_task):
      data = future.result()
      print(data)
    print("last time :{}".format(time.time() - start_time)) # 2.6130592823028564

可以看到在耗cpu的應(yīng)用中,多進程明顯優(yōu)于多線程 2.6130592823028564 < 3.905290126800537

下面模擬一個io操作

# 多進程編程
# 耗cpu的操作,用多進程編程, 對于io操作來說,使用多線程編程
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
from concurrent.futures import ProcessPoolExecutor

def io_operation(n):
  time.sleep(2)
  return n


if __name__ == '__main__':

  # 1. 對于耗cpu操作,多進程優(yōu)于多線程

  # with ThreadPoolExecutor(3) as executor:
  #   all_task = [executor.submit(io_operation, num) for num in range(25, 35)]
  #   start_time = time.time()
  #   for future in as_completed(all_task):
  #     data = future.result()
  #     print(data)
  #   print("last time :{}".format(time.time() - start_time)) # 8.00358772277832



  # 多進程 ,在window環(huán)境 下必須放在main方法中執(zhí)行,否則拋異常
  with ProcessPoolExecutor(3) as executor:
    all_task = [executor.submit(io_operation, num) for num in range(25, 35)]
    start_time = time.time()
    for future in as_completed(all_task):
      data = future.result()
      print(data)
    print("last time :{}".format(time.time() - start_time)) # 8.12435245513916

可以看到 8.00358772277832 < 8.12435245513916, 即是多線程比多進程更牛逼!

以上就是本文的全部內(nèi)容，希望對大家的學習有所幫助，也希望大家多多支持腳本之家。

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