Python併發(多線程) - Python設計模式

併發性常常被誤解爲並行性。併發意味着調度獨立代碼以系統方式執行。本章重點介紹使用Python的操作系統的併發執行。

以下程序實現執行操作系統的併發性 -

import os
import time
import threading
import multiprocessing

NUM_WORKERS = 4

def only_sleep():
   print("PID: %s, Process Name: %s, Thread Name: %s" % (
      os.getpid(),
      multiprocessing.current_process().name,
      threading.current_thread().name)
   )
   time.sleep(1)

def crunch_numbers():
   print("PID: %s, Process Name: %s, Thread Name: %s" % (
      os.getpid(),
      multiprocessing.current_process().name,
      threading.current_thread().name)
   )
   x = 0
   while x < 10000000:
      x += 1
for _ in range(NUM_WORKERS):
   only_sleep()
end_time = time.time()
print("Serial time=", end_time - start_time)

# Run tasks using threads
start_time = time.time()
threads = [threading.Thread(target=only_sleep) for _ in range(NUM_WORKERS)]
[thread.start() for thread in threads]
[thread.join() for thread in threads]
end_time = time.time()

print("Threads time=", end_time - start_time)

# Run tasks using processes
start_time = time.time()
processes = [multiprocessing.Process(target=only_sleep()) for _ in range(NUM_WORKERS)]
[process.start() for process in processes]
[process.join() for process in processes]
end_time = time.time()

print("Parallel time=", end_time - start_time)

執行上述程序生成以下輸出 -
Python併發(多線程)

說明
multiprocessing是一個類似於線程模塊的包。該軟件包支持本地和遠程併發。由於這個模塊，程序員可以在給定的系統上使用多個進程。