Python並行(多執行緒)

並行性常常被誤解為並行性。 並行意味著排程獨立程式碼以系統方式執行。 本章重點介紹使用Python的作業系統的並行執行。

以下程式實現執行作業系統的並行性 -

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)

執行上述程式生成以下輸出 -

說明
multiprocessing是一個類似於執行緒模組的包。 該軟體包支援本地和遠端並行。 由於這個模組，程式員可以在給定的系統上使用多個進程。