背景

日常開發中，難免遇到併發場景，而併發場景難免需要做流量控制，即需要對併發的程序或者執行緒的總量進行控制。 今天簡單總結兩種常用的控制執行緒個數的方法。

方法一：程序池/執行緒池

如下例demo所示， 建立了一個大小是4的程序池，然後建立5個程序，並啟動

from multiprocessing import Pool
import os,time,random


def long_time_task(name):
  print('Run task %s (%s)...' % (name,os.getpid()))
  start = time.time()
  time.sleep(random.random() * 3)
  end = time.time()
  print('Task %s runs %0.2f seconds.' % (name,(end - start)))


if __name__ == '__main__':
  print('Parent process %s.' % os.getpid())
  p = Pool(4)
  for i in range(5):
    p.apply_async(long_time_task,args=(i,))
  print('Waiting for all subprocesses done...')
  p.close()
  p.join()
  print('All subprocesses done.')

執行結果如下，可以看到第5個程序會等池子裡的程序完成一個後才會被啟動

Run task 0 (32952)...
Run task 1 (32951)...
Run task 2 (32953)...
Run task 3 (32954)...
Task 2 runs 0.68 seconds.
Run task 4 (32953)...
Task 1 runs 1.41 seconds.
Task 0 runs 1.44 seconds.
Task 4 runs 2.15 seconds.
Task 3 runs 2.98 seconds.
All subprocesses done.

方法二：queue

queue 模組即佇列，特別適合處理資訊在多個執行緒間安全交換的多執行緒程式中。 下面的demo展示瞭如何通過queue來限制執行緒的併發個數

import threading
import queue
import time
import random
import os

maxThreads = 4


class Store(threading.Thread):
  def __init__(self,q):
    threading.Thread.__init__(self)
    self.queue = q
    # self.store = store

  def run(self):
    try:
      print('Run task (%s)...' % (os.getpid()))
      start = time.time()
      time.sleep(random.random() * 3)
      end = time.time()
      t = threading.currentThread()
      # 執行緒ID
      print('Thread id : %d' % t.ident)
      print('Thread name : %s' % t.getName())
      print('Task runs %0.2f seconds.' % (end - start))
    except Exception as e:
      print(e)
    finally:
      self.queue.get()
      self.queue.task_done()


def main():
  q = queue.Queue(maxThreads)
  for s in range(6):
    q.put(s)
    t = Store(q)
    t.start()
  q.join()
  print('over')


if __name__ == '__main__':
  main()

執行結果如下：

Run task (33259)...
Run task (33259)...
Run task (33259)...
Run task (33259)...
Thread id : 123145444999168
Thread name : Thread-13
Task runs 0.04 seconds.
Run task (33259)...
Thread id : 123145394630656
Thread name : Thread-10
Task runs 1.02 seconds.
Run task (33259)...
Thread id : 123145428209664
Thread name : Thread-12
Task runs 1.20 seconds.
Thread id : 123145394630656
Thread name : Thread-17
Task runs 0.68 seconds.
Thread id : 123145444999168
Thread name : Thread-14
Task runs 1.79 seconds.
Thread id : 123145411420160
Thread name : Thread-11
Task runs 2.96 seconds.
over

以上就是python如何控制程序或者執行緒的個數的詳細內容，更多關於python 控制程序或執行緒的資料請關注我們其它相關文章！