一、问题描述
在Django视图函数中,导入 gevent 模块
import gevent from gevent import monkey; monkey.patch_all() from gevent.pool import Pool
启动Django报错:
MonkeyPatchWarning: Monkey-patching outside the main native thread. Some APIs will not be available. Expect a KeyError to be printed at shutdown. from gevent import monkey; monkey.patch_all() MonkeyPatchWarning: Monkey-patching not on the main thread; threading.main_thread().join() will hang from a greenlet from gevent import monkey; monkey.patch_all()
原因在于执行这行 monkey.patch_all() 代码时报错了。
既然Django不能使用协程,那我需要使用异步执行,怎么办?
请看下文
二、进程池、线程池与异步调用、回调机制
进程池、线程池使用案例
进程池与线程池使用几乎相同,只是调用模块不同~!!
from concurrent.futures import ProcessPoolExecutor # 进程池模块 from concurrent.futures import ThreadPoolExecutor # 线程池模块 import os, time, random # 下面是以进程池为例, 线程池只是模块改一下即可 def talk(name): print('name: %s pis%s run' % (name,os.getpid())) time.sleep(random.randint(1, 3)) if __name__ == '__main__': pool = ProcessPoolExecutor(4) # 设置线程池大小,默认等于cpu核数 for i in range(10): pool.submit(talk, '进程%s' % i) # 异步提交(只是提交需要运行的线程不等待) # 作用1:关闭进程池入口不能再提交了 作用2:相当于jion 等待进程池全部运行完毕 pool.shutdown(wait=True) print('主进程')
异步调用与同步调用
concurrent.futures模块提供了高度封装的异步调用接口
ThreadPoolExecutor:线程池,提供异步调用
ProcessPoolExecutor: 进程池,提供异步调用
同步调用
from concurrent.futures import ProcessPoolExecutor # 进程池模块 import os, time, random # 1、同步调用: 提交完任务后、就原地等待任务执行完毕,拿到结果,再执行下一行代码(导致程序串行执行) def talk(name): print('name: %s pis%s run' % (name,os.getpid())) time.sleep(random.randint(1, 3)) if __name__ == '__main__': pool = ProcessPoolExecutor(4) for i in range(10): pool.submit(talk, '进程%s' % i).result() # 同步迪奥用,result(),相当于join 串行 pool.shutdown(wait=True) print('主进程')
异步调用
from concurrent.futures import ProcessPoolExecutor # 进程池模块 import os, time, random def talk(name): print('name: %s pis%s run' % (name,os.getpid())) time.sleep(random.randint(1, 3)) if __name__ == '__main__': pool = ProcessPoolExecutor(4) for i in range(10): pool.submit(talk, '进程%s' % i) # 异步调用,不需要等待 pool.shutdown(wait=True) print('主进程')
回调机制
可以为进程池或线程池内的每个进程或线程绑定一个函数,该函数在进程或线程的任务执行完毕后自动触发,并接收任务的返回值当作参数,该函数称为回调函数
#parse_page拿到的是一个future对象obj,需要用obj.result()拿到结果 p.submit(这里异步调用).add_done_callback(方法)
案例:下载解析网页页面
import time import requests from concurrent.futures import ThreadPoolExecutor # 线程池模块 def get(url): print('GET %s' % url) response = requests.get(url) # 下载页面 time.sleep(3) # 模拟网络延时 return {'url': url, 'content': response.text} # 页面地址和页面内容 def parse(res): res = res.result() # !取到res结果 【回调函数】带参数需要这样 print('%s res is %s' % (res['url'], len(res['content']))) if __name__ == '__main__': urls = { 'http://www.baidu.com', 'http://www.360.com', 'http://www.iqiyi.com' } pool = ThreadPoolExecutor(2) for i in urls: pool.submit(get, i).add_done_callback(parse) # 【回调函数】执行完线程后,跟一个函数
本文参考链接:
https://blog.csdn.net/weixin_42329277/article/details/80741589