Python Django 协程报错,进程池、线程池与异步调用、回调机制

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

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转载自www.cnblogs.com/xiao987334176/p/11089601.html