在编写Python时, 如果我们需要同一时间内执行多个任务, 我们可以利用python内建模块multiprocessing来让其并行执行某个方法.

1. 随机执行方法

# vi ~/multipro1.py

import multiprocessing

def spawn(num):
    print('Sprawned! {}.'.format(num))


if __name__ == "__main__":
    for i in range(50):
        p = multiprocessing.Process(target=spawn, args=(i,))

        p.start()

2. 按顺序执行方法

# vi ~/multipro2.py

import multiprocessing


def spawn(num):
    print('Sprawned! {}.'.format(num))


if __name__ == "__main__":
    for i in range(50):
        p = multiprocessing.Process(target=spawn, args=(i,))

        p.start()

        # Waiting to finish One by one
        p.join()

Tip: 这里if __name__ == "__main__":的作用:

1. 当直接执行该脚本时, 内建变量__name__的值被赋予"__main__", 所以按照if逻辑, python解释器可以继续执行接下来的代码.

2. 当其他脚本去调用(import)该脚本时, __name__的值被赋予当前脚本名"multipro1", 而不是"__main__", 所以按照if逻辑, 保证if下面的代码不会被其他脚本调用.

所以在我们日常编写脚本的时候, 可以推荐按照如下结构, 在自己使用正常的同时, 保证在其他python脚本在调用test.py中的test1(), test2(), test3()的同时, 不会去执行if条件下的方法.

# vi test.py

def test1():
    ....

def test2():
    ....

def test3():
    ....

if __name__ == "__main__":
    ....

3. 多线程处理返回值.

# vi multipro3.py

from multiprocessing import pool

def job(num):
	return num * 2

if __name__ == '__main__':
	p = Pool(processes=20)
	data = p.map(job, range(5))
	data2 = p.map(job, [5, 2])
	p.close()

4.多线程爬取随机网站URL

# vi ~/multipro4.py

from multiprocessing import Pool
import bs4 as bs
import random
import requests
import string

# Return Four digits domain URL
def random_starting_url():
    starting = ''.join(random.SystemRandom().choice(
        string.ascii_lowercase) for _ in range(4))
    url = ''.join(['http://', starting, '.com'])
    return url


# Correct URL if it is relative
def handle_local_links(url, link):
    if link.startswith('/'):
        return ''.join([url, link])
    else:
        return link


# Get URL from "a" tag of 'body' tag
def get_links(url):
    try:
        # Request the URL
        resp = requests.get(url)
        # return the HTML
        soup = bs.BeautifulSoup(resp.text, 'lxml')
        # Get 'body' tag of the HTML
        body = soup.body
        # Get URL from "a" tag of 'body' tag
        links = [link.get('href') for link in body.find_all('a')]
        # Correct URL if it is relative
        links = [handle_local_links(url, link) for link in links]
        # Encoding the URL to ascii
        links = [str(link.encode('ascii')) for link in links]

        return links

    except TypeError as e:
        print(e)
        print('Got a TypeError, probably got a None that we tried to iterate over')
        return([])
    except IndexError as e:
        print(e)
        print('No valid link found, return a empty list')
        return([])
    except AttributeError as e:
        print(e)
        print('Likely got None for links, so we are throwing this')
        return([])
    except Exception as e:
        print(str(e))
        return([])


def main():
    # CPU process
    process = 5
    # The site intends to scrap
    site = 3
    p = Pool(processes=process)
    # Get random URL list
    parse_us = [random_starting_url() for _ in range(site)]
    # Multiprocessing the URL and parse the result
    data = p.map(get_links, parse_us)
    # Get each URL in a list
    data = [url for url_list in data for url in url_list]
    p.close()
    # Write to txt file
    with open('urls.txt', 'w') as f:
        f.write(str(data))


if __name__ == '__main__':
    main()

• 11-22[PYTHON] 核心编程笔记之九-Python文件和输入输出 (阅读 (8,781) 抢沙发)
• 03-18Centos6.3下单系统多mysql实例配置 (阅读 (14,971) 2条评论)