面向对象补充:对象中设置值
class Foo(object): def __init__(self): object.__setattr__(self, 'info', {}) # 在对象中设置值的本质 def __setattr__(self, key, value): self.info[key] = value def __getattr__(self, item): print(item) return self.info[item] obj = Foo() obj.name = 'alex' print(obj.name) v = [] for i in range(10000): v.append(i) print(v)
1. 进程
进程间数据不共享
data_list = [] def task(arg): data_list.append(arg) print(data_list) def run(): for i in range(10): p = multiprocessing.Process(target=task,args=(i,)) # p = threading.Thread(target=task,args=(i,)) p.start() if __name__ == '__main__': run()
常用功能:
import time def task(arg): time.sleep(2) print(arg) def run(): print('111111111') p1 = multiprocessing.Process(target=task,args=(1,)) p1.name = 'pp1' p1.start() print('222222222') p2 = multiprocessing.Process(target=task, args=(2,)) p2.name = 'pp2' p2.start() print('333333333') if __name__ == '__main__': run()
类继承方式创建进程:
class MyProcess(multiprocessing.Process): def run(self): print('当前进程',multiprocessing.current_process()) def run(): p1 = MyProcess() p1.start() p2 = MyProcess() p2.start() if __name__ == '__main__': run()
2.进程间数据共享: (multiprocessing.Queue , Manager)
import multiprocessing import threading #第一种 import queue import time q = multiprocessing.Queue() def task(arg,q): q.put(arg) def run(): for i in range(10): p = multiprocessing.Process(target=task, args=(i, q,)) p.start() while True: v = q.get() print(v) if __name__ == '__main__': run() def task(arg,dic): time.sleep(2) dic[arg] = 100 if __name__ == '__main__': m = multiprocessing.Manager() #第二种 dic = {} process_list = [] for i in range(10): p = multiprocessing.Process(target=task, args=(i,dic,)) p.start() process_list.append(p) while True: count = 0 for p in process_list: if not p.is_alive(): count += 1 if count == len(process_list): break print(dic)
进程间的数据其他电脑:
lock = multiprocessing.RLock() def task(arg,): print("鬼子扛枪") lock.acquire() time.sleep(2) print(arg) lock.release() if __name__ == '__main__': while True: ........
3.进程锁:
import time import threading import multiprocessing lock = multiprocessing.RLock() def task(arg): print('鬼子来了') lock.acquire() time.sleep(2) print(arg) lock.release() if __name__ == '__main__': p1 = multiprocessing.Process(target=task,args=(1,)) p1.start() p2 = multiprocessing.Process(target=task, args=(2,)) p2.start()
4.进程池
import time from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor def task(arg): time.sleep(2) print(arg) if __name__ == '__main__': pool = ProcessPoolExecutor(5) for i in range(10): pool.submit(task,i)
5.初始爬虫.
安装 : pip3 install requests
pip3 install beautifulsoup4
问题 : 找不到内部指令?
方式一 : C:UsersSFAppDataLocalProgramsPythonPython36Scriptspip3 install requests
方式二 : C:UsersSFAppDataLocalProgramsPythonPython36Scripts
pip3 install requests
简单爬虫示例:
import requests from bs4 import BeautifulSoup from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor # 模拟浏览器发送请求 # 内部创建 sk = socket.socket() # 和抽屉进行socket连接 sk.connect(...) # sk.sendall('...') # sk.recv(...) def task(url): print(url) r1 = requests.get( url=url, headers={ 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3497.92 Safari/537.36' } ) # 查看下载下来的文本信息 # soup = BeautifulSoup(r1.text,'html.parser') # print(soup.text) # content_list = soup.find('div',attrs={'id':'content-list'}) # for item in content_list.find_all('div',attrs={'class':'item'}): # title = item.find('a').text.strip() # target_url = item.find('a').get('href') # print(title,target_url) def run(): pool = ThreadPoolExecutor(5) for i in range(1,50): pool.submit(task,'https://dig.chouti.com/all/hot/recent/%s' %i) if __name__ == '__main__': run()
进程和线程那个好?
回答是: 线程好
进程池/ 线程池的应用 与爬虫有关