进程和线程的区别, 面相对象补充, 进程, 数据共享, 锁, 进程池, 爬虫模块(requests, bs4(beautifulsoup))
2021-07-01 14:05
标签:run key 模拟 进程间 manage 常用 mozilla 多进程 win10 一. 进程和线程的区别? IO密集型操作可以使用多线程;计算密集型可以使用多进程; 三. 进程 - 常用功能: - 类继承方式创建进程 四. 进程间数据共享 五. 进程锁 六. 进程池 进程和线程的区别, 面相对象补充, 进程, 数据共享, 锁, 进程池, 爬虫模块(requests, bs4(beautifulsoup)) 标签:run key 模拟 进程间 manage 常用 mozilla 多进程 win10 原文地址:https://www.cnblogs.com/NachoLau/p/9637177.html
第一:
进程是cpu资源分配的最小单元。
线程是cpu计算的最小单元。
第二:
一个进程中可以有多个线程。
第三:
对于Python来说他的进程和线程和其他语言有差异,是有GIL锁。
GIL锁保证一个进程中同一时刻只有一个线程被cpu调度。
二. 面向对象补充:class Foo(object):
def __init__(self):
object.__setattr__(self, ‘info‘, {}) # 在继承的对象中设置值的本质
def __setattr__(self, key, value): # 会拦截所有属性的的赋值语句
self.info[key] = value
def __getattr__(self, item): # 拦截点号运算。当对未定义的属性名称和实例进行点号
# 运算时,就会用属性名作为字符串调用这个方法。如果继承树可以找到该属性,则不调用此方法
print(item) # name
return self.info[item]
obj = Foo()
obj.name = ‘nacho‘
print(obj.name) # nacho
print(obj.info) # {‘name‘: ‘nacho‘}
- 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__‘: # win10需要用这个, linux不需要
run()
- join
- deamon
- name
- multiprocessing.current_process()
- multiprocessing.current_process().ident/pidclass 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()
Queue:
linux:
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)
run()
windows:
def task(arg,q):
q.put(arg)
if __name__ == ‘__main__‘:
q = multiprocessing.Queue()
for i in range(10):
p = multiprocessing.Process(target=task,args=(i,q,))
p.start()
while True:
v = q.get()
print(v)
Manager:(*)
Linux:
m = multiprocessing.Manager()
dic = m.dict()
def task(arg):
dic[arg] = 100
def run():
for i in range(10):
p = multiprocessing.Process(target=task, args=(i,))
p.start()
input(‘>>>‘)
print(dic.values())
if __name__ == ‘__main__‘:
run()
windows:
def task(arg,dic):
time.sleep(2)
dic[arg] = 100
if __name__ == ‘__main__‘:
m = multiprocessing.Manager()
dic = m.dict()
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)
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()
import time
from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor
def task(arg):
time.sleep(2)
print(arg)
if __name__ == ‘__main__‘:
pool = ProcessPoolExecutor(6) # 取决于CPU的核心数
for i in range(10):
pool.submit(task,i)
七. 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()
文章标题:进程和线程的区别, 面相对象补充, 进程, 数据共享, 锁, 进程池, 爬虫模块(requests, bs4(beautifulsoup))
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