线程协程和进程

不完整的单例模式

class Foo:
    instance = None

    def __init__(self, name):
        self.name = name
    def __new__(cls, *args, **kwargs):
        # 返回空对象
        if cls.instance:
            return cls.instance
        cls.instance = object.__new__(cls)
        return cls.instance

obj1 = Foo('日魔')
obj2 = Foo('SB')

print(obj1,obj2)

爬虫爬图片

# 基于多线程
import threading
def task(arg):
    ret = requests.get(arg)
    file_name = arg.rsplit('/', maxsplit=1)[-1]
    with open(file_name, mode='wb') as f:
        f.write(ret.content)

for url in url_list:
    # 实例化一个线程对象
    t = threading.Thread(target=task,args=(url,))
    # 将线程提交给cpu
    t.start()

join 和start的题

import threading


# 示例1
"""
loop = 10000000
number = 0

def _add(count):
    global number
    for i in range(count):
        number += 1


t = threading.Thread(target=_add,args=(loop,))
t.start()

t.join()
print(number)
"""

# 示例2
"""
loop = 10000000
number = 0

def _add(count):
    global number
    for i in range(count):
        number += 1

def _sub(count):
    global number
    for i in range(count):
        number -= 1

t1 = threading.Thread(target=_add,args=(loop,))
t2 = threading.Thread(target=_sub,args=(loop,))
t1.start()
t2.start()

print(number)
"""


# 示例3
"""
loop = 10000000
number = 0

def _add(count):
    global number
    for i in range(count):
        number += 1

def _sub(count):
    global number
    for i in range(count):
        number -= 1

t1 = threading.Thread(target=_add,args=(loop,))
t2 = threading.Thread(target=_sub,args=(loop,))
t1.start()
t2.start()
t1.join() # t1线程执行完毕,才继续往后走
t2.join() # t2线程执行完毕,才继续往后走

print(number)
"""

# 示例4
"""
loop = 10000000
number = 0

def _add(count):
    global number
    for i in range(count):
        number += 1

def _sub(count):
    global number
    for i in range(count):
        number -= 1

t1 = threading.Thread(target=_add,args=(loop,))
t2 = threading.Thread(target=_sub,args=(loop,))
t1.start()
t1.join() # t1线程执行完毕,才继续往后走
t2.start()
t2.join() # t2线程执行完毕,才继续往后走

print(number)
"""

守护线程

import threading
import time

def task(arg):
    time.sleep(5)
    print('任务')


t = threading.Thread(target=task,args=(11,))
t.setDaemon(False)
t.start()

print('END')

线程名称

import threading

def task(arg):
    # 获取当前执行此代码的线程
    name = threading.current_thread().getName()
    print(name)

for i in range(10):
    t = threading.Thread(target=task,args=(11,))
    t.setName('日魔-%s' %i )
    t.start()

自定义线程

import threading


class RiMo(threading.Thread):
    def run(self):
        print('执行此线程',self._args)

obj = RiMo(args=(100,))
obj.start()

3.2 线程的概念&与进程的区别?

形象的关系

• 工厂 -> 应用程序
• 车间 -> 进程
• 工人 -> 线程

进程和线程的区别?

进程是计算机资源分配的最小单位.
线程是计算机中可以被cpu调度的最小单位.
一个进程中可以有多个线程,同一个进程中的线程可以共享此进程中的资源,一个进程中至少有一个线程(一个应用程序中至少有一个进程)

在Python中因为有GIL锁,他限制在同一时刻一个进程中只能有一个线程被调度
计算密集型：多进程
IO密集型：多线程
默认进程之间无法进行资源共享,如果主要想要通讯可以基于:文件/网络/Queue.

socketserver的本质

import socket
import threading


def task(connect,address):
    pass


server = socket.socket()
server.bind(('127.0.0.1',9000))
server.listen(5)
while True:
    conn,addr = server.accept()
    # 处理用户请求
    t = threading.Thread(target=task,args=(conn,addr,))
    t.start()

3.4 线程安全

多个线程同时去操作一个"东西",不要存在数据混乱.

线程安全: logging模块 / 列表

线程不安全: 自己做文件操作 / 同时修改一个数字

使用锁来保证数据安全,来了多个线程,使用锁让他们排队,逐一执行.

线程锁

import threading
import time


num = 0
# 线程锁
lock = threading.Lock()


def task():
    global num
    # # 申请锁
    # lock.acquire()
    # num += 1
    # time.sleep(0.2)
    # print(num)
    # # 释放锁
    # lock.release()

    with lock:
        num += 1
        time.sleep(0.2)
        print(num)

for i in range(10):
    t = threading.Thread(target=task)
    t.start()

递归锁

import threading
import time


num = 0
# 线程锁
lock = threading.RLock()


def task():
    global num
    # 申请锁
    lock.acquire()
    num += 1
    lock.acquire()
    time.sleep(0.2)
    print(num)
    # 释放锁
    lock.release()
    lock.release()


for i in range(10):
    t = threading.Thread(target=task)
    t.start()

加强版的单例模式

import threading
import time
class Singleton:
    instance = None
    lock = threading.RLock()

    def __init__(self, name):
        self.name = name
    def __new__(cls, *args, **kwargs):

        if cls.instance:
            return cls.instance
        with cls.lock:
            if cls.instance:
                return cls.instance
            time.sleep(0.1)
            cls.instance = object.__new__(cls)
        return cls.instance

def task():
    obj = Singleton('x')
    print(obj)

for i in range(10):
    t = threading.Thread(target=task)
    t.start()

# 执行1000行代码

data = Singleton('asdfasdf')
print(data)

3.5GIL

GIL,全局解释器锁.

同一时刻保证一个进程中只有一个线程可以被cpu调度,所以在使用Python开发时要注意:
    计算密集型,用多进程.
    IO密集型,用多线程. 

• Python中如果创建多现场无法应用计算机的多核优势.

4.重点总结

• 初识爬虫
• 单例模式 ,重点面试 (需要默写)
  • 为什么要加锁?
  • 为什么要做判断?
• 进程和线程的区别? ,重点.面试
• GIL锁, 重点面试
• 线程的常用功能: start/join , 重点

线程池

import time
from concurrent.futures import ThreadPoolExecutor
import threading
lock=threading.RLock()
def start(i,n):
    print(id(lock))
    time.sleep(1)
    with lock:
        print("任务1")
fool=ThreadPoolExecutor(10)
for i in range(100):
    fool.submit(start,i,1)

print("end")
fool.shutdown(True)
print("所有任务执行结束")

进程池

# import time
# from concurrent.futures import ProcessPoolExecutor
#
# def tst(i):
#     time.sleep(1)
#     print("任务")
#
# if __name__ == '__main__':
#
#     fool=ProcessPoolExecutor(10)
#     for i in range(100):
#         fool.submit(tst,i)
#     print("end")
#     fool.shutdown()
#     print("所有任务结束")

# import time
# from concurrent.futures import ProcessPoolExecutor
# def start(i,n):
#     time.sleep(1)
#     print("任务1")
# if __name__ == '__main__':
#     fool=ProcessPoolExecutor(10)
#     for i in range(100):
#         fool.submit(start,i,1)
#
#     print("end")
#     fool.shutdown(True)
#     print("所有任务执行结束")

队列

from queue import Queue

q=Queue()
v2=q.put(12)


v1=q.get()
print(v1)

协程

from gevent import monkey
monkey.patch_all()
import  gevent
import time

def fun1():
    print(1)
    time.sleep(0.1)
    print(2)

def fun2():
    print(3)
    time.sleep(0.1)
    print(4)

t1=gevent.spawn(fun1)
t2=gevent.spawn(fun2)
gevent.joinall([t1,t2])

协程+io+爬虫

from gevent import monkey
monkey.patch_all()

import gevent
import requests

def f1(url):
    print('GET: %s' % url)
    data = requests.get(url)
    print('%d bytes received from %s.' % (len(data.content), url))

def f2(url):
    print('GET: %s' % url)
    data = requests.get(url)
    print('%d bytes received from %s.' % (len(data.content), url))

def f3(url):
    print('GET: %s' % url)
    data = requests.get(url)
    print('%d bytes received from %s.' % (len(data.content), url))

gevent.joinall([
        gevent.spawn(f1, 'https://www.python.org/'),
        gevent.spawn(f2, 'https://www.yahoo.com/'),
        gevent.spawn(f3, 'https://github.com/'),
])

发邮件的示例

"""
1. 申请126或163邮箱

2. 开启服务+授权码

3. 通过代码发送
"""

import smtplib
from email.mime.text import MIMEText
from email.utils import formataddr

# 写邮件的内容
msg = MIMEText('老板，我想演男一号，你想怎么着都行。', 'plain', 'utf-8')
msg['From'] = formataddr(["炮手", 'zh309603@163.com'])
msg['To'] = formataddr(["老板", '424662508@qq.com'])
msg['Subject'] = "情爱的导演"

server = smtplib.SMTP_SSL("smtp.163.com", 465)
server.login("zh309603", "zhzzhz123") # 授权码
server.sendmail('zh309603@163.com', ['424662508@qq.com', ], msg.as_string())
server.quit()

生成者消费者模型

from queue import Queue
import threading
q=Queue()

def fun():#从队列中拿任务处理
   while True :
       s=q.get()
       print(s)

def fun1(i):#将接到的任务放到队列中
    s=q.put(i)

for i  in range(10):
    t=threading.Thread(target=fun1,args=(i,))
    t.start()
for i in range(5):
    t=threading.Thread(target=fun)
    t.start()

线程池

import time
from concurrent.futures import ThreadPoolExecutor
import threading
lock=threading.RLock()
def start(i,n):
    print(id(lock))
    time.sleep(1)
    with lock:
        print("任务1")
fool=ThreadPoolExecutor(10)
for i in range(100):
    fool.submit(start,i,1)

print("end")
fool.shutdown(True)
print("所有任务执行结束")

进程池

# import time
# from concurrent.futures import ProcessPoolExecutor
#
# def tst(i):
#     time.sleep(1)
#     print("任务")
#
# if __name__ == '__main__':
#
#     fool=ProcessPoolExecutor(10)
#     for i in range(100):
#         fool.submit(tst,i)
#     print("end")
#     fool.shutdown()
#     print("所有任务结束")

# import time
# from concurrent.futures import ProcessPoolExecutor
# def start(i,n):
#     time.sleep(1)
#     print("任务1")
# if __name__ == '__main__':
#     fool=ProcessPoolExecutor(10)
#     for i in range(100):
#         fool.submit(start,i,1)
#
#     print("end")
#     fool.shutdown(True)
#     print("所有任务执行结束")

队列

from queue import Queue

q=Queue()
v2=q.put(12)


v1=q.get()
print(v1)

协程

from gevent import monkey
monkey.patch_all()
import  gevent
import time

def fun1():
    print(1)
    time.sleep(0.1)
    print(2)

def fun2():
    print(3)
    time.sleep(0.1)
    print(4)

t1=gevent.spawn(fun1)
t2=gevent.spawn(fun2)
gevent.joinall([t1,t2])

协程+io+爬虫

from gevent import monkey
monkey.patch_all()

import gevent
import requests

def f1(url):
    print('GET: %s' % url)
    data = requests.get(url)
    print('%d bytes received from %s.' % (len(data.content), url))

def f2(url):
    print('GET: %s' % url)
    data = requests.get(url)
    print('%d bytes received from %s.' % (len(data.content), url))

def f3(url):
    print('GET: %s' % url)
    data = requests.get(url)
    print('%d bytes received from %s.' % (len(data.content), url))

gevent.joinall([
        gevent.spawn(f1, 'https://www.python.org/'),
        gevent.spawn(f2, 'https://www.yahoo.com/'),
        gevent.spawn(f3, 'https://github.com/'),
])

发邮件的示例

"""
1. 申请126或163邮箱

2. 开启服务+授权码

3. 通过代码发送
"""

import smtplib
from email.mime.text import MIMEText
from email.utils import formataddr

# 写邮件的内容
msg = MIMEText('老板，我想演男一号，你想怎么着都行。', 'plain', 'utf-8')
msg['From'] = formataddr(["炮手", 'zh309603@163.com'])
msg['To'] = formataddr(["老板", '424662508@qq.com'])
msg['Subject'] = "情爱的导演"

server = smtplib.SMTP_SSL("smtp.163.com", 465)
server.login("zh309603", "zhzzhz123") # 授权码
server.sendmail('zh309603@163.com', ['424662508@qq.com', ], msg.as_string())
server.quit()

生成者消费者模型

from queue import Queue
import threading
q=Queue()

def fun():#从队列中拿任务处理
   while True :
       s=q.get()
       print(s)

def fun1(i):#将接到的任务放到队列中
    s=q.put(i)

for i  in range(10):
    t=threading.Thread(target=fun1,args=(i,))
    t.start()
for i in range(5):
    t=threading.Thread(target=fun)
    t.start()

进程，线程，协程的区别：三个都可以提高并发

• 进程是计算机分配资源的最小单位；线程是计算机中cpu 调度的最小单位
• 协程又称为“微线程”，是基于代码创造出来的，而进程和线程都是计算机中真实存在的，一个进程可以有多个线程，一个线程可以创造多个协程
• 计算密集型：多进程
• io密集型：多线程或协程+io切换
• 单纯的协程没有办法提高并发，只是代码之间的来回切换，叫上io才有意义

线程协程和进程

原文：https://www.cnblogs.com/python25/p/11578692.html