本文主要是介绍python基础-线程创建、线程池、进\线程异步回调(add_done_callback)、进\线程数据共享、ftp线程池,希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!
-
-
- 线程创建
- 线程进程pid
- 线程进程数据共享
- 线程ftp
- 线程池
- 线程池ftp
- 线程的一些其他方法
- 异步-回调函数
- ProcessPoolExecutor方式
- ThreadPoolExecutor方式
-
线程创建
进程只是用来把资源集中到一起(进程只是一个资源单位,或者说资源集合),而线程才是cpu上的执行单位。
每个进程有一个地址空间,而且默认就有一个控制线程
线程就是一条流水线工作的过程,一条流水线必须属于一个车间,一个车间的工作过程是一个进程
多线程(即多个控制线程)的概念是,在一个进程中存在多个控制线程,多个控制线程共享该进程的地址空间,相当于一个车间内有多条流水线,都共用一个车间的资源
我们之前了解过进程的2种创建方式
下面的代码是2种创建线程的方式
from threading import Thread
from multiprocessing import Process
import time,osdef task():print('%s is running' %os.getpid())time.sleep(2)print('%s is done' %os.getpid())class Mythread(Thread):def __init__(self,name):super().__init__()self.name=namedef run(self):print('%s is running' % os.getpid())time.sleep(5)print('%s is done' % os.getpid())if __name__ == '__main__':t=Thread(target=task)# t=Mythread('xxxxx')t.start()print('主')
输出如下:
E:\python\python_sdk\python.exe "E:/python/py_pro/1 开启线程的两种方式.py"
10336 is running
主
10336 is doneProcess finished with exit code 0
线程进程pid
part1:在主进程下开启多个线程,每个线程都跟主进程的pid一样
from threading import Thread
from multiprocessing import Process
import time,osdef task():print('partent:%s self:%s' %(os.getppid(),os.getpid()))time.sleep(5)if __name__ == '__main__':t=Thread(target=task,)# t=Process(target=task,)t.start()print('主',os.getppid(),os.getpid())
输出如下:
partent:9052 self:10120
主 9052 10120
开多个进程,每个进程都有不同的pid
from threading import Thread
from multiprocessing import Process
import time,osdef task():print('partent:%s self:%s' %(os.getppid(),os.getpid()))time.sleep(5)if __name__ == '__main__':t=Process(target=task,)t.start()print('主',os.getppid(),os.getpid())
输出如下:
主 9052 2668
partent:2668 self:8744
线程进程数据共享
进程之间数据不共享,但是进程之间可以通过ipc进行数据通讯
from threading import Thread
from multiprocessing import Process
import time,osn=100
def task():global nn=0if __name__ == '__main__':t=Process(target=task,)t.start()t.join()print('主',n)
输出如下:
主 100
线程之间内存空间共享
from threading import Thread
import time,osn=100
def task():global nn=0if __name__ == '__main__':t=Thread(target=task,)t.start()t.join()print('主',n)
输出如下:
主 0
线程ftp
服务端:
import multiprocessing
import threadingimport socket
s=socket.socket(socket.AF_INET,socket.SOCK_STREAM)
s.bind(('127.0.0.1',8081))
s.listen(5)def action(conn):while True:data=conn.recv(1024)print(data)conn.send(data.upper())if __name__ == '__main__':while True:conn,addr=s.accept()p=threading.Thread(target=action,args=(conn,))p.start()
客户端:
from socket import *client=socket(AF_INET,SOCK_STREAM)
client.connect(('127.0.0.1',8081))while True:msg=input('>>: ').strip()if not msg:continueclient.send(msg.encode('utf-8'))msg=client.recv(1024)print(msg.decode('utf-8'))
线程池
from concurrent.futures import ProcessPoolExecutor,ThreadPoolExecutor
from threading import current_thread
import time,random
def task(n):print('%s is running' %current_thread().getName())time.sleep(random.randint(1,3))return n**2if __name__ == '__main__':t=ThreadPoolExecutor(3) #默认是cpu的核数*5objs=[]for i in range(5):obj=t.submit(task,i)objs.append(obj)t.shutdown(wait=True)for obj in objs:print(obj.result())print('主',current_thread().getName())
输出如下:
E:\python\python_sdk\python.exe "E:/python/py_pro/4 线程池.py"
ThreadPoolExecutor-0_0 is running
ThreadPoolExecutor-0_1 is running
ThreadPoolExecutor-0_2 is runningThreadPoolExecutor-0_0 is runningThreadPoolExecutor-0_1 is running0
1
4
9
16
主 MainThread
线程池ftp
服务端:
from socket import *
from concurrent.futures import ThreadPoolExecutor
import osserver=socket(AF_INET,SOCK_STREAM)
server.setsockopt(SOL_SOCKET,SO_REUSEADDR,1)
server.bind(('127.0.0.1',8080))
server.listen(5)def talk(conn,client_addr):print('进程pid: %s' %os.getpid())while True:try:msg=conn.recv(1024)if not msg:breakconn.send(msg.upper())except Exception:breakif __name__ == '__main__':p=ThreadPoolExecutor(5)while True:conn,client_addr=server.accept()p.submit(talk,conn,client_addr)
客户端:
from socket import *client=socket(AF_INET,SOCK_STREAM)
client.connect(('127.0.0.1',8081))while True:msg=input('>>: ').strip()if not msg:continueclient.send(msg.encode('utf-8'))msg=client.recv(1024)print(msg.decode('utf-8'))
线程的一些其他方法
from threading import Thread,current_thread,enumerate,active_count
import time,osdef task():print('%s is running' %current_thread().getName())time.sleep(5)print('%s is done' %current_thread().getName())if __name__ == '__main__':t=Thread(target=task,name='xxxx')t.start()print(t.name)#查看当前活着的线程print(enumerate()[0].getName())print(active_count())print('主',current_thread().getName())print()
输出如下:
E:\python\python_sdk\python.exe "E:/python/py_pro/3 线程对象的其他属性或方法.py"
xxxx is running
xxxx
MainThread
2
主 MainThreadxxxx is done
异步-回调函数
ProcessPoolExecutor方式
我们之前总结的异步返回结果没有用到调用函数,接下来的是利用了回调函数
#pip install requests
import requests
from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor
from threading import current_thread
import time,os
def get(url):print('%s GET %s' %(os.getpid(),url))response=requests.get(url)time.sleep(3)if response.status_code == 200:return {'url':url,'text':response.text}def parse(obj):res=obj.result()print('[%s] <%s> (%s)' % (os.getpid(), res['url'],len(res['text'])))if __name__ == '__main__':urls = ['https://www.python.org','https://www.baidu.com','https://www.jd.com','https://www.tmall.com',]t=ProcessPoolExecutor(2)for url in urls:t.submit(get,url).add_done_callback(parse)t.shutdown(wait=True)print('主',os.getpid())
代码思路是:
t=ProcessPoolExecutor(2)开一个进程池,然后去并发下载网络数据,下载完毕后,
在主进程中add_done_callback去解析
这里由于主进程、子进程不是同一个进程空间,所以在解析数据时候,在主进程
输出如下:
E:\python\python_sdk\python.exe "E:/python/py_pro/5 补充异步的概念.py"
5628 GET https://www.python.org
4816 GET https://www.baidu.com4816 GET https://www.jd.com
[3204] <https://www.baidu.com> (2443)[3204] <https://www.python.org> (48856)
5628 GET https://www.tmall.com[3204] <https://www.jd.com> (124541)[3204] <https://www.tmall.com> (212080)
主 3204Process finished with exit code 0
ThreadPoolExecutor方式
import requests
from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor
from threading import current_thread
import time
import os
def get(url):print('%s GET %s,%s' %(current_thread().getName(),os.getpid(),url))response=requests.get(url)time.sleep(3)if response.status_code == 200:return {'url':url,'text':response.text}def parse(obj):res=obj.result()print('[%s] <%s> (%s)' % (current_thread().getName(), res['url'],len(res['text'])))if __name__ == '__main__':urls = ['https://www.python.org','https://www.baidu.com','https://www.jd.com','https://www.tmall.com',]t=ThreadPoolExecutor(2)for url in urls:t.submit(get,url).add_done_callback(parse)t.shutdown(wait=True)print('主',current_thread().getName(),os.getpid())
代码思路是:
t=ThreadPoolExecutor(2)开一个线程池,然后去并发下载网络数据,下载完毕后,
在主线程程中add_done_callback去解析
这里由于主线程、子线程是同一个进程空间,所以在解析数据时候,可能主线程、子线程都会解析
输出如下:
E:\python\python_sdk\python.exe "E:/python/py_pro/5 补充异步的概念.py"
ThreadPoolExecutor-0_0 GET 12956,https://www.python.org
ThreadPoolExecutor-0_1 GET 12956,https://www.baidu.com[ThreadPoolExecutor-0_1] <https://www.baidu.com> (2443)
ThreadPoolExecutor-0_1 GET 12956,https://www.jd.com[ThreadPoolExecutor-0_0] <https://www.python.org> (48856)
ThreadPoolExecutor-0_0 GET 12956,https://www.tmall.com[ThreadPoolExecutor-0_1] <https://www.jd.com> (124541)[ThreadPoolExecutor-0_0] <https://www.tmall.com> (212079)
主 MainThread 12956Process finished with exit code 0
这篇关于python基础-线程创建、线程池、进\线程异步回调(add_done_callback)、进\线程数据共享、ftp线程池的文章就介绍到这儿,希望我们推荐的文章对编程师们有所帮助!