免费网站商城建设,网站图片自动切换怎么做,wordpress抖音插件,叮当app制作线程 队列#xff1a;先进先出堆栈#xff1a;后进先出优先级#xff1a;数字越小优先级越大#xff0c;越先输出import queueq queue.Queue(3) # 先进先出--队列q.put(first)
q.put(2)
# q.put(third)
# q.put(4) #由于没有人取走#xff0c;就会卡主
q.put(4,block… 线程 队列先进先出堆栈后进先出优先级数字越小优先级越大越先输出 import queueq queue.Queue(3) # 先进先出--队列q.put(first)
q.put(2)
# q.put(third)
# q.put(4) #由于没有人取走就会卡主
q.put(4,blockFalse) #等同于q.get_nowait(), Ture 阻塞Flase不阻塞报异常满了
# # q.put(4,blockTrue,timeout3)print(q.get())
print(q.get())
print(q.get())
print(q.get(blockTrue,timeout3)) # 阻塞等待3秒 没有取走数据就报异常
# print(q.get(blockFalse)) #等同于q.get_nowait()
# print(q.get_nowait())
q queue.LifoQueue(3) #后进先出--堆栈
q.put(first)
q.put(2)
q.put(third)print(q.get())
print(q.get())
print(q.get())打印结果:
third
2
first
q queue.PriorityQueue(3) #优先级队列q.put((10,one))
q.put((40,two))
q.put((30,three))print(q.get())
print(q.get())
print(q.get())数字越小优先级越高
打印结果
(10, one)
(30, three)
(40, two)线程queue 进程池线程池 池是用来对进程(线程)的数量加以限制进程池计算密集型用多进程线程池IO密集型用多线程例如sockect网络通信就应该用多线程 from concurrent.futures import ProcessPoolExecutor,ThreadPoolExecutor
import os,time,random
sockect网络通信是IO操作所以用多线程
计算密集型用多进程
def task(name):print(name:%s pid:%s run %(name,os.getpid()))time.sleep(random.randint(1,3))if __name__ __main__:# pool ProcessPoolExecutor(4) # 进程池最多装4个进程,不指定的话默认是cpu的核数pool ThreadPoolExecutor(5)for i in range(10):pool.submit(task,yang%s %i) # 异步调用池子收了10个任务但同一时间只有4个任务在进行
pool.shutdown(waitTrue) # 类似join 代表往池子里面丢任务的入口关掉 计数器-1print(主)打印结果
name:yang0 pid:11120 run
name:yang1 pid:11120 run
name:yang2 pid:11120 run
name:yang3 pid:11120 run
name:yang4 pid:11120 runname:yang5 pid:11120 run
name:yang6 pid:11120 run
name:yang7 pid:11120 runname:yang8 pid:11120 run
name:yang9 pid:11120 run
主
from concurrent.futures import ProcessPoolExecutor,ThreadPoolExecutor
from threading import currentThread
import os,time,randomdef task():print(name:%s pid:%s run %(currentThread().getName(),os.getpid()))time.sleep(random.randint(1,3))if __name__ __main__:# pool ProcessPoolExecutor(4) # 进程池最多装4个进程,不指定的话默认是cpu的核数pool ThreadPoolExecutor(5)for i in range(10):pool.submit(task) # 异步调用池子收了10个任务但同一时间只有4个任务在进行
pool.shutdown(waitTrue) # 类似join 代表往池子里面丢任务的入口关掉 计数器-1print(主)打印结果
name:ThreadPoolExecutor-0_0 pid:14052 run
name:ThreadPoolExecutor-0_1 pid:14052 run
name:ThreadPoolExecutor-0_2 pid:14052 run
name:ThreadPoolExecutor-0_3 pid:14052 run
name:ThreadPoolExecutor-0_4 pid:14052 run
name:ThreadPoolExecutor-0_2 pid:14052 run
name:ThreadPoolExecutor-0_1 pid:14052 run
name:ThreadPoolExecutor-0_3 pid:14052 run
name:ThreadPoolExecutor-0_4 pid:14052 run
name:ThreadPoolExecutor-0_0 pid:14052 run
主进程池|线程池 同步调用和异步调用 提交任务的两种方式 同步调用:提交完任务后就在原地等待任务执行完毕拿到结果再执行下一行代码,导致程序是串行执行异步调用:提交完任务后不在原地等待任务执行完。回调机制自动触发 #1.同步调用:提交完任务后就在原地等待任务执行完毕拿到结果再执行下一行代码,导致程序是串行执行from concurrent.futures import ThreadPoolExecutor
import time
import randomdef la(name):print(%s is laing %name)time.sleep(random.randint(3,5))res random.randint(7,13)*#return {name:name,res:res}def weigh(shit):name shit[name]size len(shit[res])print(%s 拉了 %skg %(name,size))if __name__ __main__:pool ThreadPoolExecutor(10)shit1 pool.submit(la,alex).result()weigh(shit1)shit2 pool.submit(la,yang).result()weigh(shit2)shit3 pool.submit(la,hang).result()weigh(shit3)打印结果
alex is laing
alex 拉了 8kg
yang is laing
yang 拉了 8kg
hang is laing
hang 拉了 7kg同步调用 #2.异步调用:提交完任务后不在原地等待任务执行完
from concurrent.futures import ThreadPoolExecutor
import time
import randomdef la(name):print(%s is laing %name)time.sleep(random.randint(3,5))res random.randint(7,13)*#return {name:name,res:res}# weigh({name:name,res:res}) # 这样写,所有功能 不能体现出解耦合def weigh(shit):shit shit.result() # 拿到是一个对象需要进行result()name shit[name]size len(shit[res])print(%s 拉了 %skg %(name,size))if __name__ __main__:pool ThreadPoolExecutor(10)shit1 pool.submit(la,alex).add_done_callback(weigh)shit2 pool.submit(la,yang).add_done_callback(weigh)shit3 pool.submit(la,hang).add_done_callback(weigh)打印结果:
alex is laing
yang is laing
hang is laing
hang 拉了 10kg
alex 拉了 7kg
yang 拉了 12kg异步调用 异步调用的应用 from concurrent.futures import ThreadPoolExecutor
import requests
import timedef get(url):print(GET %s%url)response requests.get(url)time.sleep(3)return {url:url,content:response.text}def parse(res):res res.result()print(%s parse res is %s %(res[url],len(res[content])))if __name__ __main__:urls [http://www.cnblogs.com/linhaifeng,https://www.python.org,https://www.openstack.org,]pool ThreadPoolExecutor(2)for url in urls:pool.submit(get,url).add_done_callback(parse)打印结果
GET http://www.cnblogs.com/linhaifeng
GET https://www.python.org
http://www.cnblogs.com/linhaifeng parse res is 16320
GET https://www.openstack.org
https://www.python.org parse res is 49273
https://www.openstack.org parse res is 64040应用 转载于:https://www.cnblogs.com/Mryang123/p/8921962.html
