Python 三程三器的那些事

#! /usr/bin/env python
# -*- coding: utf-8 -*-
import time

def timer(func):
    start_time = time.time()
    func()
    print '函数执行时间为', time.time() - start_time

def test():
    print '开始执行test'
    time.sleep(3)
    print 'test执行结束'


timer(test)
'''
开始执行test
test执行结束
函数执行时间为 3.00332999229
'''

import time
def bar():
    time.sleep(3)
    print("in the bar")
def test2(func):
    print(func)
    return func
bar = test2(bar)
bar()

def foo():
    print("in the foo")
    def bar():
        print("in the bar")
    bar()
foo()

import time
def timer(func):   #timer(test1)  func=test1
    def deco(*args,**kwargs):
        start_time = time.time()
        func(*args,**kwargs)      #run test1
        stop_time = time.time()
        print("running time is %s"%(stop_time-start_time))
    return deco
@timer     # test1=timer(test1)
def test1():
    time.sleep(3)
    print("in the test1")
@timer
def test2(name):
    print("in the test2",name)
test1()
test2("tom")

import time
user,passwd = 'aaa','123'
def auth(func):
    def wrapper(*args,**kwargs):
        username = input("Username:").strip()
        password = input("Password:").strip()
        if user == username and password == passwd:
            print("User has passed authentication")
            res = func(*args,**kwargs)   #这里执行func()相当于执行调用的函数如home()
            return res          #为了获得home()函数返回值，可以将执行结果赋值给res然后返回print(home())结果是"from home"而不是"None"了
        else:
            exit("Invalid username or password")
    return wrapper
def index():
    print("welcome to index page")
@auth
def home():
    print("welcome to home page")
    return "from home"
@auth
def bbs():
    print("welcome to bbs page")
index()
print(home())   #在这里调用home()相当于调用wrapper()
bbs()

import time
user,passwd = 'aaa','123'
def auth(auth_type):
    print("auth func:",auth_type)
    def outer_wrapper(func):
        def wrapper(*args, **kwargs):
            print("wrapper func args:", *args, **kwargs)
            if auth_type == "local":
                username = input("Username:").strip()
                password = input("Password:").strip()
                if user == username and passwd == password:
                    print("\033[32;1mUser has passed authentication\033[0m")
                    res = func(*args, **kwargs)  # from home
                    print("---after authenticaion ")
                    return res
                else:
                    exit("\033[31;1mInvalid username or password\033[0m")
            elif auth_type == "ldap":
                print("搞毛线ldap,不会。。。。")

        return wrapper
    return outer_wrapper

def index():
    print("welcome to index page")
@auth(auth_type="local") # home = wrapper()
def home():
    print("welcome to home  page")
    return "from home"

@auth(auth_type="ldap")
def bbs():
    print("welcome to bbs  page")

index()
print(home()) #wrapper()
bbs()

#! /usr/bin/env python
# -*- coding: utf-8 -*-
import time
def auth(auth_type):
    print("auth func:",auth_type)
    def outer_wrapper(func):
        def wrapper(*args, **kwargs):
            print("wrapper func args:", *args, **kwargs)
            print('运行前')
            func(*args, **kwargs)
            print('运行后')
        return wrapper
    return outer_wrapper

@auth(auth_type="local") # home = wrapper()
def home():
    print("welcome to home  page")
    return "from home"
home()

#! /usr/bin/env python
# -*- coding: utf-8 -*-
import time

def timer(func):                    #timer(test1)  func=test1
    def deco(*args,**kwargs):       # # 函数嵌套
        start_time = time.time()
        func(*args,**kwargs)        # 跨域访问，引用了外部变量func   (func实质是函数内存地址)
        stop_time = time.time()
        print "running time is %s"%(stop_time-start_time)
    return deco                    # 内层函数作为外层函数返回值

def test(name):
    print "in the test2",name
    time.sleep(2)

test = timer(test)   # 等价于 ==》 @timer语法糖
test("tom")
'''
运行结果：
in the test2 tom
running time is 2.00302696228
'''

def fib(max_num):
    a,b = 1,1
    while a < max_num:
        yield b
        a,b=b,a+b

g = fib(10)               #生成一个生成器：[1，2, 3, 5, 8, 13]
print(g.__next__())       #第一次调用返回：1
print(list(g))            #把剩下元素变成列表：[2, 3, 5, 8, 13]

def consumer(name):
    print("%s 准备吃包子啦!" %name)
    while True:
       baozi = yield
       print("包子[%s]来了,被[%s]吃了!" %(baozi,name))
c = consumer("Tom")
c.__next__()
b1 = "韭菜馅包子"
c.send(b1)

# c.send(b1)作用：
# c.send()的作用是给yied的传递一个值，并且每次调用c.send()的同时自动调用一次__next__
'''运行结果：
Tom 准备吃包子啦!
包子[韭菜馅包子]来了,被[Tom]吃了!
'''

import time
def consumer(name):
    print("%s 准备吃包子啦!" %name)
    while True:
       baozi = yield
       print("包子[%s]来了,被[%s]吃了!" %(baozi,name))
def producer(name):
    c = consumer('A')
    c2 = consumer('B')
    c.__next__()
    c2.__next__()
    print("老子开始准备做包子啦!")
    for i in range(10):
        time.sleep(1)
        print("做了2个包子!")
        c.send(i)
        c2.send(i)
producer("alex")

'''运行结果：
A 准备吃包子啦!
B 准备吃包子啦!
老子开始准备做包子啦!
做了2个包子!
包子[0]来了,被[A]吃了!
包子[0]来了,被[B]吃了!
做了2个包子!
包子[1]来了,被[A]吃了!
包子[1]来了,被[B]吃了!
做了2个包子!
包子[2]来了,被[A]吃了!
包子[2]来了,被[B]吃了!
做了2个包子!
包子[3]来了,被[A]吃了!
包子[3]来了,被[B]吃了!
做了2个包子!
包子[4]来了,被[A]吃了!
包子[4]来了,被[B]吃了!
做了2个包子!
包子[5]来了,被[A]吃了!
包子[5]来了,被[B]吃了!
'''

from collections import Iterable
print(isinstance([],Iterable))                               #True
print(isinstance({},Iterable))                               #True
print(isinstance((),Iterable))                               #True
print(isinstance("aaa",Iterable))                           #True
print(isinstance((x for x in range(10)),Iterable))          #True

from collections import Iterator
t = [1,2,3,4]
print(isinstance(t,Iterator))           #False
t1 = iter(t)
print(isinstance(t1,Iterator))          #True

#! /usr/bin/env python
# -*- coding: utf-8 -*-
class MyRange(object):
    def __init__(self, n):
        self.idx = 0
        self.n = n

    def __iter__(self):
        return self

    def next(self):
        if self.idx < self.n:
            val = self.idx
            self.idx += 1
            return self.n[val]
        else:
            raise StopIteration()


l = [4,5,6,7,8]
obj = MyRange(l)
print obj.next()      # 4
print obj.next()      # 5
print obj.next()      # 6

#! /usr/bin/env python
# -*- coding: utf-8 -*
l = [1,2,3,4,5]                  # 列表是一个可迭代对象，不是一个迭代器
print dir(l)                     # 所以 l 中有 __iter__() 方法，没有 __next__()方法
iter_obj = l.__iter__()          # __iter__()方法返回迭代器对象本身(这个迭代器对象就会有 next 方法了)

print '###################################\n'
print iter_obj.next()     # 1
print iter_obj.next()     # 2
print iter_obj.next()     # 3

import threading
import time

def sayhi(num):                                   # 定义每个线程要运行的函数
    print("running on number:%s" % num)
    time.sleep(3)

#1、target=sayhi ：sayhi是定义的一个函数的名字
#2、args=(1,)    ： 括号内写的是函数的参数
t1 = threading.Thread(target=sayhi, args=(1,))    # 生成一个线程实例
t2 = threading.Thread(target=sayhi, args=(2,))    # 生成另一个线程实例

t1.start()                                        # 启动线程
t2.start()                                        # 启动另一个线程

print(t1.getName())                               # 获取线程名
print(t2.getName())

import threading
import time

class MyThread(threading.Thread):
    def __init__(self,num):
        threading.Thread.__init__(self)
        self.num = num

    def run(self):#定义每个线程要运行的函数
        print("running on number:%s" %self.num)
        time.sleep(3)

if __name__ == '__main__':
    t1 = MyThread(1)
    t2 = MyThread(2)
    t1.start()
    t2.start()

import threading
import time

def sayhi(num): #定义每个线程要运行的函数
    print("running on number:%s" %num)
    time.sleep(3)
for i in range(50):
    t = threading.Thread(target=sayhi,args=('t-%s'%i,))
    t.start()

import threading
import time
start_time = time.time()

def sayhi(num): #定义每个线程要运行的函数
    print("running on number:%s" %num)
    time.sleep(3)

t_objs = []    #将进程实例对象存储在这个列表中
for i in range(50):
    t = threading.Thread(target=sayhi,args=('t-%s'%i,))
    t.start()          #启动一个线程，程序不会阻塞
    t_objs.append(t)
print(threading.active_count())    #打印当前活跃进程数量
for t in t_objs: #利用for循环等待上面50个进程全部结束
    t.join()     #阻塞某个程序
print(threading.current_thread())    #打印执行这个命令进程

print("----------------all threads has finished.....")
print(threading.active_count())
print('cost time:',time.time() - start_time)

import threading
import time
start_time = time.time()

def sayhi(num): #定义每个线程要运行的函数
    print("running on number:%s" %num)
    time.sleep(3)
for i in range(50):
    t = threading.Thread(target=sayhi,args=('t-%s'%i,))
    t.setDaemon(True)  #把当前线程变成守护线程，必须在t.start()前设置
    t.start()          #启动一个线程，程序不会阻塞
print('cost time:',time.time() - start_time)

import time
import threading
lock = threading.Lock()          #1 生成全局锁
def addNum():
    global num                  #2 在每个线程中都获取这个全局变量
    print('--get num:',num )
    time.sleep(1)
    lock.acquire()              #3 修改数据前加锁
    num  -= 1                   #4 对此公共变量进行-1操作
    lock.release()              #5 修改后释放

# 1）第一步：count = 0   count初始值为0
        # 2）第二步：线程1要执行对count加1的操作首先申请GIL全局解释器锁
        # 3）第三步：调用操作系统原生线程在操作系统中执行
        # 4）第四步：count加1还未执行完毕，时间到了被要求释放GIL
        # 5）第五步：线程1释放了GIL后线程2此时也要对count进行操作，此时线程1还未执行完，所以count还是0
        # 6）第六步：线程2此时拿到count = 0后也要对count进行加1操作，假如线程2执行很快，一次就完成了
        #    count加1的操作，那么count此时就从0变成了1
        # 7）第七步：线程2执行完加1后就赋值count=1并释放GIL
        # 8）第八步：线程2执行完后cpu又交给了线程1，线程1根据上下文继续执行count加1操作，先拿到GIL
        #    锁，完成加1操作，由于线程1先拿到的数据count=0，执行完加1后结果还是1
        # 9）第九步：线程1将count=1在次赋值给count并释放GIL锁，此时连个线程都对数据加1，但是值最终是1

from threading import Thread,Lock
import time
mutexA=Lock()
mutexB=Lock()

class MyThread(Thread):
    def run(self):
        self.func1()
        self.func2()
    def func1(self):
        mutexA.acquire()
        print('\033[41m%s 拿到A锁\033[0m' %self.name)

        mutexB.acquire()
        print('\033[42m%s 拿到B锁\033[0m' %self.name)
        mutexB.release()

        mutexA.release()

    def func2(self):
        mutexB.acquire()
        print('\033[43m%s 拿到B锁\033[0m' %self.name)
        time.sleep(2)

        mutexA.acquire()
        print('\033[44m%s 拿到A锁\033[0m' %self.name)
        mutexA.release()

        mutexB.release()

if __name__ == '__main__':
    for i in range(2):
        t=MyThread()
        t.start()

# 运行结果：输出下面结果后程序卡死，不再向下进行了
# Thread-1 拿到A锁
# Thread-1 拿到B锁
# Thread-1 拿到B锁
# Thread-2 拿到A锁

from threading import Thread,Lock,RLock
import time

mutexA=mutexB=RLock()

class MyThread(Thread):
    def run(self):
        self.f1()
        self.f2()

    def f1(self):
        mutexA.acquire()
        print('%s 拿到A锁' %self.name)

        mutexB.acquire()
        print('%s 拿到B锁' %self.name)
        mutexB.release()

        mutexA.release()

    def f2(self):
        mutexB.acquire()
        print('%s 拿到B锁' % self.name)
        time.sleep(0.1)
        mutexA.acquire()
        print('%s 拿到A锁' % self.name)
        mutexA.release()

        mutexB.release()

if __name__ == '__main__':
    for i in range(5):
        t=MyThread()
        t.start()
# 下面是运行结果：不会产生死锁
# Thread-1 拿到A锁
# Thread-1 拿到B锁
# Thread-1 拿到B锁
# Thread-1 拿到A锁
# Thread-2 拿到A锁
# Thread-2 拿到B锁
# Thread-2 拿到B锁
# Thread-2 拿到A锁
# Thread-4 拿到A锁
# Thread-4 拿到B锁
# Thread-4 拿到B锁
# Thread-4 拿到A锁
# Thread-3 拿到A锁
# Thread-3 拿到B锁
# Thread-3 拿到B锁
# Thread-3 拿到A锁
# Thread-5 拿到A锁
# Thread-5 拿到B锁
# Thread-5 拿到B锁
# Thread-5 拿到A锁

# import threading,time
# def run(n):
#     semaphore.acquire()
#     time.sleep(1)
#     print("run the thread: %s\n" %n)
#     semaphore.release()
# 
# if __name__ == '__main__':
#     semaphore  = threading.BoundedSemaphore(5) #最多允许5个线程同时运行
#     for i in range(22):
#         t = threading.Thread(target=run,args=(i,))
#         t.start()
# 
# while threading.active_count() != 1:
#     pass #print threading.active_count()
# else:
#     print('----all threads done---')


# 代码结果说明：这里可以清晰看到运行时0-4是同时运行的没有顺序，而且是前五个，
# 表示再semaphore这个信号量的定义下程序同时仅能执行5个线程

import time,threading

event = threading.Event()
#第一：写一个红绿灯的死循环
def lighter():
    count = 0
    event.set()               #1先设置为绿灯
    while True:
        if count > 5 and count <10:      #2改成红灯
            event.clear()          #3把标志位清了
            print("red light is on.....")
        elif count > 10:
            event.set()            #4再设置标志位，变绿灯
            count = 0
        else:
            print("green light is on.....")
        time.sleep(1)
        count += 1

#第二：写一个车的死循环
def car(name):
    while True:
        if event.is_set():         #设置了标志位代表绿灯
            print("[%s] is running"%name)
            time.sleep(1)
        else:
            print('[%s] sees red light, waiting......'%name)
            event.wait()
            print('[%s] green light is on,start going.....'%name)

light = threading.Thread(target=lighter,)
light.start()
car1 = threading.Thread(target=car,args=("Tesla",))
car1.start()

import multiprocessing,time,threading

#3 被多线程调用的函数
def thread_run():
    print(threading.get_ident())   #打印线程id号
    time.sleep(2)

#2 被多进程调用的函数，以及在这个函数中起一个进程
def run(name):
    time.sleep(2)
    print("hello",name)
    t = threading.Thread(target=thread_run,)  #在进程调用的函数中启用一个线程
    t.start()

#1 一次性启动多个进程
if __name__ == '__main__':
    for i in range(10):
        p = multiprocessing.Process(target=run,args=('bob %s'%i,)) #启用一个多线程
        p.start()

from multiprocessing import Process
import queue
import threading
def f():
    q.put([42, None, 'hello'])
 
if __name__ == '__main__':
    q = queue.Queue()              #1 在父进程中定义一个队列实例q
    # p = threading.Thread(target=f,)    #在线程程中就可以相互访问，线程中内存共享
    p = Process(target=f,)        #2 在父进程中起一个子进程 p，在子进程中使用父进程的q会报错
    p.start()
    print(q.get())
    p.join()

from multiprocessing import Process, Queue

def f(qq):  # 将符进程中的q传递过来叫qq
    qq.put([42, None, 'hello'])  # 此时子进程就可以使用符进程中的q

if __name__ == '__main__':
    q = Queue()  # 使用Queue()在父进程中定义一个队列实例q
    p = Process(target=f, args=(q,))  # 在父进程中起一个子进程 p，将父进程刚定义的q传递给子进程p
    p.start()
    print(q.get())
    p.join()

# 运行结果： [42, None, 'hello']

from multiprocessing import Process, Pipe

def f(conn):
    conn.send([42, None, 'hello'])  # 3 子进程发送数据，就像socket一样
    print("son process recv:", conn.recv())
    conn.close()

if __name__ == '__main__':
    parent_conn, child_conn = Pipe()
    # 1 生成一个管道实例，实例一生成就会生成两个返回对象，一个是管道这头，一个是管道那头
    p = Process(target=f, args=(child_conn,))  # 2 启动一个子进程将管道其中一头传递给子进程
    p.start()
    print(parent_conn.recv())  # 4 父进程收消息 # prints "[42, None, 'hello']"
    parent_conn.send('i am parent process')
    p.join()

# 运行结果：
# [42, None, 'hello']
# son process recv: i am parent process

from multiprocessing import Process, Manager
import os

def f(d, l):
    d[1] = '1'  # 是个进程对字典放入的是同一个值，所以看上去效果不明显
    l.append(os.getpid())  # 将这是个进程的进程id放入列表中


if __name__ == '__main__':
    with Manager() as manager:  # 1 将Manager()赋值给manager
        d = manager.dict()  # 2 定义一个可以在多个进程间可以共享的字典
        l = manager.list(range(5))  # 3 定义一个可以在多个进程间可以共享的列表，默认写五个数据
        p_list = []
        for i in range(10):  # 生成是个进程
            p = Process(target=f, args=(d, l))  # 将刚刚生成的可共享字典和列表传递给子进程
            p.start()
            p_list.append(p)
        for res in p_list:
            res.join()
        print(d)
        print(l)

from multiprocessing import Process, Lock
def f(l, i):
    l.acquire()                     #一个进程要打印数据时先锁定
    print('hello world', i)
    l.release()                     #打印完毕后就释放这把锁
if __name__ == '__main__':
    lock = Lock()                   #先生成一把锁
    for num in range(5):
        Process(target=f, args=(lock, num)).start()

# 运行结果：
# hello world 4
# hello world 0
# hello world 2
# hello world 3
# hello world 1

from  multiprocessing import Process,Pool
import time,os
def foo(i):
    time.sleep(2)
    print("in the process",os.getpid()) #打印子进程的pid
    return i+100

def call(arg):
    print('-->exec done:',arg,os.getpid())

if __name__ == '__main__':
    pool = Pool(3)                      #进程池最多允许5个进程放入进程池
    print("主进程pid：",os.getpid())     #打印父进程的pid
    for i in range(10):
        #用法1 callback作用是指定只有当Foo运行结束后就执行callback调用的函数,父进程调用的callback函数
        pool.apply_async(func=foo, args=(i,),callback=call)

        #用法2 串行 启动进程不在用Process而是直接用pool.apply()
        # pool.apply(func=foo, args=(i,))

    print('end')
    pool.close()    #关闭pool
    pool.join()     #进程池中进程执行完毕后再关闭，如果注释，那么程序直接关闭。

#!/usr/bin/env python
#coding=utf8
 
import os, sys, time
#产生子进程
pid = os.fork()
 
if pid == 0:
    #子进程退出
    sys.exit(0)
#父进程休息30秒
time.sleep(30)
# 先产生一个子进程，子进程退出，父进程休息30秒,那就会产生一个僵尸进程

[root@linux-node4 ~]# ps -ef| grep defunct
root     110401  96083  0 19:11 pts/2    00:00:00 python defunct.py
root     110402 110401  0 19:11 pts/2    00:00:00 [python] <defunct>
root     110406  96105  0 19:11 pts/3    00:00:00 grep --color=auto defunct

import time
import queue

def consumer(name):
    print("--->starting eating baozi...")
    while True:
        new_baozi = yield  # 只要遇到yield程序就返回，yield还可以接收数据
        print("[%s] is eating baozi %s" % (name, new_baozi))
        time.sleep(1)

def producer():
    r = con.__next__()  # 直接调用消费者的__next__方法
    r = con2.__next__()  # 函数里面有yield第一次加括号调用会变成一个生成器函数不执行，运行next才执行
    n = 0
    while n < 5:
        n += 1
        con.send(n)  # send恢复生成器同时并传递一个值给yield
        con2.send(n)
        print("\033[32;1m[producer]\033[0m is making baozi %s" % n)

if __name__ == '__main__':
    con = consumer("c1")
    con2 = consumer("c2")
    p = producer()

from greenlet import greenlet

def test1():
    print(12)       #4 gr1会调用test1()先打印12
    gr2.switch()    #5 然后gr2.switch()就会切换到gr2这个协程
    print(34)       #8 由于在test2()切换到了gr1，所以gr1又从上次停止的位置开始执行
    gr2.switch()    #9 在这里又切换到gr2，会再次切换到test2()中执行

def test2():
    print(56)       #6 启动gr2后会调用test2()打印56
    gr1.switch()    #7 然后又切换到gr1
    print(78)       #10 切换到gr2后会接着上次执行，打印78

gr1 = greenlet(test1)    #1 启动一个协程gr1
gr2 = greenlet(test2)    #2 启动第二个协程gr2
gr1.switch()             #3 首先gr1.switch() 就会去执行gr1这个协程

import gevent

def func1():
    print('\033[31;1m第一次打印\033[0m')
    gevent.sleep(2)          # 为什么用gevent.sleep()而不是time.sleep()因为是为了模仿I/O
    print('\033[31;1m第六次打印\033[0m')

def func2():
    print('\033[32;1m第二次打印\033[0m')
    gevent.sleep(1)
    print('\033[32;1m第四次打印\033[0m')

def func3():
    print('\033[32;1m第三次打印\033[0m')
    gevent.sleep(1)
    print('\033[32;1m第五次打印\033[0m')

gevent.joinall([            # 将要启动的多个协程放到event.joinall的列表中，即可实现自动切换
    gevent.spawn(func1),    # gevent.spawn(func1)启动这个协程
    gevent.spawn(func2),
    gevent.spawn(func3),
])

# 运行结果：
# 第一次打印
# 第二次打印
# 第三次打印
# 第四次打印
# 第五次打印
# 第六次打印

from urllib import request
import gevent,time
from gevent import monkey
monkey.patch_all()      #把当前程序所有的I/O操作给我单独做上标记

def f(url):
    print('GET: %s' % url)
    resp = request.urlopen(url)
    data = resp.read()
    print('%d bytes received from %s.' % (len(data), url))

#1 并发执行部分
time_binxing = time.time()
gevent.joinall([
        gevent.spawn(f, 'https://www.python.org/'),
        gevent.spawn(f, 'https://www.yahoo.com/'),
        gevent.spawn(f, 'https://github.com/'),
])
print("并行时间：",time.time()-time_binxing)

#2 串行部分
time_chuanxing = time.time()
urls = [
        'https://www.python.org/',
        'https://www.yahoo.com/',
        'https://github.com/',
                                        ]
for url in urls:
    f(url)
print("串行时间：",time.time()-time_chuanxing)

# 注：为什么要在文件开通使用monkey.patch_all()
# 1. 因为有很多模块在使用I / O操作时Gevent是无法捕获的，所以为了使Gevent能够识别出程序中的I / O操作。
# 2. 就必须使用Gevent模块的monkey模块，把当前程序所有的I / O操作给我单独做上标记
# 3.使用monkey做标记仅用两步即可：
      第一步(导入monkey模块)：  from gevent import monkey
      第二步(声明做标记)    ：   monkey.patch_all()

import gevent
from gevent import socket,monkey     #下面使用的socket是Gevent的socket，实际测试monkey没用
# monkey.patch_all()

def server(port):
    s = socket.socket()
    s.bind(('0.0.0.0',port))
    s.listen(5)
    while True:
        cli,addr = s.accept()
        gevent.spawn(handle_request,cli)

def handle_request(conn):
    try:
        while True:
            data = conn.recv(1024)
            print('recv:',data)
            conn.send(data)
            if not data:
                conn.shutdown(socket.SHUT_WR)
    except Exception as e:
        print(e)
    finally:
        conn.close()

if __name__=='__main__':
    server(8001)

import socket
HOST = 'localhost'    # The remote host
PORT = 8001           # The same port as used by the server
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect((HOST, PORT))
while True:
    msg = bytes(input(">>:"),encoding="utf8").strip()
    if len(msg) == 0:continue
    s.sendall(msg)
    data = s.recv(1024)
    print('Received', repr(data))
s.close()

from concurrent.futures import ThreadPoolExecutor
import time
def return_future_result(message):
    time.sleep(2)
    return message
pool = ThreadPoolExecutor(max_workers=2)                 # 创建一个最大可容纳2个task的线程池
future1 = pool.submit(return_future_result, ("hello"))  # 往线程池里面加入一个task
future2 = pool.submit(return_future_result, ("world"))  # 往线程池里面加入一个task

print(future1.done())      # 判断task1是否结束
time.sleep(3)
print(future2.done())      # 判断task2是否结束
print(future1.result())    # 查看task1返回的结果
print(future2.result())    # 查看task2返回的结果

# 运行结果：
# False   # 这个False与下面的True会等待3秒
# True    # 后面三个输出都是一起打出来的
# hello
# world

import concurrent.futures
import urllib.request
URLS = ['http://httpbin.org', 'http://example.com/', 'https://api.github.com/']
def load_url(url, timeout):
    with urllib.request.urlopen(url, timeout=timeout) as conn:
        return conn.read()

# We can use a with statement to ensure threads are cleaned up promptly
with concurrent.futures.ThreadPoolExecutor(max_workers=3) as executor:
    # Start the load operations and mark each future with its URL
    # future_to_url = {executor.submit(load_url, url, 60): url for url in URLS}   # 这一句相当于下面for循环获取的字典
    future_to_url = {}
    for url in URLS:
        future_to_url[executor.submit(load_url,url,60)] = url      # {'future对象':'url'}   future对象作为key，url作为value
    for future in concurrent.futures.as_completed(future_to_url): # as_completed返回已经有返回结果的future对象
        url = future_to_url[future]                                # 通过future对象获取对应的url
        try:
            data = future.result()                                 # 获取future对象的返回结果
        except Exception as exc:
            print('%r generated an exception: %s' % (url, exc))
        else:
            print('%r page is %d bytes' % (url, len(data)))

from concurrent.futures import ThreadPoolExecutor

# 创建线程池
executor = ThreadPoolExecutor(10)

def test_function(num1,num2):
    return "%s + %s = %s"%(num1,num2,num1+num2)
result_iterators = executor.map(test_function,[1,2,3],[5,6,7])

for result in result_iterators:
    print(result)

# 1 + 5 = 6
# 2 + 6 = 8
# 3 + 7 = 10

import concurrent.futures
import urllib.request

URLS = ['http://httpbin.org', 'http://example.com/', 'https://api.github.com/']

def load_url(url):
    with urllib.request.urlopen(url, timeout=60) as conn:
        return conn.read()

# We can use a with statement to ensure threads are cleaned up promptly
with concurrent.futures.ThreadPoolExecutor(max_workers=3) as executor:
    future_dic = {}
    for url, data in zip(URLS, executor.map(load_url, URLS)):
        print('%r page is %d bytes' % (url, len(data)))
        future_dic[url] = data     # {'url':'执行结果'}   url作为key，执行结果作为value

# 'http://httpbin.org' page is 13011 bytes
# 'http://example.com/' page is 1270 bytes
# 'https://api.github.com/' page is 2039 bytes

import requests
url_list = [
    'https://www.baidu.com',
    'http:/https://img.qb5200.com/download-x/dig.chouti.com/',
]

for url in url_list:
    result = requests.get(url)
    print(result.text)

import requests
from concurrent.futures import ProcessPoolExecutor

def fetch_request(url):
    result = requests.get(url)
    print(result.text)

url_list = [
    'https://www.baidu.com',
    'https://www.google.com/',         #google页面会卡住，知道页面超时后这个进程才结束
    'http:/https://img.qb5200.com/download-x/dig.chouti.com/',          #chouti页面内容会直接返回，不会等待Google页面的返回
]

if __name__ == '__main__':
    pool = ProcessPoolExecutor(10)        # 创建线程池
    for url in url_list:
        pool.submit(fetch_request,url)    # 去线程池中获取一个进程，进程去执行fetch_request方法
    pool.shutdown(False)

import requests
from concurrent.futures import ThreadPoolExecutor

def fetch_request(url):
    result = requests.get(url)
    print(result.text)

url_list = [
    'https://www.baidu.com',
    'https://www.google.com/',         #google页面会卡住，知道页面超时后这个进程才结束
    'http:/https://img.qb5200.com/download-x/dig.chouti.com/',          #chouti页面内容会直接返回，不会等待Google页面的返回
]

pool = ThreadPoolExecutor(10)            # 创建一个线程池，最多开10个线程
for url in url_list:
    pool.submit(fetch_request,url)       # 去线程池中获取一个线程，线程去执行fetch_request方法

pool.shutdown(True)                      # 主线程自己关闭，让子线程自己拿任务执行

from concurrent.futures import ThreadPoolExecutor
import requests

def fetch_async(url):
    response = requests.get(url)
    return response.text

def callback(future):
    print(future.result())

url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ThreadPoolExecutor(5)
for url in url_list:
    v = pool.submit(fetch_async, url)
    v.add_done_callback(callback)
pool.shutdown(wait=True)

import gevent
import requests
from gevent import monkey

monkey.patch_all()

# 这些请求谁先回来就先处理谁
def fetch_async(method, url, req_kwargs):
    response = requests.request(method=method, url=url, **req_kwargs)
    print(response.url, response.content)

# ##### 发送请求 #####
gevent.joinall([
    gevent.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}),
    gevent.spawn(fetch_async, method='get', url='https://www.google.com/', req_kwargs={}),
    gevent.spawn(fetch_async, method='get', url='https://github.com/', req_kwargs={}),
])