asyncio模块：asyncio是Python用于解决异步IO编程的整套解决方案。

基于asyncio的框架：tornado（实现可直接部署的web服务器）、gevent、twisted（scrapy，django channels），使用这些框架必须有对应的异步驱动支持（如tornado中使用pymysql则不能异步）。

使用asyncio

import asyncio
import time
# 定义异步函数
async def get_html(url):
    print("start get url")
    await asyncio.sleep(2)
    # time.sleep(5)   # 协程是单线程执行，time.sleep是同步阻塞接口，不应在协程中实现
    print("end get url")
start_time = time.time()
loop = asyncio.get_event_loop()     # 创建事件循环（单线程：所有的函数调用都在loop中执行）
tasks = [
    get_html("http://www.imooc.com") for i in range(10)
loop.run_until_complete(asyncio.wait(tasks))    # 类似join，等待协程执行完成才往下执行
print(time.time() - start_time)
获取协程返回值
import asyncio
import time
from functools import partial
async def get_html(url):
    print("start get url")
    await asyncio.sleep(2)
    return "ywh"
def callback(url, future):
    print(url)
    print("send email to ywh")
start_time = time.time()
loop = asyncio.get_event_loop()
# get_future = asyncio.ensure_future(get_html("http://www.imooc.com"))
task = loop.create_task(get_html("http://www.imooc.com"))   # 创建一个任务，返回Future对象
task.add_done_callback(             
    partial(callback, "http://www.imooc.com")           # 把callback包装可接收参数的偏函数
)       # 执行get_html，完成后调用回调函数callback，最后再返回get_html的结果
loop.run_until_complete(task)
print(task.result())        # 获取Future对象的结果
wait与gather：gather是更高层次的封装，可以将task分组管理；
import asyncio
import time
async def get_html(url):
    print("start get url")
    await asyncio.sleep(2)
    print("end get url")
if __name__ == "__main__":
    start_time = time.time()
    loop = asyncio.get_event_loop()
    tasks = [get_html("http://www.imooc.com") for i in range(10)]
    # loop.run_until_complete(asyncio.gather(*tasks))
    # print(time.time() - start_time)
    group1 = [get_html("http://projectsedu.com") for i in range(2)]
    group2 = [get_html("http://www.imooc.com") for i in range(2)]
    group1 = asyncio.gather(*group1)
    group2 = asyncio.gather(*group2)
    group2.cancel()
    loop.run_until_complete(asyncio.gather(group1, group2))
    print(time.time() - start_time)
协程的取消，嵌套
import asyncio
loop = asyncio.get_event_loop()
loop.run_forever()                  # 一直运行不会停止
loop.run_until_complete()           # 运行指定协程后停止
取消future(task)
import asyncio
import time
async def get_html(sleep_times):
    print("waiting")
    await asyncio.sleep(sleep_times)
    print("done after {}s".format(sleep_times))
tasks = [get_html(2), get_html(3), get_html(4)]     # 模拟三个执行时长不同的任务
loop = asyncio.get_event_loop()
    loop.run_until_complete(asyncio.wait(tasks))
except KeyboardInterrupt as e:                  # 人为制造取消信号：捕捉键盘ctrl + c异常
    all_tasks = asyncio.Task.all_tasks()        # 不需要传入loop：自动从events.get_event_loop中获取loop，并获取loop中的所有task
    for task in all_tasks:                      # 获取所有tasks
        print(task.cancel())                    # 取消task，返回取消结果
    loop.stop()
    loop.run_forever()      # loop调用stop后必须重新调用run_forever，否则会抛出异常
finally:
    loop.close()
嵌套协程的调度过程（task -> print_sum -> compute）：
import asyncio
# print_sum协程嵌套await_compute协程
async def compute(x, y):                
    print("Compute %s + %s ..." %(x, y))
    await asyncio.sleep(1.0)                    # 3
    return x + y                                # 4
async def print_sum(x, y):
    result = await compute(x, y)                # 2
    print("%s + %s = %s" %(x, y, result))       # 5
loop = asyncio.get_event_loop()
loop.run_until_complete(print_sum(1, 2))        # 1
loop.close()
创建loop和需要提交到loop的task（通过task驱动协程执行），执行；
协程中的await相当于yield from，在task和compute子协程之间建立一个通道，此时进入compute调度，print_sum暂停；
子协程compute中的await表示暂停，不经过pring_sum、直接返回给task再返回给loop，等待1s；
1s过后，task经通道询问compute，compute计算好结果值会抛出异常（StopIteration）并返回计算结果，compute协程标记完成；
print_sum捕捉到compute的异常、提取结果值，最后会把异常抛出给task，print_sum协程标记完成。
call_at，call_soon，call_later，call_soon_threadsafe
import asyncio
def callback(sleep_times, loop):
    print("success time {}".format(loop.time()))
def stoploop(loop):
    loop.stop()     
loop = asyncio.get_event_loop()
now = loop.time()
loop.call_at(now + 2, callback, 2, loop)    # 当前时间的2s后执行
loop.call_at(now + 1, callback, 1, loop)
loop.call_at(now + 3, callback, 3, loop)
# loop.call_soon(stoploop, loop)              # 退出循环
loop.call_soon(callback, 4, loop)           # 立刻执行（在队列中等待到下一个循环即执行），另外还有call_later
# 处理共享变量的线程安全问题可以使用call_soon_threadsafe
loop.run_forever()
集成线程池
在协程中集成阻塞IO：对于阻塞的库和接口（如pymysql），协程中要使用多线程。
import asyncio
from concurrent.futures import ThreadPoolExecutor
import socket
import time
from urllib.parse import urlparse
def get_url(url):
    url = urlparse(url)
    host = url.netloc
    path = url.path
    client = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
    # client.setblocking(False)
    client.connect((host, 80))  
    client.send("GET {} HTTP/1.1\r\nHost:{}\r\nConnection:close\r\n\r\n".format(path, host).encode("utf8"))
    data = b""
    while True:
        d = client.recv(1024)
        if d:
            data += d
        else:
            break
    data = data.decode("utf8")
    html_data = data.split("\r\n\r\n")[1]
    print(html_data)
    client.close()
start_time = time.time()
loop = asyncio.get_event_loop()
executor = ThreadPoolExecutor(3)
tasks = []
for url in range(20):
    url = "http://shop.projectsedu.com/goods/{}/".format(url)
    task = loop.run_in_executor(executor, get_url, url)     # 指定线程池，将阻塞IO操作放入loop中，不影响系统运行
    # 把线程中的future包装成协程的future
    tasks.append(task)
loop.run_until_complete(asyncio.wait(tasks))
print("last time:{}".format(time.time() - start_time))
模拟Http请求
requests是同步的http请求模块，在asyncio不能达到异步的效果，而asyncio本身没有提供http协议的接口，可以使用aiohttp：
import time
import asyncio
import socket
from urllib.parse import urlparse
async def get_url(url):
    url = urlparse(url)
    host = url.netloc
    path = url.path
    if path == "":
        path = "/"
    # 建立socket连接比较费时，使用await
    reader, writer = await asyncio.open_connection(host, 80)
    writer.write("GET {} HTTP/1.1\r\nHost:{}\r\nConnection:close\r\n\r\n".format(path, host).encode("utf8"))
    all_lines = []
    async for raw_line in reader:    # 异步化的for循环
        data = raw_line.decode("utf8")
        all_lines.append(data)
    html = "\n".join(all_lines)
    return html
async def main():
    tasks = []
    for url in range(20):
        url = "http://shop.projectsedu.com/goods/{}/".format(url)
        tasks.append(asyncio.ensure_future(get_url(url)))
    for task in asyncio.as_completed(tasks):
        result = await task
        print(result)
if __name__ == "__main__":
    start_time = time.time()
    loop = asyncio.get_event_loop()
    loop.run_until_complete(main())
    print('last time:{}'.format(time.time() - start_time))
future和task
见asyncio源码
同步与通信
import aiohttp
import asyncio
from asyncio import Lock, Queue     # await，区别于多线程的Queue（阻塞）
cache = {}
queue = []      # 协程是单线程，因此使用list、dict就可以实现通信，而不会有线程安全问题
lock = Lock()
async def get_stuff(url):
    # 如果没有同步机制，此处可能会被两个协程都对同一个url发起请求（耗时、被反爬）
    async with lock:    # 加锁，避免parse_stuff和use_stuff同时执行这部分代码
    # 由__await__、__aenter__实现，等价于await lock.acquire()、lock.release()
        if url in cache:
            return cache[url]
        stuff = await aiohttp.request('GET', url)
        cache[url] = stuff
        return stuff
async def parse_stuff():
    stuff = await get_stuff()
async def use_stuff():
    stuff = await get_stuff()
tasks = [parse_stuff(), use_stuff()]    # 当协程函数中没有await，则会按加入tasks顺序执行
实例：基于Asyncio协程的高并发爬虫
import re
import asyncio
import aiohttp
import aiomysql
from pyquery import PyQuery
# https://www.lfd.uci.edu/
stop_flag = False
start_url = "http://www.jobbole.com/"
waitting_urls = []
seen_urls = set()
sem = asyncio.Semaphore(3)
async def fetch(url, session):
    发送http请求
    :param url:
    :return:
    async with sem:                 # 并发度控制
        await asyncio.sleep(1)      # 爬取速度控制
            async with session.get(url) as resp:
                print('url statis: {0}'.format(resp.status))
                if resp.status in [200, 201]:
                    data = await resp.text()
                    return data
        except Exception as e:
            print(e)
def extract_urls(html):
    从请求页面中获取下次要请求url
    :param html:
    :return:
    urls = []
    pq = PyQuery(html)
    for link in pq.items('a'):
        url = link.attr('href')
        if url and url.startswith('http') and url not in seen_urls:
            urls.append(url)
            waitting_urls.append(url)
    return urls
async def article_handler(url, session, pool):
    获取文章详情并解析入库
    :param url:
    :param session:
    :return:
    html = await fetch(url, session)
    seen_urls.add(url)
    extract_urls(html)
    pq = PyQuery(html)
    title = pq('title').text()  # 省略其他字段
    print(title)
    async with pool.acquire() as conn:
        async with conn.cursor() as cur:
            await cur.execute("sql")
            insert_sql = """
                INSERT INTO xxx
            print(cur.description)
            await cur.execute(insert_sql)
async def init_urls(url, session):
    解析页面，
    :param url:
    :param session:
    :return:
    html = await fetch(url, session)
    seen_urls.add(url)
    extract_urls(html)
async def consumer(pool, session):
    # async with aiohttp.ClientSession() as session:      # 发送http请求需要的session
    while not stop_flag:
        if len(waitting_urls) == 0:
            await asyncio.sleep(0.5)
            continue
        url = waitting_urls.pop()
        print('start get url: ' + url)
        # 详情页协程，解析页面内容、入库
        if re.match('http://.*?jobbole.com/\d+/', url):
            if url not in seen_urls:
                asyncio.ensure_future(article_handler(url, session, pool))
        # 非详情页协程，进一步提取出详情页的url
        else:
            if url not in seen_urls:
                asyncio.ensure_future(init_urls(url, session))
async def main(loop):
    # 等待Mysql连接池建立
    pool = await aiomysql.create_pool(
        host='', port='', user='', password='', db='mysql', loop=loop, charset='utf8', autocommit=True
    async with aiohttp.ClientSession() as session:      # 发送http请求需要的session
        html = await fetch(start_url, session)
        seen_urls.add(start_url)
        extract_urls(html)
        # consumer协程从url获取，动态向asyncio提交article_handler和init_urls协程
        asyncio.ensure_future(consumer(pool, session))