粗柳簸箕细柳斗，谁嫌爬虫男人丑 之 异步协程半秒扒光一本小说

前阵子，偶然闻同学道，想从某某网站爬取几十万条数据来做数据分析，可是速度实在太慢，为此甚是发愁。。。其实可以提速爬虫的方法常见有多线程，多进程，异步协程等，而小编要说的就是异步协程为爬虫提速！

爬虫之所以慢，往往是因为程序等待IO而被阻塞，比如爬虫中常见的阻塞有：网络阻塞，磁盘阻塞等；细点再来讲网络阻塞，假如用requests来进行请求，如果网站的响应速度过慢，程序一直等待在网络响应，最后就导致爬虫效率极其低下！

那么何为异步爬虫呢？

通俗来讲就是：当程序检测到IO阻塞，就会自动切换到程序的其他任务，这样把程序的IO降到最低，程序处于就绪状态的任务就会增多，以此对操作系统瞒天过海，操作系统便以为程序IO较少，从而尽可能多的分配CPU，达到提升程序执行效率的目的。

一，协程

import asyncio
import time

async def func1():  # asnyc 定义一个协程
    print('隔壁老王！')
    await asyncio.sleep(3)  # 模拟阻塞 异步操作 await 将其异步等待
    print('隔壁老王')


async def func2():  # asnyc 定义一个协程
    print('哈士奇')
    await asyncio.sleep(2)  # 模拟阻塞 异步操作 await 将其异步等待
    print('哈士奇')


async def func3():  # asnyc 定义一个协程
    print('阿拉斯加')
    await asyncio.sleep(1)  # 模拟阻塞 异步操作 await 将其异步等待
    print('阿拉斯加')


async def main():
    tasks = [  # tasks：任务，它是对协程对象的进一步封装，包含了任务的各个状态
        asyncio.create_task(func1()),
        asyncio.create_task(func2()),
        asyncio.create_task(func3()),
    ]
    await asyncio.wait(tasks)

if __name__ == '__main__':
    start_time = time.time()
    asyncio.run(main())  # 一次性启动多个任务(协程)
    print('程序总耗时\033[31;1m%s\033[0ms' % (time.time() - start_time))

二，异步请求aiohttp及异步写入aiofiles

随便在网上拿几张图片链接地址作为练习

import aiohttp
import aiofiles
import asyncio
import os

if not os.path.exists('./Bantu'):
    os.mkdir('./Bantu')


async def umei_picture_download(url):
    name = url.split('/')[-1]
    picture_path = './Bantu/' + name
    async with aiohttp.ClientSession() as session:  # aiohttp.ClientSession() 相当于 requests
        async with session.get(url) as resp:  # 或session.post()异步发送
            # resp.content.read()读二进制(视频，图片等)，resp.text()读文本，resp.json()读json
            down_pict = await resp.content.read()  # resp.content.read()相当于requests(xxx).content
            async with aiofiles.open(picture_path, 'wb') as f:  # aiofiles.open() 异步打开文件
                await f.write(down_pict)  # 写入内容也是异步的，需要挂起
    print('爬取图片完成！！！')


async def main():
    tasks = []
    for url in urls:
        tasks.append(asyncio.create_task(umei_picture_download(url)))

    await asyncio.wait(tasks)


if __name__ == '__main__':

    urls = [
        'https://tenfei02.cfp.cn/creative/vcg/veer/1600water/veer-158109176.jpg',
        'https://alifei03.cfp.cn/creative/vcg/veer/1600water/veer-151526132.jpg',
        'https://tenfei05.cfp.cn/creative/vcg/veer/1600water/veer-141027139.jpg',
        'https://tenfei03.cfp.cn/creative/vcg/veer/1600water/veer-132395407.jpg'
    ]

    # asyncio.run(main())
    loop = asyncio.get_event_loop()  # get_event_loop()方法创建了一个事件循环loop
    loop.run_until_complete(main())  # 调用了loop对象的run_until_complete()方法将协程注册到事件循环loop中，然后启动

三，异步协程半秒扒光一本小说

本次对象是某度上的一本小说，url地址为：http://dushu.baidu.com/pc/detail?gid=4308271440

1，简单地分析

复制URL地址并在浏览器上打开如上图页面，可以看到只显示了为数不多的几个章节标题，当点击查看全部时，网址并没有改变而加载出了全部的章节标题。

所以第一反应就是，小说的章节标题很可能是通过AJAX局部加载的！

f12打开开发者工具，点到Network下的XHR上，并点击网页上的 查看全部 按钮，如下图：


捕捉到一个包，打开看看，如下图：

OK，找到标题！再继续每章的详细内容

随便点击一个章节名，进入详细内容页面，看浏览器捕捉到的包，如下图：

除了刚才的第一个包，在其他的三个包仔细看，有没有蛛丝马迹，如下图

章节详情已找到！！！

2，着手撸代码

开始之前先把刚才的章节标题对应的url地址和章节详情页对应的url地址拿过来瞅瞅

章节标题对应的url地址：

# http://dushu.baidu.com/api/pc/getCatalog?data={%22book_id%22:%224308271440%22}

章节详情页对应的url地址：

# http://dushu.baidu.com/api/pc/getChapterContent?data={%22book_id%22:%224308271440%22,%22cid%22:%224308271440|20222925%22,%22need_bookinfo%22:1}

额，这个某度呀！url尽管稍微凌乱了那么一丢丢，但依然不能摆脱被扒的命运，如下图：

可以看到，两个url都会用到book_id，所以将book_id单另提取出来

①先上个基本的框框

import aiohttp
import asyncio
import requests
import aiofiles
import pprint
import os
import time


def get_chapter_content(url, headers):
    pass


if __name__ == '__main__':
    book_id = '4308271440'
    url = 'http://dushu.baidu.com/api/pc/getCatalog?data={%22book_id%22:%22' + book_id + '%22}'
    headers = {
    
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36'
    }

    get_chapter_content(url, headers)

②拿到章节名和对应的cid

读出对应的json文件

def get_chapter_content(url, headers):
    response = requests.get(url=url, headers=headers).json()
    pprint.pprint(response)

运行如下图：

取出cid和title

def get_chapter_content(url, headers):
    response = requests.get(url=url, headers=headers).json()
    # pprint.pprint(response)
    chapter_details = response['data']['novel']['items']  # 拿到包含了每章cid和章节名的内容
    for chapter in chapter_details:
        chapter_cid = chapter['cid']  # 拿到每章对应的cid
        chapter_title = chapter['title']  # 拿到每章对应的标题名
        print(chapter_cid, chapter_title)

③上异步

async def get_chapter_content(url, headers):
    response = requests.get(url=url, headers=headers).json()
    # pprint.pprint(response)
    tasks = []
    chapter_details = response['data']['novel']['items']  # 拿到包含了每章cid和章节名的内容
    for chapter in chapter_details:
        chapter_cid = chapter['cid']  # 拿到每章对应的cid
        chapter_title = chapter['title']  # 拿到每章对应的标题名
        # print(chapter_cid, chapter_title)
        tasks.append(asyncio.create_task(aio_download_novel(headers, chapter_cid, chapter_title, book_id)))

    await asyncio.wait(tasks)


async def aio_download_novel(headers, chapter_cid, chapter_title, book_id):
    pass


if __name__ == '__main__':
    book_id = '4308271440'
    url = 'http://dushu.baidu.com/api/pc/getCatalog?data={%22book_id%22:%22' + book_id + '%22}'
    headers = {
    
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36'
    }

    asyncio.run(get_chapter_content(url, headers))

④拿出详细内容

async def aio_download_novel(headers, chapter_cid, chapter_title, book_id):
    details_url = 'http://dushu.baidu.com/api/pc/getChapterContent?data={%22book_id%22:%22' + book_id + '%22,%22cid%22:%22' + book_id + '|' + chapter_cid + '%22,%22need_bookinfo%22:1}'
    # print(details_url)
    async with aiohttp.ClientSession() as session:
        async with session.get(url=details_url, headers=headers) as response:
            content = await response.json()
            # pprint.pprint(content)
            details_content = content['data']['novel']['content']
            print(details_content)

⑤持久化存储

import aiohttp
import asyncio
import requests
import aiofiles
import pprint
import os
import time

if not os.path.exists('./姐不要做炮灰'):
    os.mkdir('./姐不要做炮灰')


async def get_chapter_content(url, headers):
    response = requests.get(url=url, headers=headers).json()
    # pprint.pprint(response)
    tasks = []
    chapter_details = response['data']['novel']['items']  # 拿到包含了每章cid和章节名的内容
    for chapter in chapter_details:
        chapter_cid = chapter['cid']  # 拿到每章对应的cid
        chapter_title = chapter['title']  # 拿到每章对应的标题名
        # print(chapter_cid, chapter_title)
        tasks.append(asyncio.create_task(aio_download_novel(headers, chapter_cid, chapter_title, book_id)))

    await asyncio.wait(tasks)


async def aio_download_novel(headers, chapter_cid, chapter_title, book_id):
    details_url = 'http://dushu.baidu.com/api/pc/getChapterContent?data={%22book_id%22:%22' + book_id + '%22,%22cid%22:%22' + book_id + '|' + chapter_cid + '%22,%22need_bookinfo%22:1}'
    # print(details_url)
    novel_path = './姐不要做炮灰/' + chapter_title
    async with aiohttp.ClientSession() as session:
        async with session.get(url=details_url, headers=headers) as response:
            content = await response.json()
            # pprint.pprint(content)
            details_content = content['data']['novel']['content']
            # print(details_content)
            async with aiofiles.open(novel_path, mode='w', encoding='utf-8') as f:
                await f.write(details_content)

    print(chapter_title, '\033[31;1m 爬取完成！！！\033[0m')


if __name__ == '__main__':
    book_id = '4308271440'
    url = 'http://dushu.baidu.com/api/pc/getCatalog?data={%22book_id%22:%22' + book_id + '%22}'
    headers = {
    
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36'
    }
    start_time = time.time()
    asyncio.run(get_chapter_content(url, headers))
    print('\n')
    print('爬虫程序总耗时: \033[31;1m%s\033[0m s' % (time.time() - start_time))

到此结束！