python链家网二手房异步IO爬虫，使用asyncio、aiohttp和aiomysql

很多小伙伴初学python时都会学习到爬虫，刚入门时会使用requests、urllib这些同步的库进行单线程爬虫，速度是比较慢的，后学会用scrapy框架进行爬虫，速度很快，原因是scrapy是基于twisted多线程异步IO框架。

本例使用的asyncio也是一个异步IO框架，在python3.5以后加入了协程的关键字async，能够将协程和生成器区分开来，更加方便使用协程。

经过测试，平均1秒可以爬取30个详情页信息

可以使用asyncio.Semaphore来控制并发数，达到限速的效果

# -*- coding: utf-8 -*-

"""

:author: KK

:url: http://github.com/PythonerKK

:copyright: © 2019 KK <705555262@qq.com.com>

"""

import asyncio

import re

import aiohttp

from pyquery import PyQuery

import aiomysql

from lxml import etree

pool = ''

#sem = asyncio.Semaphore(4) 用来控制并发数，不指定会全速运行

stop = False

headers = {

'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.100 Safari/537.36'

}

MAX_PAGE = 10

TABLE_NAME = 'data' #数据表名

city = 'zh' #城市简写

url = 'https://{}.lianjia.com/ershoufang/pg{}/' #url地址拼接

urls = [] #所有页的url列表

links_detail = set() #爬取中的详情页链接的集合

crawled_links_detail = set() #爬取完成的链接集合，方便去重

async def fetch(url, session):

'''

aiohttp获取网页源码

'''

# async with sem:

try:

async with session.get(url, headers=headers, verify_ssl=False) as resp:

if resp.status in [200, 201]:

data = await resp.text()

return data

except Exception as e:

print(e)

def extract_links(source):

'''

提取出详情页的链接

'''

pq = PyQuery(source)

for link in pq.items("a"):

_url = link.attr("href")

if _url and re.match('https://.*?/\d+.html', _url) and _url.find('{}.lianjia.com'.format(city)):

links_detail.add(_url)

print(links_detail)

def extract_elements(source):

'''

提取出详情页里面的详情内容

'''

try:

dom = etree.HTML(source)

id = dom.xpath('//link[@rel="canonical"]/@href')[0]

title = dom.xpath('//title/text()')[0]

price = dom.xpath('//span[@class="unitPriceValue"]/text()')[0]

information = dict(re.compile('

(.*?)(.*?)').findall(source))

information.update(title=title, price=price, url=id)

print(information)

asyncio.ensure_future(save_to_database(information, pool=pool))

except Exception as e:

print('解析详情页出错！')

pass

async def save_to_database(information, pool):

'''

使用异步IO方式保存数据到mysql中

注：如果不存在数据表，则创建对应的表

'''

COLstr = '' # 列的字段

ROWstr = '' # 行字段

ColumnStyle = ' VARCHAR(255)'

for key in information.keys():

COLstr = COLstr + ' ' + key + ColumnStyle + ','

ROWstr = (ROWstr + '"%s"' + ',') % (information[key])

# 异步IO方式插入数据库

async with pool.acquire() as conn:

async with conn.cursor() as cur:

try:

await cur.execute("SELECT * FROM %s" % (TABLE_NAME))

await cur.execute("INSERT INTO %s VALUES (%s)"%(TABLE_NAME, ROWstr[:-1]))

print('插入数据成功')

except aiomysql.Error as e:

await cur.execute("CREATE TABLE %s (%s)" % (TABLE_NAME, COLstr[:-1]))

await cur.execute("INSERT INTO %s VALUES (%s)" % (TABLE_NAME, ROWstr[:-1]))

except aiomysql.Error as e:

print('mysql error %d: %s' % (e.args[0], e.args[1]))

async def handle_elements(link, session):

'''

获取详情页的内容并解析

'''

print('开始获取: {}'.format(link))

source = await fetch(link, session)

#添加到已爬取的集合中

crawled_links_detail.add(link)

extract_elements(source)

async def consumer():

'''

消耗未爬取的链接

'''

async with aiohttp.ClientSession() as session:

while not stop:

if len(urls) != 0:

_url = urls.pop()

source = await fetch(_url, session)

print(_url)

extract_links(source)

if len(links_detail) == 0:

print('目前没有待爬取的链接')

await asyncio.sleep(2)

continue

link = links_detail.pop()

if link not in crawled_links_detail:

asyncio.ensure_future(handle_elements(link, session))

async def main(loop):

global pool

pool = await aiomysql.create_pool(host='127.0.0.1', port=3306,

user='root', password='xxxxxx',

db='aiomysql_lianjia', loop=loop, charset='utf8',

autocommit=True)

for i in range(1, MAX_PAGE):

urls.append(url.format(city, str(i)))

print('爬取总页数：{} 任务开始...'.format(str(MAX_PAGE)))

asyncio.ensure_future(consumer())

if __name__ == '__main__':

loop = asyncio.get_event_loop()

asyncio.ensure_future(main(loop))

loop.run_forever()

作者：Pykk2019