爬取贝壳租房信息存储到mongoDB

前几天链家网升级成贝壳找房了，融合了十几家知名公寓的租房信息，太赞了，正好有多方面数据来源可以分析。代码是存储到mongoDB上（忍不住吐槽一下，mongoDB对32位的系统真不友好，各种问题，要么要安装补丁，每次打开都要更改存储位置，有时候还要解除进程锁），也可以改成存储到Excel中，把注释去掉就行了。下面是贝壳找房的代码：

import pymongo
import requests,codecs
import pymongo,time
from lxml import html
from multiprocessing import Pool

client = pymongo.MongoClient('mongodb://localhost:27017')
db=client['testdb']
myset=db['beike']
def get_content(j):
    print('正在爬取第{}页,还剩{}页'.format(j,100-j))
    url='https://sh.zu.ke.com/zufang/pg{}/#contentList'.format(j)
    r=requests.get(url)
    r=html.fromstring(r.text)
    lenth=len(r.xpath('//div[@class="content__article"]/div[1]/div'))
    try:
        for i in range(1,lenth+1):
            urls=r.xpath('//div[@class="content__article"]/div[1]/div[{}]/div[1]/p[1]/a/@href'.format(i))[0]
            community=r.xpath('//div[@class="content__article"]/div[1]/div[{}]/div[1]/p[1]/a/text()'.format(i))[0].replace('\n','').strip()
            addr=r.xpath('//div[@class="content__article"]/div[1]/div[1]/div[{}]/p[2]/a/text()'.format(i))
            landlord=r.xpath('//div[@class="content__article"]/div[1]/div[{}]/div[1]/p[3]/text()'.format(i))[0].replace('\n','').strip()
            postime=r.xpath('//div[@class="content__article"]/div[1]/div[{}]/div[1]/p[4]/text()'.format(i))[0]
            label=r.xpath('//div[@class="content__article"]/div[1]/div[{}]/div[1]/p[5]/i/text()'.format(i))
            price=r.xpath('//div[@class="content__article"]/div[1]/div[{}]/div[1]/span/em/text()'.format(i))[0]
            # output="{}\t{}\t{}\t{}\t{}\t{}\t{}\n".format(community,addr,price,landlord,postime,label,urls)
            # savetoexcel(output)
            info={'community':community,'addr':addr,'price':price,'lanlord':landlord,'postime':postime,'label':label,'urls':urls}
            try:
                myset.insert(info)
            except:
                print('写入失败')

    except Exception as e:
        print(e)
        print('爬取失败')
def savetoexcel(output):
    try:
        f=codecs.open('beike.xls','a+','utf-8')
        f.write(output)
        f.close()
    except Exception as e:
        print('写入失败')
if __name__ == '__main__':
    pool=Pool(processes=2)
    pool.map(get_content,list(range(1,101)))
    pool.close()
    pool.join()

爬到之后，是这样的：

转化为DataFrame方便用pandas操作

import pymongo
import pandas as pd
#建立连接
client = pymongo.MongoClient('mongodb://localhost:27017')
db=client.testdb
myset=db.beike
#从mongoDB读取数据转化为dataframe
def get_data():
    df=pd.DataFrame(columns=['community','addr','price','lanlord','postime','label','urls'])
    for i in myset.find().limit(100):
        del i['_id']
        pd_data = pd.DataFrame.from_dict(i, orient='index').T
        df = df.append(pd_data, ignore_index=True)
    return df
df=get_data()
landlord=df.lanlord.value_counts()
print(landlord)