python实战｜python爬取58同城租房数据并以Excel文件格式保存到本地

一、分析目标网站url

目标网站：https://cq.58.com/minsuduanzu/
让我们看看网站长啥样：
网站描述：
- 链接一直不变（爱了爱了
- 没有翻页设计，往下滑会无限加载（得想个办法
如何解决网页无限加载不好爬的问题？
- 团队经过讨论和参考一些博主的经验，选择了把网页先保存到本地再进行爬取。虽说是一个笨办法，但确实也是一个办法！
- 注：本方法适合所需数据不是超级大的那种（超过3k条建议另寻他法

二、代码

几个注意点??：

本文导入的modules和其作用：requests（请求网页）、bs4的BeautifulSoup（解析html）、openpyxl的Workbook（处理excel表格）、time（页面停留）、random（随机函数）
爬取的数据： ’短租房名称’, ‘短租房链接’, '短租房地址’, ‘短租房价格元/日’, ‘短租房居住人数’, ’出租类型’, ’短租房户型’, ’面积/㎡’, ’用户评论数’, ’用户评分’, ’用户满意度"（除面积外均通过css类选择器获得
跳转url：爬取的数据中面积需要进到详情页获取数据，本文通过css类选择器，先从列表页获取跳转链接，再进入链接获取面积～
价格处理：通过if函数对单位为月的价格进行处理，使价格单位统一为日，便于比较
异常值处理：通过try…except函数对缺省值/异常值进行归0处理
代码优化：页面跳转时通过 time.sleep(random.random() * 3) 随机生成页面停留时间，从而模拟人的行为

import requests
from bs4 import BeautifulSoup
from openpyxl import Workbook
import time
import random

wb = Workbook() #创建一个workbook
def createSheetObj():
    sheet = wb.active #获取当前workbook的第一个worksheet
    sheet.title = "58同城" #worksheet的标题
    sheet.append(['短租房名称', '短租房链接', '短租房地址', "短租房价格 元/日", "短租房居住人数","出租类型","短租房户型","面积/㎡","用户评论数","用户评分","用户满意度"]) #添加一行表头
    return sheet

def getpage1(): #返回网页源码
    path = '1.html'
    htmlfile = open(path, 'r', encoding='utf-8') #打开1.html文件
    htmlhandle = htmlfile.read() #返回整个文件
    soup = BeautifulSoup(htmlhandle, "lxml") #使用Beautifulsoup解析
    #print(soup)
    return soup

def getPage(url):
    # 伪造身份
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.18363'
    }

    resp = requests.get(url, headers=headers)
    print(resp.status_code)
    resp.encoding = "utf-8"
    html = resp.text

    soup = BeautifulSoup(html, "lxml")
    return soup


def parsePage():
    soup = getpage1()
    i = 0
    lis = soup.find_all("a", attrs={"class": "ui-house-item-house-wrapper"}) #找到所有li的链接地址
    for li in lis:
        print("第" + str(i) + "条")
        i = i + 1
        house_name = li.find('div',class_='ui-house-item-content-area-title').get_text()
        house_href = 'http:' + li.get('href')
        house_location = li.find('div',class_='ui-house-item-content-area-introduce2').get_text()
        house_price = li.find('span', class_='ui-house-item-price-area-nowprice-price').get_text()
        house_unit = li.find('span', class_='ui-house-item-price-area-nowprice-unit').get_text()

        z = house_unit.split('/')

        if(z[1] == "月"):
            house_price = int(house_price) // 30
        house_person_type_huxing = li.find('div', class_='ui-house-item-content-area-introduce3').get_text()
        #合住房间·4室1床·可住1人·7天起租
        x = house_person_type_huxing.split('·')
        house_type = x[0]
        house_huxing = x[1]
        house_person = x[2][2] #第三个字
		#异常/缺省值处理
        try:
            house_score_comments = li.find('div', class_='ui-house-item-content-area-introduce1').get_text()
            y = house_score_comments.split('/')
            house_score = y[0][0] + y[0][1] + y[0][2]
            house_comments = y[1][0]

        except:
            house_score = 0
            house_comments =0

        try:
            house_satisfy = li.find('div', class_='ui-house-item-pic-degreeofsatisfaction-number').get_text()
            s = house_satisfy.split(':')
            house_satisfy_num = s[1]
        except:
            house_satisfy_num = 0

        try:
            soup1 = getPage(house_href)
            house_square = soup1.find_all('div',class_='desc')[2].get_text()
            #print(house_square)
            house_square = house_square.strip('㎡')
            #print(house_square)
        except:
            house_square = 0

        print(house_name,house_href,house_location,house_price,
                      house_person,house_type,house_huxing,house_square,house_comments,house_score,house_satisfy_num)

        sheet.append([house_name,house_href,house_location,house_price,
                      house_person,house_type,house_huxing,house_square,house_comments,house_score,house_satisfy_num])

        time.sleep(random.random() * 3) #模拟人的行为
        if (i > 2000):
            print("爬取结束")
            break
    wb.save("chongqing.xlsx") #将最终的结果导出到本地文件


sheet = createSheetObj()

parsePage()