parent
820f7d98a7
commit
78e0e73666
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import requests
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from bs4 import BeautifulSoup
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from openpyxl import Workbook
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import time
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import random
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wb = Workbook() #创建一个workbook
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def createSheetObj():
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sheet = wb.active #获取当前workbook的第一个worksheet
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sheet.title = "58同城" #worksheet的标题
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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
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return sheet
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def getpage1(): #返回网页源码
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path = 'nn.html'
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htmlfile = open(path, 'r', encoding='utf-8') #打开1.html文件
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htmlhandle = htmlfile.read() #返回整个文件
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soup = BeautifulSoup(htmlhandle, "lxml") #使用Beautifulsoup解析
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#print(soup)
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return soup
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def getPage(url):
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# 伪造身份
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headers = {
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'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'
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}
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resp = requests.get(url, headers=headers)
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print(resp.status_code)
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resp.encoding = "utf-8"
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html = resp.text
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soup = BeautifulSoup(html, "lxml")
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return soup
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def parsePage():
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soup = getpage1()
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i = 0
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lis = soup.find_all("a", attrs={"class": "ui-house-item-house-wrapper"}) #找到所有li的链接地址
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for li in lis:
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print("第" + str(i) + "条")
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i = i + 1
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house_name = li.find('div',class_='ui-house-item-content-area-title').get_text()
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house_href = 'http:' + li.get('href')
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house_location = li.find('div',class_='ui-house-item-content-area-introduce2').get_text()
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house_price = li.find('span', class_='ui-house-item-price-area-nowprice-price').get_text()
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house_unit = li.find('span', class_='ui-house-item-price-area-nowprice-unit').get_text()
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z = house_unit.split('/')
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if(z[1] == "月"):
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house_price = int(house_price) // 30
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house_person_type_huxing = li.find('div', class_='ui-house-item-content-area-introduce3').get_text()
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#合住房间·4室1床·可住1人·7天起租
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x = house_person_type_huxing.split('·')
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house_type = x[0]
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house_huxing = x[1]
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house_person = x[2][2] #第三个字
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#异常/缺省值处理
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try:
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house_score_comments = li.find('div', class_='ui-house-item-content-area-introduce1').get_text()
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y = house_score_comments.split('/')
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house_score = y[0][0] + y[0][1] + y[0][2]
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house_comments = y[1][0]
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except:
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house_score = 0
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house_comments =0
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try:
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house_satisfy = li.find('div', class_='ui-house-item-pic-degreeofsatisfaction-number').get_text()
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s = house_satisfy.split(':')
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house_satisfy_num = s[1]
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except:
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house_satisfy_num = 0
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try:
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soup1 = getPage(house_href)
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house_square = soup1.find_all('div',class_='desc')[2].get_text()
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#print(house_square)
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house_square = house_square.strip('㎡')
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#print(house_square)
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except:
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house_square = 0
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print(house_name,house_href,house_location,house_price,
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house_person,house_type,house_huxing,house_square,house_comments,house_score,house_satisfy_num)
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sheet.append([house_name,house_href,house_location,house_price,
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house_person,house_type,house_huxing,house_square,house_comments,house_score,house_satisfy_num])
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time.sleep(random.random() * 3) #模拟人的行为
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if (i > 2000):
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print("爬取结束")
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break
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#wb.save("nanning.xlsx") #将最终的结果导出到本地文件
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#wb.save("nanning.csv")
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wb.save("nanning.json")
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sheet = createSheetObj()
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parsePage()
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