用Python爬取贝壳网新房和二手房数据
import randomimport requests
from bs4 import BeautifulSoup
import re
import math
USER_AGENTS = [
"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; AcooBrowser; .NET CLR 1.1.4322; .NET CLR 2.0.50727)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.0; Acoo Browser; SLCC1; .NET CLR 2.0.50727; Media Center PC 5.0; .NET CLR 3.0.04506)",
"Mozilla/4.0 (compatible; MSIE 7.0; AOL 9.5; AOLBuild 4337.35; Windows NT 5.1; .NET CLR 1.1.4322; .NET CLR 2.0.50727)",
"Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Win64; x64; Trident/5.0; .NET CLR 3.5.30729; .NET CLR 3.0.30729; .NET CLR 2.0.50727; Media Center PC 6.0)",
"Mozilla/5.0 (compatible; MSIE 8.0; Windows NT 6.0; Trident/4.0; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; .NET CLR 1.0.3705; .NET CLR 1.1.4322)",
"Mozilla/4.0 (compatible; MSIE 7.0b; Windows NT 5.2; .NET CLR 1.1.4322; .NET CLR 2.0.50727; InfoPath.2; .NET CLR 3.0.04506.30)",
"Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN) AppleWebKit/523.15 (KHTML, like Gecko, Safari/419.3) Arora/0.3 (Change: 287 c9dfb30)",
"Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.8.1.2pre) Gecko/20070215 K-Ninja/2.1.1",
"Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN; rv:1.9) Gecko/20080705 Firefox/3.0 Kapiko/3.0",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.56 Safari/535.11",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_3) AppleWebKit/535.20 (KHTML, like Gecko) Chrome/19.0.1036.7 Safari/535.20",
"Opera/9.80 (Macintosh; Intel Mac OS X 10.6.8; U; fr) Presto/2.9.168 Version/11.52",
]
def create_headers():
headers = dict()
headers["User-Agent"] = random.choice(USER_AGENTS)
headers["Referer"] = "http://www.ke.com"
return headers
class NewHouse(object):
def __init__(self, xiaoqu, price, total):
self.xiaoqu = xiaoqu
self.price = price
self.total = total
def text(self):
return self.xiaoqu + "," + \
self.price + "," + \
self.total
with open("newhouse.txt", "w", encoding='utf-8') as f:
# 开始获得需要的板块数据
total_page = 1
loupan_list = list()
page = 'http://zh.fang.ke.com/loupan/'
print(page)
headers = create_headers()
response = requests.get(page, timeout=10, headers=headers)
html = response.content
soup = BeautifulSoup(html, "lxml")
# 获得总的页数
try:
page_box = soup.find_all('div', class_='page-box')
matches = re.search('.*data-total-count="(\d+)".*', str(page_box))
total_page = int(math.ceil(int(matches.group(1)) / 10))
except Exception as e:
print(e)
print(total_page)
# 从第一页开始,一直遍历到最后一页
headers = create_headers()
for i in range(1, total_page + 1):
page = 'http://zh.fang.ke.com/loupan/pg{0}'.format(i)
print(page)
response = requests.get(page, timeout=10, headers=headers)
html = response.content
soup = BeautifulSoup(html, "lxml")
# 获得有小区信息的panel
house_elements = soup.find_all('li', class_="resblock-list")
for house_elem in house_elements:
price = house_elem.find('span', class_="number")
desc = house_elem.find('span', class_="desc")
total = house_elem.find('div', class_="second")
loupan = house_elem.find('a', class_='name')
# 继续清理数据
try:
price = price.text.strip() + desc.text.strip()
except Exception as e:
price = '0'
loupan = loupan.text.replace("\n", "")
try:
total = total.text.strip().replace(u'总价', '')
total = total.replace(u'/套起', '')
except Exception as e:
total = '0'
# 作为对象保存
loupan = NewHouse(loupan, price, total)
print(loupan.text())
loupan_list.append(loupan)
for loupan in loupan_list:
f.write(loupan.text() + "\n")
二手楼盘代码：
import random
import requests
from bs4 import BeautifulSoup
import re
import math
from lxml import etree
USER_AGENTS = [
"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; AcooBrowser; .NET CLR 1.1.4322; .NET CLR 2.0.50727)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.0; Acoo Browser; SLCC1; .NET CLR 2.0.50727; Media Center PC 5.0; .NET CLR 3.0.04506)",
"Mozilla/4.0 (compatible; MSIE 7.0; AOL 9.5; AOLBuild 4337.35; Windows NT 5.1; .NET CLR 1.1.4322; .NET CLR 2.0.50727)",
"Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Win64; x64; Trident/5.0; .NET CLR 3.5.30729; .NET CLR 3.0.30729; .NET CLR 2.0.50727; Media Center PC 6.0)",
"Mozilla/5.0 (compatible; MSIE 8.0; Windows NT 6.0; Trident/4.0; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; .NET CLR 1.0.3705; .NET CLR 1.1.4322)",
"Mozilla/4.0 (compatible; MSIE 7.0b; Windows NT 5.2; .NET CLR 1.1.4322; .NET CLR 2.0.50727; InfoPath.2; .NET CLR 3.0.04506.30)",
"Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN) AppleWebKit/523.15 (KHTML, like Gecko, Safari/419.3) Arora/0.3 (Change: 287 c9dfb30)",
"Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.8.1.2pre) Gecko/20070215 K-Ninja/2.1.1",
"Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN; rv:1.9) Gecko/20080705 Firefox/3.0 Kapiko/3.0",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.56 Safari/535.11",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_3) AppleWebKit/535.20 (KHTML, like Gecko) Chrome/19.0.1036.7 Safari/535.20",
"Opera/9.80 (Macintosh; Intel Mac OS X 10.6.8; U; fr) Presto/2.9.168 Version/11.52",
]
chinese_city_district_dict = dict()
chinese_area_dict = dict()
def create_headers():
headers = dict()
headers["User-Agent"] = random.choice(USER_AGENTS)
headers["Referer"] = "http://www.ke.com"
return headers
class SecHouse(object):
def __init__(self, district, area, name, price, desc, pic):
self.district = district
self.area = area
self.price = price
self.name = name
self.desc = desc
self.pic = pic
def text(self):
return self.district + "," + \
self.area + "," + \
self.name + "," + \
self.price + "," + \
self.desc + "," + \
self.pic
def get_districts():
url = 'https://sh.ke.com/xiaoqu/'
headers = create_headers()
response = requests.get(url, timeout=10, headers=headers)
html = response.content
root = etree.HTML(html)
elements = root.xpath('///div/div/dl/dd/div/div/a')
en_names = list()
ch_names = list()
for element in elements:
link = element.attrib['href']
en_names.append(link.split('/')[-2])
ch_names.append(element.text)
# 打印区县英文和中文名列表
for index, name in enumerate(en_names):
chinese_city_district_dict = ch_names
return en_names
def get_areas(district):
page = "http://sh.ke.com/xiaoqu/{0}".format(district)
areas = list()
try:
headers = create_headers()
response = requests.get(page, timeout=10, headers=headers)
html = response.content
root = etree.HTML(html)
links = root.xpath('//div/div/dl/dd/div/div/a')
# 针对a标签的list进行处理
for link in links:
relative_link = link.attrib['href']
# 去掉最后的"/"
relative_link = relative_link[:-1]
# 获取最后一节
area = relative_link.split("/")[-1]
# 去掉区县名,防止重复
if area != district:
chinese_area = link.text
chinese_area_dict = chinese_area
# print(chinese_area)
areas.append(area)
return areas
except Exception as e:
print(e)
with open("sechouse.txt", "w", encoding='utf-8') as f:
# 开始获得需要的板块数据
total_page = 1
sec_house_list = list()
districts = get_districts()
for district in districts:
arealist = get_areas(district)
for area in arealist:
# 中文区县
chinese_district = chinese_city_district_dict.get(district, "")
# 中文版块
chinese_area = chinese_area_dict.get(area, "")
page = 'http://sh.ke.com/ershoufang/{0}/'.format(area)
print(page)
headers = create_headers()
response = requests.get(page, timeout=10, headers=headers)
html = response.content
soup = BeautifulSoup(html, "lxml")
# 获得总的页数
try:
page_box = soup.find_all('div', class_='page-box')
matches = re.search('.*data-total-count="(\d+)".*', str(page_box))
total_page = int(math.ceil(int(matches.group(1)) / 10))
except Exception as e:
print(e)
print(total_page)
# 从第一页开始,一直遍历到最后一页
headers = create_headers()
for i in range(1, total_page + 1):
page = 'http://sh.ke.com/ershoufang/{0}/pg{1}'.format(area, i)
print(page)
response = requests.get(page, timeout=10, headers=headers)
html = response.content
soup = BeautifulSoup(html, "lxml")
# 获得有小区信息的panel
house_elements = soup.find_all('li', class_="clear")
for house_elem in house_elements:
price = house_elem.find('div', class_="totalPrice")
name = house_elem.find('div', class_='title')
desc = house_elem.find('div', class_="houseInfo")
pic = house_elem.find('a', class_="img").find('img', class_="lj-lazy")
# 继续清理数据
price = price.text.strip()
name = name.text.replace("\n", "")
desc = desc.text.replace("\n", "").strip()
pic = pic.get('data-original').strip()
# 作为对象保存
sec_house = SecHouse(chinese_district, chinese_area, name, price, desc, pic)
print(sec_house.text())
sec_house_list.append(sec_house)
for sec_house in sec_house_list:
f.write(sec_house.text() + "\n")
可以 学到辽 租房平台真的easy啊 值得好好研究，希望楼主多谢点python的东西 小松鼠 发表于 2020-11-16 23:09
我有个房产网站，大神可分析一下？
啥样的，有没有链接 小松鼠 发表于 2020-11-17 13:21
0898mmf.com
需要啥样的数据 学习一下 小松鼠 发表于 2020-11-18 10:15
分楼盘名命名 图片缩略图
以楼盘名命名的楼盘图片吗
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