因為期末考試的緣故，本打算一個星期結束的爬蟲，拖了很久，不過，也有好處：之前寫的時候總是被反爬，這幾天複習之餘寫了些反爬取的py code 下面發出來和大家探讨
做了些反爬取的手段
随機擷取一個headers
headers.py
__author__ = 'Lee'
import requests
import random #随機數子產品
def requests_headers():
head_connection = ['Keep-Alive','close']
head_accept = ['text/html,application/xhtml+xml,*/*']
head_accept_language = ['zh-CN,fr-FR;q=0.5','en-US,en;q=0.8,zh-Hans-CN;q=0.5,zh-Hans;q=0.3']
head_user_agent = ['Mozilla/5.0 (Windows NT 6.3; WOW64; Trident/7.0; rv:11.0) like Gecko',
'Mozilla/5.0 (Windows NT 5.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/28.0.1500.95 Safari/537.36',
'Mozilla/5.0 (Windows NT 6.1; WOW64; Trident/7.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; rv:11.0) like Gecko)',
'Mozilla/5.0 (Windows; U; Windows NT 5.2) Gecko/2008070208 Firefox/3.0.1',
'Mozilla/5.0 (Windows; U; Windows NT 5.1) Gecko/20070309 Firefox/2.0.0.3',
'Mozilla/5.0 (Windows; U; Windows NT 5.1) Gecko/20070803 Firefox/1.5.0.12',
'Opera/9.27 (Windows NT 5.2; U; zh-cn)',
'Mozilla/5.0 (Macintosh; PPC Mac OS X; U; en) Opera 8.0',
'Opera/8.0 (Macintosh; PPC Mac OS X; U; en)',
'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.8.1.12) Gecko/20080219 Firefox/2.0.0.12 Navigator/9.0.0.6',
'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; Win64; x64; Trident/4.0)',
'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; Trident/4.0)',
'Mozilla/5.0 (compatible; MSIE 10.0; Windows NT 6.1; WOW64; Trident/6.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; InfoPath.2; .NET4.0C; .NET4.0E)',
'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Maxthon/4.0.6.2000 Chrome/26.0.1410.43 Safari/537.1 ',
'Mozilla/5.0 (compatible; MSIE 10.0; Windows NT 6.1; WOW64; Trident/6.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; InfoPath.2; .NET4.0C; .NET4.0E; QQBrowser/7.3.9825.400)',
'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:21.0) Gecko/20100101 Firefox/21.0 ',
'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.92 Safari/537.1 LBBROWSER',
'Mozilla/5.0 (compatible; MSIE 10.0; Windows NT 6.1; WOW64; Trident/6.0; BIDUBrowser 2.x)',
'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.11 TaoBrowser/3.0 Safari/536.11']
#header 為随機産生一套由上邊資訊的header檔案
header = {
'Connection':head_connection[random.randrange(0,len(head_connection))],
'Accept':head_accept[0],
'Accept-Language':head_accept_language[random.randrange(0,len(head_accept_language))],
'User-Agent':head_user_agent[random.randrange(0,len(head_user_agent))],
}
print('headers.py connection Success!')
return header #傳回值為 header這個字典
# for i in range(100): #随機産生100套資訊
# print(requests_headers()) #列印
# #print(random.randrange(1,10))
從IP池随機選擇個代理IP
ip_proxy.py
__author__ = 'Lee'
import random
ip_pool = [
'117.143.109.136:80'
]
def ip_proxy():
ip = ip_pool[random.randrange(0,len(ip_pool))]
proxy_ip = 'http://'+ip
proxies = {'http':proxy_ip}
print(proxies)
return proxies
items_combination.py
__author__ = 'Lee'
from bs4 import BeautifulSoup
import requests
import pymongo
import time
from headers import requests_headers
from ip_proxy import ip_proxy
client = pymongo.MongoClient('localhost',27017) #連結資料庫
ceshi = client['ceshi']
url_list = ceshi['url_list']
item_list = ceshi['item_info']
url_list1 = []
channel = 'https://bj.lianjia.com/zufang/dongcheng/'
#spider1 爬取房屋資訊連結并用mongodb存儲
def get_pages_url(channel,pag):
url = str(channel+'pg'+ pag)
wb_data = requests.get(url,headers=requests_headers(),proxies=ip_proxy())
soup = BeautifulSoup(wb_data.text,'lxml')
time.sleep(1)
no_data = '呣..沒有找到相關内容，請您換個條件試試吧~'
# 面包屑子產品
# 面包屑 breadcrumbs
bread_crumbs =soup.select('#house-lst > li')
item_url = soup.select('#house-lst > li > div > h2 > a')
blank_url = str(soup.find(text = no_data))
if no_data != blank_url:
for url in item_url:
url1 = url.get('href')
url_list1.append(url1)
#url_list.insert_one({'url':url1})
print(url1)
else:
pass
#get_pages_url(channel,'2')
# spider2 爬取詳細資訊并用mongodb存儲
def get_massages(url):
web_data = requests.get(url,headers=requests_headers(),proxies=ip_proxy())
soup = BeautifulSoup(web_data.text,'lxml')
title = (soup.title.text).split('|')[0] #房名
address = soup.select('div.zf-room > p > a')[0].text #位址
price = soup.select(' div.price > span.total')[0].text + '元'
area = (soup.select('div.zf-room > p ')[0].text).split('：')[-1]
home_url = url
print({'title':title ,
'address':address,
'price':price,
'area':area,
'home_url':home_url,
})
item_list.insert_one({'title':title ,
'address':address,
'price':price,
'area':area,
'home_url':home_url})
get_massages('https://bj.lianjia.com/zufang/101101635089.html')
'''
#house-lst > li > p
list-no-data clear
'''