Python使用爬蟲爬取貴陽房價的方法詳解

#==========導 包=============
import requests
#=====step_1 : 指 定 url=========
url = 'https://gy.fang.lianjia.com/ /'
#=====step_2 : 發 起 請 求 :======
#使 用 get 方 法 發 起 get 請 求 ， 該 方 法 會 返 回 一 個 響 應 對 象 。 參 數 url 表 示 請 求 對 應 的 url
response = requests . get ( url = url )
#=====step_3 : 獲 取 響 應 數 據 :===
#通 過 調 用 響 應 對 象 的 text 屬 性 ， 返 回 響 應 對 象 中 存 儲 的 字 符 串 形 式 的 響 應 數 據 （ 頁 面 源 碼數 據 ）
page_text = response . text
#====step_4 : 持 久 化 存 儲=======
with open ('貴陽房價 . html ','w', encoding ='utf -8') as fp:
    fp.write ( page_text )
print (' 爬 取 數 據 完 畢 !!!')

爬 取 數 據 完 畢 !!!
Process finished with exit code 0

#==================導入相關庫==================================
from bs4 import BeautifulSoup
import numpy as np
import requests
from requests.exceptions import  RequestException
import pandas as pd
#=============讀取網頁=========================================
def craw(url,page):
    try:
        headers = {
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3947.100 Safari/537.36"}
        html1 = requests.request("GET", url, headers=headers,timeout=10)
        html1.encoding ='utf-8' # 加編碼，重要！轉換為字符串編碼，read()得到的是byte格式的
        html=html1.text
        return html
    except RequestException:#其他問題
        print('第{0}讀取網頁失敗'.format(page))
        return None
#==========解析網頁並保存數據到表格======================
def pase_page(url,page):
    html=craw(url,page)
    html = str(html)
    if html is not None:
        soup = BeautifulSoup(html, 'lxml')
        "--先確定房子信息，即li標簽列表--"
        houses=soup.select('.resblock-list-wrapper li')#房子列表
        "--再確定每個房子的信息--"
        for j in range(len(houses)):#遍歷每一個房子
            house=houses[j]
            "名字"
            recommend_project=house.select('.resblock-name a.name')
            recommend_project=[i.get_text()for i in recommend_project]#名字 英華天元，斌鑫江南禦府...
            recommend_project=' '.join(recommend_project)
            #print(recommend_project)
            "類型"
            house_type=house.select('.resblock-name span.resblock-type')
            house_type=[i.get_text()for i in house_type]#寫字樓,底商...
            house_type=' '.join(house_type)
            #print(house_type)
            "銷售狀態"
            sale_status = house.select('.resblock-name span.sale-status')
            sale_status=[i.get_text()for i in sale_status]#在售,在售,售罄,在售...
            sale_status=' '.join(sale_status)
            #print(sale_status)
            "大地址"
            big_address=house.select('.resblock-location span')
            big_address=[i.get_text()for i in big_address]#
            big_address=''.join(big_address)
            #print(big_address)
            "具體地址"
            small_address=house.select('.resblock-location a')
            small_address=[i.get_text()for i in small_address]#
            small_address=' '.join(small_address)
            #print(small_address)
            "優勢。"
            advantage=house.select('.resblock-tag span')
            advantage=[i.get_text()for i in advantage]#
            advantage=' '.join(advantage)
            #print(advantage)
            "均價：多少1平"
            average_price=house.select('.resblock-price .main-price .number')
            average_price=[i.get_text()for i in average_price]#16000,25000,價格待定..
            average_price=' '.join(average_price)
            #print(average_price)
            "總價,單位萬"
            total_price=house.select('.resblock-price .second')
            total_price=[i.get_text()for i in total_price]#總價400萬/套，總價100萬/套'...
            total_price=' '.join(total_price)
            #print(total_price)
            #=====================寫入表格=================================================
            information = [recommend_project, house_type, sale_status,big_address,small_address,advantage,average_price,total_price]
            information = np.array(information)
            information = information.reshape(-1, 8)
            information = pd.DataFrame(information, columns=['名稱', '類型', '銷售狀態','大地址','具體地址','優勢','均價','總價'])
            information.to_csv('貴陽房價.csv', mode='a+', index=False, header=False)  # mode='a+'追加寫入
        print('第{0}頁存儲數據成功'.format(page))
    else:
        print('解析失敗')
#==================雙線程=====================================
import threading
for i  in range(1,100,2):#遍歷網頁1-101
    url1="https://gy.fang.lianjia.com/loupan/pg"+str(i)+"/"
    url2 = "https://gy.fang.lianjia.com/loupan/pg" + str(i+1) + "/"
    t1 = threading.Thread(target=pase_page, args=(url1,i))#線程1
    t2 = threading.Thread(target=pase_page, args=(url2,i+1))#線程2
    t1.start()
    t2.start()v