python 爬虫实例（四）

环境：

OS：Window10

python：3.7

爬取链家地产上面的数据，两个画面上的数据的爬取

效果，下面的两个网页中的数据取出来

代码

import datetime
import threading

import requests
from bs4 import BeautifulSoup

class LianjiaHouseInfo:

    '''
        初期化变量的值
    '''
    def __init__(self):
        # 定义自己要爬取的URL
        self.url = "https://dl.lianjia.com/ershoufang/pg{0}"
        self.path = r"C:pythonProjectLianjia_House"
        self.headers = {
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36"}

    '''
        访问URL
    '''
    def request(self, param):

        # 如果不加的话可能会出现403的错误，所以尽量的都加上header，模仿网页来访问
        req = requests.get(param, headers=self.headers)
        # req.raise_for_status()
        # req.encoding = req.apparent_encoding
        return req.text
    '''
        page設定
    '''
    def all_pages(self, pageCn):
        dataListA = []
        for i in range(1, pageCn+1):
            if pageCn == 1:
                dataListA = dataListA + self.getData(self.url[0:self.url.find("pg")])
            else:
                url = self.url.format(i)
                dataListA = dataListA + self.getData(url)
        # self.dataOrganize(dataListA)
    '''
       数据取得
    '''
    def getData(self, url):
        dataList = []
        thread_lock.acquire()
        req = self.request(url)
        # driver = webdriver.Chrome()
        # driver.get(self.url)
        # iframe_html = driver.page_source
        # driver.close()
        # print(iframe_html)
        soup = BeautifulSoup(req, 'lxml')
        countHouse = soup.find(class_="total fl").find("span")
        print("共找到 ", countHouse.string, " 套大连二手房")

        sell_all = soup.find(class_="sellListContent").find_all("li")
        for sell in sell_all:

            title = sell.find(class_="title")
            if title is not None:
                print("------------------------概要--------------------------------------------")
                title = title.find("a")
                print("title:", title.string)
                housInfo = sell.find(class_="houseInfo").get_text()
                print("houseInfo:", housInfo)
                positionInfo = sell.find(class_="positionInfo").get_text()
                print("positionInfo:", positionInfo)

                followInfo = sell.find(class_="followInfo").get_text()
                print("followInfo:", followInfo)

                print("------------------------詳細信息--------------------------------------------")
                url_detail = title["href"]
                req_detail = self.request(url_detail)
                soup_detail = BeautifulSoup(req_detail, "lxml")
                total = soup_detail.find(class_="total")
                unit = soup_detail.find(class_="unit").get_text()
                dataList.append(total.string+unit)
                print("总价:", total.string, unit)
                unitPriceValue = soup_detail.find(class_="unitPriceValue").get_text()
                dataList.append(unitPriceValue)
                print("单价:", unitPriceValue)
                room_mainInfo = soup_detail.find(class_="room").find(class_="mainInfo").get_text()
                dataList.append(room_mainInfo)
                print("户型:", room_mainInfo)
                type_mainInfo = soup_detail.find(class_="type").find(class_="mainInfo").get_text()
                dataList.append(type_mainInfo)
                print("朝向:", type_mainInfo)
                area_mainInfo = soup_detail.find(class_="area").find(class_="mainInfo").get_text()
                dataList.append(area_mainInfo)
                print("面积:", area_mainInfo)

            else:
                print("広告です")
        thread_lock.release()
        return dataList
    #
    # def dataOrganize(self, dataList):
    #
    #     data2 = pd.DataFrame(dataList)
    #     data2.to_csv(r'C:UserspeiqiangDesktoplagoujob.csv', header=False, index=False, mode='a+')
    #     data3 = pd.read_csv(r'C:UserspeiqiangDesktoplagoujob.csv', encoding='gbk')



thread_lock = threading.BoundedSemaphore(value=100)
house_Info = LianjiaHouseInfo()
startTime = datetime.datetime.now()
house_Info.all_pages(1)
endTime = datetime.datetime.now()
print("実行時間：", (endTime - startTime).seconds)

　　运行之后的效果