Scrapy anjuke.com 广州二手房数据(保存为 csv)

Spiders

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# -*- coding: utf-8 -*-
from scrapy import Spider,Request
from anjuke.items import AnjukeItem

class AnjukehouseSpider(Spider):
    name = 'anjukeHouse'
    allowed_domains = ['anjuke.com']
    start_urls = ['https://guangzhou.anjuke.com/sale/p1-rd1/#filtersort']

    def parse(self, response):
        # 所有房子URL
        urls = response.xpath('//div[@class="house-title"]/a/@href').extract()
        for url in urls:
            yield Request(url,callback=self.parse_detail)

        # 下一页
        next = response.xpath('//*[@id="content"]/div[4]/div[7]/a[7]/@href').extract()
        if next:
            next = response.urljoin(next[0])
            yield Request(next,callback=self.parse)

    def parse_detail(self,response):
        item = AnjukeItem()
        item['date'] = response.xpath('//span[@class="house-encode"]/text()').extract()[0].split()
        item['tittle'] = response.xpath('//h3[@class="long-title"]/text()').extract()
        item['price'] = response.xpath('//span[@class="light info-tag"]/em/text()').extract_first().split()

        houseInfo = response.xpath('//div[@class="houseInfo-content"]/text()').extract()
        item['huxing'] = houseInfo[2].strip().replace("\n","").replace("\t","").split()
        item['area'] = houseInfo[7].strip().split()
        item['built'] = houseInfo[9].strip().replace("\n", "").replace("\t", "").split()
        item['chaoxiang'] = houseInfo[10].strip().split()
        item['leixing'] = houseInfo[-8].strip().split()
        item['louceng'] = houseInfo[-7].strip().split()
        item['zhuangxiu'] = houseInfo[-6].strip().split()
        print(item)
    return item

items

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from scrapy import Item,Field

class AnjukeItem(Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    tittle = Field()
    huxing = Field()
    area = Field()
    chaoxiang = Field()
    louceng = Field()
    price = Field()
    zhuangxiu = Field()
    leixing = Field()
    date = Field()
    built = Field()

settings

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BOT_NAME = 'anjuke'

SPIDER_MODULES = ['anjuke.spiders']
NEWSPIDER_MODULE = 'anjuke.spiders'

# Obey robots.txt rules
ROBOTSTXT_OBEY = False

DOWNLOAD_DELAY = 3

DEFAULT_REQUEST_HEADERS = {
    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
    'Accept-Language': 'en',
    'user-agent':'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.110 Safari/537.36',
    'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',
    'accept-encoding': 'gzip, deflate, br',
    'accept-language': 'zh-CN,zh;q=0.9',
    'cache-control': 'max-age=0',
}

ITEM_PIPELINES = {
'anjuke.pipelines.Pipeline_ToCSV': 300,
}

pipelines

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import csv
import os

class Pipeline_ToCSV(object):

    def __init__(self):
        self.csvwriter = csv.writer(open('anjuke.csv', 'w'), delimiter=',')
        self.csvwriter.writerow(['date','tittle', 'price', 'huxing', 'area','built','chaoxiang','leibie','loucheng','zhuangxiu'])

    def process_item(self, item, ampa):
        rows = zip(item['date'],item['tittle'], item['price'],item['huxing'],item['area'],item['built'],item['chaoxiang'],item['leixing'],item['louceng'],item['zhuangxiu'])

        for row in rows:
            self.csvwriter.writerow(row)

        return item

Selenium

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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time    : 18-12-28 下午6:48
# @Author  : Vitan
# @File    : anjuke.py

from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from bs4 import  BeautifulSoup
import pandas
import time,random

broswer = webdriver.Chrome()
wait = WebDriverWait(broswer,10)
houseInfo = []
def get_urls():
    page_urls = []
    star_url = 'https://guangzhou.anjuke.com/sale/p'
    for i in range(1,51):
        url = star_url+str(i)
        page_urls.append(url)
    return page_urls

def HouseUrl(url):
    time.sleep(random.random()*10)
    broswer.get(url)
    wait.until(EC.presence_of_element_located((By.CSS_SELECTOR, '.curr')))
    urls = broswer.find_elements_by_css_selector('.houseListTitle') # a 标签
    house_urls = []
    for a in urls:
        urls = a.get_attribute('href')
        house_urls.append(urls)
    return house_urls

def get_detail(url):
    time.sleep(random.random()*10)
    broswer.get(url)
    wait.until(EC.presence_of_element_located((By.CSS_SELECTOR, '.houseInfoBox')))
    info = {}
    # info['标题'] = broswer.find_element_by_css_selector('.long-title').get_attribute('textContent')
    # info['总价'] = broswer.find_elements_by_css_selector('.basic-info span')[0].get_attribute('textContent')
    # info['户型'] = broswer.find_elements_by_css_selector('.basic-info span')[1].get_attribute('textContent')
    # info['面积'] = broswer.find_elements_by_css_selector('.basic-info span')[2].get_attribute('textContent')
    # info['单价'] = broswer.find_elements_by_css_selector('.houseInfo-content')[2].get_attribute('textContent')
    # info['朝向'] = broswer.find_elements_by_css_selector('.houseInfo-content')[7].get_attribute('textContent')
    # info['月供'] = broswer.find_elements_by_css_selector('.houseInfo-content')[8].get_attribute('textContent')
    # info['楼层'] = broswer.find_elements_by_css_selector('.houseInfo-content')[-7].get_attribute('textContent')
    # info['装修'] = broswer.find_elements_by_css_selector('.houseInfo-content')[-6].get_attribute('textContent')
    html = broswer.page_source
    soup = BeautifulSoup(html,'lxml')
    info['标题'] = soup.select('.long-title')[0].text
    info['总价'] = soup.select('.basic-info span')[0].text
    info['户型'] = soup.select('.basic-info span')[1].text
    info['面积'] = soup.select('.basic-info span')[2].text
    info['单价'] = soup.select('.houseInfo-content')[2].text
    info['朝向'] = soup.select('.houseInfo-content')[7].text
    info['月供'] = soup.select('.houseInfo-content')[8].text
    info['楼层'] = soup.select('.houseInfo-content')[-7].text
    info['装修'] = soup.select('.houseInfo-content')[-6].text
    k = ['标题','总价','户型','面积','单价','朝向','月供','楼层','装修']
    info_adj = dict(zip(k,list(info.values())))
    houseInfo.append(info_adj)
    print(houseInfo)
    return houseInfo

def save_to_csv(houseInfo):
    df = pandas.DataFrame(houseInfo)
    df.to_csv('maoming.csv')

def main():
    page_urls = get_urls()
    for url in page_urls:
        house_urls = HouseUrl(url)
        for url in house_urls:
            houseInfo=get_detail(url)
            save_to_csv(houseInfo)

if __name__ == '__main__':
    main()
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