使用python爬取全国所有热门景点数据---去哪儿网

2019-11-10 18:34:07

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来源：转载

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要爬取去哪儿上面的所有的热门景点的数据可以先再搜索出搜索热门景点

http://piao.qunar.com/ticket/list.htm?keyWord=%E7%83%AD%E9%97%A8%E6%99%AF%E7%82%B9®ion=&from=mpl_search_suggest

可以看到有几千页的景点数据,我们要爬取的就是这些数据;

最好是从分类开始爬取:

分析完之后现在就开始写python代码爬取所有热门景点的数据 :

# -*- coding: utf-8 -*-import requestsfrom bs4 import BeautifulSoupimport csvfrom multiprocessing import Queueimport  threadingimport randomfrom time import sleepUser_Agent=["Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/51.0.2704.106 Safari/537.36","Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_8; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50","Mozilla/5.0 (Windows; U; Windows NT 6.1; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50","Mozilla/5.0 (Macintosh; Intel Mac OS X 10.6; rv:2.0.1) Gecko/20100101 Firefox/4.0.1","Mozilla/5.0 (Windows NT 6.1; rv:2.0.1) Gecko/20100101 Firefox/4.0.1"]HEADERS = {    'User-Agent':  User_Agent[random.randint(0,4)],    # 'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:55.0) Gecko/201002201 Firefox/55.0',    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',    'Accept-Language': 'zh-CN,zh;q=0.8,en-US;q=0.5,en;q=0.3',    'Accept-Encoding': 'gzip, deflate, br',    'Cookie': '',    'Connection': 'keep-alive',    'PRagma': 'no-cache',    'Cache-Control': 'no-cache'}csvfile = open('去哪儿景点.csv','w',encoding='utf-8', newline='')writer = csv.writer(csvfile)writer.writerow(["区域","名称","景点id","类型","级别","热度","地址","特色","经纬度"])def download_page(url):  # 下载页面    try:        data = requests.get(url, headers=HEADERS, allow_redirects=True).content  # 请求页面，获取要爬取的页面内容        return data    except:        pass#下载页面 如果没法下载就 等待1秒 再下载def download_soup_waitting(url):    try:        response= requests.get(url,headers=HEADERS,allow_redirects=False,timeout=5)        if response.status_code==200:            html=response.content            html=html.decode("utf-8")            soup = BeautifulSoup(html, "html.parser")            return soup        else:            sleep(1)            print("等待ing")            return download_soup_waitting(url)    except:        return ""def getTypes():    types=["文化古迹","自然风光","公园","古建筑","寺庙","遗址","古镇","陵墓陵园","故居","宗教"] #实际不止这些分组 需要自己补充    for type in types:        url="http://piao.qunar.com/ticket/list.htm?keyword=%E7%83%AD%E9%97%A8%E6%99%AF%E7%82%B9&region=&from=mpl_search_suggest&subject="+type+"&page=1"        getType(type,url)def getType(type,url):    soup=download_soup_waitting(url)    search_list=soup.find('div', attrs={'id': 'search-list'})    sight_items=search_list.findAll('div', attrs={'class': 'sight_item'})    for sight_item in sight_items:        name=sight_item['data-sight-name']        districts=sight_item['data-districts']        point=sight_item['data-point']        address=sight_item['data-address']        data_id=sight_item['data-id']        level=sight_item.find('span',attrs={'class':'level'})        if level:            level=level.text        else:            level=""        product_star_level=sight_item.find('span',attrs={'class':'product_star_level'})        if product_star_level:            product_star_level=product_star_level.text        else:            product_star_level=""        intro=sight_item.find('div',attrs={'class':'intro'})        if intro:            intro=intro['title']        else:            intro=""        writer.writerow([districts.replace("/n",""),name.replace("/n",""),data_id.replace("/n",""),type.replace("/n",""),level.replace("/n",""),product_star_level.replace("/n",""),address.replace("/n",""),intro.replace("/n",""),point.replace("/n","")])    next=soup.find('a',attrs={'class':'next'})    if next:        next_url="http://piao.qunar.com"+next['href']        getType(type,next_url)if __name__ == '__main__':    getTypes()之后只要让它执行就好  如果发现 控制台中一直打印  等待ing  很有可能 ip被封了  只要使用代理换个ip就会继续爬取,
最后爬取出来的数据总共有 4,5万的数据:
      如果需要这份数据    请联系 zhenpeng_lin@QQ.com