使用python爬虫爬取信息时会遇到哪些问题-创新互联
今天就跟大家聊聊有关使用python 爬虫爬取信息时会遇到哪些问题,可能很多人都不太了解,为了让大家更加了解,小编给大家总结了以下内容,希望大家根据这篇文章可以有所收获。
我们拥有十载网页设计和网站建设经验,从网站策划到网站制作,我们的网页设计师为您提供的解决方案。为企业提供成都网站设计、网站建设、外贸网站建设、微信开发、微信小程序开发、手机网站制作设计、H5建站、等业务。无论您有什么样的网站设计或者设计方案要求,我们都将富于创造性的提供专业设计服务并满足您的需求。爬取代码:
import requests from requests.exceptions import RequestException from pyquery import PyQuery as pq from bs4 import BeautifulSoup import pymongo from config import * from multiprocessing import Pool client = pymongo.MongoClient(MONGO_URL) # 申明连接对象 db = client[MONGO_DB] # 申明数据库 def get_one_page_html(url): # 获取网站每一页的html headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/85.0.4183.121 Safari/537.36" } try: response = requests.get(url, headers=headers) if response.status_code == 200: return response.text else: return None except RequestException: return None def get_room_url(html): # 获取当前页面上所有room_info的url doc = pq(html) room_urls = doc('.r_lbx .r_lbx_cen .r_lbx_cena a').items() return room_urls def parser_room_page(room_html): soup = BeautifulSoup(room_html, 'lxml') title = soup.h2.text price = soup.find('div', {'class': 'room-price-sale'}).text[:-3] x = soup.find_all('div', {'class': 'room-list'}) area = x[0].text[7:-11] # 面积 bianhao = x[1].text[4:] house_type = x[2].text.strip()[3:7] # 户型 floor = x[5].text[4:-2] # 楼层 location1 = x[6].find_all('a')[0].text # 分区 location2 = x[6].find_all('a')[1].text location3 = x[6].find_all('a')[2].text subway = x[7].text[4:] addition = soup.find_all('div', {'class': 'room-title'})[0].text yield { 'title': title, 'price': price, 'area': area, 'bianhao': bianhao, 'house_type': house_type, 'floor': floor, 'location1': location1, 'location2': location2, 'location3': location3, 'subway': subway, 'addition': addition } def save_to_mongo(result): if db[MONGO_TABLE].insert_one(result): print('存储到mongodb成功', result) return True return False def main(page): url = 'http://www.xxxxx.com/room/sz?page=' + str(page) # url就不粘啦,嘻嘻 html = get_one_page_html(url) room_urls = get_room_url(html) for room_url in room_urls: room_url_href = room_url.attr('href') room_html = get_one_page_html(room_url_href) if room_html is None: # 非常重要,否则room_html为None时会报错 pass else: results = parser_room_page(room_html) for result in results: save_to_mongo(result) if __name__ == '__main__': pool = Pool() # 使用多进程提高爬取效率 pool.map(main, [i for i in range(1, 258)])
当前文章:使用python爬虫爬取信息时会遇到哪些问题-创新互联
分享链接:http://pwwzsj.com/article/dpdcgc.html