scrapy爬取当当网

Posted 2021-02-08 pontoon

春节已经临近了尾声，也该收收心了。博客好久都没更新了，自己在年前写的爬虫也该“拿”出来了。

本次爬取的目标是当当网，获取当当网所有的书籍信息。采用scrapy+mongodb来采集存储数据。开干！

起始url：

start_urls = [‘http://category.dangdang.com/cp01.00.00.00.00.00-shlist.html‘]

 当当书籍的一级分类二级分类都很明显的展示了出来。

ok~入口找到了，当当网也没有设置反爬措施，所以可以直接的放心爬取，如果需要大规模爬取的时候可以对爬虫的请求时间设置下，不要给别人的服务器带来太多的压力。

DOWNLOAD_DELAY = 5

 ok，我直接上代码了！

items.py

 1 class BookDangdangItem(scrapy.Item):
 2     # 将数据插入到moongodb中
 3     price = scrapy.Field()  # 价格
 4     type_tag = scrapy.Field()  # 所属分类
 5     name = scrapy.Field()  # 书籍名称
 6     image_url = scrapy.Field()  # 首页的图片url
 7     link = scrapy.Field()  # url
 8     star_level = scrapy.Field()  # 星
 9     pub_time = scrapy.Field()  # 出版时间
10     publish = scrapy.Field()  # 出版社
11     brief = scrapy.Field()  # 描述
12 
13     detail = scrapy.Field()  # 书籍详情 {}

 spiders.py

  1 # -*- coding: utf-8 -*-
  2 import time
  3 import logging
  4 
  5 import scrapy
  6 from scrapy.http.cookies import CookieJar
  7 
  8 from ..items import BookDangdangItem
  9 from ..settings import DEFAULT_REQUEST_HEADERS
 10 
 11 
 12 class DangdangSpider(scrapy.Spider):
 13     name = ‘dangdang‘
 14     allowed_domains = [‘dangdang.com‘]
 15     start_urls = [‘http://category.dangdang.com/cp01.00.00.00.00.00-shlist.html‘]
 16     dom = ‘http://category.dangdang.com‘  # 用于拼接url
 17     cookie_dict = {}
 18 
 19     def start_requests(self):
 20         return [scrapy.Request(url=self.start_urls[0], callback=self.parse, headers=DEFAULT_REQUEST_HEADERS)]
 21 
 22     def parse(self, response):
 23         try:
 24             typestr = response.meta[‘type‘]
 25         except(KeyError):
 26             typestr = ""
 27         types = response.xpath(‘//*[@id="navigation"]/ul/li[1]/div[2]/div[1]/div/span/a‘)  # 获取书籍分类
 28         tyname = response.xpath(‘//*[@id="navigation"]/ul/li[1]/@dd_name‘).extract_first()
 29         if types and tyname == ‘分类‘:  # 到分类终止递归
 30             for type in types:
 31                 url = self.dom + type.xpath(‘@href‘).extract_first()  # 每一个书籍分类下面的url
 32                 typestr_new = typestr + "{0}>>".format(type.xpath(‘text()‘).extract_first())  # 多级分类
 33 
 34                 scrapy.Spider.log(self, "Find url:{0},type{1}".format(url, typestr_new), logging.INFO)  # 配置日志信息
 35                 yield scrapy.Request(url=url, callback=self.parse, meta={‘type‘: typestr_new},
 36                                      headers=DEFAULT_REQUEST_HEADERS)
 37         else:
 38             page = int(response.xpath(‘//*[@id="go_sort"]/div/div[2]/span[1]/text()‘).extract_first())  # 当前页
 39             all_page = int(response.xpath(‘//*[@id="go_sort"]/div/div[2]/span[2]/text()‘).extract_first().lstrip(‘/‘))  # 总页数
 40             for x in range(page, all_page):  # 处理分页
 41                 yield scrapy.Request(url=self.dom + ‘/pg{0}-‘.format(x) + response.url.split(‘/‘)[-1],
 42                                      callback=self.parse_page, headers=DEFAULT_REQUEST_HEADERS,
 43                                      meta={‘type‘: typestr})
 44 
 45     def parse_page(self, response):
 46         """解析列表页中书籍的信息"""
 47         # cookie可以不用加，我加上只是为了测试
 48         cookie_jar = CookieJar()
 49         cookie_jar.extract_cookies(response, response.request)
 50         for k, v in cookie_jar._cookies.items():
 51             for i, j in v.items():
 52                 for m, n in j.items():
 53                     self.cookie_dict[m] = n.value
 54         # print(self.cookie_dict)
 55 
 56         for item in response.xpath(‘//*[@id="search_nature_rg"]/ul[@class="bigimg"]/li‘):
 57             # 所有图书
 58             book = BookDangdangItem()
 59             book[‘price‘] = float(item.xpath(‘./p[@class="price"]/span[1]/text()‘).extract_first().lstrip(‘¥‘))
 60             book[‘type_tag‘] = response.meta[‘type‘]
 61             book[‘name‘] = item.xpath(‘./p[@class="name"]/a/text()‘).extract_first().strip()
 62             book[‘image_url‘] = item.xpath(‘./a/img/@src‘).extract_first()
 63             book[‘link‘] = item.xpath(‘./p[1]/a/@href‘).extract_first()
 64             book[‘star_level‘] = int(item.xpath(‘./p[@class="search_star_line"]/span/span/@style‘).extract_first()
 65                                                  .split(‘ ‘)[-1].rstrip(‘%;‘))
 66             try:
 67                 book[‘pub_time‘] = item.xpath(‘.//p[@class="search_book_author"]/span[2]/text()‘).extract_first().split(‘/‘)[-1]
 68             except Exception as e:
 69                 book[‘pub_time‘] = time.strftime("%Y-%m-%d")
 70             try:
 71                 book[‘publish‘] = item.xpath(
 72                     ‘./p[@class="search_book_author"]/span[3]/a/text()‘).extract_first().strip()
 73             except Exception as e:
 74                 book[‘publish‘] = "暂无出版社信息"
 75             try:
 76                 book[‘brief‘] = item.xpath(‘./p[2]/text()‘).extract_first().strip()
 77             except Exception as e:
 78                 book[‘brief‘] = "暂无书籍简述"
 79             yield scrapy.Request(callback=self.parse_book, cookies=self.cookie_dict,
 80                                  headers=DEFAULT_REQUEST_HEADERS, meta={‘item‘: book}, url=book[‘link‘])
 81 
 82     def parse_book(self, response):
 83         """跟进url解析书籍详情"""
 84         book = response.meta[‘item‘]
 85         book[‘detail‘] = {}
 86         info = response.xpath("//ul[@class=‘key clearfix‘]/li/text()").extract()
 87         print(info)
 88         for i in info:
 89             t = i.partition("：")
 90             k = t[0].replace(" ", "")
 91             v = t[-1]
 92             if v == ‘‘:
 93                 v = "暂无详情"
 94             book[‘detail‘][k] = v
 95 
 96         # 这个作者详情当当不同的板块有不同的取法，看了下有很多种，写起来挺麻烦的就暂时这样处理
 97         try:
 98             book[‘detail‘][‘author_detail‘] = response.xpath("//span[@id=‘authorIntroduction-show’]/text()") 99                 .extract_first().replace(‘
‘, ‘‘)
100         except Exception as e:
101             book[‘detail‘][‘author_detail‘] = "暂无作者信息"
102 
103         yield book

View Code

说明下：cookie在本次爬虫中可以不用加，我加上只是为了测试。请求头做太多的定制。

piplines.py

 1 from scrapy.conf import settings
 2 from scrapy import signals
 3 from pymongo import MongoClient
 4 
 5 
 6 class DangDangSpiderPipeline(object):
 7     def __init__(self):
 8         # 获取setting中主机名，端口号和集合名
 9         host = settings[‘MONGODB_HOST‘]
10         port = settings[‘MONGODB_PORT‘]
11         dbname = settings[‘MONGODB_DBNAME‘]
12         col = settings[‘MONGODB_COL‘]
13 
14         # 创建一个mongo实例
15         client = MongoClient(host=host, port=port)
16 
17         # 访问数据库
18         db = client[dbname]
19 
20         # 访问集合
21         self.col = db[col]
22 
23     def process_item(self, item, spider):
24         data = dict(item)
25         self.col.insert(data)
26         return item

View Code

settings.py

 1 USER_AGENT = ‘Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/49.0.2623.22  2               Safari/537.36 SE 2.X MetaSr 1.0‘
 3 
 4 ROBOTSTXT_OBEY = False
 5 
 6 DOWNLOAD_DELAY = 5
 7 
 8 COOKIES_ENABLED = False
 9 
10 DEFAULT_REQUEST_HEADERS = {
11     ‘Accept‘: ‘text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8‘,
12     ‘Accept-Language‘: ‘en‘,
13     "authority": " www.dangdang.com",
14     "method": "GET",
15     "path": "/",
16     "scheme": "http",
17     "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8",
18     "accept-encoding": ‘gzip, deflate, br‘,
19     "accept-language": ‘en-US,en;q=0.9‘,
20     "referer": None,
21     "upgrade-insecure-requests": 1,
22     "User-Agent": ‘Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/49.0.2623.22 23                       Safari/537.36 SE 2.X MetaSr 1.0‘
24 }    # 可以不写使用默认的
25 
26 ITEM_PIPELINES = {
27     ‘dangdangspider.pipelines.DangDangSpiderPipeline‘: 300,
28 }
29 
30 # Mongodb
31 # 主机环回地址
32 MONGODB_HOST = ‘127.0.0.1‘
33 # 端口号，默认27017
34 MONGODB_POST = 27017
35 # 设置数据库名称
36 MONGODB_DBNAME = ‘dangdangs‘
37 # 设置集合名称
38 MONGODB_COL = ‘books‘

View Code

settings.py请求头可以不用写，使用默认的就行，我之所以加上也是测试用的，同理上面写了两个user-agent。just for fun  :-)

这次爬虫其实主要的目的是，我想了解下scrapy中的cookie是如何加上的，以及怎么用，有多少中用法！scrapy中的cookie无论是在官方文档或者一些大V的博客里都很少介绍到，但是他在实际的场景中却会用到，那就是模拟登录的时候。或者向淘宝那样需要携带cookie才能访问页面的时候。关于如何使用cookie请查看我的另一篇博客