京东图书爬虫

效果：

 

 

 

 

 

 

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version_0

分析：

返回的数据是Json
大分类：https://lapi.jd.com/pool?body={%22pid%22:%220101947%22}&source=book,每个poolid对应一个大title
      ```
      title: "文学综合馆",
      operate_title: "",
      sort_num: 2,
      fid: 0,
      id: 7369,
      ext_info: {
         poolId: "0101945"
      }
      ```
      部分数据，即title对应一个poolId，属于同一个字典下
拿到大分类的poolId，就可以用pooId取构造请求：https://lapi.jd.com/pool?body={%22pid%22:%220101945%22}&source=book，来获取中title以及小title,以及对应的小title的url
请求小title的url拿到图书列表，图书信息在https://list.jd.com/listNew.php?cat=1713%2C3260%2C3345&page=150，在这个地址中，有总的页数，SEARCH.adv_param={page:"150",page_count:"200",psort:"0",cid1: 0,
其中page_count为总的页数,page为当前页数,价格未有单独请求，包含在这个网址中，至此，网页分析完毕。

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源代码

# -*- coding: utf-8 -*-
import scrapy
import json
from copy import deepcopy
from pprint import pprint
import re
from urllib import parse


class JdtsSpider(scrapy.Spider):
    name = \'jdts\'
    # allowed_domains = [\'book.jd.com\',\'lapi.jd.com\',\'coll.jd.com\',\'list.jd.com\',\'search.jd.com\']
    allowed_domains = ["jd.com"]
    start_urls = [\'https://lapi.jd.com/pool?body={%22pid%22:%220101947%22}&source=book\']

    def parse(self, response):
        item = dict()
        json_obj = json.loads(response.body.decode())
        data_list = json_obj["data"][1:-4]
        for data in data_list:
            # 拿到大分类及poolId
            item["b_title"] = data["title"]
            item["poolId"] = data["ext_info"]["poolId"]
            # 用poolId去请求中级分类和下级分类
            temporary_var = \'"pid":"{}"\'.format(item["poolId"])
            next_url = \'https://lapi.jd.com/pool?body={\'+temporary_var+\'}&source=book\'
            yield scrapy.Request(
                url=next_url,
                callback=self.parse_poolid,
                meta={"item":item}
            )
            break

    def parse_poolid(self,response):
        item = response.meta["item"]

        json_obj = json.loads(response.body.decode())
        data_list = json_obj["data"][2:]

        # 获取中级分类
        for data in data_list:
            item["m_title"] =    data["title"]
            s_item_list = data["children"]
            # 获得下级分类
            for s_item in s_item_list:
                item["s_title"] = s_item["title"]
                item["s_href"] = s_item["link_value"]
                yield scrapy.Request(
                    url=item["s_href"],
                    callback=self.parse_s_href,
                    meta={"item":item}
                )

    def parse_s_href(self,response):
        item = deepcopy(response.meta["item"])
        book_info = dict()
        print("-"*20)
        print("响应的url：", response.url)
        # with open   ("test.html",\'w\',encoding=\'utf8\') as f:
        #     f.write(response.body.decode())
        # 拿到总页数
        count_page = int(re.findall(r\'page_count:\"(.*?)\"\',response.body.decode(),re.S)[0])
        print("count_page:",count_page)
        # 获取书籍列表
        content_list = re.findall(r\'class="p-img">(.*?)<div class="p-commit">\',response.body.decode(),re.S)
        for content in content_list:
            # 获取书籍信息
            item["book_info"] = book_info
            item["book_info"]["book_title"] = re.findall(r\'<em>(.*?)</em>\', content, re.S)[1]
            item["book_info"]["book_href"] = re.findall(r\'href="(.*?)"\',content,re.S)[0]
            item["book_info"]["book_href"] = parse.urljoin(response.url,item["book_info"]["book_href"])
            item["book_info"]["book_price"] = re.findall(r\'<i>(.*?)</i>\', content, re.S)[0]
            yield scrapy.Request(
                url=item["book_info"]["book_href"],
                callback=self.parse_detail,
                meta={"item":deepcopy(item)}
            )
        num = 2     # 计数指针
        while num<count_page:
            if "&page=" in response.url:
                next_page_href = response.url.split("&page",1)[0]+"&page={}".format(num)
                # print("*"*20)
                # print("next_page_url:", next_page_href)
                # print("*"*20)
            else:
                next_page_href = response.url+"&page={}".format(num)
                # print("next_page_url:",next_page_href)
            yield scrapy.Request(
                url=next_page_href,
                callback=self.parse_s_href,
                meta={"item":response.meta["item"]}
            )
            num += 1

    def parse_detail(self,response):
        item = response.meta["item"]
        item["book_info"]["book_author"] = response.xpath("//div[@class=\'p-author\']/a/text()").extract_first()
        # url_1 = "https://dx.3.cn/desc/12234231"  skudid
        # url_2 = "https://cd.jd.com/description/channel?skuId=69612641897&mainSkuId=14541400416" skuid mainskuid
        skuid = re.findall(r\'com/(.*?)\.html\',response.url,re.S)[0]
        mainskuid = re.findall(r"mainSkuId:\'(.*?)\'",response.body.decode(),re.S)
        if mainskuid:
            mainskuid = mainskuid[0]
            url = "https://cd.jd.com/description/channel?skuId={}&mainSkuId={}"
            next_url = url.format(skuid,mainskuid)
        else:
            url = "https://dx.3.cn/desc/{}"
            next_url = url.format(skuid)
        item["book_info"]["book_description"] = next_url
        print("*"*20)
        print("描述文件获取地址:",next_url)
        print("*"*20)
        pprint(item)