使用scrapy-redis 爬取京东图书信息 （案例）

scrapy startproject JD  # 创建

scrapy genspider jdbook jd.com  # 生成

# -*- coding: utf-8 -*- import scrapy from copy import deepcopy import json import urllib class JdbookSpider(scrapy.Spider): name = 'jdbook' allowed_domains = ['jd.com', 'p.3.cn']
    start_urls = ['https://book.jd.com/booksort.html'] def parse(self, response): dt_list = response.xpath("//div[@class='mc']/dl/dt") # 大分类列表 for dt in dt_list:
            item = {}
            item["b_category"] = dt.xpath("./a/text()").extract_first()
            em_list = dt.xpath("./following-sibling::dd[1]/em") # 小分类列表 for em in em_list:
                item["s_href"] = em.xpath("./a/@href").extract_first()
                item["s_cate"] = em.xpath("./a/text()").extract_first() if item["s_href"] is not None:
                    item["s_href"] = "https:" + item["s_href"] yield scrapy.Request(
                        item["s_href"],
                        callback=self.parse_book_list,
                        meta={"item":deepcopy(item)}
                    ) def parse_book_list(self, response): # 解析列表页 item = response.meta["item"]
        li_list = response.xpath("//div[@id='plist']/ul/li") for li in li_list:
            item["book_img"] = li.xpath(".//div[@class='p-img']//img/@src").extract_first() if item["book_img"] is None:
                item["book_img"] = li.xpath(".//div[@class='p-img']//img/@data-lazy-img").extract_first()
            item["book_img"] = "https:" + item["book_img"] if item["book_img"] is not None else None item["book_name"] = li.xpath(".//div[@class='p-name']/a/em/text()").extract_first().strip()
            item["book_author"] = li.xpath(".//span[@class='author_type_1']/a/text()").extract()
            item["book_press"] = li.xpath(".//span[@class='p-bi-store']/a/@title").extract_first()
            item["book_publish_date"] = li.xpath(".//span[@class='p-bi-date']/text()").extract_first().strip()
            item["book_sku"] = li.xpath("./div/@data-sku").extract_first() yield scrapy.Request( "https://p.3.cn/prices/mgets?skuIds=J_{}".format(item["book_sku"]),
                callback=self.parse_book_price,
                meta={"item":deepcopy(item)}
            ) # 列表页翻页 next_url = response.xpath("//a[@class='pn-next']/@href").extract_first() if next_url is not None:
            next_url = urllib.parse.urljoin(response.url, next_url) yield scrapy.Request(
                next_url,
                callback=self.parse_book_list,
                meta={"item":item}
            ) def parse_book_price(self, response): item = response.meta["item"]
        item["book_price"] = json.loads(response.body.decode())[0]["op"]
        print(item)