1.jd.py
# -*- coding: utf-8 -*- import scrapy from copy import deepcopy import json import urllib from scrapy_redis.spiders import RedisSpider from JingDong.items import JingdongItem class JdSpider(RedisSpider): name = \'jd\' # allowed_domains = [\'jd.com\'] # start_urls = [\'https://book.jd.com/booksort.html/\'] redis_key = \'jingdong\' # #解析分类 def parse(self, response): dt_list=response.xpath(\'//div[@class="mc"]/dl/dt\') #大分类列表 for dt in dt_list: item=JingdongItem() item[\'b_cate\']=dt.xpath(\'./a/text()\').extract_first()#当前循环大标题 em_list=dt.xpath(\'./following-sibling::dd[1]/em\') #下小分类列表 for em in em_list: item[\'s_href\']=em.xpath(\'./a/@href\').extract_first() #小分类的标题 item[\'s_cate\']=em.xpath(\'./a/text()\').extract_first() #小分类得到url 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\':item}) #解析每个小分类下的所有图书 def parse_book_list(self,response): item=response.meta[\'item\'] li_list=response.xpath(\'//div[@id="plist"]/ul/li\') for li in li_list: item[\'book_name\']=li.xpath(\'.//div[@class="p-name"]/a/em/text()\').extract_first().strip() item[\'book_img\']=li.xpath(\'.//div[@class="p-img"]//img/@src\').extract_first() #封面照片连接 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_author\']=li.xpath(\'.//span[@class="author_type_1"]/a/text()\').extract() #作者 item[\'book_publish\']=li.xpath(\'.//span[@class="p-bi-store"]/a/@title\').extract_first() #出版社 item[\'book_publish_date\']=li.xpath(\'.//span[@class="p-bi-date"]/text()\').extract_first().strip() #出版日期 item[\'book_sku\']=li.xpath(\'./div/@data-sku\').extract_first()#书籍编号 #这边价格是去后端再次请求得到的 #因为这边后边还需要用到item，所以需要用到深拷贝,sccrapy有三级分类的都要注意是否要使用深拷贝 yield scrapy.Request(\'https://p.3.cn/prices/mgets?skuIds={}\'.format(item[\'book_sku\']),callback=self.parse_book_price,meta={\'item\':deepcopy(item)}) #列表翻页 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}) #解析价格函数 def parse_book_price(self,response): item=response.meta[\'item\'] #这边返回的json串 book_info_dict=json.loads(response.body.decode()) item[\'boo_price\']=book_info_dict[0][\'op\'] print(\'=========\',item)
2.item
import scrapy class JingdongItem(scrapy.Item): # define the fields for your item here like: # name = scrapy.Field() b_cate=scrapy.Field() s_href=scrapy.Field() s_cate=scrapy.Field() book_name=scrapy.Field() book_img=scrapy.Field() book_author=scrapy.Field() book_publish=scrapy.Field() book_publish_date=scrapy.Field() book_sku=scrapy.Field() boo_price=scrapy.Field()
3.settings
# -*- coding: utf-8 -*- # Scrapy settings for JingDong project # # For simplicity, this file contains only settings considered important or # commonly used. You can find more settings consulting the documentation: # # https://doc.scrapy.org/en/latest/topics/settings.html # https://doc.scrapy.org/en/latest/topics/downloader-middleware.html # https://doc.scrapy.org/en/latest/topics/spider-middleware.html BOT_NAME = \'JingDong\' SPIDER_MODULES = [\'JingDong.spiders\'] NEWSPIDER_MODULE = \'JingDong.spiders\' # Crawl responsibly by identifying yourself (and your website) on the user-agent USER_AGENT = \'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3626.109 Safari/537.36\' # Obey robots.txt rules ROBOTSTXT_OBEY = False # Configure maximum concurrent requests performed by Scrapy (default: 16) #CONCURRENT_REQUESTS = 32 # Configure a delay for requests for the same website (default: 0) # See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay # See also autothrottle settings and docs #DOWNLOAD_DELAY = 3 # The download delay setting will honor only one of: #CONCURRENT_REQUESTS_PER_DOMAIN = 16 #CONCURRENT_REQUESTS_PER_IP = 16 # Disable cookies (enabled by default) #COOKIES_ENABLED = False # Disable Telnet Console (enabled by default) #TELNETCONSOLE_ENABLED = False # Override the default request headers: #DEFAULT_REQUEST_HEADERS = { # \'Accept\': \'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\', # \'Accept-Language\': \'en\', #} # Enable or disable spider middlewares # See https://doc.scrapy.org/en/latest/topics/spider-middleware.html #SPIDER_MIDDLEWARES = { # \'JingDong.middlewares.JingdongSpiderMiddleware\': 543, #} # Enable or disable downloader middlewares # See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html #DOWNLOADER_MIDDLEWARES = { # \'JingDong.middlewares.JingdongDownloaderMiddleware\': 543, #} # Enable or disable extensions # See https://doc.scrapy.org/en/latest/topics/extensions.html #EXTENSIONS = { # \'scrapy.extensions.telnet.TelnetConsole\': None, #} # Configure item pipelines # See https://doc.scrapy.org/en/latest/topics/item-pipeline.html ITEM_PIPELINES = { # \'JingDong.pipelines.JingdongPipeline\': 300, \'scrapy_redis.pipelines.RedisPipeline\': 400 } # Enable and configure the AutoThrottle extension (disabled by default) # See https://doc.scrapy.org/en/latest/topics/autothrottle.html #AUTOTHROTTLE_ENABLED = True # The initial download delay #AUTOTHROTTLE_START_DELAY = 5 # The maximum download delay to be set in case of high latencies #AUTOTHROTTLE_MAX_DELAY = 60 # The average number of requests Scrapy should be sending in parallel to # each remote server #AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0 # Enable showing throttling stats for every response received: #AUTOTHROTTLE_DEBUG = False # Enable and configure HTTP caching (disabled by default) # See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings #HTTPCACHE_ENABLED = True #HTTPCACHE_EXPIRATION_SECS = 0 #HTTPCACHE_DIR = \'httpcache\' #HTTPCACHE_IGNORE_HTTP_CODES = [] #HTTPCACHE_STORAGE = \'scrapy.extensions.httpcache.FilesystemCacheStorage\' DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter" SCHEDULER = "scrapy_redis.scheduler.Scheduler" SCHEDULER_PERSIST = True REDIS_URL=\'redis://127.0.0.1:6379\'