Image Pipeline

Image Pipeline

Scrapy 提供了专门下载文件或者图片的Pipeline，下载图片与文件的原理同抓取网页的原理是一样的，所以他们的下载过程支持多线程与异步，十分的高效

Image Pipeline的工作流程

1. itemPipeline从item中获取需要下载的数据，通过Request重新放入到项目队列等待调度器调度下载
2. 当图片下载完成，另一个组(images)将被更新到结构中,其中包括下载图片的信息,比如下载路径,源抓取地址(从image_urls组获得)和图片的校验码. images列表中的图片顺序将和源image_urls组保持一致.如果某个图片下载失败,将会记录下错误信息,图片也不会出现在images组中

参考链接

案例

1. 首先在settings中配置图片存放路径

   IMAGES_STORE = './images'

2. 在item中定义需要的数据结构

   class Images360Item(scrapy.Item):
       # define the fields for your item here like:
       # name = scrapy.Field()
       collection = table = "images"
       id = scrapy.Field()
       title = scrapy.Field()
       url = scrapy.Field()
       thumb = scrapy.Field()

3. 定义spider与parse

   import scrapy
   from urllib.parse import urlencode
   from scrapy import Request
   from images360.images360.items import Images360Item
   
   class ImagesSpider(scrapy.Spider):
       name = 'images'
       allowed_domains = ['images.so.com']
       start_urls = ['http://images.so.com/']
   
       def start_requests(self):
           data = {'ch': 'photography','listtype': 'hot',}
           base_url = 'http://images.so.com/zj?'
           for page in range(1,self.settings.get('MAX_PAGE_SIZE') + 1):
               sn = page * 30
               data['sn'] = sn
               params = urlencode(data)
               url = base_url + params
               print(url)
               yield Request(url,self.parse)
   
       def parse(self,response):
           html = json.loads(response.text)
           datas = html.get('list','')
           if datas:
               for data in datas:
                   images_item = Images360Item()
                   images_item['id'] = data.get('imageid','')
                   images_item['title'] = data.get('group_title','')
                   images_item['url'] = data.get('qhimg_url','')
                   images_item['thumb'] = data.get('qhimg_thumb_url','')
                   yield images_item

4. 定义项目管道

   from scrapy import Request
   from scrapy.exceptions import DropItem
   from scrapy.pipelines.images import ImagesPipeline
   
   class ImagesPipeline(ImagesPipeline):
   
       # 将item中的url取出来 通过Request继续放入到调度器中执行
       def get_media_requests(self,item,info):
           yield Request(item['url'])
   
       # request对应的是当前下载对象，该函数用于放回 文件名
       def file_path(self,request,response=None,info=None):
           url = request.url
           print('url============',url)
           file_name = url.split('/')[-1]
           return file_name
   
       # 单个item完成下载时的处理方法
       def item_completed(self,results,info):
                # results为Item对应的下载结果
           # print(results) 
           # [(True,{'url': 'http://p2.so.qhimgs1.com/t01b866193d9b2101de.jpg','path': 't01b866193d9b2101de.jpg',#          'checksum': 'e074b5cbacd22ac38480d84506fedf02'})]
   
           image_path = [x['path'] for ok,x in results if ok]
           if image_path:
               return item
           else:
               raise DropItem('image download failed')

   注：ImagePipeline的优先级别应该比存入数据库的级别高