在使用ImagesPipeline下载图片数据时，我们需要对其中的三个管道类方法进行重写，其中 — get_media_request 是对图片地址发起请求

— file path 是返回图片名称

— item_completed 返回item,将其返回给下一个即将被执行的管道类

那具体代码是什么样的呢，首先我们需要在pipelines.py文件中，导入ImagesPipeline类，然后重写上述所说的3个方法：

from scrapy.pipelines.images import ImagesPipeline
import  scrapy
import os
  
  
class ImgsPipLine(ImagesPipeline):
    def get_media_requests(self, item, info):
        yield scrapy.Request(url = item['img_src'],meta={'item':item})
  
  
    #返回图片名称即可
    def file_path(self, request, response=None, info=None):
        item = request.meta['item']
        print('########',item)
        filePath = item['img_name']
        return filePath
  
    def item_completed(self, results, item, info):
        return item

方法定义好后，我们需要在settings.py配置文件中进行设置，一个是指定图片保存的位置IMAGES_STORE = 'D:\\ImgPro'，然后就是启用“ImgsPipLine”管道，

ITEM_PIPELINES = {
   'imgPro.pipelines.ImgsPipLine': 300,  #300代表优先级，数字越小优先级越高
}

设置完成后，我们运行程序后就可以看到“D:\\ImgPro”下保存成功的图片。

完整代码如下：

spider文件代码：

# -*- coding: utf-8 -*-
import scrapy
from imgPro.items import ImgproItem
  
  
  
class ImgSpider(scrapy.Spider):
    name = 'img'
    allowed_domains = ['www.521609.com']
    start_urls = ['//www.521609.com/daxuemeinv/']
  
    def parse(self, response):
        #解析图片地址和图片名称
        li_list = response.xpath('//div[@class="index_img list_center"]/ul/li')
        for li in li_list:
            item = ImgproItem()
            item['img_src'] = '//www.521609.com/'  + li.xpath('./a[1]/img/@src').extract_first()
            item['img_name'] = li.xpath('./a[1]/img/@alt').extract_first() + '.jpg'
            # print('***********')
            # print(item)
            yield item

items.py文件

import scrapy
  
  
class ImgproItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    img_src = scrapy.Field()
    img_name = scrapy.Field()

pipelines.py文件

from scrapy.pipelines.images import ImagesPipeline
import  scrapy
import os
from  imgPro.settings import IMAGES_STORE as IMGS
  
class ImgsPipLine(ImagesPipeline):
    def get_media_requests(self, item, info):
        yield scrapy.Request(url = item['img_src'],meta={'item':item})
  
  
    #返回图片名称即可
    def file_path(self, request, response=None, info=None):
        item = request.meta['item']
        print('########',item)
        filePath = item['img_name']
        return filePath
  
    def item_completed(self, results, item, info):
        return item

settings.py文件

import random
BOT_NAME = 'imgPro'
  
SPIDER_MODULES = ['imgPro.spiders']
NEWSPIDER_MODULE = 'imgPro.spiders'
  
IMAGES_STORE = 'D:\\ImgPro'   #文件保存路径
LOG_LEVEL = "WARNING"
ROBOTSTXT_OBEY = False
#设置user-agent
USER_AGENTS_LIST = [
        "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1",
        "Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11",
        "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6",
        "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6",
        "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1",
        "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5",
        "Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5",
        "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
        "Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
        "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
        "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",
        "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",
        "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
        "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
        "Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
        "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3",
        "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24",
        "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24"
    ]
USER_AGENT = random.choice(USER_AGENTS_LIST)
DEFAULT_REQUEST_HEADERS = {
    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
    'Accept-Language': 'en',
   # 'User-Agent':"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36",
    'User-Agent':USER_AGENT
}
  
#启动pipeline管道
ITEM_PIPELINES = {
   'imgPro.pipelines.ImgsPipLine': 300,
}

 以上即是使用ImagesPipeline下载保存图片的方法，今天突生一个疑惑，爬虫爬的好，真的是牢饭吃的饱吗？还请各位大佬解答！

原文来自：

本文地址：//gulass.cn/python-scrapy-imagespipeline.html编辑：xiangping wu，审核员：逄增宝

Linux大全：

Linux系统大全：

红帽认证RHCE考试心得：