Python中scrapy下載保存圖片的示例

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        在日常爬蟲練習中，我們爬取到的數據需要進行保存操作，在scrapy中我們可以使用ImagesPipeline這個類來進行相關操作，這個類是scrapy已經封裝好的瞭，我們直接拿來用即可。

                                                                   

     在使用ImagesPipeline下載圖片數據時，我們需要對其中的三個管道類方法進行重寫，其中         — get_media_request   是對圖片地址發起請求

   — file path   是返回圖片名稱

   — item_completed  返回item,將其返回給下一個即將被執行的管道類

                                                

        那具體代碼是什麼樣的呢，首先我們需要在pipelines.py文件中，導入ImagesPipeline類，然後重寫上述所說的3個方法：

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})
 
 
    #返回圖片名稱即可
    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

        方法定義好後，我們需要在settings.py配置文件中進行設置，一個是指定圖片保存的位置IMAGES_STORE = ‘D:\\ImgPro’，然後就是啟用“ImgsPipLine”管道，

ITEM_PIPELINES = {
   'imgPro.pipelines.ImgsPipLine': 300,  #300代表優先級，數字越小優先級越高
}

         設置完成後，我們運行程序後就可以看到“D:\\ImgPro”下保存成功的圖片。

完整代碼如下：

spider文件代碼：

# -*- coding: utf-8 -*-
import scrapy
from imgPro.items import ImgproItem
 
 
 
class ImgSpider(scrapy.Spider):
    name = 'img'
    allowed_domains = ['www.521609.com']
    start_urls = ['http://www.521609.com/daxuemeinv/']
 
    def parse(self, response):
        #解析圖片地址和圖片名稱
        li_list = response.xpath('//div[@class="index_img list_center"]/ul/li')
        for li in li_list:
            item = ImgproItem()
            item['img_src'] = 'http://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})
 
 
    #返回圖片名稱即可
    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'   #文件保存路徑
LOG_LEVEL = "WARNING"
ROBOTSTXT_OBEY = False
#設置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
}
 
#啟動pipeline管道
ITEM_PIPELINES = {
   'imgPro.pipelines.ImgsPipLine': 300,
}

         以上即是使用ImagesPipeline下載保存圖片的方法，今天突生一個疑惑，爬蟲爬的好，真的是牢飯吃的飽嗎？還請各位大佬解答！更多相關Python scrapy下載保存內容請搜索WalkonNet以前的文章或繼續瀏覽下面的相關文章希望大傢以後多多支持WalkonNet！

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