本文实例讲述了Python3爬虫爬取英雄联盟高清桌面壁纸功能。分享给大家供大家参考，具体如下：

使用Scrapy爬虫抓取英雄联盟高清桌面壁纸

源码地址：https://github.com/snowyme/loldesk

开始项目前需要安装python3和Scrapy，不会的自行百度，这里就不具体介绍了

首先，创建项目

scrapy startproject loldesk

生成项目的目录结构

首先需要定义抓取元素，在item.py中，我们这个项目用到了图片名和链接

import scrapy

class LoldeskItem(scrapy.Item):

name = scrapy.Field()

ImgUrl = scrapy.Field()

pass

接下来在爬虫目录创建爬虫文件，并编写主要代码，loldesk.py

import scrapy

from loldesk.items import LoldeskItem

class loldeskpiderSpider(scrapy.Spider):

name = "loldesk"

allowed_domains = ["www.win4000.com"]

# 抓取链接

start_urls = [

'http://www.win4000.com/zt/lol.html'

]

def parse(self, response):

list = response.css(".Left_bar ul li")

for img in list:

imgurl = img.css("a::attr(href)").extract_first()

imgurl2 = str(imgurl)

next_url = response.css(".next::attr(href)").extract_first()

if next_url is not None:

# 下一页

yield response.follow(next_url, callback=self.parse)

yield scrapy.Request(imgurl2, callback=self.content)

def content(self, response):

item = LoldeskItem()

item['name'] = response.css(".pic-large::attr(title)").extract_first()

item['ImgUrl'] = response.css(".pic-large::attr(src)").extract()

yield item

# 判断页码

next_url = response.css(".pic-next-img a::attr(href)").extract_first()

allnum = response.css(".ptitle em::text").extract_first()

thisnum = next_url[-6:-5]

if int(allnum) > int(thisnum):

# 下一页

yield response.follow(next_url, callback=self.content)

图片的链接和名称已经获取到了，接下来需要使用图片通道下载图片并保存到本地，pipelines.py：

from scrapy.pipelines.images import ImagesPipeline

from scrapy.exceptions import DropItem

from scrapy.http import Request

import re

class MyImagesPipeline(ImagesPipeline):

def get_media_requests(self, item, info):

for image_url in item['ImgUrl']:

yield Request(image_url,meta={'item':item['name']})

def file_path(self, request, response=None, info=None):

name = request.meta['item']

name = re.sub(r'[？\\*|“<>:/()0123456789]', '', name)

image_guid = request.url.split('/')[-1]

filename = u'full/{0}/{1}'.format(name, image_guid)

return filename

def item_completed(self, results, item, info):

image_path = [x['path'] for ok, x in results if ok]

if not image_path:

raise DropItem('Item contains no images')

item['image_paths'] = image_path

return item

最后在settings.py中设置存储目录并开启通道：

# 设置图片存储路径

IMAGES_STORE = 'F:/python/loldesk'

#启动pipeline中间件

ITEM_PIPELINES = {

'loldesk.pipelines.MyImagesPipeline': 300,

}

在根目录下运行程序：

scrapy crawl loldesk

大功告成！！！一共抓取到128个文件夹

希望本文所述对大家Python程序设计有所帮助。