先用CSS提取数据学习章节方法定位文章位置：

图中红色箭头属性为全局唯一

下面图片为要抓取的文章对应图片样例：

图中红色箭头为要抓取图片

<dl class="list_userbar">

                    <dt>
                        <a href="https://blog.csdn.net/valada" target="_blank" class="user_img">
                            <img src="https://avatar.csdn.net/E/2/6/1_valada.jpg" alt="valada" title="valada">
                        </a>
                    </dt>
                    <dd class="name">
                        <a href="https://blog.csdn.net/valada?utm_source=feed" target="_blank">
                            GitChat的博客                        </a>
                    </dd>
                                            <div class="interval"></div>
                        <dd class="tag">
                            <a href="/nav/ai" target="_blank">
                                人工智能                            </a>
                        </dd>
                                        <div class="interval"></div>
                    <dd class="time">
                        08月14日                    </dd>
                                        <div class="interval"></div>
                    <dd class="blogtitle">
                        来自 <a href="https://blog.csdn.net/valada?utm_source=feed" target="_blank">GitChat 的 blog</a>
                    </dd>
                                        <div class="interactive floatR">
                        <!--阅读 begin-->
                        <dd class="read_num">
                            <a href="https://blog.csdn.net/valada/article/details/81639661" data-track-click="{&quot;mod&quot;:&quot;popu_459&quot;,&quot;con&quot;:&quot;,https://blog.csdn.net/valada/article/details/81639661,none&quot;}">
                                <span class="num">3845</span>
                                <span class="text">阅读</span>
                            </a>
                        </dd>
                        <!--阅读 end-->
                        <!--新增评论数+阅读 begin-->
                        <div class="interval"></div>
                        <dd class="common_num ">
                            <a href="https://blog.csdn.net/valada/article/details/81639661#commentBox" target="_blank" data-track-click="{&quot;mod&quot;:&quot;popu_459&quot;,&quot;con&quot;:&quot;,https://blog.csdn.net/valada/article/details/81639661#commentBox,none&quot;}">
                                                                    <span class="num">10</span>                                <span class="text">评论</span>
                            </a>
                        </dd>
                        <!--新增评论数+阅读 end-->
                    </div>
                </dl>               

html源码分析：从代码中可以看到img对应的src地址是直接可访问地址，直接获取地址后就能获取图片。
下面是应用scrapy抓取代码：

#use scrapy shell debug
scrapy shell https://blog.csdn.net/
#get article title and url
response.css("#feedlist_id .clearfix .list_con .title h2 a::text").extract()
response.css("#feedlist_id .clearfix .list_con .title h2 a::attr(href)").extract()
#get the portrait of the author
import scrapy
import re
from scrapy.http import Request
from urllib import parse

post_nodes = response.css("#feedlist_id .clearfix .list_con .list_userbar dt a")    
        for post_node in post_nodes:
            image_url = post_node.css("img::attr(src)").extract_first("")
            post_url = post_node.css("::attr(href)").extract_first("")
            yield Request(url=parse.urljoin(response.url,post_url), meta={"front_image_url":}, callback=self.parse_detail)

在运行时会发现缺少pillow组件需安装，安装如下：

 (py3env) MacBook~/Python/tutorial/MySpider$ pip3 install -i https://pypi.douban.com/simple  pillow
Looking in indexes: https://pypi.douban.com/simple
Collecting pillow
  Downloading https://pypi.doubanio.com/packages/d1/21/bef2816809fac16754e07ed935469fc65f42ced1a94766de7c804179311d/Pillow-5.3.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (3.6MB)
    100% |████████████████████████████████| 3.6MB 2.2MB/s
Installing collected packages: pillow
Successfully installed pillow-5.3.0
You are using pip version 18.0, however version 18.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.