从原理到实战，一份详实的 Scrapy 爬虫教程

知行编程网 2022-07-22 08:00 知行编程网 | 隐藏边栏 | 抢沙发 | 6 0

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之前分享了很多 requests 、selenium 的 Python 爬虫文章，本文将从原理到实战带领大家入门另一个强大的框架 Scrapy。如果对Scrapy感兴趣的话，不妨跟随本文动手做一遍！

一、Scrapy框架简介

Scrapy是:由Python语言开发的一个快速、高层次的屏幕抓取和web抓取框架，用于抓取web站点并从页面中提取结构化的数据，只需要实现少量的代码，就能够快速的抓取。

二、运行原理

Scrapy框架的运行原理看下面一张图就够了（事实上原理是比较复杂的，也不是三言两语能够说清楚的，因此感兴趣的读者可以进一步阅读更多的相关文章来了解，本文不做过多讲解）

Scrapy主要包括了以下组件：

引擎(Scrapy Engine)
Item 项目
调度器(Scheduler)
下载器(Downloader)
爬虫(Spiders)
项目管道(Pipeline)
下载器中间件(Downloader Middlewares)
爬虫中间件(Spider Middlewares)
调度中间件(Scheduler Middewares)

三. 入门

3.1安装

第一种：在命令行模式下使用pip命令即可安装：

第二种：首先下载，然后再安装：

进入下载目录后执行下面命令安装：

3.2使用

使用大概分为下面四步1 创建一个scrapy项目

2 生成一个爬虫

3 提取数据

4 保存数据

3.3 程序运行

在命令中运行爬虫

在pycharm中运行爬虫

四、基本步骤

Scrapy 爬虫框架的具体使用步骤如下：

“

选择目标网站

定义要抓取的数据（通过Scrapy Items来完成的）

编写提取数据的spider

执行spider，获取数据

数据存储

”

五. 目录文件说明

当我们创建了一个scrapy项目后,继续创建了一个spider,目录结构是这样的：

下面来简单介绍一下各个主要文件的作用：

“

scrapy.cfg ：项目的配置文件

mySpider/ ：项目的Python模块，将会从这里引用代码

mySpider/items.py ：项目的目标文件

mySpider/pipelines.py ：项目的管道文件

mySpider/settings.py ：项目的设置文件

mySpider/spiders/ ：存储爬虫代码目录

”

5.1 scrapy.cfg文件

项目配置文件。这个是文件的内容：

5.2 mySpider/

项目的Python模块，将会从这里引用代码

5.3 mySpider/items.py

项目的目标文件

定义scrapy items的模块,示例: name = scrapy.Field()

5.4 mySpider/pipelines.py

项目的管道文件

这个文件也就是我们说的管道,当Item在Spider中被收集之后，它将会被传递到Item Pipeline(管道)，这些Item Pipeline组件按定义的顺序处理Item。每个Item Pipeline都是实现了简单方法的Python类，比如决定此Item是丢弃而存储。以下是item pipeline的一些典型应用：

验证爬取的数据(检查item包含某些字段，比如说name字段)
查重(并丢弃)
将爬取结果保存到文件或者数据库中

5.5 mySpider/settings.py

项目的设置文件

省略号省略代码,一般重要点,给了注释

6.mySpider/spiders/ ：存储爬虫代码目录

六. Scrapy shell

Scrapy终端是一个交互终端，我们可以在未启动spider的情况下尝试及调试代码，也可以用来测试XPath或CSS表达式，查看他们的工作方式，方便我们爬取的网页中提取的数据,但是一般使用的不多。感兴趣的查看官方文档:

官方文档

Scrapy Shell根据下载的页面会自动创建一些方便使用的对象，例如 Response 对象，以及 Selector 对象 (对HTML及XML内容)。

当shell载入后，将得到一个包含response数据的本地 response 变量，输入 response.body将输出response的包体，输出 response.headers 可以看到response的包头。
输入 response.selector 时，将获取到一个response 初始化的类 Selector 的对象，此时可以通过使用 response.selector.xpath()或response.selector.css() 来对 response 进行查询。
Scrapy也提供了一些快捷方式, 例如 response.xpath()或response.css()同样可以生效（如之前的案例）。

Selectors选择器

“

Scrapy Selectors 内置 XPath 和 CSS Selector 表达式机制

”

Selector有四个基本的方法，最常用的还是xpath:

xpath(): 传入xpath表达式，返回该表达式所对应的所有节点的selector list列表
extract(): 序列化该节点为字符串并返回list
css(): 传入CSS表达式，返回该表达式所对应的所有节点的selector list列表，语法同 BeautifulSoup4
re(): 根据传入的正则表达式对数据进行提取，返回字符串list列表

七、案例实战

本节，我将使用Scrapy爬取站酷数据作为示例

7.1 案例说明

既然已经初步了解了scrapy的工作流程以及原理,我们来做一个入门的小案例,爬取站酷首页推荐的item信息。如下图所示，一个小方框就是一个item信息。我们要提取每一个item的六个组成部分：

imgLink(封面图片链接)；
title(标题）;
types（类型）;
vistor（人气）;
comment（评论数）;
likes（推荐人数）

然后只是一个页面的item，我们还要通过翻页实现批量数据采集。

7.2 文件配置

目录结构

在上一篇中我们说明了新建scrapy项目（zcool）和spider项目（zc），这里不再赘述，然后得到我们的目录结构如下图所示：

start.py文件

然后为了方便运行，在zcool目录下新建start文件。并进行初始化设置。

settings.py文件

在这个文件里我们需要做几样设置👇

避免在程序运行的时候打印log日志信息

添加请求头：

打开管道：

item.py文件

7.3 页面数据提取

首先我们在站酷页面使用xpath-helper测试一下：

然后zc.py文件里面初步测试一下：

运行结果如下图所示：

没有问题，然后我们对各种信息分别解析提取，

解释： xpath提取数据方法：

S.N.	方法 & 描述
extract()	返回的是符合要求的所有的数据，存在一个列表里。
extract_first()	返回的hrefs 列表里的第一个数据。
get()	和extract_first()方法返回的是一样的，都是列表里的第一个数据。
getall()	和extract()方法一样，返回的都是符合要求的所有的数据，存在一个列表里。

注意：

“

get() 、getall() 方法是新的方法，extract() 、extract_first()方法是旧的方法。extract() 、extract_first()方法取不到就返回None。get() 、getall() 方法取不到就raise一个错误。

”

item实例创建（yield上面一行代码）

这里我们之前在目录文件配置的item文件中已经进行了设置，对于数据存储，我们在爬虫文件中开头要导入这个类：

然后使用yield返回数据。

为什么使用yield而不是return

不能使用return这个无容置疑，因为要翻页，使用return直接退出函数；而对于yield:在调用for的时候，函数内部不会立即执行，只是返回了一个生成器对象。在迭代的时候函数会开始执行，当在yield的时候，会返回当前值(i)。之后的这个函数会在循环中进行，直到没有下一个值。

7.4 翻页实现批量数据采集

通过上面的代码已经可以初步实现数据采集，只不过只有第一页的，如下图所示：

但是我们的目标是100个页面的批量数据采集，所以代码还需要修改。针对翻页这里介绍两种方式：

方式一：我们首先在页面中定位到下一页的按钮，如下图所示：

然后编写如下代码，在for循环完毕后。

scrapy.Request(): 把下一页的url传递给Request函数,进行翻页循环数据采集。

注意方式一只有下一页按钮它的href对应属性值和下一页的url一致才行。

方式二：定义一个全局变量count = 0,每爬取一页数据，令其加一，构建新的url,再使用scrapy.Request() 发起请求。

如下图所示：

这两种方式在实际案例中择机采用。

7.5 数据存储

数据存储是在pipline.py中进行的,代码如下：

解释:

line1: 打开文件，指定方式为写，利用第3个参数把csv写数据时产生的空行消除
line2: 设置文件第一行的字段名，注意要跟spider传过来的字典key名称相同
line3: 指定文件的写入方式为csv字典写入，参数1为指定具体文件，参数2为指定字段名
line4: 写入第一行字段名，因为只要写入一次，所以文件放在__init__里面
line5: 写入spider传过来的具体数值,注意在spider文件中yield的item,是一个由类创建的实例对象，我们写入数据时，写入的是字典，所以这里还要转化一下。
line6: 写入完返回

7.6 程序运行

因为之前创建了start.py文件,并且对它就行了初始化设置，现在运行爬虫程序不需要在控制台中输入命令：

直运行start.py文件：得到如下结果：

对应于页面：

打开csv文件如下图所示：（由于csv文件在word中乱码了，此处我是用Notepad++打开）

没有问题，数据采集完毕。

7.7. 总结

入门案例，需要细心，主要是基础知识的巩固，以便于为进阶学习做好准备。

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data-darkmode-original-color-15900529136199="rgb(51, 51, 51)" data-darkmode-bgimage-15900529136199="1" style="max-width: 100%;font-size: 14px;color: rgb(51, 51, 51);text-align: left;box-sizing: border-box !important;overflow-wrap: break-word !important;"><span style="max-width: 100%;font-family: 楷体, 楷体_GB2312, SimKai;white-space: pre-wrap;font-size: 12px;box-sizing: border-box !important;overflow-wrap: break-word !important;">点阅读原文,领AI全套资料！</span><span style="font-family: PingFangSC-light;font-size: 16px;letter-spacing: 0px;"></span></section></section></section></section></section></section></section>

一、Scrapy框架简介

二、运行原理