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Python中常用的网络爬虫框架有哪些?

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网络爬虫是指通过代码模拟浏览器访问网页、解析页面内容,并将所需信息提取出来存储到本地或数据库中。在实际工作场景中,我们经常需要从互联网上获取特定类型或特定格式的数据。而 Python 作为一门高级编程语言,其强大的库支持和简洁易懂的语法使得它成为了众多开发者喜欢使用的语言之一。当然,在进行 Python 网络爬虫开发时,借助现有稳定可靠且功能强大的框架能够更快速、更方便地完成任务。

本文将介绍 Python 中常用的几种流行的网络爬虫框架:Scrapy, BeautifulSoup, Requests 和 Selenium,并比较这些框架之间各自优缺点,帮助读者选择最适合自己项目需求和个人能力水平的工具。

Scrapy

Scrapy 是一个基于 Twisted 框架构建、专门针对于 Web 爬虫设计开发、高度模块化、可扩展性非常优秀并且已经广泛应用于企业级别开源项目中去(例如:知乎)。其主要特点包括:

  1. 强大且灵活: 可以处理从简单到复杂甚至异步请求等多种情况;
  2. 高效: 支持异步IO操作,在同样硬件条件下相比其他同类软件有着不小优势;
  3. 开放性和通用性: 可以轻松运行在 Windows, Linux and Mac OS 上;
  4. 内置组件齐全: 包含了整套生命周期内所需组件(例如链接管理器、管道等).

BeautifulSoup

BeautifulSoup 常被称为“万能解析器”,因为它可以解析任何 HTML/XML 文本并从中提取出所需要信息。此外,BeautifulSoup 还可以配合 urllib 或 requests 库发送 Http 请求并接收响应结果。
该库主要优点包括:

  1. 使用简单直观;
  2. 解析速度快;
  3. 兼容性好;
  4. 自动转换编码格式.
    但同时也存在以下局限:
    a) 功能相对较少;
    b) 不支持js执行;
    c) 不能发送请求对象.
    d) 执行效率没有 Scrapy 高。
    e) 虽说是万能解析器但对于某些HTML还是无法正确处理。
    f)beautifulsoup4不再支持python2.x版本。
    g)bs4属于第三方库可能会产生兼容问题及安装配置问题

Requests

The Requests 库旨在使 HTTP 请求变得更加人性化。它基于 urllib,并改进了许多原始库未曾处理过问题。Requests 提供了一个很友好但功能完备型 API 来处理 HTTP/1.1 协议。(HTTP协议详见相关文章)
The Request 主要特点包括:
a) 易学易记;b) 封装度高;c) 更接近人们思考方式;d)安装便捷;e)支持文件上传;f)核心对象返回Response对象即http响应报文;g)底层可以调用urllib3(线程池机制),代理设置灵活;h)requests内部默认UTF-8传输字符集 ,而urllib默认传输ASCII码字符; i ) 对cookie做了封装;i ) requests还可以有效避免重复提交表单等一系列恶意攻击手段(javascript脚本注入),增强了Web程序客户端安全性。
j )requests只是一个HTTP库,并不像scrapy那样涉及到其他领域(比如数据库),如果你想使用requests来写spider必须先研究清楚spider整体结构(分布式?),否则你很可能会感觉requests太弱小了.
k )由于request只是个http协议客户端并不包含web服务器相关内容故不能像Scrapy那样按照固定流程完成整个网站抓取过程。(如果只是简单抓取某个网页还是挺好用)
l )没有scapy那么深入底层跑起来就很快 。
m ) 最后值得注意request仅仅只负责下载服务端返回回来html/css/js/img/png/jpg等资源与服务端交互查询关键字,但不负责解释HTML/CSS/JS(比如登录验证),这就意味着我们需要另外选型一款HTML/CSS/JS渲染引擎对页面进行渲染分析才能真正获取页面数据。(PhantomJS/Selenium/Splash….)
n)supports http keep-alive and connection pooling to reuse TCP connections between requests for better performance while handling multiple load-intensive tasks . It means when you send a request to the server then it will maintain that connection until response is completed or closed by server end for better performance in network as well as CPU utilization.
o)secure and strong SSL/TLS encryption support over HTTPS protocol with high configurable options like certificate verification etc., also supports different types of authentication mechanisms including token based which makes it more secure than other similar libraries available on internet.
p)supports various session management techniques such as cookie-based sessions or token-based sessions depending upon project requirement but it does not have built-in support for distributed task scheduling unlike scrapy which has advanced features like distributed crawling/scraping using celery/rabbitmq etc., so if we need this kind of feature then we should use scrapy instead of requests library alone .q)maintains compatibility with older versions of python (including python 2.x series).r)Limited support for JavaScript rendering/dynamic page content extraction compared to other frameworks like Scrapy due to its lack of automatic browser emulation capabilities(rather than manual implementation via headless browsers). However, this can be overcome using third-party tools like Selenium WebDriver in conjunction with Requests for full web page scraping capability..s)treat cookies differently from some other client-side storage mechanisms(treat them separately from sessionStorage/localStorage/etc.).t)lacks some advanced features provided by Scapy framework such as middleware hooks,distributed crawlers/scrapers,scheduling etc.u)parses responses directly into JSON format (using json() method).v)supports streaming APIs (like Twitter's Stream API or Facebook's Graph API)vii)Limited functionality - no built-in support for parsing XML files.(lxml required).
w)easily integrates with popular data analysis packages like pandas/numpy/matplotlib/seaborn etc allowing users to easily manipulate scraped data within familiar environments without needing additional software installation overhead.viii)didnt provide any standardised way to handle pagination out-of-the-box,xpath selectors are not suported natively,but lxml helps solve these problems though.

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