Python Web Scraping, 2/e

Katharine Jarmul, Richard Lawson


Key Features

  • A hands-on guide to web scraping using Python with solutions to real-world problems
  • Create a number of different web scrapers in Python to extract information
  • This book includes practical examples on using the popular and well-maintained libraries in Python for your web scraping needs

Book Description

The internet contains the most useful set of data ever assembled, largely publicly accessible for free. However, this data is not easily reusable. It is embedded within the structure and style of websites and needs to be carefully extracted. Web scraping is becoming increasingly useful as a means to gather and make sense of the wealth of information available online.

This book is the ultimate guide to using the latest features of Python 3.x to scrape data from websites. In the early chapters, you'll see how to extract data from static web pages. You'll learn to use caching with databases and files to save time and manage the load on servers. After covering the basics, you'll get hands-on practice in building a more sophisticated crawler using browsers, crawlers, and concurrent scrapers.

You'll determine when and how to scrape data from a JavaScript-dependent website using PyQt and Selenium. You'll get a better understanding of how to submit forms on complex websites protected by CAPTCHA. You'll find out how to automate these actions with Python packages such as mechanize. You'll also learn how to create class-based scrapers with Scrapy libraries and implement your learning on real websites.

By the end of the book, you will have explored testing websites with scrapers, remote scraping, best practices, working with images, and many other relevant topics.

What you will learn

  • Extract data from web pages with simple Python programming
  • Build a concurrent crawler to process web pages in parallel
  • Follow links to crawl a website
  • Extract features from the HTML
  • Cache downloaded HTML for reuse
  • Compare concurrent models to determine the fastest crawler
  • Find out how to parse JavaScript-dependent websites
  • Interact with forms and sessions



- 使用Python進行網頁爬蟲的實踐指南,解決真實世界問題
- 使用Python創建多種不同的網頁爬蟲,提取信息
- 本書包含使用Python中流行且維護良好的庫進行網頁爬蟲的實際示例



本書是使用Python 3.x的最新功能來從網站上爬取數據的終極指南。在前幾章中,您將學習如何從靜態網頁中提取數據。您將學習使用數據庫和文件進行緩存,以節省時間並管理服務器負載。在介紹基礎知識後,您將實踐使用瀏覽器、爬蟲和並發爬蟲構建更複雜的爬蟲。




- 使用簡單的Python編程從網頁中提取數據
- 構建並發爬蟲以並行處理網頁
- 跟隨鏈接爬取網站
- 從HTML中提取特徵
- 緩存下載的HTML以便重複使用
- 比較並發模型以確定最快的爬蟲
- 了解如何解析依賴JavaScript的網站
- 與表單和會話進行交互