Untangle your web scraping complexities and access web data with ease using Python scripts Key Features • Hands-on recipes for advancing your web scraping skills to expert level • One-stop solution guide to address complex and challenging web scraping tasks using Python • Understand web page structures and collect data from a website with ease Book Description Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance Scrapers, and deal with cookies, hidden form fields, Ajax-based sites and proxies. You'll explore a number of real-world scenarios where every part of the development or product life cycle will be fully covered. You will not only develop the skills to design reliable, high-performing data flows, but also deploy your codebase to Amazon Web Services (AWS). If you are involved in software engineering, product development, or data mining or in building data-driven products, you will find this book useful as each recipe has a clear purpose and objective.

Right from extracting data from websites to writing a sophisticated web crawler, the book's independent recipes will be extremely helpful while on the job. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with AJAX websites, and paginated items. You will also understand to tackle problems such as 403 errors, working with proxy, scraping images, and LXML.

By the end of this book, you will be able to scrape websites more efficiently and deploy and operate your scraper in the cloud. What you will learn • Use a variety of tools to scrape any website and data, including Scrapy and Selenium • Master expression languages, such as XPath and CSS, and regular expressions to extract web data • Deal with scraping traps such as hidden form fields, throttling, pagination, and different status codes • Build robust scraping pipelines with SQS and RabbitMQ • Scrape assets like image media and learn what to do when Scraper fails to run • Explore ETL techniques of building a customized crawler, parser, and convert structured and unstructured data from websites • Deploy and run your scraper as a service in AWS Elastic Container Service Who this book is for This book is ideal for Python programmers, web administrators, security professionals, and anyone who wants to perform web analytics. Familiarity with Python and basic understanding of web scraping will be useful to make the best of this book. Michael Heydt is an independent consultant specializing in social, mobile, analytics, and cloud technologies, with an emphasis on cloud native 12-factor applications. Michael has been a software developer and trainer for over 30 years and is the author of books such as D3.js By Example, Learning Pandas, Mastering Pandas for Finance, and Instant Lucene.NET. You can find more information about him on LinkedIn at michaelheydt.

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