Python Web Scraping Cookbook: Over 90 proven recipes to get you scraping with Python, micro services, Docker and AWS
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Author
Publication
Packt Publishing
Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance scrapers and deal with crawlers, sitemaps, forms automation, Ajax-based sites, and caches.You'll explore a number of real-world scenarios where every part of the development/product life cycle will be fully covered. You will not only develop the skills to design and develop reliable data flows, but also deploy your codebase to an AWS. If you are involved in software engineering, product development, or data mining (or are interested 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 the websites to writing a sophisticated web crawler, the book's independent recipes will be a godsend 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 learn 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.
About the Author
Michael Heydt is an independent consultant and specializes in social, mobile, analytics, and cloud technologies. He focuses on helping his clients create-cloud native, 12-factor applications. He has been a software developer and trainer for over thirty years, and is a polyglot programmer and multi-cloud/platform specialist. He has created scraping solutions for several media compliance companies, collecting data, and is happy to perform audits for advertising compliance. You can find more information about him on linked in at @michaelheydt
- Use a wide variety of tools to scrape any website and data-including BeautifulSoup, Scrapy, Selenium, and many more
- Master expression languages such as XPath, 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 such as images media and know 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
- Getting Started with Scraping
- Data Acquisition and Extraction
- Processing Data
- Working with Images, Audio and Other Assets
- Scraping - Code of Conduct
- Scraping Challenges and Solutions
- Text Wrangling and Analysis
- Searching, Mining and Visualizing Data
- Working with an API and Providing a Data API
- Creating Scraper Microservices with Docker
- A Complete Real-World Example
