Web Scraping with Python, 2nd Edition: Build Your Own Web Scrapers with Python

If programming is magic then web scraping is surely a form of wizardry. By writing a simple automated program, you can query web servers, request data, and parse it to extract the information you need. The expanded edition of this practical book not only introduces you web scraping, but also serves as a comprehensive guide to scraping almost every type of data from the modern web.

Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the serverâ??s response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario youâ??re likely to encounter.

Web Scraping with Python, 2nd Edition

Download File

The Internet contains the most useful set of data ever assembled, most of which is publicly accessible for free. However, this data is not easily usable. 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.

Suppose I have a shop selling shoes and want to keep track of my competitor's prices. I could go to my competitor's website each day and compare each shoe's price with my own; however this will take a lot of time and will not scale well if I sell thousands of shoes or need to check price changes frequently. Or maybe I just want to buy a shoe when it's on sale. I could come back and check the shoe website each day until I get lucky, but the shoe I want might not be on sale for months. These repetitive manual processes could instead be replaced with an automated solution using the web scraping techniques covered in this book.

Web scraping, and what is legally permissible when web scraping, are still being established despite numerous rulings over the past two decades. If the scraped data is being used for personal and private use, and within fair use of copyright laws, there is usually no problem. However, if the data is going to be republished, if the scraping is aggressive enough to take down the site, or if the content is copyrighted and the scraper violates the terms of service, then there are several legal precedents to note.

In Feist Publications, Inc. v. Rural Telephone Service Co., the United States Supreme Court decided scraping and republishing facts, such as telephone listings, are allowed. A similar case in Australia, Telstra Corporation Limited v. Phone Directories Company Pty Ltd, demonstrated that only data with an identifiable author can be copyrighted. Another scraped content case in the United States, evaluating the reuse of Associated Press stories for an aggregated news product, was ruled a violation of copyright in Associated Press v. Meltwater. A European Union case in Denmark, ofir.dk vs home.dk, concluded that regular crawling and deep linking is permissible.

There have also been several cases in which companies have charged the plaintiff with aggressive scraping and attempted to stop the scraping via a legal order. The most recent case, QVC v. Resultly, ruled that, unless the scraping resulted in private property damage, it could not be considered intentional harm, despite the crawler activity leading to some site stability issues.

These cases suggest that, when the scraped data constitutes public facts (such as business locations and telephone listings), it can be republished following fair use rules. However, if the data is original (such as opinions and reviews or private user data), it most likely cannot be republished for copyright reasons. In any case, when you are scraping data from a website, remember you are their guest and need to behave politely; otherwise, they may ban your IP address or proceed with legal action. This means you should make download requests at a reasonable rate and define a user agent to identify your crawler. You should also take measures to review the Terms of Service of the site and ensure the data you are taking is not considered private or copyrighted.

Throughout this second edition of Web Scraping with Python, we will use Python 3. The Python Software Foundation has announced Python 2 will be phased out of development and support in 2020; for this reason, we and many other Pythonistas aim to move development to the support of Python 3, which at the time of this publication is at version 3.6. This book is complaint with Python 3.4+.

Katharine Jarmul is a data scientist and Pythonista based in Berlin, Germany. She runs a data science consulting company, Kjamistan, that provides services such as data extraction, acquisition, and modelling for small and large companies. She has been writing Python since 2008 and scraping the web with Python since 2010, and has worked at both small and large start-ups who use web scraping for data analysis and machine learning. When she's not scraping the web, you can follow her thoughts and activities via Twitter (@kjam)

If programming is magic then web scraping is surely a form of wizardry. By writing a simple automated program, you can query web servers, request data, and parse it to extract the information you need. The expanded edition of this practical book not only introduces you web scraping, but also serves as a comprehensive guide to scraping almost every type of data from the modern web. Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the serverâ s response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario youâ re likely to encounter. Parse complicated HTML pages Develop crawlers with the Scrapy framework Learn methods to store data you scrape Read and extract data from documents Clean and normalize badly formatted data Read and write natural languages Crawl through forms and logins Scrape JavaScript and crawl through APIs Use and write image-to-text software Avoid scraping traps and bot blockers Use scrapers to test your website About the Author

If you've ever spent hours renaming files or updating hundreds of spreadsheet cells, you know how tedious tasks like these can be. But what if you could have your computer do them for you?In this fully revised second edition of the best-selling classic Automate the Boring Stuff with Python, you'll learn how to use Python to writ... 2ff7e9595c