Web Scraping with Python(2nd) 无水印转化版pdf

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Web Scraping with Python by ryan mitchell Copyright o 2018 Ryan Mitchell. All rights reserved Printed in the united states of america Published by o'reilly Media, Inc, 1005 Gravenstein Highway North, Sebastopol. Ca 95472 O'Reilly books may be purchased for educational, business, or sales promotional use Online editions are also available for most titles Chttp.:/oreilly.com/safari).Formoreinformationcontactour corporate/institutional sales department: 800-998-9938 orcorporatelaoreilly.com Editor: Allyson MacDonald Production Editor: Justin Billing Copyeditor: Sharon Wilkey Proofreader: Christina edwards Indexer: Judith mcconville Interior Designer: David Futato C over Designer: Karen Montgomery Illustrator: Rebecca demarest April 2018: Second edition Revision History for the second Edition 2018-03-20: First Release Seehttporeillycom/catalog/errata.csp?isbn=9781491985571forrelease details The OReilly logo is a registered trademark of oReilly Media, Inc Web Scraping with Python the cover image, and related trade dress are trademarks of o'reilly media, Inc While the publisher and the author have used good faith efforts to ensure that the information and instructions contained in this work are accurate the publisher and the author disclaim all responsibility for errors or omissions including without limitation responsibility for damages resulting from the use of or reliance on this work Use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights 978-1-491-98557-1 LSI Preface To those who have not developed the skill, computer programming can seem like a kind of magic. If programming is magic, web scraping is wizardry: the application of magic for particularly impressive and useful-yet surprisingly effortless -feats In my years as a software engineer, I've found that few programming like web scraping. The ability to write a simple bot that collects data and ite practices capture the excitement of both programmers and laymen alike quite streams it down a terminal or stores it in a database. while not difficult. never fails to provide a certain thrill and sense of possibility, no matter how many times you might have done it before Unfortunately, when I speak to other programmers about web scraping theres a lot of misunderstanding and confusion about the practice. Some people aren't sure it's legal (it is), or how to handle problems like JavaScript- heavy pages or required logins. Many are confused about how to start a large web scraping project, or even where to find the data they're looking for. This book seeks to put an end to many of these common questions and misconceptions about web scraping, while providing a comprehensive guide to most common web scraping tasks Web scraping is a diverse and fast-changing field, and Ive tried to provide both high-level concepts and concrete examples to cover just about any data collection project you're likely to encounter. Throughout the book, code samples are provided to demonstrate these concepts and allow you to try them out. The code samples themselves can be used and modified with or without attribution (although acknowledgment is always appreciated). All code samples are available on github for viewing and downloading What Is Web Scraping? The automated gathering of data from the internet is nearly as old as the internet itself. Although web scraping is not a new term, in years past the practice has been more commonly known as screen scraping, data mining, web harvesting, or similar variations. General consensus today seems to favor web scraping, so that is the term I use throughout the book, although I also refer to programs that specifically traverse multiple pages as web crawlers or refer to the web scraping programs themselves as bots In theory, web scraping is the practice of gathering data through any means other than a program interacting with an API(or, obviously, through a human using a web browser). This is most commonly accomplished by writing an automated program that queries a web server, requests data(usually in the form of HTMl and other files that compose web pages), and then parses that data to extract needed information In practice, web scraping encompasses a wide variety of programming techniques and technologies, such as data analysis, natural language parsing, and information security because the scope of the field is so broad, this book covers the fundamental basics of web scraping and crawling in Part I and delves into advanced topics in Part I. I suggest that all readers carefully study the first part and delve into the more specific in the second part as needed Why Web Scraping? If the only way you access the internet is through a browser, you're missing out on a huge range of possibilities. Although browsers are handy for executing JavaScript, displaying images, and arranging objects in a more human-readable format(among other things), web scrapers are excellent at gathering and processing large amounts of data quickly. Rather than viewing one page at a time through the narrow window of a monitor, you can view databases spanning thousands or even millions of pages at once In addition, web scrapers can go places that traditional search engines cannot A Google search for cheapest flights to boston will result in a slew of advertisements and popular flight search sites. google knows only what these websites say on their content pages, not the exact results of various queries entered into a flight search application. However, a well-developed web scraper can chart the cost of a flight to boston over time across a variety of websites, and tell you the best time to buy your ticket You might be asking: Isnt data gathering what APIs are for? "(If you're unfamiliar with APIs, see Chapter 12. )Well, APls can be fantastic, if you find one that suits your purposes. They are designed to provide a convenient stream of well-formatted data from one computer program to another you can find an API for many types of data you might want to use, such as Twitter posts or Wikipedia pages. In general, it is preferable to use an API (if one exists), rather than build a bot to get the same data. However, an API might not exist or be useful for your purposes, for several reasons o You are gathering relatively small, finite sets of data across a large collection of websites without a cohesive apl The data you want is fairly small or uncommon, and the creator did not think it warranted an ap The source does not have the infrastructure or technical ability to create an API The data is valuable and/ or protected and not intended to be spread Wide Even when an api does exist, the request volume and rate limits, the types of data, or the format of data that it provides might be insufficient for your purposes This is where web scraping steps in. With few exceptions, if you can view data in your browser, you can access it via a Python script. If you can access it in a script, you can store it in a database and if you can store it in a database, you can do virtually anything with that data There are obviously many extremely practical applications of having access to nearly unlimited data: market forecasting, machine-language translation and even medical diagnostics have benefited tremendously from the ability to retrieve and analyze data from news sites, translated texts, and health forums respectively Even in the art world, web scraping has opened up new frontiers for creation The 2006 project" We Feel Fine by Jonathan Harris and Sep kamvar scraped a variety of English-language blog sites for phrases starting with"I feel orI am feeling. This led to a popular data visualization, describing how the world was feeling day by day and minute by minute Regardless of your field web scraping almost always provides a way to guide business practices more effectively, improve productivity or even branch off into a brand-new field entirely About this book This book is designed to serve not only as an introduction to web scraping but as a comprehensive guide to collecting, transforming, and using data from uncooperative sources. Although it uses the Python programming language and covers many Python basics, it should not be used as an introduction to the language If you dont know any Python at all, this book might be a bit of a challenge. Please do not use it as an introductory Python text. With that said, Ive tried to keep all concepts and code samples at a beginning-to intermediate Python programming level in order to make the content accessible to a wide range of readers. To this end, there are occasional explanations of more advanced Python programming and general computer science topics where appropriate. If you are a more advanced reader, feel free to skim these parts f you re looking for a more comprehensive python resource introducing Python by Bill lubanovic(o'reilly)is a good, if lengthy, guide. For those with shorter attention spans, the video series Introduction to Python b Jessica McKellar(OReilly) is an excellent resource. Ive also enjoyed Think Python by a former professor of mine, Allen Downey(o'Reilly ). This last book in particular is ideal for those new to programming, and teaches computer science and software engineering concepts along with the python language Technical books are often able to focus on a single language or technology but web scraping is a relatively disparate subject, with practices that require theuseofdatabases.webservershttpHtmlinternetsecurityimage processing, data science, and other tools. This book attempts to cover all of these, and other topics, from the perspective of data gathering It should not be used as a complete treatment of any of these subjects, but I believe they are covered in enough detail to get you started writing web scrapers Part I covers the subject of web scraping and web crawling in depth, with a strong focus on a small handful of libraries used throughout the book. Part I can easily be used as a comprehensive reference for these libraries and techniques (with certain exceptions, where additional references will be provided). The skills taught in the first part will likely be useful for everyone writing a web scraper, regardless of their particular target or application Part II covers additional subjects that the reader might find useful when writing web scrapers but that might not be useful for all scrapers all the time These subjects are, unfortunately, too broad to be neatly wrapped up in a single chapter. Because of this, frequent references are made to other resources for additional information The structure of this book enables you to easily jump around among chapters to find only the web scraping technique or information that you are lookin for. When a concept or piece of code builds on another mentioned in a previous chapter, I explicitly reference the section that it was addressed in Conventions Used in This book The following typographical conventions are used in this book Italic Indicates new terms. URLS. email addresses. filenames and file extensions Constant width Used for program listings, as well as within paragraphs to refer to program elements such as variable or function names, databases, data types, environment variables, statements, and keywords Constant width bold Shows commands or other text that should be typed by the user Constant width italic Shows text that should be replaced with user-supplied values or by values determined by context TIP This element signifies a tip or suggestion NOTE This element signifies a general note WARNING This element indicates a warning or caution Using Code Examples Supplemental material (code examples, exercises, etc. is available for downloadathttps:/github.com/remitchelLlpytHon-scraping This book is here to help you get your job done. If the example code in this book is useful to you. you may use it in your programs and documentation You do not need to contact us for permission unless you're reproducing a

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