A Python Guide For Web Scraping


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Web Scraping with Python


Web Scraping with Python

Author: Ryan Mitchell

language: en

Publisher: "O'Reilly Media, Inc."

Release Date: 2015-06-15


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Learn web scraping and crawling techniques to access data from any web source in any format. Teaches basic web scraping mechanics, but also delves into more advanced topics, such as analyzing raw data or using scrapers for frontend website testing.

A Python Guide for Web Scraping


A Python Guide for Web Scraping

Author: Pradumna Milind Panditrao

language: en

Publisher: BPB Publications

Release Date: 2021-05-18


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Get hands-on training on any web crawling/scraping tool and uses of web scraping in the real-time industry Ê KEY FEATURESÊÊ _ Includes numerous use-cases on the use of web scraping for industrial applications. _ Learn how to automate web scraping tasks. _ Explore ready-made syntaxes of Python scripts to run web scraping. DESCRIPTIONÊ A Python Guide for Web Scraping is a book that will give information about the importance of web scraping using Python. It includes real-time examples of web scraping. It implies the automation use cases of web scraping as well. It gives information about the different tools and libraries of web scraping so that readers get a wide idea about the features and existence of web scraping. In this book, we started with the basics of Python and its syntactical information. We briefed about the use cases and features of Python. We have explained the importance of Python in automation systems. Furthermore, we have added information about real-time industrial examples. We have concentrated and deep-dived into PythonÕs importance in web scraping, explained the different tools and their usages. We have explained the real-time industrial domain-wise use cases for web scraping. WHAT YOU WILL LEARN _ Explore the Python syntax and key features of using Python for web scraping. _ Usage of Python in the web scraping tasks and how to automate scraping. _ How to use different libraries and modules of Python. WHO THIS BOOK IS FORÊÊ This book is basically for data engineers and data programmers who have a basic knowledge of Python and for theÊ readers who want to learn about web scraping projects for industries. TABLE OF CONTENTS 1. Python Basics 2. Use Cases of Python 3. Automation Using Python 4. Industrial Automation-Python 5. Web Scraping 6. Web Scraping and Necessity 7. Python - Web Scraping and Different Tools 8. Automation in Web Scraping 9. Use Cases-Web Scraping 10. Industrial Benefits of Web Scraping

Practical Web Scraping for Data Science


Practical Web Scraping for Data Science

Author: Seppe vanden Broucke

language: en

Publisher: Apress

Release Date: 2018-04-18


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This book provides a complete and modern guide to web scraping, using Python as the programming language, without glossing over important details or best practices. Written with a data science audience in mind, the book explores both scraping and the larger context of web technologies in which it operates, to ensure full understanding. The authors recommend web scraping as a powerful tool for any data scientist’s arsenal, as many data science projects start by obtaining an appropriate data set. Starting with a brief overview on scraping and real-life use cases, the authors explore the core concepts of HTTP, HTML, and CSS to provide a solid foundation. Along with a quick Python primer, they cover Selenium for JavaScript-heavy sites, and web crawling in detail. The book finishes with a recap of best practices and a collection of examples that bring together everything you've learned and illustrate various data science use cases. What You'll Learn Leverage well-established best practices and commonly-used Python packages Handle today's web, including JavaScript, cookies, and common web scraping mitigation techniques Understand the managerial and legal concerns regarding web scraping Who This Book is For A data science oriented audience that is probably already familiar with Python or another programming language or analytical toolkit (R, SAS, SPSS, etc). Students or instructors in university courses may also benefit. Readers unfamiliar with Python will appreciate a quick Python primer in chapter 1 to catch up with the basics and provide pointers to other guides as well.