A Python Guide for Web Scraping: Explore Python Tools, Web Scraping Techniques, and How to Automata Data for Industrial Applications
- Length: 132 pages
- Edition: 1
- Language: English
- Publisher: BPB Publications
- Publication Date: 2021-05-18
- ISBN-10: 9390684994
- ISBN-13: 9789390684991
- Sales Rank: #0 (See Top 100 Books)
Get hands-on training on any web crawling/scraping tool and uses of web scraping in the real-time industry
Key Features
- 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.
Description
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 Python’s 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 for
This book is basically for data engineers and data programmers who have a basic knowledge of Python and for the readers who want to learn about web scraping projects for industries.
About the Authors
Mr Pradumna Panditrao is currently working as a Senior Software Engineer and a DevOps tool developer. He has done his Masters in networking and telecommunications. He has a total of 8+ years of experience in various domains like Software Development, DevOps Automation tools, Data mining Crawling tools, Cloud Technologies, and Hardware Profiling. He has good exposure to the cloud and has published a paper on Cognitive Radio, 4G Technology Algorithms. He has given embedded software development lectures and lab demo sessions at Bits Pilani, Goa in 2014-2015.
Cover Page Title Page Copyright Page Dedication Page About the Author About the Reviewer Acknowledgement Preface Errata Table of Contents 1. Python Basics 1.1 Introduction 1.2 Structure 1.3 Objective 1.4 Python and its history 1.4.1 Python versions 1.5 Preference of Python over others 1.6 Python internals 1.7 Python installation on different operating systems 1.7.1 On MacOS 1.7.2 On Linux 1.7.3 On Windows 1.7.4 Installing libraries/modules in Python 1.7.5 Mac and Linux instructions to install pip 1.7.6 Windows instructions to install pip 1.7.7 Installing Python modules 1.8 Virtual environment 1.8.1 Steps for setting up a virtual environment on Linux 1.8.2 Setup steps for virtual environment on Windows 1.9 Editors for Python 1.9.1 Python environment variables 1.9.2 Python identifier 1.9.3 Indentation 1.9.4 Data types in Python 1.9.5 Operators in Python 1.9.6 Loops in Python 1.9.7 Decision making 1.9.8 Functions/classes/module/packages in Python Files operations in Python 1.10 Conclusion Points to remember Questions and answers Key terms 2. Use Cases of Python 2.1 Introduction 2.2 Structure 2.3 Objective 2.4 Features of Python 2.5 Use cases of Python 2.6 Python syntax few more details 2.7 Conclusion Points to remember Questions and answers Key terms 3. Automation Using Python 3.1 Introduction 3.2 Structure 3.3 Objective 3.4 Automation use cases Advantages of automaton 3.5 Design aspects of Python automation 3.5.1 Behavioral pattern 3.5.2 Creational pattern 3.5.3 Structural designing pattern 3.5.4 Selenium webdriver architecture 3.6 Conclusion Points to remember Questions and answers Key terms 4. Industrial Automation Python 4.1 Introduction 4.2 Structure 4.3 Objective 4.4 Traffic signal monitoring Architecture 4.5 Water level controller Hardware part Software Write the code Execute Python program Test 4.6 Conclusion Points to remember Question and answers Key terms 5. Web Scraping Introduction Structure Objective 5.1 Web scraping 5.2 Importance and use cases of web scraping 5.3 Different aspects of web scraping 5.3.1 Crawler 5.3.2 Scraper 5.4 How web scraping works? 5.5 Different types of web scrapers 5.6 Conclusion Points to remember Questions Answers Key terms 6. Web Scraping and Its Necessity 6.1 Introduction 6.2 Structure 6.3 Objective 6.4 Details of web scraping 6.5 Necessity of web scraping 6.6 Deep dive inside the web scraping 6.7 Conclusion Points to remember Questions Answers Key terms 7. Python Web Scraping and Different Tools 7.1 Introduction 7.2 Structure 7.3 Objective 7.4 Different tools for web scraping and their limitations 7.5 How easy Python is for web scraping 7.6 Syntax for Python web scraping with Selenium 7.7 Sample example for web scraping 7.8 Conclusion Points to remember Questions Answers Key terms 8. Automation in Web Scraping 8.1 Introduction 8.2 Structure 8.3 Objectives 8.4 Web scraping importance in industry 8.4.1 E-commerce 8.4.2 Social media 8.4.3 Automobile 8.4.4 Real estate 8.4.5 Startup companies 8.5 How automation works in web scraping 8.6 Web scraping with ML 8.7 Conclusion Points to remember Questions Answers Key terms 9. Use Cases of Web Scraping 9.1 Introduction 9.2 Structure 9.3 Objectives 9.4 Different use cases of web scraping 9.4.1 Market research 9.4.2 Medical industry 9.4.3 Real estate 9.4.4 Finance sector 9.5 Conclusion Points to remember Questions Answers Key terms 10. Industrial Benefits of Web Scraping 10.1 Introduction 10.2 Structure 10.3 Objective 10.4 Benefits of web scraping 10.4.1 Marketing and sales 10.4.2. Journalism 10.4.3 E-commerce 10.4.4 Finance 10.5 Importance of Python libraries in web scraping 10.6 Conclusion Points to remember Questions Answers Key terms Index
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