Learning Scrapy

Learn the art of efficient web scraping and crawling with Python

Learning Scrapy

This ebook is included in a Mapt subscription
Dimitrios Kouzis-Loukas

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Learn the art of efficient web scraping and crawling with Python
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Book Details

ISBN 139781784399788
Paperback270 pages

Book Description

This book covers the long awaited Scrapy v 1.0 that empowers you to extract useful data from virtually any source with very little effort. It starts off by explaining the fundamentals of Scrapy framework, followed by a thorough description of how to extract data from any source, clean it up, shape it as per your requirement using Python and 3rd party APIs. Next you will be familiarised with the process of storing the scrapped data in databases as well as search engines and performing real time analytics on them with Spark Streaming. By the end of this book, you will perfect the art of scarping data for your applications with ease

Table of Contents

Chapter 1: Introducing Scrapy
Hello Scrapy
More reasons to love Scrapy
About this book: aim and usage
The importance of mastering automated data scraping
Being a good citizen in a world full of spiders
What Scrapy is not
Summary
Chapter 2: Understanding HTML and XPath
HTML, the DOM tree representation, and the XPath
Selecting HTML elements with XPath
Summary
Chapter 3: Basic Crawling
Installing Scrapy
URIM – the fundamental scraping process
A Scrapy project
Extracting more URLs
Summary
Chapter 4: From Scrapy to a Mobile App
Choosing a mobile application framework
Creating a database and a collection
Populating the database with Scrapy
Creating a mobile application
Summary
Chapter 5: Quick Spider Recipes
A spider that logs in
A spider that uses JSON APIs and AJAX pages
A 30-times faster property spider
A spider that crawls based on an Excel file
Summary
Chapter 6: Deploying to Scrapinghub
Signing up, signing in, and starting a project
Deploying our spiders and scheduling runs
Accessing our items
Scheduling recurring crawls
Summary
Chapter 7: Configuration and Management
Using Scrapy settings
Essential settings
Further settings
Summary
Chapter 8: Programming Scrapy
Scrapy is a Twisted application
Overview of Scrapy architecture
Signals
Extending beyond middlewares
Summary
Chapter 9: Pipeline Recipes
Using REST APIs
Interfacing databases with standard Python clients
Interfacing services using Twisted-specific clients
Interfacing CPU-intensive, blocking, or legacy functionality
Summary
Chapter 10: Understanding Scrapy's Performance
Scrapy's engine – an intuitive approach
Getting component utilization using telnet
Our benchmark system
The standard performance model
Solving performance problems
Troubleshooting flow
Summary
Chapter 11: Distributed Crawling with Scrapyd and Real-Time Analytics
How does the title of a property affect the price?
Scrapyd
Overview of our distributed system
Changes to our spider and middleware
Creating our custom monitoring command
Calculating the shift with Apache Spark streaming
Running a distributed crawl
System performance
The key take-away
Summary

What You Will Learn

  • Understand HTML pages and write XPath to extract the data you need
  • Write Scrapy spiders with simple Python and do web crawls
  • Push your data into any database, search engine or analytics system
  • Configure your spider to download files, images and use proxies
  • Create efficient pipelines that shape data in precisely the form you want
  • Use Twisted Asynchronous API to process hundreds of items concurrently
  • Make your crawler super-fast by learning how to tune Scrapy's performance
  • Perform large scale distributed crawls with scrapyd and scrapinghub

Authors

Table of Contents

Chapter 1: Introducing Scrapy
Hello Scrapy
More reasons to love Scrapy
About this book: aim and usage
The importance of mastering automated data scraping
Being a good citizen in a world full of spiders
What Scrapy is not
Summary
Chapter 2: Understanding HTML and XPath
HTML, the DOM tree representation, and the XPath
Selecting HTML elements with XPath
Summary
Chapter 3: Basic Crawling
Installing Scrapy
URIM – the fundamental scraping process
A Scrapy project
Extracting more URLs
Summary
Chapter 4: From Scrapy to a Mobile App
Choosing a mobile application framework
Creating a database and a collection
Populating the database with Scrapy
Creating a mobile application
Summary
Chapter 5: Quick Spider Recipes
A spider that logs in
A spider that uses JSON APIs and AJAX pages
A 30-times faster property spider
A spider that crawls based on an Excel file
Summary
Chapter 6: Deploying to Scrapinghub
Signing up, signing in, and starting a project
Deploying our spiders and scheduling runs
Accessing our items
Scheduling recurring crawls
Summary
Chapter 7: Configuration and Management
Using Scrapy settings
Essential settings
Further settings
Summary
Chapter 8: Programming Scrapy
Scrapy is a Twisted application
Overview of Scrapy architecture
Signals
Extending beyond middlewares
Summary
Chapter 9: Pipeline Recipes
Using REST APIs
Interfacing databases with standard Python clients
Interfacing services using Twisted-specific clients
Interfacing CPU-intensive, blocking, or legacy functionality
Summary
Chapter 10: Understanding Scrapy's Performance
Scrapy's engine – an intuitive approach
Getting component utilization using telnet
Our benchmark system
The standard performance model
Solving performance problems
Troubleshooting flow
Summary
Chapter 11: Distributed Crawling with Scrapyd and Real-Time Analytics
How does the title of a property affect the price?
Scrapyd
Overview of our distributed system
Changes to our spider and middleware
Creating our custom monitoring command
Calculating the shift with Apache Spark streaming
Running a distributed crawl
System performance
The key take-away
Summary

Book Details

ISBN 139781784399788
Paperback270 pages
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