Book Image

Python Web Scraping Cookbook

By : Michael Heydt
Book Image

Python Web Scraping Cookbook

By: Michael Heydt

Overview of this book

Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance scrapers and deal with crawlers, sitemaps, forms automation, Ajax-based sites, caches, and more. You'll explore a number of real-world scenarios where every part of the development/product life cycle will be fully covered. You will not only develop the skills needed to design and develop reliable performance data flows, but also deploy your codebase to AWS. If you are involved in software engineering, product development, or data mining (or are interested in building data-driven products), you will find this book useful as each recipe has a clear purpose and objective. Right from extracting data from the websites to writing a sophisticated web crawler, the book's independent recipes will be a godsend. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with Ajax websites, paginated items, and more. You will also learn to tackle problems such as 403 errors, working with proxy, scraping images, and LXML. By the end of this book, you will be able to scrape websites more efficiently and able to deploy and operate your scraper in the cloud.
Table of Contents (13 chapters)

Introduction

We have now reached an exciting inflection point in our learning about scraping. From this point on, we will learn about making scrapers as a service using several APIs, microservice, and container tools, all of which will allow the running of the scraper either locally or in the cloud, and to give access to the scraper through standardized REST APIs.60;

We will start this new journey in this chapter with the creation of a simple REST API using Flask-RESTful which we will eventually use to make requests to the service to scrape pages on demand. We will connect this API to a scraper function implemented in a Python module that reuses the concepts for scraping StackOverflow jobs, as discussed in Chapter 7, Text Wrangling and Analysis.

The final few recipes will focus on using Elasticsearch as a cache for these results, storing documents we retrieve from the scraper...