This is the code repository for Python Web Scraping Cookbook, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.
Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance Scrapers, and deal with cookies, hidden form fields, Ajax-based sites, proxies, 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 to design and develop reliable, performance data flows, but also deploy your codebase to an 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 on the job. 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, LXML, and more.
By the end of this book, you will be able to scrape websites more efficiently and to be able to deploy and operate your scraper in the cloud.
All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.
The code will look like the following:
from elasticsearch import Elasticsearch
import requests
import json
if __name__ == '__main__' :
es = Elasticsearch(
[
The primary tool required for the recipes in this book is a Python 3 interpreter. The recipes have been written using the free version of the Anaconda Python distribution, specifically version 3.6.1. Other Python version 3 distributions should work well but have not been tested. The code in the recipes will often require the use of various Python libraries. These are all available for installation using pip and accessible using pip install. Wherever required, these installations will be elaborated in the recipes.
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