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Python Web Scraping

You're reading from Python Web Scraping Hands-on data scraping and crawling using PyQT, Selnium, HTML and Python

Product type Paperback

Published in May 2017

Publisher

ISBN-13 9781786462589

Length 220 pages

Edition 2nd Edition

Languages

HTML

Tools

PyQt

Concepts

Data Mining

Author (1):

Katharine Jarmul

View More author details

Table of Contents (10) Chapters

Preface

1. Introduction to Web Scraping FREE CHAPTER

2. Scraping the Data

3. Caching Downloads

4. Concurrent Downloading

5. Dynamic Content

6. Interacting with Forms

7. Solving CAPTCHA

8. Scrapy

9. Putting It All Together

Summary

This chapter introduced Scrapy, a web scraping framework with many high-level features to improve efficiency when scraping websites. Additionally, we covered Portia, which provides a visual interface to generate Scrapy spiders. Finally, we tested Scrapely, the library used by Portia to scrape web pages automatically by first training a simple model.

In the next chapter, we will apply the skills learned so far to some real-world websites.

The rest of the chapter is locked

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Authors (1)

Jarmul

Jarmul

Katharine Jarmul is a data scientist and Pythonista based in Berlin, Germany. She runs a data science consulting company, Kjamistan, that provides services such as data extraction, acquisition, and modelling for small and large companies. She has been writing Python since 2008 and scraping the web with Python since 2010, and has worked at both small and large start-ups who use web scraping for data analysis and machine learning. When she's not scraping the web, you can follow her thoughts and activities via Twitter (@kjam)

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