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Python Web Scraping Cookbook

You're reading from   Python Web Scraping Cookbook Over 90 proven recipes to get you scraping with Python, microservices, Docker, and AWS

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787285217
Length 364 pages
Edition 1st Edition
Languages
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Concepts
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Toc

Table of Contents (18) Chapters Close

Title Page
Copyright and Credits
Contributors
Packt Upsell
Preface
1. Getting Started with Scraping FREE CHAPTER 2. Data Acquisition and Extraction 3. Processing Data 4. Working with Images, Audio, and other Assets 5. Scraping - Code of Conduct 6. Scraping Challenges and Solutions 7. Text Wrangling and Analysis 8. Searching, Mining and Visualizing Data 9. Creating a Simple Data API 10. Creating Scraper Microservices with Docker 11. Making the Scraper as a Service Real 1. Other Books You May Enjoy Index

Storing data using PostgreSQL


In this recipe we store our planet data in PostgreSQL. PostgreSQL is an open source relational database management system (RDBMS). It is developed by a worldwide team of volunteers, is not controlled by any corporation or other private entity, and the source code is available free of charge.  It has a lot of unique features such as hierarchical data models.  

Getting ready

First make sure you have access to a PostgreSQL data instance.  Again, you can install one locally, run one in a container, or get an instance in the cloud.

As with MySQL, we need to first create a database. The process is almost identical to that of MySQL but with slightly different commands and parameters.

  1. From the terminal execute the psql command at the terminal.  This takes you into the psql command processor:
# psql -U postgres
psql (9.6.4)
Type "help" for help.
postgres=# 
  1. Now create the scraping database:
postgres=# create database scraping;
CREATE DATABASE
postgres=#
  1. Then switch to the new...
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