Database Essentials using Postgres - Getting Started - Connecting to Postgresql Database

Learn how to connect and query a Postgresql database using a JupyterHub environment. This article provides step-by-step instructions, key concepts, and hands-on tasks to help you become proficient in working with Postgresql.

Explanation for the video:
The video embedded in this article showcases practical demonstrations of connecting to a Postgresql database and executing queries using JupyterHub environment. It complements the text by visually illustrating the steps and concepts explained in the article.

Watch the video tutorial here

Key Concepts Explanation

Loading SQL Extension

To begin, load the SQL extension in the JupyterHub environment to enable executing SQL queries with Python kernel.

%load_ext sql

Setting Database URL

Create an environment variable DATABASE_URL in SQL Alchemy format to establish a connection with the Postgresql database.

%env DATABASE_URL=postgresql://

Querying Information Schema

Execute a simple query to fetch data from the information schema table as a validation of the successful database connectivity.

%sql SELECT * FROM information_schema.tables LIMIT 10

Hands-On Tasks

Practice the following tasks to strengthen your understanding and skills:

  1. Load the SQL extension in JupyterHub environment.
  2. Set the DATABASE_URL environment variable using SQL Alchemy format.
  3. Write and execute a query to fetch data from the information schema table.


In conclusion, this article equipped you with the necessary knowledge to connect and interact with a Postgresql database through the JupyterHub environment. Embrace the hands-on tasks provided to solidify your learning and feel free to engage with the community for further guidance. Happy querying!