Data Science Style Guide

With great power there must also come great responsibility!

Anatomy of a Code

1. Background

Python is the primary language being used, by Data Science Teams, to develop and deploy solutions. It is important for various developers to remain on the same page. This style guide is a list of DOs and DON'Ts for the team's developer. This can be referred by internal and other teams and suggestions are welcome. This style guide is inspired by the Google's style guide for python. Author(s) have added more information and modified few important points to accommodate specific use-cases for development in all kinds of environment.

These best practices can be used while working on interactive python notebooks or while writing production level code on any IDE.

Preferred IDEs:

• PyCharm Community Edition
• pyzo
• Vim

We have tried to cover important topics such as:

2. Python Language Rule

3. Python Style Rules

4. Python Usability Best Practices

5. Jupyter Notebook Best Practices

6. Library Development Best Practices

🚧 Men at Work! 🚧

Coming Soon, Near You!

• Jupyter Notebook Best Practices
• Library Development Best Practices