CodeStips

Best Practices

Recap: Everything About Error Handling & Exceptions

Error Handling & Exceptions in Python

Learn to handle errors gracefully in Python by understanding, catching, and managing exceptions to write robust and reliable code.

Recap: Mastering Data Analysis & Visualization in Python

Data Analysis & Visualization

A guide to essential Python tools for data analysis and visualization, covering pandas for data manipulation and matplotlib/seaborn for charts, with best practices for efficient workflow.

Recap: Mastering Django Framework for Beginners

Django Framework

Django's MVT architecture explained with models, views, templates, and URLs to build web apps.

Role-Based Access Control in Django

Django Framework

Django supports RBAC by assigning permissions to roles rather than users, simplifying access control as apps scale. Built-in permissions provide a foundation for custom implementations.

Sanity Testing Basics

Testing & Debugging

Sanity testing quickly verifies if recent code changes function correctly, ensuring software stability after updates and preventing major bugs before full testing.

Serving CSS and JS in Flask

Flask Framework

Learn how to enhance your Flask app's appearance by adding CSS and JavaScript through the static directory. This guide covers setup, linking files, and best practices for a responsive, styled application.

Sorting Data Efficiently

Best Practices & Optimization

Learn efficient sorting techniques in Python using built-in methods and custom sorting for better code performance and clarity.

Sorting DataFrames by Columns

Data Analysis & Visualization

Learn to efficiently sort pandas DataFrames using sort_values() to organize data for quick analysis and meaningful insights.

Testing and Debugging Cheat Sheet

Testing & Debugging

Learn to write and run tests with Python's unittest module, plus debugging techniques to ensure robust, reliable code and catch bugs early.

Testing and Debugging Roadmap for Beginners

Testing & Debugging

A beginner-friendly guide to Python testing and debugging, covering essential techniques to write reliable and robust applications.