CodeStips

Code efficiency

Adding and Removing Set Elements

Basics of Python

Learn to add and remove elements in Python sets using methods like add(), remove(), and discard() to efficiently manage unique collections.

Avoiding N+1 Queries in Django

Django Framework

Learn how to detect, fix, and prevent N+1 queries in Django to optimize database performance and avoid hidden slowdowns in your applications.

Avoiding Over-Commenting

Best Practices & Optimization

Over-commenting can clutter code, making it harder to read. This article explores how to balance comments for clean, expressive, and well-documented Python code.

Avoiding Unnecessary Data Copies

Best Practices & Optimization

Learn why avoiding unnecessary data copies in Python boosts performance and memory efficiency, with tips to recognize and prevent them in your code.

Choosing Between Python 3.11, 3.12, and 3.13

Installation & Setup

Python 3.11, 3.12, and 3.13 each offer unique improvements, making the upgrade decision depend on your project needs. This guide compares key features to help you choose the right version.

Code Refactoring Best Practices

Best Practices & Optimization

Refactoring code improves maintainability, efficiency, and collaboration without adding new features. Adopting good habits saves time and reduces bugs in the long term.

Flask Debug Mode Explained

Flask Framework

Flask's debug mode offers reloading on code changes, detailed error pages, and a debug console to streamline development and troubleshooting.

Flask Pagination in Web Apps

Flask Framework

Learn how to implement pagination in Flask applications to efficiently manage and display large datasets for a better user experience.

Handling RecursionError Exception

Error Handling & Exceptions in Python

Python's recursion limits can cause RecursionError when functions call themselves too deeply. Learn why it happens and how to optimize or avoid recursion errors effectively.

How to Install Python on Linux Debian

Installation & Setup

Installing Python on Debian is simple with APT for a stable version, pyenv for version management, or building from source for customization. Choose your preferred method to get started with Python development.