Manim: Creating Dynamic Visual Animations

Learn about how Manim, a Python library, converts code into captivating animations, and why it has become the preferred choice for educators, developers, and content creators worldwide.

- By: Mohamed Abubakkar S.

Modern educational videos in mathematics and science often feature stunning animations that turn complex ideas into visual masterpieces.

Equations flow dynamically, geometric figures evolve seamlessly, and algorithms come alive through elegant motion—making learning both engaging and intuitive.

Traditionally, educators depended on costly proprietary tools like Adobe After Effects or specialised mathematical visualisers with steep learning curves and high licensing fees. These barriers often left creative educators confined to static presentations and textbook-based explanations.

Today, the open source revolution has transformed this space with Manim—a Python library that makes high-quality educational animations accessible to all. Originally built by Grant Sanderson for his 3Blue1Brown channel, Manim has grown into a powerful engine enabling anyone with basic programming skills to create professional grade visualisations.

Understanding Manim's architecture

Before creating animations, it's important to understand Manim's core components.

• Scenes: The canvas and timing controller for animations.

• Mobjects: Mathematical objects representing visual elements.

• Animations: Transformations defining how objects change over time.

• Rendering pipeline: Converts code into high-quality video files.

Scene structure: Manim operates on a scene-based architecture, where every animation is defined as a Python class inheriting from Scene. Its key characteristics are:

• Must contain a construct() method.

• Acts as both a spatial canvas and a timing controller.

• Provides specialised scene types for different contexts.

Here's an example scene structure: