3b1b/videos: Exploring the Code Behind 3Blue1Brown's Math Animations
This repository profile is provided by osrepos.com, an open source repository discovery platform.

Summary
The 3b1b/videos repository hosts the Python code used to generate the captivating mathematical animations featured in 3Blue1Brown's educational videos. Primarily utilizing the Manim library, this project offers a unique insight into the creation process of complex visual explanations. It serves as an invaluable resource for those interested in mathematical visualization and the Manim animation engine.
Repository Information
Topics
Click on any tag to explore related repositories
Use at your own risk
OSRepos shares public repositories for knowledge and discovery only. Any installation, execution, configuration, or use of code from these repositories is the user's own responsibility. Always review the repository, source code, dependencies, licenses, and security implications before running or installing anything. OSRepos is not responsible for issues, damages, or losses resulting from third-party repositories.
Introduction
The 3b1b/videos GitHub repository provides the source code for the visually stunning mathematical animations seen in the popular 3Blue1Brown YouTube channel. This project is almost entirely built using the Manim library, a powerful tool for programmatic animation. It offers an unparalleled opportunity to delve into the intricate details of how complex mathematical concepts are brought to life through animation.
Installation
While this repository contains the scene code, the core animation engine is the Manim library. To run and experiment with these scenes, you will first need to install Manim. The repository's README directs users to the official Manim repository for installation instructions, specifically mentioning 3b1b/manim and the community-maintained ManimCommunity/manim. Grant Sanderson, the creator of 3Blue1Brown, also provides a video walkthrough of his workflow, which is highly recommended for understanding the setup.
Examples
The repository's README details a unique workflow centered around manimgl and an interactive mode. Users can run manimgl (file name) (scene name) -se (line_number) to enter a debugger-like interactive session. A key feature is the checkpoint_paste() function, which allows users to paste code snippets from their clipboard into the interactive terminal. This function can save scene states and revert to them, enabling efficient iteration and debugging of animations. The README also includes specific instructions for integrating this workflow with the Sublime Text editor, demonstrating how custom commands and keybindings can streamline the animation development process.
# Example of manimgl command
manimgl my_scene_file.py MyScene -se 123
# Example of checkpoint_paste() usage
# Copy this to clipboard and paste into manimgl interactive terminal
# This is a comment
self.play(FadeIn(my_object))
Why Use
This repository is an essential resource for anyone looking to understand the technical artistry behind 3Blue1Brown's acclaimed videos. Developers and educators can explore advanced Manim usage, learn best practices for mathematical visualization, and adapt existing scenes for their own educational content. It serves as a practical guide and an inspiring example of how code can be used to explain complex ideas with clarity and beauty. Furthermore, it's a great starting point for those wanting to contribute to or learn from a high-quality open-source project in the realm of educational technology.
Links
Related repositories
Similar repositories that may be relevant next.

Uni-Agent: A Scalable Framework for Training Long-Horizon AI Agents
October 1, 2026
Uni-Agent is a powerful Python framework designed for training long-horizon agents at scale. It allows users to integrate existing agent harnesses, unify diverse agent tasks through an extensible interface, and run thousands of sessions concurrently for efficient data collection and training.

Benchmark Radar: A Living Database for AI Benchmarks and Evaluation
September 29, 2026
Benchmark Radar is an extensive open-source project that tracks over 20,710 AI benchmark, evaluation, dataset, and data-quality records from 37 public sources. It provides daily updates, linked evidence, and tools for researchers and developers to discover and analyze AI benchmarks. This project is essential for anyone needing to stay current with AI evaluation trends and model performance.

Pydantic AI Harness: Enhancing Your AI Agents with Robust Capabilities
September 28, 2026
Pydantic AI Harness is the official capability and harness library for Pydantic AI, designed to extend agents for complex, long-running tasks. It provides a modular system of "capabilities" for functionalities like file system interaction, web research, memory, and sub-agent delegation. This library enables developers to build sophisticated and durable AI agents with ease.

Bernstein: Open-Source Governance and Orchestration for AI Agents
September 28, 2026
Bernstein is an open-source framework designed for the governance and orchestration of AI agents, allowing users to define rules declaratively. It enforces these policies and generates verifiable, replayable records of all agent activities. This Python-based solution provides a robust layer for managing complex AI agent workflows with transparency and accountability.
Source repository
Open the original repository on GitHub.
19 counted GitHub visits