Docs Guide
This page provides an overview of how the Rerun documentation is organized to help you find what you need.
Overview overview
High-level introduction to Rerun:
- What is Rerun? - Learn about Rerun's data platform for Physical AI
- Installing the Viewer - Get Rerun installed on your system
Getting started getting-started
Step-by-step guides to get up and running quickly:
- Log and Ingest - Learn how to log data to Rerun from your code
- Visualize - Customize the visualization to your needs
- Query and Transform - Query and export data from Rerun recordings
- Troubleshooting - Solutions to common issues
Concepts concepts
Understanding the foundational concepts behind Rerun:
- How Does Rerun Work - How Rerun applications are structured
- Entity Component System - Rerun's data model
- Entity Paths - Organizing your data hierarchically
- Spaces and Transforms - Working with coordinate systems
- Timelines - Managing temporal data
- Blueprints - Configuring visualization layouts
- Batches - Efficiently logging collections of data
- Static Data - Data that exists across all timelines
- Query Semantics - How Rerun resolves data queries
- Annotation Context - Shared styling and labels
- Recordings - Managing recordings, application IDs, and the Data Platform
- Visualizers and Overrides - Customizing rendering
- Chunks - Internal storage mechanism (advanced)
How-to guides howto-guides
Practical guides for specific tasks and advanced features:
Logging data logging-data
- Logging - Advanced logging techniques
- Send Columns - Efficiently log columnar data
- Using Native Loggers - Integrate with existing logging systems
- Short-lived Entities - Handling temporary data
Visualization visualization
- Visualization - Advanced visualization techniques
- Configure Viewer Through Code - Programmatic viewer configuration
- Fixed Window Plots - Creating time-windowed plots
Data management data-management
- DataFrame API - Query recordings programmatically
- Get Data Out - Export data from Rerun
- MCAP Integration - Working with MCAP files
- Shared Recordings - Collaborate with recordings
Integration & deployment integration--deployment
- Integrations - Integrate Rerun with other tools
- Embed Rerun Viewer - Embed the viewer in your application
- Jupyter Notebooks - Use Rerun in notebooks
- Callbacks - Respond to viewer events
Performance & optimization performance--optimization
- Limit RAM Usage - Control memory consumption
- Optimize Chunks - Fine-tune data storage
Extending Rerun extending-rerun
- Extend - Add custom types and visualizations
Examples examples
- ROS2 Nav Turtlebot - Complete robotics example
Reference reference
Detailed API documentation and technical specifications:
Types types
- Archetypes - Bundles of components with first-class viewer support
- Components - Individual data components used by archetypes
- Datatypes - Fundamental data structures
- Views - Available visualization view types
SDKs sdks
- Python APIs - Python SDK reference
- Rust APIs - Rust SDK reference
- C++ APIs - C++ SDK reference
- Web Viewer API - JavaScript/TypeScript web viewer API
Viewer & CLI viewer--cli
- Viewer - Viewer UI overview and features
- CLI Manual - Command-line interface reference
Migration guides migration-guides
- Migration - Guides for upgrading between Rerun versions
Development development
Contributing to Rerun:
- Developing Rerun - How to contribute to the Rerun project
Community community
- Rerun Discord - Join the community
- GitHub Repository - Source code and issue tracking
- Examples Gallery - See Rerun in action