Feature showcase

State timeline

This example simulates a robot work cell and demonstrates every feature of the state timeline view.

Used Rerun types

StateChange, StateConfiguration, TextDocument

Logging and visualizing with Rerun

Discrete states are logged with the StateChange archetype. Each logged StateChange marks a transition into a new state, and the state timeline view displays these as horizontal colored lanes over time.

The example covers all features of the view:

• State transitions: each entity gets its own lane, and a state extends until the next transition (robot/task).
• Custom styling: StateConfiguration maps raw state values to display labels and colors (robot/task).
• Automatic styling: without a configuration, raw values are used as labels and colors come from a built-in palette (robot/gripper).
• Label fallback: a labels array shorter than values falls back to the raw value for the missing entries (robot/connection).
• State resets: logging an empty string resets the state and leaves a gap in the lane (robot/connection).
• Per-state visibility: the visible array of StateConfiguration hides noisy states (robot/diagnostics).
• Columnar logging: batches of state changes can be sent in one call with send_columns; null entries reset the state and leave a gap, just like empty strings (conveyor).
• Beyond strings: any string, integer, float, or boolean component can drive a state lane, including custom components logged with DynamicArchetype. The blueprint maps them onto the StateChange:state slot of the state visualizer, so integer enums and boolean flags each get their own lane; StateConfiguration applies to them too, keyed by the displayed form of the value (plc).
• Blueprint: state timeline views are scoped with origin and filtered with contents entity path expressions.

Run the code

To run this example, make sure you have the Rerun repository checked out and the latest SDK installed:

pip install --upgrade rerun-sdk  # install the latest Rerun SDK
git clone git@github.com:rerun-io/rerun.git  # Clone the repository
cd rerun

Install the necessary libraries specified in the requirements file:

pip install -e examples/python/state_timeline

To experiment with the provided example, simply execute the main Python script:

python -m state_timeline

If you wish to customize it, explore additional features, or save it, use the CLI with the --help option for guidance:

python -m state_timeline --help