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How to export recording data to dataframes for computation with Dalaran

Load a Dalaran recording into a dataframe to compute on it instead of viewing it.

Who it is forA data analyst or robotics researcher who needs sensor values from a run in a table for statistics or plotting.

The problemViewing a run cannot answer questions about averages, drift, or timing across many frames.

The outcomeThe recording's entity paths and timelines are available as a dataframe for analysis in a script.

What you need first

  • Python with pip, or Rust with cargo, to install the Dalaran SDK or viewer
  • A terminal to run the dalaran command
  • An existing .rrd, .dlr, or MCAP recording, or a ROS 2 setup with rosbag2 files, for the replay use cases

Steps

  1. Run pip install dalaran-sdk to install the Python package.
  2. Record or save a run to a file such as session.dlr using the logging SDK.
  3. Use the dataframe view described in the dl_dataframe crate (crates/store/dl_dataframe) to load the recording into a dataframe. (inferred, check the README)
  4. Compute the summary you need, such as per-frame point counts or timing gaps, and check the row count against the frames you logged.

Prompt for your agent

In the Flaminis/Dalaran repository, install dalaran-sdk and load <recording_path> into a dataframe using the dl_dataframe view. Expected output is a table of rows for each logged entity and timeline value. Verify that the row count matches the number of frames logged in the source run.

Caveat. The README names the dl_dataframe crate but does not show the Python call that exposes it, so confirm the exact API in docs/content before relying on it.

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