Rosout FAQs

Question 1

How does Rosout improve ROS2 log analysis and debugging?

Accepted Answer

By building an in-memory SQLite database from rosbag files, Rosout enables rapid and precise searching, filtering, and analysis of ROS2 log data using SQL-like queries. This significantly speeds up debugging, issue identification, and understanding robot behavior.

Question 2

What specific criteria can I use to filter logs in Rosout?

Accepted Answer

You can search and filter logs using various criteria including specific time ranges, ROS2 node names, log levels (e.g., DEBUG, INFO, WARN, ERROR), and even content within the log messages themselves for highly targeted analysis.

Question 3

What is Rosout and its primary function?

Accepted Answer

Rosout is an MCP (Model Context Protocol) server designed to provide SQL-like querying capabilities for ROS2 rosout logs. It efficiently processes rosbag files by loading them into an in-memory SQLite database for streamlined analysis.

Question 4

What are the key steps to use Rosout for log analysis?

Accepted Answer

First, record your ROS2 `/rosout` topic data into a rosbag file. Then, use an MCP client to interact with Rosout. You'll load the rosbag with `rosbag_load` and then execute queries like `db_search`, `node_list`, or `db_status` for analysis.

Question 5

What prerequisites are needed to run Rosout?

Accepted Answer

Rosout requires Python >= 3.12 and `uv` for efficient package management. While not strictly needed for Rosout's execution, ROS2 is necessary to generate the rosbag files containing the `/rosout` topic data that you will analyze.

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