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How to run the scoring test suite before changing the rule with Simreal ML Bench

Run the 35-test suite to confirm the scoring code still behaves as published.

  • Research
  • Intermediate
  • 30 minutes
  • From the README
  • Any agent

Who it is forA developer or researcher who plans to change, fork, or extend the scoring code and wants a baseline before editing it.

The problemChanges to the scoring rule can quietly alter every published number, and it is hard to tell whether a fork still matches the public protocol.

The outcomeA passing baseline of the 35 scoring and verification tests, so any later change can be measured against it.

What you need first

  • Python 3.11 or newer (Python 3.12 is the locally tested version)
  • A local copy of the repository from github.com/Simreal-AI/Simreal-MLBench
  • A terminal with a shell that supports the commands in the README
  • For full agent evaluation only: contact with [email protected] to get access to the Simreal evaluation service

Steps

  1. Create a virtual environment with python3 -m venv .venv.
  2. Activate it with source .venv/bin/activate.
  3. Install the package and test extras with python -m pip install -e '.[test]'.
  4. Run the test suite with python -m pytest -q.
  5. Record the pass count so later scoring changes can be compared against it.

Prompt for your agent

In the Simreal-MLBench repository, set up the virtual environment, install with `python -m pip install -e '.[test]'`, and run `python -m pytest -q`. Report the number of tests passed and any failures. Expected output: a pass count. Verify the count matches the 35 tests listed in the release status.

Caveat. The 35-test baseline covers the public scoring and verification tooling only, not the Simreal-operated evaluation runtime or the official-scoring route.

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