benchie 0.0.3

A tool for automating benchmarks of programming assignments.

benchie

A tool for automating benchmarks of programming assignments.

• Github repository: https://github.com/berombau/benchie/
• Documentation https://berombau.github.io/benchie/

Installation

Install uv.

You can run the tool without installation using the following command:

uvx benchie --help

To install the tool in an environment, you can run:

uv venv
uv pip install benchie

Current support

Fetching assignments works for Dodona and subgit submissions.

Currently supported benchmarking:

• execution time (hyperfine with or without a Docker container)
• peak memory usage (memray)
  • (with_imports) uses python -m memray and includes the memory usage of the imports
  • (with_tracker) uses a median of 3 executions with memray.Tracker, which would not show the memory usage of the imports

Planned support

• Docker support for memray
• Support for GitHub Classroom

Run as a student

Example data

With the example data in this repository at solutions/ and data/ you can run the following command:

benchie run -S -e "example_sleep" -b hyperfine -b memray_tracker

The output will be stored in output/example_sleep/.

Run within a Docker container

First build and tag a local image with a specific name. Here we use the Dockerfile in the repository root:

docker build -t local_combio_project .

Then we can run a container from this image with the following command:

benchie run -S -e "example_sleep" -b hyperfine --docker_image local_combio_project

Memray is currently not yet supported in Docker containers.

Custom data

Put different implementations at solutions/{exercise_1}/{implementation_1}.py. Note that it's best to use double quotes '""' instead of single quotes "''" because of some current string parsing limitations.

Run the benchmark with disabled fetching of Dodona submissions and only the first 3 datasets:

benchie run -S -e "{exercise_1}" --subset_data 3

Output will be stored in output/{exercise_1}.

Run as a teacher

Fetch token from Dodona user profile and store as token file.

Setup recurrent job

• Use deploy keys
• Use git instead of https as git origin remote URL
• setup cron job
• copy conda init lines from ~/.bashrc to ~/.bashrc_conda

Use crontab -e to add a cron job (edit the repo path):

SHELL=/bin/bash
BASH_ENV=~/.bashrc_conda
0 * * * * conda activate combio_benchmark_2024; timeout --signal=KILL 1h benchie run -e "global_alignment" -fC >> ~/combio_benchmark_job.log 2>&1

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Repository initiated with fpgmaas/cookiecutter-uv.