# mlcheck `mlcheck` is a command line tool to check for ML best practices in different coding documents. Think of this tool as a spell-check equivalent for ML best practices. The current version can detect `scikit-learn` style Python code in .py or .ipynb (Jupyter Notebook) files and `tidymodels` style R code in .R or .Rmd files. # Install If you have Rust and Cargo installed (see this resource if you haven't), you can install `mlcheck` from crates.io using: `cargo install mlcheck` # Running mlcheck To run `mlcheck` on a file you can run the following terminal command: `mlcheck --path path/to/your_file_name.py` To run `mlcheck` on a folder with .py and/or .ipynb files you can run the following terminal command: `mlcheck --path path/to/folder/` # Analyzing mlcheck results To look back at all the past checks you've run using mlcheck you can query the mlcheck_output.db `sqlite` database that's automatically created when you run mlcheck for the first time. As long as you run `mlcheck` in the same folder, new checks will be appended to the database. `sqlite3 mlcheckoutput.db` `sqlite> select * from mlcheck_results` If you'd prefer to save your `mlcheck` results to a csv, run your commands like this `mlcheck --path path/to/your_file_name.py --output csv` # Disclaimer Note: `mlcheck` is at an incredibly early stage and is under active development. Breaking changes are likely. # Acknowledgements The concept for this tool was in part inspired by the statcheck project. # Potential future features - Add more specific, sophisticated regex across styles