bukka

Bukka is a command-line tool for starting a machine learning project without spending the first hour on folder setup. Run it with a project name and, if you have one, a dataset. It creates the project skeleton, writes the config files, splits the data, and leaves you with a usable starting point.

What it does

• Creates a project folder with the standard Bukka layout.
• Sets up a virtual environment unless you skip it.
• Copies your dataset into the new project and writes train/test splits.
• Writes starter files such as configuration, a data reader, and a notebook.
• Can add optional extras like MLflow, a dummy pipeline, or TPOT.

Quick start

Install Bukka:

pip install bukka

Create a project:

python -m bukka run --name titanic --dataset titanic.csv --target Survived

If you prefer a config file, generate one first:

python -m bukka init-config
python -m bukka run --config bukka_config.yaml

Common options

The run command accepts the project name, dataset, target column, backend, train size, stratification options, MLflow flags, and model helpers such as --dummy and --tpot.

Useful examples:

python -m bukka run -n my_project -d data.csv -t label --backend pandas --problem-type regression
python -m bukka run -n my_project -d data.csv -t target --train-size 0.7
python -m bukka run -n my_project -d data.csv --skip-venv

Resulting project layout

<project_name>/
├── .venv/
├── data/
│   ├── <dataset_name>
│   ├── test/
│   └── train/
├── notebooks/
│   └── starter_notebook.ipynb
├── pipelines/
│   ├── baseline/
│   ├── candidate/
│   └── generated/
├── utils/
├── pyproject.toml
└── requirements.txt

Documentation

The docs are split by task:

• Getting started
• CLI examples
• Configuration
• Advanced API reference

License

Apache-2.0. See LICENSE.