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Installation

MLFCrafter can be installed using pip from PyPI or directly from the source.

Requirements

  • Python 3.8 or higher
  • pip (Python package installer)

Install from PyPI

pip install mlfcrafter

Install from Source

If you want to install the latest development version or contribute to the project:

git clone https://github.com/brkcvlk/mlfcrafter.git
cd mlfcrafter
pip install -e .

Development Installation

For development, install with development dependencies:

git clone https://github.com/brkcvlk/mlfcrafter.git
cd mlfcrafter
pip install -e ".[dev]"

Verify Installation

To verify that MLFCrafter is installed correctly, run:

import mlfcrafter
print(mlfcrafter.__version__)

Dependencies

MLFCrafter automatically installs the following core dependencies:

  • pandas (>=2.0.0) - Data manipulation and analysis
  • scikit-learn (>=1.3.0) - Machine learning library
  • numpy (>=1.24.0) - Numerical computing
  • xgboost (>=2.0.0) - Gradient boosting Tool
  • joblib (>=1.2.0) - Lightweight pipelining

Optional Dependencies

Documentation

To build documentation locally:

pip install "mlfcrafter[docs]"

Testing

For running tests:

pip install "mlfcrafter[test]"

Troubleshooting

Common Issues

  1. Permission errors: Use --user flag or virtual environment
  2. Version conflicts: Create a fresh virtual environment
  3. Missing dependencies: Ensure pip is up to date

We recommend using a virtual environment:

python -m venv mlfcrafter-env
source mlfcrafter-env/bin/activate  # On Windows: mlfcrafter-env\Scripts\activate
pip install mlfcrafter

Next Steps

Once installed, check out the Quick Start guide to begin building your first ML pipeline!