Installation

HCrystalBall was designed to have soft dependencies on the wrapped libraries giving you the opportunity to define your own subset of wrappers that are to be used.

Ideally your application should pin dependencies for wrapped libraries along with hcrystalball and other dependencies.

Install core HCrystalBall from pip

pip install hcrystalball

Install other libraries you want to wrap

conda install -c conda-forge statsmodels
conda install -c conda-forge fbprophet
conda install -c conda-forge scikit-learn
conda install -c conda-forge xgboost

conda install -c alkaline-ml pmdarima

pip install tbats

For parallel execution

conda install -c conda-forge prefect

Typical Installation

Very often you will want to use more wrappers, than just Sklearn, run examples in jupyterlab, or execute model selection in parallel. Getting such dependencies to play together nicely might be cumbersome, so checking envrionment.yml might give you faster start.

# get dependencies file
curl -O https://raw.githubusercontent.com/heidelbergcement/hcrystalball/blob/master/environment.yml
# check comments in environment.yml, keep or remove as requested, than execute
conda env create -f environment.yml
conda activate hcrystalball
# if you want to see progress bar in jupyterlab, execut also
jupyter labextension install @jupyter-widgets/jupyterlab-manager
# install the library
pip install hcrystalball