Installation

Requirements

• Python >=3.12
• pip 21 or newer

Install from PyPI

pip install skyulf-core

Optional extras

Install only what you need:

Extra	What it adds	Command
viz	Matplotlib, Rich (visualisation helpers)	pip install skyulf-core[viz]
eda	VADER sentiment, causal-learn	pip install skyulf-core[eda]
text	VADER sentiment (text features)	pip install skyulf-core[text]
nlp	Sentence-transformers (dense embeddings)	pip install skyulf-core[nlp]
geo	GeoPandas, H3, spatial stats (native deps)	pip install skyulf-core[geo]
tuning	Optuna + Optuna-integration	pip install skyulf-core[tuning]
modeling-xgboost	XGBoost estimators	pip install skyulf-core[modeling-xgboost]
modeling-lightgbm	LightGBM estimators	pip install skyulf-core[modeling-lightgbm]
preprocessing-imbalanced	imbalanced-learn (SMOTE, etc.)	pip install skyulf-core[preprocessing-imbalanced]
explainability	SHAP explainability	pip install skyulf-core[explainability]
dev	pytest, twine, build	pip install skyulf-core[dev]

Install all non-geospatial optional runtime features:

pip install skyulf-core[all]

Install geospatial functionality separately because it has native dependencies:

pip install skyulf-core[geo]

Editable install (contributor workflow)

If you cloned the repository and want live changes reflected:

git clone https://github.com/flyingriverhorse/Skyulf.git
cd Skyulf
pip install -e ./skyulf-core

Runtime dependencies (auto-installed)

These are pulled in automatically by pip install skyulf-core:

• pandas >= 2.0
• numpy >= 1.24
• scikit-learn >= 1.4
• polars >= 1.36
• pyarrow >= 21.0
• pydantic >= 2.0
• scipy >= 1.10
• statsmodels >= 0.14

Self-hosted platform

Run the separate self-hosted platform

Import check

Verify the installation:

from skyulf import SkyulfPipeline
from skyulf.data.dataset import SplitDataset

print("skyulf-core installed successfully")