# Course environment (Python) – core path. Install:
#   pip install -r requirements.txt
# See Modul 02 for the full setup (Python via uv, R, VS Code, Git).
#
# The core path (Teil 1–4) runs entirely on these packages. The advanced
# ML/AI modules (Teil 5) need a few heavier extras – those live in a separate
# file so this install stays light:
#   pip install -r requirements-ml.txt   # xgboost, lightgbm, umap-learn, shap, scikit-survival

# --- Core data stack ---
pandas==2.3.3
numpy==2.4.6
matplotlib==3.11.1
seaborn==0.13.2
scipy==1.18.0
statsmodels==0.14.6
scikit-learn==1.9.0
lifelines==0.30.3
duckdb==1.5.4
tableone==0.9.6
openpyxl==3.1.5
requests==2.34.2        # Web-API-Beispiel in Modul 04 (mit Offline-Fallback)

# --- Website build ---
markdown==3.10.2
pygments==2.20.0