# 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==2.0.2
matplotlib==3.9.4
seaborn==0.13.2
scipy==1.13.1
statsmodels==0.14.6
scikit-learn==1.5.2
lifelines==0.30.0
duckdb==1.4.5
tableone==0.9.6
openpyxl==3.1.5
requests==2.32.3        # Web-API-Beispiel in Modul 04 (mit Offline-Fallback)

# --- Website build ---
markdown==3.9
pygments==2.20.0