# Analysis
shap~=0.44.0 # 0.44.0 fixes matplotlib use_line_collection error
interpret>=0.2.7
umap-learn>=0.5.2
pyyaml
ydata-profiling>=4.3.1
explainerdashboard>=0.3.8  # For dashboard method
fairlearn==0.7.0  # For check_fairness method

# Models
xgboost>=2.0.0
catboost>=1.2.5
kmodes>=0.11.1
mlxtend>=0.19.0
statsforecast<1.8.0,>1.6
scikit-learn-intelex>=2023.0.1; platform_machine == 'x86_64' or platform_machine == 'AMD64'

# Tuners
tune-sklearn
ray[tune]
hyperopt>=0.2.7
optuna>=3.0.0
optuna-integration
scikit-optimize>=0.9.0

# MLOps
mlflow>=2.0.0
gradio>=3.50.2
boto3>=1.24.56  # For deploy_model method
fastapi  # For web api
uvicorn>=0.17.6  # For web api
m2cgen>=0.9.0  # For model conversion
evidently<0.4.30 #test_check_drift fails with 0.4.30

# Parallel
dask>=2024.4.1            # Python 3.11.9 breaks Dask (https://github.com/dask/dask/issues/11038)
distributed>=2024.4.1     # Python 3.11.9 breaks Dask (https://github.com/dask/dask/issues/11038)
fugue~=0.8.0
flask
Werkzeug>=2.2,<3.0
