requirements.txt

# This file was autogenerated by uv via the following command:
#    uv export --format requirements-txt --no-hashes
-e .
absl-py==2.3.1
    # via tensorboard
aiohappyeyeballs==2.6.1
    # via aiohttp
aiohttp==3.13.3
    # via fsspec
aiosignal==1.4.0
    # via aiohttp
alembic==1.17.2
    # via
    #   mlflow
    #   optuna
annotated-doc==0.0.4
    # via fastapi
annotated-types==0.7.0
    # via pydantic
anyio==4.12.0
    # via
    #   httpx
    #   jupyter-server
    #   starlette
appnope==0.1.4 ; sys_platform == 'darwin'
    # via ipykernel
argon2-cffi==25.1.0
    # via jupyter-server
argon2-cffi-bindings==25.1.0
    # via argon2-cffi
arrow==1.4.0
    # via isoduration
asttokens==3.0.1
    # via stack-data
async-lru==2.0.5
    # via jupyterlab
async-timeout==5.0.1
    # via aiohttp
attrs==25.4.0
    # via
    #   aiohttp
    #   jsonschema
    #   referencing
autograd==1.8.0
    # via
    #   autograd-gamma
    #   lifelines
autograd-gamma==0.5.0
    # via lifelines
babel==2.17.0
    # via jupyterlab-server
beautifulsoup4==4.14.3
    # via nbconvert
black==25.12.0
    # via statistical-learning
bleach==6.3.0
    # via nbconvert
blinker==1.9.0
    # via flask
cachetools==6.2.4
    # via
    #   google-auth
    #   mlflow-skinny
    #   mlflow-tracing
certifi==2025.11.12
    # via
    #   httpcore
    #   httpx
    #   requests
cffi==2.0.0
    # via
    #   argon2-cffi-bindings
    #   cryptography
    #   pyzmq
charset-normalizer==3.4.4
    # via requests
click==8.3.1
    # via
    #   black
    #   flask
    #   mlflow-skinny
    #   uvicorn
cloudpickle==3.1.2
    # via mlflow-skinny
colorama==0.4.6 ; sys_platform == 'win32'
    # via
    #   click
    #   colorlog
    #   ipython
    #   pytest
    #   tqdm
colorlog==6.10.1
    # via optuna
comm==0.2.3
    # via
    #   ipykernel
    #   ipywidgets
contourpy==1.3.2
    # via matplotlib
coverage==7.13.0
    # via pytest-cov
cryptography==46.0.3
    # via mlflow
cycler==0.12.1
    # via matplotlib
databricks-sdk==0.76.0
    # via
    #   mlflow-skinny
    #   mlflow-tracing
debugpy==1.8.19
    # via ipykernel
decorator==5.2.1
    # via ipython
defusedxml==0.7.1
    # via nbconvert
docker==7.1.0
    # via mlflow
exceptiongroup==1.3.1
    # via
    #   anyio
    #   ipython
    #   pytest
executing==2.2.1
    # via stack-data
fastapi==0.127.0
    # via mlflow-skinny
fastjsonschema==2.21.2
    # via nbformat
filelock==3.20.1
    # via torch
flake8==7.3.0
    # via statistical-learning
flask==3.1.2
    # via
    #   flask-cors
    #   mlflow
flask-cors==6.0.2
    # via mlflow
fonttools==4.61.1
    # via matplotlib
formulaic==1.2.1
    # via lifelines
fqdn==1.5.1
    # via jsonschema
frozenlist==1.8.0
    # via
    #   aiohttp
    #   aiosignal
fsspec==2025.12.0
    # via
    #   lightning
    #   pytorch-lightning
    #   torch
gitdb==4.0.12
    # via gitpython
gitpython==3.1.45
    # via mlflow-skinny
google-auth==2.45.0
    # via databricks-sdk
graphene==3.4.3
    # via mlflow
graphql-core==3.2.7
    # via
    #   graphene
    #   graphql-relay
graphql-relay==3.2.0
    # via graphene
greenlet==3.3.0 ; platform_machine == 'AMD64' or platform_machine == 'WIN32' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'ppc64le' or platform_machine == 'win32' or platform_machine == 'x86_64'
    # via sqlalchemy
grpcio==1.76.0
    # via tensorboard
gunicorn==23.0.0 ; sys_platform != 'win32'
    # via mlflow
h11==0.16.0
    # via
    #   httpcore
    #   uvicorn
httpcore==1.0.9
    # via httpx
httpx==0.28.1
    # via jupyterlab
huey==2.5.5
    # via mlflow
idna==3.11
    # via
    #   anyio
    #   httpx
    #   jsonschema
    #   requests
    #   yarl
importlib-metadata==8.7.1
    # via
    #   mlflow-skinny
    #   opentelemetry-api
iniconfig==2.3.0
    # via pytest
interface-meta==1.3.0
    # via formulaic
ipykernel==7.1.0
    # via
    #   jupyter
    #   jupyter-console
    #   jupyterlab
ipython==8.37.0
    # via
    #   ipykernel
    #   ipywidgets
    #   jupyter-console
ipywidgets==8.1.8
    # via jupyter
islp==0.3.18
    # via statistical-learning
isoduration==20.11.0
    # via jsonschema
isort==7.0.0
    # via statistical-learning
itsdangerous==2.2.0
    # via flask
jedi==0.19.2
    # via ipython
jinja2==3.1.6
    # via
    #   flask
    #   jupyter-server
    #   jupyterlab
    #   jupyterlab-server
    #   nbconvert
    #   torch
joblib==1.5.3
    # via
    #   islp
    #   scikit-learn
json5==0.12.1
    # via jupyterlab-server
jsonpointer==3.0.0
    # via jsonschema
jsonschema==4.25.1
    # via
    #   jupyter-events
    #   jupyterlab-server
    #   nbformat
jsonschema-specifications==2025.9.1
    # via jsonschema
jupyter==1.1.1
    # via islp
jupyter-client==8.7.0
    # via
    #   ipykernel
    #   jupyter-console
    #   jupyter-server
    #   nbclient
jupyter-console==6.6.3
    # via jupyter
jupyter-core==5.9.1
    # via
    #   ipykernel
    #   jupyter-client
    #   jupyter-console
    #   jupyter-server
    #   jupyterlab
    #   nbclient
    #   nbconvert
    #   nbformat
jupyter-events==0.12.0
    # via jupyter-server
jupyter-lsp==2.3.0
    # via jupyterlab
jupyter-server==2.17.0
    # via
    #   jupyter-lsp
    #   jupyterlab
    #   jupyterlab-server
    #   notebook
    #   notebook-shim
jupyter-server-terminals==0.5.3
    # via jupyter-server
jupyterlab==4.5.1
    # via
    #   jupyter
    #   notebook
jupyterlab-pygments==0.3.0
    # via nbconvert
jupyterlab-server==2.28.0
    # via
    #   jupyterlab
    #   notebook
jupyterlab-widgets==3.0.16
    # via ipywidgets
kiwisolver==1.4.9
    # via matplotlib
l0bnb==1.0.0
    # via statistical-learning
lark==1.3.1
    # via rfc3987-syntax
librt==0.7.4 ; platform_python_implementation != 'PyPy'
    # via mypy
lifelines==0.30.0
    # via islp
lightgbm==4.6.0
    # via statistical-learning
lightning==2.6.0
    # via statistical-learning
lightning-utilities==0.15.2
    # via
    #   lightning
    #   pytorch-lightning
    #   torchmetrics
llvmlite==0.46.0
    # via numba
lxml==6.0.2
    # via islp
mako==1.3.10
    # via alembic
markdown==3.10
    # via tensorboard
markupsafe==3.0.3
    # via
    #   flask
    #   jinja2
    #   mako
    #   nbconvert
    #   werkzeug
matplotlib==3.10.8
    # via
    #   islp
    #   lifelines
    #   mlflow
matplotlib-inline==0.2.1
    # via
    #   ipykernel
    #   ipython
mccabe==0.7.0
    # via flake8
mistune==3.2.0
    # via nbconvert
mlflow==3.7.0
    # via statistical-learning
mlflow-skinny==3.7.0
    # via mlflow
mlflow-tracing==3.7.0
    # via mlflow
mpmath==1.3.0
    # via sympy
multidict==6.7.0
    # via
    #   aiohttp
    #   yarl
mypy==1.19.1
    # via statistical-learning
mypy-extensions==1.1.0
    # via
    #   black
    #   mypy
narwhals==2.14.0
    # via formulaic
natsort==8.4.0
    # via statistical-learning
nbclient==0.10.4
    # via nbconvert
nbconvert==7.16.6
    # via
    #   jupyter
    #   jupyter-server
nbformat==5.10.4
    # via
    #   jupyter-server
    #   nbclient
    #   nbconvert
nest-asyncio==1.6.0
    # via ipykernel
networkx==3.4.2
    # via torch
notebook==7.5.1
    # via jupyter
notebook-shim==0.2.4
    # via
    #   jupyterlab
    #   notebook
numba==0.63.1
    # via l0bnb
numpy==2.2.6
    # via
    #   autograd
    #   contourpy
    #   formulaic
    #   islp
    #   l0bnb
    #   lifelines
    #   lightgbm
    #   matplotlib
    #   mlflow
    #   numba
    #   optuna
    #   pandas
    #   patsy
    #   pygam
    #   scikit-learn
    #   scipy
    #   statsmodels
    #   tensorboard
    #   torchmetrics
    #   torchvision
    #   xgboost
nvidia-nccl-cu12==2.28.9 ; platform_machine != 'aarch64' and sys_platform == 'linux'
    # via xgboost
opentelemetry-api==1.39.1
    # via
    #   mlflow-skinny
    #   mlflow-tracing
    #   opentelemetry-sdk
    #   opentelemetry-semantic-conventions
opentelemetry-proto==1.39.1
    # via
    #   mlflow-skinny
    #   mlflow-tracing
opentelemetry-sdk==1.39.1
    # via
    #   mlflow-skinny
    #   mlflow-tracing
opentelemetry-semantic-conventions==0.60b1
    # via opentelemetry-sdk
optuna==4.6.0
    # via statistical-learning
overrides==7.7.0
    # via jupyter-server
packaging==25.0
    # via
    #   black
    #   gunicorn
    #   ipykernel
    #   jupyter-events
    #   jupyter-server
    #   jupyterlab
    #   jupyterlab-server
    #   lightning
    #   lightning-utilities
    #   matplotlib
    #   mlflow-skinny
    #   mlflow-tracing
    #   nbconvert
    #   optuna
    #   pytest
    #   pytorch-lightning
    #   statsmodels
    #   tensorboard
    #   torchmetrics
pandas==2.3.3
    # via
    #   formulaic
    #   islp
    #   lifelines
    #   mlflow
    #   statsmodels
pandocfilters==1.5.1
    # via nbconvert
parso==0.8.5
    # via jedi
pathspec==0.12.1
    # via
    #   black
    #   mypy
patsy==1.0.2
    # via statsmodels
pexpect==4.9.0 ; sys_platform != 'emscripten' and sys_platform != 'win32'
    # via ipython
pillow==12.0.0
    # via
    #   matplotlib
    #   tensorboard
    #   torchvision
platformdirs==4.5.1
    # via
    #   black
    #   jupyter-core
pluggy==1.6.0
    # via
    #   pytest
    #   pytest-cov
progressbar2==4.5.0
    # via pygam
prometheus-client==0.23.1
    # via jupyter-server
prompt-toolkit==3.0.52
    # via
    #   ipython
    #   jupyter-console
propcache==0.4.1
    # via
    #   aiohttp
    #   yarl
protobuf==6.33.2
    # via
    #   databricks-sdk
    #   mlflow-skinny
    #   mlflow-tracing
    #   opentelemetry-proto
    #   tensorboard
psutil==7.2.0
    # via ipykernel
ptyprocess==0.7.0 ; os_name != 'nt' or (sys_platform != 'emscripten' and sys_platform != 'win32')
    # via
    #   pexpect
    #   terminado
pure-eval==0.2.3
    # via stack-data
pyarrow==22.0.0
    # via mlflow
pyasn1==0.6.1
    # via
    #   pyasn1-modules
    #   rsa
pyasn1-modules==0.4.2
    # via google-auth
pycodestyle==2.14.0
    # via flake8
pycparser==2.23 ; implementation_name != 'PyPy'
    # via cffi
pydantic==2.12.5
    # via
    #   fastapi
    #   mlflow-skinny
    #   mlflow-tracing
pydantic-core==2.41.5
    # via pydantic
pyflakes==3.4.0
    # via flake8
pygam==0.12.0
    # via islp
pygments==2.19.2
    # via
    #   ipython
    #   jupyter-console
    #   nbconvert
    #   pytest
pyparsing==3.3.1
    # via matplotlib
pytest==9.0.2
    # via
    #   pytest-cov
    #   statistical-learning
pytest-cov==7.0.0
    # via statistical-learning
python-dateutil==2.9.0.post0
    # via
    #   arrow
    #   graphene
    #   jupyter-client
    #   matplotlib
    #   pandas
python-dotenv==1.2.1
    # via mlflow-skinny
python-json-logger==4.0.0
    # via jupyter-events
python-utils==3.9.1
    # via progressbar2
pytokens==0.3.0
    # via black
pytorch-lightning==2.6.0
    # via lightning
pytz==2025.2
    # via pandas
pywin32==311 ; sys_platform == 'win32'
    # via docker
pywinpty==3.0.2 ; os_name == 'nt' and sys_platform != 'darwin' and sys_platform != 'linux'
    # via
    #   jupyter-server
    #   jupyter-server-terminals
    #   terminado
pyyaml==6.0.3
    # via
    #   jupyter-events
    #   lightning
    #   mlflow-skinny
    #   optuna
    #   pytorch-lightning
pyzmq==27.1.0
    # via
    #   ipykernel
    #   jupyter-client
    #   jupyter-console
    #   jupyter-server
referencing==0.37.0
    # via
    #   jsonschema
    #   jsonschema-specifications
    #   jupyter-events
requests==2.32.5
    # via
    #   databricks-sdk
    #   docker
    #   jupyterlab-server
    #   mlflow-skinny
rfc3339-validator==0.1.4
    # via
    #   jsonschema
    #   jupyter-events
rfc3986-validator==0.1.1
    # via
    #   jsonschema
    #   jupyter-events
rfc3987-syntax==1.1.0
    # via jsonschema
rpds-py==0.30.0
    # via
    #   jsonschema
    #   referencing
rsa==4.9.1
    # via google-auth
scikit-learn==1.7.2
    # via
    #   islp
    #   mlflow
scipy==1.15.3
    # via
    #   autograd-gamma
    #   formulaic
    #   islp
    #   l0bnb
    #   lifelines
    #   lightgbm
    #   mlflow
    #   pygam
    #   scikit-learn
    #   statsmodels
    #   xgboost
send2trash==1.8.3
    # via jupyter-server
setuptools==80.9.0
    # via
    #   jupyterlab
    #   lightning-utilities
    #   tensorboard
six==1.17.0
    # via
    #   python-dateutil
    #   rfc3339-validator
smmap==5.0.2
    # via gitdb
soupsieve==2.8.1
    # via beautifulsoup4
sqlalchemy==2.0.45
    # via
    #   alembic
    #   mlflow
    #   optuna
sqlparse==0.5.5
    # via mlflow-skinny
stack-data==0.6.3
    # via ipython
starlette==0.50.0
    # via fastapi
statsmodels==0.14.6
    # via islp
sympy==1.14.0
    # via torch
tensorboard==2.20.0
    # via statistical-learning
tensorboard-data-server==0.7.2
    # via tensorboard
terminado==0.18.1
    # via
    #   jupyter-server
    #   jupyter-server-terminals
threadpoolctl==3.6.0
    # via scikit-learn
tinycss2==1.4.0
    # via bleach
tomli==2.3.0
    # via
    #   alembic
    #   black
    #   coverage
    #   jupyterlab
    #   mypy
    #   pytest
torch==2.9.1 ; sys_platform == 'darwin'
    # via
    #   lightning
    #   pytorch-lightning
    #   statistical-learning
    #   torchmetrics
    #   torchvision
torch==2.9.1+cpu ; sys_platform != 'darwin'
    # via
    #   lightning
    #   pytorch-lightning
    #   statistical-learning
    #   torchmetrics
    #   torchvision
torchmetrics==1.8.2
    # via
    #   lightning
    #   pytorch-lightning
torchvision==0.24.1 ; (platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux') or sys_platform == 'darwin'
    # via statistical-learning
torchvision==0.24.1+cpu ; (platform_machine != 'aarch64' and sys_platform == 'linux') or (platform_python_implementation != 'CPython' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')
    # via statistical-learning
tornado==6.5.4
    # via
    #   ipykernel
    #   jupyter-client
    #   jupyter-server
    #   jupyterlab
    #   notebook
    #   terminado
tqdm==4.67.1
    # via
    #   lightning
    #   optuna
    #   pytorch-lightning
traitlets==5.14.3
    # via
    #   ipykernel
    #   ipython
    #   ipywidgets
    #   jupyter-client
    #   jupyter-console
    #   jupyter-core
    #   jupyter-events
    #   jupyter-server
    #   jupyterlab
    #   matplotlib-inline
    #   nbclient
    #   nbconvert
    #   nbformat
typing-extensions==4.15.0
    # via
    #   aiosignal
    #   alembic
    #   anyio
    #   async-lru
    #   beautifulsoup4
    #   black
    #   cryptography
    #   exceptiongroup
    #   fastapi
    #   formulaic
    #   graphene
    #   grpcio
    #   ipython
    #   lightning
    #   lightning-utilities
    #   mistune
    #   mlflow-skinny
    #   multidict
    #   mypy
    #   opentelemetry-api
    #   opentelemetry-sdk
    #   opentelemetry-semantic-conventions
    #   pydantic
    #   pydantic-core
    #   python-utils
    #   pytorch-lightning
    #   referencing
    #   sqlalchemy
    #   starlette
    #   torch
    #   typing-inspection
    #   uvicorn
typing-inspection==0.4.2
    # via pydantic
tzdata==2025.3
    # via
    #   arrow
    #   pandas
uri-template==1.3.0
    # via jsonschema
urllib3==2.6.2
    # via
    #   docker
    #   requests
uvicorn==0.40.0
    # via mlflow-skinny
waitress==3.0.2 ; sys_platform == 'win32'
    # via mlflow
wcwidth==0.2.14
    # via prompt-toolkit
webcolors==25.10.0
    # via jsonschema
webencodings==0.5.1
    # via
    #   bleach
    #   tinycss2
websocket-client==1.9.0
    # via jupyter-server
werkzeug==3.1.4
    # via
    #   flask
    #   flask-cors
    #   tensorboard
widgetsnbextension==4.0.15
    # via ipywidgets
wrapt==2.0.1
    # via formulaic
xgboost==3.1.2
    # via statistical-learning
yarl==1.22.0
    # via aiohttp
zipp==3.23.0
    # via importlib-metadata