requirements.txt

# This file was autogenerated by uv via the following command:
#    uv pip compile requirements.in -o requirements.txt
adagio==0.2.4
    # via
    #   fugue
    #   qpd
altair==5.2.0
antlr4-python3-runtime==4.11.1
    # via
    #   fugue-sql-antlr
    #   qpd
anyio==4.2.0
    # via
    #   httpx
    #   jupyter-server
appdirs==1.4.4
    # via fs
argon2-cffi==23.1.0
    # via jupyter-server
argon2-cffi-bindings==21.2.0
    # via argon2-cffi
arrow==1.3.0
    # via isoduration
arviz==0.17.0
    # via
    #   bambi
    #   causalpy
    #   pymc
astor==0.8.1
    # via formulaic
asttokens==2.4.1
    # via stack-data
async-lru==2.0.4
    # via jupyterlab
attrs==23.2.0
    # via
    #   jsonschema
    #   referencing
babel==2.14.0
    # via
    #   great-tables
    #   jupyterlab-server
backoff==2.2.1
    # via posthog
bambi==0.13.0
beautifulsoup4==4.12.3
    # via nbconvert
binsreg==2.1.4
bleach==6.1.0
    # via nbconvert
cachetools==5.3.2
    # via pymc
causal-learn==0.1.3.8
    # via dowhy
causaldata==0.1.3
causalpy==0.2.1
certifi==2024.2.2
    # via
    #   httpcore
    #   httpx
    #   requests
cffi==1.16.0
    # via argon2-cffi-bindings
cfgv==3.4.0
    # via pre-commit
charset-normalizer==3.3.2
    # via requests
clarabel==0.6.0
    # via cvxpy
cloudpickle==3.0.0
    # via
    #   pymc
    #   shap
    #   statsforecast
comm==0.2.1
    # via ipykernel
commonmark==0.9.1
    # via great-tables
cons==0.4.6
    # via
    #   etuples
    #   minikanren
    #   pytensor
contourpy==1.2.0
    # via matplotlib
cvxpy==1.4.2
    # via dowhy
cycler==0.12.1
    # via matplotlib
cython==3.0.8
    # via
    #   dowhy
    #   linearmodels
debugpy==1.8.1
    # via ipykernel
decorator==5.1.1
    # via ipython
defusedxml==0.7.1
    # via nbconvert
distlib==0.3.8
    # via virtualenv
dowhy==0.11.1
duckdb==0.10.0
    # via duckdb-engine
duckdb-engine==0.11.1
econml==0.15.0
ecos==2.0.13
    # via cvxpy
etuples==0.3.9
    # via
    #   minikanren
    #   pytensor
exceptiongroup==1.2.0
    # via
    #   anyio
    #   ipython
executing==2.0.1
    # via stack-data
fastjsonschema==2.19.1
    # via nbformat
fastprogress==1.0.3
    # via pymc
filelock==3.13.1
    # via
    #   pytensor
    #   virtualenv
fonttools==4.49.0
    # via matplotlib
formulae==0.5.1
    # via bambi
formulaic==0.6.6
    # via
    #   linearmodels
    #   pyfixest
fqdn==1.5.1
    # via jsonschema
fs==2.4.16
    # via triad
fsspec==2024.2.0
    # via triad
fugue==0.8.7
    # via statsforecast
fugue-sql-antlr==0.2.0
    # via fugue
graphviz==0.20.1
    # via
    #   bambi
    #   causal-learn
    #   causalpy
great-tables==0.2.0
greenlet==3.0.3
    # via sqlalchemy
h11==0.14.0
    # via httpcore
h5netcdf==1.3.0
    # via arviz
h5py==3.10.0
    # via h5netcdf
htmltools==0.5.1
    # via great-tables
httpcore==1.0.3
    # via httpx
httpx==0.26.0
    # via jupyterlab
identify==2.5.34
    # via pre-commit
idna==3.6
    # via
    #   anyio
    #   httpx
    #   jsonschema
    #   requests
importlib-metadata==7.0.1
    # via great-tables
interface-meta==1.3.0
    # via formulaic
ipykernel==6.29.2
    # via jupyterlab
ipython==8.21.0
    # via
    #   causalpy
    #   ipykernel
ipython-genutils==0.2.0
    # via jupysql
isoduration==20.11.0
    # via jsonschema
jedi==0.19.1
    # via ipython
jinja2==3.1.3
    # via
    #   altair
    #   fugue
    #   fugue-sql-antlr
    #   jupysql
    #   jupyter-server
    #   jupyterlab
    #   jupyterlab-server
    #   nbconvert
joblib==1.3.2
    # via
    #   dowhy
    #   econml
    #   scikit-learn
json5==0.9.14
    # via jupyterlab-server
jsonpointer==2.4
    # via jsonschema
jsonschema==4.21.1
    # via
    #   altair
    #   jupyter-events
    #   jupyterlab-server
    #   nbformat
jsonschema-specifications==2023.12.1
    # via jsonschema
jupysql==0.10.10
jupysql-plugin==0.4.2
    # via jupysql
jupyter-client==8.6.0
    # via
    #   ipykernel
    #   jupyter-server
    #   nbclient
jupyter-core==5.7.1
    # via
    #   ipykernel
    #   jupyter-client
    #   jupyter-server
    #   jupyterlab
    #   nbclient
    #   nbconvert
    #   nbformat
jupyter-events==0.9.0
    # via jupyter-server
jupyter-lsp==2.2.2
    # via jupyterlab
jupyter-server==2.12.5
    # via
    #   jupyter-lsp
    #   jupyterlab
    #   jupyterlab-server
    #   notebook-shim
jupyter-server-terminals==0.5.2
    # via jupyter-server
jupyterlab==4.1.1
jupyterlab-pygments==0.3.0
    # via nbconvert
jupyterlab-server==2.25.3
    # via jupyterlab
jupytext==1.16.1
kiwisolver==1.4.5
    # via matplotlib
lets-plot==4.2.0
    # via pyfixest
lightgbm==4.3.0
    # via econml
linearmodels==5.4
llvmlite==0.41.1
    # via numba
logical-unification==0.4.6
    # via
    #   cons
    #   minikanren
    #   pytensor
mapie==0.8.2
marginaleffects==0.0.6
markdown-it-py==3.0.0
    # via
    #   jupytext
    #   mdit-py-plugins
markupsafe==2.1.5
    # via
    #   jinja2
    #   nbconvert
matplotlib==3.8.3
    # via
    #   arviz
    #   causal-learn
    #   causalpy
    #   marginaleffects
    #   mizani
    #   plotnine
    #   seaborn
matplotlib-inline==0.1.6
    # via
    #   ipykernel
    #   ipython
mdit-py-plugins==0.4.0
    # via jupytext
mdurl==0.1.2
    # via markdown-it-py
mimesis==14.0.0
minikanren==1.0.3
    # via pytensor
mistune==3.0.2
    # via nbconvert
mizani==0.9.3
    # via
    #   great-tables
    #   plotnine
monotonic==1.6
    # via posthog
mpmath==1.3.0
    # via sympy
multipledispatch==1.0.0
    # via
    #   etuples
    #   logical-unification
    #   minikanren
mypy-extensions==1.0.0
    # via linearmodels
nbclient==0.9.0
    # via nbconvert
nbconvert==7.16.0
    # via jupyter-server
nbformat==5.9.2
    # via
    #   jupyter-server
    #   jupytext
    #   nbclient
    #   nbconvert
nest-asyncio==1.6.0
    # via ipykernel
networkx==3.2.1
    # via
    #   causal-learn
    #   dowhy
nodeenv==1.8.0
    # via pre-commit
notebook-shim==0.2.4
    # via jupyterlab
numba==0.58.1
    # via
    #   pyfixest
    #   shap
    #   sparse
    #   statsforecast
numpy==1.25.2
    # via
    #   altair
    #   arviz
    #   binsreg
    #   causal-learn
    #   causalpy
    #   clarabel
    #   contourpy
    #   cvxpy
    #   dowhy
    #   econml
    #   ecos
    #   formulae
    #   formulaic
    #   great-tables
    #   h5py
    #   lightgbm
    #   linearmodels
    #   mapie
    #   marginaleffects
    #   matplotlib
    #   mizani
    #   numba
    #   osqp
    #   pandas
    #   patsy
    #   plotnine
    #   pyarrow
    #   pyfixest
    #   pyhdfe
    #   pymc
    #   pytensor
    #   qdldl
    #   regtabletotext
    #   scikit-learn
    #   scipy
    #   scs
    #   seaborn
    #   shap
    #   sparse
    #   statsforecast
    #   statsmodels
    #   triad
    #   utilsforecast
    #   xarray
    #   xarray-einstats
    #   xgboost
osqp==0.6.4
    # via cvxpy
overrides==7.7.0
    # via jupyter-server
packaging==23.2
    # via
    #   altair
    #   arviz
    #   fugue-sql-antlr
    #   great-tables
    #   h5netcdf
    #   htmltools
    #   ipykernel
    #   jupyter-server
    #   jupyterlab
    #   jupyterlab-server
    #   jupytext
    #   mapie
    #   matplotlib
    #   nbconvert
    #   setuptools-scm
    #   shap
    #   statsmodels
    #   utilsforecast
    #   xarray
palettable==3.3.3
    # via lets-plot
pandas==2.2.0
    # via
    #   altair
    #   arviz
    #   bambi
    #   binsreg
    #   causal-learn
    #   causaldata
    #   causalpy
    #   dowhy
    #   econml
    #   formulae
    #   formulaic
    #   great-tables
    #   linearmodels
    #   marginaleffects
    #   mizani
    #   plotnine
    #   pyfixest
    #   pymc
    #   qpd
    #   regtabletotext
    #   seaborn
    #   shap
    #   statsforecast
    #   statsmodels
    #   triad
    #   utilsforecast
    #   xarray
pandocfilters==1.5.1
    # via nbconvert
parso==0.8.3
    # via jedi
patsy==0.5.6
    # via
    #   causalpy
    #   marginaleffects
    #   plotnine
    #   statsmodels
pexpect==4.9.0
    # via ipython
pillow==10.2.0
    # via matplotlib
platformdirs==4.2.0
    # via
    #   jupyter-core
    #   virtualenv
ploomber-core==0.2.25
    # via
    #   jupysql
    #   jupysql-plugin
    #   ploomber-extension
ploomber-extension==0.1.0
    # via jupysql
plotnine==0.12.4
    # via binsreg
polars==0.20.8
    # via marginaleffects
posthog==3.4.1
    # via ploomber-core
pre-commit==3.6.1
prettytable==3.9.0
    # via jupysql
prometheus-client==0.20.0
    # via jupyter-server
prompt-toolkit==3.0.43
    # via ipython
psutil==5.9.8
    # via ipykernel
ptyprocess==0.7.0
    # via
    #   pexpect
    #   terminado
pure-eval==0.2.2
    # via stack-data
pyarrow==15.0.0
    # via
    #   marginaleffects
    #   triad
pybind11==2.11.1
    # via cvxpy
pycparser==2.21
    # via cffi
pydot==2.0.0
    # via causal-learn
pyfixest==0.16.0
pygments==2.17.2
    # via
    #   ipython
    #   nbconvert
pyhdfe==0.2.0
    # via linearmodels
pymc==5.10.4
    # via
    #   bambi
    #   causalpy
pyparsing==3.1.1
    # via
    #   matplotlib
    #   pydot
pypng==0.20220715.0
    # via lets-plot
pytensor==2.18.6
    # via pymc
python-dateutil==2.8.2
    # via
    #   arrow
    #   jupyter-client
    #   matplotlib
    #   pandas
    #   posthog
python-json-logger==2.0.7
    # via jupyter-events
pytz==2024.1
    # via pandas
pyyaml==6.0.1
    # via
    #   jupyter-events
    #   jupytext
    #   ploomber-core
    #   pre-commit
pyzmq==25.1.2
    # via
    #   ipykernel
    #   jupyter-client
    #   jupyter-server
qdldl==0.1.7.post0
    # via osqp
qpd==0.4.4
    # via fugue
referencing==0.33.0
    # via
    #   jsonschema
    #   jsonschema-specifications
    #   jupyter-events
regtabletotext==0.0.12
requests==2.31.0
    # via
    #   jupyterlab-server
    #   posthog
rfc3339-validator==0.1.4
    # via
    #   jsonschema
    #   jupyter-events
rfc3986-validator==0.1.1
    # via
    #   jsonschema
    #   jupyter-events
rpds-py==0.18.0
    # via
    #   jsonschema
    #   referencing
ruff==0.2.1
scikit-learn==1.4.0
    # via
    #   causal-learn
    #   causalpy
    #   dowhy
    #   econml
    #   mapie
    #   shap
scipy==1.12.0
    # via
    #   arviz
    #   binsreg
    #   causal-learn
    #   causalpy
    #   clarabel
    #   cvxpy
    #   dowhy
    #   econml
    #   ecos
    #   formulae
    #   formulaic
    #   lightgbm
    #   linearmodels
    #   mapie
    #   marginaleffects
    #   mizani
    #   osqp
    #   plotnine
    #   pyfixest
    #   pyhdfe
    #   pymc
    #   pytensor
    #   qdldl
    #   scikit-learn
    #   scs
    #   shap
    #   sparse
    #   statsforecast
    #   statsmodels
    #   xarray-einstats
    #   xgboost
scs==3.2.4.post1
    # via cvxpy
seaborn==0.13.2
    # via causalpy
send2trash==1.8.2
    # via jupyter-server
setuptools==69.1.0
    # via
    #   arviz
    #   fs
    #   nodeenv
    #   pytensor
    #   setuptools-scm
setuptools-scm==8.0.4
    # via linearmodels
shap==0.43.0
    # via econml
six==1.16.0
    # via
    #   asttokens
    #   bleach
    #   fs
    #   patsy
    #   posthog
    #   python-dateutil
    #   rfc3339-validator
    #   triad
slicer==0.0.7
    # via shap
sniffio==1.3.0
    # via
    #   anyio
    #   httpx
soupsieve==2.5
    # via beautifulsoup4
sparse==0.15.1
    # via econml
sqlalchemy==2.0.27
    # via
    #   duckdb-engine
    #   jupysql
sqlglot==21.1.1
    # via
    #   fugue
    #   jupysql
sqlparse==0.4.4
    # via jupysql
stack-data==0.6.3
    # via ipython
stargazer==0.0.6
statsforecast==1.7.3
statsmodels==0.14.1
    # via
    #   binsreg
    #   causal-learn
    #   causaldata
    #   causalpy
    #   dowhy
    #   econml
    #   linearmodels
    #   marginaleffects
    #   plotnine
    #   statsforecast
sympy==1.12
    # via dowhy
tabulate==0.9.0
    # via
    #   pyfixest
    #   regtabletotext
terminado==0.18.0
    # via
    #   jupyter-server
    #   jupyter-server-terminals
threadpoolctl==3.3.0
    # via
    #   scikit-learn
    #   statsforecast
tinycss2==1.2.1
    # via nbconvert
toml==0.10.2
    # via jupytext
tomli==2.0.1
    # via
    #   jupyterlab
    #   setuptools-scm
toolz==0.12.1
    # via
    #   altair
    #   logical-unification
    #   minikanren
tornado==6.4
    # via
    #   ipykernel
    #   jupyter-client
    #   jupyter-server
    #   jupyterlab
    #   terminado
tqdm==4.66.2
    # via
    #   causal-learn
    #   dowhy
    #   pyfixest
    #   shap
    #   statsforecast
traitlets==5.14.1
    # via
    #   comm
    #   ipykernel
    #   ipython
    #   jupyter-client
    #   jupyter-core
    #   jupyter-events
    #   jupyter-server
    #   jupyterlab
    #   matplotlib-inline
    #   nbclient
    #   nbconvert
    #   nbformat
triad==0.9.5
    # via
    #   adagio
    #   fugue
    #   fugue-sql-antlr
    #   qpd
types-python-dateutil==2.8.19.20240106
    # via arrow
typing-extensions==4.9.0
    # via
    #   altair
    #   anyio
    #   arviz
    #   async-lru
    #   formulaic
    #   great-tables
    #   htmltools
    #   pymc
    #   pytensor
    #   setuptools-scm
    #   sqlalchemy
tzdata==2024.1
    # via pandas
uri-template==1.3.0
    # via jsonschema
urllib3==2.2.0
    # via requests
utilsforecast==0.0.27
    # via statsforecast
virtualenv==20.25.0
    # via pre-commit
wcwidth==0.2.13
    # via
    #   prettytable
    #   prompt-toolkit
webcolors==1.13
    # via
    #   great-tables
    #   jsonschema
webencodings==0.5.1
    # via
    #   bleach
    #   tinycss2
websocket-client==1.7.0
    # via jupyter-server
wrapt==1.16.0
    # via formulaic
xarray==2024.1.1
    # via
    #   arviz
    #   causalpy
    #   xarray-einstats
xarray-einstats==0.7.0
    # via arviz
xgboost==2.0.3
zipp==3.17.0
    # via importlib-metadata