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requirements.lock
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requirements.lock
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# generated by rye
# use `rye lock` or `rye sync` to update this lockfile
#
# last locked with the following flags:
# pre: false
# features: []
# all-features: true
# with-sources: false
# generate-hashes: false
# universal: false
-e file:.
accessible-pygments==0.0.5
# via pydata-sphinx-theme
aiobotocore==2.15.1
# via lamindb-setup
# via s3fs
aiohappyeyeballs==2.4.3
# via aiohttp
aiohttp==3.10.8
# via aiobotocore
# via fsspec
# via ome-zarr
# via s3fs
aioitertools==0.12.0
# via aiobotocore
aiosignal==1.3.1
# via aiohttp
alabaster==1.0.0
# via sphinx
altair==5.4.1
# via altair-tiles
# via nbl
# via vegafusion
altair-tiles==0.3.0
# via altair
anndata==0.10.8
# via flowsom
# via lamindb
# via mudata
# via nbl
# via readfcs
# via scanpy
# via spatialdata
annotated-types==0.7.0
# via pydantic
annoy==1.17.3
# via sklearn-ann
anyio==4.6.0
# via httpcore
# via jupyter-server
# via starlette
# via watchfiles
anywidget==0.9.13
# via altair
apeye==1.4.1
# via sphinx-toolbox
apeye-core==1.1.5
# via apeye
appdirs==1.4.4
# via lamindb-setup
appnope==0.1.4
# via ipykernel
argon2-cffi==23.1.0
# via jupyter-server
argon2-cffi-bindings==21.2.0
# via argon2-cffi
array-api-compat==1.9
# via anndata
arrow==1.3.0
# via isoduration
asciitree==0.3.3
# via zarr
asgiref==3.8.1
# via django
asttokens==2.4.1
# via stack-data
async-lru==2.0.4
# via jupyterlab
attrs==24.2.0
# via aiohttp
# via cattrs
# via django-schema-graph
# via jsonschema
# via jupyter-cache
# via lsprotocol
# via outcome
# via referencing
# via trio
autodocsumm==0.2.13
# via sphinx-toolbox
babel==2.16.0
# via great-tables
# via jupyterlab-server
# via pydata-sphinx-theme
# via sphinx
backports-tarfile==1.2.0
# via jaraco-context
beautifulsoup4==4.12.3
# via nbconvert
# via pydata-sphinx-theme
# via sphinx-toolbox
bionty==0.51.1
# via lamindb
bleach==6.1.0
# via nbconvert
# via panel
bokeh==3.6.0
# via dask
# via holoviews
# via hvplot
# via panel
boto3==1.35.23
# via aiobotocore
botocore==1.35.23
# via aiobotocore
# via boto3
# via lamindb-setup
# via s3transfer
bottleneck==1.4.0
# via pandas
# via xarray
buckaroo==0.7.3
# via nbl
cachecontrol==0.14.0
# via sphinx-toolbox
cattrs==24.1.2
# via django-schema-graph
# via lsprotocol
# via pygls
certifi==2024.8.30
# via httpcore
# via httpx
# via pyogrio
# via pyproj
# via requests
# via selenium
# via sentry-sdk
# via sphinx-prompt
cffi==1.17.1
# via argon2-cffi-bindings
cfgv==3.4.0
# via pre-commit
chardet==5.2.0
# via pronto
charset-normalizer==3.3.2
# via requests
click==8.1.7
# via dask
# via distributed
# via jupyter-cache
# via mercantile
# via rich-click
# via spatialdata
# via uvicorn
# via wandb
cloudpickle==3.0.0
# via dask
# via distributed
# via doit
colorama==0.4.6
# via sphinx-autobuild
colorcet==3.1.0
# via datashader
# via holoviews
# via hvplot
comm==0.2.2
# via ipykernel
# via ipywidgets
commonmark==0.9.1
# via great-tables
contourpy==1.3.0
# via bokeh
# via matplotlib
coverage==7.6.1
# via nbl
cssutils==2.11.1
# via dict2css
cycler==0.12.1
# via matplotlib
dask==2024.9.1
# via dask-expr
# via dask-image
# via datashader
# via distributed
# via multiscale-spatial-image
# via nbl
# via numpydantic
# via ome-zarr
# via spatialdata
# via xarray
# via xbatcher
dask-expr==1.1.15
# via dask
dask-image==2024.5.3
# via nbl
# via spatialdata
datashader==0.16.3
# via xarray-spatial
debugpy==1.8.6
# via ipykernel
decorator==5.1.1
# via ipython
defusedxml==0.7.1
# via nbconvert
# via odfpy
deprecation==2.1.0
# via postgrest
dict2css==0.3.0.post1
# via sphinx-toolbox
distlib==0.3.8
# via virtualenv
distributed==2024.9.1
# via dask
# via ome-zarr
dj-database-url==2.2.0
# via lamindb-setup
django==5.1.1
# via dj-database-url
# via lamindb-setup
django-schema-graph==3.1.0
# via lamindb
docker-pycreds==0.4.0
# via wandb
docutils==0.21.2
# via jupyterlite-sphinx
# via myst-parser
# via nbl
# via pybtex-docutils
# via pydata-sphinx-theme
# via readme-renderer
# via sphinx
# via sphinx-prompt
# via sphinx-tabs
# via sphinx-toolbox
# via sphinxcontrib-bibtex
doit==0.36.0
# via jupyterlite-core
domdf-python-tools==3.9.0
# via apeye
# via apeye-core
# via dict2css
# via sphinx-toolbox
einops==0.8.0
# via xarray-einstats
einx==0.3.0
# via nbl
esbonio==0.16.5
# via nbl
et-xmlfile==1.1.0
# via openpyxl
executing==2.1.0
# via stack-data
faiss-cpu==1.8.0.post1
# via sklearn-ann
faker==30.1.0
# via faker-biology
# via nbl
faker-biology==0.6.4
# via nbl
faker-python==0.0.1
# via faker-biology
fasteners==0.19
# via zarr
fastjsonschema==2.20.0
# via nbformat
fastobo==0.12.3
# via pronto
fcsparser==0.2.8
# via readfcs
filelock==3.16.1
# via bionty
# via cachecontrol
# via sphinx-toolbox
# via torch
# via virtualenv
flowsom @ git+https://github.com/saeyslab/FlowSOM_Python@211ad7cd083141f4a7541b217d009ee5c7da00f6
# via nbl
flox==0.9.13
# via nbl
# via xarray
fonttools==4.54.1
# via matplotlib
fqdn==1.5.1
# via jsonschema
frozendict==2.4.4
# via einx
frozenlist==1.4.1
# via aiohttp
# via aiosignal
fsspec==2024.6.1
# via dask
# via lamindb
# via lightning
# via ome-zarr
# via pytorch-lightning
# via s3fs
# via spatialdata
# via torch
# via universal-pathlib
geopandas==1.0.1
# via spatialdata
gitdb==4.0.11
# via gitpython
gitpython==3.1.43
# via tach
# via wandb
gotrue==2.8.1
# via lamindb-setup
# via supabase
graphlib-backport==1.1.0
# via buckaroo
graphviz==0.20.3
# via lamindb
# via nbl
great-tables==0.12.0
# via nbl
h11==0.14.0
# via httpcore
# via uvicorn
# via wsproto
h2==4.1.0
# via httpx
h5py==3.12.1
# via anndata
# via mudata
# via scanpy
holoviews==1.19.1
# via hvplot
hpack==4.0.0
# via h2
html5lib==1.1
# via sphinx-toolbox
htmltools==0.5.3
# via great-tables
httpcore==0.17.3
# via httpx
httpx==0.24.1
# via gotrue
# via postgrest
# via storage3
# via supabase
# via supafunc
hvplot==0.11.0
# via nbl
hyperframe==6.0.1
# via h2
identify==2.6.1
# via pre-commit
idna==3.10
# via anyio
# via apeye-core
# via httpx
# via jsonschema
# via requests
# via sphinx-prompt
# via trio
# via yarl
igraph==0.11.6
# via flowsom
# via leidenalg
imageio==2.35.1
# via pims
# via scikit-image
imagesize==1.4.1
# via sphinx
importlib-metadata==8.5.0
# via dask
# via doit
# via great-tables
# via jupyter-cache
# via keyring
# via myst-nb
# via nbproject
# via twine
importlib-resources==6.4.5
# via great-tables
iniconfig==2.0.0
# via pytest
ipycytoscape==1.3.3
# via nbl
ipykernel==6.29.5
# via jupyterlab
# via myst-nb
# via nbl
ipylab==1.0.0
# via nbl
ipython==8.28.0
# via ipykernel
# via ipywidgets
# via myst-nb
# via nbl
ipywidgets==8.1.5
# via anywidget
# via buckaroo
# via ipycytoscape
# via ipylab
isoduration==20.11.0
# via jsonschema
jaraco-classes==3.4.0
# via keyring
jaraco-context==6.0.1
# via keyring
jaraco-functools==4.1.0
# via keyring
jedi==0.19.1
# via ipython
jinja2==3.1.4
# via altair
# via bokeh
# via dask
# via distributed
# via jupyter-server
# via jupyterlab
# via jupyterlab-server
# via myst-parser
# via nbconvert
# via sphinx
# via sphinx-jinja2-compat
# via torch
jmespath==1.0.1
# via boto3
# via botocore
joblib==1.4.2
# via pynndescent
# via scanpy
# via scikit-learn
json5==0.9.25
# via jupyterlab-server
jsonpointer==3.0.0
# via jsonschema
jsonschema==4.23.0
# via altair
# via jupyter-events
# via jupyterlab-server
# via nbformat
jsonschema-specifications==2023.12.1
# via jsonschema
jupyter-cache==1.0.0
# via myst-nb
jupyter-client==8.6.3
# via ipykernel
# via jupyter-server
# via nbclient
jupyter-core==5.7.2
# via ipykernel
# via jupyter-client
# via jupyter-server
# via jupyterlab
# via jupyterlite-core
# via nbclient
# via nbconvert
# via nbformat
jupyter-events==0.10.0
# via jupyter-server
jupyter-lsp==2.2.5
# via jupyterlab
jupyter-server==2.14.2
# via jupyter-lsp
# via jupyterlab
# via jupyterlab-server
# via jupyterlite-sphinx
# via notebook
# via notebook-shim
jupyter-server-terminals==0.5.3
# via jupyter-server
jupyterlab==4.0.13
# via nbl
# via notebook
jupyterlab-pygments==0.3.0
# via nbconvert
jupyterlab-server==2.27.3
# via jupyterlab
# via jupyterlite-sphinx
# via notebook
jupyterlab-widgets==3.0.13
# via ipywidgets
jupyterlite-core==0.4.1
# via jupyterlite-pyodide-kernel
# via jupyterlite-sphinx
jupyterlite-pyodide-kernel==0.4.2
# via nbl
jupyterlite-sphinx==0.16.5
# via nbl
jupytext==1.16.4
# via lamindb
keyring==25.4.1
# via twine
kiwisolver==1.4.7
# via matplotlib
lamin-cli==0.17.8
# via lamindb
lamin-utils==0.13.6
# via lamindb
# via lamindb-setup
# via nbproject
# via readfcs
lamindb==0.76.11
# via bionty
# via nbl
lamindb-setup==0.77.7
# via bionty
# via lamindb
latexcodec==3.0.0
# via pybtex
lazy-loader==0.4
# via scikit-image
legacy-api-wrap==1.4
# via scanpy
legendkit==0.3.4
# via marsilea
leidenalg==0.10.2
# via nbl
lightning==2.4.0
# via nbl
lightning-utilities==0.11.7
# via lightning
# via pytorch-lightning
# via torchmetrics
linkify-it-py==2.0.3
# via panel
llvmlite==0.43.0
# via numba
# via pynndescent
lnschema-core==0.74.6
# via lamindb
# via lamindb-setup
locket==1.0.0
# via distributed
# via partd
loguru==0.7.2
# via flowsom
lsprotocol==2023.0.1
# via pygls
lz4==4.3.3
# via dask
markdown==3.7
# via panel
markdown-it-py==3.0.0
# via jupytext
# via mdit-py-plugins
# via myst-parser
# via panel
# via rich
markupsafe==2.1.5
# via jinja2
# via nbconvert
# via sphinx-jinja2-compat
marsilea==0.4.6
# via nbl
matplotlib==3.9.2
# via flowsom
# via legendkit
# via marsilea
# via matplotlib-scalebar
# via nbl
# via scanpy
# via seaborn
# via spatialdata-plot
matplotlib-inline==0.1.7
# via ipykernel
# via ipython
matplotlib-scalebar==0.8.1
# via spatialdata-plot
mdit-py-plugins==0.4.2
# via jupytext
# via myst-parser
# via panel
mdurl==0.1.2
# via markdown-it-py
mercantile==1.2.1
# via altair-tiles
mistune==3.0.2
# via nbconvert
more-itertools==10.5.0
# via cssutils
# via jaraco-classes
# via jaraco-functools
mpmath==1.3.0
# via sympy
msgpack==1.1.0
# via cachecontrol
# via distributed
mudata==0.2.4
# via flowsom
multidict==6.1.0
# via aiohttp
# via yarl
multipledispatch==1.0.0
# via datashader
multiscale-spatial-image==1.0.1
# via spatialdata
myst-nb==1.1.2
# via nbl
myst-parser==4.0.0
# via myst-nb
narwhals==1.9.0
# via altair
natsort==8.4.0
# via anndata
# via domdf-python-tools
# via nbl
# via scanpy
nb-clean==3.3.0
# via nbl
nbclient==0.10.0
# via jupyter-cache
# via myst-nb
# via nbconvert
nbconvert==7.16.4
# via jupyter-server
# via lamindb
nbformat==5.10.4
# via jupyter-cache
# via jupyter-server
# via jupyterlite-sphinx
# via jupytext
# via myst-nb
# via nb-clean
# via nbclient
# via nbconvert
nbproject==0.10.4
# via lamindb
nest-asyncio==1.6.0
# via ipykernel
networkx==3.3
# via pronto
# via scanpy
# via scikit-image
# via spatialdata
# via tach
# via torch
nh3==0.2.18
# via readme-renderer
nodeenv==1.9.1
# via pre-commit
notebook==7.0.8
# via nbl
notebook-shim==0.2.4
# via jupyterlab
# via notebook
numba==0.60.0
# via datashader
# via flowsom
# via nbl
# via numbagg
# via pandas
# via pynndescent
# via scanpy
# via umap-learn
# via xarray-einstats
# via xarray-spatial
numbagg==0.8.2
# via xarray
numcodecs==0.13.0
# via zarr
numexpr==2.10.1
# via pandas
numpy==1.26.4
# via altair
# via anndata
# via bokeh
# via bottleneck
# via contourpy
# via dask
# via dask-image
# via datashader
# via einx
# via faiss-cpu
# via fcsparser
# via flowsom
# via flox
# via geopandas
# via great-tables
# via h5py
# via holoviews
# via hvplot
# via imageio
# via marsilea
# via matplotlib
# via mudata
# via multiscale-spatial-image
# via nbl
# via numba
# via numbagg
# via numcodecs
# via numexpr
# via numpy-groupies
# via numpydantic
# via ome-zarr
# via pandas
# via patsy
# via pims
# via pyarrow
# via pyogrio
# via scanpy
# via scikit-image
# via scikit-learn
# via scipy
# via seaborn
# via shapely
# via spatial-image
# via spatialdata
# via statsmodels
# via tifffile
# via torchmetrics
# via treescope
# via umap-learn
# via xarray
# via xarray-dataclasses
# via xarray-einstats
# via xarray-schema
# via xarray-spatial
# via xbatcher
# via zarr
numpy-groupies==0.11.2
# via flox
numpydantic==1.6.3
# via nbl
odfpy==1.4.1
# via pandas
ome-zarr==0.9.0
# via spatialdata
openpyxl==3.1.5
# via pandas
opt-einsum==3.4.0
# via xarray
orjson==3.10.7
# via nbproject
outcome==1.3.0.post0
# via trio
overrides==7.7.0
# via jupyter-server
packaging==24.1
# via altair
# via anndata
# via bokeh
# via buckaroo
# via dask
# via datashader
# via deprecation
# via distributed
# via faiss-cpu
# via flox
# via geopandas
# via holoviews
# via htmltools
# via hvplot
# via ipykernel
# via jupyter-server
# via jupyterlab
# via jupyterlab-server
# via jupytext
# via lazy-loader
# via lightning
# via lightning-utilities
# via matplotlib
# via nbconvert
# via nbproject
# via panel
# via pims
# via pooch
# via pydata-sphinx-theme
# via pyogrio
# via pytest
# via pytorch-lightning
# via scanpy
# via scikit-image
# via sphinx
# via statsmodels
# via torchmetrics
# via xarray
# via xarray-datatree
pandas==2.2.3
# via altair
# via anndata
# via bokeh
# via dask
# via dask-expr
# via dask-image
# via datashader
# via fcsparser
# via flowsom
# via flox
# via geopandas
# via holoviews
# via hvplot
# via lamindb
# via marsilea
# via mudata
# via nbl
# via panel
# via scanpy
# via seaborn
# via spatialdata
# via statsmodels
# via vega-datasets
# via vegafusion
# via xarray
pandocfilters==1.5.1
# via nbconvert
panel==1.5.1
# via holoviews
# via hvplot
param==2.1.1
# via datashader
# via holoviews
# via hvplot
# via panel
# via pyct
# via pyviz-comms
parso==0.8.4
# via jedi
partd==1.4.2
# via dask
patsy==0.5.6
# via scanpy
# via statsmodels
pexpect==4.9.0
# via ipython
pillow==10.4.0
# via bokeh
# via datashader
# via imageio
# via matplotlib
# via scikit-image
pims==0.7
# via dask-image
pkginfo==1.10.0
# via jupyterlite-pyodide-kernel
# via twine
platformdirs==4.3.6
# via apeye
# via esbonio
# via jupyter-core
# via marsilea
# via pooch
# via virtualenv
# via wandb
pluggy==1.5.0
# via pytest
pooch==1.8.2
# via spatialdata
postgrest==0.13.2
# via supabase
pre-commit==3.8.0
# via nbl
prometheus-client==0.21.0
# via jupyter-server
prompt-toolkit==3.0.48
# via ipython
# via tach
pronto==2.5.5
# via bionty
protobuf==5.28.2
# via vegafusion
# via wandb
psutil==6.0.0
# via distributed
# via ipykernel
# via lamindb-setup
# via vegafusion
# via wandb
psycopg2-binary==2.9.9
# via lamindb
psygnal==0.11.1
# via anywidget
ptyprocess==0.7.0
# via pexpect
# via terminado
pure-eval==0.2.3
# via stack-data
pyarrow==17.0.0
# via altair
# via dask
# via dask-expr
# via lamindb
# via pandas
# via spatialdata
# via vegafusion
pybtex==0.24.0
# via pybtex-docutils
# via sphinxcontrib-bibtex
pybtex-docutils==1.0.3
# via sphinxcontrib-bibtex
pycparser==2.22
# via cffi
pyct==0.5.0
# via datashader
pydantic==2.9.2
# via gotrue
# via nbproject
# via numpydantic
# via postgrest
# via pydantic-settings
pydantic-core==2.23.4
# via pydantic
pydantic-settings==2.5.2
# via lamindb-setup
pydata-sphinx-theme==0.15.4
# via sphinx-book-theme
pydot==3.0.2
# via tach
pygls==1.3.1
# via esbonio
pygments==2.18.0
# via accessible-pygments
# via ipython
# via nbconvert
# via pydata-sphinx-theme
# via readme-renderer
# via rich
# via sphinx
# via sphinx-prompt
# via sphinx-tabs
pykan==0.2.6
# via nbl
pymupdf==1.24.11
# via nbl
pynndescent==0.5.13
# via scanpy
# via sklearn-ann
# via umap-learn
pyogrio==0.10.0
# via geopandas
pyparsing==3.1.4
# via matplotlib
# via pydot
pyproj==3.7.0
# via geopandas
pysocks==1.7.1
# via urllib3
pyspellchecker==0.8.1
# via esbonio
pytest==8.3.3
# via nbl
python-calamine==0.2.3
# via pandas
python-dateutil==2.9.0.post0
# via arrow
# via botocore
# via faker
# via jupyter-client
# via lamindb
# via matplotlib
# via multiscale-spatial-image
# via pandas
# via pronto
# via realtime
# via storage3
python-dotenv==1.0.1
# via pydantic-settings
python-json-logger==2.0.7
# via jupyter-events
pytorch-lightning==2.4.0
# via lightning
pytz==2024.2
# via pandas
pyviz-comms==3.0.3
# via holoviews
# via panel
pyxlsb==1.0.10
# via pandas
pyyaml==6.0.2
# via bionty
# via bokeh
# via dask
# via distributed
# via jupyter-cache
# via jupyter-events
# via jupytext
# via lightning
# via myst-nb
# via myst-parser
# via nbproject
# via pre-commit
# via pybtex
# via pytorch-lightning
# via tach
# via wandb
pyzmq==26.2.0
# via ipykernel
# via jupyter-client
# via jupyter-server
rapidfuzz==3.10.0
# via lamindb
readfcs==1.1.8
# via flowsom
readme-renderer==44.0
# via twine
realtime==1.0.6
# via supabase
referencing==0.35.1
# via jsonschema
# via jsonschema-specifications
# via jupyter-events
requests==2.32.3
# via apeye
# via bionty
# via cachecontrol