requirements.txt

#
# This file is autogenerated by pip-compile with Python 3.10
# by the following command:
#
#    pip-compile --extra-index-url=https://packages.dea.ga.gov.au/ --output-file=requirements.txt requirements.in
#
--extra-index-url https://packages.dea.ga.gov.au/

affine==2.4.0
    # via
    #   -r requirements.in
    #   datacube
    #   datacube-ows
    #   odc-algo
    #   odc-geo
    #   odc-stac
    #   rasterio
    #   rasterstats
aiohappyeyeballs==2.3.2
    # via aiohttp
aiohttp==3.10.0
    # via
    #   -r requirements.in
    #   dea-tools
aiosignal==1.3.1
    # via aiohttp
annotated-types==0.7.0
    # via pydantic
asttokens==2.4.1
    # via stack-data
async-timeout==4.0.3
    # via aiohttp
attrs==23.2.0
    # via
    #   aiohttp
    #   datacube
    #   fiona
    #   jsonschema
    #   rasterio
    #   referencing
babel==2.15.0
    # via
    #   datacube-ows
    #   flask-babel
blinker==1.8.2
    # via flask
boto3==1.34.151
    # via
    #   datacube
    #   dea-tools
botocore==1.34.151
    # via
    #   -r requirements.in
    #   boto3
    #   datacube
    #   dea-tools
    #   s3transfer
bottleneck==1.4.0
    # via datacube
branca==0.7.2
    # via
    #   dea-tools
    #   folium
    #   ipyleaflet
cachetools==5.4.0
    # via
    #   datacube
    #   odc-geo
certifi==2024.7.4
    # via
    #   fiona
    #   netcdf4
    #   pyproj
    #   rasterio
    #   requests
cffi==1.16.0
    # via timezonefinder
cftime==1.6.4
    # via netcdf4
charset-normalizer==3.3.2
    # via requests
ciso8601==2.3.1
    # via
    #   datacube
    #   dea-tools
click==8.1.7
    # via
    #   -r requirements.in
    #   click-plugins
    #   cligj
    #   dask
    #   datacube
    #   datacube-ows
    #   distributed
    #   fiona
    #   flask
    #   planetary-computer
    #   rasterio
    #   rasterstats
click-plugins==1.1.1
    # via
    #   fiona
    #   rasterio
cligj==0.7.2
    # via
    #   fiona
    #   rasterio
    #   rasterstats
cloudpickle==3.0.0
    # via
    #   dask
    #   dask-glm
    #   datacube
    #   distributed
colour==0.1.5
    # via datacube-ows
comm==0.2.2
    # via ipywidgets
contourpy==1.2.1
    # via matplotlib
cycler==0.12.1
    # via matplotlib
dask[array,dataframe]==2024.4.2
    # via
    #   -r requirements.in
    #   dask-expr
    #   dask-glm
    #   dask-image
    #   dask-ml
    #   datacube
    #   dea-tools
    #   distributed
    #   odc-algo
    #   odc-stac
dask-expr==1.0.14
    # via dask
dask-glm==0.3.2
    # via dask-ml
dask-image==2024.5.3
    # via odc-algo
dask-ml==2024.4.4
    # via dea-tools
datacube[performance,s3]==1.8.18
    # via
    #   -r requirements.in
    #   datacube-ows
    #   dea-tools
    #   odc-algo
    #   odc-ui
datacube-ows==1.8.41
    # via dea-tools
dea-tools==0.3.4
    # via -r requirements.in
decorator==5.1.1
    # via ipython
deepdiff==7.0.1
    # via datacube-ows
deprecat==2.1.3
    # via datacube
distributed==2024.4.2
    # via
    #   dask-glm
    #   dask-ml
    #   datacube
    #   odc-algo
exceptiongroup==1.2.2
    # via ipython
executing==2.0.1
    # via stack-data
fiona==1.9.4
    # via
    #   -r requirements.in
    #   dea-tools
    #   geopandas
    #   rasterstats
flask==3.0.3
    # via
    #   datacube-ows
    #   flask-babel
    #   prometheus-flask-exporter
flask-babel==4.0.0
    # via datacube-ows
folium==0.17.0
    # via dea-tools
fonttools==4.53.1
    # via matplotlib
frozenlist==1.4.1
    # via
    #   aiohttp
    #   aiosignal
fsspec==2024.6.1
    # via
    #   dask
    #   datacube-ows
geoalchemy2==0.15.2
    # via
    #   datacube
    #   datacube-ows
geographiclib==2.0
    # via geopy
geopandas==0.14.3
    # via
    #   -r requirements.in
    #   dea-tools
geopy==2.4.1
    # via dea-tools
greenlet==3.0.3
    # via sqlalchemy
h3==3.7.7
    # via timezonefinder
hdstats==0.2.1
    # via dea-tools
idna==3.7
    # via
    #   requests
    #   yarl
imageio==2.34.2
    # via
    #   pims
    #   scikit-image
importlib-metadata==8.2.0
    # via dask
ipyleaflet==0.19.2
    # via odc-ui
ipython==8.26.0
    # via
    #   ipywidgets
    #   jupyter-ui-poll
    #   odc-ui
ipywidgets==8.1.3
    # via
    #   ipyleaflet
    #   odc-ui
iso8601==2.1.0
    # via pyows
itsdangerous==2.2.0
    # via flask
jedi==0.19.1
    # via ipython
jinja2==3.1.4
    # via
    #   branca
    #   distributed
    #   flask
    #   flask-babel
    #   folium
jmespath==1.0.1
    # via
    #   boto3
    #   botocore
joblib==1.4.2
    # via
    #   dea-tools
    #   scikit-learn
jsonschema==4.23.0
    # via
    #   datacube
    #   pystac
jsonschema-specifications==2023.12.1
    # via jsonschema
jupyter-leaflet==0.19.2
    # via ipyleaflet
jupyter-ui-poll==1.0.0
    # via odc-ui
jupyterlab-widgets==3.0.11
    # via ipywidgets
kiwisolver==1.4.5
    # via matplotlib
lark==1.1.9
    # via
    #   datacube
    #   datacube-ows
lazy-loader==0.4
    # via scikit-image
llvmlite==0.43.0
    # via numba
locket==1.0.0
    # via
    #   distributed
    #   partd
lxml==5.2.2
    # via
    #   datacube-ows
    #   dea-tools
    #   owslib
    #   pyows
    #   pytmd
    #   timescale
markupsafe==2.1.5
    # via
    #   jinja2
    #   werkzeug
matplotlib==3.8.4
    # via
    #   -r requirements.in
    #   datacube-ows
    #   dea-tools
    #   odc-ui
matplotlib-inline==0.1.7
    # via ipython
mdutils==1.5.0
    # via -r requirements.in
msgpack==1.0.8
    # via distributed
multidict==6.0.5
    # via
    #   aiohttp
    #   yarl
multipledispatch==1.0.0
    # via
    #   dask-glm
    #   dask-ml
netcdf4==1.7.1.post1
    # via
    #   datacube
    #   pytmd
networkx==3.3
    # via scikit-image
numba==0.60.0
    # via
    #   dask-ml
    #   sparse
numexpr==2.10.1
    # via odc-algo
numpy==1.26.4
    # via
    #   -r requirements.in
    #   bottleneck
    #   cftime
    #   contourpy
    #   dask
    #   dask-image
    #   dask-ml
    #   datacube
    #   datacube-ows
    #   dea-tools
    #   folium
    #   hdstats
    #   imageio
    #   matplotlib
    #   netcdf4
    #   numba
    #   numexpr
    #   odc-algo
    #   odc-geo
    #   odc-stac
    #   odc-ui
    #   pandas
    #   pims
    #   pyarrow
    #   pygeos
    #   pytmd
    #   rasterio
    #   rasterstats
    #   rioxarray
    #   scikit-image
    #   scikit-learn
    #   scipy
    #   shapely
    #   snuggs
    #   sparse
    #   tifffile
    #   timescale
    #   timezonefinder
    #   xarray
odc-algo==0.2.3
    # via odc-ui
odc-geo==0.4.3
    # via
    #   -r requirements.in
    #   dea-tools
    #   odc-stac
odc-stac==0.3.9
    # via dea-tools
odc-ui==0.2.1
    # via
    #   -r requirements.in
    #   dea-tools
ordered-set==4.1.0
    # via deepdiff
owslib==0.31.0
    # via dea-tools
packaging==24.1
    # via
    #   dask
    #   dask-ml
    #   datacube
    #   dea-tools
    #   distributed
    #   geoalchemy2
    #   geopandas
    #   lazy-loader
    #   matplotlib
    #   pims
    #   planetary-computer
    #   rioxarray
    #   scikit-image
    #   setuptools-scm
    #   xarray
pandas==2.2.2
    # via
    #   -r requirements.in
    #   dask
    #   dask-expr
    #   dask-image
    #   dask-ml
    #   datacube
    #   dea-tools
    #   geopandas
    #   odc-stac
    #   odc-ui
    #   xarray
parso==0.8.4
    # via jedi
partd==1.4.2
    # via dask
pexpect==4.9.0
    # via ipython
pillow==10.4.0
    # via
    #   datacube-ows
    #   imageio
    #   matplotlib
    #   scikit-image
pims==0.7
    # via dask-image
planetary-computer==1.0.0
    # via dea-tools
prometheus-client==0.20.0
    # via prometheus-flask-exporter
prometheus-flask-exporter==0.23.1
    # via datacube-ows
prompt-toolkit==3.0.47
    # via ipython
psutil==6.0.0
    # via distributed
psycopg2==2.9.9
    # via
    #   datacube
    #   datacube-ows
ptyprocess==0.7.0
    # via pexpect
pure-eval==0.2.3
    # via stack-data
pyarrow==17.0.0
    # via dask-expr
pycparser==2.22
    # via cffi
pydantic==2.8.2
    # via planetary-computer
pydantic-core==2.20.1
    # via pydantic
pygeos==0.14
    # via -r requirements.in
pygments==2.18.0
    # via ipython
pyows==0.3.1
    # via datacube-ows
pyparsing==3.1.2
    # via
    #   datacube-ows
    #   matplotlib
    #   snuggs
pyproj==3.6.1
    # via
    #   -r requirements.in
    #   datacube
    #   dea-tools
    #   geopandas
    #   odc-geo
    #   pytmd
    #   rioxarray
pystac[validation]==1.10.1
    # via
    #   odc-stac
    #   planetary-computer
    #   pystac-client
pystac-client==0.8.3
    # via
    #   dea-tools
    #   planetary-computer
python-dateutil==2.9.0.post0
    # via
    #   botocore
    #   datacube
    #   datacube-ows
    #   dea-tools
    #   matplotlib
    #   owslib
    #   pandas
    #   pystac
    #   pystac-client
    #   pytmd
    #   timescale
python-dotenv==1.0.1
    # via planetary-computer
python-geohash==0.8.5
    # via -r requirements.in
python-slugify==8.0.4
    # via datacube-ows
pytmd==2.1.4
    # via
    #   -r requirements.in
    #   dea-tools
pytz==2024.1
    # via
    #   -r requirements.in
    #   datacube-ows
    #   dea-tools
    #   flask-babel
    #   owslib
    #   pandas
    #   planetary-computer
pyyaml==6.0.1
    # via
    #   -r requirements.in
    #   dask
    #   datacube
    #   distributed
    #   owslib
rasterio==1.3.8
    # via
    #   -r requirements.in
    #   datacube
    #   datacube-ows
    #   dea-tools
    #   odc-algo
    #   odc-stac
    #   odc-ui
    #   rasterstats
    #   rioxarray
rasterstats==0.19.0
    # via dea-tools
referencing==0.35.1
    # via
    #   jsonschema
    #   jsonschema-specifications
regex==2024.7.24
    # via datacube-ows
requests==2.32.3
    # via
    #   datacube-ows
    #   dea-tools
    #   folium
    #   owslib
    #   planetary-computer
    #   pystac-client
rioxarray==0.17.0
    # via dea-tools
rpds-py==0.19.1
    # via
    #   jsonschema
    #   referencing
ruamel-yaml==0.18.6
    # via datacube
ruamel-yaml-clib==0.2.8
    # via ruamel-yaml
s3transfer==0.10.2
    # via boto3
scikit-image==0.22.0
    # via
    #   -r requirements.in
    #   dea-tools
    #   odc-algo
scikit-learn==1.4.2
    # via
    #   -r requirements.in
    #   dask-glm
    #   dask-ml
    #   dea-tools
scipy==1.13.0
    # via
    #   -r requirements.in
    #   dask-glm
    #   dask-image
    #   dask-ml
    #   datacube-ows
    #   dea-tools
    #   hdstats
    #   pytmd
    #   scikit-image
    #   scikit-learn
    #   sparse
    #   timescale
setuptools-scm==8.1.0
    # via
    #   datacube-ows
    #   pytmd
    #   timescale
shapely==2.0.1
    # via
    #   -r requirements.in
    #   datacube
    #   dea-tools
    #   geopandas
    #   odc-geo
    #   rasterstats
simplejson==3.19.2
    # via rasterstats
six==1.16.0
    # via
    #   asttokens
    #   fiona
    #   python-dateutil
slicerator==1.1.0
    # via pims
snuggs==1.4.7
    # via rasterio
sortedcontainers==2.4.0
    # via distributed
sparse==0.15.4
    # via dask-glm
sqlalchemy==1.4.53
    # via
    #   datacube
    #   geoalchemy2
stack-data==0.6.3
    # via ipython
tblib==3.0.0
    # via distributed
text-unidecode==1.3
    # via python-slugify
threadpoolctl==3.5.0
    # via scikit-learn
tifffile==2024.7.24
    # via
    #   dask-image
    #   pims
    #   scikit-image
timescale==0.0.4
    # via pytmd
timezonefinder==6.5.2
    # via datacube-ows
tomli==2.0.1
    # via setuptools-scm
toolz==0.12.1
    # via
    #   dask
    #   datacube
    #   distributed
    #   odc-algo
    #   odc-stac
    #   partd
tornado==6.4.1
    # via distributed
tqdm==4.66.2
    # via
    #   -r requirements.in
    #   dea-tools
traitlets==5.14.3
    # via
    #   comm
    #   ipython
    #   ipywidgets
    #   matplotlib-inline
    #   traittypes
traittypes==0.2.1
    # via ipyleaflet
typing-extensions==4.12.2
    # via
    #   ipython
    #   pydantic
    #   pydantic-core
tzdata==2024.1
    # via pandas
urllib3==2.2.2
    # via
    #   botocore
    #   distributed
    #   requests
wcwidth==0.2.13
    # via prompt-toolkit
werkzeug==3.0.3
    # via flask
widgetsnbextension==4.0.11
    # via ipywidgets
wrapt==1.16.0
    # via deprecat
xarray==2024.3.0
    # via
    #   -r requirements.in
    #   datacube
    #   datacube-ows
    #   dea-tools
    #   odc-algo
    #   odc-stac
    #   odc-ui
    #   rioxarray
xyzservices==2024.6.0
    # via
    #   folium
    #   ipyleaflet
yarl==1.9.4
    # via aiohttp
zict==3.0.0
    # via distributed
zipp==3.19.2
    # via importlib-metadata

# The following packages are considered to be unsafe in a requirements file:
# setuptools