# RETROCHANGE / canopy gaps — pip fallback for a JupyterHub where you cannot
# create a conda environment (the EOSC EU Node, for instance). Run it in a cell:
#
#     %pip install -r env/requirements-canopy-gaps.txt
#
# then Kernel > Restart Kernel and run the notebook from section 3.
#
# These are MINIMUMS, not pins: on a managed image you usually cannot downgrade
# numpy or GDAL, and the notebook does not need you to. Its section 4.1 verifies
# that whatever you end up with actually behaves correctly.
numpy>=1.22
scipy>=1.8
pandas>=1.5
matplotlib>=3.5
rasterio>=1.3
geopandas>=0.13
shapely>=2.0
scikit-image>=0.19
scikit-learn>=1.0
pyogrio>=0.7
