Looping through geopandas df, loading datacube data, masking with geometry

mask_dc_data.py

import sys
import datacube
import xarray as xr
import geopandas as gpd
from datacube.utils import geometry

sys.path.append('../Scripts')
from deafrica_datahandling import load_ard
from deafrica_spatialtools import xr_rasterize

#Connect to datacube
dc = datacube.Datacube(app='masking')

for index, row in gdf.iterrows():
        
    # Get the geometry
    geom = geometry.Geometry(row.geometry.__geo_interface__,
                             geometry.CRS(f'EPSG:{gdf.crs.to_epsg()}'))

     # generate a datacube query object
    query = {
        'time': time,
        'measurements': measurements,
        'resolution': resolution,
        'output_crs': output_crs,
        'group_by' : 'solar_day',
    }
    
    # Update dc query with geometry      
    query.update({'geopolygon': geom}) 
    
    #load data from datacube
    ds = load_ard(dc=dc,
                  products=products,
                  dask_chunks=dask_chunks,
                  **query)

    # Mask dataset to set pixels outside the polygon to `NaN`
    mask = xr_rasterize(gdf.iloc[[index]], ds)
    ds = ds.where(mask)