with rasterio.open('/data/my_output.tif', 'w', 

               driver='GTiff',

               height=masked_raster.shape[1], 

               width=masked_raster.shape[2], 

               count=1, 

               dtype=rasterio.ubyte, 

               crs=file.crs, 

               transform=transform

              ) as outfile:

            outfile.write(masked_raster, indexes=1) 

I'm trying to use rasterio to mask a raster. According to the mask documentation, I need to load a raster file in 'r' mode, which I have done like so:

file = rasterio.open('/data/corine2018_100m/test.tif')
print(file)
<open DatasetReader name='/data/corine2018_100m/test.tif' mode='r'>

I also need a shapes which is an iterable GeoJSON-like object. I have GeoJSON serialised a Polygon object from a Django PolygonField() and added it to a list (my interpretation of the documentation's 'iterable object'):

obj = newJob.objects.create(job_loc="SRID=4326;POLYGON ((0.9063720703125029 52.32023207609735, 0.8239746093749998 52.10819209746323, 1.170043945312496 52.14191683166823, 1.170043945312496 52.31351619974807, 0.9063720703125029 52.32023207609735))")

poly = [obj.job_loc.geojson]
print(poly)
['{ "type": "Polygon", "coordinates": [ [ [ 0.906372070312503, 52.320232076097348 ], [ 0.823974609375, 52.108192097463231 ], [ 1.170043945312496, 52.141916831668233 ], [ 1.170043945312496, 52.313516199748072 ], [ 0.906372070312503, 52.320232076097348 ] ] ] }']

print(type(poly))
<class 'list'>

I then attempt the mask with:

masked_band, masked_transform = rasterio.mask.mask(file, poly, crop=True)

However, I get the error:

AttributeError: 'str' object has no attribute 'get'

I have tried following this (i.e. adding my JSON to a list) but I still get the error. Can someone help me mask this raster?

[Edited Message Follows]

factor = 2

with rasterio.open("mwi_ppp_2020.tif") as dataset:

    arr = dataset.read(1,masked=True)
    #Show total population of Malawi 
    print(arr.sum())

    data = dataset.read(1, masked=True, resampling=Resampling.bilinear,
        out_shape=(
            int(dataset.height * factor),
            int(dataset.width * factor)))

     #Show total population of array 
    print(data.sum())

     # scale image transform
    transform = dataset.transform * dataset.transform.scale(
            (dataset.width / data.shape[1]),

            (dataset.height / data.shape[0])
                                )