Python has become the leading programming language in a wide variety of sciences including remote sensing. Developments in N-dimensional array handling using numpy, and particularly xarray and its integration with projects like Dask, Jax, and CUDA allow for intuitive and scalable analysis of multi-dimensional data in Python. Spatial data types can now be handled by projects like rasterio and GDAL for gridded spatial data formats like GeoTIFF, and geopandas for spatial vectors. Once gridded arrays are accessible, they can be passed to tools like scikit-learn for machine learning or for use in deep-learning with packages like Keras to predict labels. Together these packages provide all the core components for an end-to-end raster and remote sensing operations.