- Puhti - serial/array/parallel processing with Python. How to parallelize your Python code with different methods for running in Puhti supercomputer.
- Working with Allas data from Python. Examples with S3 and Swift APIs
- Reading NLS topographic database geopackage with Python
- GRASS multiprocessing from Python
- Routing Examples using NetworkX and igraph, serial and parallel.
- Sentinel data download from Finhub using sentinelsat
- STAC, xarray and dask for downloading and processing data
- Zonal statistics in parallel using rasterstats, serial and parallel.
- Python Dask-geopandas using Dask-geopandas in spatial analysis.
NOTE: If you are using Jupyter lab on your own computer, the Jupyter-github extension provides you with the possibility to browse public github repositories within Jupyter. Install the extension, click on the little github/cat icon in the left bar and fill
csc-training/geocomputinginto the search field and press enter. This lets you open and run all python files and notebooks within this repository on your own computer.