This online workshop is meant to give an overview of working with research data in Python using general libraries for storing, processing, analysing and sharing data. The focus is on improving performance. After covering tools for performant processing (netcdf, numpy, pandas, scipy) on single workstations the focus shifts to parallel, distributed and GPU computing (snakemake, numba, dask, multiprocessing, mpi4py).
This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and its associated countries .
