Dask and Jupyter

Parallel python with dask and jupyter The dask framework provides an incredibly useful environment for parallel execution of python code in interactive settings (e.g. jupyter) or batch mode. Its key features are (from what I’ve seen so far): Representation of threading, multiprocessing, and distributed computing with one unified API and CLI. Abstraction of HPC schedulers (PBS, Moab, SLURM, …) Data structures for distributed computing with pandas and numpy syntax Dask-jobqueue The package dask_jobqueue seems to me to be the most userfriendly if it comes to parallelization on HPC clusters with a scheduling system such as SLURM. [Read More]