Dask is a flexible tool for parallelizing Python code on a single machine or across a cluster. It builds upon familiar tools in the SciPy ecosystem (e.g. NumPy and Pandas) while allowing them to scale across multiple cores or machines. This tutorial will cover both the high-level use of dask collections, as well as the low-level use of dask graphs and schedulers.
See tutorial materials here: https://scipy2018.scipy.org/ehome/299527/648136/