The growing Python data science ecosystem, including the foundational packagesNumpy and Pandas, provides powerful tools for data analysis that are widelyused in a variety of applications. Typically, these libraries were designedfor data that fits in memory and for computations that run on a single core. Dask is a Python library for parallel and distributed computing, using blockedalgorithms and task scheduling. By leveraging the existing Python dataecosystem, Dask enables to compute on arrays and dataframes that are largerthan memory, while exploiting parallelism or distributed computing power, butin a familiar interface (mirroring Numpy arrays and Pandas dataframes).