A lot of the commentary here focuses on comparison with tabular/dataframe based analyses, but one of the killer use cases for Dask is more generalized out-of-co

A lot of the commentary here focuses on comparison with tabular/dataframe based analyses, but one of the killer use cases for Dask is more generalized out-of-core array computing. It greatly simplifies many of the forms of dimensional reductions or aggregations that one might perform on n-dimensional data cubes, without worrying about the boilerplate and cognitive overhead of blocking out your calculation and keeping track of all the intermediates. And in the fact that you can accomplish the reduction out-of-core and you've got an incredibly useful tool. Is it the perfect tool for all applications? Absolutely not. But for many of my workloads as a geoscientist it allows me to trivially matriculate a toy/prototype code to something at "scale" (maybe not for production, but certainly for research) with very little effort. That frees me up to work on other problems.