Performing out-of-core computations on large arrays with Dask
Dask is a parallel computing library that offers not only a general framework for distributing complex computations on many nodes, but also a set of convenient high-level APIs to deal with out-of-core computations on large arrays. Dask provides data structures resembling NumPy arrays (dask.array) and Pandas DataFrames (dask.dataframe) that efficiently scale to huge datasets. The core idea of Dask is to split a large array into smaller arrays (chunks).
In this recipe, we illustrate the basic principles of dask.array.
Getting ready
Dask should already be installed in Anaconda, but you can always install it manually with conda install dask. You also need memory_profiler, which you can install ...
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