PyCon Nove


19-22 aprile 2018

Going Functional in the Python Data Science Stack

Functional concepts are on the rise. In the big data space, this has been known ever since Map Reduce took the stage and nowadays, spark’s resilient, distributed data frames are a primary example of how functional, immutable concepts translate into successful architectures, that we can leverage from Python.

In this presentation I show how a functional approach to programming leads to a formulation of computation problems by directed acyclic graphs, which drives innovative libraries like Dask to provide an abstraction over the limitations of the von Neumann architecture.

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