Part 3: What Next?

You’ve now learned the basics of functional programming, and how to write parallel Python scripts that can run across the cores of your desktop, or across the processors of a distributed or HPC cluster.

If you want to learn more, you may want to look at the Python interface to the MPI library, e.g. via SciPy or via PyMPI.

You may also want to explore other parallel Python libraries, e.g. IPython Parallel, Pathos (contains Dill for pickling functions) or Parallel Python.

You should also check out this wiki on python.org that lists all of the different parallel Python libraries.

Also, for more general advanced Python tips and tricks, check out these blog posts from the Toptal community.

Also, parallel coding is advancing to cover accelerators, such as GPUs. You can code these by using, e.g. PyOpenCL.

Finally, there were some extra things that you may find useful that I couldn’t fit into this course. They are contained in the epilogue.


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