There are much more active projects that do the same thing as this. - IPython parallel (https://ipyparallel.readthedocs.io/en/latest/ https://ipyparallel.readt

There are much more active projects that do the same thing as this. - IPython parallel (https://ipyparallel.readthedocs.io/en/latest/ https://ipyparallel.readthedocs.io/en/latest/ ) is pretty much the same idea but under active development, supports both local processes, small clusters, cloud computng, an HPC environments (SGE style supercomputing schedulers). - Joblib is a great tool for common embarrassingly parallel problems - run on many cores with a one liner (https://pythonhosted.org/joblib/index.html https://pythonhosted.org/joblib/index.html) - Dask provides a graph-based approach to lasily building up task graphs and finding an optimal way to run them in parallel (http://dask.pydata.org/ http://dask.pydata.org/)