For anyone interested in contributing to the project, there's a need for people with non-Mac machines to compile the lib and contribute it to a machine/architecture specific directory so it can be used easily for people without a C compiler.

There's also a need for people to add custom encoder/decoders for efficient data type transfer from Mathematica to convenient python forms. Currently things like PackedArray, RawArray, Image, SparseArray, and HashTable are supported. This uses an encoder on the Mathematica side and a decoder on the python side. Submissions of either are highly appreciated.

All ideas and other contributions are welcome, too.

Sorry, I should have been more clear about some things in the post, I think.

As you likely know, Jupyter is a just a front-end for python. I am personally annoyed by/opposed to Anaconda and so only ever start Jupyer from the command line (i.e. with jupyter notebook), but starting Jupyter from Anaconda should be fine. You can also use PJLink without Jupyter, as I generally do—Jupyter is just ersatz Mathematica so I thought it'd be fun to run real and fake Mathematica at the same time.

If you want that demo notebook I can provide it, but all the code is in the post.

PJLink is a dual Mathematica-python package so the way you start the Mathematica kernel is by launching it via python code. See this block in particular:

ker = SubprocessKernel()
def MEval (expr, wait = True, kernel = ker) :
     "" "MEval evaluates a Mathematica expression in the Mathematica kernel
      
      " ""
    kernel.drain() # just to make sure things are clen
    return kernel.evaluate (expr, wait = wait)
ker.start()
ker.start_evaluator()

ker.start() starts the Mathematica kernel and ker.start_evaluator() starts a python-side evaluator that Mathematica can call into. Those two lines are the real magic here. Beyond that I'm just calling into python.