pypy VS repo2jupyterlite

You'll note I said I was playing with RPython, not PyPy. In my case, I was playing with writing a small interpreter, and comparing the RPython toolchain with the Truffle/Graal framework.

Writing RPython code, even if one is not developing or contributing to PyPy, means writing within a subset of python 2.

> RPython ("Restricted Python") is a subset of Python 2

https://www.pypy.org/posts/2022/04/how-is-pypy-tested.html

And RPython's translator specifically uses pypy, and uses python 2 syntax:

https://github.com/pypy/pypy/blob/main/rpython/bin/rpython#L...

... so getting the RPython toolchain (even if one is intending to improve the PyPy 3+ interpreters) requires setting up a pypy 2 interpreter. Hence the question in my post.

https://data-apis.org/dataframe-protocol/latest/purpose_and_...

Practically, pd.DataFrame(,dtype_backend="arrow") may be a quick performance boost.

Jupyter kernels with Papermill or cron and templated parameters at the top of a notebook with a dated filename in a (repo2docker compatible) git repo also solve for interactive reports. To provision a temporary container for a user editing report notebooks, there's Voila on binderhub / jupyterhub, https://github.com/binder-examples/voila

or repo2jupyterlite in WASM with MathTex and Pyodide's NumPy/pandas/sympy: https://github.com/jupyterlite/repo2jupyterlite

But that's not a GUI, that's notebooks. For Jupyter integration, TIL pyqtgraph has jupyter_rfb, Remote Frame Buffer: https://github.com/vispy/jupyter_rfb