ptpython VS Jupyter Notebook (IPython)

Ptpython reads from a configuration file where we can specify custom keybindings and the REPL colorscheme. The default configuration file can be copied from prompt-toolkit/ptpython/blob/master/examples/ptpython_config/config.py.

If you like using the REPL, for Python I recommend you try https://github.com/prompt-toolkit/ptpython

REPL??? Do you have a very-easy-to-use way of running and testing your code? From vim-slime to nvim sniprun to autocommands with the built in terminal, to an external repl like ptpython (for python obviously). iron.nvim and conjure are two other neovim repl plugins. There are many ways of running the code that you're working on, and having something that makes this really easy for you is pretty essential. (sometimes I use inotifytools on linux to literally just run the script every time I save it.)

I use ptpython for my python repl https://github.com/prompt-toolkit/ptpython. I find it very convenient because it has a vim mode, and many vim similarities.

A library like ptpython should be what you're looking for, however this probably isn't an option for an exam setting.

create a repl to the standard that ptpython sets for python (both croissant and ilua leave a lot to be desired)

My bad - the >>> and ... in my post are from an interactive shell session. - so there is an implicit print - which is why you see the output.

https://github.com/prompt-toolkit/ptpython is also a good one

Even better than iPython is PTPython, which can be used like a regular python interpreter with cool features.

Based on this conversation, this more or less means that your Python installation is kind of borked. By default it should use the built-in sqlite3, but apparently your installation is either ignoring it or it's missing for some reason.

this is just a summary of the jupyterhub docs: https://github.com/jupyterhub/jupyterhub/wiki/Using-sudo-to-run-JupyterHub-without-root-privileges

Something quite nifty I found about recently is that you can directly head over to the issues marked with these labels directly by going to the projects contributing page. For example, for JupyterHub, you would head over to https://github.com/jupyterhub/jupyterhub/contribute. Plus the Contribution guidelines are also made visible so you can access them directly!