vscode-python VS jupyter

help get this supported in vscode by liking the issue here: https://github.com/microsoft/vscode-python/issues/24916

The issue involved preventing test coverage from running a second time if it had already failed. I located the GitHub Actions workflow file and found the step responsible for running test coverage. By using the needs argument, I made the step depend on the earlier test steps to be completed. After updating the workflow and creating a pull request, I was happy to see it accepted and merged.

VS Code Python

The main contribution I worked on was for the vscode-python extension. The issue involved removing redundant JSDoc comments that TypeScript can already infer. Some of the comments were a repeat of what was can be understood from the typescript code, which meant they would need to be updated every time the code changed. The idea was to get rid of those types of comments but keep parts that added useful context.

Ah, Chrome and slow spinners.

Python tests were taking ages on VSCode due to an SVG spinner:

https://bugs.chromium.org/p/chromium/issues/detail?id=103626...

https://github.com/microsoft/vscode-python/issues/9216

It seems to be a problem caused by the new version of the Python extension. Here is a GitHub link for you to follow up.

For the python extension, please file your issue here: https://github.com/microsoft/vscode-python/issues

There seems to be a focus on feature velocity, and as the big parts start to stabilize (language server stuff, refactoring, extension framework, general UI/UX expectations), I hope we'll see some more attention paid to the default experience. But changing defaults in an ecosystem where users embrace configurability is tough, see the pythonPath fiasco, so I don't know the way forward. Core dev Brett Cannon seems to support the opinionated path for the VSCode Python experience going forward, so we'll see where that takes us.

I filed a GitHub report, you can always follow up.

6. Jupyter Jupyter is a collection of tools and applications designed for interactive computing and data visualization. At the heart of the Jupyter ecosystem is the Jupyter Notebook, an interactive web-based platform that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It’s an excellent tool for exploratory data analysis, model prototyping, and creating reproducible data science workflows.

How cool. This motivated a quick search - this could be fun:

How to write your own kernel

https://jupyter-client.readthedocs.io/en/stable/kernels.html

All the language kernels (a lot of abandoned ones - the mariaDB one ('binder') will take a while to load but SQL in Jupyter!)

https://github.com/jupyter/jupyter/wiki/Jupyter-kernels

There are Jupyter kernels for Python, Mathics, Wolfram, R, Octave, Matlab, xeus-cling, allthekernels (the polyglot kernel). https://github.com/jupyter/jupyter/wiki/Jupyter-kernels

Not only there is. But it is only a simple Google search away... But to make it simpler... There are 3 😁 https://github.com/jupyter/jupyter/wiki/Jupyter-kernels

As it seems, this is not quite straight forward and manyusers have similar troubles.

Community maintained kernels : https://github.com/jupyter/jupyter/wiki/Jupyter-kernels

Derek Banas on YouTube is doing a "Python for Finance" course at ghe moment using Jupyter, and is making the files available. I believe he's done others too.Failing that, there's this Git repo: A gallery of interesting jupyter notebooks