frontends-team-compass
best-of-jupyter
frontends-team-compass | best-of-jupyter | |
---|---|---|
3 | 3 | |
53 | 849 | |
- | 3.9% | |
6.9 | 7.9 | |
2 months ago | 4 days ago | |
BSD 3-clause "New" or "Revised" License | Creative Commons Attribution Share Alike 4.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
frontends-team-compass
-
Jupyter + copilot
You may be interested in reading/leaving feedback on https://github.com/jupyterlab/team-compass/issues/172
- Research software code is likely to remain a tangled mess
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I'm working on a tool to help people learn data science with screen readers, so please give me feedback!
On the other hand, it seems that there will be accessibility improvements for Jupyter in the not too distant future. https://github.com/jupyterlab/team-compass/issues/98
best-of-jupyter
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Spreadsheet errors can have disastrous consequences – yet we keep making them
What are some Software Development methods for reducing errors:
1. AUTOMATED TESTS; test assertions
To write spreadsheet tests:
A. Write your own test assertion library for their macro language; write assertEqual() in VBscript and Apps Script.
B. Use another language with a test library and a test runner; e.g. Python and the `assert` keyword, unittest.TestCase().assertEqual() or pytest.
C. Test the spreadsheet GUI with something like AutoHotKey.
From https://news.ycombinator.com/item?id=35896192 :
> The Scientific Method is testing, so testing (tests, assertions, fixtures) should be core to any scientific workflow system.
> awesome-jupyter#testing: https://github.com/markusschanta/awesome-jupyter#testing
> ml-tooling/best-of-jupyter lists papermill/papermill under "Interactive Widgets/Visualization" https://github.com/ml-tooling/best-of-jupyter#interactive-wi...
- Mathics: A free, open-source alternative to Mathematica
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[P] best-of-ml-python: A ranked list of awesome machine learning Python libraries
best-of-jupyter: Jupyter Notebook, Hub, and Lab projects.