ubelt
best-of-jupyter
ubelt | best-of-jupyter | |
---|---|---|
7 | 3 | |
711 | 836 | |
- | 2.4% | |
8.3 | 7.9 | |
7 days ago | 7 days ago | |
Python | ||
Apache License 2.0 | 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.
ubelt
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Python libs that I wish were part of the standard library
I can't give you a stdlib, but I can give you a package with a lot of the basic functionality but still small enough that it installs quickly and has negligable overhead. The ubelt library is a set of 100ish utility functions and classes. It's similar to boltons, but I suppose it reflects a different perspective on what's useful.
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How do you feel about vendored packages?
Number 3 is the one I feel most conflicted about. Specifically, I tout my ubelt library as having 0 required dependencies. However, it vendors two libraries: progiter and orderedset. The first of which I also maintain and the second of which I don't maintain, but have contributed to. It feels odd to have a single dependency for a library that would otherwise have zero. But at the same time it feels odd to maintain that code myself. Also if I didn't vendor it, it would not be included in the documentation, so there is that. I've recently been thinking I should split ubelt up into many smaller packages and then use ubelt as a "hub" to include them all. However, that's a lot more work than just maintaining one (still quite small) package, and I think having everything broken up with incur a lot of overhead at pip install time, so I'm very conflicted on the whole subject.
- Useful helper libraries
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Python projects with best practices on Github?
I'm fairly happy with my ubelt library.
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[D] What is some cool python magic(s) that you've learned over the years?
The ubelt.util_platform module is a good example of including references to similar functionality.
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[P] best-of-ml-python: A ranked list of awesome machine learning Python libraries
I also have a utility library ubelt with 552 stars and 6.9k downloads / month.
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.
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