ipympl
nbdime
ipympl | nbdime | |
---|---|---|
3 | 7 | |
1,536 | 2,596 | |
1.4% | 0.3% | |
5.6 | 8.4 | |
25 days ago | 6 days ago | |
TypeScript | TypeScript | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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.
ipympl
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Using ADTK for easy time series anomaly detection
I discovered this little library called ADTK that offers a sklearn-like Python API on top of statsmodels and proved to be very useful. Since I don't have a background in time series forecasting it was very useful to have a high level class that performed seasonality detection and deviations automatically. The documentation also explains the different kinds of anomalies one would want to detect, which was also very useful. And finally, it provides some nifty visualization utilities on top of matplotlib, which I combined with ipympl to have interactivity.
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Large plots in Jupyter notebooks (in Windows)
Install https://github.com/matplotlib/ipympl
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jupyterlab interactive plot
JavaScript output is disabled in JupyterLab I have also tried the magic (with jupyter-matplotlib installed):
nbdime
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Stuff I Learned during Hanukkah of Data 2023
I remember hearing about nbdime and thinking it sounded useful, but I've never really needed it since I rarely use Jupyter in the first place. But then I made some changes to my Hanukkah of Data 2023 notebook to work with the follow-up "speed run" challenge (a new dataset and slightly tweaked clues), and the native Git diff was too noisy to be useful. nbdime came to the rescue! Here are the changes I had to make for days 2 and 3 during the speed run:
- The Jupyter+Git problem is now solved
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Ask HN: Are there any good Diff tools for Jupyter Notebooks?
[5] ReviewNB for reviewing & diff'ing notebook PRs / Commits on GitHub
Disclaimer: While I’m the author of last two (GitPlus & ReviewNB), I’ve represented the overall landscape in an unbiased way. I've been working on this specific problem for 3+ years & regularly talk to teams who use GitHub with notebooks.
[1] https://nbdime.readthedocs.io
- Notebooks suck: change my mind
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What if Git worked with Programming Languages?
Interesting they mentioned Jupyter Notebooks but not NBDime https://github.com/jupyter/nbdime which is a Jupyter plugin specifically to address this problem. Without it, diffing notebooks is not feasible.
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Jupyter diff in Magit
A bit off-topic but someone might know; I'm working with jupyter notebook files (ipynb) which are basically json files. Git diff is very noisy so there's nbdime which works great in the CLI. Is there a way to have Magit aware of its integration with git diff?
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The Notepad++
I use nbdime which allows you to ignore parts of a notebook (e.g. outputs) when diffing.
What are some alternatives?
ipywidgets - Interactive Widgets for the Jupyter Notebook
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
ipyflex - A WYSIWYG layout editor for Jupyter widgets
poetry-dynamic-versioning - Plugin for Poetry to enable dynamic versioning based on VCS tags
jupyterlite - Wasm powered Jupyter running in the browser 💡
nvim-treesitter-context - Show code context
webdiff - Two-column web-based git difftool
locust - "git diff" over abstract syntax trees
unison - A friendly programming language from the future
pretty-diff - Pretty printing a diff of two values
nbstripout - strip output from Jupyter and IPython notebooks
doorstop - Requirements management using version control.