jupyterlab-git
qgrid
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jupyterlab-git | qgrid | |
---|---|---|
7 | 6 | |
1,391 | 3,028 | |
2.2% | 0.5% | |
7.9 | 0.0 | |
11 days ago | 4 months ago | |
TypeScript | Python | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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.
jupyterlab-git
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The Jupyter+Git problem is now solved
- GitHub PR code reviews with ReviewNB[4]
Alternatively, if you don't care about cell outputs then Jupytext[5]
Disclaimer: I built ReviewNB. It's a completely bootstrapped business, 5 years in the making and now used by leading DS teams at Meta, AWS, NASA JPL, AirBnB, Lyft, Affirm, AMD, Microsoft & more (https://www.reviewnb.com/#customers)
[1] https://github.com/jupyterlab/jupyterlab-git
I use this plugin for my jupyter notebook git integration. It has a git diff option that's useful but gets very slow for complex documents. Perhaps under the hood it's using one of the other tools mentioned in the postscript.
https://github.com/jupyterlab/jupyterlab-git
- Ask HN: Are there any good Diff tools for Jupyter Notebooks?
- Best extensions for JupyterLab!!
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Git extension for JupyterLab 3 released. Node/build step no longer needed (see updated install instructions). Adds commit & push, file browser context menu integration, Ctrl + enter to commit, "update diff" button and more!
Change log for this release: https://github.com/jupyterlab/jupyterlab-git/releases/tag/v0.30.0
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Recommendations for co-working on Jupyter Notebooks
Also there is an awesome jupyterlab-git extension.
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[D] Official Jupyter survey. How can Jupyter bet fit your workflow?
Official git extension https://github.com/jupyterlab/jupyterlab-git
qgrid
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Using spreadsheet widgets in Jupyter notebooks
There are a bunch of projects which seem to offer spreadsheet-style widgets for editing and presenting CSV and similar data in Jupyter: mitosheet, qgrid (abandoned?), jupyterlab-spreadsheet-editor, ipysheet (deprecated?), ipydatagrid, and ipyaggrid (and maybe others?). So far, mitosheet looks like the most flexible, featureful and up-to-date. Has anyone used these and can compare how useful they've been in practice? Or does anyone have some I've missed and should check out?
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How do I get my Jupyter Notebook to look more tabular like I see in tutorials vs the raw text output (and I guess what are they called?
you can check qgrid https://github.com/quantopian/qgrid
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Mito – Excel-like interface for Pandas dataframes in Jupyter notebook
I played around with many of these before:
https://github.com/quantopian/qgrid
- Best extensions for JupyterLab!!
- Replacing Jupyter Notebook with Org Mode
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Mito Write Python 10x faster by editing a spreadsheet
This looks like a copy of qgrid (https://github.com/quantopian/qgrid), which is open source and free.
What are some alternatives?
jupyterlab-spreadsheet-editor - JupyterLab spreadsheet editor for tabular data (e.g. csv, tsv)
jupyterlab-lsp - Coding assistance for JupyterLab (code navigation + hover suggestions + linters + autocompletion + rename) using Language Server Protocol [Moved to: https://github.com/jupyter-lsp/jupyterlab-lsp]
debugger - A visual debugger for Jupyter notebooks, consoles, and source files
mito - The mitosheet package, trymito.io, and other public Mito code.
JupyterLab - JupyterLab computational environment.
dtale - Visualizer for pandas data structures
nbdime - Tools for diffing and merging of Jupyter notebooks.
ipydatagrid - Fast Datagrid widget for the Jupyter Notebook and JupyterLab
jupyterlab-desktop - JupyterLab desktop application, based on Electron.
jupyterlab-spreadsheet - JupyterLab plugin for viewing spreadsheets, such as Excel .xls/.xlsx workbooks and OpenOffice .ods files
jupyterlab-system-monitor - JupyterLab extension to display system metrics
lux - Automatically visualize your pandas dataframe via a single print! 📊 💡