jupyterlab-git
nbdev
| jupyterlab-git | nbdev | |
|---|---|---|
| 7 | 45 | |
| 1,395 | 4,755 | |
| 1.1% | 0.9% | |
| 7.7 | 6.5 | |
| 23 days ago | 8 days ago | |
| TypeScript | Jupyter Notebook | |
| 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
nbdev
- The Jupyter+Git problem is now solved
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What is literate programming used for?
One example I've seen is ML/DL folks using jupyter notebooks to develop DL libraries in jupyter notebooks, see https://github.com/fastai/nbdev
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GitHub Accelerator: our first cohort and what's next
- https://github.com/fastai/nbdev: Increase developer productivity by 10x with a new exploratory programming workflow.
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Startups are in first batch of GitHub OS Accelerator
9. Nbdev: Boost developer productivity with an exploratory programming workflow - https://nbdev.fast.ai/
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Start learning python for a Statistician with SAS experience and little R experience
See if you like nbdev way of working with data through python and jupyter. nbdev is an optional part that will create python packages from jupyter notebooks. Also even the simple tutorials are opinionated and will guide you to unit test your code and write CICD pipelines.
- FastKafka - free open source python lib for building Kafka-based services
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isn't this just too much for a take home assignment?
You probably don’t have time for this for the purposes of your task, but I will also throw in the recommendation of nbdev especially if you’re a Python person. I haven’t had a project to use it on yet, but I’ve gone through the docs and the walkthrough and it seems like a great framework for starting potential projects with all the infrastructure needed for if/when they eventually get big and need all the packaging and stuff
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Any experience dealing with a non-technical manager?
nbdev: jupyter notebooks -> python package
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Resources to bridge the gap between jupyter notebooks and regular python development
Take a look at https://github.com/fastai/nbdev - haven't used it but supposedly the whole if fast.ai library was written that way. It sounds like a natural direction in your scenario - allowing your to keep working in a familiar environment and still producing production ready code (will, at least in paper 😅)
- Rant: Jupyter notebooks are trash.
What are some alternatives?
jupyterlab-spreadsheet-editor - JupyterLab spreadsheet editor for tabular data (e.g. csv, tsv)
papermill - 📚 Parameterize, execute, and analyze notebooks
debugger - A visual debugger for Jupyter notebooks, consoles, and source files
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
JupyterLab - JupyterLab computational environment.
dbt - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. [Moved to: https://github.com/dbt-labs/dbt-core]
jupyterlab-desktop - JupyterLab desktop application, based on Electron.
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
nbdime - Tools for diffing and merging of Jupyter notebooks.
rr - Record and Replay Framework
qgrid - An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks
Jupyter-PowerShell - Jupyter Kernel for PowerShell