dockerized-jupyter-notebook
mercury
dockerized-jupyter-notebook | mercury | |
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2 | 77 | |
1 | 3,789 | |
- | 1.2% | |
4.7 | 8.5 | |
6 months ago | 4 days ago | |
Jupyter Notebook | Python | |
MIT License | GNU Affero General Public License v3.0 |
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dockerized-jupyter-notebook
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Ask HN: Fastest way to turn a Jupyter notebook into a website these days?
your task is very very broad
you mention you don't want to deal with AWS, if it's because of ad-hoc installation concerns and nothing else you can just run your notebooks in ready-made solutions like Google Colab, or Jupyter-book in Github ( https://github.com/executablebooks/jupyter-book ))
that would cover a lot of use cases right away without next to no learning curve
If you don't want to deal with AWS or similar, in that case:
- if it's a static notebook then you can obviously render it and serve the web content (might seem obvious but needs to be considered)
- if it's dynamic but has light hardware requirements, you can try jupyterlite which runs in the browser and should do a pyodine (webassembly CPython kernel) can do: https://jupyterlite.readthedocs.io/en/latest/try/lab/
- otherwise, you can try exposing a dockerised jupyter env ( as in https://github.com/MKAbuMattar/dockerized-jupyter-notebook/b... ) or even better a nixified one ( https://github.com/tweag/jupyenv )
there might be other approaches I'm missing, but I think that's pretty much it that doesn't entail some proprietary solution or an ad-hoc installation as you've been doing
mercury
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Ask HN: What's the best charting library for customer-facing dashboards?
I'm build dashboards in Jupyter Lab. My plotting libraries are Altair, matplotlib, seaborn, Plotly - all work well in notebook.
My favorite is Altair. It provides interactivity for charts, so you can move/zoom your plots and have tooltips. It is much lighter than Plotly after saving the notebook to ipynb file. Altair charts looks much better than in matplotlib. One drawback, that exporting to PDF doesn't work. To serve notebook as dashboard with code hidden, I use Mercury framework, you can check example https://runmercury.com/tutorials/vega-altair-dashboard/
disclaimer: I'm author of Mercury framework https://github.com/mljar/mercury
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mercury VS solara - a user suggested alternative
2 projects | 13 Oct 2023
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Show HN: Web App with GUI for AutoML on Tabular Data
Web App is using two open-source packages that I've created:
- MLJAR AutoML - Python package for AutoML on tabular data https://github.com/mljar/mljar-supervised
- Mercury - framework for converting Jupyter Notebooks into Web App https://github.com/mljar/mercury
You can run Web App locally. What is more, you can adjust notebook's code for your needs. For example, you can set different validation strategies or evalutaion metrics or longer training times. The notebooks in the repo are good starting point for you to develop more advanced apps.
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streamlit VS mercury - a user suggested alternative
2 projects | 8 Jul 2023
- GitHub - mljar/mercury: Convert Jupyter Notebooks to Web Apps
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[P] Opinionated Web Framework for Converting Jupyter Notebooks to Web Apps
The GitHub repository https://github.com/mljar/mercury
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Show HN: Opinionated Web Framework for Converting Jupyter Notebooks to Web Apps
We are working on open-source web framework Mercury that converts Python notebooks to Web Apps.
It is very opinionated:
- it has no callbacks - we automatically re-execute cells below updated widget
- it has no layout widgets, all input widgets are always in the left sidebar
Thanks to above decisions you don't need to change notebook's code to have web app and fit to the framework.
The simplicity of the framework is very important to us. We also care about deployment simplicity. That's why we created a shared hosting service called Mercury Cloud. You can deploy notebook by uploading a file.
The GitHub repository https://github.com/mljar/mercury
Documentation https://RunMercury.com/docs/
Mercury Cloud https://cloud.runmercury.com
- Show HN: Build Web Apps in Jupyter Notebook with Python Only
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[OC] Analyzing 15,963 Job Listings to Uncover the Top Skills for Data Analysts (update)
Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.
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[OC] Data Analyst Skills in need based on 15,963 job listings
Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.
What are some alternatives?
livebook - Automate code & data workflows with interactive Elixir notebooks
streamlit - Streamlit — A faster way to build and share data apps.
jupyter-book - Create beautiful, publication-quality books and documents from computational content.
voila - Voilà turns Jupyter notebooks into standalone web applications
awesome-jupyter - A curated list of awesome Jupyter projects, libraries and resources
papermill - 📚 Parameterize, execute, and analyze notebooks
voila-gridstack - Dashboard template for Voilà based on GridStackJS
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
awesome-streamlit - The purpose of this project is to share knowledge on how awesome Streamlit is and can be
ipython - Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
jupyter_console - Jupyter Terminal Console