nb_conda_kernels
datapane
| nb_conda_kernels | datapane | |
|---|---|---|
| 3 | 30 | |
| 564 | 1,349 | |
| 0.9% | 0.5% | |
| 8.3 | 7.3 | |
| 10 days ago | 7 months ago | |
| Python | 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.
nb_conda_kernels
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JupyterLab 4.0
If you use conda there are extensions that can help with this by automatically registering any available conda environments that include ipykernel in your Jupyter Lab environment.
nb_conda_kernels is pretty reliable but not actively maintained. Gator from the mamba folks is new and still a bit rough around the edges but looks like it will be pretty slick eventually.
https://github.com/Anaconda-Platform/nb_conda_kernels
https://github.com/mamba-org/gator
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How to open Notebook in new tab from a Launcher Terminal
it sounds like what you're trying to do is what https://github.com/Anaconda-Platform/nb_conda_kernels does, except with pipenv. I unfortunately do not have a solution for you for pipenv, but nb_conda_kernels does seamlessly allow you to launch kernels in environments other than the environment Jupyter is running in without having to start multiple instances of jupyter.
datapane
- Datapane: Build and share data reports in 100% Python
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Polars: Company Formation Announcement
If you're looking for an easy way to build an HTML report using Python, you might find Datapane (https://github.com/datapane/datapane) helpful. I'm one of the people building it! We don't support polars (yet, on the roadmap) but we do support pandas so you can convert to a pandas DataFrame and include your data and any plots, etc.
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JupyterLab 4.0
If you're interested in an easier way to create reports using Python and Plotly/Pandas, you should check out our open-source library, Datapane: https://github.com/datapane/datapane - you can create a standalone, redistributable HTML file in a few lines of Python.
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Evidence – Business Intelligence as Code
You might be interested in what we're hacking on at Datapane (I'm one of the founders): https://github.com/datapane/datapane.
You can create standalone HTML data reports from Python/Jupyter in ~3 lines of code: https://docs.datapane.com/reports/overview/
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Ask HN: Fastest way to turn a Jupyter notebook into a website these days?
You can build web apps from Jupyter using Datapane [0]. I'm one of the founders, so let me know if I can help at all.
You can either export a static site [1] (and host on GH pages or S3), or, if you need backend logic, you can add Python functions [2] and serve on your favourite host (we use Fly).
We have specific Jupyter integration to automatically convert your notebook into an app [3].
[0] https://github.com/datapane/datapane
[1] https://docs.datapane.com/reference/reports/#datapane.proces...
[2] https://docs.datapane.com/apps/overview/
[3] https://docs.datapane.com/reports/jupyter-integration/#conve...
- Datapane – Build full-stack data apps in 100% Python
-
Datapane - Build full-stack data apps in 100% Python
Our GitHub is https://github.com/datapane/datapane and you can get started here: https://docs.datapane.com/quickstart/
- Datapane: Build internal analytics products in minutes using Python
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Datapane - Build internal data products in 100% Python
Thanks a lot! Yes, absolutely, a few people have brought this up and working working on removing the header right now. If I can help at all, feel free to reach us on GH Discussions: https://github.com/datapane/datapane/discussions
- Datapane/datapane: Build full-stack data analytics apps in Python
What are some alternatives?
JupyterLab - JupyterLab computational environment.
streamlit - Streamlit — A faster way to build and share data apps.
papermill - 📚 Parameterize, execute, and analyze notebooks
dash - Data Apps & Dashboards for Python. No JavaScript Required.
gator - Conda environment and package management extension from within Jupyter
jupyter-dash - OBSOLETE - Dash v2.11+ has Jupyter support built in!
notebooker - Productionise & schedule your Jupyter Notebooks as easily as you wrote them.
perspective - A data visualization and analytics component, especially well-suited for large and/or streaming datasets.
m1_huggingface_diffusers_demo - Demo of how to get HuggingFace Diffusers working on an M1 Mac
superset - Apache Superset is a Data Visualization and Data Exploration Platform
cufflinks - Productivity Tools for Plotly + Pandas
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!