bloxs
literary
bloxs | literary | |
---|---|---|
8 | 1 | |
213 | 11 | |
-0.5% | - | |
0.0 | 0.0 | |
almost 2 years ago | over 1 year ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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bloxs
- Show HN: Build dashboards in Jupyter Notebook with numeric and chart boxes
- Show HN: Build dashboard boxes with charts and numbers in Jupyter Notebook
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Automated PDF Reports with Python Notebooks
Right now it is flowing the notebook html. It should be possible to add some layout library (Python library that will do HTML+CSS to get nice layout).
Recently I did similar for displaying numbers in the notebook as a good looking boxes. I created a small Python package that takes the number and creates a box with borders with HTML+CSS. It is pretty handy for building dashboards in Python. The package name is Bloxs https://github.com/mljar/bloxs
- Show HN: Build dashboards in Jupyter Notebook from bloxs
- Bloxs: Display your data as cards in your Python notebook!
- Show HN: Bloxs – display data as cards in your notebook
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Bloxs: display your data in an attractive way in your notebook
Hi, I would like to share with you a small python package that I've created to display data in a notebook in an attractive way. The package is called bloxs and is available on GitHub https://github.com/mljar/bloxs.
literary
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Automated PDF Reports with Python Notebooks
Eh, I think this misses the point of why Jupyter Notebooks are useful, and who is using them.
I agree that in terms of literate programming as Knuth defined it, Notebooks are not great. There are tools to improve that story; I wrote https://github.com/agoose77/literary which at least lets you do a bit more "tangling and weaving" than you can out of the box. It doesn't let you define functions in arbitrary order, or implement fragments of a code block, but it does let you "boil down" a literate representation into something that is zero-cost at runtime and imports. There's also nbdev, although it's not my cup of tea.
The real point, though, is that most data-scientists aren't using (imo) notebooks to write and share libraries of code. Instead, they're using notebooks as semi-reproducible reports. I'm a physicist, and that's what I've been using Jupyter for. For me, Jupyter Notebooks are fantastic - the cell mechanism lends itself to rich-outputs that augment the narrative, and present the information in-line with the code that wrote it.
For me, the biggest gap here is writing _libraries_ that are leveraged in these notebooks. That's why I wrote Literary - to try and resolve some of the pain points that currently require you to use two tools (Jupyter Lab & e.g. PyCharm). I'm not saying it will work for everyone, or solve all of the problems, but for me it's enough to write my analysis as a package, so that's a limited success in my book.
What are some alternatives?
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
rfsoc_studio - The Strathclyde RFSoC Studio Installer for PYNQ.
Flight-Test-Data-Analytics-Module-01 - Code to support Module 01 of the Daedalus Aerospace Flight Test Data Analytics course.
mercury - Convert Jupyter Notebooks to Web Apps