Automated PDF Reports with Python Notebooks

• mercury

  76 3,761 8.7 Python

  Convert Jupyter Notebooks to Web Apps

  

Hey! Author here. I'm working on open-source framework called Mercury. I'm building it to make notebooks sharing easy, especially with non-technical users. The Mercury can turn Python notebook to web application, dashboard, presentation, REST API or report. It has option to easily hide the code, schedule automatic execution, convert to PDF, and send email notifications. The Github repo: https://github.com/mljar/mercury

• bloxs

  8 214 0.0 Python

  Build dashboards in Jupyter Notebook with numeric and chart boxes

  

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

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• datapane

  30 1,349 7.3 Python

  Build and share data reports in 100% Python

  

You might find the Python framework we've been working on helpful for that use-case: https://github.com/datapane/datapane. It allows you to create interactive HTML reports comprised of pandas DataFrames, plots, and UI elements (e.g. dropdowns, selects, pages).

Standalone HTML files provide a really nice alternative to PDF as they maintain interactively: you can host them static sites, allow people to download data, use plots interactively, click through pages, similar to a statically generated website. That said, there is still a definite blocker in non-technical people receiving a .HTML file over email and immediately thinking it's suspicious or a virus (doesn't help that gmail has such poor support for them.) It's a shame, because PDFs have so many warts and HTML can be used as a really nice distributable file format, especially as you can make them fully standalone by baking in datasets, plots, libraries, etc. so they can be used without network.

IMO Jupyter is great at what it is - a REPL - but, outside of sharing a step-by-step "here are the steps I took to come to this answer", isn't the ideal format for sharing insights, as there is no reason a report would follow the same narrative as the analysis itself.

• literary

  1 11 0.0 Jupyter Notebook

  Literate Python package development with Jupyter

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.

Suggest a related project