Our great sponsors
-
evidence
Business intelligence as code: build fast, interactive data visualizations in pure SQL and markdown
-
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
-
-
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
And it's Open Source: https://github.com/evidence-dev/evidence
I'd also highly recommend Blazer https://github.com/ankane/blazer if you are into the Ruby on Rails world. It's super solid, and it's been an indispensable tool integrated to all my projects.
> Works with CI/CD out of the box. Deploy to vercel, netlify, your own infra.
Jupyter is suited for whatever you want to do with it. Voila exists to enable the use case of re-generating notebooks on a CI/CD system: https://github.com/voila-dashboards/voila
Anyways, seems like the templating is more powerful than the one being offered by Jupyter Notebooks.
Good luck and much success with it :)
How about something like [`input`](magic-link)? I came up with this for https://codeberg.org/macchiato ( though it's not yet implemented in the new project, just in the predecessor, https://github.com/ResourcesCo/notebook ). The backquotes differentiate from non-magic links. (I tried badges, but they aligned weirdly.)
You could use [`data.mrr`](https://evidence.dev/md/value) or any other internal DSL you can come up with.
Another thing you could do is just decide against MDX the format and keep the style and transform inline codeblocks that match.
That you said Markdown to me says you aren't on board with using an incompatible syntax.
If anyone is looking for something like this in Python/Jupyter, check out JupySQL: https://github.com/ploomber/jupysql
And it's Open Source: https://github.com/evidence-dev/evidence
I'd also highly recommend Blazer https://github.com/ankane/blazer if you are into the Ruby on Rails world. It's super solid, and it's been an indispensable tool integrated to all my projects.
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/
Thanks for sharing, that looks great! That Datapane example is more a hello world web app that runs Python code in the backend (so requires a backend server - Fly.io in this example).
An example of a standalone report would be something like this, from one of our users: https://cloud.datapane.com/reports/dkjbvwk/literature-in-blo... (code: https://github.com/ryancahildebrandt/hanakotoba) or https://cloud.datapane.com/reports/aAMaqoA/when-fact-is-fals...
We have support for duckdb (and CSVs and Parquet through duckdb). We don't support python, but some people have also told us they have used evidence as the front-end for a python project - used python to do data transformation and calculations, then dumped the results into a duckdb file in an evidence project and built the visuals and narrative in evidence.
"Containerized" approaches with evidence are also quite interesting - lets you combine several tools and use evidence as the last mile. Here's a great example: https://github.com/matsonj/nba-monte-carlo