pandoc-plot VS ihp

That's great news. I've been waiting for years for a dedicated 'Figure' element. The workaround was pretty brittle. It'll make pandoc-plot [0] easier to maintain as well.

[0]: https://github.com/LaurentRDC/pandoc-plot

That's the perfect learning project because there's something tangible at the end.

Whenever the question of "How do I learn Haskell" comes up, I always suggest to come up with a project that would be useful on its own, regardless of the technology used to create it, and use Haskell to do it. In my case it was a pandoc filter to embed plots in documents (https://github.com/LaurentRDC/pandoc-plot), which was ultimately useful to create my PhD dissertation.

There's only so much you can learn about Haskell by working through toy examples.

I found IHP straightforward:

https://ihp.digitallyinduced.com/

despite not remembering much haskell!

This assumes you can get past nix for the install.

I find IHP well-designed. I just wish the licensing scheme were more transparent.

You can find the docs at https://ihp.digitallyinduced.com/ and some getting started videos at https://www.youtube.com/watch?v=PLl9Sjq6Nzc&list=PLenFm8BWuKlS0IaE31DmKB_PbkMLmwWmG

In case this got you interested in Haskell, and you want a good way to start your Haskell journey (and have something to apply the optimization handbook to), check out IHP. It's the Rails/Laravel of the Haskell world. You can start here https://ihp.digitallyinduced.com/Guide/index.html or check it out on GitHub here https://github.com/digitallyinduced/ihp

At IHP we've been using Algora for a while now and it works really great. Here's e.g. one PR that was merged last week with a bounty attached https://github.com/digitallyinduced/ihp/issues/1621 Everything was set up in less than 15 minutes and ioannis and zafer have been super helpful with any questions we had.

In general I think this is a good direction and an interesting take on the open question around sustainable open source. Congrats on the launch and keep up the great work! :)

You could contribute to IHP! We have some great docs to get started here https://github.com/digitallyinduced/ihp/blob/master/CONTRIBUTING.md And we have some low hanging fruits in GitHub issues for you to get started with, e.g. https://github.com/digitallyinduced/ihp/issues/1601 (also there's always lots of activity in the IHP Slack, in case you have any questions/need help)