clerk VS athens

Something I really like in the Clojure data science stack that isn't mentioned is Clerk* — an interesting take on notebooks. I think it's a good gateway into Clojure for those coming from a Python or R background.

*https://clerk.vision/

Clojure's lazy sequences by default are wonderful ergonomically, but it provides many ways to use strict evaluation if you want to. They aren't really a hassle either. I've been doing Clojure for the last few years and have a few grievances, but overall it's the most coherent, well thought out language I've used and I can't recommend it enough.

There is the issue of startup time with the JVM, but you can also do AOT compilation now so that really isn't a problem. Here are some other cool projects to look at if you're interested:

Malli: https://github.com/metosin/malli

Babashka: https://github.com/babashka/babashka

Clerk: https://github.com/nextjournal/clerk

I'm really enjoying using Clojure with Clerk: https://github.com/nextjournal/clerk

It's a bit like a Jupyter notebook, but you get to use your own editor, you still have a normal Clojure REPL, it's stored in git like "normal" code, etc.

Hey all, I'm new to Clojure and would appreciate your help with a few questions I had getting started. I'm using Leiningen to setup my projects and manage my packages as recommended in Brave & True. So far I've been able to add any dependencies I've needed without much issue, Neanderthal, tech.v3.dataset, etc. I'm interested in data science, and was hoping to set up a notebook environment to be able to quickly produce data visualizations on the fly since I'm used to working with Jupyter. I came across Clerk, but I'm having some trouble adding it to my project. Here's what I tried:

Clojure also has Clerk, which is like Jupyter, but more befitting Clojure's overall philosophy: https://clerk.vision/

If I were working long enough with gnarly enough equations I'd look into using Clerk to visualize the equations with MathJax or similar, probably following Sam Ritchie's footsteps with SICMUtils. To me this is the true readability answer: lisp notation for precise implementations, compiling to a rich & familiar visual representation.

You might be interested in how in Athens we modelled properties as named (map-like) block relationships: https://github.com/athensresearch/athens/blob/main/doc/adr/0026-properties.md

https://github.com/athensresearch/athens

The underlying in memory datalog style database that can run in the browser that enables these apps

There is a docker compose file on there github that made things easy to get started. Has a web interface and was very quick. You could have multiple users as well.

I need a guide how to install athens for installing previously downloaded go packages. I have created a binary file from athens https://github.com/athensresearch/athens and configure .toml with path to local storage, also change the storage parameter to [disk

Athens

Get the docker compose manager. Create a new stack and put in the docker Compose file from Athens. Change to the ports and volumes you want and you are good to go.

Has anyone successfully running a selfhosted version of Athens from athensreseach. There is a demo. They even have a document page with some help for docker.