datascript VS clerk

Hi pests, I don't think the criticism in the comments gives a full picture.

I wrote about a particular flavor of datalog, in common use today. [1] [2]. The earliest representation I know, which matches the syntax of my essay, was in SICP [3]

There's another, more academic form of datalog, which looks a lot more like prolog. Both have lots of similarities: both systems have a set of facts and rules. Both systems have can take a partially filled fact or rule, and find all matching facts. The more academic flavors of Datalog are useful for general logic, and particularly powerful for recursive questions. The variant I showed is more tailed for database queries.

[1] https://github.com/tonsky/datascript

There is also datascript as a similar option.

What's the use case for relic? Sounds similar to https://github.com/tonsky/datascript ?

This look nice !

Datascript seems to be another Datalog engine (in memory only)

https://github.com/tonsky/datascript

Inspired by past work: LINQ, inline-python, crepe, DataScript, Riffle.

An in-memory database like Datascript may be worth looking into. Otherwise you could take an indexing approach: put all the data into one big map indexed by some unique key, and have a bunch of supplementary indexes that are updated on insertion.

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.