truss VS datascript

When type checking is needed, I find the Truss library* does the trick quite well.

As for the syntax, there is very little, which can make it a harder lift but once you have the hang of it you won't deal with the issues identified in the parent comment.

* https://github.com/taoensso/truss

I use truss extensively throughout my code to prevent those types of errors.

I haven't tried it myself. I generally just use truss for runtime constraint checking. I use a modified version that integrates scope-capture. And malli validation for more complex cases, but I try to limit that. For me it is better to validate individual attributes as needed, vs validating an entire "type"/collection of attributes. So each function only cares about the attributes that it needs, and validates only as needed.

Use assertions for all data requirements inside functions - I use a modified version of https://github.com/ptaoussanis/truss to ensure that I never get NullReference exceptions, and this also helps make functions more self-documenting. Also use this to assert return data.

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.