TIL: CLP (Q) is a natural consequence of CLP (FD)

[kwon-young]

@Johnny_Rotten

Somehow I have the feeling they follow a different philosophy than
most constraint logic programming CLP(X). The later often sees an
application as doing two steps, first building a model via attribute variables
and then solving the model. This approach breaks if I want to have a
knowledge base of constraints, so that I have a kind of facts being
constraints. Sympy can do that somehow:

from sympy.physics.units import *

(5000 * gram) / (2 * gram)
# 2500

Sorry, it’s not really relevant to your goal, but I have recently made a pack for unit aware computation that is compatible with clpBNR, meaning you can do this:

?- qeval({A == 5000*gram / 2 * gram}). % wrong equation, see below
A = 2500.

Here is the original post: Units: a new pack for units and quantities

edit:
the correct equation was this:

?- qeval({A == 5000*gram / (2 * gram)}).
A = 2500.