Crate cspsolver 

CSP Solver

A constraint satisfaction problem (CSP) solver library.

Variable Types

• Integer variables: m.int(min, max) - continuous range
• Float variables: m.float(min, max) - continuous range with precision control
• Custom domains: m.ints(vec![values]) - specific integer values only
• Boolean variables: m.bool() - equivalent to m.int(0, 1)

Constraint Types

• Arithmetic: +, -, *, /, %, abs(), min(), max(), sum()
• Comparison: ==, !=, <, <=, >, >=
• Boolean logic: and(), or(), not()
• Global constraints: alldiff()

post() - Post a mathematical constraint to the model

Supported constraint patterns:

Basic comparisons: var op var, var op literal, var op (expr), var op int(value), var op float(value)

Arithmetic: var op var +/- var, var op var */÷ var, var op var % divisor

Functions: func(var) op target where func is abs, min, max, sum

Boolean: and(vars...), or(vars...), not(var)

Global: alldiff([vars...])

Multiplication with constants: target op var * int(value), target op var * float(value)

Where op is any of: ==, !=, <, <=, >, >=

postall() - Post multiple constraints to the model in a single call

Accepts comma-separated constraint expressions, each following the same patterns as post!:

Basic comparisons: var op var, var op literal, var op (expr), var op int(value), var op float(value)

Arithmetic: var op var +/- var, var op var */÷ var, var op var % divisor

Functions: func(var) op target where func is abs, min, max, sum

Boolean: and(vars...), or(vars...), not(var)

Global: alldiff([vars...])

Multiplication with constants: target op var * int(value), target op var * float(value)

Where op is any of: ==, !=, <, <=, >, >=

Example 1: Basic Integer Problem

use cspsolver::prelude::*;

let mut m = Model::default();
let x = m.int(1, 10);
let y = m.int(1, 10);

post!(m, x + y == int(12));
post!(m, x > y);

if let Ok(solution) = m.solve() {
    println!("x = {:?}, y = {:?}", solution[x], solution[y]);
}

Example 2: Mixed Integer-Float Optimization

use cspsolver::prelude::*;

let mut m = Model::default();
let items = m.int(1, 100);        // Number of items
let cost = m.float(0.0, 1000.0);  // Total cost

post!(m, cost == items * float(12.5));  // $12.50 per item
post!(m, cost <= float(500.0));         // Budget constraint

// Maximize number of items within budget
if let Ok(solution) = m.maximize(items) {
    println!("Optimal: {:?} items, cost: {:?}", 
             solution[items], solution[cost]);
}

Example 3: Custom Domains and Global Constraints

use cspsolver::prelude::*;

let mut m = Model::default();
 
// Variables with custom domains
let red = m.ints(vec![1, 3, 5, 7]);      // Odd numbers
let blue = m.ints(vec![2, 4, 6, 8]);     // Even numbers  
let green = m.ints(vec![2, 3, 5, 7]);    // Prime numbers

// All must be different
post!(m, alldiff([red, blue, green]));

if let Ok(solution) = m.solve() {
    println!("Red: {:?}, Blue: {:?}, Green: {:?}",
             solution[red], solution[blue], solution[green]);
}

Modules

boolean_operators

Operator overloads for VarId to provide clean syntax.

config

Configuration system for the CSP solver

error

model

prelude

Prelude module for CSP solver

solution

vars