Files
lux/docs/guide/03-functions.md
Brandon Lucas 44f88afcf8 docs: add comprehensive language documentation
Documentation structure inspired by Rust Book, Elm Guide, and others:

Guide (10 chapters):
- Introduction and setup
- Basic types (Int, String, Bool, List, Option, Result)
- Functions (closures, higher-order, composition)
- Data types (ADTs, pattern matching, records)
- Effects (the core innovation)
- Handlers (patterns and techniques)
- Modules (imports, exports, organization)
- Error handling (Fail, Option, Result)
- Standard library reference
- Advanced topics (traits, generics, optimization)

Reference:
- Complete syntax reference

Tutorials:
- Calculator (parsing, evaluation, REPL)
- Dependency injection (testing with effects)
- Project ideas (16 projects by difficulty)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-13 17:43:41 -05:00

4.9 KiB

Chapter 3: Functions

Functions are the building blocks of Lux programs. They're first-class values—you can pass them around, return them, and store them in data structures.

Defining Functions

Basic syntax:

fn name(param1: Type1, param2: Type2): ReturnType = body

Examples:

fn add(a: Int, b: Int): Int = a + b

fn greet(name: String): String = "Hello, " + name

fn isEven(n: Int): Bool = n % 2 == 0

Single Expression vs Block Body

Simple functions use =:

fn square(x: Int): Int = x * x

Complex functions use = { ... }:

fn classify(n: Int): String = {
    let abs_n = if n < 0 then -n else n
    if abs_n == 0 then "zero"
    else if abs_n < 10 then "small"
    else "large"
}

The last expression in a block is the return value. No return keyword needed.

Type Inference

Return types can often be inferred:

fn add(a: Int, b: Int) = a + b  // Returns Int
fn not(b: Bool) = !b            // Returns Bool

But parameter types are always required:

fn double(x) = x * 2  // Error: parameter type required

Anonymous Functions (Lambdas)

Functions without names:

fn(x: Int): Int => x * 2

Used with higher-order functions:

List.map([1, 2, 3], fn(x: Int): Int => x * 2)  // [2, 4, 6]

List.filter([1, 2, 3, 4], fn(x: Int): Bool => x > 2)  // [3, 4]

Store in variables:

let double = fn(x: Int): Int => x * 2
double(5)  // 10

Higher-Order Functions

Functions that take or return functions:

// Takes a function
fn apply(f: fn(Int): Int, x: Int): Int = f(x)

apply(fn(x: Int): Int => x + 1, 5)  // 6

// Returns a function
fn makeAdder(n: Int): fn(Int): Int =
    fn(x: Int): Int => x + n

let add10 = makeAdder(10)
add10(5)   // 15
add10(20)  // 30

Closures

Functions capture their environment:

fn counter(): fn(): Int with {State} = {
    let count = 0
    fn(): Int with {State} => {
        State.put(State.get() + 1)
        State.get()
    }
}

// The returned function remembers `count`

More practical example:

fn makeMultiplier(factor: Int): fn(Int): Int =
    fn(x: Int): Int => x * factor

let triple = makeMultiplier(3)
triple(4)  // 12
triple(7)  // 21

Recursion

Functions can call themselves:

fn factorial(n: Int): Int =
    if n <= 1 then 1
    else n * factorial(n - 1)

factorial(5)  // 120

Tail Call Optimization

Lux optimizes tail-recursive functions:

// Not tail-recursive (stack grows)
fn factorial(n: Int): Int =
    if n <= 1 then 1
    else n * factorial(n - 1)  // Must multiply AFTER recursive call

// Tail-recursive (constant stack)
fn factorialTail(n: Int, acc: Int): Int =
    if n <= 1 then acc
    else factorialTail(n - 1, n * acc)  // Recursive call is LAST operation

fn factorial(n: Int): Int = factorialTail(n, 1)

The tail-recursive version won't overflow the stack.

Function Composition

Combine functions:

fn compose<A, B, C>(f: fn(B): C, g: fn(A): B): fn(A): C =
    fn(x: A): C => f(g(x))

fn addOne(x: Int): Int = x + 1
fn double(x: Int): Int = x * 2

let addOneThenDouble = compose(double, addOne)
addOneThenDouble(5)  // 12 = (5 + 1) * 2

Partial Application

Create new functions by fixing some arguments:

fn add(a: Int, b: Int): Int = a + b

// Manually partial apply
fn add5(b: Int): Int = add(5, b)

add5(3)  // 8

Pipeline Style

Chain operations readably:

// Without pipeline
toString(List.sum(List.map(List.filter([1,2,3,4,5], isEven), square)))

// With intermediate variables
let nums = [1, 2, 3, 4, 5]
let evens = List.filter(nums, isEven)
let squared = List.map(evens, square)
let total = List.sum(squared)
toString(total)

Functions with Effects

Functions that perform effects declare them:

fn pureAdd(a: Int, b: Int): Int = a + b  // No effects

fn printAdd(a: Int, b: Int): Unit with {Console} = {
    let sum = a + b
    Console.print("Sum: " + toString(sum))
}

Effects propagate:

fn helper(): Int with {Console} = {
    Console.print("Computing...")
    42
}

// Must also declare Console since it calls helper
fn main(): Int with {Console} = {
    let x = helper()
    x * 2
}

Generic Functions

Functions that work with any type:

fn identity<T>(x: T): T = x

identity(42)       // 42
identity("hello")  // "hello"
identity(true)     // true

fn pair<A, B>(a: A, b: B): (A, B) = (a, b)

pair(1, "one")  // (1, "one")

Summary

// Basic function
fn name(param: Type): Return = body

// Lambda
fn(x: Int): Int => x * 2

// Higher-order (takes function)
fn apply(f: fn(Int): Int, x: Int): Int = f(x)

// Higher-order (returns function)
fn makeAdder(n: Int): fn(Int): Int = fn(x: Int): Int => x + n

// Generic
fn identity<T>(x: T): T = x

// With effects
fn greet(name: String): Unit with {Console} = Console.print("Hi " + name)

Next

Chapter 4: Data Types - Algebraic data types and pattern matching.