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>
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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.