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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

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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:
```lux
fn name(param1: Type1, param2: Type2): ReturnType = body
```
Examples:
```lux
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 `=`:
```lux
fn square(x: Int): Int = x * x
```
Complex functions use `= { ... }`:
```lux
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:
```lux
fn add(a: Int, b: Int) = a + b // Returns Int
fn not(b: Bool) = !b // Returns Bool
```
But parameter types are always required:
```lux
fn double(x) = x * 2 // Error: parameter type required
```
## Anonymous Functions (Lambdas)
Functions without names:
```lux
fn(x: Int): Int => x * 2
```
Used with higher-order functions:
```lux
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:
```lux
let double = fn(x: Int): Int => x * 2
double(5) // 10
```
## Higher-Order Functions
Functions that take or return functions:
```lux
// 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:
```lux
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:
```lux
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:
```lux
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:
```lux
// 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:
```lux
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:
```lux
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:
```lux
// 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:
```lux
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:
```lux
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:
```lux
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
```lux
// 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](04-data-types.md) - Algebraic data types and pattern matching.