rust/doc/tutorial.md

% The Rust Language Tutorial

Introduction

Rust is a programming language with a focus on type safety, memory safety, concurrency and performance. It is intended for writing large-scale, high-performance software that is free from several classes of common errors. Rust has a sophisticated memory model that encourages efficient data structures and safe concurrency patterns, forbidding invalid memory accesses that would otherwise cause segmentation faults. It is statically typed and compiled ahead of time.

As a multi-paradigm language, Rust supports writing code in procedural, functional and object-oriented styles. Some of its pleasant high-level features include:

• Type inference. Type annotations on local variable declarations are optional.
• Safe task-based concurrency. Rust's lightweight tasks do not share memory, instead communicating through messages.
• Higher-order functions. Efficient and flexible closures provide iteration and other control structures
• Pattern matching and algebraic data types. Pattern matching on Rust's enumeration types (a more powerful version of C's enums, similar to algebraic data types in functional languages) is a compact and expressive way to encode program logic.
• Polymorphism. Rust has type-parametric functions and types, type classes and OO-style interfaces.

Scope

This is an introductory tutorial for the Rust programming language. It covers the fundamentals of the language, including the syntax, the type system and memory model, generics, and modules. Additional tutorials cover specific language features in greater depth.

This tutorial assumes that the reader is already familiar with one or more languages in the C family. Understanding of pointers and general memory management techniques will help.

Conventions

Throughout the tutorial, language keywords and identifiers defined in example code are displayed in code font.

Code snippets are indented, and also shown in a monospaced font. Not all snippets constitute whole programs. For brevity, we'll often show fragments of programs that don't compile on their own. To try them out, you might have to wrap them in fn main() { ... }, and make sure they don't contain references to names that aren't actually defined.

Warning: Rust is a language under ongoing development. Notes about potential changes to the language, implementation deficiencies, and other caveats appear offset in blockquotes.

Getting started

The Rust compiler currently must be built from a tarball, unless you are on Windows, in which case using the installer is recommended.

Since the Rust compiler is written in Rust, it must be built by a precompiled "snapshot" version of itself (made in an earlier state of development). The source build automatically fetches these snapshots from the Internet on our supported platforms.

Snapshot binaries are currently built and tested on several platforms:

• Windows (7, Server 2008 R2), x86 only
• Linux (various distributions), x86 and x86-64
• OSX 10.6 ("Snow Leopard") or greater, x86 and x86-64

You may find that other platforms work, but these are our "tier 1" supported build environments that are most likely to work.

Note: Windows users should read the detailed "getting started" notes on the wiki. Even when using the binary installer, the Windows build requires a MinGW installation, the precise details of which are not discussed here. Finally, rustc may need to be referred to as rustc.exe. It's a bummer, we know.

To build from source you will also need the following prerequisite packages:

• g++ 4.4 or clang++ 3.x
• python 2.6 or later (but not 3.x)
• perl 5.0 or later
• gnu make 3.81 or later
• curl

If you've fulfilled those prerequisites, something along these lines should work.

$ curl -O http://static.rust-lang.org/dist/rust-0.8.tar.gz
$ tar -xzf rust-0.8.tar.gz
$ cd rust-0.8
$ ./configure
$ make && make install

You may need to use sudo make install if you do not normally have permission to modify the destination directory. The install locations can be adjusted by passing a --prefix argument to configure. Various other options are also supported: pass --help for more information on them.

When complete, make install will place several programs into /usr/local/bin: rustc, the Rust compiler; rustdoc, the API-documentation tool; rustpkg, the Rust package manager; rusti, the Rust REPL; and rust, a tool which acts both as a unified interface for them, and for a few common command line scenarios.

Compiling your first program

Rust program files are, by convention, given the extension .rs. Say we have a file hello.rs containing this program:

fn main() {
    println("hello?");
}

If the Rust compiler was installed successfully, running rustc hello.rs will produce an executable called hello (or hello.exe on Windows) which, upon running, will likely do exactly what you expect.

The Rust compiler tries to provide useful information when it encounters an error. If you introduce an error into the program (for example, by changing println to some nonexistent function), and then compile it, you'll see an error message like this:

hello.rs:2:4: 2:16 error: unresolved name: print_with_unicorns
hello.rs:2     print_with_unicorns("hello?");
               ^~~~~~~~~~~~~~~~~~~~~~~

In its simplest form, a Rust program is a .rs file with some types and functions defined in it. If it has a main function, it can be compiled to an executable. Rust does not allow code that's not a declaration to appear at the top level of the file: all statements must live inside a function. Rust programs can also be compiled as libraries, and included in other programs.

Using the rust tool

While using rustc directly to generate your executables, and then running them manually is a perfectly valid way to test your code, for smaller projects, prototypes, or if you're a beginner, it might be more convenient to use the rust tool.

The rust tool provides central access to the other rust tools, as well as handy shortcuts for directly running source files. For example, if you have a file foo.rs in your current directory, rust run foo.rs would attempt to compile it and, if successful, directly run the resulting binary.

To get a list of all available commands, simply call rust without any argument.

Editing Rust code

There are vim highlighting and indentation scripts in the Rust source distribution under src/etc/vim/. There is an emacs mode under src/etc/emacs/ called rust-mode, but do read the instructions included in that directory. In particular, if you are running emacs 24, then using emacs's internal package manager to install rust-mode is the easiest way to keep it up to date. There is also a package for Sublime Text 2, available both standalone and through Sublime Package Control, and support for Kate under src/etc/kate.

There is ctags support via src/etc/ctags.rust, but many other tools and editors are not yet supported. If you end up writing a Rust mode for your favorite editor, let us know so that we can link to it.

Syntax basics

Assuming you've programmed in any C-family language (C++, Java, JavaScript, C#, or PHP), Rust will feel familiar. Code is arranged in blocks delineated by curly braces; there are control structures for branching and looping, like the familiar if and while; function calls are written myfunc(arg1, arg2); operators are written the same and mostly have the same precedence as in C; comments are again like C; module names are separated with double-colon (::) as with C++.

The main surface difference to be aware of is that the condition at the head of control structures like if and while does not require parentheses, while their bodies must be wrapped in braces. Single-statement, unbraced bodies are not allowed.

# mod universe { pub fn recalibrate() -> bool { true } }
fn main() {
    /* A simple loop */
    loop {
        // A tricky calculation
        if universe::recalibrate() {
            return;
        }
    }
}

The let keyword introduces a local variable. Variables are immutable by default. To introduce a local variable that you can re-assign later, use let mut instead.

let hi = "hi";
let mut count = 0;

while count < 10 {
    println(fmt!("count: %?", count));
    count += 1;
}

Although Rust can almost always infer the types of local variables, you can specify a variable's type by following it with a colon, then the type name. Static items, on the other hand, always require a type annotation.

static MONSTER_FACTOR: float = 57.8;
let monster_size = MONSTER_FACTOR * 10.0;
let monster_size: int = 50;

Local variables may shadow earlier declarations, as in the previous example: monster_size was first declared as a float, and then a second monster_size was declared as an int. If you were to actually compile this example, though, the compiler would determine that the first monster_size is unused and issue a warning (because this situation is likely to indicate a programmer error). For occasions where unused variables are intentional, their names may be prefixed with an underscore to silence the warning, like let _monster_size = 50;.

Rust identifiers start with an alphabetic character or an underscore, and after that may contain any sequence of alphabetic characters, numbers, or underscores. The preferred style is to write function, variable, and module names with lowercase letters, using underscores where they help readability, while writing types in camel case.

let my_variable = 100;
type MyType = int;     // primitive types are _not_ camel case

Expressions and semicolons

Though it isn't apparent in all code, there is a fundamental difference between Rust's syntax and predecessors like C. Many constructs that are statements in C are expressions in Rust, allowing code to be more concise. For example, you might write a piece of code like this:

# let item = "salad";
let price;
if item == "salad" {
    price = 3.50;
} else if item == "muffin" {
    price = 2.25;
} else {
    price = 2.00;
}

But, in Rust, you don't have to repeat the name price:

# let item = "salad";
let price =
    if item == "salad" {
        3.50
    } else if item == "muffin" {
        2.25
    } else {
        2.00
    };

Both pieces of code are exactly equivalent: they assign a value to price depending on the condition that holds. Note that there are no semicolons in the blocks of the second snippet. This is important: the lack of a semicolon after the last statement in a braced block gives the whole block the value of that last expression.

Put another way, the semicolon in Rust ignores the value of an expression. Thus, if the branches of the if had looked like { 4; }, the above example would simply assign () (nil or void) to price. But without the semicolon, each branch has a different value, and price gets the value of the branch that was taken.

In short, everything that's not a declaration (declarations are let for variables; fn for functions; and any top-level named items such as traits, enum types, and static items) is an expression, including function bodies.

fn is_four(x: int) -> bool {
   // No need for a return statement. The result of the expression
   // is used as the return value.
   x == 4
}

Primitive types and literals

There are general signed and unsigned integer types, int and uint, as well as 8-, 16-, 32-, and 64-bit variants, i8, u16, etc. Integers can be written in decimal (144), hexadecimal (0x90), or binary (0b10010000) base. Each integral type has a corresponding literal suffix that can be used to indicate the type of a literal: i for int, u for uint, i8 for the i8 type.

In the absence of an integer literal suffix, Rust will infer the integer type based on type annotations and function signatures in the surrounding program. In the absence of any type information at all, Rust will assume that an unsuffixed integer literal has type int.

let a = 1;       // a is an int
let b = 10i;     // b is an int, due to the 'i' suffix
let c = 100u;    // c is a uint
let d = 1000i32; // d is an i32

There are three floating-point types: float, f32, and f64. Floating-point numbers are written 0.0, 1e6, or 2.1e-4. Like integers, floating-point literals are inferred to the correct type. Suffixes f, f32, and f64 can be used to create literals of a specific type.

The keywords true and false produce literals of type bool.

Characters, the char type, are four-byte Unicode codepoints, whose literals are written between single quotes, as in 'x'. Just like C, Rust understands a number of character escapes, using the backslash character, such as \n, \r, and \t. String literals, written between double quotes, allow the same escape sequences. More on strings later.

The nil type, written (), has a single value, also written ().

Operators

Rust's set of operators contains very few surprises. Arithmetic is done with *, /, %, +, and - (multiply, quotient, remainder, add, and subtract). - is also a unary prefix operator that negates numbers. As in C, the bitwise operators >>, <<, &, |, and ^ are also supported.

Note that, if applied to an integer value, ! flips all the bits (like ~ in C).

The comparison operators are the traditional ==, !=, <, >, <=, and >=. Short-circuiting (lazy) boolean operators are written && (and) and || (or).

For type casting, Rust uses the binary as operator. It takes an expression on the left side and a type on the right side and will, if a meaningful conversion exists, convert the result of the expression to the given type.

let x: float = 4.0;
let y: uint = x as uint;
assert!(y == 4u);

Syntax extensions

Syntax extensions are special forms that are not built into the language, but are instead provided by the libraries. To make it clear to the reader when a name refers to a syntax extension, the names of all syntax extensions end with !. The standard library defines a few syntax extensions, the most useful of which is fmt!, a sprintf-style text formatter that you will often see in examples.

fmt! supports most of the directives that printf supports, but unlike printf, will give you a compile-time error when the types of the directives don't match the types of the arguments.

# let mystery_object = ();

println(fmt!("%s is %d", "the answer", 43));

// %? will conveniently print any type
println(fmt!("what is this thing: %?", mystery_object));

You can define your own syntax extensions with the macro system. For details, see the macro tutorial.

Control structures

Conditionals

We've seen if expressions a few times already. To recap, braces are compulsory, an if can have an optional else clause, and multiple if/else constructs can be chained together:

if false {
    println("that's odd");
} else if true {
    println("right");
} else {
    println("neither true nor false");
}

The condition given to an if construct must be of type bool (no implicit conversion happens). If the arms are blocks that have a value, this value must be of the same type for every arm in which control reaches the end of the block:

fn signum(x: int) -> int {
    if x < 0 { -1 }
    else if x > 0 { 1 }
    else { 0 }
}

Pattern matching

Rust's match construct is a generalized, cleaned-up version of C's switch construct. You provide it with a value and a number of arms, each labelled with a pattern, and the code compares the value against each pattern in order until one matches. The matching pattern executes its corresponding arm.

# let my_number = 1;
match my_number {
  0     => println("zero"),
  1 | 2 => println("one or two"),
  3..10 => println("three to ten"),
  _     => println("something else")
}

Unlike in C, there is no "falling through" between arms: only one arm executes, and it doesn't have to explicitly break out of the construct when it is finished.

A match arm consists of a pattern, then an arrow =>, followed by an action (expression). Literals are valid patterns and match only their own value. A single arm may match multiple different patterns by combining them with the pipe operator (|), so long as every pattern binds the same set of variables. Ranges of numeric literal patterns can be expressed with two dots, as in M..N. The underscore (_) is a wildcard pattern that matches any single value. The asterisk (*) is a different wildcard that can match one or more fields in an enum variant.

The patterns in a match arm are followed by a fat arrow, =>, then an expression to evaluate. Each case is separated by commas. It's often convenient to use a block expression for each case, in which case the commas are optional.

# let my_number = 1;
match my_number {
  0 => { println("zero") }
  _ => { println("something else") }
}

match constructs must be exhaustive: they must have an arm covering every possible case. For example, the typechecker would reject the previous example if the arm with the wildcard pattern was omitted.

A powerful application of pattern matching is destructuring: matching in order to bind names to the contents of data types.

Note: The following code makes use of tuples ((float, float)) which are explained in section 5.3. For now you can think of tuples as a list of items.

use std::float;
use std::num::atan;
fn angle(vector: (float, float)) -> float {
    let pi = float::consts::pi;
    match vector {
      (0f, y) if y < 0f => 1.5 * pi,
      (0f, y) => 0.5 * pi,
      (x, y) => atan(y / x)
    }
}

A variable name in a pattern matches any value, and binds that name to the value of the matched value inside of the arm's action. Thus, (0f, y) matches any tuple whose first element is zero, and binds y to the second element. (x, y) matches any two-element tuple, and binds both elements to variables.

Any match arm can have a guard clause (written if EXPR), called a pattern guard, which is an expression of type bool that determines, after the pattern is found to match, whether the arm is taken or not. The variables bound by the pattern are in scope in this guard expression. The first arm in the angle example shows an example of a pattern guard.

You've already seen simple let bindings, but let is a little fancier than you've been led to believe. It, too, supports destructuring patterns. For example, you can write this to extract the fields from a tuple, introducing two variables at once: a and b.

# fn get_tuple_of_two_ints() -> (int, int) { (1, 1) }
let (a, b) = get_tuple_of_two_ints();

Let bindings only work with irrefutable patterns: that is, patterns that can never fail to match. This excludes let from matching literals and most enum variants.

Loops

while denotes a loop that iterates as long as its given condition (which must have type bool) evaluates to true. Inside a loop, the keyword break aborts the loop, and loop aborts the current iteration and continues with the next.

let mut cake_amount = 8;
while cake_amount > 0 {
    cake_amount -= 1;
}

loop denotes an infinite loop, and is the preferred way of writing while true:

let mut x = 5u;
loop {
    x += x - 3;
    if x % 5 == 0 { break; }
    println(x.to_str());
}

This code prints out a weird sequence of numbers and stops as soon as it finds one that can be divided by five.

Data structures

Structs

Rust struct types must be declared before they are used using the struct syntax: struct Name { field1: T1, field2: T2 [, ...] }, where T1, T2, ... denote types. To construct a struct, use the same syntax, but leave off the struct: for example: Point { x: 1.0, y: 2.0 }.

Structs are quite similar to C structs and are even laid out the same way in memory (so you can read from a Rust struct in C, and vice-versa). Use the dot operator to access struct fields, as in mypoint.x.

struct Point {
    x: float,
    y: float
}

Inherited mutability means that any field of a struct may be mutable, if the struct is in a mutable slot (or a field of a struct in a mutable slot, and so forth).

With a value (say, mypoint) of such a type in a mutable location, you can do mypoint.y += 1.0. But in an immutable location, such an assignment to a struct without inherited mutability would result in a type error.

# struct Point { x: float, y: float }
let mut mypoint = Point { x: 1.0, y: 1.0 };
let origin = Point { x: 0.0, y: 0.0 };

mypoint.y += 1.0; // mypoint is mutable, and its fields as well
origin.y += 1.0; // ERROR: assigning to immutable field

match patterns destructure structs. The basic syntax is Name { fieldname: pattern, ... }:

# struct Point { x: float, y: float }
# let mypoint = Point { x: 0.0, y: 0.0 };
match mypoint {
    Point { x: 0.0, y: yy } => { println(yy.to_str());                     }
    Point { x: xx,  y: yy } => { println(xx.to_str() + " " + yy.to_str()); }
}

In general, the field names of a struct do not have to appear in the same order they appear in the type. When you are not interested in all the fields of a struct, a struct pattern may end with , _ (as in Name { field1, _ }) to indicate that you're ignoring all other fields. Additionally, struct fields have a shorthand matching form that simply reuses the field name as the binding name.

# struct Point { x: float, y: float }
# let mypoint = Point { x: 0.0, y: 0.0 };
match mypoint {
    Point { x, _ } => { println(x.to_str()) }
}

Enums

Enums are datatypes that have several alternate representations. For example, consider the type shown earlier:

# struct Point { x: float, y: float }
enum Shape {
    Circle(Point, float),
    Rectangle(Point, Point)
}

A value of this type is either a Circle, in which case it contains a Point struct and a float, or a Rectangle, in which case it contains two Point structs. The run-time representation of such a value includes an identifier of the actual form that it holds, much like the "tagged union" pattern in C, but with better static guarantees.

The above declaration will define a type Shape that can refer to such shapes, and two functions, Circle and Rectangle, which can be used to construct values of the type (taking arguments of the specified types). So Circle(Point { x: 0f, y: 0f }, 10f) is the way to create a new circle.

Enum variants need not have parameters. This enum declaration, for example, is equivalent to a C enum:

enum Direction {
    North,
    East,
    South,
    West
}

This declaration defines North, East, South, and West as constants, all of which have type Direction.

When an enum is C-like (that is, when none of the variants have parameters), it is possible to explicitly set the discriminator values to a constant value:

enum Color {
  Red = 0xff0000,
  Green = 0x00ff00,
  Blue = 0x0000ff
}

If an explicit discriminator is not specified for a variant, the value defaults to the value of the previous variant plus one. If the first variant does not have a discriminator, it defaults to 0. For example, the value of North is 0, East is 1, South is 2, and West is 3.

When an enum is C-like, you can apply the as cast operator to convert it to its discriminator value as an int.

For enum types with multiple variants, destructuring is the only way to get at their contents. All variant constructors can be used as patterns, as in this definition of area:

use std::float;
# struct Point {x: float, y: float}
# enum Shape { Circle(Point, float), Rectangle(Point, Point) }
fn area(sh: Shape) -> float {
    match sh {
        Circle(_, size) => float::consts::pi * size * size,
        Rectangle(Point { x, y }, Point { x: x2, y: y2 }) => (x2 - x) * (y2 - y)
    }
}

You can write a lone _ to ignore an individual field, and can ignore all fields of a variant like: Circle(*). As in their introduction form, nullary enum patterns are written without parentheses.

# struct Point { x: float, y: float }
# enum Direction { North, East, South, West }
fn point_from_direction(dir: Direction) -> Point {
    match dir {
        North => Point { x:  0f, y:  1f },
        East  => Point { x:  1f, y:  0f },
        South => Point { x:  0f, y: -1f },
        West  => Point { x: -1f, y:  0f }
    }
}

Enum variants may also be structs. For example:

use std::float;
# struct Point { x: float, y: float }
# fn square(x: float) -> float { x * x }
enum Shape {
    Circle { center: Point, radius: float },
    Rectangle { top_left: Point, bottom_right: Point }
}
fn area(sh: Shape) -> float {
    match sh {
        Circle { radius: radius, _ } => float::consts::pi * square(radius),
        Rectangle { top_left: top_left, bottom_right: bottom_right } => {
            (bottom_right.x - top_left.x) * (bottom_right.y - top_left.y)
        }
    }
}

Tuples

Tuples in Rust behave exactly like structs, except that their fields do not have names. Thus, you cannot access their fields with dot notation. Tuples can have any arity except for 0 (though you may consider unit, (), as the empty tuple if you like).

let mytup: (int, int, float) = (10, 20, 30.0);
match mytup {
  (a, b, c) => info!(a + b + (c as int))
}

Tuple structs

Rust also has tuple structs, which behave like both structs and tuples, except that, unlike tuples, tuple structs have names (so Foo(1, 2) has a different type from Bar(1, 2)), and tuple structs' fields do not have names.

For example:

struct MyTup(int, int, float);
let mytup: MyTup = MyTup(10, 20, 30.0);
match mytup {
  MyTup(a, b, c) => info!(a + b + (c as int))
}

There is a special case for tuple structs with a single field, which are sometimes called "newtypes" (after Haskell's "newtype" feature). These are used to define new types in such a way that the new name is not just a synonym for an existing type but is rather its own distinct type.

struct GizmoId(int);

For convenience, you can extract the contents of such a struct with the dereference (*) unary operator:

# struct GizmoId(int);
let my_gizmo_id: GizmoId = GizmoId(10);
let id_int: int = *my_gizmo_id;

Types like this can be useful to differentiate between data that have the same type but must be used in different ways.

struct Inches(int);
struct Centimeters(int);

The above definitions allow for a simple way for programs to avoid confusing numbers that correspond to different units.

Functions

We've already seen several function definitions. Like all other static declarations, such as type, functions can be declared both at the top level and inside other functions (or in modules, which we'll come back to later). The fn keyword introduces a function. A function has an argument list, which is a parenthesized list of expr: type pairs separated by commas. An arrow -> separates the argument list and the function's return type.

fn line(a: int, b: int, x: int) -> int {
    return a * x + b;
}

The return keyword immediately returns from the body of a function. It is optionally followed by an expression to return. A function can also return a value by having its top-level block produce an expression.

fn line(a: int, b: int, x: int) -> int {
    a * x + b
}

It's better Rust style to write a return value this way instead of writing an explicit return. The utility of return comes in when returning early from a function. Functions that do not return a value are said to return nil, (), and both the return type and the return value may be omitted from the definition. The following two functions are equivalent.

fn do_nothing_the_hard_way() -> () { return (); }

fn do_nothing_the_easy_way() { }

Ending the function with a semicolon like so is equivalent to returning ().

fn line(a: int, b: int, x: int) -> int { a * x + b  }
fn oops(a: int, b: int, x: int) -> ()  { a * x + b; }

assert!(8 == line(5, 3, 1));
assert!(() == oops(5, 3, 1));

As with match expressions and let bindings, function arguments support pattern destructuring. Like let, argument patterns must be irrefutable, as in this example that unpacks the first value from a tuple and returns it.

fn first((value, _): (int, float)) -> int { value }

Destructors

A destructor is a function responsible for cleaning up the resources used by an object when it is no longer accessible. Destructors can be defined to handle the release of resources like files, sockets and heap memory.

Objects are never accessible after their destructor has been called, so there are no dynamic failures from accessing freed resources. When a task fails, the destructors of all objects in the task are called.

The ~ sigil represents a unique handle for a memory allocation on the heap:

{
    // an integer allocated on the heap
    let y = ~10;
}
// the destructor frees the heap memory as soon as `y` goes out of scope

Rust includes syntax for heap memory allocation in the language since it's commonly used, but the same semantics can be implemented by a type with a custom destructor.

Ownership

Rust formalizes the concept of object ownership to delegate management of an object's lifetime to either a variable or a task-local garbage collector. An object's owner is responsible for managing the lifetime of the object by calling the destructor, and the owner determines whether the object is mutable.

Ownership is recursive, so mutability is inherited recursively and a destructor destroys the contained tree of owned objects. Variables are top-level owners and destroy the contained object when they go out of scope. A box managed by the garbage collector starts a new ownership tree, and the destructor is called when it is collected.

// the struct owns the objects contained in the `x` and `y` fields
struct Foo { x: int, y: ~int }

{
    // `a` is the owner of the struct, and thus the owner of the struct's fields
    let a = Foo { x: 5, y: ~10 };
}
// when `a` goes out of scope, the destructor for the `~int` in the struct's
// field is called

// `b` is mutable, and the mutability is inherited by the objects it owns
let mut b = Foo { x: 5, y: ~10 };
b.x = 10;

If an object doesn't contain garbage-collected boxes, it consists of a single ownership tree and is given the Owned trait which allows it to be sent between tasks. Custom destructors can only be implemented directly on types that are Owned, but garbage-collected boxes can still contain types with custom destructors.

Boxes

Many modern languages represent values as pointers to heap memory by default. In contrast, Rust, like C and C++, represents such types directly. Another way to say this is that aggregate data in Rust are unboxed. This means that if you let x = Point { x: 1f, y: 1f };, you are creating a struct on the stack. If you then copy it into a data structure, you copy the entire struct, not just a pointer.

For small structs like Point, this is usually more efficient than allocating memory and indirecting through a pointer. But for big structs, or mutable state, it can be useful to have a single copy on the stack or on the heap, and refer to that through a pointer.

Owned boxes

An owned box (~) is a uniquely owned allocation on the heap. It inherits the mutability and lifetime of the owner as it would if there was no box:

let x = 5; // immutable
let mut y = 5; // mutable
y += 2;

let x = ~5; // immutable
let mut y = ~5; // mutable
*y += 2; // the * operator is needed to access the contained value

The purpose of an owned box is to add a layer of indirection in order to create recursive data structures or cheaply pass around an object larger than a pointer. Since an owned box has a unique owner, it can only be used to represent a tree data structure.

The following struct won't compile, because the lack of indirection would mean it has an infinite size:

struct Foo {
    child: Option<Foo>
}

Note: The Option type is an enum that represents an optional value. It's comparable to a nullable pointer in many other languages, but stores the contained value unboxed.

Adding indirection with an owned pointer allocates the child outside of the struct on the heap, which makes it a finite size and won't result in a compile-time error:

struct Foo {
    child: Option<~Foo>
}

Managed boxes

A managed box (@) is a heap allocation with the lifetime managed by a task-local garbage collector. It will be destroyed at some point after there are no references left to the box, no later than the end of the task. Managed boxes lack an owner, so they start a new ownership tree and don't inherit mutability. They do own the contained object, and mutability is defined by the type of the managed box (@ or @mut). An object containing a managed box is not Owned, and can't be sent between tasks.

let a = @5; // immutable

let mut b = @5; // mutable variable, immutable box
b = @10;

let c = @mut 5; // immutable variable, mutable box
*c = 10;

let mut d = @mut 5; // mutable variable, mutable box
*d += 5;
d = @mut 15;

A mutable variable and an immutable variable can refer to the same box, given that their types are compatible. Mutability of a box is a property of its type, however, so for example a mutable handle to an immutable box cannot be assigned a reference to a mutable box.

let a = @1;     // immutable box
let b = @mut 2; // mutable box

let mut c : @int;       // declare a variable with type managed immutable int
let mut d : @mut int;   // and one of type managed mutable int

c = a;          // box type is the same, okay
d = b;          // box type is the same, okay

// but b cannot be assigned to c, or a to d
c = b;          // error

Move semantics

Rust uses a shallow copy for parameter passing, assignment and returning values from functions. A shallow copy is considered a move of ownership if the ownership tree of the copied value includes an owned box or a type with a custom destructor. After a value has been moved, it can no longer be used from the source location and will not be destroyed there.

let x = ~5;
let y = x.clone(); // y is a newly allocated box
let z = x; // no new memory allocated, x can no longer be used

Since in owned boxes mutability is a property of the owner, not the box, mutable boxes may become immutable when they are moved, and vice-versa.

let r = ~13;
let mut s = r; // box becomes mutable
*s += 1;
let t = s; // box becomes immutable

Borrowed pointers

Rust's borrowed pointers are a general purpose reference type. In contrast with owned boxes, where the holder of an owned box is the owner of the pointed-to memory, borrowed pointers never imply ownership. A pointer can be borrowed to any object, and the compiler verifies that it cannot outlive the lifetime of the object.

As an example, consider a simple struct type, Point:

struct Point {
    x: float,
    y: float
}

We can use this simple definition to allocate points in many different ways. For example, in this code, each of these three local variables contains a point, but allocated in a different location:

# struct Point { x: float, y: float }
let on_the_stack : Point  =  Point { x: 3.0, y: 4.0 };
let managed_box  : @Point = @Point { x: 5.0, y: 1.0 };
let owned_box    : ~Point = ~Point { x: 7.0, y: 9.0 };

Suppose we want to write a procedure that computes the distance between any two points, no matter where they are stored. For example, we might like to compute the distance between on_the_stack and managed_box, or between managed_box and owned_box. One option is to define a function that takes two arguments of type point—that is, it takes the points by value. But this will cause the points to be copied when we call the function. For points, this is probably not so bad, but often copies are expensive. So we’d like to define a function that takes the points by pointer. We can use borrowed pointers to do this:

# struct Point { x: float, y: float }
# fn sqrt(f: float) -> float { 0f }
fn compute_distance(p1: &Point, p2: &Point) -> float {
    let x_d = p1.x - p2.x;
    let y_d = p1.y - p2.y;
    sqrt(x_d * x_d + y_d * y_d)
}

Now we can call compute_distance() in various ways:

# struct Point{ x: float, y: float };
# let on_the_stack : Point  =  Point { x: 3.0, y: 4.0 };
# let managed_box  : @Point = @Point { x: 5.0, y: 1.0 };
# let owned_box    : ~Point = ~Point { x: 7.0, y: 9.0 };
# fn compute_distance(p1: &Point, p2: &Point) -> float { 0f }
compute_distance(&on_the_stack, managed_box);
compute_distance(managed_box, owned_box);

Here the & operator is used to take the address of the variable on_the_stack; this is because on_the_stack has the type Point (that is, a struct value) and we have to take its address to get a value. We also call this borrowing the local variable on_the_stack, because we are creating an alias: that is, another route to the same data.

In the case of the boxes managed_box and owned_box, however, no explicit action is necessary. The compiler will automatically convert a box like @point or ~point to a borrowed pointer like &point. This is another form of borrowing; in this case, the contents of the managed/owned box are being lent out.

Whenever a value is borrowed, there are some limitations on what you can do with the original. For example, if the contents of a variable have been lent out, you cannot send that variable to another task, nor will you be permitted to take actions that might cause the borrowed value to be freed or to change its type. This rule should make intuitive sense: you must wait for a borrowed value to be returned (that is, for the borrowed pointer to go out of scope) before you can make full use of it again.

For a more in-depth explanation of borrowed pointers, read the borrowed pointer tutorial.

Freezing

Borrowing an immutable pointer to an object freezes it and prevents mutation. Owned objects have freezing enforced statically at compile-time.

let mut x = 5;
{
    let y = &x; // x is now frozen, it cannot be modified
}
// x is now unfrozen again
# x = 3;

Mutable managed boxes handle freezing dynamically when any of their contents are borrowed, and the task will fail if an attempt to modify them is made while they are frozen:

let x = @mut 5;
let y = x;
{
    let z = &*y; // the managed box is now frozen
    // modifying it through x or y will cause a task failure
}
// the box is now unfrozen again

Dereferencing pointers

Rust uses the unary star operator (*) to access the contents of a box or pointer, similarly to C.

let managed = @10;
let owned = ~20;
let borrowed = &30;

let sum = *managed + *owned + *borrowed;

Dereferenced mutable pointers may appear on the left hand side of assignments. Such an assignment modifies the value that the pointer points to.

let managed = @mut 10;
let mut owned = ~20;

let mut value = 30;
let borrowed = &mut value;

*managed = *owned + 10;
*owned = *borrowed + 100;
*borrowed = *managed + 1000;

Pointers have high operator precedence, but lower precedence than the dot operator used for field and method access. This precedence order can sometimes make code awkward and parenthesis-filled.

# struct Point { x: float, y: float }
# enum Shape { Rectangle(Point, Point) }
# impl Shape { fn area(&self) -> int { 0 } }
let start = @Point { x: 10f, y: 20f };
let end = ~Point { x: (*start).x + 100f, y: (*start).y + 100f };
let rect = &Rectangle(*start, *end);
let area = (*rect).area();

To combat this ugliness the dot operator applies automatic pointer dereferencing to the receiver (the value on the left-hand side of the dot), so in most cases, explicitly dereferencing the receiver is not necessary.

# struct Point { x: float, y: float }
# enum Shape { Rectangle(Point, Point) }
# impl Shape { fn area(&self) -> int { 0 } }
let start = @Point { x: 10f, y: 20f };
let end = ~Point { x: start.x + 100f, y: start.y + 100f };
let rect = &Rectangle(*start, *end);
let area = rect.area();

You can write an expression that dereferences any number of pointers automatically. For example, if you feel inclined, you could write something silly like

# struct Point { x: float, y: float }
let point = &@~Point { x: 10f, y: 20f };
println(fmt!("%f", point.x));

The indexing operator ([]) also auto-dereferences.

Vectors and strings

A vector is a contiguous section of memory containing zero or more values of the same type. Like other types in Rust, vectors can be stored on the stack, the local heap, or the exchange heap. Borrowed pointers to vectors are also called 'slices'.

# enum Crayon {
#     Almond, AntiqueBrass, Apricot,
#     Aquamarine, Asparagus, AtomicTangerine,
#     BananaMania, Beaver, Bittersweet,
#     Black, BlizzardBlue, Blue
# }
// A fixed-size stack vector
let stack_crayons: [Crayon, ..3] = [Almond, AntiqueBrass, Apricot];

// A borrowed pointer to stack-allocated vector
let stack_crayons: &[Crayon] = &[Aquamarine, Asparagus, AtomicTangerine];

// A local heap (managed) vector of crayons
let local_crayons: @[Crayon] = @[BananaMania, Beaver, Bittersweet];

// An exchange heap (owned) vector of crayons
let exchange_crayons: ~[Crayon] = ~[Black, BlizzardBlue, Blue];

The + operator means concatenation when applied to vector types.

# enum Crayon { Almond, AntiqueBrass, Apricot,
#               Aquamarine, Asparagus, AtomicTangerine,
#               BananaMania, Beaver, Bittersweet };
# impl Clone for Crayon {
#     fn clone(&self) -> Crayon {
#         *self
#     }
# }

let my_crayons = ~[Almond, AntiqueBrass, Apricot];
let your_crayons = ~[BananaMania, Beaver, Bittersweet];

// Add two vectors to create a new one
let our_crayons = my_crayons + your_crayons;

// .push_all() will append to a vector, provided it lives in a mutable slot
let mut my_crayons = my_crayons;
my_crayons.push_all(your_crayons);

Note: The above examples of vector addition use owned vectors. Some operations on slices and stack vectors are not yet well-supported. Owned vectors are often the most usable.

Square brackets denote indexing into a vector:

# enum Crayon { Almond, AntiqueBrass, Apricot,
#               Aquamarine, Asparagus, AtomicTangerine,
#               BananaMania, Beaver, Bittersweet };
# fn draw_scene(c: Crayon) { }
let crayons: [Crayon, ..3] = [BananaMania, Beaver, Bittersweet];
match crayons[0] {
    Bittersweet => draw_scene(crayons[0]),
    _ => ()
}

A vector can be destructured using pattern matching:

let numbers: &[int] = &[1, 2, 3];
let score = match numbers {
    [] => 0,
    [a] => a * 10,
    [a, b] => a * 6 + b * 4,
    [a, b, c, ..rest] => a * 5 + b * 3 + c * 2 + rest.len() as int
};

The elements of a vector inherit the mutability of the vector, and as such, individual elements may not be reassigned when the vector lives in an immutable slot.

# enum Crayon { Almond, AntiqueBrass, Apricot,
#               Aquamarine, Asparagus, AtomicTangerine,
#               BananaMania, Beaver, Bittersweet };
let crayons: ~[Crayon] = ~[BananaMania, Beaver, Bittersweet];

crayons[0] = Apricot; // ERROR: Can't assign to immutable vector

Moving it into a mutable slot makes the elements assignable.

# enum Crayon { Almond, AntiqueBrass, Apricot,
#               Aquamarine, Asparagus, AtomicTangerine,
#               BananaMania, Beaver, Bittersweet };
let crayons: ~[Crayon] = ~[BananaMania, Beaver, Bittersweet];

// Put the vector into a mutable slot
let mut mutable_crayons = crayons;

// Now it's mutable to the bone
mutable_crayons[0] = Apricot;

This is a simple example of Rust's dual-mode data structures, also referred to as freezing and thawing.

Strings are implemented with vectors of u8, though they have a distinct type. They support most of the same allocation options as vectors, though the string literal without a storage sigil (for example, "foo") is treated differently than a comparable vector ([foo]). Whereas plain vectors are stack-allocated fixed-length vectors, plain strings are borrowed pointers to read-only (static) memory. All strings are immutable.

// A plain string is a slice to read-only (static) memory
let stack_crayons: &str = "Almond, AntiqueBrass, Apricot";

// The same thing, but with the `&`
let stack_crayons: &str = &"Aquamarine, Asparagus, AtomicTangerine";

// A local heap (managed) string
let local_crayons: @str = @"BananaMania, Beaver, Bittersweet";

// An exchange heap (owned) string
let exchange_crayons: ~str = ~"Black, BlizzardBlue, Blue";

Both vectors and strings support a number of useful methods, defined in std::vec and std::str. Here are some examples.

# enum Crayon {
#     Almond, AntiqueBrass, Apricot,
#     Aquamarine, Asparagus, AtomicTangerine,
#     BananaMania, Beaver, Bittersweet
# }
# fn unwrap_crayon(c: Crayon) -> int { 0 }
# fn eat_crayon_wax(i: int) { }
# fn store_crayon_in_nasal_cavity(i: uint, c: Crayon) { }
# fn crayon_to_str(c: Crayon) -> &str { "" }

let crayons = [Almond, AntiqueBrass, Apricot];

// Check the length of the vector
assert!(crayons.len() == 3);
assert!(!crayons.is_empty());

// Iterate over a vector, obtaining a pointer to each element
// (`for` is explained in the container/iterator tutorial)
for crayon in crayons.iter() {
    let delicious_crayon_wax = unwrap_crayon(*crayon);
    eat_crayon_wax(delicious_crayon_wax);
}

// Map vector elements
let crayon_names = crayons.map(|v| crayon_to_str(*v));
let favorite_crayon_name = crayon_names[0];

// Remove whitespace from before and after the string
let new_favorite_crayon_name = favorite_crayon_name.trim();

if favorite_crayon_name.len() > 5 {
   // Create a substring
   println(favorite_crayon_name.slice_chars(0, 5));
}

Closures

Named functions, like those we've seen so far, may not refer to local variables declared outside the function: they do not close over their environment (sometimes referred to as "capturing" variables in their environment). For example, you couldn't write the following:

let foo = 10;

fn bar() -> int {
   return foo; // `bar` cannot refer to `foo`
}

Rust also supports closures, functions that can access variables in the enclosing scope.

fn call_closure_with_ten(b: &fn(int)) { b(10); }

let captured_var = 20;
let closure = |arg| println(fmt!("captured_var=%d, arg=%d", captured_var, arg));

call_closure_with_ten(closure);

Closures begin with the argument list between vertical bars and are followed by a single expression. Remember that a block, { <expr1>; <expr2>; ... }, is considered a single expression: it evaluates to the result of the last expression it contains if that expression is not followed by a semicolon, otherwise the block evaluates to ().

The types of the arguments are generally omitted, as is the return type, because the compiler can almost always infer them. In the rare case where the compiler needs assistance, though, the arguments and return types may be annotated.

let square = |x: int| -> uint { (x * x) as uint };

There are several forms of closure, each with its own role. The most common, called a stack closure, has type &fn and can directly access local variables in the enclosing scope.

let mut max = 0;
[1, 2, 3].map(|x| if *x > max { max = *x });

Stack closures are very efficient because their environment is allocated on the call stack and refers by pointer to captured locals. To ensure that stack closures never outlive the local variables to which they refer, stack closures are not first-class. That is, they can only be used in argument position; they cannot be stored in data structures or returned from functions. Despite these limitations, stack closures are used pervasively in Rust code.

Managed closures

When you need to store a closure in a data structure, a stack closure will not do, since the compiler will refuse to let you store it. For this purpose, Rust provides a type of closure that has an arbitrary lifetime, written @fn (boxed closure, analogous to the @ pointer type described earlier). This type of closure is first-class.

A managed closure does not directly access its environment, but merely copies out the values that it closes over into a private data structure. This means that it can not assign to these variables, and cannot observe updates to them.

This code creates a closure that adds a given string to its argument, returns it from a function, and then calls it:

fn mk_appender(suffix: ~str) -> @fn(~str) -> ~str {
    // The compiler knows that we intend this closure to be of type @fn
    return |s| s + suffix;
}

fn main() {
    let shout = mk_appender(~"!");
    println(shout(~"hey ho, let's go"));
}

Owned closures

Owned closures, written ~fn in analogy to the ~ pointer type, hold on to things that can safely be sent between processes. They copy the values they close over, much like managed closures, but they also own them: that is, no other code can access them. Owned closures are used in concurrent code, particularly for spawning tasks.

Closure compatibility

Rust closures have a convenient subtyping property: you can pass any kind of closure (as long as the arguments and return types match) to functions that expect a &fn(). Thus, when writing a higher-order function that only calls its function argument, and does nothing else with it, you should almost always declare the type of that argument as &fn(). That way, callers may pass any kind of closure.

fn call_twice(f: &fn()) { f(); f(); }
let closure = || { "I'm a closure, and it doesn't matter what type I am"; };
fn function() { "I'm a normal function"; }
call_twice(closure);
call_twice(function);

Note: Both the syntax and the semantics will be changing in small ways. At the moment they can be unsound in some scenarios, particularly with non-copyable types.

Do syntax

The do expression provides a way to treat higher-order functions (functions that take closures as arguments) as control structures.

Consider this function that iterates over a vector of integers, passing in a pointer to each integer in the vector:

fn each(v: &[int], op: &fn(v: &int)) {
   let mut n = 0;
   while n < v.len() {
       op(&v[n]);
       n += 1;
   }
}

As a caller, if we use a closure to provide the final operator argument, we can write it in a way that has a pleasant, block-like structure.

# fn each(v: &[int], op: &fn(v: &int)) { }
# fn do_some_work(i: &int) { }
each([1, 2, 3], |n| {
    do_some_work(n);
});

This is such a useful pattern that Rust has a special form of function call that can be written more like a built-in control structure:

# fn each(v: &[int], op: &fn(v: &int)) { }
# fn do_some_work(i: &int) { }
do each([1, 2, 3]) |n| {
    do_some_work(n);
}

The call is prefixed with the keyword do and, instead of writing the final closure inside the argument list, it appears outside of the parentheses, where it looks more like a typical block of code.

do is a convenient way to create tasks with the task::spawn function. spawn has the signature spawn(fn: ~fn()). In other words, it is a function that takes an owned closure that takes no arguments.

use std::task::spawn;

do spawn() || {
    debug!("I'm a task, whatever");
}

Look at all those bars and parentheses -- that's two empty argument lists back to back. Since that is so unsightly, empty argument lists may be omitted from do expressions.

use std::task::spawn;

do spawn {
   debug!("Kablam!");
}

If you want to see the output of debug! statements, you will need to turn on debug! logging. To enable debug! logging, set the RUST_LOG environment variable to the name of your crate, which, for a file named foo.rs, will be foo (e.g., with bash, export RUST_LOG=foo).

Methods

Methods are like functions except that they always begin with a special argument, called self, which has the type of the method's receiver. The self argument is like this in C++ and many other languages. Methods are called with dot notation, as in my_vec.len().

Implementations, written with the impl keyword, can define methods on most Rust types, including structs and enums. As an example, let's define a draw method on our Shape enum.

# fn draw_circle(p: Point, f: float) { }
# fn draw_rectangle(p: Point, p: Point) { }
struct Point {
    x: float,
    y: float
}

enum Shape {
    Circle(Point, float),
    Rectangle(Point, Point)
}

impl Shape {
    fn draw(&self) {
        match *self {
            Circle(p, f) => draw_circle(p, f),
            Rectangle(p1, p2) => draw_rectangle(p1, p2)
        }
    }
}

let s = Circle(Point { x: 1f, y: 2f }, 3f);
s.draw();

This defines an implementation for Shape containing a single method, draw. In most respects the draw method is defined like any other function, except for the name self.

The type of self is the type on which the method is implemented, or a pointer thereof. As an argument it is written either self, &self, @self, or ~self. A caller must in turn have a compatible pointer type to call the method.

# fn draw_circle(p: Point, f: float) { }
# fn draw_rectangle(p: Point, p: Point) { }
# struct Point { x: float, y: float }
# enum Shape {
#     Circle(Point, float),
#     Rectangle(Point, Point)
# }
impl Shape {
    fn draw_borrowed(&self) { ... }
    fn draw_managed(@self) { ... }
    fn draw_owned(~self) { ... }
    fn draw_value(self) { ... }
}

let s = Circle(Point { x: 1f, y: 2f }, 3f);

(@s).draw_managed();
(~s).draw_owned();
(&s).draw_borrowed();
s.draw_value();

Methods typically take a borrowed pointer self type, so the compiler will go to great lengths to convert a callee to a borrowed pointer.

# fn draw_circle(p: Point, f: float) { }
# fn draw_rectangle(p: Point, p: Point) { }
# struct Point { x: float, y: float }
# enum Shape {
#     Circle(Point, float),
#     Rectangle(Point, Point)
# }
# impl Shape {
#    fn draw_borrowed(&self) { ... }
#    fn draw_managed(@self) { ... }
#    fn draw_owned(~self) { ... }
#    fn draw_value(self) { ... }
# }
# let s = Circle(Point { x: 1f, y: 2f }, 3f);
// As with typical function arguments, managed and owned pointers
// are automatically converted to borrowed pointers

(@s).draw_borrowed();
(~s).draw_borrowed();

// Unlike typical function arguments, the self value will
// automatically be referenced ...
s.draw_borrowed();

// ... and dereferenced
(& &s).draw_borrowed();

// ... and dereferenced and borrowed
(&@~s).draw_borrowed();

Implementations may also define standalone (sometimes called "static") methods. The absence of a self parameter distinguishes such methods. These methods are the preferred way to define constructor functions.

impl Circle {
    fn area(&self) -> float { ... }
    fn new(area: float) -> Circle { ... }
}

To call such a method, just prefix it with the type name and a double colon:

use std::float::consts::pi;
struct Circle { radius: float }
impl Circle {
    fn new(area: float) -> Circle { Circle { radius: (area / pi).sqrt() } }
}
let c = Circle::new(42.5);

Generics

Throughout this tutorial, we've been defining functions that act only on specific data types. With type parameters we can also define functions whose arguments have generic types, and which can be invoked with a variety of types. Consider a generic map function, which takes a function function and a vector vector and returns a new vector consisting of the result of applying function to each element of vector:

fn map<T, U>(vector: &[T], function: &fn(v: &T) -> U) -> ~[U] {
    let mut accumulator = ~[];
    for element in vector.iter() {
        accumulator.push(function(element));
    }
    return accumulator;
}

When defined with type parameters, as denoted by <T, U>, this function can be applied to any type of vector, as long as the type of function's argument and the type of the vector's contents agree with each other.

Inside a generic function, the names of the type parameters (capitalized by convention) stand for opaque types. All you can do with instances of these types is pass them around: you can't apply any operations to them or pattern-match on them. Note that instances of generic types are often passed by pointer. For example, the parameter function() is supplied with a pointer to a value of type T and not a value of type T itself. This ensures that the function works with the broadest set of types possible, since some types are expensive or illegal to copy and pass by value.

Generic type, struct, and enum declarations follow the same pattern:

use std::hashmap::HashMap;
type Set<T> = HashMap<T, ()>;

struct Stack<T> {
    elements: ~[T]
}

enum Option<T> {
    Some(T),
    None
}

These declarations can be instantiated to valid types like Set<int>, Stack<int>, and Option<int>.

The last type in that example, Option, appears frequently in Rust code. Because Rust does not have null pointers (except in unsafe code), we need another way to write a function whose result isn't defined on every possible combination of arguments of the appropriate types. The usual way is to write a function that returns Option<T> instead of T.

# struct Point { x: float, y: float }
# enum Shape { Circle(Point, float), Rectangle(Point, Point) }
fn radius(shape: Shape) -> Option<float> {
    match shape {
        Circle(_, radius) => Some(radius),
        Rectangle(*)      => None
    }
}

The Rust compiler compiles generic functions very efficiently by monomorphizing them. Monomorphization is a fancy name for a simple idea: generate a separate copy of each generic function at each call site, a copy that is specialized to the argument types and can thus be optimized specifically for them. In this respect, Rust's generics have similar performance characteristics to C++ templates.

Traits

Within a generic function the operations available on generic types are very limited. After all, since the function doesn't know what types it is operating on, it can't safely modify or query their values. This is where traits come into play. Traits are Rust's most powerful tool for writing polymorphic code. Java developers will see them as similar to Java interfaces, and Haskellers will notice their similarities to type classes. Rust's traits are a form of bounded polymorphism: a trait is a way of limiting the set of possible types that a type parameter could refer to.

As motivation, let us consider copying in Rust. The clone method is not defined for all Rust types. One reason is user-defined destructors: copying a type that has a destructor could result in the destructor running multiple times. Therefore, types with destructors cannot be copied unless you explicitly implement Clone for them.

This complicates handling of generic functions. If you have a type parameter T, can you copy values of that type? In Rust, you can't, and if you try to run the following code the compiler will complain.

// This does not compile
fn head_bad<T>(v: &[T]) -> T {
    v[0] // error: copying a non-copyable value
}

However, we can tell the compiler that the head function is only for copyable types: that is, those that implement the Clone trait. In that case, we can explicitly create a second copy of the value we are returning using the clone keyword:

// This does
fn head<T: Clone>(v: &[T]) -> T {
    v[0].clone()
}

This says that we can call head on any type T as long as that type implements the Clone trait. When instantiating a generic function, you can only instantiate it with types that implement the correct trait, so you could not apply head to a type that does not implement Clone.

While most traits can be defined and implemented by user code, three traits are automatically derived and implemented for all applicable types by the compiler, and may not be overridden:

• Send - Sendable types. Types are sendable unless they contain managed boxes, managed closures, or borrowed pointers.

• Freeze - Constant (immutable) types. These are types that do not contain anything intrinsically mutable. Intrinsically mutable values include @mut and Cell in the standard library.

• 'static - Non-borrowed types. These are types that do not contain any data whose lifetime is bound to a particular stack frame. These are types that do not contain any borrowed pointers, or types where the only contained borrowed pointers have the 'static lifetime.

Note: These two traits were referred to as 'kinds' in earlier iterations of the language, and often still are.

Additionally, the Drop trait is used to define destructors. This trait defines one method called drop, which is automatically called when a value of the type that implements this trait is destroyed, either because the value went out of scope or because the garbage collector reclaimed it.

struct TimeBomb {
    explosivity: uint
}

impl Drop for TimeBomb {
    fn drop(&mut self) {
        for _ in range(0, self.explosivity) {
            println("blam!");
        }
    }
}

It is illegal to call drop directly. Only code inserted by the compiler may call it.

Declaring and implementing traits

A trait consists of a set of methods without bodies, or may be empty, as is the case with Send and Freeze. For example, we could declare the trait Printable for things that can be printed to the console, with a single method:

trait Printable {
    fn print(&self);
}

Traits may be implemented for specific types with impls. An impl that implements a trait includes the name of the trait at the start of the definition, as in the following impls of Printable for int and ~str.

# trait Printable { fn print(&self); }
impl Printable for int {
    fn print(&self) { println(fmt!("%d", *self)) }
}

impl Printable for ~str {
    fn print(&self) { println(*self) }
}

# 1.print();
# (~"foo").print();

Methods defined in an implementation of a trait may be called just like any other method, using dot notation, as in 1.print(). Traits may themselves contain type parameters. A trait for generalized sequence types might look like the following:

trait Seq<T> {
    fn length(&self) -> uint;
}

impl<T> Seq<T> for ~[T] {
    fn length(&self) -> uint { self.len() }
}

The implementation has to explicitly declare the type parameter that it binds, T, before using it to specify its trait type. Rust requires this declaration because the impl could also, for example, specify an implementation of Seq<int>. The trait type (appearing between impl and for) refers to a type, rather than defining one.

The type parameters bound by a trait are in scope in each of the method declarations. So, re-declaring the type parameter T as an explicit type parameter for len, in either the trait or the impl, would be a compile-time error.

Within a trait definition, Self is a special type that you can think of as a type parameter. An implementation of the trait for any given type T replaces the Self type parameter with T. The following trait describes types that support an equality operation:

// In a trait, `self` refers to the self argument.
// `Self` refers to the type implementing the trait.
trait Eq {
    fn equals(&self, other: &Self) -> bool;
}

// In an impl, `self` refers just to the value of the receiver
impl Eq for int {
    fn equals(&self, other: &int) -> bool { *other == *self }
}

Notice that in the trait definition, equals takes a second parameter of type Self. In contrast, in the impl, equals takes a second parameter of type int, only using self as the name of the receiver.

Just as in type implementations, traits can define standalone (static) methods. These methods are called by prefixing the method name with the trait name and a double colon. The compiler uses type inference to decide which implementation to use.

use std::float::consts::pi;
trait Shape { fn new(area: float) -> Self; }
struct Circle { radius: float }
struct Square { length: float }

impl Shape for Circle {
    fn new(area: float) -> Circle { Circle { radius: (area / pi).sqrt() } }
}
impl Shape for Square {
    fn new(area: float) -> Square { Square { length: (area).sqrt() } }
}

let area = 42.5;
let c: Circle = Shape::new(area);
let s: Square = Shape::new(area);

Bounded type parameters and static method dispatch

Traits give us a language for defining predicates on types, or abstract properties that types can have. We can use this language to define bounds on type parameters, so that we can then operate on generic types.

# trait Printable { fn print(&self); }
fn print_all<T: Printable>(printable_things: ~[T]) {
    for thing in printable_things.iter() {
        thing.print();
    }
}

Declaring T as conforming to the Printable trait (as we earlier did with Clone) makes it possible to call methods from that trait on values of type T inside the function. It will also cause a compile-time error when anyone tries to call print_all on an array whose element type does not have a Printable implementation.

Type parameters can have multiple bounds by separating them with +, as in this version of print_all that copies elements.

# trait Printable { fn print(&self); }
fn print_all<T: Printable + Clone>(printable_things: ~[T]) {
    let mut i = 0;
    while i < printable_things.len() {
        let copy_of_thing = printable_things[i].clone();
        copy_of_thing.print();
        i += 1;
    }
}

Method calls to bounded type parameters are statically dispatched, imposing no more overhead than normal function invocation, so are the preferred way to use traits polymorphically.

This usage of traits is similar to Haskell type classes.

Trait objects and dynamic method dispatch

The above allows us to define functions that polymorphically act on values of a single unknown type that conforms to a given trait. However, consider this function:

# type Circle = int; type Rectangle = int;
# impl Drawable for int { fn draw(&self) {} }
# fn new_circle() -> int { 1 }
trait Drawable { fn draw(&self); }

fn draw_all<T: Drawable>(shapes: ~[T]) {
    for shape in shapes.iter() { shape.draw(); }
}
# let c: Circle = new_circle();
# draw_all(~[c]);

You can call that on an array of circles, or an array of rectangles (assuming those have suitable Drawable traits defined), but not on an array containing both circles and rectangles. When such behavior is needed, a trait name can alternately be used as a type, called an object.

# trait Drawable { fn draw(&self); }
fn draw_all(shapes: &[@Drawable]) {
    for shape in shapes.iter() { shape.draw(); }
}

In this example, there is no type parameter. Instead, the @Drawable type denotes any managed box value that implements the Drawable trait. To construct such a value, you use the as operator to cast a value to an object:

# type Circle = int; type Rectangle = bool;
# trait Drawable { fn draw(&self); }
# fn new_circle() -> Circle { 1 }
# fn new_rectangle() -> Rectangle { true }
# fn draw_all(shapes: &[@Drawable]) {}

impl Drawable for Circle { fn draw(&self) { ... } }
impl Drawable for Rectangle { fn draw(&self) { ... } }

let c: @Circle = @new_circle();
let r: @Rectangle = @new_rectangle();
draw_all([c as @Drawable, r as @Drawable]);

We omit the code for new_circle and new_rectangle; imagine that these just return Circles and Rectangles with a default size. Note that, like strings and vectors, objects have dynamic size and may only be referred to via one of the pointer types. Other pointer types work as well. Casts to traits may only be done with compatible pointers so, for example, an @Circle may not be cast to an ~Drawable.

# type Circle = int; type Rectangle = int;
# trait Drawable { fn draw(&self); }
# impl Drawable for int { fn draw(&self) {} }
# fn new_circle() -> int { 1 }
# fn new_rectangle() -> int { 2 }
// A managed object
let boxy: @Drawable = @new_circle() as @Drawable;
// An owned object
let owny: ~Drawable = ~new_circle() as ~Drawable;
// A borrowed object
let stacky: &Drawable = &new_circle() as &Drawable;

Method calls to trait types are dynamically dispatched. Since the compiler doesn't know specifically which functions to call at compile time, it uses a lookup table (also known as a vtable or dictionary) to select the method to call at runtime.

This usage of traits is similar to Java interfaces.

By default, each of the three storage classes for traits enforce a particular set of built-in kinds that their contents must fulfill in order to be packaged up in a trait object of that storage class.

• The contents of owned traits (~Trait) must fulfill the Send bound.
• The contents of managed traits (@Trait) must fulfill the 'static bound.
• The contents of borrowed traits (&Trait) are not constrained by any bound.

Consequently, the trait objects themselves automatically fulfill their respective kind bounds. However, this default behavior can be overridden by specifying a list of bounds on the trait type, for example, by writing ~Trait: (which indicates that the contents of the owned trait need not fulfill any bounds), or by writing ~Trait:Send+Freeze, which indicates that in addition to fulfilling Send, contents must also fulfill Freeze, and as a consequence, the trait itself fulfills Freeze.

• ~Trait:Send is equivalent to ~Trait.
• @Trait:'static is equivalent to @Trait.
• &Trait: is equivalent to &Trait.

Builtin kind bounds can also be specified on closure types in the same way (for example, by writing fn:Freeze()), and the default behaviours are the same as for traits of the same storage class.

Trait inheritance

We can write a trait declaration that inherits from other traits, called supertraits. Types that implement a trait must also implement its supertraits. For example, we can define a Circle trait that inherits from Shape.

trait Shape { fn area(&self) -> float; }
trait Circle : Shape { fn radius(&self) -> float; }

Now, we can implement Circle on a type only if we also implement Shape.

use std::float::consts::pi;
# trait Shape { fn area(&self) -> float; }
# trait Circle : Shape { fn radius(&self) -> float; }
# struct Point { x: float, y: float }
# fn square(x: float) -> float { x * x }
struct CircleStruct { center: Point, radius: float }
impl Circle for CircleStruct {
    fn radius(&self) -> float { (self.area() / pi).sqrt() }
}
impl Shape for CircleStruct {
    fn area(&self) -> float { pi * square(self.radius) }
}

Notice that methods of Circle can call methods on Shape, as our radius implementation calls the area method. This is a silly way to compute the radius of a circle (since we could just return the radius field), but you get the idea.

In type-parameterized functions, methods of the supertrait may be called on values of subtrait-bound type parameters. Refering to the previous example of trait Circle : Shape:

# trait Shape { fn area(&self) -> float; }
# trait Circle : Shape { fn radius(&self) -> float; }
fn radius_times_area<T: Circle>(c: T) -> float {
    // `c` is both a Circle and a Shape
    c.radius() * c.area()
}

Likewise, supertrait methods may also be called on trait objects.

use std::float::consts::pi;
# trait Shape { fn area(&self) -> float; }
# trait Circle : Shape { fn radius(&self) -> float; }
# struct Point { x: float, y: float }
# struct CircleStruct { center: Point, radius: float }
# impl Circle for CircleStruct { fn radius(&self) -> float { (self.area() / pi).sqrt() } }
# impl Shape for CircleStruct { fn area(&self) -> float { pi * square(self.radius) } }

let concrete = @CircleStruct{center:Point{x:3f,y:4f},radius:5f};
let mycircle: @Circle = concrete as @Circle;
let nonsense = mycircle.radius() * mycircle.area();

Note: Trait inheritance does not actually work with objects yet

Deriving implementations for traits

A small number of traits in std and extra can have implementations that can be automatically derived. These instances are specified by placing the deriving attribute on a data type declaration. For example, the following will mean that Circle has an implementation for Eq and can be used with the equality operators, and that a value of type ABC can be randomly generated and converted to a string:

#[deriving(Eq)]
struct Circle { radius: float }

#[deriving(Rand, ToStr)]
enum ABC { A, B, C }

The full list of derivable traits is Eq, TotalEq, Ord, TotalOrd, Encodable Decodable, Clone, DeepClone, IterBytes, Rand, Default, Zero, and ToStr.

Crates and the module system

Rust's module system is very powerful, but because of that also somewhat complex. Nevertheless, this section will try to explain every important aspect of it.

Crates

In order to speak about the module system, we first need to define the medium it exists in:

Let's say you've written a program or a library, compiled it, and got the resulting binary. In Rust, the content of all source code that the compiler directly had to compile in order to end up with that binary is collectively called a 'crate'.

For example, for a simple hello world program your crate only consists of this code:

// main.rs
fn main() {
    println("Hello world!");
}

A crate is also the unit of independent compilation in Rust: rustc always compiles a single crate at a time, from which it produces either a library or an executable.

Note that merely using an already compiled library in your code does not make it part of your crate.

The module hierarchy

For every crate, all the code in it is arranged in a hierarchy of modules starting with a single root module. That root module is called the 'crate root'.

All modules in a crate below the crate root are declared with the mod keyword:

// This is the crate root

mod farm {
    // This is the body of module 'farm' declared in the crate root.

    fn chicken() { println("cluck cluck"); }
    fn cow() { println("mooo"); }

    mod barn {
        // Body of module 'barn'

        fn hay() { println("..."); }
    }
}

fn main() {
    println("Hello farm!");
}

As you can see, your module hierarchy is now three modules deep: There is the crate root, which contains your main() function, and the module farm. The module farm also contains two functions and a third module barn, which contains a function hay.

(In case you already stumbled over extern mod: It isn't directly related to a bare mod, we'll get to it later. )

Paths and visibility

We've now defined a nice module hierarchy. But how do we access the items in it from our main function? One way to do it is to simply fully qualifying it:

mod farm {
    fn chicken() { println("cluck cluck"); }
    // ...
}

fn main() {
    println("Hello chicken!");

    ::farm::chicken(); // Won't compile yet, see further down
}

The ::farm::chicken construct is what we call a 'path'.

Because it's starting with a ::, it's also a 'global path', which qualifies an item by its full path in the module hierarchy relative to the crate root.

If the path were to start with a regular identifier, like farm::chicken, it would be a 'local path' instead. We'll get to them later.

Now, if you actually tried to compile this code example, you'll notice that you get a unresolved name: 'farm::chicken' error. That's because per default, items (fn, struct, static, mod, ...) are only visible inside the module they are defined in.

To make them visible outside their containing modules, you need to mark them public with pub:

mod farm {
    pub fn chicken() { println("cluck cluck"); }
    pub fn cow() { println("mooo"); }
    // ...
}

fn main() {
    println("Hello chicken!");
    ::farm::chicken(); // This compiles now
}

Visibility restrictions in Rust exist only at module boundaries. This is quite different from most object-oriented languages that also enforce restrictions on objects themselves. That's not to say that Rust doesn't support encapsulation: both struct fields and methods can be private. But this encapsulation is at the module level, not the struct level.

For convenience, fields are public by default, and can be made private with the priv keyword:

mod farm {
# pub type Chicken = int;
# struct Human(int);
# impl Human { fn rest(&self) { } }
# pub fn make_me_a_farm() -> Farm { Farm { chickens: ~[], farmer: Human(0) } }
    pub struct Farm {
        priv chickens: ~[Chicken],
        farmer: Human
    }

    impl Farm {
        fn feed_chickens(&self) { ... }
        pub fn add_chicken(&self, c: Chicken) { ... }
    }

    pub fn feed_animals(farm: &Farm) {
        farm.feed_chickens();
    }
}

fn main() {
    let f = make_me_a_farm();
    f.add_chicken(make_me_a_chicken());
    farm::feed_animals(&f);
    f.farmer.rest();

    // This wouldn't compile because both are private:
    // f.feed_chickens();
    // let chicken_counter = f.chickens.len();
}
# fn make_me_a_farm() -> farm::Farm { farm::make_me_a_farm() }
# fn make_me_a_chicken() -> farm::Chicken { 0 }

Note: Visibility rules are currently buggy and not fully defined, you might have to add or remove pub along a path until it works.

Files and modules

One important aspect about Rusts module system is that source files are not important: You define a module hierarchy, populate it with all your definitions, define visibility, maybe put in a fn main(), and that's it: No need to think about source files.

The only file that's relevant is the one that contains the body of your crate root, and it's only relevant because you have to pass that file to rustc to compile your crate.

And in principle, that's all you need: You can write any Rust program as one giant source file that contains your crate root and everything below it in mod ... { ... } declarations.

However, in practice you usually want to split you code up into multiple source files to make it more manageable. In order to do that, Rust allows you to move the body of any module into it's own source file, which works like this:

If you declare a module without its body, like mod foo;, the compiler will look for the files foo.rs and foo/mod.rs. If it finds either, it uses the content of that file as the body of the module. If it finds both, that's a compile error.

So, if we want to move the content of mod farm into it's own file, it would look like this:

// main.rs - contains body of the crate root
mod farm; // Compiler will look for 'farm.rs' and 'farm/mod.rs'

fn main() {
    println("Hello farm!");
    ::farm::cow();
}

// farm.rs - contains body of module 'farm' in the crate root
pub fn chicken() { println("cluck cluck"); }
pub fn cow() { println("mooo"); }

pub mod barn {
    pub fn hay() { println("..."); }
}
# fn main() { }

So, in short mod foo; is just syntactic sugar for mod foo { /* include content of foo.rs or foo/mod.rs here */ }.

This also means that having two or more identical mod foo; somewhere in your crate hierarchy is generally a bad idea, just like copy-and-paste-ing a module into two or more places is one. Both will result in duplicate and mutually incompatible definitions.

The directory the compiler looks in for those two files is determined by starting with the same directory as the source file that contains the mod foo; declaration, and concatenating to that a path equivalent to the relative path of all nested mod { ... } declarations the mod foo; is contained in, if any.

For example, given a file with this module body:

// src/main.rs
mod plants;
mod fungi;
mod animals {
    mod fish;
    mod mammals {
        mod humans;
    }
}

The compiler would then try all these files:

src/plants.rs
src/plants/mod.rs

src/fungi.rs
src/fungi/mod.rs

src/animals/fish.rs
src/animals/fish/mod.rs

src/animals/mammals/humans.rs
src/animals/mammals/humans/mod.rs

These rules per default result in any directory structure mirroring the crates's module hierarchy, and allow you to have both small modules that only need to consist of one source file, and big modules that group the source files of submodules together.

If you need to circumvent those defaults, you can also overwrite the path a mod foo; would take:

#[path="../../area51/classified.rs"]
mod alien;

Importing names into the local scope

Always referring to definitions in other modules with their global path gets old really fast, so Rust has a way to import them into the local scope of your module: use-statements.

They work like this: At the beginning of any module body, fn body, or any other block you can write a list of use-statements, consisting of the keyword use and a global path to an item without the :: prefix. For example, this imports cow into the local scope:

use farm::cow;
# mod farm { pub fn cow() { println("I'm a hidden ninja cow!") } }
# fn main() { cow() }

The path you give to use is per default global, meaning relative to the crate root, no matter how deep the module hierarchy is, or whether the module body it's written in is contained in its own file (remember: files are irrelevant).

This is different to other languages, where you often only find a single import construct that combines the semantic of mod foo; and use-statements, and which tend to work relative to the source file or use an absolute file path

• Rubys require or C/C++'s #include come to mind.

However, it's also possible to import things relative to the module of the use-statement: Adding a super:: in front of the path will start in the parent module, while adding a self:: prefix will start in the current module:

# mod workaround {
# pub fn some_parent_item(){ println("...") }
# mod foo {
use super::some_parent_item;
use self::some_child_module::some_item;
# pub fn bar() { some_parent_item(); some_item() }
# pub mod some_child_module { pub fn some_item() {} }
# }
# }

Again - relative to the module, not to the file.

Imports are also shadowed by local definitions: For each name you mention in a module/block, rust will first look at all items that are defined locally, and only if that results in no match look at items you brought in scope with corresponding use statements.

# // XXX: Allow unused import in doc test
use farm::cow;
// ...
# mod farm { pub fn cow() { println("Hidden ninja cow is hidden.") } }
fn cow() { println("Mooo!") }

fn main() {
    cow() // resolves to the locally defined cow() function
}

To make this behavior more obvious, the rule has been made that use-statement always need to be written before any declaration, like in the example above. This is a purely artificial rule introduced because people always assumed they shadowed each other based on order, despite the fact that all items in rust are mutually recursive, order independent definitions.

One odd consequence of that rule is that use statements also go in front of any mod declaration, even if they refer to things inside them:

use farm::cow;
mod farm {
    pub fn cow() { println("Moooooo?") }
}

fn main() { cow() }

This is what our farm example looks like with use statements:

use farm::chicken;
use farm::cow;
use farm::barn;

mod farm {
    pub fn chicken() { println("cluck cluck"); }
    pub fn cow() { println("mooo"); }

    pub mod barn {
        pub fn hay() { println("..."); }
    }
}

fn main() {
    println("Hello farm!");

    // Can now refer to those names directly:
    chicken();
    cow();
    barn::hay();
}

And here an example with multiple files:

// a.rs - crate root
use b::foo;
mod b;
fn main() { foo(); }

// b.rs
use b::c::bar;
pub mod c;
pub fn foo() { bar(); }

// c.rs
pub fn bar() { println("Baz!"); }

There also exist two short forms for importing multiple names at once:

1. Explicit mention multiple names as the last element of an use path:

use farm::{chicken, cow};
# mod farm {
#     pub fn cow() { println("Did I already mention how hidden and ninja I am?") }
#     pub fn chicken() { println("I'm Bat-chicken, guardian of the hidden tutorial code.") }
# }
# fn main() { cow(); chicken() }

2. Import everything in a module with a wildcard:

use farm::*;
# mod farm {
#     pub fn cow() { println("Bat-chicken? What a stupid name!") }
#     pub fn chicken() { println("Says the 'hidden ninja' cow.") }
# }
# fn main() { cow(); chicken() }

However, that's not all. You can also rename an item while you're bringing it into scope:

use egg_layer = farm::chicken;
# mod farm { pub fn chicken() { println("Laying eggs is fun!")  } }
// ...

fn main() {
    egg_layer();
}

In general, use creates an local alias: An alternate path and a possibly different name to access the same item, whiteout touching the original, and with both being interchangeable.

Reexporting names

It is also possible to reexport items to be accessible under your module.

For that, you write pub use:

mod farm {
    pub use self::barn::hay;

    pub fn chicken() { println("cluck cluck"); }
    pub fn cow() { println("mooo"); }

    mod barn {
        pub fn hay() { println("..."); }
    }
}

fn main() {
    farm::chicken();
    farm::cow();
    farm::hay();
}

Just like in normal use statements, the exported names merely represent an alias to the same thing and can also be renamed.

The above example also demonstrate what you can use pub use for: The nested barn module is private, but the pub use allows users of the module farm to access a function from barn without needing to know that barn exists.

In other words, you can use them to decouple an public api from their internal implementation.

Using libraries

So far we've only talked about how to define and structure your own crate.

However, most code out there will want to use preexisting libraries, as there really is no reason to start from scratch each time you start a new project.

In Rust terminology, we need a way to refer to other crates.

For that, Rust offers you the extern mod declaration:

extern mod extra;
// extra ships with Rust, you'll find more details further down.

fn main() {
    // The rational number '1/2':
    let one_half = ::extra::rational::Ratio::new(1, 2);
}

Despite its name, extern mod is a distinct construct from regular mod declarations: A statement of the form extern mod foo; will cause rustc to search for the crate foo, and if it finds a matching binary it lets you use it from inside your crate.

The effect it has on your module hierarchy mirrors aspects of both mod and use:

• Like mod, it causes rustc to actually emit code: The linkage information the binary needs to use the library foo.

• But like use, all extern mod statements that refer to the same library are interchangeable, as each one really just presents an alias to an external module (the crate root of the library your linking against).

Remember how use-statements have to go before local declarations because the latter shadows the former? Well, extern mod statements also have their own rules in that regard: Both use and local declarations can shadow them, so the rule is that extern mod has to go in front of both use and local declarations.

Which can result in something like this:

extern mod extra;

use farm::dog;
use extra::rational::Ratio;

mod farm {
    pub fn dog() { println("woof"); }
}

fn main() {
    farm::dog();
    let a_third = Ratio::new(1, 3);
}

It's a bit weird, but it's the result of shadowing rules that have been set that way because they model most closely what people expect to shadow.

Package ids

If you use extern mod, per default rustc will look for libraries in the the library search path (which you can extend with the -L switch).

However, Rust also ships with rustpkg, a package manager that is able to automatically download and build libraries if you use it for building your crate. How it works is explained here, but for this tutorial it's only important to know that you can optionally annotate an extern mod statement with an package id that rustpkg can use to identify it:

extern mod rust = "github.com/mozilla/rust"; // pretend Rust is an simple library

Crate metadata and settings

For every crate you can define a number of metadata items, such as link name, version or author. You can also toggle settings that have crate-global consequences. Both mechanism work by providing attributes in the crate root.

For example, Rust uniquely identifies crates by their link metadate, which includes the link name and the version. It also hashes the filename and the symbols in a binary based on the link metadata, allowing you to use two different versions of the same library in a crate without conflict.

Therefor, if you plan to compile your crate as a library, you should annotate it with that information:

// lib.rs

# #[crate_type = "lib"];
// Crate linkage metadata
#[link(name = "farm", vers = "2.5")];

// ...
# pub fn farm() {}

You can also in turn require in a extern mod statement that certain link metadata items match some criteria. For that, Rust currently parses a comma-separated list of name/value pairs that appear after it, and ensures that they match the attributes provided in the link attribute of a crate file. This enables you to, eg, pick a a crate based on it's version number, or to link an library under an different name. For example, this two mod statements would both accept and select the crate define above:

extern mod farm(vers = "2.5");
extern mod my_farm(name = "farm", vers = "2.5");

Other crate settings and metadata include things like enabling/disabling certain errors or warnings, or setting the crate type (library or executable) explicitly:

// lib.rs
// ...

// This crate is a library ("bin" is the default)
#[crate_type = "lib"];

// Turn on a warning
#[warn(non_camel_case_types)]
# pub fn farm() {}

If you're compiling your crate with rustpkg, link annotations will not be necessary, because they get inferred by rustpkg based on the Package id and naming conventions.

Note: The rules regarding link metadata, both as attributes and on extern mod, as well as their interaction with rustpkg are currently not clearly defined and will likely change in the future.

A minimal example

Now for something that you can actually compile yourself.

We define two crates, and use one of them as a library in the other.

// world.rs
#[link(name = "world", vers = "0.42")];
pub fn explore() -> &'static str { "world" }

// main.rs
extern mod world;
fn main() { println("hello " + world::explore()); }

Now compile and run like this (adjust to your platform if necessary):

> rustc --lib world.rs  # compiles libworld-<HASH>-0.42.so
> rustc main.rs -L .    # compiles main
> ./main
"hello world"

Notice that the library produced contains the version in the file name as well as an inscrutable string of alphanumerics. As explained in the previous paragraph, these are both part of Rust's library versioning scheme. The alphanumerics are a hash representing the crates link metadata.

The standard library and the prelude

While reading the examples in this tutorial, you might have asked yourself where all those magical predefined items like println() are coming from.

The truth is, there's nothing magical about them: They are all defined normally in the std library, which is a crate that ships with Rust.

The only magical thing that happens is that rustc automatically inserts this line into your crate root:

extern mod std;

As well as this line into every module body:

use std::prelude::*;

The role of the prelude module is to re-exports common definitions from std.

This allows you to use common types and functions like Option<T> or println without needing to import them. And if you need something from std that's not in the prelude, you just have to import it with an use statement.

For example, it re-exports println which is defined in std::io::println:

use puts = std::io::println;

fn main() {
    println("println is imported per default.");
    puts("Doesn't hinder you from importing it under an different name yourself.");
    ::std::io::println("Or from not using the automatic import.");
}

Both auto-insertions can be disabled with an attribute if necessary:

// In the crate root:
#[no_std];

// In any module:
#[no_implicit_prelude];

The standard library in detail

The Rust standard library provides runtime features required by the language, including the task scheduler and memory allocators, as well as library support for Rust built-in types, platform abstractions, and other commonly used features.

std includes modules corresponding to each of the integer types, each of the floating point types, the bool type, tuples, characters, strings, vectors, managed boxes, owned boxes, and unsafe and borrowed pointers. Additionally, std provides some pervasive types (option and result), task creation and communication primitives, platform abstractions (os and path), basic I/O abstractions (io), containers like hashmap, common traits (kinds, ops, cmp, num, to_str, clone), and complete bindings to the C standard library (libc).

The full documentation for std can be found here: standard library.

The extra library

Rust also ships with the extra library, an accumulation of useful things, that are however not important enough to deserve a place in the standard library. You can use them by linking to extra with an extern mod extra;.

Right now extra contains those definitions directly, but in the future it will likely just re-export a bunch of 'officially blessed' crates that get managed with rustpkg.

What next?

Now that you know the essentials, check out any of the additional tutorials on individual topics.

• Borrowed pointers
• Tasks and communication
• Macros
• The foreign function interface
• Containers and iterators
• Error-handling and Conditions
• Packaging up Rust code

There is further documentation on the wiki, however those tend to be even more out of date as this document.