% 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](#what-next) 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][win-exe] 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). As such, source builds require a connection to
the Internet, to fetch snapshots, and an OS that can execute the
available snapshot binaries.
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][wiki-start]" 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`][bug-3319]. It's a bummer, we
> know.
[bug-3319]: https://github.com/mozilla/rust/issues/3319
[wiki-start]: https://github.com/mozilla/rust/wiki/Note-getting-started-developing-Rust
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.
~~~~ {.notrust}
$ curl -O http://static.rust-lang.org/dist/rust-0.5.tar.gz
$ tar -xzf rust-0.5.tar.gz
$ cd rust-0.5
$ ./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.
[wiki-start]: https://github.com/mozilla/rust/wiki/Note-getting-started-developing-Rust
[tarball]: http://static.rust-lang.org/dist/rust-0.5.tar.gz
[win-exe]: http://static.rust-lang.org/dist/rust-0.5-install.exe
## 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() {
io::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
`io::println` to some nonexistent function), and then compile it, you'll see
an error message like this:
~~~~ {.notrust}
hello.rs:2:4: 2:16 error: unresolved name: io::print_with_unicorns
hello.rs:2 io::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][sublime] and through
[Sublime Package Control][sublime-pkg], 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.
[sublime]: http://github.com/dbp/sublime-rust
[sublime-pkg]: http://wbond.net/sublime_packages/package_control
# 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 {
io::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. Constants, on the other hand, always require a type annotation.
~~~~
const 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](#traits), [enum types](#enums), and [constants](#constants)) 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](#vectors-and-strings).
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, divide, take 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][pf] 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 = ();
io::println(fmt!("%s is %d", "the answer", 43));
// %? will conveniently print any type
io::println(fmt!("what is this thing: %?", mystery_object));
~~~~
[pf]: http://en.cppreference.com/w/cpp/io/c/fprintf
You can define your own syntax extensions with the macro system. For details, see the [macro tutorial][macros].
[macros]: tutorial-macros.html
# 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 {
io::println("that's odd");
} else if true {
io::println("right");
} else {
io::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 { return 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 => io::println("zero"),
1 | 2 => io::println("one or two"),
3..10 => io::println("three to ten"),
_ => io::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 => { io::println("zero") }
_ => { io::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. Remember that `(float, float)` is a tuple of two floats:
~~~~
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) => float::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 = 5;
loop {
x += x - 3;
if x % 5 == 0 { break; }
io::println(int::to_str(x));
}
~~~~
This code prints out a weird sequence of numbers and stops as soon as
it finds one that can be divided by five.
For more involved iteration, such as enumerating the elements of a
collection, Rust uses [higher-order functions](#closures).
# 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`.
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).
~~~~
struct Stack {
content: ~[int],
head: uint
}
~~~~
With a value (say, `mystack`) of such a type in a mutable location, you can do
`mystack.head += 1`. But in an immutable location, such an assignment to a
struct without inherited mutability would result in a type error.
`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 } => { io::println(yy.to_str()); }
Point { x: xx, y: yy } => { io::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, _ } => { io::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`.
There is a special case for enums with a single variant, which are
sometimes called "newtype-style enums" (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 its own
distinct type: `type` creates a structural synonym, while this form of
`enum` creates a nominal synonym. If you say:
~~~~
enum GizmoId = int;
~~~~
That is a shorthand for this:
~~~~
enum GizmoId { GizmoId(int) }
~~~~
You can extract the contents of such an enum type with the
dereference (`*`) unary operator:
~~~~
# enum 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.
~~~~
enum Inches = int;
enum Centimeters = int;
~~~~
The above definitions allow for a simple way for programs to avoid
confusing numbers that correspond to different units.
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`:
~~~~
# 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 core::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 or 1 (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) => log(info, a + b + (c as int))
}
~~~~
## Tuple structs
Rust also has _nominal tuples_, which behave like both structs and tuples,
except that nominal tuple types have names
(so `Foo(1, 2)` has a different type from `Bar(1, 2)`),
and nominal tuple types' _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) => log(info, a + b + (c as int))
}
~~~~
# 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](#modules-and-crates)). 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 }
~~~
# Boxes and pointers
Many modern languages have a so-called "uniform representation" for
aggregate types like structs and enums, so as to represent these types
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
those with mutable fields, it can be useful to have a single copy on
the stack or on the heap, and refer to that through a pointer.
Whenever memory is allocated on the heap, the program needs a strategy to
dispose of the memory when no longer needed. Most languages, such as Java or
Python, use *garbage collection* for this, a strategy in which the program
periodically searches for allocations that are no longer reachable in order
to dispose of them. Other languages, such as C, use *manual memory
management*, which relies on the programmer to specify when memory should be
reclaimed.
Rust is in a different position. It differs from the garbage-collected
environments in that allows the programmer to choose the disposal
strategy on an object-by-object basis. Not only does this have benefits for
performance, but we will later see that this model has benefits for
concurrency as well, by making it possible for the Rust compiler to detect
data races at compile time. Rust also differs from the manually managed
languages in that it is *safe*—it uses a [pointer lifetime
analysis][borrow] to ensure that manual memory management cannot cause memory
errors at runtime.
[borrow]: tutorial-borrowed-ptr.html
The cornerstone of Rust's memory management is the concept of a *smart
pointer*—a pointer type that indicates the lifetime of the object it points
to. This solution is familiar to C++ programmers; Rust differs from C++,
however, in that a small set of smart pointers are built into the language.
The safe pointer types are `@T`, for *managed* boxes allocated on the *local
heap*, `~T`, for *uniquely-owned* boxes allocated on the *exchange
heap*, and `&T`, for *borrowed* pointers, which may point to any memory, and
whose lifetimes are governed by the call stack.
All pointer types can be dereferenced with the `*` unary operator.
> ***Note***: You may also hear managed boxes referred to as 'shared
> boxes' or 'shared pointers', and owned boxes as 'unique boxes/pointers'.
> Borrowed pointers are sometimes called 'region pointers'. The preferred
> terminology is what we present here.
## Managed boxes
Managed boxes are pointers to heap-allocated, garbage-collected
memory. Applying the unary `@` operator to an expression creates a
managed box. The resulting box contains the result of the
expression. Copying a managed box, as happens during assignment, only
copies a pointer, never the contents of the box.
~~~~
let x: @int = @10; // New box
let y = x; // Copy of a pointer to the same box
// x and y both refer to the same allocation. When both go out of scope
// then the allocation will be freed.
~~~~
A _managed_ type is either of the form `@T` for some type `T`, or any
type that contains managed boxes or other managed types.
~~~
// A linked list node
struct Node {
next: MaybeNode,
prev: MaybeNode,
payload: int
}
enum MaybeNode {
SomeNode(@mut Node),
NoNode
}
let node1 = @mut Node { next: NoNode, prev: NoNode, payload: 1 };
let node2 = @mut Node { next: NoNode, prev: NoNode, payload: 2 };
let node3 = @mut Node { next: NoNode, prev: NoNode, payload: 3 };
// Link the three list nodes together
node1.next = SomeNode(node2);
node2.prev = SomeNode(node1);
node2.next = SomeNode(node3);
node3.prev = SomeNode(node2);
~~~
Managed boxes never cross task boundaries. This has several benefits for
performance:
* The Rust garbage collector does not need to stop multiple threads in order
to collect garbage.
* You can separate your application into "real-time" tasks that do not use
the garbage collector and "non-real-time" tasks that do, and the real-time
tasks will not be interrupted by the non-real-time tasks.
C++ programmers will recognize `@T` as similar to `std::shared_ptr`.
> ***Note:*** Currently, the Rust compiler generates code to reclaim
> managed boxes through reference counting and a cycle collector, but
> we will switch to a tracing garbage collector eventually.
## Owned boxes
In contrast with managed boxes, owned boxes have a single owning
memory slot and thus two owned boxes may not refer to the same
memory. All owned boxes across all tasks are allocated on a single
_exchange heap_, where their uniquely-owned nature allows tasks to
exchange them efficiently.
Because owned boxes are uniquely owned, copying them requires allocating
a new owned box and duplicating the contents.
Instead, owned boxes are _moved_ by default, transferring ownership,
and deinitializing the previously owning variable.
Any attempt to access a variable after the value has been moved out
will result in a compile error.
~~~~
let x = ~10;
// Move x to y, deinitializing x
let y = x;
~~~~
If you really want to copy an owned box you must say so explicitly.
~~~~
let x = ~10;
let y = copy x;
let z = *x + *y;
assert z == 20;
~~~~
When they do not contain any managed boxes, owned boxes can be sent
to other tasks. The sending task will give up ownership of the box
and won't be able to access it afterwards. The receiving task will
become the sole owner of the box. This prevents *data races*—errors
that could otherwise result from multiple tasks working on the same
data without synchronization.
When an owned pointer goes out of scope or is overwritten, the object
it points to is immediately freed. Effective use of owned boxes can
therefore be an efficient alternative to garbage collection.
C++ programmers will recognize `~T` as similar to `std::unique_ptr`
(or `std::auto_ptr` in C++03 and below).
## Borrowed pointers
Rust borrowed pointers are a general purpose reference/pointer type,
similar to the C++ reference type, but guaranteed to point to valid
memory. In contrast with owned pointers, where the holder of an owned
pointer is the owner of the pointed-to memory, borrowed pointers never
imply ownership. Pointers may be borrowed from any type, in which case
the pointer is guaranteed not to outlive the value it points to.
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 wanted to write a procedure that computed the distance
between any two points, no matter where they were 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 or, worse, if there are mutable
fields, they can change the semantics of your program. 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][borrowtut].
[borrowtut]: tutorial-borrowed-ptr.html
## 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() -> 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() -> 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 felt inclined, you could write
something silly like
~~~
# struct Point { x: float, y: float }
let point = &@~Point { x: 10f, y: 20f };
io::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 };
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;
// += will append to a vector, provided it lives in a mutable slot
let mut my_crayons = my_crayons;
my_crayons += 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 * 3] = [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.
~~~ {.xfail-test}
# 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](#functions-and-methods), defined in [`core::vec`]
and [`core::str`]. Here are some examples.
[`core::vec`]: core/vec.html
[`core::str`]: core/str.html
~~~
# use core::io::println;
# 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 crayons.each |crayon| {
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.substr(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:
~~~~ {.ignore}
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.
~~~~
# use println = core::io::println;
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. 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:
~~~~
# extern mod std;
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(~"!");
io::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][tasks].
[tasks]: tutorial-tasks.html
## 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 an aside, the reason we pass in a *pointer* to an integer rather
than the integer itself is that this is how the actual `each()`
function for vectors works. `vec::each` though is a
[generic](#generics) function, so must be efficient to use for all
types. Passing the elements by pointer avoids copying potentially
large objects.
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 core::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 core::task::spawn;
do spawn {
debug!("Kablam!");
}
~~~~
## For loops
The most common way to express iteration in Rust is with a `for`
loop. Like `do`, `for` is a nice syntax for describing control flow
with closures. Additionally, within a `for` loop, `break`, `loop`,
and `return` work just as they do with `while` and `loop`.
Consider again our `each` function, this time improved to
break early when the iteratee returns `false`:
~~~~
fn each(v: &[int], op: fn(v: &int) -> bool) {
let mut n = 0;
while n < v.len() {
if !op(&v[n]) {
break;
}
n += 1;
}
}
~~~~
And using this function to iterate over a vector:
~~~~
# use each = core::vec::each;
# use println = core::io::println;
each([2, 4, 8, 5, 16], |n| {
if *n % 2 != 0 {
println("found odd number!");
false
} else { true }
});
~~~~
With `for`, functions like `each` can be treated more
like built-in looping structures. When calling `each`
in a `for` loop, instead of returning `false` to break
out of the loop, you just write `break`. To skip ahead
to the next iteration, write `loop`.
~~~~
# use each = core::vec::each;
# use println = core::io::println;
for each([2, 4, 8, 5, 16]) |n| {
if *n % 2 != 0 {
println("found odd number!");
break;
}
}
~~~~
As an added bonus, you can use the `return` keyword, which is not
normally allowed in closures, in a block that appears as the body of a
`for` loop: the meaning of `return` in such a block is to return from
the enclosing function, not just the loop body.
~~~~
# use each = core::vec::each;
fn contains(v: &[int], elt: int) -> bool {
for each(v) |x| {
if (*x == elt) { return true; }
}
false
}
~~~~
Notice that, because `each` passes each value by borrowed pointer,
the iteratee needs to dereference it before using it.
In these situations it can be convenient to lean on Rust's
argument patterns to bind `x` to the actual value, not the pointer.
~~~~
# use each = core::vec::each;
# fn contains(v: &[int], elt: int) -> bool {
for each(v) |&x| {
if (x == elt) { return true; }
}
# false
# }
~~~~
`for` syntax only works with stack closures.
> ***Note:*** This is, essentially, a special loop protocol:
> the keywords `break`, `loop`, and `return` work, in varying degree,
> with `while`, `loop`, `do`, and `for` constructs.
# 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 unique 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 _static_ methods,
which don't have an explicit `self` argument.
The `static` keyword distinguishes static methods from methods that have a `self`:
~~~~ {.xfail-test}
impl Circle {
fn area(&self) -> float { ... }
static fn new(area: float) -> Circle { ... }
}
~~~~
> ***Note***: In the future the `static` keyword will be removed and static methods
> will be distinguished solely by the presence or absence of the `self` argument.
> In the current langugage instance methods may also be declared without an explicit
> `self` argument, in which case `self` is an implicit reference.
> That form of method is deprecated.
Constructors are one common application for static methods, as in `new` above.
To call a static method, you have to prefix it with the type name and a double colon:
~~~~
# use core::float::consts::pi;
# use core::float::sqrt;
struct Circle { radius: float }
impl Circle {
static fn new(area: float) -> Circle { Circle { radius: sqrt(area / pi) } }
}
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(vector: &[T], function: fn(v: &T) -> U) -> ~[U] {
let mut accumulator = ~[];
for vec::each(vector) |element| {
accumulator.push(function(element));
}
return accumulator;
}
~~~~
When defined with type parameters, as denoted by ``, 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::oldmap::HashMap;
type Set = HashMap;
struct Stack {
elements: ~[T]
}
enum Option {
Some(T),
None
}
~~~~
These declarations can be instantiated to valid types like `Set`,
`Stack`, and `Option`.
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` instead of `T`.
~~~~
# struct Point { x: float, y: float }
# enum Shape { Circle(Point, float), Rectangle(Point, Point) }
fn radius(shape: Shape) -> Option {
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 `copy` operation
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 user-defined
destructors cannot be copied, either implicitly or explicitly, and
neither can types that own other types containing destructors.
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.
~~~~ {.xfail-test}
// This does not compile
fn head_bad(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 have the `Copy` trait.
~~~~
// This does
fn head(v: &[T]) -> T {
v[0]
}
~~~~
This says that we can call `head` on any type `T` as long as that type
implements the `Copy` 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 with a
destructor. (`Copy` is a special trait that is built in to the
compiler, making it possible for the compiler to enforce this
restriction.)
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:
* `Copy` - Types that can be copied, either implicitly, or explicitly with the
`copy` operator. All types are copyable unless they have destructors or
contain types with destructors.
* `Owned` - Owned types. Types are owned unless they contain managed
boxes, managed closures, or borrowed pointers. Owned types may or
may not be copyable.
* `Const` - Constant (immutable) types. These are types that do not contain
mutable fields.
> ***Note:*** These three 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 `finalize`, 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 finalize(&self) {
for iter::repeat(self.explosivity) {
io::println("blam!");
}
}
}
~~~
It is illegal to call `finalize` 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 `Copy`, `Owned`, and `Const`. 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`.
[impls]: #functions-and-methods
~~~~
# trait Printable { fn print(&self); }
impl Printable for int {
fn print(&self) { io::println(fmt!("%d", *self)) }
}
impl Printable for &str {
fn print(&self) { io::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 {
fn len(&self) -> uint;
fn iter(&self, b: fn(v: &T));
}
impl Seq for ~[T] {
fn len(&self) -> uint { vec::len(*self) }
fn iter(&self, b: fn(v: &T)) {
for vec::each(*self) |elt| { b(elt); }
}
}
~~~~
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`. 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`. Simply, in a
trait, `self` is a type, and in an impl, `self` is a value. 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.
Traits can also define static methods which are called by prefixing
the method name with the trait name.
The compiler will use type inference to decide which implementation to call.
~~~~
trait Shape { static fn new(area: float) -> Self; }
# use core::float::consts::pi;
# use core::float::sqrt;
struct Circle { radius: float }
struct Square { length: float }
impl Shape for Circle {
static fn new(area: float) -> Circle { Circle { radius: sqrt(area / pi) } }
}
impl Shape for Square {
static fn new(area: float) -> Square { Square { length: sqrt(area) } }
}
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(printable_things: ~[T]) {
for printable_things.each |thing| {
thing.print();
}
}
~~~~
Declaring `T` as conforming to the `Printable` trait (as we earlier
did with `Copy`) 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(printable_things: ~[T]) {
let mut i = 0;
while i < printable_things.len() {
let copy_of_thing = printable_things[i];
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(shapes: ~[T]) {
for shapes.each |shape| { 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 shapes.each |shape| { 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 `Circle`s and `Rectangle`s 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.
## 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`.
~~~~
# trait Shape { fn area(&self) -> float; }
# trait Circle : Shape { fn radius(&self) -> float; }
# struct Point { x: float, y: float }
# use core::float::consts::pi;
# use core::float::sqrt;
# fn square(x: float) -> float { x * x }
struct CircleStruct { center: Point, radius: float }
impl Circle for CircleStruct {
fn radius(&self) -> float { sqrt(self.area() / pi) }
}
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 `circle` 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(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.
~~~ {.xfail-test}
# trait Shape { fn area(&self) -> float; }
# trait Circle : Shape { fn radius(&self) -> float; }
# use core::float::consts::pi;
# use core::float::sqrt;
# struct Point { x: float, y: float }
# struct CircleStruct { center: Point, radius: float }
# impl Circle for CircleStruct { fn radius(&self) -> float { sqrt(self.area() / pi) } }
# 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
# Modules and crates
The Rust namespace is arranged in a hierarchy of modules. Each source
(.rs) file represents a single module and may in turn contain
additional modules.
~~~~
mod farm {
pub fn chicken() -> &str { "cluck cluck" }
pub fn cow() -> &str { "mooo" }
}
fn main() {
io::println(farm::chicken());
}
~~~~
The contents of modules can be imported into the current scope
with the `use` keyword, optionally giving it an alias. `use`
may appear at the beginning of crates, `mod`s, `fn`s, and other
blocks.
~~~
# mod farm { pub fn chicken() { } }
# fn main() {
// Bring `chicken` into scope
use farm::chicken;
fn chicken_farmer() {
// The same, but name it `my_chicken`
use my_chicken = farm::chicken;
...
# my_chicken();
}
# chicken();
# }
~~~
These farm animal functions have a new keyword, `pub`, attached to
them. The `pub` keyword modifies an item's visibility, making it
visible outside its containing module. An expression with `::`, like
`farm::chicken`, can name an item outside of its containing
module. Items, such as those declared with `fn`, `struct`, `enum`,
`type`, or `const`, are module-private by default.
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. Note that fields and methods are _public_ by default.
~~~
mod farm {
# use farm;
# pub type Chicken = int;
# type Cow = int;
# enum Human = int;
# impl Human { fn rest(&self) { } }
# pub fn make_me_a_farm() -> farm::Farm { farm::Farm { chickens: ~[], cows: ~[], farmer: Human(0) } }
pub struct Farm {
priv chickens: ~[Chicken],
priv cows: ~[Cow],
farmer: Human
}
impl Farm {
priv fn feed_chickens(&self) { ... }
priv fn feed_cows(&self) { ... }
pub fn add_chicken(&self, c: Chicken) { ... }
}
pub fn feed_animals(farm: &Farm) {
farm.feed_chickens();
farm.feed_cows();
}
}
fn main() {
let f = make_me_a_farm();
f.add_chicken(make_me_a_chicken());
farm::feed_animals(&f);
f.farmer.rest();
}
# fn make_me_a_farm() -> farm::Farm { farm::make_me_a_farm() }
# fn make_me_a_chicken() -> farm::Chicken { 0 }
~~~
## Crates
The unit of independent compilation in Rust is the crate: rustc
compiles a single crate at a time, from which it produces either a
library or an executable.
When compiling a single `.rs` source file, the file acts as the whole crate.
You can compile it with the `--lib` compiler switch to create a shared
library, or without, provided that your file contains a `fn main`
somewhere, to create an executable.
Larger crates typically span multiple files and are, by convention,
compiled from a source file with the `.rc` extension, called a *crate file*.
The crate file extension distinguishes source files that represent
crates from those that do not, but otherwise source files and crate files are identical.
A typical crate file declares attributes associated with the crate that
may affect how the compiler processes the source.
Crate attributes specify metadata used for locating and linking crates,
the type of crate (library or executable),
and control warning and error behavior,
among other things.
Crate files additionally declare the external crates they depend on
as well as any modules loaded from other files.
~~~~ { .xfail-test }
// Crate linkage metadata
#[link(name = "farm", vers = "2.5", author = "mjh")];
// Make a library ("bin" is the default)
#[crate_type = "lib"];
// Turn on a warning
#[warn(non_camel_case_types)]
// Link to the standard library
extern mod std;
// Load some modules from other files
mod cow;
mod chicken;
mod horse;
fn main() {
...
}
~~~~
Compiling this file will cause `rustc` to look for files named
`cow.rs`, `chicken.rs`, and `horse.rs` in the same directory as the
`.rc` file, compile them all together, and, based on the presence of
the `crate_type = "lib"` attribute, output a shared library or an
executable. (If the line `#[crate_type = "lib"];` was omitted,
`rustc` would create an executable.)
The `#[link(...)]` attribute provides meta information about the
module, which other crates can use to load the right module. More
about that later.
To have a nested directory structure for your source files, you can
nest mods:
~~~~ {.ignore}
mod poultry {
mod chicken;
mod turkey;
}
~~~~
The compiler will now look for `poultry/chicken.rs` and
`poultry/turkey.rs`, and export their content in `poultry::chicken`
and `poultry::turkey`. You can also provide a `poultry.rs` to add
content to the `poultry` module itself.
## Using other crates
The `extern mod` directive lets you use a crate (once it's been
compiled into a library) from inside another crate. `extern mod` can
appear at the top of a crate file or at the top of modules. It will
cause the compiler to look in the library search path (which you can
extend with the `-L` switch) for a compiled Rust library with the
right name, then add a module with that crate's name into the local
scope.
For example, `extern mod std` links the [standard library].
[standard library]: std/index.html
When a comma-separated list of name/value pairs appears after `extern
mod`, the compiler front-end matches these pairs against the
attributes provided in the `link` attribute of the crate file. The
front-end will only select this crate for use if the actual pairs
match the declared attributes. You can provide a `name` value to
override the name used to search for the crate.
Our example crate declared this set of `link` attributes:
~~~~
#[link(name = "farm", vers = "2.5", author = "mjh")];
~~~~
Which you can then link with any (or all) of the following:
~~~~ {.xfail-test}
extern mod farm;
extern mod my_farm (name = "farm", vers = "2.5");
extern mod my_auxiliary_farm (name = "farm", author = "mjh");
~~~~
If any of the requested metadata do not match, then the crate
will not be compiled successfully.
## A minimal example
Now for something that you can actually compile yourself. We have
these two files:
~~~~
// world.rs
#[link(name = "world", vers = "1.0")];
pub fn explore() -> &str { "world" }
~~~~
~~~~ {.xfail-test}
// main.rs
extern mod world;
fn main() { io::println(~"hello " + world::explore()); }
~~~~
Now compile and run like this (adjust to your platform if necessary):
~~~~ {.notrust}
> rustc --lib world.rs # compiles libworld-94839cbfe144198-1.0.so
> rustc main.rs -L . # compiles main
> ./main
"hello world"
~~~~
Notice that the library produced contains the version in the filename
as well as an inscrutable string of alphanumerics. These are both
part of Rust's library versioning scheme. The alphanumerics are
a hash representing the crate metadata.
## The core library
The Rust [core] library is the language runtime and contains
required memory management and task scheduling code as well as a
number of modules necessary for effective usage of the primitive
types. Methods on [vectors] and [strings], implementations of most
comparison and math operators, and pervasive types like [`Option`]
and [`Result`] live in core.
All Rust programs link to the core library and import its contents,
as if the following were written at the top of the crate.
~~~ {.xfail-test}
extern mod core;
use core::*;
~~~
[core]: core/index.html
[vectors]: core/vec.html
[strings]: core/str.html
[`Option`]: core/option.html
[`Result`]: core/result.html
# What next?
Now that you know the essentials, check out any of the additional
tutorials on individual topics.
* [Borrowed pointers][borrow]
* [Tasks and communication][tasks]
* [Macros][macros]
* [The foreign function interface][ffi]
There is further documentation on the [wiki], including articles about
[unit testing] in Rust, [documenting][rustdoc] and [packaging][cargo]
Rust code, and a discussion of the [attributes] used to apply metadata
to code.
[borrow]: tutorial-borrowed-ptr.html
[tasks]: tutorial-tasks.html
[macros]: tutorial-macros.html
[ffi]: tutorial-ffi.html
[wiki]: https://github.com/mozilla/rust/wiki/Docs
[unit testing]: https://github.com/mozilla/rust/wiki/Doc-unit-testing
[rustdoc]: https://github.com/mozilla/rust/wiki/Doc-using-rustdoc
[cargo]: https://github.com/mozilla/rust/wiki/Doc-using-cargo-to-manage-packages
[attributes]: https://github.com/mozilla/rust/wiki/Doc-attributes
[pound-rust]: http://chat.mibbit.com/?server=irc.mozilla.org&channel=%23rust