% 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 while preventing 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:
* **Pattern matching and algebraic data types (enums).** As
popularized by functional languages, pattern matching on ADTs
provides a compact and expressive way to encode program logic.
* **Type inference.** Type annotations on local variable
declarations are optional.
* **Task-based concurrency.** Rust uses lightweight tasks that do
not share memory.
* **Higher-order functions.** Rust's efficient and flexible closures
are heavily relied on to provide iteration and other control
structures
* **Parametric polymorphism (generics).** Functions and types can be
parameterized over type variables with optional trait-based type
constraints.
* **Trait polymorphism.** Rust's type system features a unique
combination of type classes and object-oriented 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, and generics. [Additional
tutorials](#what-next) cover specific language features in greater
depth.
It assumes the reader is familiar with the basic concepts of
programming, and has programmed in one or more other languages
before. It will often make comparisons to other languages,
particularly those in the C family.
## Conventions
Throughout the tutorial, words that indicate language keywords or
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 things that aren't actually defined.
> ***Warning:*** Rust is a language under heavy 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 10.7 ("Lion"), 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 in this tutorial.
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
Assuming you're on a relatively modern *nix system and have met the
prerequisites, something along these lines should work.
~~~~ {.notrust}
$ wget http://dl.rust-lang.org/dist/rust-0.4.tar.gz
$ tar -xzf rust-0.4.tar.gz
$ cd rust-0.4
$ ./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 the following programs into
`/usr/local/bin`:
* `rustc`, the Rust compiler
* `rustdoc`, the API-documentation tool
* `cargo`, the Rust package manager
[wiki-start]: https://github.com/mozilla/rust/wiki/Note-getting-started-developing-Rust
[tarball]: http://dl.rust-lang.org/dist/rust-0.4.tar.gz
[win-exe]: http://dl.rust-lang.org/dist/rust-0.4-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? yes, this is rust");
}
~~~~
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
(unless you are on Windows, in which case what it does is subject
to local weather conditions).
> ***Note:*** That may or may not be hyperbole, but there are some
> 'gotchas' to be aware of on Windows. First, the MinGW environment
> must be set up perfectly. Please read [the
> wiki][wiki-started]. Second, `rustc` may need to be [referred to as
> `rustc.exe`][bug-3319]. It's a bummer, I know, and I am so very
> sorry.
[bug-3319]: https://github.com/mozilla/rust/issues/3319
[wiki-started]: https://github.com/mozilla/rust/wiki/Note-getting-started-developing-Rust
The Rust compiler tries to provide useful information when it runs
into an error. If you modify the program to make it invalid (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_it
hello.rs:2 io::print_it("hello? yes, this is rust");
^~~~~~~~~~~~
~~~~
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. The `extern mod std`
directive that appears at the top of many examples imports the
[standard library][std], described in more detail [later
on](#modules-and-crates).
[std]: http://doc.rust-lang.org/doc/std
## 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].
Other editors are not provided for yet. 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 `when`; 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.
The main surface difference to be aware of is that the condition at
the head of control structures like `if` and `while` do not require
paretheses, while their bodies *must* be wrapped in
brackets. Single-statement, bracket-less bodies are not allowed.
~~~~
# fn recalibrate_universe() -> bool { true }
fn main() {
/* A simple loop */
loop {
// A tricky calculation
if recalibrate_universe() {
return;
}
}
}
~~~~
The `let` keyword, introduces a local variable. By default, variables
are immutable. `let mut` can be used to introduce a local variable
that can be reassigned.
~~~~
let hi = "hi";
let mut count = 0;
while count < 10 {
io::println(hi);
count += 1;
}
~~~~
Although Rust can almost always infer the types of local variables, it
can help readability to specify a variable's type by following it with
a colon, then the type name. Local variables may shadow earlier
declarations, making the earlier variables inaccessible.
~~~~
let my_favorite_value: float = 57.8;
let my_favorite_value: int = my_favorite_value as int;
~~~~
Rust identifiers follow the same rules as C; they 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
begin function, variable, and module names with a lowercase letter, using
underscores where they help readability, while writing types in camel case.
~~~
let my_variable = 100;
type MyType = int; // built-in types though are _not_ camel case
~~~
## Expression syntax
Though it isn't apparent in all code, there is a fundamental
difference between Rust's syntax and its predecessors in this family
of languages. 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 the
semicolons are omitted from the blocks in 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 (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 (`let` for variables,
`fn` for functions, et cetera) 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
}
~~~~
If all those things are expressions, you might conclude that you have
to add a terminating semicolon after *every* statement, even ones that
are not traditionally terminated with a semicolon in C (like `while`).
That is not the case, though. Expressions that end in a block only
need a semicolon if that block contains a trailing expression. `while`
loops do not allow trailing expressions, and `if` statements tend to
only have a trailing expression when you want to use their value for
something—in which case you'll have embedded it in a bigger statement.
~~~
# fn foo() -> bool { true }
# fn bar() -> bool { true }
# fn baz() -> bool { true }
// `let` is not an expression, so it is semi-colon terminated;
let x = foo();
// When used in statement position, bracy expressions do not
// usually need to be semicolon terminated
if x {
bar();
} else {
baz();
} // No semi-colon
// Although, if `bar` and `baz` have non-nil return types, and
// we try to use them as the tail expressions, rustc will
// make us terminate the expression.
if x {
bar()
} else {
baz()
}; // Semi-colon to ignore non-nil block type
// An `if` embedded in `let` again requires a semicolon to terminate
// the `let` statement
let y = if x { foo() } else { bar() };
~~~
This may sound a bit intricate, but it is super-useful, and it will
grow on you (hopefully).
## Types
The basic types include the usual boolean, integral, and floating point types.
------------------------- -----------------------------------------------
`()` Nil, the type that has only a single value
`bool` Boolean type, with values `true` and `false`
`int`, `uint` Machine-pointer-sized signed and unsigned integers
`i8`, `i16`, `i32`, `i64` Signed integers with a specific size (in bits)
`u8`, `u16`, `u32`, `u64` Unsigned integers with a specific size
`float` The largest floating-point type efficiently supported on the target machine
`f32`, `f64` Floating-point types with a specific size.
`char` A Unicode character (32 bits).
------------------------- -----------------------------------------------
These can be combined in composite types, which will be described in
more detail later on (the `T`s here stand for any other type):
------------------------- -----------------------------------------------
`[T * N]` Vector (like an array in other languages) with N elements
`[mut T * N]` Mutable vector with N elements
`(T1, T2)` Tuple type. Any arity above 1 is supported
`@T`, `~T`, `&T` [Pointer types](#boxes-and-pointers)
------------------------- -----------------------------------------------
Some types can only be manipulated by pointer, never directly. For instance,
you cannot refer to a string (`str`); instead you refer to a pointer to a
string (`@str`, `~str`, or `&str`). These *dynamically-sized* types consist
of:
------------------------- -----------------------------------------------
`fn(a: T1, b: T2) -> T3` Function types
`str` String type (in UTF-8)
`[T]` Vector with unknown size (also called a slice)
`[mut T]` Mutable vector with unknown size
------------------------- -----------------------------------------------
In function types, the return type is specified with an arrow, as in
the type `fn() -> bool` or the function declaration `fn foo() -> bool
{ }`. For functions that do not return a meaningful value, you can
optionally write `-> ()`, but usually the return annotation is simply
left off, as in `fn main() { ... }`.
Types can be given names with `type` declarations:
~~~~
type MonsterSize = uint;
~~~~
This will provide a synonym, `MonsterSize`, for unsigned integers. It will not
actually create a new, incompatible type—`MonsterSize` and `uint` can be used
interchangeably, and using one where the other is expected is not a type
error. Read about [single-variant enums](#single_variant_enum)
further on if you need to create a type name that's not just a
synonym.
## Literals
Integers can be written in decimal (`144`), hexadecimal (`0x90`), and
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`, and `i8` for the `i8` type, etc.
In the absense 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 as a uint
let d = 1000i32; // d is an i32
~~~~
Floating point numbers are written `0.0`, `1e6`, or `2.1e-4`. Without
a suffix, the literal is assumed to be of type `float`. Suffixes `f32`
(32-bit) and `f64` (64-bit) can be used to create literals of a
specific type.
The nil literal is written just like the type: `()`. The keywords
`true` and `false` produce the boolean literals.
Character literals are written between single quotes, as in `'x'`. Just as in
C, Rust understands a number of character escapes, using the backslash
character, `\n`, `\r`, and `\t` being the most common. String literals,
written between double quotes, allow the same escape sequences. Rust strings
may contain newlines.
## Operators
Rust's set of operators contains very few surprises. Arithmetic is done with
`*`, `/`, `%`, `+`, and `-` (multiply, divide, remainder, plus, minus). `-` is
also a unary prefix operator that does negation. As in C, the bit 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;
~~~~
The main difference with C is that `++` and `--` are missing, and that
the logical bitwise operators have higher precedence — in C, `x & 2 > 0`
comes out as `x & (2 > 0)`, in Rust, it means `(x & 2) > 0`, which is
more likely to be what you expect (unless you are a C veteran).
## 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 syntax extension is being used, 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 is expanded at compile
time.
`fmt!` supports most of the directives that [printf][pf] supports, but
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, which is out
of scope of this tutorial.
# Control structures
## Conditionals
We've seen `if` pass by a few times already. To recap, braces are
compulsory, an optional `else` clause can be appended, 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 boolean (no
implicit conversion happens). If the arms return 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 will attempt to match each pattern
in order. For the first one that matches, the arm is executed.
~~~~
# 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")
}
~~~~
There is no 'falling through' between arms, as in C—only one arm is
executed, and it doesn't have to explicitly `break` out of the
construct when it is finished.
The part to the left of the arrow `=>` is called the *pattern*. Literals are
valid patterns and will match only their own value. The pipe operator
(`|`) can be used to assign multiple patterns to a single arm. Ranges
of numeric literal patterns can be expressed with two dots, as in `M..N`. The
underscore (`_`) is a wildcard pattern that matches everything.
The patterns in an 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 a 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, if the arm with the wildcard pattern was left off
in the above example, the typechecker would reject it.
A powerful application of pattern matching is *destructuring*, where
you use the matching to get at 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 everything, *and* binds that name
to the value of the matched thing inside of the arm block. Thus, `(0f,
y)` matches any tuple whose first element is zero, and binds `y` to
the second element. `(x, y)` matches any tuple, and binds both
elements to a variable.
Any `match` arm can have a guard clause (written `if EXPR`), 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 available in this guard expression.
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 say this to extract the fields from a
tuple, introducing two variables, `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` produces a loop that runs as long as its given condition
(which must have type `bool`) evaluates to true. Inside a loop, the
keyword `break` can be used to abort the loop, and `again` can be used
to abort the current iteration and continue with the next.
~~~~
let mut cake_amount = 8;
while cake_amount > 0 {
cake_amount -= 1;
}
~~~~
`loop` is the preferred way of writing `while true`:
~~~~
let mut x = 5;
loop {
x += x - 3;
if x % 5 == 0 { break; }
io::println(int::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 going over the elements of a
collection, Rust uses higher-order functions. We'll come back to those
in a moment.
# Basic datatypes
The core datatypes of Rust are structs, enums (tagged unions, algebraic data
types), and tuples. They are immutable by default.
~~~~
struct Point { x: float, y: float }
enum Shape {
Circle(Point, float),
Rectangle(Point, Point)
}
~~~~
## 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). The dot
operator is used to access struct fields (`mypoint.x`).
Fields that you want to mutate must be explicitly marked `mut`.
~~~~
struct Stack {
content: ~[int],
mut head: uint
}
~~~~
With a value of such a type, you can do `mystack.head += 1`. If `mut` were
omitted from the type, such an assignment would result in a type error.
Structs can be destructured in `match` patterns. 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: y } => { io::println(y.to_str()); }
Point { x: x, y: y } => { io::println(x.to_str() + " " + y.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.
## 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 records. 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 ergonomics.
The above declaration will define a type `shape` that can be used to
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({x: 0f, y: 0f}, 10f)` is the way to
create a new circle.
Enum variants need not have type parameters. This, for example, is
equivalent to a C enum:
~~~~
enum Direction {
North,
East,
South,
West
}
~~~~
This will define `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 an integer 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, etc.
When an enum is C-like the `as` cast operator can be used to get the
discriminator's value.
There is a special case for enums with a single variant. 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. If you say:
~~~~
enum GizmoId = int;
~~~~
That is a shorthand for this:
~~~~
enum GizmoId { GizmoId(int) }
~~~~
Enum types like this can have their content extracted with the
dereference (`*`) unary operator:
~~~~
# enum GizmoId = int;
let my_gizmo_id = GizmoId(10);
let id_int: int = *my_gizmo_id;
~~~~
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`:
~~~~
# type 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({x, y}, {x: x2, y: y2}) => (x2 - x) * (y2 - y)
}
}
~~~~
Like other patterns, a lone underscore ignores individual fields.
Ignoring all fields of a variant can be written `Circle(*)`. As in
their introductory form, nullary enum patterns are written without
parentheses.
~~~~
# type Point = {x: float, y: float};
# enum Direction { North, East, South, West }
fn point_from_direction(dir: Direction) -> Point {
match dir {
North => {x: 0f, y: 1f},
East => {x: 1f, y: 0f},
South => {x: 0f, y: -1f},
West => {x: -1f, y: 0f}
}
}
~~~~
## Tuples
Tuples in Rust behave exactly like records, except that their fields
do not have names (and can thus not be accessed with dot notation).
Tuples can have any arity except for 0 or 1 (though you may consider
nil, `()`, 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))
}
~~~~
# Functions and methods
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 modules, which we'll come
back to [later](#modules-and-crates)). They are introduced with the
`fn` keyword, the type of arguments are specified following colons and
the return type follows the arrow.
~~~~
fn repeat(string: &str, count: int) -> ~str {
let mut result = ~"";
for count.times {
result += string;
}
return result;
}
~~~~
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.
~~~~
# const copernicus: int = 0;
fn int_to_str(i: int) -> ~str {
if i == copernicus {
return ~"tube sock";
} else {
return ~"violin";
}
}
~~~~
~~~~
# const copernicus: int = 0;
fn int_to_str(i: int) -> ~str {
if i == copernicus { ~"tube sock" }
else { ~"violin" }
}
~~~~
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() { }
~~~~
Methods are like functions, except that they are defined for a specific
'self' type (like 'this' in C++). Calling a method is done with
dot notation, as in `my_vec.len()`. Methods may be defined on most
Rust types with the `impl` keyword. As an example, lets 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() {
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 most respects the `draw` method is defined
like any other function, with the exception of the name `self`. `self`
is a special value that is automatically defined in each method,
referring to the value being operated on. If we wanted we could add
additional methods to the same impl, or multiple impls for the same
type. We'll discuss methods more in the context of [traits and
generics](#generics).
> ***Note:*** The method definition syntax will change to require
> declaring the self type explicitly, as the first argument.
# The Rust memory model
At this junction let's take a detour to explain the concepts involved
in Rust's memory model. We've seen some of Rust's pointer sigils (`@`,
`~`, and `&`) float by in a few examples, and we aren't going to get
much further without explaining them. Rust has a very particular
approach to memory management that plays a significant role in shaping
the "feel" of the language. Understanding the memory landscape will
illuminate several of Rust's unique features as we encounter them.
Rust has three competing goals that inform its view of memory:
* Memory safety: memory that is managed by and is accessible to the
Rust language must be guaranteed to be valid; under normal
circumstances it must be impossible for Rust to trigger a
segmentation fault or leak memory
* Performance: high-performance low-level code must be able to employ
a number of allocation strategies; low-performance high-level code
must be able to employ a single, garbage-collection-based, heap
allocation strategy
* Concurrency: Rust must maintain memory safety guarantees, even for
code running in parallel
## How performance considerations influence the memory model
Most languages that offer strong memory safety guarantees rely upon a
garbage-collected heap to manage all of the objects. This approach is
straightforward both in concept and in implementation, but has
significant costs. Languages that take this approach tend to
aggressively pursue ways to ameliorate allocation costs (think the
Java Virtual Machine). Rust supports this strategy with _managed
boxes_: memory allocated on the heap whose lifetime is managed
by the garbage collector.
By comparison, languages like C++ offer very precise control over
where objects are allocated. In particular, it is common to put them
directly on the stack, avoiding expensive heap allocation. In Rust
this is possible as well, and the compiler will use a clever _pointer
lifetime analysis_ to ensure that no variable can refer to stack
objects after they are destroyed.
## How concurrency considerations influence the memory model
Memory safety in a concurrent environment involves avoiding race
conditions between two threads of execution accessing the same
memory. Even high-level languages often require programmers to
correctly employ locking to ensure that a program is free of races.
Rust starts from the position that memory cannot be shared between
tasks. Experience in other languages has proven that isolating each
task's heap from the others is a reliable strategy and one that is
easy for programmers to reason about. Heap isolation has the
additional benefit that garbage collection must only be done
per-heap. Rust never "stops the world" to garbage-collect memory.
Complete isolation of heaps between tasks implies that any data
transferred between tasks must be copied. While this is a fine and
useful way to implement communication between tasks, it is also very
inefficient for large data structures. Because of this, Rust also
employs a global _exchange heap_. Objects allocated in the exchange
heap have _ownership semantics_, meaning that there is only a single
variable that refers to them. For this reason, they are referred to as
_owned boxes_. All tasks may allocate objects on the exchange heap,
then transfer ownership of those objects to other tasks, avoiding
expensive copies.
## What to be aware of
Rust has three "realms" in which objects can be allocated: the stack,
the local heap, and the exchange heap. These realms have corresponding
pointer types: the borrowed pointer (`&T`), the managed box (`@T`),
and the owned box (`~T`). These three sigils will appear
repeatedly as we explore the language. Learning the appropriate role
of each is key to using Rust effectively.
# Boxes and pointers
In contrast to a lot of modern languages, aggregate types like records
and enums are _not_ represented as pointers to allocated memory in
Rust. They are, as in C and C++, represented directly. This means that
if you `let x = {x: 1f, y: 1f};`, you are creating a record on the
stack. If you then copy it into a data structure, the whole record is
copied, not just a pointer.
For small records like `point`, this is usually more efficient than
allocating memory and going through a pointer. But for big records, or
records with mutable fields, it can be useful to have a single copy on
the heap, and refer to that through a pointer.
Rust supports several types of pointers. 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 as presented here.
## Managed boxes
Managed boxes are pointers to heap-allocated, garbage collected memory.
Creating a managed box is done by simply applying the unary `@`
operator to an expression. The result of the expression will be boxed,
resulting in a box of the right type. Copying a shared 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.
~~~~
Any type that contains managed boxes or other managed types is
considered _managed_. Managed types are the only types that can
construct cyclic data structures in Rust, such as doubly-linked lists.
~~~
// A linked list node
struct Node {
mut next: MaybeNode,
mut prev: MaybeNode,
payload: int
}
enum MaybeNode {
SomeNode(@Node),
NoNode
}
let node1 = @Node { next: NoNode, prev: NoNode, payload: 1 };
let node2 = @Node { next: NoNode, prev: NoNode, payload: 2 };
let node3 = @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.
> ***Note:*** managed boxes are currently reclaimed through reference
> counting and cycle collection, but we will switch to a tracing
> garbage collector eventually.
## Owned boxes
In contrast to 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 them to be passed
between tasks efficiently.
Because owned boxes are uniquely owned, copying them involves allocating
a new owned box and duplicating the contents. Copying owned boxes
is expensive so the compiler will complain if you do so without writing
the word `copy`.
~~~~
let x = ~10;
let y = x; // error: copying a non-implicitly copyable type
~~~~
If you really want to copy a unique box you must say so explicitly.
~~~~
let x = ~10;
let y = copy x;
~~~~
This is where the 'move' operator comes in. It is similar to
`copy`, but it de-initializes its source. Thus, the owned box can move
from `x` to `y`, without violating the constraint that it only has a
single owner (if you used assignment instead of the move operator, the
box would, in principle, be copied).
~~~~
let x = ~10;
let y = move x;
~~~~
Owned boxes, when they do not contain any managed 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.
> ***Note:*** this discussion of copying vs moving does not account
> for the "last use" rules that automatically promote copy operations
> to moves. Last use is expected to be removed from the language in
> favor of explicit moves.
## 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 to owned pointers, where the holder of a unique
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 ways. For
example, in this code, each of these three local variables contains a
point, but allocated in a different place:
~~~
# struct Point { x: float, y: float }
let on_the_stack : Point = Point {x: 3.0, y: 4.0};
let shared_box : @Point = @Point {x: 5.0, y: 1.0};
let unique_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
`shared_box`, or between `shared_box` and `unique_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 shared_box : @Point = @Point {x: 5.0, y: 1.0};
# let unique_box : ~Point = ~Point {x: 7.0, y: 9.0};
# fn compute_distance(p1: &Point, p2: &Point) -> float { 0f }
compute_distance(&on_the_stack, shared_box);
compute_distance(shared_box, unique_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 record 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 created an alias: that is, another
route to the same data.
In the case of the boxes `shared_box` and `unique_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 shared/unique box is 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
# Vectors and strings
Vectors are 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
}
// A fixed-size stack vector
let stack_crayons: [Crayon * 3] = [Almond, AntiqueBrass, Apricot];
// A borrowed pointer to stack allocated vector
let stack_crayons: &[Crayon] = &[Almond, AntiqueBrass, Apricot];
// A local heap (managed) vector of crayons
let local_crayons: @[Crayon] = @[Aquamarine, Asparagus, AtomicTangerine];
// An exchange heap (owned) vector of crayons
let exchange_crayons: ~[Crayon] = ~[BananaMania, Beaver, Bittersweet];
~~~
Vector literals are enclosed in square brackets and dereferencing is
also done with square brackets (zero-based):
~~~~
# enum Crayon { Almond, AntiqueBrass, Apricot,
# Aquamarine, Asparagus, AtomicTangerine,
# BananaMania, Beaver, Bittersweet };
# fn draw_scene(c: Crayon) { }
let crayons = [BananaMania, Beaver, Bittersweet];
match crayons[0] {
Bittersweet => draw_scene(crayons[0]),
_ => ()
}
~~~~
By default, vectors are immutable—you can not replace their elements.
The type written as `[mut T]` is a vector with mutable
elements. Mutable vector literals are written `[mut]` (empty) or `[mut
1, 2, 3]` (with elements).
~~~~
# enum Crayon { Almond, AntiqueBrass, Apricot,
# Aquamarine, Asparagus, AtomicTangerine,
# BananaMania, Beaver, Bittersweet };
let crayons = [mut BananaMania, Beaver, Bittersweet];
crayons[0] = AtomicTangerine;
~~~~
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];
let our_crayons = my_crayons + your_crayons;
~~~~
The `+=` operator also works as expected, provided the assignee
lives in a mutable slot.
~~~~
# enum Crayon { Almond, AntiqueBrass, Apricot,
# Aquamarine, Asparagus, AtomicTangerine,
# BananaMania, Beaver, Bittersweet };
let mut my_crayons = ~[Almond, AntiqueBrass, Apricot];
let your_crayons = ~[BananaMania, Beaver, Bittersweet];
my_crayons += your_crayons;
~~~~
> ***Note:*** The above examples of vector addition use owned
> vectors. Some operations on slices and stack vectors are
> not well supported yet, owned vectors are often the most
> usable.
Strings are simply vectors of `[u8]`, though they have a distinct
type. They support most of the same allocation aptions as
vectors, though the string literal without a storage sigil, e.g.
`"foo"` is treated differently than a comparable vector (`[foo]`).
Where
~~~
// A plain string is a slice to read-only (static) memory
let stack_crayons: &str = "Almond, AntiqueBrass, Apricot";
// The same thing, but without
let stack_crayons: &str = &"Almond, AntiqueBrass, Apricot";
// A local heap (managed) string
let local_crayons: @str = @"Aquamarine, Asparagus, AtomicTangerine";
// An exchange heap (owned) string
let exchange_crayons: ~str = ~"BananaMania, Beaver, Bittersweet";
~~~
Both vectors and strings support a number of useful
[methods](#implementation). While we haven't covered methods yet,
most vector functionality is provided by methods, so let's have a
brief look at a few common ones.
~~~
# use 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". 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 = 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 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.
~~~~
# type mygoodness = fn(~str) -> ~str; type what_the = int;
let bloop = |well, oh: mygoodness| -> what_the { fail oh(well) };
~~~~
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, they can only be used in argument
position and cannot be stored in structures nor returned from
functions. Despite the 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).
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
will not 'see' 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 {
return fn@(s: ~str) -> ~str { s + suffix };
}
fn main() {
let shout = mk_appender(~"!");
io::println(shout(~"hey ho, let's go"));
}
~~~~
This example uses the long closure syntax, `fn@(s: ~str) ...`,
making the fact that we are declaring a box closure explicit. In
practice boxed closures are usually defined with the short closure
syntax introduced earlier, in which case the compiler will infer
the type of closure. Thus our managed closure example could also
be written:
~~~~
fn mk_appender(suffix: ~str) -> fn@(~str) -> ~str {
return |s| s + suffix;
}
~~~~
## 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—meaning no other code can access
them. Owned closures are used in concurrent code, particularly
for spawning [tasks](#tasks).
## Closure compatibility
A nice property of Rust closures is that 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
wants to do nothing with its function argument beyond calling it, you
should almost always specify the type of that argument as `fn()`, so
that callers have the flexibility to pass whatever they want.
~~~~
fn call_twice(f: fn()) { f(); f(); }
call_twice(|| { ~"I am an inferred stack closure"; } );
call_twice(fn&() { ~"I am also a stack closure"; } );
call_twice(fn@() { ~"I am a managed closure"; });
call_twice(fn~() { ~"I am a owned closure"; });
fn bare_function() { ~"I am a plain function"; }
call_twice(bare_function);
~~~~
> ***Note:*** Both the syntax and the semantics will be changing
> in small ways. At the moment they can be unsound in multiple
> scenarios, particularly with non-copyable types.
## Do syntax
Closures in Rust are frequently used in combination with higher-order
functions to simulate control structures like `if` and
`loop`. 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;
}
}
~~~~
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. Using a pointer means that the function can be used
for vectors of any type, even large records that would be impractical
to copy out of the vector on each iteration. 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| {
debug!("%i", *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| {
debug!("%i", *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 is moved outside of the
parenthesis where it looks visually more like a typical block of
code. The `do` expression is purely syntactic sugar for a call that
takes a final closure argument.
`do` is often used for task spawning.
~~~~
use task::spawn;
do spawn() || {
debug!("I'm a task, whatever");
}
~~~~
That's nice, but look at all those bars and parentheses - that's two empty
argument lists back to back. Wouldn't it be great if they weren't
there?
~~~~
# use task::spawn;
do spawn {
debug!("Kablam!");
}
~~~~
Empty argument lists can be omitted from `do` expressions.
## For loops
Most iteration in Rust is done with `for` loops. Like `do`,
`for` is a nice syntax for doing control flow with closures.
Additionally, within a `for` loop, `break`, `again`, 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 = vec::each;
# use println = 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 builtin 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 `again`.
~~~~
# use each = vec::each;
# use println = 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 — this will cause a return to happen from the outer
function, not just the loop body.
~~~~
# use each = 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.
# Generics
Throughout this tutorial, we've been defining functions that act only on
single data types. With type parameters we can also define functions that
may be invoked on multiple types.
~~~~
fn map(vector: &[T], function: fn(v: &T) -> U) -> ~[U] {
let mut accumulator = ~[];
for vec::each(vector) |element| {
vec::push(accumulator, 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 content agree with
each other.
Inside a generic function, the names of the type parameters
(capitalized by convention) stand for opaque types. You can't look
inside them, but you can pass them around. Note that instances of
generic types are almost always 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::map::HashMap;
type Set = HashMap;
struct Stack {
elements: ~[mut T]
}
enum Maybe {
Just(T),
Nothing
}
~~~~
These declarations produce valid types like `Set`, `Stack`
and `Maybe`.
Generic functions in Rust are compiled to very efficient runtime code
through a process called _monomorphisation_. This big word just means
that, for each generic function you call, the compiler generates a
specialized version that is optimized specifically for the argument
types. 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
in them aspects of Java interfaces, and Haskellers will notice their
similarities to type classes.
As motivation, let us consider copying in Rust. Perhaps surprisingly,
the copy operation is not defined for all Rust types. In
particular, types with user-defined destructors cannot be copied,
either implicitly or explicitly, and neither can types that own other
types containing destructors (the actual mechanism for defining
destructors will be discussed elsewhere).
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
}
~~~~
We can tell the compiler though that the `head` function is only for
copyable types with 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.
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 using the
`copy` expression. All types are copyable unless they are classes
with destructors or otherwise contain classes with destructors.
* `Send` - Sendable (owned) types. All types are sendable unless they
contain managed boxes, managed closures, or otherwise managed
types. Sendable 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.
## Declaring and implementing traits
A trait consists of a set of methods, or may be empty, as is the case
with `Copy`, `Send`, and `Const`. A method is a function that
can be applied to a `self` value and a number of arguments, using the
dot notation: `self.foo(arg1, arg2)`.
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();
}
~~~~
To actually implement a trait for a given type, the `impl` form is
used. This defines implementations of `Printable` for the `int` and
`~str` types.
~~~~
# trait Printable { fn print(); }
impl int: Printable {
fn print() { io::println(fmt!("%d", self)) }
}
impl ~str: Printable {
fn print() { io::println(self) }
}
# 1.print();
# (~"foo").print();
~~~~
Given these, we may call `1.print()` to print `"1"`, or
`(~"foo").print()` to print `"foo"` again, as with . This is basically a form of
static overloading—when the Rust compiler sees the `print` method
call, it looks for an implementation that matches the type with a
method that matches the name, and simply calls that.
Traits may themselves contain type parameters. A trait for
generalized sequence types might look like the following:
~~~~
trait Seq {
fn len() -> uint;
fn iter(b: fn(v: &T));
}
impl ~[T]: Seq {
fn len() -> uint { vec::len(self) }
fn iter(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
after the colon in the `impl` -- *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 type implementing the trait
trait Eq {
fn equals(other: &self) -> bool;
}
// In an impl, self refers to the value of the receiver
impl int: Eq {
fn equals(other: &int) -> bool { *other == self }
}
~~~~
Notice that in the trait definition, `equals` takes a `self` type
argument, whereas, in the impl, `equals` takes an `int` type argument,
and uses `self` as the name of the receiver (analogous to the `this` pointer
in C++).
## Bounded type parameters and static method dispatch
Traits give us a language for talking about the abstract capabilities
of types, and we can use this to place _bounds_ on type parameters,
so that we can then operate on generic types.
~~~~
# trait Printable { fn print(); }
fn print_all(printable_things: ~[T]) {
for printable_things.each |thing| {
thing.print();
}
}
~~~~
By declaring `T` as conforming to the `Printable` trait (as we earlier
did with `Copy`), it becomes possible to call methods from that trait
on values of that type 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 spaces,
as in this version of `print_all` that makes copies of elements.
~~~
# trait Printable { fn print(); }
fn print_all(printable_things: ~[T]) {
let mut i = 0;
while i < printable_things.len() {
let copy_of_thing = printable_things[0];
copy_of_thing.print();
}
}
~~~
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.
## Casting to a trait type 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 int: Drawable { fn draw() {} }
# fn new_circle() -> int { 1 }
trait Drawable { fn draw(); }
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 squares
(assuming those have suitable `Drawable` traits defined), but not on
an array containing both circles and squares. When such behavior is
needed, a trait name can alternately be used as a type.
~~~~
# trait Drawable { fn draw(); }
fn draw_all(shapes: ~[@Drawable]) {
for shapes.each |shape| { shape.draw(); }
}
~~~~
In this example there is no type parameter. Instead, the `@Drawable`
type is used to refer to any managed box value that implements the
`Drawable` trait. To construct such a value, you use the `as` operator
to cast a value to a trait type:
~~~~
# type Circle = int; type Rectangle = bool;
# trait Drawable { fn draw(); }
# fn new_circle() -> Circle { 1 }
# fn new_rectangle() -> Rectangle { true }
# fn draw_all(shapes: ~[Drawable]) {}
impl @Circle: Drawable { fn draw() { ... } }
impl @Rectangle: Drawable { fn draw() { ... } }
let c: @Circle = @new_circle();
let r: @Rectangle = @new_rectangle();
draw_all(~[c as @Drawable, r as @Drawable]);
~~~~
Note that, like strings and vectors, trait types have dynamic size
and may only be used via one of the pointer types. In turn, the
`impl` is defined for `@Circle` and `@Rectangle` instead of for
just `Circle` and `Rectangle`. Other pointer types work as well.
~~~{.xfail-test}
# type Circle = int; type Rectangle = int;
# trait Drawable { fn draw(); }
# impl int: Drawable { fn draw() {} }
# fn new_circle() -> int { 1 }
# fn new_rectangle() -> int { 2 }
// A managed trait instance
let boxy: @Drawable = @new_circle() as @Drawable;
// An owned trait instance
let owny: ~Drawable = ~new_circle() as ~Drawable;
// A borrowed trait instance
let stacky: &Drawable = &new_circle() as &Drawable;
~~~
> ***Note:*** Other pointer types actually _do not_ work here. This is
> an evolving corner of the language.
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 (vtable) to decide at runtime which
method to call.
This usage of traits is similar to Java interfaces.
# Modules and crates
The Rust namespace is divided into modules. Each source file starts
with its own module.
## Local modules
The `mod` keyword can be used to open a new, local module. In the
example below, `chicken` lives in the module `farm`, so, unless you
explicitly import it, you must refer to it by its long name,
`farm::chicken`.
~~~~
#[legacy_exports]
mod farm {
fn chicken() -> ~str { ~"cluck cluck" }
fn cow() -> ~str { ~"mooo" }
}
fn main() {
io::println(farm::chicken());
}
~~~~
Modules can be nested to arbitrary depth.
## Crates
The unit of independent compilation in Rust is the crate. Libraries
tend to be packaged as crates, and your own programs may consist of
one or more crates.
When compiling a single `.rs` 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.
It is also possible to include multiple files in a crate. For this
purpose, you create a `.rc` crate file, which references any number of
`.rs` code files. A crate file could look like this:
~~~~ {.ignore}
#[link(name = "farm", vers = "2.5", author = "mjh")];
#[crate_type = "lib"];
mod cow;
mod chicken;
mod horse;
~~~~
Compiling this file will cause `rustc` to look for files named
`cow.rs`, `chicken.rs`, `horse.rs` in the same directory as the `.rc`
file, compile them all together, and, depending 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(...)]` part 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 in your `.rc` file:
~~~~ {.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
Having compiled a crate that contains the `#[crate_type = "lib"]`
attribute, you can use it in another crate with a `use`
directive. We've already seen `extern mod std` in several of the
examples, which loads in the [standard library][std].
[std]: http://doc.rust-lang.org/doc/std/index/General.html
`use` directives can appear in a crate file, or at the top level of a
single-file `.rs` crate. They will cause the compiler to search its
library search path (which you can extend with `-L` switch) for a Rust
crate library with the right name.
It is possible to provide more specific information when using an
external crate.
~~~~ {.ignore}
extern mod myfarm (name = "farm", vers = "2.7");
~~~~
When a comma-separated list of name/value pairs is given after `use`,
these are matched against the attributes provided in the `link`
attribute of the crate file, and a crate is only used when the two
match. A `name` value can be given to override the name used to search
for the crate. So the above would import the `farm` crate under the
local name `myfarm`.
Our example crate declared this set of `link` attributes:
~~~~ {.ignore}
#[link(name = "farm", vers = "2.5", author = "mjh")];
~~~~
The version does not match the one provided in the `use` directive, so
unless the compiler can find another crate with the right version
somewhere, it will complain that no matching crate was found.
## The core library
A set of basic library routines, mostly related to built-in datatypes
and the task system, are always implicitly linked and included in any
Rust program.
This library is documented [here][core].
[core]: http://doc.rust-lang.org/doc/core
## A minimal example
Now for something that you can actually compile yourself. We have
these two files:
~~~~
// mylib.rs
#[link(name = "mylib", vers = "1.0")];
fn world() -> ~str { ~"world" }
~~~~
~~~~ {.ignore}
// main.rs
extern mod mylib;
fn main() { io::println(~"hello " + mylib::world()); }
~~~~
Now compile and run like this (adjust to your platform if necessary):
~~~~ {.notrust}
> rustc --lib mylib.rs
> rustc main.rs -L .
> ./main
"hello world"
~~~~
## Importing
When using identifiers from other modules, it can get tiresome to
qualify them with the full module path every time (especially when
that path is several modules deep). Rust allows you to import
identifiers at the top of a file, module, or block.
~~~~
extern mod std;
use io::println;
fn main() {
println(~"that was easy");
}
~~~~
It is also possible to import just the name of a module (`use
std::list;`, then use `list::find`), to import all identifiers exported
by a given module (`use io::*`), or to import a specific set
of identifiers (`use math::{min, max, pi}`).
You can rename an identifier when importing using the `=` operator:
~~~~
use prnt = io::println;
~~~~
## Exporting
By default, a module exports everything that it defines. This can be
restricted with `export` directives at the top of the module or file.
~~~~
mod enc {
export encrypt, decrypt;
const SUPER_SECRET_NUMBER: int = 10;
fn encrypt(n: int) -> int { n + SUPER_SECRET_NUMBER }
fn decrypt(n: int) -> int { n - SUPER_SECRET_NUMBER }
}
~~~~
This defines a rock-solid encryption algorithm. Code outside of the
module can refer to the `enc::encrypt` and `enc::decrypt` identifiers
just fine, but it does not have access to `enc::super_secret_number`.
## Namespaces
Rust uses three different namespaces: one for modules, one for types,
and one for values. This means that this code is valid:
~~~~
#[legacy_exports]
mod buffalo {
type buffalo = int;
fn buffalo(+buffalo: buffalo) -> buffalo { buffalo }
}
fn main() {
let buffalo: buffalo::buffalo = 1;
buffalo::buffalo::(buffalo::buffalo(buffalo));
}
~~~~
You don't want to write things like that, but it *is* very practical
to not have to worry about name clashes between types, values, and
modules.
## Resolution
The resolution process in Rust simply goes up the chain of contexts,
looking for the name in each context. Nested functions and modules
create new contexts inside their parent function or module. A file
that's part of a bigger crate will have that crate's context as its
parent context.
Identifiers can shadow each other. In this program, `x` is of type
`int`:
~~~~
type MyType = ~str;
fn main() {
type MyType = int;
let x: MyType;
}
~~~~
An `use` directive will only import into the namespaces for which
identifiers are actually found. Consider this example:
~~~~
mod foo { fn bar() {} }
fn baz() {
let bar = 10u;
{
use foo::bar;
let quux = bar;
}
}
~~~~
When resolving the type name `bar` in the `quux` definition, the
resolver will first look at local block context for `baz`. This has an
import named `bar`, but that's function, not a value, So it continues
to the `baz` function context and finds a value named `bar` defined
there.
Normally, multiple definitions of the same identifier in a scope are
disallowed. Local variables defined with `let` are an exception to
this—multiple `let` directives can redefine the same variable in a
single scope. When resolving the name of such a variable, the most
recent definition is used.
~~~~
fn main() {
let x = 10;
let x = x + 10;
assert x == 20;
}
~~~~
This makes it possible to rebind a variable without actually mutating
it, which is mostly useful for destructuring (which can rebind, but
not assign).
# 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 metada
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