Tutorialcontents

REPL

Let's start by getting acquainted with Roc's Read-Eval-Print-Loop, or REPL for short.

You can use the online REPL at roc-lang.org/repl.

Or you can run this in a terminal: roc repl, and if Roc is installed, you should see this:

  The rockin’ roc repl
────────────────────────

Enter an expression, or :help, or :q to quit.

So far, so good!

Hello, World!

Try typing this in the REPL and pressing Enter:

"Hello, World!"

The REPL should cheerfully display the following:

"Hello, World!" : Str

Congratulations! You've just written your first Roc code.

Naming Things

When you entered the expression "Hello, World!", the REPL printed it back out. It also printed : Str, because Str is that expression's type. We'll talk about types later; for now, let's ignore the : and whatever comes after it whenever we see them.

You can assign specific names to expressions. Try entering these lines:

greeting = "Hi"
audience = "World"

From now until you exit the REPL, you can refer to either greeting or audience by those names! We'll use these later on in the tutorial.

Arithmetic

Now let's try using an operator, specifically the + operator. Enter this:

1 + 1

You should see this output:

2 : Num * 

According to the REPL, one plus one equals two. Sounds right!

Roc will respect order of operations when using multiple arithmetic operators like + and -, but you can use parentheses to specify exactly how they should be grouped.

1 + 2 * (3 - 4)

-1 : Num *

Calling Functions

Let's try calling a function:

Str.concat "Hi " "there!"

"Hi there!" : Str

Here we're calling the Str.concat function and passing two arguments: the string "Hi " and the string "there!". This concatenates the two strings together (that is, it puts one after the other) and returns the resulting combined string of "Hi there!".

Note that in Roc, we don't need parentheses or commas to call functions. We don't write Str.concat("Hi ", "there!") but rather Str.concat "Hi " "there!".

That said, just like in the arithmetic example above, we can use parentheses to specify how nested function calls should work. For example, we could write this:

Str.concat "Birds: " (Num.toStr 42)

"Birds: 42" : Str

This calls Num.toStr on the number 42, which converts it into the string "42", and then passes that string as the second argument to Str.concat.

The parentheses are important here to specify how the function calls nest. Try removing them, and see what happens:

Str.concat "Birds: " Num.toStr 42

<error>

The error tells us that we've given Str.concat too many arguments. Indeed we have! We've passed it three arguments:

1. The string "Birds"
2. The function Num.toStr
3. The number 42

That's not what we intended to do. Putting parentheses around the Num.toStr 42 call clarifies that we want it to be evaluated as its own expression, rather than being two arguments to Str.concat.

Both the Str.concat function and the Num.toStr function have a dot in their names. In Str.concat, Str is the name of a module, and concat is the name of a function inside that module. Similarly, Num is a module, and toStr is a function inside that module.

We'll get into more depth about modules later, but for now you can think of a module as a named collection of functions. Eventually we'll discuss how to use them for more than that.

String Interpolation

An alternative syntax for Str.concat is string interpolation, which looks like this:

"$(greeting) there, $(audience)!"

This is syntax sugar for calling Str.concat several times, like so:

Str.concat greeting (Str.concat " there, " (Str.concat audience "!"))

You can put entire single-line expressions inside the parentheses in string interpolation. For example:

"Two plus three is: $(Num.toStr (2 + 3))"

By the way, there are many other ways to put strings together! Check out the documentation for the Str module for more.

Building an Application

Let's move out of the REPL and create our first Roc application!

Make a file named main.roc and put this in it:

app "hello"
    packages { pf: "https://github.com/roc-lang/basic-cli/releases/download/0.9.0/oKWkaruh2zXxin_xfsYsCJobH1tO8_JvNkFzDwwzNUQ.tar.br" }
    imports [pf.Stdout]
    provides [main] to pf

main =
    Stdout.line "I'm a Roc application!"

Try running this with:

roc dev

You should see a message about a file being downloaded, followed by this:

I'm a Roc application!

Congratulations, you've written your first Roc application! We'll go over what the parts above main do later, but let's play around a bit first.

Defs

Try replacing the main line with this:

birds = 3

iguanas = 2

total = Num.toStr (birds + iguanas)

main =
    Stdout.line "There are $(total) animals."

Now run roc dev again. This time the "Downloading ..." message won't appear; the file has been cached from last time, and won't need to be downloaded again.

You should see this:

There are 5 animals.

main.roc now has four definitions (defs for short) birds, iguanas, total, and main.

A definition names an expression.

• The first two defs assign the names birds and iguanas to the expressions 3 and 2.
• The next def assigns the name total to the expression Num.toStr (birds + iguanas).
• The last def assigns the name main to an expression which returns a Task. We'll discuss tasks later.

Once we have a def, we can use its name in other expressions. For example, the total expression refers to birds and iguanas, and Stdout.line "There are $(total) animals." refers to total.

You can name a def using any combination of letters and numbers, but they have to start with a lowercase letter.

Note: Defs are constant; they can't be reassigned. We'd get an error if we wrote these two defs in the same scope:

birds = 3
birds = 2

Defining Functions

So far we've called functions like Num.toStr, Str.concat, and Stdout.line. Next let's try defining a function of our own.

birds = 3

iguanas = 2

total = addAndStringify birds iguanas

main =
    Stdout.line "There are $(total) animals."

addAndStringify = \num1, num2 ->
    Num.toStr (num1 + num2)

This new addAndStringify function we've defined accepts two numbers, adds them, calls Num.toStr on the result, and returns that.

The \num1, num2 -> syntax defines a function's arguments, and the expression after the -> is the body of the function. Whenever a function gets called, its body expression gets evaluated and returned.

if-then-else

Let's modify this function to return an empty string if the numbers add to zero.

addAndStringify = \num1, num2 ->
    sum = num1 + num2

    if sum == 0 then
        ""
    else
        Num.toStr sum

We did two things here:

• We introduced a local def named sum, and set it equal to num1 + num2. Because we defined sum inside addAndStringify, it's local to that scope and can't be accessed outside that function.
• We added an if-then-else conditional to return either "" or Num.toStr sum depending on whether sum == 0.

Every if must be accompanied by both then and also else. Having an if without an else is an error, because if is an expression, and all expressions must evaluate to a value. If there were ever an if without an else, that would be an expression that might not evaluate to a value!

else if

We can combine if and else to get else if, like so:

addAndStringify = \num1, num2 ->
    sum = num1 + num2

    if sum == 0 then
        ""
    else if sum < 0 then
        "negative"
    else
        Num.toStr sum

Note that else if is not a separate language keyword! It's just an if/else where the else branch contains another if/else. This is easier to see with different indentation:

addAndStringify = \num1, num2 ->
    sum = num1 + num2

    if sum == 0 then
        ""
    else
        if sum < 0 then
            "negative"
        else
            Num.toStr sum

This differently-indented version is equivalent to writing else if sum < 0 then on the same line, although the convention is to use the original version's style.

Comments

This is a comment in Roc:

# The 'name' field is unused by addAndStringify

Whenever you write # it means that the rest of the line is a comment, and will not affect the running program. Roc does not have multiline comment syntax.

Doc Comments

Comments that begin with ## are "doc comments" which will be included in generated documentation (roc docs). They can include code blocks by adding five spaces after ##.

## This is a comment for documentation, and includes a code block.
##
##     x = 2
##     expect x == 2

Like other comments, doc comments do not affect the running program.

Debugging

Print debugging is the most common debugging technique in the history of programming, and Roc has a dbg keyword to facilitate it. Here's an example of how to use dbg:

pluralize = \singular, plural, count ->
    dbg count

    if count == 1 then
        singular
    else
        plural

Whenever this dbg line of code is reached, the value of count will be printed to stderr, along with the source code file and line number where the dbg itself was written:

[pluralize.roc 6:8] 5

Here, [pluralize.roc 6:8] tells us that this dbg was written in the file pluralize.roc on line 6, column 8.

You can give dbg any expression you like, for example:

dbg Str.concat singular plural

An easy way to print multiple values at a time is to wrap them in a tag, for example a concise tag like T:

dbg T "the value of count is:" count

Note: dbg is a debugging tool, and is only available when running your program with roc program.roc, roc dev program.roc or roc test program.roc. When you build a standalone binary with roc build, any uses of dbg won't be included!

Records

Currently our addAndStringify function takes two arguments. We can instead make it take one argument like so:

total = addAndStringify { birds: 5, iguanas: 7 }

addAndStringify = \counts ->
    Num.toStr (counts.birds + counts.iguanas)

The function now takes a record, which is a group of named values. Records are not objects; they don't have methods or inheritance, they just store information.

The expression { birds: 5, iguanas: 7 } defines a record with two fields (the birds field and the iguanas field) and then assigns the number 5 to the birds field and the number 7 to the iguanas field. Order doesn't matter with record fields; we could have also specified iguanas first and birds second, and Roc would consider it the exact same record.

When we write counts.birds, it accesses the birds field of the counts record, and when we write counts.iguanas it accesses the iguanas field.

When we use == on records, it compares all the fields in both records with ==, and only considers the two records equal if all of their fields are equal. If one record has more fields than the other, or if the types associated with a given field are different between one field and the other, the Roc compiler will give an error at build time.

Note: Some other languages have a concept of "identity equality" that's separate from the "structural equality" we just described. Roc does not have a concept of identity equality; this is the only way equality works!

Accepting extra fields

The addAndStringify function will accept any record with at least the fields birds and iguanas, but it will also accept records with more fields. For example:

total = addAndStringify { birds: 5, iguanas: 7 }

# The `note` field is unused by addAndStringify
totalWithNote = addAndStringify { birds: 4, iguanas: 3, note: "Whee!" }

addAndStringify = \counts ->
    Num.toStr (counts.birds + counts.iguanas)

This works because addAndStringify only uses counts.birds and counts.iguanas. If we were to use counts.note inside addAndStringify, then we would get an error because total is calling addAndStringify passing a record that doesn't have a note field.

Record shorthands

Roc has a couple of shorthands you can use to express some record-related operations more concisely.

Instead of writing \record -> record.x we can write .x and it will evaluate to the same thing: a function that takes a record and returns its x field. You can do this with any field you want. For example:

# returnFoo is a function that takes a record
# and returns the `foo` field of that record.
returnFoo = .foo

returnFoo { foo: "hi!", bar: "blah" }
# returns "hi!"

Sometimes we assign a def to a field that happens to have the same name—for example, { x: x }. In these cases, we shorten it to writing the name of the def alone—for example, { x }. We can do this with as many fields as we like; here are several different ways to define the same record:

• { x: x, y: y }
• { x, y }
• { x: x, y }
• { x, y: y }

Record destructuring

We can use destructuring to avoid naming a record in a function argument, instead giving names to its individual fields:

addAndStringify = \{ birds, iguanas } ->
    Num.toStr (birds + iguanas)

Here, we've destructured the record to create a birds def that's assigned to its birds field, and an iguanas def that's assigned to its iguanas field. We can customize this if we like:

addAndStringify = \{ birds, iguanas: lizards } ->
    Num.toStr (birds + lizards)

In this version, we created a lizards def that's assigned to the record's iguanas field. (We could also do something similar with the birds field if we like.)

Finally, destructuring can be used in defs too:

{ x, y } = { x: 5, y: 10 }

Making records from other records

So far we've only constructed records from scratch, by specifying all of their fields. We can also construct new records by using another record to use as a starting point, and then specifying only the fields we want to be different. For example, here are two ways to get the same record:

original = { birds: 5, zebras: 2, iguanas: 7, goats: 1 }
fromScratch = { birds: 4, zebras: 2, iguanas: 3, goats: 1 }
fromOriginal = { original & birds: 4, iguanas: 3 }

The fromScratch and fromOriginal records are equal, although they're defined in different ways.

• fromScratch was built using the same record syntax we've been using up to this point.
• fromOriginal created a new record using the contents of original as defaults for fields that it didn't specify after the &.

Note that & can't introduce new fields to a record, or change the types of existing fields. (Trying to do either of these will result in an error at build time!)

Default Value Record Fields

Roc supports default value record fields using the ? operator. This can be a useful pattern where you pass a function a record of configuration values, some of which you'd like to provide defaults for.

In Roc you can write a function like:

table = \{
        height,
        width,
        title ? "oak",
        description ? "a wooden table"
    }
    ->

This is using default value field destructuring to destructure a record while providing default values for any fields that might be missing.

Here's the type of table:

table :
    {
        height : Pixels,
        width : Pixels,
        title ? Str,
        description ? Str,
    }
    -> Table

This says that table takes a record with two fields that are required, height and width, and two fields that may be omitted, title and description. It also says that the height and width fields have the type Pixels, a type alias for some numeric type, and the title and description fields have the type Str. This means you can choose to omit the title, description, or both fields, when calling the function... but if you provide them, they must have the type Str.

This is also the type that would have been inferred for table if no annotation had been written. Roc's compiler can tell from the destructuring syntax title ? "" that title is a default value field, and that it has the type Str.

Destructuring is the only way to implement a record with default value fields. For example, if you write the expression config.title and title is a default value field, you'll get a compile error.

Default values is a concept that exists only in record fields, and it's intended for the use case of config records like this. The ergonomics of destructuring mean this wouldn't be a good fit for data modeling, consider using a custom tag union or the Result type instead.

Tags & Pattern Matching

Sometimes we want to represent that something can have one of several values. For example:

stoplightColor =
    if something > 0 then
        Red
    else if something == 0 then
        Yellow
    else
        Green

Here, stoplightColor can have one of three values: Red, Yellow, or Green. The capitalization is very important! If these were lowercase (red, yellow, green), then they would refer to defs. However, because they are capitalized, they instead refer to tags.

A tag is a literal value just like a number or a string. Similarly to how I can write the number 42 or the string "forty-two" without defining them first, I can also write the tag FortyTwo without defining it first. Also, similarly to how 42 == 42 and "forty-two" == "forty-two", it's also the case that FortyTwo == FortyTwo.

Let's say we wanted to turn stoplightColor from a Red, Green, or Yellow into a string. Here's one way we could do that:

stoplightStr =
    if stoplightColor == Red then
        "red"
    else if stoplightColor == Green then
        "green"
    else
        "yellow"

We can express this logic more concisely using when/is instead of if/then:

stoplightStr =
    when stoplightColor is
        Red -> "red"
        Green -> "green"
        Yellow -> "yellow"

This results in the same value for stoplightStr. In both the when version and the if version, we have three conditional branches, and each of them evaluates to a string. The difference is how the conditions are specified; here, we specify between when and is that we're making comparisons against stoplightColor, and then we specify the different things we're comparing it to: Red, Green, and Yellow.

Besides being more concise, there are other advantages to using when here.

1. We don't have to specify an else branch, so the code can be more self-documenting about exactly what all the options are.
2. We get more compiler help. If we try deleting any of these branches, we'll get a compile-time error saying that we forgot to cover a case that could come up. For example, if we delete the Green -> branch, the compiler will say that we didn't handle the possibility that stoplightColor could be Green. It knows this because Green is one of the possibilities in our stoplightColor = if ... definition.

We can still have the equivalent of an else branch in our when if we like. Instead of writing else, we write _ -> like so:

stoplightStr =
    when stoplightColor is
        Red -> "red"
        _ -> "not red"

This lets us more concisely handle multiple cases. However, it has the downside that if we add a new case - for example, if we introduce the possibility of stoplightColor being Orange, the compiler can no longer tell us we forgot to handle that possibility in our when. After all, we are handling it - just maybe not in the way we'd decide to if the compiler had drawn our attention to it!

We can make this when exhaustive (that is, covering all possibilities) without using _ -> by using | to specify multiple matching conditions for the same branch:

stoplightStr =
    when stoplightColor is
        Red -> "red"
        Green | Yellow -> "not red"

You can read Green | Yellow as "either Green or Yellow". By writing it this way, if we introduce the possibility that stoplightColor can be Orange, we'll get a compiler error telling us we forgot to cover that case in this when, and then we can handle it however we think is best.

We can also combine if and when to make branches more specific:

stoplightStr =
    when stoplightColor is
        Red -> "red"
        Green | Yellow if contrast > 75 -> "not red, but very high contrast"
        Green | Yellow if contrast > 50 -> "not red, but high contrast"
        Green | Yellow -> "not red"

This will give the same answer for stoplightStr as if we had written the following:

stoplightStr =
    when stoplightColor is
        Red -> "red"
        Green | Yellow ->
            if contrast > 75 then
                "not red, but very high contrast"
            else if contrast > 50 then
                "not red, but high contrast"
            else
                "not red"

Either style can be a reasonable choice depending on the circumstances.

Tags with payloads

Tags can have payloads—that is, values inside them. For example:

stoplightColor =
    if something > 100 then
        Red
    else if something > 0 then
        Yellow
    else if something == 0 then
        Green
    else
        Custom "some other color"

stoplightStr =
    when stoplightColor is
        Red -> "red"
        Green | Yellow -> "not red"
        Custom description -> description

This makes two changes to our earlier stoplightColor / stoplightStr example.

1. We sometimes chose to set stoplightColor to be Custom "some other color". When we did this, we gave the Custom tag a payload of the string "some other color".
2. We added a Custom tag in our when, with a payload which we named description. Because we did this, we were able to refer to description in the body of the branch (that is, the part after the ->) just like a def or a function argument.

Any tag can be given a payload like this. A payload doesn't have to be a string; we could also have said (for example) Custom { r: 40, g: 60, b: 80 } to specify an RGB color instead of a string. Then in our when we could have written Custom record -> and then after the -> used record.r, record.g, and record.b to access the 40, 60, 80 values. We could also have written Custom { r, g, b } -> to destructure the record, and then accessed these r, g, and b defs after the -> instead.

A tag can also have a payload with more than one value. Instead of Custom { r: 40, g: 60, b: 80 } we could write Custom 40 60 80. If we did that, then instead of destructuring a record with Custom { r, g, b } -> inside a when, we would write Custom r g b -> to destructure the values directly out of the payload.

We refer to whatever comes before a -> in a when expression as a pattern—so for example, in the Custom description -> description branch, Custom description would be a pattern. In programming, using patterns in branching conditionals like when is known as pattern matching. You may hear people say things like "let's pattern match on Custom here" as a way to suggest making a when branch that begins with something like Custom description ->.

Pattern Matching on Lists

You can also pattern match on lists, like so:

when myList is
    [] -> 0 # the list is empty
    [Foo, ..] -> 1 # it starts with a Foo tag
    [_, ..] -> 2 # it contains at least one element, which we ignore
    [Foo, Bar, ..] -> 3 # it starts with a Foo tag followed by a Bar tag
    [Foo, Bar, Baz] -> 4 # it has exactly 3 elements: Foo, Bar, and Baz
    [Foo, a, ..] -> 5 # its first element is Foo, and its second we name `a`
    [Ok a, ..] -> 6 # it starts with an Ok containing a payload named `a`
    [.., Foo] -> 7 # it ends with a Foo tag
    [A, B, .., C, D] -> 8 # it has certain elements at the beginning and end
    [head, .. as tail] -> 9 # destructure a list into a first element (head) and the rest (tail)

This can be both more concise and more efficient (at runtime) than calling List.get multiple times, since each call to get requires a separate conditional to handle the different Results they return.

Note: Each list pattern can only have one .., which is known as the "rest pattern" because it's where the rest of the list goes.

See the Pattern Matching example which shows different ways to do pattern matching in Roc using tags, strings, and numbers.

Booleans

In many programming languages, true and false are special language keywords that refer to the two boolean values. In Roc, booleans do not get special keywords; instead, they are exposed as the ordinary values Bool.true and Bool.false.

This design is partly to keep the number of special keywords in the language smaller, but mainly to suggest how booleans are intended to be used in Roc: for boolean logic (&&, ||, and so on) as opposed to for data modeling. Tags are the preferred choice for data modeling, and having tag values be more concise than boolean values helps make this preference clear.

As an example of why tags are encouraged for data modeling, in many languages it would be common to write a record like { name: "Richard", isAdmin: Bool.true }, but in Roc it would be preferable to write something like { name: "Richard", role: Admin }. At first, the role field might only ever be set to Admin or Normal, but because the data has been modeled using tags instead of booleans, it's much easier to add other alternatives in the future, like Guest or Moderator - some of which might also want payloads.

Lists

Another thing we can do in Roc is to make a list of values. Here's an example:

names = ["Sam", "Lee", "Ari"]

This is a list with three elements in it, all strings. We can add a fourth element using List.append like so:

List.append names "Jess"

This returns a new list with "Jess" after "Ari", and doesn't modify the original list at all. All values in Roc (including lists, but also records, strings, numbers, and so on) are immutable, meaning whenever we want to "change" them, we want to instead pass them to a function which returns some variation of what was passed in.

List.map

A common way to transform one list into another is to use List.map. Here's an example of how to use it:

List.map [1, 2, 3] \num -> num * 2

This returns [2, 4, 6].

List.map takes two arguments:

1. An input list
2. A function that will be called on each element of that list

It then returns a list which it creates by calling the given function on each element in the input list. In this example, List.map calls the function \num -> num * 2 on each element in [1, 2, 3] to get a new list of [2, 4, 6].

We can also give List.map a named function, instead of an anonymous one:

List.map [1, 2, 3] Num.isOdd

This Num.isOdd function returns Bool.true if it's given an odd number, and Bool.false otherwise. So Num.isOdd 5 returns Bool.true and Num.isOdd 2 returns Bool.false.

As such, calling List.map [1, 2, 3] Num.isOdd returns a new list of [Bool.true, Bool.false, Bool.true].

List element type compatibility

If we tried to give List.map a function that didn't work on the elements in the list, then we'd get an error at compile time. Here's a valid, and then an invalid example:

# working example
List.map [-1, 2, 3, -4] Num.isNegative
# returns [Bool.true, Bool.false, Bool.false, Bool.true]

# invalid example
List.map ["A", "B", "C"] Num.isNegative
# error: isNegative doesn't work on strings!

Because Num.isNegative works on numbers and not strings, calling List.map with Num.isNegative and a list of numbers works, but doing the same with a list of strings doesn't work.

This wouldn't work either:

List.map ["A", "B", "C", 1, 2, 3] Num.isNegative

Every element in a Roc list has to share the same type. For example, we can have a list of strings like ["Sam", "Lee", "Ari"], or a list of numbers like [1, 2, 3, 4, 5] but we can't have a list which mixes strings and numbers like ["Sam", 1, "Lee", 2, 3], that would be a compile-time error.

Ensuring that all elements in a list share a type eliminates entire categories of problems. For example, it means that whenever you use List.append to add elements to a list, as long as you don't have any compile-time errors, you won't get any runtime errors from calling List.map afterwards, no matter what you appended to the list! More generally, it's safe to assume that unless you run out of memory, List.map will run successfully unless you got a compile-time error about an incompatibility (like Num.neg on a list of strings).

Lists that hold elements of different types

We can use tags with payloads to make a list that contains a mixture of different types. For example:

List.map [StrElem "A", StrElem "b", NumElem 1, StrElem "c", NumElem -3] \elem ->
    when elem is
        NumElem num -> Num.isNegative num
        StrElem str -> Str.isCapitalized str
# returns [Bool.true, Bool.false, Bool.false, Bool.false, Bool.true]

Compare this with the example from earlier, which caused a compile-time error:

List.map ["A", "B", "C", 1, 2, 3] Num.isNegative

The version that uses tags works because we aren't trying to call Num.isNegative on each element. Instead, we're using a when to tell when we've got a string or a number, and then calling either Num.isNegative or Str.isCapitalized depending on which type we have.

We could take this as far as we like, adding more different tags (e.g. BoolElem Bool.true) and then adding more branches to the when to handle them appropriately.

Using tags as functions

Let's say I want to apply a tag to a bunch of elements in a list. For example:

List.map ["a", "b", "c"] \str -> Foo str

This is a perfectly reasonable way to write it, but I can also write it like this:

List.map ["a", "b", "c"] Foo

These two versions compile to the same thing. As a convenience, Roc lets you specify a tag name where a function is expected; when you do this, the compiler infers that you want a function which uses all of its arguments as the payload to the given tag.

List.any and List.all

There are several functions that work like List.map, they walk through each element of a list and do something with it. Another is List.any, which returns Bool.true if calling the given function on any element in the list returns Bool.true:

List.any [1, 2, 3] Num.isOdd
# returns `Bool.true` because 1 and 3 are odd

List.any [1, 2, 3] Num.isNegative
# returns `Bool.false` because none of these is negative

There's also List.all which only returns Bool.true if all the elements in the list pass the test:

List.all [1, 2, 3] Num.isOdd
# returns `Bool.false` because 2 is not odd

List.all [1, 2, 3] Num.isPositive
# returns `Bool.true` because all of these are positive

Removing elements from a list

You can also drop elements from a list. One way is List.dropAt - for example:

List.dropAt ["Sam", "Lee", "Ari"] 1
# drops the element at offset 1 ("Lee") and returns ["Sam", "Ari"]

Another way is to use List.keepIf, which passes each of the list's elements to the given function, and then keeps them only if that function returns Bool.true.

List.keepIf [1, 2, 3, 4, 5] Num.isEven
# returns [2, 4]

There's also List.dropIf, which does the opposite:

List.dropIf [1, 2, 3, 4, 5] Num.isEven
# returns [1, 3, 5]

Getting an individual element from a list

Another thing we can do with a list is to get an individual element out of it. List.get is a common way to do this; it takes a list and an index, and then returns the element at that index... if there is one. But what if there isn't?

For example, what do each of these return?

List.get ["a", "b", "c"] 1

List.get ["a", "b", "c"] 100

The answer is that the first one returns Ok "b" and the second one returns Err OutOfBounds. They both return tags! This is done so that the caller becomes responsible for handling the possibility that the index is outside the bounds of that particular list.

Here's how calling List.get can look in practice:

when List.get ["a", "b", "c"] index is
    Ok str -> "I got this string: $(str)"
    Err OutOfBounds -> "That index was out of bounds, sorry!"

There's also List.first, which always gets the first element, and List.last which always gets the last. They return Err ListWasEmpty instead of Err OutOfBounds, because the only way they can fail is if you pass them an empty list!

These functions demonstrate a common pattern in Roc: operations that can fail returning either an Ok tag with the answer (if successful), or an Err tag with another tag describing what went wrong (if unsuccessful). In fact, it's such a common pattern that there's a whole module called Result which deals with these two tags. Here are some examples of Result functions:

Result.withDefault (List.get ["a", "b", "c"] 100) ""
# returns "" because that's the default we said to use if List.get returned an Err

Result.isOk (List.get ["a", "b", "c"] 1)
# returns `Bool.true` because `List.get` returned an `Ok` tag. (The payload gets ignored.)

# Note: There's a Result.isErr function that works similarly.

Walking the elements in a list

We've now seen a few different ways you can transform lists. Sometimes, though, there's nothing that quite does what you want, and you might find yourself calling List.get repeatedly to retrieve every element in the list and use it to build up the new value you want. That approach can work, but it has a few downsides:

• Each List.get call returns a Result that must be dealt with, even though you plan to use every element in the list anyway
• There's a runtime performance overhead associated with each of these Results, which you won't find in other "look at every element in the list" operations like List.keepIf.
• It's more verbose than the alternative we're about to discuss

The List.walk function gives you a way to walk over the elements in a list and build up whatever return value you like. It's a great alternative to calling List.get on every element in the list because it's more concise, runs faster, and doesn't give you any Results to deal with.

Here's an example:

List.walk [1, 2, 3, 4, 5] { evens: [], odds: [] } \state, elem ->
    if Num.isEven elem then
        { state & evens: List.append state.evens elem }
    else
        { state & odds: List.append state.odds elem }

# returns { evens: [2, 4], odds: [1, 3, 5] }

In this example, we walk over the list [1, 2, 3, 4, 5] and add each element to either the evens or odds field of a state record: { evens, odds }. By the end, that record has a list of all the even numbers in the list and a list of all the odd numbers.

List.walk takes a few ingredients:

1. A list. ([1, 2, 3, 4, 5])
2. An initial state value. ({ evens: [], odds: [] })
3. A function which takes the current state and element, and returns a new state. (\state, elem -> ...)

It then proceeds to walk over each element in the list and call that function. Each time, the state that function returns becomes the argument to the next function call. Here are the arguments the function will receive, and what it will return, as List.walk walks over the list [1, 2, 3, 4, 5]:

Note that the initial state argument is { evens: [], odds: [] } because that's the argument we passed List.walk for its initial state. From then on, each state argument is whatever the previous function call returned.

Once the list has run out of elements, List.walk returns whatever the final function call returned—in this case, { evens: [2, 4], odds: [1, 3, 5] }. (If the list was empty, the function never gets called and List.walk returns the initial state.)

Note that the state doesn't have to be a record; it can be anything you want. For example, if you made it a Bool, you could implement List.any using List.walk. You could also make the state be a list, and implement List.map, List.keepIf, or List.dropIf. There are a lot of things you can do with List.walk!

A helpful way to remember the argument order for List.walk is that that its arguments follow the same pattern as what we've seen with List.map, List.any, List.keepIf, and List.dropIf: the first argument is a list, and the last argument is a function. The difference here is that List.walk has one more argument than those other functions; the only place it could go while preserving that pattern is in the middle!

Note: Other languages give this operation different names, such as fold, reduce, accumulate, aggregate, compress, and inject. Some languages also have operations like forEach or for...in syntax, which walk across every element and perform potentially side-effecting operations on them; List.walk can be used to replace these too, if you include a Task in the state. We'll talk about tasks, and how to use them with List.walk, later on.

The pipe operator

When you have nested function calls, sometimes it can be clearer to write them in a "pipelined" style using the |> operator. Here are three examples of writing the same expression; they all compile to exactly the same thing, but two of them use the |> operator to change how the calls look.

Result.withDefault (List.get ["a", "b", "c"] 1) ""

List.get ["a", "b", "c"] 1
|> Result.withDefault ""

The |> operator takes the value that comes before the |> and passes it as the first argument to whatever comes after the |>. So in the example above, the |> takes List.get ["a", "b", "c"] 1 and passes that value as the first argument to Result.withDefault, making "" the second argument to Result.withDefault.

We can take this a step further like so:

["a", "b", "c"]
|> List.get 1
|> Result.withDefault ""

This is still equivalent to the first expression. Since |> is known as the "pipe operator," we can read this as "start with ["a", "b", "c"], then pipe it to List.get, then pipe it to Result.withDefault."

One reason the |> operator injects the value as the first argument is to make it work better with functions where argument order matters. For example, these two uses of List.append are equivalent:

List.append ["a", "b", "c"] "d"

["a", "b", "c"]
|> List.append "d"

Another example is Num.div. All three of the following do the same thing, because a / b in Roc is syntax sugar for Num.div a b:

first / second

Num.div first second

first |> Num.div second

All operators in Roc are syntax sugar for normal function calls. See the Operator Desugaring Table at the end of this tutorial for a complete list of them.

Types

Sometimes you may want to document the type of a definition. For example, you might write:

# Takes a firstName string and a lastName string, and returns a string
fullName = \firstName, lastName ->
    "$(firstName) $(lastName)"

Comments can be valuable documentation, but they can also get out of date and become misleading. If someone changes this function and forgets to update the comment, it will no longer be accurate.

Type Annotations

Here's another way to document this function's type, which doesn't have that problem:

fullName : Str, Str -> Str
fullName = \firstName, lastName ->
    "$(firstName) $(lastName)"

The fullName : line is a type annotation. It's a strictly optional piece of metadata we can add above a def to describe its type. Unlike a comment, the Roc compiler will check type annotations for accuracy. If the annotation ever doesn't fit with the implementation, we'll get a compile-time error.

The annotation fullName : Str, Str -> Str says "fullName is a function that takes two strings as arguments and returns a string."

We can give type annotations to any value, not just functions. For example:

firstName : Str
firstName = "Amy"

lastName : Str
lastName = "Lee"

These annotations say that both firstName and lastName have the type Str.

We can annotate records similarly. For example, we could move firstName and lastName into a record like so:

amy : { firstName : Str, lastName : Str }
amy = { firstName: "Amy", lastName: "Lee" }

jen : { firstName : Str, lastName : Str }
jen = { firstName: "Jen", lastName: "Majura" }

Type Aliases

When we have a recurring type annotation like this, it can be nice to give it its own name. We do this like so:

Musician : { firstName : Str, lastName : Str }

amy : Musician
amy = { firstName: "Amy", lastName: "Lee" }

simone : Musician
simone = { firstName: "Simone", lastName: "Simons" }

Here, Musician is a type alias. A type alias is like a def, except it gives a name to a type instead of to a value. Just like how you can read name : Str as "name has the type Str," you can also read Musician : { firstName : Str, lastName : Str } as "Musician has the type { firstName : Str, lastName : Str }."

Type Parameters

Annotations for lists must specify what type the list's elements have:

names : List Str
names = ["Amy", "Simone", "Tarja"]

You can read List Str as "a list of strings." Here, Str is a type parameter that tells us what type of List we're dealing with. List is a parameterized type, which means it's a type that requires a type parameter. There's no way to give something a type of List without a type parameter. You have to specify what type of list it is, such as List Str or List Bool or List { firstName : Str, lastName : Str }.

Wildcard Types (*)

There are some functions that work on any list, regardless of its type parameter. For example, List.isEmpty has this type:

isEmpty : List * -> Bool

The * is a wildcard type; a type that's compatible with any other type. List * is compatible with any type of List like List Str, List Bool, and so on. So you can call List.isEmpty ["I am a List Str"] as well as List.isEmpty [Bool.true], and they will both work fine.

The wildcard type also comes up with empty lists. Suppose we have one function that takes a List Str and another function that takes a List Bool. We might reasonably expect to be able to pass an empty list (that is, []) to either of these functions, and we can! This is because a [] value has the type List *. It is a "list with a wildcard type parameter", or a "list whose element type could be anything."

Type Variables

List.reverse works similarly to List.isEmpty, but with an important distinction. As with isEmpty, we can call List.reverse on any list, regardless of its type parameter. However, consider these calls:

strings : List Str
strings = List.reverse ["a", "b"]

bools : List Bool
bools = List.reverse [Bool.true, Bool.false]

In the strings example, we have List.reverse returning a List Str. In the bools example, it's returning a List Bool. So what's the type of List.reverse?

We saw that List.isEmpty has the type List * -> Bool, so we might think the type of List.reverse would be reverse : List * -> List *. However, remember that we also saw that the type of the empty list is List *? List * -> List * is actually the type of a function that always returns empty lists! That's not what we want.

What we want is something like one of these:

reverse : List elem -> List elem

reverse : List value -> List value

reverse : List a -> List a

Any of these will work, because elem, value, and a are all type variables. A type variable connects two or more types in the same annotation. So you can read List elem -> List elem as "takes a list and returns a list that has the same element type." Just like List.reverse does!

You can choose any name you like for a type variable, but it has to be lowercase. (You may have noticed all the types we've used until now are uppercase; that is no accident! Lowercase types are always type variables, so all other named types have to be uppercase.) All three of the above type annotations are equivalent; the only difference is that we chose different names (elem, value, and a) for their type variables.

You can tell some interesting things about functions based on the type parameters involved. For example, any function that returns List * definitely always returns an empty list. You don't need to look at the rest of the type annotation, or even the function's implementation! The only way to have a function that returns List * is if it returns an empty list.

Similarly, the only way to have a function whose type is a -> a is if the function's implementation returns its argument without modifying it in any way. This is known as the identity function.

Tag Union Types

We can also annotate types that include tags:

colorFromStr : Str -> [Red, Green, Yellow]
colorFromStr = \string ->
    when string is
        "red" -> Red
        "green" -> Green
        _ -> Yellow

You can read the type [Red, Green, Yellow] as "a tag union of the tags Red, Green, and Yellow."

Some tag unions have only one tag in them. For example:

redTag : [Red]
redTag = Red

Accumulating Tag Types

Tag union types can accumulate more tags based on how they're used. Consider this if expression:

\str ->
    if Str.isEmpty str then
        Ok "it was empty"
    else
        Err ["it was not empty"]

Here, Roc sees that the first branch has the type [Ok Str] and that the else branch has the type [Err (List Str)], so it concludes that the whole if expression evaluates to the combination of those two tag unions: [Ok Str, Err (List Str)].

This means this entire \str -> ... function has the type Str -> [Ok Str, Err (List Str)]. However, it would be most common to annotate it as Result Str (List Str) instead, because the Result type (for operations like Result.withDefault, which we saw earlier) is a type alias for a tag union with Ok and Err tags that each have one payload:

Result ok err : [Ok ok, Err err]

We just saw how tag unions get combined when different branches of a conditional return different tags. Another way tag unions can get combined is through pattern matching. For example:

when color is
    Red -> "red"
    Yellow -> "yellow"
    Green -> "green"

Here, Roc's compiler will infer that color's type is [Red, Yellow, Green], because those are the three possibilities this when handles.

Opaque Types

A type can be defined to be opaque to hide its internal structure. This is a lot more amazing than it may seem. It can make your code more modular, robust, and easier to read:

• If a type is opaque you can modify its internal structure and be certain that no dependencies need to be updated.
• You can prevent that data needs to be checked multiple times. For example, you can create an opaque NonEmptyList from a List after you've checked it. Now all functions that you pass this NonEmptyList to do not need to handle the empty list case.
• Having the type Username in a type signature gives you more context compared to Str. Even if the Username is an opaque type for Str.

You can create an opaque type with the := operator. Let's make one called Username:

Username := Str

fromStr : Str -> Username
fromStr = \str ->
    @Username str

toStr : Username -> Str
toStr = \@Username str ->
    str

The fromStr function turns a string into a Username by calling @Username on that string. The toStr function turns a Username back into a string by pattern matching @Username str to unwrap the string from the Username opaque type.

Now we can expose the Username opaque type so that other modules can use it in type annotations. However, other modules can't use the @Username syntax to wrap or unwrap Username values. That operation is only available in the same scope where Username itself was defined; trying to use it outside that scope will give an error.

Note that if we define Username := Str inside another module (e.g. Main) and also use @Username, this will compile, however the new Username type in main would not be equal to the one defined in the Username module. Although both opaque types have the name Username, they were defined in different modules and so they are type-incompatible with each other, and even attempting to use == to compare them would be a type mismatch.

Numeric types

Roc has different numeric types that each have different tradeoffs. They can all be broken down into two categories: fractions, and integers. In Roc we call these Frac and Int for short.

Integers

Roc's integer types have two important characteristics: their size and their signedness. Together, these two characteristics determine the range of numbers the integer type can represent.

For example, the Roc type U8 can represent the numbers 0 through 255, whereas the I16 type can represent the numbers -32768 through 32767. You can actually infer these ranges from their names (U8 and I16) alone!

The U in U8 indicates that it's unsigned, meaning that it can't have a minus sign, and therefore can't be negative. The fact that it's unsigned tells us immediately that its lowest value is zero. The 8 in U8 means it is 8 bits in size, which means it has room to represent 2⁸ (=256) different numbers. Since one of those 256 different numbers is 0, we can look at U8 and know that it goes from 0 (since it's unsigned) to 255 (2⁸ - 1, since it's 8 bits).

If we change U8 to I8, making it a signed 8-bit integer, the range changes. Because it's still 8 bits, it still has room to represent 2⁸ different numbers. However, now in addition to one of those 256 numbers being zero, about half of the rest will be negative, and the others positive. So instead of ranging from, say -255 to 255 (which, counting zero, would represent 511 different numbers; too many to fit in 8 bits!) an I8 value ranges from -128 to 127.

Notice that the negative extreme is -128 versus 127 (not 128) on the positive side. That's because of needing room for zero; the slot for zero is taken from the positive range because zero doesn't have a minus sign.

Following this pattern, the 16 in I16 means that it's a signed 16-bit integer. That tells us it has room to represent 2¹⁶ (=65536) different numbers. Half of 65536 is 32768, so the lowest I16 would be -32768, and the highest would be 32767.

Choosing a size depends on your performance needs and the range of numbers you want to represent. Consider:

• Larger integer sizes can represent a wider range of numbers. If you absolutely need to represent numbers in a certain range, make sure to pick an integer size that can hold them!
• Smaller integer sizes take up less memory. These savings rarely matters in variables and function arguments, but the sizes of integers that you use in data structures can add up. This can also affect whether those data structures fit in cache lines, which can easily be a performance bottleneck.
• Certain processors work faster on some numeric sizes than others. There isn't even a general rule like "larger numeric sizes run slower" (or the reverse, for that matter) that applies to all processors. In fact, if the CPU is taking too long to run numeric calculations, you may find a performance improvement by experimenting with numeric sizes that are larger than otherwise necessary. However, in practice, doing this typically degrades overall performance, so be careful to measure properly!

Here are the different fixed-size integer types that Roc supports:

If any operation would result in an integer that is either too big or too small to fit in that range (e.g. calling Int.maxI32 + 1, which adds 1 to the highest possible 32-bit integer), then the operation will overflow. When an overflow occurs, the program will crash.

As such, it's very important to design your integer operations not to exceed these bounds!

Fractions

Roc has three fractional types:

• F32, a 32-bit floating-point number
• F64, a 64-bit floating-point number
• Dec, a 128-bit decimal fixed-point number

These are different from integers, they can represent numbers with fractional components, such as 1.5 and -0.123.

Dec is the best default choice for representing base-10 decimal numbers like currency, because it is base-10 under the hood. In contrast, F64 and F32 are base-2 under the hood, which can lead to decimal precision loss even when doing addition and subtraction. For example, when using F64, running 0.1 + 0.2 returns 0.3000000000000000444089209850062616169452667236328125, whereas when using Dec, 0.1 + 0.2 returns 0.3.

F32 and F64 have direct hardware support on common processors today. There is no hardware support for fixed-point decimals, so under the hood, a Dec is an I128; operations on it perform base-10 fixed-point arithmetic with 18 decimal places of precision.

This means a Dec can represent whole numbers up to slightly over 170 quintillion, along with 18 decimal places. (To be precise, it can store numbers between -170_141_183_460_469_231_731.687303715884105728 and 170_141_183_460_469_231_731.687303715884105727.) Why 18 decimal places? It's the highest number of decimal places where you can still convert any U64 to a Dec without losing information.

While the fixed-point Dec has a fixed range, the floating-point F32 and F64 do not. Instead, outside of a certain range they start to lose precision instead of immediately overflowing the way integers and Dec do. F64 can represent between 15 and 17 significant digits before losing precision, whereas F32 can only represent between 6 and 9.

There are some use cases where F64 and F32 can be better choices than Dec despite their precision drawbacks. For example, in graphical applications they can be a better choice for representing coordinates because they take up less memory, various relevant calculations run faster, and decimal precision loss isn't as big a concern when dealing with screen coordinates as it is when dealing with something like currency.

Num, Int, and Frac

Some operations work on specific numeric types - such as I64 or Dec - but some operations support multiple numeric types. For example, the Num.abs function works on any number, since you can take the absolute value of integers and fractions alike. Its type is:

abs : Num a -> Num a

This type says abs takes a number and then returns a number of the same type. Remember that we can see the type of number is the same because the type variable a is used on both sides. That's because the Num type is compatible with both integers and fractions.

There's also an Int type which is only compatible with integers, and a Frac type which is only compatible with fractions. For example:

Num.bitwiseXor : Int a, Int a -> Int a

Num.cos : Frac a -> Frac a

When you write a number literal in Roc, it has the type Num *. So you could call Num.bitwiseXor 1 1 and also Num.cos 1 and have them all work as expected; the number literal 1 has the type Num *, which is compatible with the more constrained types Int and Frac. For the same reason, you can pass number literals to functions expecting even more constrained types, like I32 or F64.

Number Literals

By default, a number literal with no decimal point has the type Num *—that is, we know it's "a number" but nothing more specific. (Number literals with decimal points have the type Frac * instead.)

You can give a number literal a more specific type by adding the type you want as a lowercase suffix. For example, 1u8 specifies 1 with the type U8, and 5dec specifies 5 with the type Dec.

The full list of possible suffixes includes:

u8, i8, u16, i16, u32, i32, u64, i64, u128, i128, f32, f64, dec

Integer literals can be written in hexadecimal form by prefixing with 0x followed by hexadecimal characters (a - f in addition to 0 - 9). For example, writing 0xfe is the same as writing 254. Similarly, the prefix 0b specifies binary integers. Writing 0b0000_1000 is the same as writing 8.

Crashing

Ideally, Roc programs would never crash. However, there are some situations where they may. For example:

1. When doing normal integer arithmetic (e.g. x + y) that overflows.
2. When the system runs out of memory.
3. When a variable-length collection (like a List or Str) gets too long to be representable in the operating system's address space. (A 64-bit operating system's address space can represent several exabytes of data, so this case should not come up often.)

Crashes in Roc are not like try/catch exceptions found in some other programming languages. There is no way to "catch" a crash. It immediately ends the program, and what happens next is defined by the platform. For example, a command-line interface platform might exit with a nonzero exit code, whereas a web server platform might have the current request respond with a HTTP 500 error.

Crashing in unreachable branches

You can intentionally crash a Roc program, for example inside a conditional branch that you believe is unreachable. Suppose you're certain that a particular List U8 contains valid UTF-8 bytes, which means when you call Str.fromUtf8 on it, the Result it returns will always be Ok. In that scenario, you can use the crash keyword to handle the Err case like so:

answer : Str
answer =
    when Str.fromUtf8 definitelyValidUtf8 is
        Ok str -> str
        Err _ -> crash "This should never happen!"

If the unthinkable happens, and somehow the program reaches this Err branch even though that was thought to be impossible, then it will crash - just like if the system had run out of memory. The string passed to crash will be provided to the platform as context; each platform may do something different with it.

Note: crash is a language keyword and not a function; you can't assign crash to a variable or pass it to a function.

Crashing for TODOs

Another use for crash is as a TODO marker when you're in the middle of building something:

if x > y then
    transmogrify (x * 2)
else
    crash "TODO handle the x <= y case"

This lets you do things like write tests for the non-crash branch, and then come back and finish the other branch later.

Crashing for error handling

crash is not for error handling.

The reason Roc has a crash keyword is for scenarios where it's expected that no error will ever happen (like in unreachable branches), or where graceful error handling is infeasible (like running out of memory).

Errors that are recoverable should be represented using normal Roc types (like Result) and then handled without crashing. For example, by having the application report that something went wrong, and then continue running from there.

Tests and expectations

You can write automated tests for your Roc code like so:

pluralize = \singular, plural, count ->
    countStr = Num.toStr count

    if count == 1 then
        "$(countStr) $(singular)"
    else
        "$(countStr) $(plural)"

expect pluralize "cactus" "cacti" 1 == "1 cactus"

expect pluralize "cactus" "cacti" 2 == "2 cacti"

If you put this in a file named main.roc and run roc test, Roc will execute the two expect expressions (that is, the two pluralize calls) and report any that returned Bool.false.

If a test fails, it will not show the actual value that differs from the expected value. This will be resolved in the future. For now, to show the actual value you can write the expect like this:

expect
    funcOut = pluralize "cactus" "cacti" 1

    funcOut == "2 cactus"

Inline Expectations

Expects do not have to be at the top level:

pluralize = \singular, plural, count ->
    countStr = Num.toStr count

    if count == 1 then
        "$(countStr) $(singular)"
    else
        expect count > 0

        "$(countStr) $(plural)"

This expect will fail if you call pluralize passing a count of 0.

Note that inline expects do not halt the program! They are designed to inform, not to affect control flow. Different roc commands will also handle expects differently:

• roc build discards all expects for optimal runtime performance.
• roc dev only runs inline expects that are encountered during normal execution of the program.
• roc test runs top level expects and inline expects that are encountered because of the running of top level expects.

Let's clear up any confusion with an example:

main =
    expect 1 == 2

    Stdout.line "Hello, World!"

double = \num ->
    expect num > -1

    num * 2

expect double 0 == 0

• roc build wil run main, ignore expect 1 == 2 and just print Hello, World!.
• roc dev will run main, tell you expect 1 == 2 failed but will still print Hello, World!.
• roc test will run expect double 0 == 0 followed by expect num > -1 and will print how many top level expects passed: 0 failed and 1 passed in 100 ms..

Modules

Each .roc file is a separate module and contains Roc code for different purposes. Here are all of the different types of modules that Roc supports;

• Builtins provide functions that are automatically imported into every module.
• Applications are combined with a platform and compiled into an executable.
• Interfaces provide functions which can be imported into other modules.
• Packages organise modules to share functionality across applications and platforms.
• Platforms provide effects such as IO to interface with the outside world.
• Hosted note this module type is likely to be deprecated soon.

Builtin Modules

There are several modules that are built into the Roc compiler, which are imported automatically into every Roc module. They are:

1. Bool
2. Str
3. Num
4. List
5. Result
6. Dict
7. Set

You may have noticed that we already used the first five. For example, when we wrote Str.concat and Num.isEven, we were referencing functions stored in the Str and Num modules.

These modules are not ordinary .roc files that live on your filesystem. Rather, they are built directly into the Roc compiler. That's why they're called "builtins!"

Besides being built into the compiler, the builtin modules are different from other modules in that:

• They are always imported. You never need to add them to imports.
• All their types are imported unqualified automatically. So you never need to write Num.Dec, because it's as if the Num module was imported using imports [Num.{ Dec }] (the same is true for all the other types in the Num module.)

App Module Header

Let's take a closer look at the part of main.roc above the main def:

app "hello"
    packages { pf: "https://github.com/roc-lang/basic-cli/releases/download/0.9.0/oKWkaruh2zXxin_xfsYsCJobH1tO8_JvNkFzDwwzNUQ.tar.br" }
    imports [pf.Stdout]
    provides [main] to pf

This is known as a module header. Every .roc file is a module, and there are different types of modules. We know this particular one is an application module because it begins with the app keyword.

The line app "hello" shows that this module is a Roc application. The "hello" after the app keyword will be removed soon and is no longer used. If the file is named hello.roc, building this application should produce an executable named hello. This means when you run roc dev, the Roc compiler will build an executable named hello (or hello.exe on Windows) and run it. You can also build the executable without running it by running roc build.

The remaining lines all involve the platform this application is built on:

packages { pf: "https://github.com/roc-lang/basic-cli/releases/download/0.9.0/oKWkaruh2zXxin_xfsYsCJobH1tO8_JvNkFzDwwzNUQ.tar.br" }
imports [pf.Stdout]
provides [main] to pf

The packages { pf: "https://...tar.br" } part says three things:

• We're going to be using a package (a collection of modules) that can be downloaded from the URL "https://...tar.br"
• That package's base64-encoded BLAKE3 cryptographic hash is the long string at the end (before the .tar.br file extension). Once the file has been downloaded, its contents will be verified against this hash, and it will only be installed if they match. This way, you can be confident the download was neither corrupted nor changed since it was originally published.
• We're going to name that package pf so we can refer to it more concisely in the future.

The imports [pf.Stdout] line says that we want to import the Stdout module from the pf package, and make it available in the current module.

This import has a direct interaction with our definition of main. Let's look at that again:

main = Stdout.line "I'm a Roc application!"

Here, main is calling a function called Stdout.line. More specifically, it's calling a function named line which is exposed by a module named Stdout.

When we write imports [pf.Stdout], it specifies that the Stdout module comes from the package we named pf in the packages { pf: ... } section.

If we would like to include other modules in our application, say AdditionalModule.roc and AnotherModule.roc, then they can be imported directly in imports like this:

imports [pf.Stdout, AdditionalModule, AnotherModule]

You can find documentation for the Stdout.line function in the Stdout module documentation.

Package Modules

Package modules enable Roc code to be easily re-used and shared. This is achieved by organizing code into different Interface modules and then including these in the exposes field of the package file structure, package "name" exposes [ MyInterface ] packages {}. The modules that are listed in the exposes field are then available for use in applications, platforms, or other packages. Internal modules that are not listed will be unavailable for use outside of the package.

See Parser Package for an example.

Package documentation can be generated using the Roc cli with roc docs /package/*.roc.

Build a package for distribution with roc build --bundle .tar.br /package/main.roc. This will create a single tarball that can then be easily shared online using a URL.

You can import a package that is available either locally, or from a URL into a Roc application or platform. This is achieved by specifying the package in the packages section of the application or platform file structure. For example, packages { .., parser: "" } is an example that imports a parser module from a URL.

How does the Roc cli import and download a package from a URL?

1. First it checks to see whether the relevant folder already exists in the local filesystem and if not, creates it. If there is a package already downloaded then there is no need to download or extract anything. Packages are cached in a directory, typically ~/.cache/roc on UNIX, and %APPDATA%\\Roc on Windows.
2. It then downloads the file at that URL and verifies that the hash of the file matches the hash at the end of the URL.
3. If the hash of the file matches the hash in the URL, then decompress and extract its contents into the cache folder so that it can be used.

Why is a Roc package URL so long?

Including the hash solves a number of problems:

1. The package at the URL can not suddenly change and cause different behavior.
2. Because of 1. there is no need to check the URL on every compilation to see if we have the latest version.
3. If the domain of the URL expires, a malicious actor can change the package but the hash will not match so the roc cli will reject it.

Interface Modules

[This part of the tutorial has not been written yet. Coming soon!]

See Html Interface for an example.

Platform Modules

[This part of the tutorial has not been written yet. Coming soon!]

See Platform Switching Rust for an example.

Importing Files

You can import files directly into your module as a Str or a List U8 at compile time. This is can be useful when working with data you would like to keep in a separate file, e.g. JSON or YAML configuration.

imports [
    "some-file" as someStr : Str,
    "some-file" as someBytes : List U8,
]

See the Ingest Files Example for a demonstration on using this feature.

Tasks

Tasks are technically not part of the Roc language, but they're very common in platforms. Let's continue using the basic-cli platform we've been using up to this point as an example!

In the basic-cli platform, we have four operations we can do:

• Write a string to the terminal
• Read a string from user input
• Write a string to a file
• Read a string from a file

We'll use these four operations to learn about tasks.

Let's start with a basic "Hello World" program.

app "cli-tutorial"
    packages { pf: "https://github.com/roc-lang/basic-cli/releases/download/0.9.0/oKWkaruh2zXxin_xfsYsCJobH1tO8_JvNkFzDwwzNUQ.tar.br" }
    imports [pf.Stdout]
    provides [main] to pf

main =
    Stdout.line "Hello, World!"

The Stdout.line function takes a Str and writes it to standard output. It has this type:

Stdout.line : Str -> Task {} *

A Task represents an effect; an interaction with state outside your Roc program, such as the terminal's standard output, or a file.

When we set main to be a Task, the task will get run when we run our program. Here, we've set main to be a task that writes "Hello, World!" to stdout when it gets run, so that's what our program does!

Task has two type parameters: the type of value it produces when it finishes running, and any errors that might happen when running it. Stdout.line has the type Task {} * because it doesn't produce any values when it finishes (hence the {}) and there aren't any errors that can happen when it runs (hence the *).

In contrast, when Stdin.line finishes reading a line from standard input, it produces either a Str or else End if standard input reached its end (which can happen if the user types Ctrl+D on UNIX systems or Ctrl+Z on Windows). Those two possibilities are reflected in its type:

Stdin.line : Task [Input Str, End] *

Once this task runs, we'll end up with the tag union [Input Str, End]. Then we can check whether we got an End or some actual Input, and print out a message accordingly.

Printing Roc values with Inspect.toStr

Let's change main to read a line from stdin, and then print what we got:

app "cli-tutorial"
    packages { pf: "https://github.com/roc-lang/basic-cli/releases/download/0.9.0/oKWkaruh2zXxin_xfsYsCJobH1tO8_JvNkFzDwwzNUQ.tar.br" }
    imports [pf.Stdout, pf.Stdin, pf.Task]
    provides [main] to pf

main =
    Task.await Stdin.line \input ->
        Stdout.line "Your input was: $(Inspect.toStr input)"

The Inspect.toStr function returns a Str representation of any Roc value. It's useful for things like debugging and logging (although dbg is often nicer for debugging), but its output is almost never something that should be shown to end users! In this case we're just using it for our own learning, but in a real program we'd run a when on input and do something different depending on whether we got an End or Input tag.

If you run this program, at first it won't do anything. It's waiting for you to type something in and press Enter! Once you do, it should print back out what you entered—either Your input was: End or Your input was: Input depending on whether you pressed Enter or the key combination to close stdin (namely Ctrl+D on UNIX or Ctrl+Z on Windows). Try doing it both ways to watch the output change!

Chaining tasks with Task.await

The Task.await function combines two tasks into one bigger Task which first runs one of the given tasks and then the other. In this case, it's combining a Stdin.line task with a Stdout.line task into one bigger Task, and then setting main to be that bigger task.

The type of Task.await is:

Task.await : Task a err, (a -> Task b err) -> Task b err

The second argument to Task.await is a "callback function" which runs after the first task completes. This callback function receives the output of that first task, and then returns the second task. This means the second task can make use of output from the first task, like we did in our \input -> ... callback function here:

\input ->
    Stdout.line "Your input was: $(Inspect.toStr input)"

Notice that, just like before, we're still building main from a single Task. This is how we'll always do it! We'll keep building up bigger and bigger Tasks out of smaller tasks, and then setting main to be that one big Task.

For example, we can print a prompt before we pause to read from stdin, so it no longer looks like the program isn't doing anything when we start it up:

main =
    Task.await (Stdout.line "Type something press Enter:") \_ ->
        Task.await Stdin.line \input ->
            Stdout.line "Your input was: $(Inspect.toStr input)"

This works, but we can make it a little nicer to read. Let's change it to the following:

app "cli-tutorial"
    packages { pf: "https://github.com/roc-lang/basic-cli/releases/download/0.9.0/oKWkaruh2zXxin_xfsYsCJobH1tO8_JvNkFzDwwzNUQ.tar.br" }
    imports [pf.Stdout, pf.Stdin, pf.Task.{ await }]
    provides [main] to pf

main =
    await (Stdout.line "Type something press Enter:") \_ ->
        await Stdin.line \input ->
            Stdout.line "Your input was: $(Inspect.toStr input)"

Here we've changed how we're importing the Task module. Before it was pf.Task and now it's pf.Task.{ await }. The difference is that we're importing await in an unqualified way, meaning that whenever we write await in this module, it will refer to Task.await. Now we no longer need to write Task. every time we want to use await.

It's most common in Roc to call functions from other modules in a qualified way (Task.await) rather than unqualified (await) like this, but it can be nice for a function with an uncommon name (like "await") which often gets called repeatedly across a small number of lines of code.

Speaking of calling await repeatedly, if we keep calling it more and more on this code, we'll end up doing a lot of indenting. If we'd rather not indent so much, we can rewrite task into this style which looks different but does the same thing:

main =
    _ <- await (Stdout.line "Type something press Enter:")
    input <- await Stdin.line

    Stdout.line "Your input was: $(Inspect.toStr input)"

Backpassing

This <- syntax is called backpassing. The <- is a way to define an anonymous function, just like \ ... -> is.

Here, we're using backpassing to define two anonymous functions. Here's one of them:

input <-

Stdout.line "Your input was: $(Inspect.toStr input)"

It may not look like it, but this code is defining an anonymous function! You might remember it as the anonymous function we previously defined like this:

\input ->
    Stdout.line "Your input was: $(Inspect.toStr input)"

These two anonymous functions are the same, just defined using different syntax.

The reason the <- syntax is called backpassing is because it both defines a function and passes that function back as an argument to whatever comes after the <- (which in this case is await Stdin.line).

Let's look at these two complete expressions side by side. They are both saying exactly the same thing, with different syntax!

Here's the original:

await Stdin.line \input ->
    Stdout.line "Your input was: $(Inspect.toStr input)"

And here's the equivalent expression with backpassing syntax:

input <- await Stdin.line

Stdout.line "Your input was: $(Inspect.toStr input)"

Here's the other function we're defining with backpassing:

_ <-
input <- await Stdin.line

Stdout.line "Your input was: $(Inspect.toStr input)"

We could also have written that function this way if we preferred:

_ <-

await Stdin.line \input ->
    Stdout.line "Your input was: $(Inspect.toStr input)"

This is using a mix of a backpassing function _ <- and a normal function \input ->, which is totally allowed! Since backpassing is nothing more than syntax sugar for defining a function and passing back as an argument to another function, there's no reason we can't mix and match if we like.

That said, the typical style in which this task would be written in Roc is using backpassing for all the await calls, like we had above:

main =
    _ <- await (Stdout.line "Type something press Enter:")
    input <- await Stdin.line

    Stdout.line "Your input was: $(Inspect.toStr input)"

This way, it reads like a series of instructions:

1. First, run the Stdout.line task and await its completion. Ignore its output (hence the underscore in _ <-)
2. Next, run the Stdin.line task and await its completion. Name its output input.
3. Finally, run the Stdout.line task again, using the input value we got from the Stdin.line effect.

Some important things to note about backpassing and await:

• await is not a language keyword in Roc! It's referring to the Task.await function, which we imported unqualified by writing Task.{ await } in our module imports. (That said, it is playing a similar role here to the await keyword in languages that have async/await keywords, even though in this case it's a function instead of a special keyword.)
• Backpassing syntax does not need to be used with await in particular. It can be used with any function.
• Roc's compiler treats functions defined with backpassing exactly the same way as functions defined the other way. The only difference between \input -> and input <- is how they look, so feel free to use whichever looks nicer to you!

See the Task & Error Handling example for a more detailed explanation of how to use tasks to help with error handling in a larger program.

Examples

Well done on making it this far!

We've covered all of the basic syntax and features of Roc in this Tutorial. You should now have a good foundation and be ready to start writing your own applications.

You can continue reading through more advanced topics below, or perhaps checkout some of the Examples for more a detailed exploration of ways to do various things.

Appendix: Advanced Concepts

Here are some concepts you likely won't need as a beginner, but may want to know about eventually. This is listed as an appendix rather than the main tutorial, to emphasize that it's totally fine to stop reading here and go build things!

Open Records and Closed Records

Let's say I write a function which takes a record with a firstName and lastName field, and puts them together with a space in between:

fullName = \user ->
    "$(user.firstName) $(user.lastName)"

I can pass this function a record that has more fields than just firstName and lastName, as long as it has at least both of those fields (and both of them are strings). So any of these calls would work:

• fullName { firstName: "Sam", lastName: "Sample" }
• fullName { firstName: "Sam", lastName: "Sample", email: "blah@example.com" }
• fullName { age: 5, firstName: "Sam", things: 3, lastName: "Sample", role: Admin }

This user argument is an open record - that is, a description of a minimum set of fields on a record, and their types. When a function takes an open record as an argument, it's okay if you pass it a record with more fields than just the ones specified.

In contrast, a closed record is one that requires an exact set of fields (and their types), with no additional fields accepted.

If we add a type annotation to this fullName function, we can choose to have it accept either an open record or a closed record:

# Closed record
fullName : { firstName : Str, lastName : Str } -> Str
fullName = \user ->
    "$(user.firstName) $(user.lastName)"

# Open record (because of the `*`)
fullName : { firstName : Str, lastName : Str }* -> Str
fullName = \user ->
    "$(user.firstName) $(user.lastName)"

The * in the type { firstName : Str, lastName : Str }* is what makes it an open record type. This * is the wildcard type we saw earlier with empty lists. (An empty list has the type List *, in contrast to something like List Str which is a list of strings.)

This is because record types can optionally end in a type variable. Just like how we can have List * or List a -> List a, we can also have { first : Str, last : Str }* or { first : Str, last : Str }a -> { first : Str, last : Str }a. The differences are that in List a, the type variable is required and appears with a space after List; in a record, the type variable is optional, and appears (with no space) immediately after }.

If the type variable in a record type is a * (such as in { first : Str, last : Str }*), then it's an open record. If the type variable is missing, then it's a closed record. You can also specify a closed record by putting a {} as the type variable (so for example, { email : Str }{} is another way to write { email : Str }). In practice, closed records are basically always written without the {} on the end, but later on we'll see a situation where putting types other than * in that spot can be useful.

Constrained Records

The type variable can also be a named type variable, like so:

addHttps : { url : Str }a -> { url : Str }a
addHttps = \record ->
    { record & url: "https://$(record.url)" }

This function uses constrained records in its type. The annotation is saying:

• This function takes a record which has at least a url field, and possibly others
• That url field has the type Str
• It returns a record of exactly the same type as the one it was given

So if we give this function a record with five fields, it will return a record with those same five fields. The only requirement is that one of those fields must be url: Str.

In practice, constrained records appear in type annotations much less often than open or closed records do.

Here's when you can typically expect to encounter these three flavors of type variables in records:

• Open records are what the compiler infers when you use a record as an argument, or when destructuring it (for example, { x, y } =).
• Closed records are what the compiler infers when you create a new record (for example, { x: 5, y: 6 })
• Constrained records are what the compiler infers when you do a record update (for example, { user & email: newEmail })

Of note, you can pass a closed record to a function that accepts a smaller open record, but not the reverse. So a function { a : Str, b : Bool }* -> Str can accept an { a : Str, b : Bool, c : Bool } record, but a function { a : Str, b : Bool, c : Bool } -> Str would not accept an { a : Str, b : Bool }* record.

This is because if a function accepts { a : Str, b : Bool, c : Bool }, that means it might access the c field of that record. So if you passed it a record that was not guaranteed to have all three of those fields present (such as an { a : Str, b : Bool }* record, which only guarantees that the fields a and b are present), the function might try to access a c field at runtime that did not exist!

Type Variables in Record Annotations

You can add type annotations to make record types less flexible than what the compiler infers, but not more flexible. For example, you can use an annotation to tell the compiler to treat a record as closed when it would be inferred as open (or constrained), but you can't use an annotation to make a record open when it would be inferred as closed.

If you like, you can always annotate your functions as accepting open records. However, in practice this may not always be the nicest choice. For example, let's say you have a User type alias, like so:

User : {
    email : Str,
    firstName : Str,
    lastName : Str,
}

This defines User to be a closed record, which in practice is the most common way records named User tend to be defined.

If you want to have a function take a User, you might write its type like so:

isValid : User -> Bool

If you want to have a function return a User, you might write its type like so:

userFromEmail : Str -> User

A function which takes a user and returns a user might look like this:

capitalizeNames : User -> User

This is a perfectly reasonable way to write all of these functions. However, I might decide that I really want the isValid function to take an open record; a record with at least the fields of this User record, but possibly others as well.

Since open records have a type variable (like * in { email : Str }* or a in { email : Str }a -> { email : Str }a), in order to do this I'd need to add a type variable to the User type alias:

User a : {
    email : Str
    firstName : Str
    lastName : Str
}a

Notice that the a type variable appears not only in User a but also in }a at the end of the record type!

Using User a type alias, I can still write the same three functions, but now their types need to look different. This is what the first one would look like:

isValid : User * -> Bool

Here, the User * type alias substitutes * for the type variable a in the type alias, which takes it from { email : Str, ... }a to { email : Str, ... }*. Now I can pass it any record that has at least the fields in User, and possibly others as well, which was my goal.

userFromEmail : Str -> User {}

Here, the User {} type alias substitutes {} for the type variable a in the type alias, which takes it from { email : Str, ... }a to { email : Str, ... }{}. As noted earlier, this is another way to specify a closed record: putting a {} after it, in the same place that you'd find a * in an open record.

Aside: This works because you can form new record types by replacing the type variable with other record types. For example, { a : Str, b : Str } can also be written { a : Str }{ b : Str }. You can chain these more than once, e.g. { a : Str }{ b : Str }{ c : Str, d : Str }. This is more useful when used with type annotations; for example, { a : Str, b : Str }User describes a closed record consisting of all the fields in the closed record User, plus a : Str and b : Str.

This function still returns the same record as it always did, it just needs to be annotated as User {} now instead of just User, because the User type alias has a variable in it that must be specified.

The third function might need to use a named type variable:

capitalizeNames : User a -> User a

If this function does a record update on the given user, and returns that - for example, if its definition were capitalizeNames = \user -> { user & email: "blah" } - then it needs to use the same named type variable for both the argument and return value.

However, if returns a new User that it created from scratch, then its type could instead be:

capitalizeNames : User * -> User {}

This says that it takes a record with at least the fields specified in the User type alias, and possibly others...and then returns a record with exactly the fields specified in the User type alias, and no others.

These three examples illustrate why it's relatively uncommon to use open records for type aliases: it makes a lot of types need to incorporate a type variable that otherwise they could omit, all so that isValid can be given something that has not only the fields User has, but some others as well. (In the case of a User record in particular, it may be that the extra fields were included due to a mistake rather than on purpose, and accepting an open record could prevent the compiler from raising an error that would have revealed the mistake.)

That said, this is a useful technique to know about if you want to (for example) make a record type that accumulates more and more fields as it progresses through a series of operations.

Open and Closed Tag Unions

Just like how Roc has open records and closed records, it also has open and closed tag unions.

The open tag union (or open union for short) [Foo Str, Bar Bool]* represents a tag that might be Foo Str and might be Bar Bool, but might also be some other tag whose type isn't known at compile time.

Because an open union represents possibilities that are impossible to know ahead of time, any when I use on a [Foo Str, Bar Bool]* value must include a catch-all _ -> branch. Otherwise, if one of those unknown tags were to come up, the when would not know what to do with it! For example:

example : [Foo Str, Bar Bool]* -> Bool
example = \tag ->
    when tag is
        Foo str -> Str.isEmpty str
        Bar bool -> bool
        _ -> Bool.false

In contrast, a closed tag union (or closed union) like [Foo Str, Bar Bool] (without the *) represents the set of all possible tags. If I use a when on one of these, I can match on Foo only and then on Bar only, with no need for a catch-all branch. For example:

example : [Foo Str, Bar Bool] -> Bool
example = \tag ->
    when tag is
        Foo str -> Str.isEmpty str
        Bar bool -> bool

If we were to remove the type annotations from the previous two code examples, Roc would infer the same types for them anyway.

It would infer tag : [Foo Str, Bar Bool] for the latter example because the when tag is expression only includes a Foo Str branch and a Bar Bool branch, and nothing else. Since the when doesn't handle any other possibilities, these two tags must be the only possible ones.

It would infer tag : [Foo Str, Bar Bool]* for the former example because the when tag is expression includes a Foo Str branch and a Bar Bool branch but also a _ -> branch, indicating that there may be other tags we don't know about. Since the when is flexible enough to handle all possible tags, tag gets inferred as an open union.

Putting these together, whether a tag union is inferred to be open or closed depends on which possibilities the implementation actually handles.

Aside: As with open and closed records, we can use type annotations to make tag union types less flexible than what would be inferred. If we added a _ -> branch to the second example above, the compiler would still accept example : [Foo Str, Bar Bool] -> Bool as the type annotation, even though the catch-all branch would permit the more flexible example : [Foo Str, Bar Bool]* -> Bool annotation instead.

Combining Open Unions

When we make a new record, it's inferred to be a closed record. For example, in foo { a: "hi" }, the type of { a: "hi" } is inferred to be { a : Str }. In contrast, when we make a new tag, it's inferred to be an open union. So in foo (Bar "hi"), the type of Bar "hi" is inferred to be [Bar Str]*.

This is because open unions can accumulate additional tags based on how they're used in the program, whereas closed unions cannot. For example, let's look at this conditional:

if x > 5 then
    "foo"
else
    7

This will be a type mismatch because the two branches have incompatible types. Strings and numbers are not type-compatible! Now let's look at another example:

if x > 5 then
    Ok "foo"
else
    Err "bar"

This shouldn't be a type mismatch, because we can see that the two branches are compatible; they are both tags that could easily coexist in the same tag union. But if the compiler inferred the type of Ok "foo" to be the closed union [Ok Str], and likewise for Err "bar" and [Err Str], then this would have to be a type mismatch - because those two closed unions are incompatible.

Instead, the compiler infers Ok "foo" to be the open union [Ok Str]*, and Err "bar" to be the open union [Err Str]*. Then, when using them together in this conditional, the inferred type of the conditional becomes [Ok Str, Err Str]* - that is, the combination of the unions in each of its branches. (Branches in a when work the same way with open unions.)

Earlier we saw how a function which accepts an open union must account for more possibilities, by including catch-all _ -> patterns in its when expressions. So accepting an open union means you have more requirements. In contrast, when you already have a value which is an open union, you have fewer requirements. A value which is an open union (like Ok "foo", which has the type [Ok Str]*) can be provided to anything that's expecting a tag union (no matter whether it's open or closed), as long as the expected tag union includes at least the tags in the open union you're providing.

So if I have an [Ok Str]* value, I can pass it to functions with any of these types (among others):

That last one works because a function accepting an open union can accept any unrecognized tag (including Ok Str) even though it is not mentioned as one of the tags in [Err Bool, Whatever]*! Remember, when a function accepts an open tag union, any when branches on that union must include a catch-all _ -> branch, which is the branch that will end up handling the Ok Str value we pass in.

However, I could not pass an [Ok Str]* to a function with a closed tag union argument that did not mention Ok Str as one of its tags. So if I tried to pass [Ok Str]* to a function with the type [Err Bool, Whatever] -> Str, I would get a type mismatch - because a when in that function could be handling the Err Bool possibility and the Whatever possibility, and since it would not necessarily have a catch-all _ -> branch, it might not know what to do with an Ok Str if it received one.

Note: It wouldn't be accurate to say that a function which accepts an open union handles "all possible tags." For example, if I have a function [Ok Str]* -> Bool and I pass it Ok 5, that will still be a type mismatch. If you think about it, a when in that function might have the branch Ok str -> which assumes there's a string inside that Ok, and if Ok 5 type-checked, then that assumption would be false and things would break!

So [Ok Str]* is more restrictive than []*. It's basically saying "this may or may not be an Ok tag, but if it is an Ok tag, then it's guaranteed to have a payload of exactly Str."

In summary, here's a way to think about the difference between open unions in a value you have, compared to a value you're accepting:

• If you have a closed union, that means it has all the tags it ever will, and can't accumulate more.
• If you have an open union, that means it can accumulate more tags through conditional branches.
• If you accept a closed union, that means you only have to handle the possibilities listed in the union.
• If you accept an open union, that means you have to handle the possibility that it has a tag you can't know about.

Type Variables in Tag Unions

Earlier we saw these two examples, one with an open tag union and the other with a closed one:

example : [Foo Str, Bar Bool]* -> Bool
example = \tag ->
    when tag is
        Foo str -> Str.isEmpty str
        Bar bool -> bool
        _ -> Bool.false

example : [Foo Str, Bar Bool] -> Bool
example = \tag ->
    when tag is
        Foo str -> Str.isEmpty str
        Bar bool -> bool

Similarly to how there are open records with a *, closed records with nothing, and constrained records with a named type variable, we can also have constrained tag unions with a named type variable. Here's an example:

example : [Foo Str, Bar Bool]a -> [Foo Str, Bar Bool]a
example = \tag ->
    when tag is
        Foo str -> Bar (Str.isEmpty str)
        Bar bool -> Bar Bool.false
        other -> other

This type says that the example function will take either a Foo Str tag, or a Bar Bool tag, or possibly another tag we don't know about at compile time and it also says that the function's return type is the same as the type of its argument.

So if we give this function a [Foo Str, Bar Bool, Baz (List Str)] argument, then it will be guaranteed to return a [Foo Str, Bar Bool, Baz (List Str)] value. This is more constrained than a function that returned [Foo Str, Bar Bool]* because that would say it could return any other tag (in addition to the Foo Str and Bar Bool we already know about).

If we removed the type annotation from example above, Roc's compiler would infer the same type anyway. This may be surprising if you look closely at the body of the function, because:

• The return type includes Foo Str, but no branch explicitly returns Foo. Couldn't the return type be [Bar Bool]a instead?
• The argument type includes Bar Bool even though we never look at Bar's payload. Couldn't the argument type be inferred to be Bar * instead of Bar Bool, since we never look at it?

The reason it has this type is the other -> other branch. Take a look at that branch, and ask this question: "What is the type of other?" There has to be exactly one answer! It can't be the case that other has one type before the -> and another type after it; whenever you see a named value in Roc, it is guaranteed to have the same type everywhere it appears in that scope.

For this reason, any time you see a function that only runs a when on its only argument, and that when includes a branch like x -> x or other -> other, the function's argument type and return type must necessarily be equivalent.

Note: Just like with records, you can also replace the type variable in tag union types with a concrete type. For example, [Foo Str][Bar Bool][Baz (List Str)] is equivalent to [Foo Str, Bar Bool, Baz (List Str)].

Also just like with records, you can use this to compose tag union type aliases. For example, you can write NetworkError : [Timeout, Disconnected] and then Problem : [InvalidInput, UnknownFormat]NetworkError

Record Builder

The record builder syntax sugar is a useful feature which leverages the functional programming concept of applicative functors, to provide a flexible method for constructing complex types.

The record builder syntax sugar helps to build up a record by applying a series of functions to it.

For example, let's say we write a record-builder as follows:

{ aliceID, bobID, trudyID } =
    initIDCount {
        aliceID: <- incID,
        bobID: <- incID,
        trudyID: <- incID,
    } |> extractState

The above desguars to the following.

{ aliceID, bobID, trudyID } =
    initIDCount (\aID -> \bID -> \cID -> { aliceID: aID, bobID: bID, trudyID: cID })
    |> incID
    |> incID
    |> incID
    |> extractState

See the Record Builder Example for an explanation of how to use this feature.

Reserved Keywords

These are all the reserved keywords in Roc. You can't choose any of these as names, except as record field names.

if, then, else, when, as, is, dbg, expect, expect-fx, crash, interface, app, package, platform, hosted, exposes, imports, with, generates, packages, requires, provides, to

Operator Desugaring Table

Here are various Roc expressions involving operators, and what they desugar to.