path: root/learnxiny.tm

# Tomo is a statically typed, garbage collected imperative language with
# emphasis on simplicity, safety, and speed. Tomo code cross compiles to C,
# which is compiled to a binary using your C compiler of choice.

# To begin with, let's define a main function:
func main():
    # This function's code will run if you run this file.

    # Print to the console
    say("Hello world!")

    # You can also use !! as a shorthand:
    !! This is the same as using say(), but a bit easier to type

    # Declare a variable with ':=' (the type is inferred to be integer)
    my_variable := 123

    # Assign a new value
    my_variable = 99

    # Floating point numbers are similar, but require a decimal point:
    my_num := 2.0

    # Strings can use interpolation with the dollar sign $:
    say("My variable is $my_variable and this is a sum: $(1 + 2)")

    say("
        Multiline strings begin with a " at the end of a line and continue in
        an indented region below.
          You can have leading spaces after the first line
          and they'll be preserved.

        The multiline string won't include a leading or trailing newline.
    ")

    # Docstring tests use ">>" and when the program runs, they will print
    # their source code to the console on stderr.
    >> 1 + 2

    # If there is a following line with "=", you can perform a check that
    # the output matches what was expected.
    >> 2 + 3
    = 5
    # If there is a mismatch, the program will halt and print a useful
    # error message.

    # Booleans use "yes" and "no" instead of "true" and "false"
    my_bool := yes

    # Conditionals:
    if my_bool:
        say("It worked!")
    else if my_variable == 99:
        say("else if")
    else:
        say("else")

    # Arrays:
    my_numbers := [10, 20, 30]

    # Empty arrays require specifying the type:
    empty_array := [:Int]
    >> empty_array.length
    = 0

    # Arrays are 1-indexed, so the first element is at index 1:
    >> my_numbers[1]
    = 10

    # Negative indices can be used to get items from the back of the array:
    >> my_numbers[-1]
    = 30

    # If an invalid index outside the array's bounds is used (e.g.
    # my_numbers[999]), an error message will be printed and the program will
    # exit.

    # Iteration:
    for num in my_numbers:
        >> num

    # Optionally, you can use an iteration index as well:
    for index, num in my_numbers:
        pass # Pass means "do nothing"

    # Arrays can be created with array comprehensions, which are loops:
    >> [x*10 for x in my_numbers]
    = [100, 200, 300]
    >> [x*10 for x in my_numbers if x != 20]
    = [100, 300]

    # Loop control flow uses "skip" and "stop"
    for x in my_numbers:
        for y in my_numbers:
            if x == y:
                skip

            # For readability, you can also use postfix conditionals:
            skip if x == y

            if x + y == 60:
                # Skip or stop can specify a loop variable if you want to
                # affect an enclosing loop:
                stop x

    # Tables are efficient hash maps
    table := {"one": 1, "two": 2}
    >> table:get("two")
    = 2

    # You can supply a default argument in case a key isn't found:
    >> table:get("xxx", default=0)
    = 0

    # Otherwise, a runtime error will be raised:
    # >> table:get("xxx")

    # Empty tables require specifying the key and value types:
    empty_table := {:Text:Int}

    # Tables can be iterated over either by key or key,value:
    for key in table:
        pass

    for key, value in table:
        pass

    # Tables also have ".keys" and ".values" fields to explicitly access the
    # array of keys or values in the table.
    >> table.keys
    = ["one", "two"]
    >> table.values
    = [1, 2]

    # Tables can have a fallback table that's used as a fallback when the key
    # isn't found in the table itself:
    table2 := {"three": 3; fallback=table}
    >> table2:get("two")
    = 2
    >> table2:get("three")
    = 3

    # Tables can also be created with comprehension loops:
    >> {x:10*x for x in 5}
    = {1:10, 2:20, 3:30, 4:40, 5:50}

    # If no default is provided and a missing key is looked up, the program
    # will print an error message and halt.

    # Any types can be used in tables, for example, a table mapping arrays to
    # strings:
    table3 := {[10, 20]: "one", [30, 40, 50]: "two"}
    >> table3:get([10, 20])
    = "one"

    # Sets are similar to tables, but they represent an unordered collection of
    # unique values:
    set := {10, 20, 30}
    >> set:has(20)
    = yes
    >> set:has(999)
    = no

    # You can do some operations on sets:
    other_set := {30, 40, 50}
    >> set:with(other_set)
    = {10, 20, 30, 40, 50}
    >> set:without(other_set)
    = {10, 20}
    >> set:overlap(other_set)
    = {30}

    # So far, the datastructures that have been discussed are all *immutable*,
    # meaning you can't add, remove, or change their contents. If you want to
    # have mutable data, you need to allocate an area of memory which can hold
    # different values using the "@" operator (think: "(a)llocate").
    my_arr := @[10, 20, 30]
    my_arr[1] = 999
    >> my_arr
    = @[999, 20, 30]

    # To call a method, you must use ":" and the name of the method:
    my_arr:sort()
    >> my_arr
    = @[20, 30, 999]

    # To access the immutable value that resides inside the memory area, you
    # can use the "[]" operator:
    >> my_arr[]
    = [20, 30, 999]

    # You can think of this like taking a photograph of what's at that memory
    # location. Later, a new value might end up there, but the photograph will
    # remain unchanged.
    snapshot := my_arr[]
    my_arr:insert(1000)
    >> my_arr
    = @[20, 30, 999, 1000]
    >> snapshot
    = [20, 30, 999]
    # Internally, this is implemented using copy-on-write, so it's quite
    # efficient.

    # These demos are defined below:
    demo_keyword_args()
    demo_structs()
    demo_enums()
    demo_lambdas()

# Functions must be declared at the top level of a file and must specify the
# types of all of their arguments and return value (if any):
func add(x:Int, y:Int)->Int:
    return x + y

# Default values for arguments can be provided in place of a type (the type is
# inferred from the default value):
func show_both(first:Int, second=0)->Text:
    return "first=$first second=$second"

func demo_keyword_args():
    >> show_both(1, 2)
    = "first=1 second=2"

    # If unspecified, the default argument is used:
    >> show_both(1)
    = "first=1 second=0"

    # Arguments can be specified by name, in any order:
    >> show_both(second=20, 10)
    = "first=10 second=20"

# Here are some different type signatures:
func takes_many_types(
    boolean:Bool,
    integer:Int,
    floating_point_number:Num,
    text_aka_string:Text,
    array_of_ints:[Int],
    table_of_text_to_bools:{Text:Bool},
    pointer_to_mutable_array_of_ints:@[Int],
    optional_int:Int?,
    function_from_int_to_text:func(x:Int)->Text,
):
    pass

# Now let's define our own datastructure, a humble struct:
struct Person(name:Text, age:Int):
    # We can define constants here if we want to:
    max_age := 122

    # Methods are defined here as well:
    func say_age(self:Person):
        say("My age is $self.age")

    # If you want to mutate a value, you must have a mutable pointer:
    func increase_age(self:@Person, amount=1):
        self.age += amount

    # Methods don't have to take a Person as their first argument:
    func get_cool_name()->Text:
        return "Blade"

func demo_structs():
    # Creating a struct:
    alice := Person("Alice", 30)
    >> alice
    = Person(name="Alice", age=30)

    # Accessing fields:
    >> alice.age
    = 30

    # Calling methods:
    alice:say_age()

    # You can call static methods by using the class name and ".":
    >> Person.get_cool_name()
    = "Blade"

    # Comparisons, conversion to text, and hashing are all handled
    # automatically when you create a struct:
    bob := Person("Bob", 30)
    >> alice == bob
    = no

    >> "$alice" == 'Person(name="Alice", age=30)'
    = yes

    table := {alice: "first", bob: "second"}
    >> table:get(alice)
    = "first"


# Now let's look at another feature: enums. Tomo enums are tagged unions, also
# known as "sum types". You enumerate all the different types of values
# something could have, and it's stored internally as a small integer that
# indicates which type it is, and any data you want to associate with it.
enum Shape(
    Point,
    Circle(radius:Num),
    Rectangle(width:Num, height:Num),
):
    # Just like with structs, you define methods and constants inside a level
    # of indentation:
    func get_area(self:Shape)->Num:
        # In order to work with an enum, it's most often handy to use a 'when'
        # statement to get the internal values:
        when self is Point:
            return 0
        is Circle(r):
            return Num.PI * r^2
        is Rectangle(w, h):
            return w * h
        # 'when' statements are checked for exhaustiveness, so the compiler
        # will give an error if you forgot any cases. You can also use 'else:'
        # if you want a fallback to handle other cases.

func demo_enums():
    # Enums are constructed like this:
    my_shape := Shape.Circle(1.0)

    # If an enum type doesn't have any associated data, it is not invoked as a
    # function, but is just a static value:
    other_shape := Shape.Point

    # Similar to structs, enums automatically define comparisons, conversion
    # to text, and hashing:
    >> my_shape == other_shape
    = no

    >> "$my_shape" == "Shape.Circle(radius=1)"
    = yes

    >> {my_shape:"nice"}
    = {Shape.Circle(radius=1):"nice"}

func demo_lambdas():
    # Lambdas, or anonymous functions, can be used like this:
    add_one := func(x:Int): x + 1
    >> add_one(5)
    = 6

    # Lambdas can capture closure values, but only as a snapshot from when the
    # lambda was created:
    n := 10
    add_n := func(x:Int): x + n
    >> add_n(5)
    = 15

    # The lambda's closure won't change when this variable is reassigned:
    n = -999
    >> add_n(5)
    = 15