Lobster Language Reference

This is the definition of the language that tries to be a more exact a description of how the language works (the most exact description, however, will always be the source code :) ). As such, this is not the easiest way to learn the language, start with a tutorial first, and then use this for more difficult questions.

Syntactically Lobster tries to follow a mix of Python and C conventions where possible, but has a lot of unique syntax too.

Lexical definition


Below, ... indicates a loop with exit point at that scope level (ex. (ident ... ,) -> (ident (, ident)*), * meaning optionaly repeating), and || is like | except indicates a precedence level difference. [rule] Means optional.

program = stats end_of_file

stats = topexp … linefeed

topexp = namespace ident |import [ from ] ( string_constant | ( ident ... . ) ) | [ private ] ( functiondef | class | vardef | enumdef ) | expstat | attrdef

class = ( class | struct ) ident ( = ident specializers | [ generics ] : [ ident [ specializers ] ] indlist( ident [ : type ] [ = exp ] | functiondef ) )

specializers = < list( type ) >

generics = < list( ident ) >

vardef = ( var | let ) list( ident [ : type ] ) = opexp

enumdef = ( enum | enum_flags ) ident : indlist( ident [ = integer_constant ] )

functiondef = ( def | constructor ) ident [ generics ] functionargsbody

functionargsbody = ( args ) : body

block = [ args ] : body | functionargsbody

args = [ list( ident [ ( : | :: ) type ] [ = exp ] ) ]

body = ( expstat | indent stats dedent )

type = int | float | string | [ type ] | resource < ident > | void | ident [ specializers ]

call = [ specializers ] ( [ list( exp ) ] ) [ block [ fn block … ] ]

expstat = exp | return ( [ list( opexp ) ] ) [ from ( program | ident ) ]

exp = opexp [ ( = | += | -= | *= | /= | %= ) exp ]

opexp = unary [ ( * | / | % || + | - || < | > | >= | <= || == | != || & | | | and | or | ^ | << | >>) unary ]

unary = ( - | ++ | -- | ~ | not ) unary | deref

deref = factor [ [ exp ] | . ident [ call ] | -> ident | ++ | -- | is type ]

factor = constant | ( exp ) | super | ctrlflow | pakfile string_constant | constructor | fn functionargsbody | ident [ call ]

ctrlflow = if ifpart | (for | while) exp : body | guard exp [ : body ]

ifpart = exp : body (else : body | elif : ifpart)

constructor = [ [ list( exp ) ] ] [ :: type ] | ident { [ list( ident : exp | exp ] }

constant = numeric_constant | string_constant | character_constant | nil [ :: type ]

attrdef = attribute ident [ = ( string_constant | numeric_constant | ident ) ]

indlist(e) = indent list(e) [ linefeed ] dedent linefeed

list(e) = e ... ,


Lobster is statically typed, and any variable, argument or vector element can be a value of one of the following types:

Lobster does not have a built-in boolean type, though it does have a pre-defined bool enum (see enums below). In general, for boolean tests such as the not and or operators (see below) or the builtin function if, the values 0 0.0 nil (which includes the enum value false) are all considered to be false, and all other values are true.

The vector and class types are the only mutable objects (can change after creation), and have reference semantics (multiple values can refer to the same object in memory, and thus changes can be observed from each).

User Defined Types

The class and struct keywords allow you to define a user defined type. For example:

struct int2:

struct int3 : int2

You can use either class or struct to define these, with the latter being more restrictive: they are stored in-inline in their parent and copied. This makes sense for small objects such as the one in this example.

You specify a list of fields using indentation.

Optionally, you specify a supertype, which has the effect of adding all the fields of the supertype to the current type, thus making it an extension of the former.

The above example uses ints directly, but you can also define types more generically, and then define named specializations of them:

struct vec2<T>:

struct int2 = vec2<int>
struct float2 = vec2<float>

You construct values of these types you use a similar syntax:

let v = int2 { 1, 0 }

(Or use float2 { 1, 0 } / vec2<bool> { true, false } to explicitly pick a different specialization).

struct float2:
    x = 0.0
    y = 0.0

Additionally, you may specify default values, if these are given, then these values are not arguments to the constructor, e.g. vec2 {}.

For more complex structs, you can use field names as "tags" in a constructor call, for example:

vec2 { x: 1, y: 2 }

Besides being more readable, it allows you to specify the fields in any order, and to override fields that have defaults.

For more complex ways of constructing types, see constructor functions below.

To declare a type whose only purpose is to serve as a superclass for other types and is not to be instantiated, declare it with abstract:

abstract class Node


Lobster comes with a set of built-in operators mostly familiar from other languages that attempt to work on as many of the above types as makes sense. In particular, unlike most languages, many of them work on (numeric) structs, which makes typical game code both convenient and fast.

Assignment and Definition

The assignment operators simply copies the value on the right hand side into the variable or vector index on the left hand side:

a = 1
v[0] = 1
v.x = 1

All variables must already have been declared, or this will result in an error. var defines and assigns in one go, and requires the variable to not have been declared yet in this scope. let does the same for variables which cannot be modified afterwards:

var a = 1
let b = 1
var d, e = 1, 2

As you can see in the last 2 lines, all of these operators also allow multiple values to be assigned at once (see also multiple return values below).


As indicated, square brackets can be used to index into vectors, and similarly . can dereference fields of a class or struct. These may be chained arbitrarily.

You may even use a vector as index, e.g.

let mat = [ [ 1, 2 ],  [ 3, 4 ] ]
let pos = int2 { 0, 1 }
print mat[pos]

This prints 3, and is a convenient shortcut for mat[pos.y][pos.x]. Note how it uses the last element to index with first, this is because in code and other places 2d arrays are usually most naturally thought of as row-major.

Mathematical Operators

The 5 binary mathematical operators + - * / % (the last 3 having higher precedence) work on int, float (or a combination, where the end result will be float). They also work on structs containing ints or floats with either another struct or a single int or float. These structs must be the same type.

int2 { 1, 2 } * int2 { 4, 5 }  // results in int2 { 4, 10 }

All 5 also have have a combined assignment operator version, += -= *= /= %=, which are implemented to have exactly the same effect as their expanded form, e.g. a += 1 is always exactly the same as a = a + 1.

In addition, the + operator also works as string concatenation if either side is of string type (the other side will be converted to a string representation if it wasn't already), though in most cases you should prefer to use string interpolation (see below).

Unary minus (-) acts on the same types in the same way as the binary version.

The increment and decrement operators ++ and -- work either as prefix (increment, return new value) and as postfix (increment, return old value) on any lvalues.

Bitwise operators & | ^ ~ << >> behave like they do in any other language.

Comparison and Logical Operators

The next lower level of precedence are the comparison operators < > <= >= which work on int, float and string and structs (returning a struct of ints, use builtin functions any and all to test these), and then the equality operators == and != which additionally work on all other types, but in particular for vector and class compare by reference, i.e they will give true only if both sides refer to the same object (object identity). To test for structural identity instead, use the built-in function equal.

The logical operators and and or are the next lower level of precedence, and both short-circuit: a or b returns a if it is not a false value (one of 0 0.0 nil), and b otherwise. a and b returns a if it is a false value, b otherwise. The unary operator not turns false values into 1 and others into 0.

The is operator returns true if the left hand side value is of the type specified on the right, e.g. x is float.

Function Definitions

Lobster's entire design centers around functions and how they can be composed. It has both named functions and function values.

Named Functions

Named functions can be declared at any scope level (may be local), like so:

def name(arg1, arg2): body

body can either be a single expression, or, most commonly, an indentation (start of code on the next line further than the previous line, in this case the def keyword), and then any number of expressions on their own line separated by linefeeds, until a de-dedentation occurs (return to the indentation level of the parent, in this case again the def keyword). It is an error to de-dedent less than the parent level. For example:

def name(arg1, arg2):

The return value of a function is determined by its return statements (see below) or void (no return value) otherwise, except for anonymous functions, which don't need an explicit return (it is automatically the last expression evaluated).

Arguments can be just an argument name (which will be available as a lexically scoped local variable inside body), or a typed name (e.g. s:string). If you don't specify types, the function is generic, meaning it will receive types from the caller. If called with multiple combinations of incompatible arguments, you automatically get multiple "specializations" of the same function, meaning working with different types is very easy. Alternatively, you can specify generic types explicitly as well (more in type system).

You can use :: instead of : for typed class/struct arguments, which allows you to access all fields / functions of that object directly, without having to prefix them with the argument name, e.g.:

def magnitude(v::vec2): return sqrt(x * x + y * y)

You can also leave out the v::vec2 entirely if you define this function as part of a class / struct definition of type vec2 (see above). Both types of definition are equivalent.

You can specify an explicit return type, like so:

def f(a:int, b:int) -> float: return a + b

This is typically not necessary, but may be helpful when coercing to a more general type.

Function calls

Functions can be called as part of an expression with a similar syntax to its definition, e.g. name(1, 2). Alternatively, you may use the . notation to place the first argument ahead of the call, for example 1.name(2). If you are using the . notation with a function that has just one argument, the () may be omitted, v.length being a common example. You are encouraged to only do this for simple functions that return a property of the argument, and don't modify the argument.

Optionally, you may also call functions without any parentheses at all, e.g. print "hi!". This is only allowed for known functions (that are not ambiguous with variables) that have 1 expression argument (followed by any number of function value arguments that don't take arguments themselves, see below). It is up to the programmer to use good judgement on when to use this, the recommended use case is for calls used as statements (no nesting) that don't cause additional parentheses to be needed elsewhere. In case of doubt, use the standard call syntax.

Function Values

You can also create anonymous (nameless) functions as values. In the most general case, this has the syntax:

let f = fn(a:type, n:type): body

Or, if you are not specifying any types:

let f = fn a, b: body

You call these just like any other function, e.g. f(1, 2). You currently must call them using a variable (not any expression, not even a field).

The full fn syntax is infrequently used however, because most function values are created to be passed to other functions, and Lobster has a special syntax for this situation that is meant to mimic control structures in other languages. Any function call may be followed by one or more function values, where the fn keyword is omitted:

g(10) i: print(i)

Here, the function g is called with 2 arguments, the first is 10, and the second is the function value fn i: print(i) (as before, we left out the the () around the arguments). Lobster allows yet further simplification of the syntax:

g(10): print(_)
g 10: print _

You may use anonymous arguments, which are variable names starting with an _ that will automatically be declared as arguments for you. If you use multiple such arguments (e.g. _a and _b), they will become arguments in the order they appear in the body. Using anonymous variables is only recommended for very simple function bodies.

As mentioned above, you may drop the parentheses entirely if the body doesn't have any argument declarations.

This style of syntax is intended to make each function that takes a function as argument (a higher order function) have the convenient syntax of a control structure, since that's what those functions usually are meant to be anyway. Lobster's built-in control structures if for and while have syntax that is closely compatible with this function call syntax (and in the case of for allow the same argument simplifications).

The return value of these functions is the last expression in body. You don't use explicit return statements, as those are used with the enclosing named function instead, see "Explicit Returns" below.

Though not recommend (as readability suffers), it is even possible to pass multiple function values to a function, but then every function value except the first can't omit the fn keyword:

g(10) i:
    print i
    print "reached the end"

For example, to pass an additional function to do something special at the end of an iteration.

Writing your own functions that take function values is the key to getting the most out of Lobster. It allows you to refactor pretty much any code into something that has no redundancy yet is easy to create, use and modify.

Typically, to write a function that takes a function value argument, simply use an argument with no type:

def twice(f):
    for(2): f()

Sometimes, you may want to be explicit about the function type. You can declare new function types, and then use them as a type:

def function_type(i:int) -> int
def g(f:function_type): return 1 + f(2)

Besides enforcing the type of function that can be passed (which makes for more readable errors when it fails), it also forces the function passed to not be inlined (which may reduce code-bloat if functions taking this function type are called many times, at a minimal hit in speed). Function values called over a generic variable are always inlined (since they represent a unique function type even if its signature is accidentally the same as another function value), to ensure higher order functions are competitive in speed with hard-coded equivalents.

Lobster really wants you to be able to use function values everywhere at no cost, so besides guaranteed inlining, the other way they differ from other languages is that they are always non-escaping. What that means is, that while function values may use free variables (refer to variables from enclosing scopes), they are not "closures", i.e. they do not close over (capture) these variables, they merely refer to them. This means these function values cannot be called from an environment where those free variables are not available anymore (this will typically result in a compile-time error). This makes a function value in Lobster a single code pointer without any variable information attached, and thus extremely cheap. The downside is that they can't be used for things like certain kinds of callbacks, though you probably shouldn't be using those in game-like contexts anyway ;)

Explicit Returns

Using return you return from the closest lexically enclosing named function, e.g.:

def find(list, x):
    for list:
        if x == _:
            return true
    return false

find's return value is false unless the nested return gets evaluated, and then it becomes true. Importantly, return true is an expression that sits inside a function value being passed to if (which in turn sits in a function value passed to for), but bypasses all of this (unlike most programming languages with function values). This is essential for functions to be able to work as proper control structures.

If this feels like it is similar to exception handling in other programming languages, that's because it is. Lobster even allows you to specify the name of the function to return from (e.g. return "expression expected" from parse), which is extremely handy when you want to be able to return errors from a bunch of helper functions without having to pass it back through all intermediate functions, such as when writing a parser. This is a simple form of exception handling, that is also powerful enough to allow you to implement fully general exception handling in Lobster code, see exception.lobster.

You can use the keyword program instead of a function name to force returning from the entire program.

If you need to return from a function value with an explicit return, you need to turn that particular function into a named function instead.

Multiple Return Values

return can specify more than one value to be returned, which can then be received by the multiple assignment syntax introduced above:

def m(): return 1, 2
let a, b = m()

All return statements for any function must all return the same number of return values.

When m returns multiple values, they get assigned to each variable in turn. If there are more return values than there are variables, additionally values are thrown away, and if there are more variables than there are return values, this is an error.

Other than functions (and in assignments statements, see above), expressions can return multiple values in other contexts too, but there may need to be placed in parentheses to disambiguate them from other uses of ,:

let x, y = if foo: m() else: (1, 2)


Functions and variables declared there-in always obey lexical scope: any use of a variable always refers to the closest enclosing definition of it.

Since functions and function values can be defined at any scope level, this means they can access variables from enclosing scopes, called free variables. Free variables are essential to make Lobster's higher order functions convenient. References to free variables are only valid within the scope they are defined, which luckily is almost always the case, but can be broken by storing a function value and then calling it at a later time outside of the context where its free variables were valid, which will result in a runtime error. Other languages use closures to ensure availability in all cases, which are very costly (parent stackframe(s) may have to be dynamically allocated) as opposed to Lobster's approach which makes function values and free variables have no overhead compared to regular functions and variables.

Overloading and dynamic dispatch

Overloading and dynamic dispatch are part of the same system, the only difference being wether choosing the right function is done at compile time or runtime.

You can define these overloads anywhere, either as part of a class, or outside of them, regardless of wether you wrote the original class. For example:

def f(a::A): return 1
def f(b::B): return 2
def f(c::C): return 3
def f(i:int): return 4

(as we note above, using :: instead of : merely means all fields of that type become directly available, saving you having to type a., but is otherwise equivalent.)

What happens when you call f depends on the types above, and the type you call it with. If all 4 types are unrelated, then you guaranteed get static dispatch (a normal function call). If B inherits from A, but C is unrelated, and you call with either a B, C or int argument type, you still get static dispatch, since there is statically only one option.

Only if you call with an A argument however, you get dynamic dispatch, since the argument may point to a B value, and B has a different function implementation. A dynamic dispatch goes thru a "virtual table", and while slower than static dispatch, is still very fast. As you can see, wether something is "virtual" gets decided per call, and with knowledge of the whole program (all types and functions that can possibly exist), so typically less calls result in dynamic dispatch than in other languages.

Types like int never participate in dynamic dispatch, since they don't have a sub-class relation to any other type.

Defining these functions can also be done "in line" in a class declaration, like so:

class A:
    def f(): return 1

This definition of f for A is entirely equivalent to the one above, except the name of the first argument is now this instead of a above.

Only the first argument to a function is used to resolve dynamic dispatch, but for static overloading, all arguments will be taken into consideration. Lobster used to have the ability to dispatch on all arguments, called "multi-methods", which at least academically seem very elegant. In practice however, these are slow (require complicated look-up tables) and ambiguous (hard to tell which function will get called, sometimes accidentally combine unrelated functions into a multimethod and get unexpected errors or slow-down). Single dispatch gives predictable, fast polymorphism that seems to work well for most languages, so for the moment, multi-methods are removed from the language.

Overloading and dynamic dispatch can even be mixed with type specialization (see type system), meaning you can generate multiple versions of a polymorphic call that do different things. Simply leave out the type of any arguments beyond the first:

class A:
    def g(c): return c + 1
class B : A
    def g(c): return c + 2
x : A = B {}  // Type is A, but dynamic value is a B!
assert x.g("hi") == "hi2"
assert x.g(3) == 5

Here, the call to g is dynamically dispatched for A or B, but choosing the int or string specialization is entirely static.

You can force calling a superclass method with the super keyword:

class B : A
    def f(): return 1 + super f()

That f() is statically dispatched to call A's version of f (or its superclass, if it doesn't have one).

You can also "dynamic dispatch" with switch ! You can use class names as switch cases:

switch x:
    case A: print x.field_in_a
    case B: print x.field_in_b

As you can see, the type of variable switched on will be "upgraded" to the type matched, so you can access its fields.

switches on types are "exhaustive", meaning if you don't use a default case (and its a good habit to not use those) you will get a compile-time error if a type is not covered by a switch (all possible subclasses of the type of the switched on value).

Superclass cases can apply to subclass cases, and if both are present, the most specific case will always be used. It is a good idea to make superclasses abstract for use with switch, that way you may omit a case for them, causing all their subclasses to need their own case.

The actual implementation use vtables much like the above dynamic dispatch, so is similar in speed too.

Functions with different number of arguments / default arguments.

You can define functions with the same name but different number of arguments. These are essentially treated as independent functions, in the sense that which is being called is always determined completely statically.

Functions can even have default arguments, as long as the default arguments don't cause ambiguity with other functions of the same name:

def da(a:X, b, c = x + 1): return c
def da(a:Y, b, c = x + 1): return c
def da(a): return a

This defines 2 complete separate functions, one that has 3 arguments (and can be called with 2, since it has one default argument), and one with 1 argument. As you can see, since there is no overlap in number of arguments, it is always clear which variant is being called.

The version with 3 arguments has 2 overloads. Overloads must have exactly the same default arguments, if any.

Default arguments are simple substitution, writing da(1, 2) is exactly the same as writing da(1, 2, x + 1). That's why you can even use variables in these default arguments, as long as they're in scope when called.

Operator overloading.

You can overload what operators do on class and struct types, by writing a function that defines what the operator should do:

struct A:
    def operator+(o:A): return A { x + o.x }
    def operator-(): return A { -x }

print - A { 2 } + A { 3 }  // A { 1 }

You may currently overload: + - * / % ++ -- == != < > <= >= & | ^ ~ << >> = += -= *= /= %= &= |= ^= <<= >>= [] (indexing).

Overloaded operators are parsed with the same operator precedence as for the built-in operators, but when it comes to typechecking, they are handled as regular function calls, with all that entails. The above expression is thus handled internally as operator+(operator-(A { 2 }), A { 3 }) where operator+ is just an ordinary function name.

The assignment operators make most sense to overload on class types, since there you can overwrite the members of the this (or left) argument of the operator. There is currently no way to do this with struct which are always copied by value.

See more examples in modules/quaternion.lobster and tests/operators.lobster.

Global and Class member variables with function scope.

You may declare a (what appears to be) a local variable with the member keyword instead of let, which automatically stores it in the surrounding class:

class Foo:
    a = 1
    def bar():
        member b = 2
        b += a
        return b

Calling bar will give different results each time, it really is almost the same as writing:

class Foo:
    a = 1
    b = 2
    def bar():
        b += a
        return b

The difference is that b is not available outside of bar, trying to access it will result in an error.

But why would you want to do this, if it so similar? A small example doesn't do this justice, but in games it is very common to need a lot of variables that track state of things that happen across frames, which are often used in just a single method, and end up cluttering the class they are in. By using member, you put the declaration closer to where it is used, which makes it easier to view all occurrences in larger classes. It also makes it easy to see that the variable is used only in a single method. This reduces "cognitive load" in understanding the code, compared to seeing a long list of member variables at the top of a class and not knowing what their relationship is. Seeing that the variable is local to, say, render() also gives additional information what the variable may be used for.

Currently, member must occur in a function declaration that is declared inside a class (not a struct), restrictions that may be lifted in the future.

You can do the same for functions outside of classes with the keyword static:

let a = 1
def bar():
    static b = 2
    b += a
    return b

Which again is pretty much the same as writing:

let a = 1
var b = 2
def bar():
    b += a
    return b

With again the main difference being that in the former, b's scope is restricted to bar. This is not as useful as member because there is only ever one instance possible, but still nice to use when you can to simplify the complexity of global scope elements.

But these two features are just the start of the real fun: the member_frame and static_frame keywords. These behave like their counterparts above, with one subtle difference: they will be reset to their initializer whenever a frame does NOT use the variable. Or rather, their state is persisted as long as frames keep using the state. It's like "immediate mode", but for state. For example using static_frame (member_frame works the same other than where the variable is stored):

def foo():
    static_frame b = 0
    print b++

gl.window("foo", 100, 100)
while gl.frame():
    static a = 0
    if a % 4:
        print "/"

This will print an endless sequence of 0 1 2 / 0 1 2 / 0 1 2 / .. until you close the window. Why is this special? Notice that foo didn't need to be told when to reset its sequence, that was automatic. In a game, you often have a lot of systems and states those systems can be in, and when something changes (the user goes into a menu or a particular gameplay or animation state), all these systems need to be "updated" to be aware of the new situation. Here, much like with an immediate mode gui where you don't need to worry about creating and deleting widgets, simple control flow can dictate what systems are "active", and their associated state automatically gets reset when the situation changes. It's as if the variable b doesn't exist when foo is not being used, and it automatically gets created/deleted for you.

variables declared this way use more space and an extra check (an extra variable to check the frame count) but otherwise function just like normal variables, so you should feel free to use them wherever they make the code simpler/clearer.

Constructor functions

As shown above, a user defined type always comes with a plain constructor that requires exactly all initialized fields in {}. That is sufficient for most cases but sometimes you may want to do additional processing on the inputs where the mapping from inputs to fields in not 1:1.

In that case you can declare a function with the keyword constructor instead of def:

constructor Foo(n:int):
    return Foo { map(n): 0, map(n): 1 }

This function behaves like a normal function, except that it marks type Foo as having a constructor, and hence forth doesn't allow code outside of this function to be constructed using a plain {} constructor, it must call this function instead. This is because a constructor may encode an invariant, such as in this case that the object is always initialized to two vectors of the same length with elements initialized to 0 and 1 respectively. You couldn't do this with a plain constructor, since there would be no way to take the variable n into account.

Another common case is wanting to make a variable non-nil, but there is no way to construct a general instance of the type that would work for all cases. Now you can make it depend on a caller supplied argument.

You call these constructors with regular function calling syntax (e.g. Foo(10)) instead of with {}, to make it clear that additional code may be executed beyond plain field initialization (and that a function is called).

You may create overloads for constructors much like regular functions, or even make them dynamically dispatch, as long as they all result in the given type.


Lobster is statically typed, though most of the time you don’t notice, since most types can be inferred. You specify types:

As we've seen, you can type function arguments and UDT fields.

For more detail, see the type system.


enum example:
    foo = 1

An enum defines a "strongly typed alias" for the int type. What this means is that these values are fully compatible with int in any use, but a regular int can't be passed to a context where an enum type is explicitly requested.

You can convert integers explicitly to an enum with a coercion function, e.g. example(1) will create a value equivalent in type and value to foo.

If you leave out the = 1, the sequence will start at 0 instead. Values automatically increment from the last explicitly specified value, so bar will be 2 here. Instead of enum you can use enum_flags, which changes the default first value to 1 and uses * 2 to get to next value instead of + 1.

Functions like string, print will get you the name of an enum value, and likewise parse_data can turn these names into enum values (when part of a data structure).

When you use an enum in a switch, it is an error to not test all values of an enum (if there is no default case).


A bool is not a built-in type, rather it is defined as an enum in stdtype.lobster:

enum bool:

Because they are enums, they have the same typing rules: a bool can be used anywhere an int is expected, but not the other way around. Similarly, you can use e.g. bool(1) to convert ints.

Programs Structure

A lobster program is like the body of a function: a list of expressions on separate lines, defined by a single file, the main file of your program. At this top level of a file, you can additionally use the import keyword to bring additional code into your program:

import std

The contents of that file will be merged into your main file at the location of the import for the purpose of compilation. If you you import the same file twice, the second occurrence will be ignored.

An identifier like std is the same as specifying "std.lobster", similarly a.b is short for "a/b.lobster".

Modules will typically be loaded relative to 2 locations: the current main .lobster file being compiled, and wherever the lobster compiler is installed. In both those locations, files may be optionally be found under an modules sub-directory. You can use import from "path/to/" to provide additional such starting directories (relative to the current main .lobster file being compiled) that any following import statements (recursively) can use.

You may use the keyword private at the top level in a file to prefix structs, variables, functions, enums, fields and methods that you don't want to be visible outside that file.

Memory Management

Lobster uses (compile time) reference counting as its form of management for many reasons. Besides simplicity and space efficiency, reference counting makes a language more predictable in how much time is spent for a given amount of code, since memory management cost is spread equally through all code, instead of causing possibly long pauses like with garbage collection. Lobster has a custom allocator that is very fast.

Most reference counting happens at compile time using a "lifetime analysis" algorithm, details here.

Reference counting has one problem, which is that it can't deallocate cycles. For example, this code:

class rec:

var x = nil
x = rec { nil }
x.r = x
x = nil

will cause a memory leak, since initially the object that x points at has a reference count of 1, then that count increases to 2 because it now points to itself, and then when the count is reduced to 1 because of x's reference going away, we now have an object with no outside references that still thinks its being referenced, thus not deallocated. That is a leak. Now this is a simple example, but in the general case with complex data structures, it is not generally possible for a programming language to ensure this never happens.

Leaks like these are not common, as they only occur with graph-like structures or "parent reference" common in more complicated data structures. An example in a game might be if two game units refer to each other as their "enemy", and then both die at the same time with the programmer forgetting to reset the enemy field before they die.

Lobster deals with this by detecting that such objects are left over at the end of the program, and alerting the programmer that there are leaks. It then outputs a "leak report" with all leaks in somewhat readable form (with types and values), making it easier for the programmer to figure out what caused the leak. The programmer can then easily fix the leak by setting the reference causing the cycle to nil, like clearing the enemy field when a unit dies, or by writing x.r = nil in the above simplified example.

More details on Lobster's memory management.

Control Structures

As noted, all of these follow closely the function call syntax introduced above as much as possible, but are otherwise treated specially by the language.

if may be followed by multiple elif blocks and a single else block:

if a < 0:
    print "negativity not allowed!"
elif a < 10:
    print "single digit!"
elif a < 100:
    print "double digit!"
    print "way too big!"

elif is simply short for writing else: if. You can also write these on a single line, which is only recommended when very short, e.g. if a < 0: 0 else: a

for is the only built-in construct taking 0 to 2 arguments to the block: the element being iterated over, and iteration index.

We can iterate over vectors (each element), strings (each byte), or integers (values 0..N-1):

for("hello") a, i:
    print "{i}: {a}"

Here a will contain the 5 characters and i will be just 0 to 4.

The module std contains further useful loop constructs on top of for, like map, filter, and exists etc.

while is an odd function, since it is an exception to the rule of Lobster syntax:

while a < 10: a++

That looks perfectly normal, but one thing should stand out: while takes not one, but 2 function values. Normally, in Lobster, this would make more sense:

    a < 10

but since people are so used to the way while loops work from other languages, the first argument has a special type that automatically converts an expression into a function value. When you think about it, even in languages like C the condition of a while is the only part of the language that can be executed more than once yet does not use / cannot use the block {} syntax. This exception is carried over in Lobster. This is not great for readability so isn't generally used elsewhere.

while returns void. A similar function int module std called collectwhile returns a vector of all body return values.

Both for and while can have a break statement inside of them, that exits the enclosing loop. Alternatively, use return or return from (see above) for more complex cases.

Many other functions that look like regular functions are actually also control structures, like many of the graphics function that change the current rendering state. An example is gl.translate, that optionally takes a body, and will run the body and restore the previous transform afterwards.

switch has special syntax, since it does a lot of things different:

var st = switch i:
        case 1: "no"
        case 2, 3:
            var x = i
        case 4..6, 8: "maybe"
        default: "what?"

The value you switch on may be int, float, string or class instance. Cases may test for multiple values, even ranges (which are inclusive). When testing for class instances, the cases are types which must exhaustively cover all non-abstract sub-classes of the class type.

guard is a special variant of if for writing code in "early-out" style:

guard a >= 0:
    print "error: a is negative!"

Is equivalent to:

if a >= 0:
    print "error: a is negative!"

Why would you want this over a traditional if-else? The idea that code becomes easier to read if it is written in a more linear style, dealing with all cases where the code does not apply first, before getting to the main body of code. This becomes more obvious if you use nested if-thens.

A lot of code tends to use a return inside an if for this early-out style of programming, but that has the problem that it only works at the top level of a function. guard works for code anywhere, and does not require the extra return statement.

If there is no code to run in the error/exceptional case, you may even shorten it to:

guard a >= 0

Is equivalent to:

if a >= 0:

That reads like an assert except instead of aborting the program, it skips the rest of the block.

Modules and Name Spaces

A module is simply a single .lobster file, that can be imported into another using the import keyword. You can import a module from multiple files and it will only be compiled once.

You can prefix any top-level declaration by private to cause it not be available to users of the module.

Lobster has a namespacing mechanism that uses . for separating namespaces:

namespace foo

class bar:
    x = 1

def baz(): return bar {}

Names bar and baz can be used as-is inside this module, but must be referred to as foo.bar and foo.baz outside of this module. Non-top level items like x are not affected.

Most built-in functions come with a namespace, such as gl etc.

Since namespaces look the same as object dereferencing, it is recommended to use a name with a leading uppercase for namespaces wherever possible.

Declaration order

Lobster is a language that relies heavily on type inference and generic types, and generally not requiring you to specify types, the order in which things get type-checked sometimes matters.

Lobster type-checks function calls in call order, but type declaration in the order in which they are specified in the source code, or imported.

As such, to allow the maximum amount of freedom it what can refer to what, it is recommended to import files and declare types (structs and classes) as much as possible in the order of dependencies (least dependent things first), and call functions from top level (which triggers a lot of use of these types) only after all have been declared.

This is not always possible, so there are ways to declare things ahead of definition, for example:

class Monster

(note the lack of : introducing the definition) pre-declares this type, so it can be referred to by types defined before Monster is finally defined. This allows for circular dependencies.

Similarly, you may declare variables before you define them:

class World
var world:World

// Lots of types that may want to access `world` as a global in their methods goes here.
// Then finally `World` gets defined based on the earlier types.

var world:World = World {}

It is an error to access world by code in between its declaration and definition. Typically, all code accessing world in any methods in between only gets called below, so this works out fine.

Type Checking

This has its own document, here.

Built-in Functions

Please refer to the built-in function reference.

String Interpolation

This is a convenience feature that allows you to write arguments to string conversion inline in the string, instead of endless amounts of " + " separators, which tends to be less readable for longer sequences.

"a = {a} and b = {b}"  // Same as: "a = " + a + " and b = " + b
"a = {f(a) + 1}"       // Same as: "a = " + (f(a) + 1)
"{a}"                  // Same as: string(a)

Because of this feature, if you actually want to put { or } in a string constant, they must be escaped (by using 2 of them, or prefixing with a \), e.g.

let a = 42
print "\{ {a} \}"  // Prints: "{ 42 }"


Lobster has built-in multi-threading functionality, that is in its early stages.

It is different from multi-threading in most other languages, in that it does not allow threads to share memory or any other VM state. It essentially runs one Lobster VM per hardware thread / core, each running an independent and isolated copy of your Lobster program. This prevents entire classes of potential concurrency bugs, like race conditions.

Communication/synchronisation between the threads is explicit through the use of a "tuple space" (a bag of Lobster objects used as messages) which are copied rather than shared. While copying is potentially slower than sharing, it allows each Lobster VM to run as-if it was single-threaded, with no synchronisation primitives to slow it down (for example, memory allocators in Lobster are single-threaded), no GIL (global interpreter lock) or other multi-threading overhead, so overall performance can easily be higher than shared memory concurrency systems.

The use of tuple spaces and 1 VM per thread suits "worker" style concurrency, for example if you have 100 parallel tasks to perform, you throw each of those in the tuple space, and the individual VMs grab and complete them, given automatic load balancing for however many cores are available.

For now, the easiest way to get a feel for how this works is to read samples/threads.lobster.