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Label is a bit more accurate than "symbol" for this sort of node in terms of its function in the AST.

"Qualified labels" are those which are namespaced, e.g. `module.function` or `record.field` (though the latter doesn't work yet.)

This was a fairly invasive change that also impacted how module names are handled but I think it's a relatively big step towards a lot more consistency and clarity in the AST.

* Renaming "symbol" to "label", adding "qualified labels"

"Label" is a more appropriate name for how these things are used since
they're quite literally labelling variables, modules, etc.

Qualified labels are those that are prefixed with some sort of
namespace, like a module or record, e.g. `lists.keyfind`.

* Parser and scanner changes for symbol -> label

Lots of this is trivial renaming but there are some more substantial
changes in how module names are handled now.  Since they're initially
captured as labels which use binaries for names, I carried this binary
format through elsewhere.  Following commits will show the more
invasive changes this required.

* AST and Code generation symbol -> label changes

This had the side-effect of making some inter-module checks more
strict earlier in the AST generation which I think is not a bad
thing.  It basically meant that some code generation tests which
separately compiled modules need to now include them all up front.
This additionally made one of the stacktrace tests redundant, changes
coming in a later commit.

* Typer changes for symbol -> label

Lots of atom -> binary things which required a lot of
spelunking (missed having static typing in this pass.)  Took the
opportunity to document a few things more, and found a private types
bug as well which will need fixing but I might defer to when we get
into abstract types.

* Exhaustiveness and printer symbol -> label changes

Nothing particularly drastic here although both modules' tests helped
turn up some earlier silly mistakes.

* Final symbol -> label changes

Added a version of `compile/2` to help tests that have multiple
modules in memory rather than on-disk.

* alpaca.hrl to allow general use of `compiled_module` record

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Alpaca is a statically typed, strict/eagerly evaluated, functional programming language for the Erlang virtual machine (BEAM). At present it relies on type inference but does provide a way to add type specifications to top-level function and value bindings. It was formerly known as ML-flavoured Erlang (MLFE).

TLDR; How Do I Use It?

Make sure the following are installed:

Installing Alpaca

Releases for OTP 19.3 and 20.0 are built by Travis CI and are available under this repository's releases page here. You will want one of the following:

  • alpaca_19.3.tgz
  • alpaca_20.0.tgz

You can unpack these anywhere and point the environment variable ALPACA_ROOT at the base folder, or place the beams sub-folder in any of the following locations:

  • /usr/lib/alpaca
  • /usr/local/lib/alpaca
  • /opt/alpaca

Please see the rebar3 plugin documentation for more details.

Using Alpaca in a Project

Make a new project with rebar3 new app your_app_name and in the rebar.config file in your project's root folder (e.g. your_app_name/rebar.config) add the following:

{plugins, [
    {rebar_prv_alpaca, ".*", {git, "", {branch, "master"}}}

{provider_hooks, [{post, [{compile, {alpaca, compile}}]}]}.

Check out the tour for the language basics, put source files ending in .alp in your source folders, run rebar3 compile and/or rebar3 eunit.

Building and Using Your Own Alpaca

Rather than using an official build, you can build and test your own version of Alpaca. Please note that Alpaca now needs itself in order to build. The basic steps are:

  • Clone and/or modify Alpaca to suit your needs.
  • Compile your build with rebar3 compile.
  • Make a local untagged release for your use with bash ./ in the root folder of Alpaca.

Then export ALPACA_ROOT, e.g. in the Alpaca folder:

export ALPACA_ROOT=`pwd`/alpaca-unversioned_`

The rebar3 plugin should now find the Alpaca binaries you built above.

Editor Support

Alpaca plugins are available for various editors.


Something that looks and operates a little bit like an ML on the Erlang VM with:

  • Static typing of itself. We're deliberately ignoring typing of Erlang code that calls into Alpaca.
  • Parametric polymorphism
  • Infinitely recursive functions as a distinct and allowable type for processes looping on receive.
  • Recursive data types
  • Syntax somewhere between OCaml and Elm
  • FFI to Erlang code that does not allow the return of values typed as term() or any()
  • Simple test annotations for something like eunit, tests live beside the functions they test

The above is still a very rough and incomplete set of wishes. In future it might be nice to have dialyzer check the type coming back from the FFI and suggest possible union types if there isn't an appropriate one in scope.

What Works Already

  • Type inferencer with ADTs. Tuples, maps, and records for product types and unions for sum. Please note that Alpaca's records are not compatible with Erlang records as the former are currently compiled to maps.
  • Compile type-checked source to .beam binaries
  • Simple FFI to Erlang
  • Type-safe message flows for processes defined inside Alpaca

Here's an example module:

module simple_example

-- a basic top-level function:
let add2 x = x + 2

let something_with_let_bindings x =
  -- a function:
  let adder a b = a + b in
  -- a variable (immutable):
  let x_plus_2 = adder x 2 in
  add2 x

-- a polymorphic ADT:
type messages 'x = 'x | Fetch pid 'x

{- A function that can be spawned to receive `messages int`
    messages, that increments its state by received integers
    and can be queried for its state.
let will_be_a_process x = receive with
    i -> will_be_a_process (x + i)
  | Fetch sender ->
    let sent = send x sender in
    will_be_a_process x

let start_a_process init = spawn will_be_a_process init


Alpaca is released under the terms of the Apache License, Version 2.0

Copyright 2016 Jeremy Pierre

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Contributions and Help

Please note that this project is released with a Contributor Code of Conduct, version 1.4. By participating in this project you agree to abide by its terms. See for details.

You can join #alpaca-lang on freenode to discuss the language (directions, improvement) or get help. This IRC channel is governed by the same code of conduct detailed in this repository.

Pull requests with improvements and bug reports with accompanying tests welcome.

Using It

It's still quite early in Alpaca's evolution but the tests should give a relatively clear picture as to where we're going. test_files contains some example source files used in unit tests. You can call alpaca:compile({files, [List, Of, File, Names, As, Strings]}, [list, of, options]) or alpaca:compile({text, CodeAsAString}, [options, again]) for now but generally we recommend using the rebar3 plugin.

Supported options are:

  • 'test' - This option will cause all tests in a module to be type checked and exported as functions that EUnit should pick up.
  • {'warn_exhaustiveness', boolean()} - If set to true (the default), the compiler will print warnings regarding missed patterns in top level functions.

Errors from the compiler (e.g. type errors) are almost comically hostile to usability at the moment. See the tests in alpaca_typer.erl.


You will generally want the following two things installed:

Writing Alpaca with Rebar3

Thanks to @tsloughter's Alpaca Rebar3 plugin it's pretty easy to get up and running.

Make a new project with Rebar3 (substituting whatever project name you'd like for alpaca_example):

$ rebar3 new app alpaca_example
$ cd alpaca_example

In the rebar.config file in your project's root folder add the following (borrowed from @tsloughter's docs):

{plugins, [
    {rebar_prv_alpaca, ".*", {git, "", {branch, "master"}}}

{provider_hooks, [{post, [{compile, {alpaca, compile}}]}]}.

Now any files in the project's source folders that end with the extension .alp will be compiled and included in Rebar3's output folders (provided they type-check and compile successfully of course). For a simple module, open src/example.alp and add the following:

module example

export add/2

let add x y = x + y

The above is just what it looks like: a module named example with a function that adds two integers. You can call the function directly from the Erlang shell after compiling like this (note alpaca prepends alpaca_ to the module name, so in the erlang shell you must explicitly add this):

$ rebar3 shell
... compiler output skipped ...
1> alpaca_example:add(2, 6).

Note that calling Alpaca from Erlang won't do any type checking but if you've written a variety of Alpaca modules in your project, all their interactions with each other will be type checked and safe (provided the compile succeeds).

Compiler Hacking

If you have installed the prerequisites given above, clone this repository and run tests and dialyzer with:

rebar3 eunit
rebar3 dialyzer

There's no command line front-end for the compiler so unless you use @tsloughter's Rebar3 plugin detailed in the previous section, you will need to boot the erlang shell and then run alpaca:compile/2 to build and type-check things written in Alpaca. For example, if you wanted to compile the type import test file in the test_files folder:

rebar3 shell
1> Files = ["test_files/basic_adt.alp", "test_files/type_import.alp"].
2> alpaca:compile({files, Files}, []).

This will result in either an error or a list of tuples of the following form:

{compiled_module, ModuleName, FileName, BeamBinary}

The files will not actually be written by the compiler so the binaries described by the tuples can either be loaded directly into the running VM (see the tests in alpaca.erl) or written manually for now unless of course you're using the aforementioned rebar3 plugin/

Built-In Stuff

Most of the basic Erlang data types are supported:

  • booleans, true or false
  • atoms, :atom, :"Quoted Atom!"
  • floats, 1.0
  • integers, 1
  • strings, "A string". These are encoded as UTF-8 binaries.
  • character lists, like default Erlang strings, c"characters here"
  • lists, [1, 2, 3] or 1 :: 2 :: [3]
  • binaries, <<"์•ˆ๋…•, this is some UTF-8 text": type=utf8>>, <<1, 2, 32798: type=int, size=16, signed=false>>, etc
  • tuples, ("a", :tuple, "of arity", 4)
  • maps (basic support), e.g. #{:atom_key => "string value"}. These are statically typed as lists are (generics, parametric polymorphism).
  • records (basic support), these look a bit like OCaml and Elm records, e.g. {x=1, hello="world"} will produce a record with an x: int and hello: string field. Please see the language tour for more details.
  • pids, these are also parametric (like lists, "generics"). If you're including them in a type you can do something like type t = int | pid int for a type that covers integers and processes that receive integers.

In addition there is a unit type, expressed as ().

Note that the tuple example above is typed as a tuple of arity 4 that requires its members to have the types string, atom, string, integer in that order.

On top of that you can define ADTs, e.g.

type try 'success 'error = Ok 'success | Error 'error

And ADTs with more basic types in unions work, e.g.

type json = int | float | string | bool
          | list json
          | list (string, json)

Types start lower-case, type constructors upper-case.

Integer and float math use different symbols as in OCaml, e.g.

1 + 2      -- ok
1.0 + 2    -- type error
1.0 + 2.0  -- type error
1.0 +. 2.0 -- ok

Basic comparison functions are in place and are type checked, e.g. > and < will work both in a guard and as a function but:

1 > 2             -- ok
1 < 2.0           -- type error
"Hello" > "world" -- ok
"a" > 1           -- type error

See src/builtin_types.hrl for the included functions.

Pattern Matching

Pretty simple and straightforward for now:

let length l = match l with
    [] -> 0
  | h :: t -> 1 + (length t)

The first clause doesn't start with | since it's treated like a logical OR.

Pattern match guards in clauses essentially assert types, e.g. this will evaluate to a t_bool type:

match x with
  b, is_bool b -> b


match x with
  (i, f), is_integer i, is_float f -> :some_tuple

will type to a tuple of integer, float.

Since strings are currently compiled as UTF-8 Erlang binaries, only the first clause will ever match:

type my_binary_string_union = binary | string

match "Hello, world" with
    b, is_binary b -> b
  | s, is_string s -> s

Further, nullary type constructors are encoded as atoms and unary constructors in tuples led by atoms, e.g.

type my_list 'x = Nil | Cons ('x, my_list 'x)

Nil will become 'Nil' after compilation and Cons (1, Nil) will become {'Cons', {1, 'Nil'}}. Exercise caution with the order of your pattern match clauses accordingly.


No distinction is made syntactically between map literals and map patterns (=> vs := in Erlang), e.g

match my_map with
  #{:a_key => some_val} -> some_val

You can of course use variables to match into a map so you could write a simple get-by-key function as follows:

type my_opt 'a = Some 'a | None

let get_by_key m k =
  match m with
      #{k => v} -> Some v
    | _ -> None

Modules (The Erlang Kind)

ML-style modules aren't implemented at present. For now modules in Alpaca are the same as modules in Erlang with top-level entities including:

  • a module name (required)
  • function exports (with arity, as in Erlang)
  • type imports (e.g. use module.type)
  • type declarations (ADTs)
  • functions which can contain other functions and variables via let bindings.
  • functions are automatically curried (with some limitations)
  • simple test definitions

An example:

module try

export map/2  -- separate multiple exports with commas

-- type variables start with a single quote:
type maybe_success 'error 'ok = Error 'error | Success 'ok

-- Apply a function to a successful result or preserve an error.
let try_map e f = match e with
    Error _ -> e
  | Success ok -> Success (f ok)


Tests are expressed in an extremely bare-bones manner right now and there aren't even proper assertions available. If the compiler is invoked with options [test], the following will synthesize and export a function called add_2_and_2_test:

let add x y = x + y

test "add 2 and 2" =
  let res = add 2 2 in
  assert_equal res 4

let assert_equal x y =
  match x == y with
    | true -> :ok
    | _ -> throw (:not_equal, x, y)

Any test that throws an exception will fail so the above would work but if we replaced add/2 with add x y = x + (y + 1) we'd get a failing test. If you use the rebar3 plugin mentioned above, rebar3 eunit should run the tests you've written. There's a bug currently where the very first test run won't execute the tests but all runs after will (not sure why yet).

The expression that makes up a test's body is type inferenced and checked. Type errors in a test will always cause a compilation error.


An example:

let f x = receive with
  (y, sender) ->
    let z = x + y in
    let sent = send z sender in
  f z

let start_f init = spawn f init

All of the above is type checked, including the spawn and message sends. Any expression that contains a receive block becomes a "receiver" with an associated type. The type inferred for f above is the following:

  {t_tuple, [t_int, {t_pid, t_int}]},
  {t_arrow, [t_int], t_rec}}

This means that:

  • f has it's own function type (the t_arrow part) but it also contains one or more receive calls that handle tuples of integers and PIDs that receive integers themselves.
  • f's function type is one that takes integers and is infinitely recursive.

send returns unit but there's no "do" notation/side effect support at the moment hence the let binding. spawn for the moment can only start functions defined in the module it's called within to simplify some cross-module lookup stuff for the time being. I intend to support spawning functions in other modules fairly soon.

Note that the following will yield a type error:

let a x = receive with
  i -> b x + i

let b x = receive with
  f -> a x +. i

This is because b is a t_float receiver while a is a t_int receiver. Adding a union type like type t = int | float will solve the type error.

If you spawn a function which nowhere in its call graph posesses a receive block, the pid will be typed as undefined, which means all message sends to that process will be a type error.

Current FFI

The FFI is quite limited at present and operates as follows:

beam :a_module :a_function [3, "different", "arguments"] with
    (ok, _) -> :ok
  | (error, _) -> :error

There's clearly room to provide a version that skips the pattern match and succeeds if dialyzer supplies a return type for the function that matches a type in scope (union or otherwise). Worth noting that the FFI assumes you know what you're doing and does not check that the module and function you're calling exist.


Compiler error messages may be localized by calling alpaca_error_format:fmt/2. If no translation is available in the specified locale, the translation for en_US will be used.

Localization is performed using gettext ".po" files stored in priv/lang. To add a new language, say Swedish (sv_SE), create a new file priv/lang/alpaca.sv_SE.po. If you use Poedit, you may then import all messages to be translated by selecting "Catalog -> Update from POT file..." in the menu, and then pick priv/lang/alpaca.pot. The messages may be a bit cryptic. Use the en_US as an aid to understand them.

The POT file is automatically updated whenever alpaca is compiled. Updates to po-files are also picked up at the compile phase.


What's Missing

A very incomplete list:

  • self() - it's a little tricky to type. The type-safe solution is to spawn a process and then send it its own pid. Still thinking about how to do this better.
  • exception handling (try/catch)
  • any sort of standard library. Biggest missing things right now are things like basic string manipulation functions and adapters for gen_server, etc.
  • anything like behaviours or things that would support them. Traits, type classes, ML modules, etc all smell like supersets but we don't have a definite direction yet.
  • simpler FFI, there's an open issue for discussion: #7
  • annotations in the BEAM file output (source line numbers, etc). Not hard based on what can be seen in the LFE code base.
  • support for typing anything other than a raw source file.
  • side effects, like using ; in OCaml for printing in a function with a non-unit result.

Implementation Issues

This has been a process of learning-while-doing so there are a number of issues with the code, including but not limited to:

  • there's a lot of cruft around error handling that should all be refactored into some sort of basic monad-like thing. This is extremely evident in alpaca_ast_gen.erl and alpaca_typer.erl. Frankly the latter is begging for a complete rewrite.
  • type unification error line numbers can be confusing. Because of the sequence of unification steps, sometimes the unification error might occur at a function variable's location or in a match expression rather than in the clauses. I'm considering tracking the history of changes over the course of unifications in a reference cell in order to provide a typing trace to the user.
  • generalization of type variables is incompletely applied.

Parsing Approach

Parsing/validating occurs in several passes:

  1. yecc for the initial rough syntax form and basic module structure. This is where exports and top-level function definitions are collected and the initial construction of the AST is completed.
  2. Validating function definitions and bindings inside of them. This stage uses environments to track whether a function application is referring to a known function or a variable. The output of this stage is either a module definition or a list of errors found. This stage also renames variables internally.
  3. Type checking. This has some awkward overlaps with the environments built in the previous step and may benefit from some interleaving at some point. An argument against this mixing might be that having all functions defined before type checking does permit forward references.

AST Construction

Several passes internally

  • for each source file (module), validate function definitions and report syntax errors, e.g. params that are neither unit nor variable bindings (so-called "symbols" from the yecc parser), building a list of top-level internal-only and exported functions for each module. The output of this is a global environment containing all exported functions by module and an environment of top-level functions per module or a list of found errors.
  • for each function defined in each module, check that every variable and function reference is valid. For function applications, arity is checked where the function applied is not in a variable.

Type Inferencing and Checking

At present this is based off of the sound and eager type inferencer in with some influence from where the arrow type and type schema instantiation are concerned.

Single Module Typing

module example

export add/2

let add x y = adder x y

let adder x y = x + y

The forward reference in add/2 is permitted but currently leads to some wasted work. When typing add/2 the typer encounters a reference to adder/2 that is not yet bound in its environment but is available in the module's definition. The typer will look ahead in the module's definition to determine the type of adder/2, use it to type add/2, and then throw that work away before proceeding to type adder/2 again. It may be beneficial to leverage something like ETS here in the near term.


Infinitely recursive functions are typed as such and permitted as they're necessary for processes that loop on receive. Bi-directional calls between modules are disallowed for simplicity. This means that given module A and B, calls can occur from functions in A to those in B or the opposite but not in both directions.

I think this is generally pretty reasonable as bidirectional references probably indicate a failure to separate concerns but it has the additional benefit of bounding how complicated inferencing a set of mutually recursive functions can get. The case I'm particularly concerned with can be illustrated with the following Module.function examples:

let A.x = B.y ()
let B.y = C.z ()
let C.z = A.x ()

This loop, while I belive possible to check, necessitates either a great deal of state tracking complexity or an enormous amount of wasted work and likely has some nasty corner cases I'm as yet unaware of.

The mechanism for preventing this is simple and relatively naive to start: entering a module during type inferencing/checking adds that module to the list of modules encountered in this pass. When a call occurs (a function application that crosses module boundaries), we check to see if the referenced module is already in the list of entered modules. If so, type checking fails with an error.

No "Any" Type

There is currently no "any" root/bottom type. This is going to be a problem for something like a simple println/printf function as a simple to use version of this would best take a List of Any. The FFI to Erlang code gets around this by not type checking the arguments passed to it and only checking the result portion of the pattern matches.