Welcome to ExtensibleEffects.jl. This package provides an implementation of Extensible Effects. We follow the approach presented in the paper Freer Monads, More Extensible Effects which already has an Haskell implementation as well as a Scala implementation.

This Julia implementation is massively simplified, and hence can also serve as a good introduction to get to know the details behind Extensible Effects.

Many effects are provided, ranging from Option, which can be handled very simple, to the very limit of what can be supported by ExtensibleEffects - the State effect. Still, all the implementations are short and easy to follow, so look into the instances.jl file to see how to write your own Effect handlings.


using Pkg
pkg"add ExtensibleEffects"

Use it like

using ExtensibleEffects


The power of ExtensibleEffects.jl is to combine multiple different contexts into one composable super context abstraction. Its key macro is

@syntax_eff begin
  a = an_effect
  b = another_effect
  @pure a, b

which provides a syntax similar to TypeClasses.@syntax_flatmap for working seamlessly with effects. See its documentation @syntax_eff for more details.

There is another version of the key macro called @syntax_eff_noautorun, which as the name indicates disables the autorun feature of @syntax_eff. You may need this in case you don't want to execute your effects immediately, but staying in the meta-monad ExtensibleEffects.Eff for further composition with other effectful algorithms. Effects and How does it actually work? also provide some examples of using @syntax_eff_noautorun for explanation purposes.

You can also specifically disable the autorun feature for individual effects only by using the noautorun function like

@syntax_eff noautorun(Vector) begin

which in this case would not handle the Vector effect.

In addition to @syntax_eff, @syntax_eff_noautorun and @syntax_eff noautorun(effect1, effect2, ...) the package reexports all data types from DataTypesBasic.jl and TypeClasses.jl

For the more complicated effects Writer, Callable, ContextManager and State extra handlers and further helper macros are provided. Take a look at Example and Effects for further details.


To start small, you can use ExtensibleEffects.@syntax_eff instead of TypeClasses.@syntax_flatmap.

julia> @syntax_eff begin
         a = [1, 2]
         b = ["one", "two"]
         @pure a, b
4-element Vector{Tuple{Int64, String}}:
 (1, "one")
 (1, "two")
 (2, "one")
 (2, "two")

julia> option_example(n) = @syntax_eff begin
         a = Option(n)
         b = @Try isodd(a) ? error("fail") : a+1
         @pure a, b
option_example (generic function with 1 method)

julia> option_example(nothing)

julia> option_example(41)

julia> option_example(42)
Identity((42, 43))

Some monads of TypeClasses need a bit more work to translate them into effects. They need little extra wrappers, but nothing fancy, just use their respective @run... macro.

Let's directly jump to super complicated interactions of many effects at once. Please experiment with this little example. Take effects out, reorder them, etc.

julia> # simple ContextManager for example purposes
       create_context(x) = @ContextManager continuation -> begin
         println("before $x")
         result = continuation(x)
         println("after $x")
create_context (generic function with 1 method)

julia> contextmanager_callable_state = @runcontextmanager @runcallable @runstate @syntax_eff begin
         co = create_context(4)
         ve = collect(1:co)
         st = State(s -> (ve+s, 2s))
         op = isodd(st) ? Option(100) : Option()
         ca = Callable(x -> "x = $x, st = $st, op = $op")
         @pure [co, ve, st, op, ca]

julia> # running the contextmanager
       result, nextstate = run(contextmanager_callable_state) do value
         @show value  
       end |>
       # calling the callable
       callable_state -> callable_state("hello") |>
       # providing initial state for the state
       state -> run(state, 11);
before 4
value = (Option{Vector{Any}}[Const(nothing), Const(nothing), Identity(Any[4, 3, 47, 100, "x = hello, st = 47, op = 100"]), Const(nothing)], 176)
after 4

julia> result
4-element Vector{Option{Vector{Any}}}:
 Identity(Any[4, 3, 47, 100, "x = hello, st = 47, op = 100"])

julia> nextstate

Welcome to fully composable effects. Effects and How does it actually work? can provide you more details.

Core Interface eff_applies, eff_pure, eff_flatmap

All effects and effect handlers need to overwrite the three core functions. We specify them by using Vector as an example:

core functiondefaultdescription
eff_applies(handler::Type{<:Vector}, effectful::Vector) = truethere is no defaultspecify on which values the handler applies (the handler Vector applies to Vector of course)
eff_pure(handler::Type{<:Vector}, value) = [value]defaulting to TypeClasses.pure (enough for Vector)wrap a plain value into the Monad of the handler, here Vector.
eff_flatmap(continuation, effectful::Vector)defaults to using map, flatmap, and flip_types from TypeClasses (this is enough for Vector)apply a continuation to the current effect (here again Vector as an example). The key difference to plainTypeClasses.flatmap is that continuation does not return a plain Vector, but a Eff{Vector}. Applying this continuation with a plain map would lead Vector{Eff{Vector}}. However, eff_flatmap needs to return an Eff{Vector} instead.

Future Work

Julia's type-inference seems to have quite some trouble inferring through the core algorithms of ExtensibleEffects. Hence in case type-inference and speed is crucial to your effectful/monadic code, we recommend to use TypeClasses.jl as of now. The monads of TypeClasses.jl do not compose that well as the effects in ExtensibleEffects.jl, but type-inference is much simpler.