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Design of the monoidal category classes and the new Arrow/proc desugaring story

What are monoidal categories and why are they useful?

Monoidal (and related) categories capture the basic notion of process. This is most easily noticed by recognising a tool for using monoidal categories called string diagrams. Examples of string diagrams include circuit diagrams, flow charts, signal flow diagrams, Feynman diagrams, proof nets, etc. In that way, monoidal categories are like Arrows (indeed, every Arrow is a monoidal category with an additional structure which allows reification of functions, and application of one input to another) - except much more general. For example, Megacz's work on Generalized Arrows can be entirely subsumed by monoidal categories (indeed, I even based the initial design off of parts of his thesis)


The new class hierarchy is based on monoidal categories, and monoidal categories with additional structure. What is a monoidal category? From ncatlab:

⊗:M×M→MBifunctor called the tensor product
1::MAn object called the unit
ax,y,z:(x⊗y)⊗z→x⊗(y⊗z)The tensor product is associative both ways (isomorphism)
λx:1⊗x→xAn elimination and introduction rule for removing the left unit from a tensor (isomorphism)
ρx:x⊗1→xAn elimination and introduction rule for removing the right unit from a tensor (isomorphism)

It also obeys two laws known as the Pentagon equation and the Triangle equation.


  1. Write monoidal category class heirarchy in GHC.Arrows.Experimental and provide instances for Arrow and several other basic types, and visa versa; make SMC instances for Arrows
  2. Convert or write a small FRP library to be based on the new classes to test the design
  3. Provide optimisation RULES pragmas as much as possible; for example, the work on Causal Commutative Arrows can be converted relatively straightforwardly to plain monoidal categories
  4. Convert the proc/arrow desugarer in GHC to emit instances of the new classes; since all Arrows are monoidal categories, this change will be backwards compatible with user code - use
  5. Change GHC.Arrows.Experimental to GHC.MonoidalCats before the milestone it is merged for

I will be updating this page to document/brainstorm the design as I go along.

Current challenges

How to implement the unit/counit morphisms from compact closed categories? That is, how to implement a morphism unit :: I -> A*⊗A and A⊗A* -> I? I can see several options:

  1. In terms of closures + choice

-- Have an intermediate closure object, with two inputs and two outputs - send a "switch" signal (so this would require a choice class as well as a closure class) to tell which input is active, and then pass it through for one of the outputs and compute the appropriate dual for the other output.

  1. In terms of bidirectional signal flow

-- Similar to the above but instead of a switch, a bidirectional wire - if you put in the object A, you get A* (or *A depending on weather left or right autonomous), and if you put in A* (*A) you get A.

  1. One of the above in combination with a source/sink object

Desugaring plans

Current (arrows):

    proc p -> f -< e = arr (\ p -> e) >>> f           if Vars(f) and Vars(p) disjoint
                     = arr (\ p -> (f, e)) >>> app    otherwise

    proc p -> \ p1 ... pn -> c = proc (...(p, p1), ... pn) -> c

    proc p -> form e c1 ... cn =
        e (proc p -> c1) ... (proc p -> cn)

    proc p -> let decls in c =
        arr (\ p -> let decls in (p,p')) >>>          Vars(p') = Defvars(decls)
	(proc (p,p') -> c)

    proc p -> if e then c1 else c2 =
        arr (\ p -> if e then Left p else Right p) >>>
        (proc p -> c1) ||| (proc p -> c2)

    proc p -> case e of { p1 -> c1 ; ... ; pn -> cn } =
        arr (\ p ->
             case e of
             p1 -> Left (p, Flatten(p1))
             pn-1 -> Rightn-2 (Left (p, Flatten(pn-1)))
             pn -> Rightn-1 (p, Flatten(pn))) >>>
        (proc (p, Flatten(p1)) -> c1) ||| ... ||| (proc (p, Flatten(pn)) -> cn)

New (SMC) (wip, these need to be as generalised as possible; look at GA thesis and

Last modified 3 years ago Last modified on Sep 19, 2014 8:21:22 AM