So far, we've defined monads as single-layered boxes. Though in the Groenendijk, Stokhof, and Veltman homework, we had to figure out how to combine Reader, State, and Set monads in an ad-hoc way. In practice, one often wants to combine the abilities of several monads. Corresponding to each monad like Reader, there's a corresponding ReaderT monad transformer. That takes an existing monad M and wraps Readerish monad packaging around it. The way these are defined parallels the way the single-layer versions are defined. For example, here's the Reader monad:

(* monadic operations for the Reader monad *)

env -> 'a;;
let unit (a : 'a) : 'a reader =
fun e -> a;;
fun e -> (fun a -> f a e) (u e);;


We've just beta-expanded the familiar f (u e) e into (fun a -> f a e) (u e). We did that so as to factor out the parts where any Reader monad is being supplied as an argument to another function. That will help make some patterns that are coming up more salient.

Well, one way to proceed would be to just let values of the other monad M be the 'a in your 'a reader. Then you could apply reader_bind to get at the wrapped 'a M, and then apply M.bind to get at its wrapped 'a. This sometimes works. It's what we did in the hints to GSV assignment, where as we said, we "combined State and Set in an ad hoc way."

But there are two problems: (1) It's cumbersome having to work with both reader_bind and M.bind. It'd be nice to figure out some systematic way to connect the plumbing of the different monadic layers, so that we could have a single bind that took our 'a M_inside_Reader, and sequenced it with a single 'a -> 'b M_inside_Reader function. Similarly for unit. This is what the ReaderT monad transformer will let us do.

(2) For some combinations of monads, the best way to implement a Tish monadic wrapper around an inner M monad won't be equivalent to either an ('a m) t or an ('a t) m. It will be a tighter intermingling of the two. So some natural activities will remain out of reach until we equip ourselves to go beyond ('a m) ts and so on.

What we want in general are monadic transformers. For example, a ReaderT transformer will be parameterized not just on the type of its innermost contents 'a, but also on the monadic box M that wraps 'a. It will make use of monad M's existing operations M.unit and M.bind, together with the Reader patterns for unit and bind, to define a new monad ReaderT(M) that fuses the behavior of Reader and M.

Here's how it's implemented:

(* monadic operations for the ReaderT monadic transformer *)

(* We're not giving valid OCaml code, but rather something
* that's conceptually easier to digest.
* How you really need to write this in OCaml is more circuitous...
* for some details. *)

env -> 'a M;;
(* this _happens_ also to be the type of an ('a M) reader
* but as we noted, you can't rely on that pattern always to hold *)

let unit (a : 'a) : 'a readerT(M) =
fun e -> M.unit a;;

fun e -> M.bind (u e) (fun a -> f a e);;


Notice the key differences: where before unit was implemented by a function that just returned a, now we instead return M.unit a. Where before bind just supplied value u e of type 'a reader as an argument to a function, now we instead M.bind the corresponding value to the function. Notice also the differences in the types.

type 'a identity = 'a;;
let unit (a : 'a) : 'a = a;;
let bind (u : 'a) (f : 'a -> 'b) : 'b = f u;;


and you used the ReaderT transformer to wrap the Identity monad inside Readerish packaging. What do you suppose you would get?

The relations between the State monad and the StateT monadic transformer are parallel:

(* monadic operations for the State monad *)

type 'a state =
store -> ('a * store);;

let unit (a : 'a) : 'a state =
fun s -> (a, s);;

let bind (u : 'a state) (f : 'a -> 'b state) : 'b state =
fun s -> (fun (a, s') -> f a s') (u s);;


We've used (fun (a, s') -> f a s') (u s) instead of the more familiar let (a, s') = u s in f a s' in order to factor out the part where a value of type 'a state is supplied as an argument to a function. Now StateT will be:

(* monadic operations for the StateT monadic transformer *)

type 'a stateT(M) =
store -> ('a * store) M;;
(* notice this is not an ('a M) state *)

let unit (a : 'a) : 'a stateT(M) =
fun s -> M.unit (a, s);;

let bind (u : 'a stateT(M)) (f : 'a -> 'b stateT(M)) : 'b stateT(M) =
fun s -> M.bind (u s) (fun (a, s') -> f a s');;


Do you see the pattern? Where before unit was implemented by a function that returned an 'a * store value, now we instead use M.unit to return an ('a * store) M value. Where before bind supplied an 'a state value (u s) as an argument to a function, now we instead M.bind it to that function.

Once again, what do you think you'd get if you wrapped StateT monadic packaging around an Identity monad?

We spell out all the common monads, their common dedicated operations (such as lookup- and shift-like operations for the Reader monad), and monad transformer cousins of all of these, in an OCaml monad library. Read the linked page for details about how to use the library, and some design choices we made. Our State Monad Tutorial gives some more examples of using the library.

When a T monadic layer encloses an inner M monad, the T's interface is the most exposed one. To use operations defined in the inner M monad, you'll have to "elevate" them into the outer T packaging. Haskell calls this operation lift, but we call it elevate because the term "lift" is already now too overloaded. In our usage, lift (and lift2) are functions that bring non-monadic operations into a monad; elevate brings monadic operations from a wrapped monad out into the wrapping.

Here's an example. Suppose S is an instance of a State monad:

# #use "path/to/monads.ml";;
# module S = State_monad(struct type store = int end);;


and MS is a MaybeT wrapped around S:

# module MS = Maybe_monad.T(S);;


Then if you want to use an S-specific monad like puts succ inside MS, you'll have to use MS's elevate function, like this:

# MS.(...elevate (S.puts succ) ...)


Each monad transformer's elevate function will be defined differently. They have to obey the following laws:

• Outer.elevate (Inner.unit a) <~~> Outer.unit a
• Outer.elevate (Inner.bind u f) <~~> Outer.bind (Outer.elevate u) (fun a -> Outer.elevate (f a))

We said that when T encloses M, you can rely on T's interface to be most exposed. That is intuitive. What you cannot also assume is that the implementing type has a Tish structure surrounding an Mish structure. Often it will be reverse: a ListT(Maybe) is implemented by a 'a list option, not by an 'a option list. Until you've tried to write the code to a monadic transformer library yourself, this will probably remain counter-intuitive. But you don't need to concern yourself with it in practise. Think of what you have as a ListT(Maybe); don't worry about whether the underlying implementation is as an 'a list option or an 'a option list or as something more complicated.

Notice from the code for StateT, above, that an 'a stateT(M) is not an ('a M) state; neither is it an ('a state) M. The pattern by which we transform the types from a Blah monad to a BlahT monad transformer is:

't0                  --->  't0 M
't1 -> 't0           --->  't1 -> 't0 M
('t1 -> 't0) -> 't0  --->  ('t1 -> 't0 M) -> 't0 M


Ken Shan's paper Monads for natural language semantics (2001) discusses how to systematically move from some base monads to the corresponding monad transformers. But as he notes, his algorithm isn't the only one possible, and it only applies to monads whose type has a certain form. (Reader and State have that form; List for example doesn't.)

As best we know, figuring out how a monad transformer should be defined is still something of an art, not something that can be done mechanically. However, you can think that all of the art goes into deciding what StateT and so on should be; having figured that out, plain State would follow as the simple case where StateT is parameterized on the Identity monad.

Apart from whose interface is outermost, the behavior of a StateT(Maybe) and a MaybeT(State) will partly coincide. But in certain crucial respects they will diverge, and you need to think carefully about which behavior you want and what the appropriate layering is for your needs. Consider these examples:

# module MS = Maybe_monad.T(S);;
# MS.(run (elevate (S.puts succ) >> zero () >> elevate S.get >>= fun cur -> unit (cur+10) )) 0;;
- : int option * S.store = (None, 1)
# MS.(run (elevate (S.puts succ) >> zero () >> elevate (S.put 5) )) 0;;
- : unit option * S.store = (None, 1)


Although we have a wrapped None, notice that the store (as it was at the point of failure) is still retrievable.

# SM.(run (puts succ >> elevate (Maybe_monad.zero ()) >> get >>= fun cur -> unit (cur+10) )) 0;;
- : ('a, int * S.store) Maybe_monad.result = None


When Maybe is on the inside, on the other hand, a failure means the whole computation has failed, and even the store is no longer available.

Here's an example wrapping Maybe around List, and vice versa:

# module LM = List_monad.T(Maybe_monad);;
# ML.(run (plus (zero ()) (unit 20) >>= fun i -> unit (i+10)));;
- : ('_a, int) ML.result = [Some 30]


When List is on the inside, the failed results just get dropped and the computation proceeds without them.

# LM.(run (plus (elevate (Maybe_monad.zero ())) (unit 20) >>= fun i -> unit (i+10)));;
- : ('_a, int) LM.result = None


On the other hand, when Maybe is on the inside, failures abort the whole computation.

This is fun. Notice the difference it makes whether the second plus is native to the outer List_monad, or whether it's the inner List_monad's plus elevated into the outer wrapper:

# module LL = List_monad.T(List_monad);;

# LL.(run(plus (unit 1) (unit 2) >>= fun i -> plus (unit i) (unit(10*i)) ));;
- : ('_a, int) LL.result = [[1; 10; 2; 20]]
# LL.(run(plus (unit 1) (unit 2) >>= fun i -> elevate L.(plus (unit i) (unit(10*i)) )));;
- : ('_a, int) LL.result = [[1; 2]; [1; 20]; [10; 2]; [10; 20]]


Our monad library includes a Tree_monad, for binary, leaf-labeled trees. There are other kinds of trees you might want to monadize, but we took the name Tree_monad for this one. Like the Haskell SearchTree monad, our Tree_monad also incorporates an Optionish layer. (See the comments in our library code about plus and zero for discussion of why.)

So how does our Tree_monad behave? Simplified, its implementation looks something like this:

(* monadic operations for the Tree monad *)

type 'a tree =
Leaf of 'a | Node of ('a tree) * ('a tree);;

let unit (a: 'a) : 'a tree =
Leaf a;;

let rec bind (u : 'a tree) (f : 'a -> 'b tree) : 'b tree =
match u with
| Leaf a -> f a;;
| Node (l, r) ->
let l' = bind l f in
let r' = bind r f in
Node (l', r')


Recall how bind works for the List monad. If you have a list:

let u = [1; 2; 4; 8];;


and a function f such that:

f 1 ~~> []
f 2 ~~> [2]
f 4 ~~> [2; 4]
f 8 ~~> [2; 4; 8]


then list_bind u f would be concat [[]; [2]; [2; 4]; [2; 4; 8]], that is [2; 2; 4; 2; 4; 8]. It splices the lists returned by f into the corresponding positions in the original list structure. The tree_bind operation works the same way. If f' maps 2 to the tree Leaf 2 and 8 to the tree Node (Leaf 2, Node (Leaf 4, Leaf 8)), then binding the tree u to f' will splice the trees returned by f' to the corresponding positions in the original structure:

 u
.                    .
_|__  >>=  f' ~~>    _|__
|  |                 |  |
2  8                 2  .
_|__
|  |
2  .
_|__
|  |
4  8


Except, as we mentioned, our implementation of the Tree monad incorporates an Optionish layer too. So f' 2 should be not Leaf 2 but Some (Leaf 2). What if f' also mapped 1 to None and 4 to Some (Node (Leaf 2, Leaf 4)). Then binding the tree Node (Leaf 1, Node (Leaf 2, Leaf 4)) (really the tree itself needs to be wrapped in a Some, too, but let me neglect that) to f' would delete the branch corresponding to the original Leaf 1, and would splice in the results for f' 2 and f' 4, yielding:

 .
_|__  >>=  f' ~~>
|  |
1  .                    .
_|__                 _|__
|  |                 |  |
2  4                 2  .
_|__
|  |
2  4


As always, the functions you bind an 'a tree to need not map 'as to 'a trees; they can map them to 'b trees instead. For instance, we could transform Node (Leaf 1, Node (Leaf 2, Leaf 4)) instead into Node (Leaf "two", Node (Leaf "two", Leaf "four")).

As we mention in the notes, our monad library encapsulates the implementation of its monadic types. So to work with it you have to use the primitives it provides. You can't say:

# Tree_monad.(orig_tree >>= fun a -> match a with
| 4 -> Some (Node (Leaf 2, Leaf 4))
| _ -> None);;
Error: This expression has type int Tree_monad.tree option
but an expression was expected of type ('a, 'b) Tree_monad.m


You have to instead say something like this:

# Tree_monad.(orig_tree >>= fun a -> match a with
| 4 -> plus (unit 2) (unit 4)
| _ -> zero () );;
- : ('_a, int) Tree_monad.m = <abstr>


## How is all this related to our tree_monadize function?

Our Tree monad has a corresponding TreeT transformer. Simplified, its implementation looks something like this (we apply it to an inner Reader monad):

type 'a tree_reader = 'a tree reader;;
(* really it's an 'a tree option reader, but as I said we're simplifying *)

let rec loop us = match us with
| Leaf a ->
f a
| Node(l,r) ->
reader_bind (loop l) (fun ls ->
reader_bind (loop r) (fun rs ->
in loop us);;



Recall our earlier definition of tree_monadize, specialized for the Reader monad:

let rec tree_monadize (f : 'a -> 'b reader) (t : 'a tree) : 'b tree reader =
match t with
| Leaf a ->
(* the next line is equivalent to: tree_reader_elevate (f a) *)
| Node (l, r) ->


We rendered the result type here as 'b tree reader, as we did in our earlier discussion, but as we can see from the above implementation of TreeT(Reader), that's the type of an 'b tree_reader, that is, of a layered box consisting of TreeT packaging wrapped around an inner Reader box.

The definitions of tree_monadize and tree_reader_bind should look very similar. They're not quite the same. There's the difference in the order of their function-like and tree-like arguments, but that's inconsequential. More important is that the types of their arguments differs. tree_reader_bind wants a tree that's already fused with a reader; tree_monadize instead just wants a plain tree. tree_reader_bind wants a function that takes the elements occupying its leaves into other tree_readers; tree_monadize just wants it to take them into plain readers. That's why the application of f to a has to be elevated in the tree_monadize clause for Leaf a -> ....

But there is an obvious common structure to these two functions, and indeed in the monad library their more complicated cousins are defined in terms of common pieces. In the monad library, the tree_monadize function is called distribute; this is an operation living inside the TreeT packaging. There's an analogous distribute function living inside the ListT packaging. (Haskell has the second but not the first; it calls it mapM and it lives inside the wrapped base monad, instead of the List packaging.)

We linked to some code earlier that demonstrated all the tree_monadize examples in a compact way.

Here's how to demonstrate the same examples, using the monad library. First, preliminaries:

# #use "path/to/monads.ml";;
# module R = Reader_monad(struct type env = int -> int end);;
# module S = State_monad(struct type store = int end);;
# module TR = T.T(R);;
# module TS = T.T(S);;
# module TL = T.T(L);;
# module TC = T.T(C);;
# let t1 = Some (T.Node (T.Node (T.Leaf 2, T.Leaf 3), T.Node (T.Leaf 5, T.Node (T.Leaf 7, T.Leaf 11))));;


We can use TreeT(Reader) to modify leaves:

# let tree_reader = TR.distribute (fun i -> R.asks (fun e -> e i)) t1;;
# TR.run tree_reader (fun i -> i+i);;
- : int T.tree option =
Some
(T.Node
(T.Node (T.Leaf 4, T.Leaf 6),
T.Node (T.Leaf 10, T.Node (T.Leaf 14, T.Leaf 22))))


Here's a comparison of how distribute works for trees and how it works for lists:

# module LR = L.T(R);;
# let l1 = [2; 3; 5; 7; 11];;
# LR.(run (distribute (fun i -> R.(asks (fun e -> e i))) l1)) (fun i -> i+i);;
- : int list = [4; 6; 10; 14; 22]


We can use TreeT(State) to count leaves:

# let tree_counter = TS.distribute (fun i -> S.(puts succ >> unit i)) t1 in
TS.run tree_counter 0;;
- : int T.tree option * S.store =
(Some
(T.Node
(T.Node (T.Leaf 2, T.Leaf 3),
T.Node (T.Leaf 5, T.Node (T.Leaf 7, T.Leaf 11)))),
5)


or to annotate leaves:

# let tree_annotater = TS.distribute (fun i -> S.(puts succ >> get >>= fun s -> unit (i,s))) t1 in
TS.run tree_annotater 0;;
- : (int * S.store) T.tree option * S.store =
(Some
(T.Node
(T.Node (T.Leaf (2, 1), T.Leaf (3, 2)),
T.Node (T.Leaf (5, 3), T.Node (T.Leaf (7, 4), T.Leaf (11, 5))))),
5)


Here's a comparison of how distribute works for trees and how it works for lists:

# module LS = L.T(S);;

# let list_counter = LS.distribute (fun i -> S.(puts succ >> unit i)) l1 in
LS.run list_counter 0;;
- : int list * S.store = ([2; 3; 5; 7; 11], 5)

# let list_annotater = LS.distribute (fun i -> S.(puts succ >> get >>= fun s -> unit (i,s) )) l1 in
LS.run list_annotater 0;;
- : (int * S.store) list * S.store =
([(2, 1); (3, 2); (5, 3); (7, 4); (11, 5)], 5)


We can use TreeT(List) to copy the tree with different choices for some of the leaves:

# let tree_chooser = TL.distribute (fun i -> L.(if i = 2 then plus (unit 20) (unit 21) else unit i)) t1;;
# TL.run tree_chooser;;
- : ('_a, int) TL.result =
[Some
(T.Node
(T.Node (T.Leaf 20, T.Leaf 3),
T.Node (T.Leaf 5, T.Node (T.Leaf 7, T.Leaf 11))));
Some
(T.Node
(T.Node (T.Leaf 21, T.Leaf 3),
T.Node (T.Leaf 5, T.Node (T.Leaf 7, T.Leaf 11))))]


Finally, we use TreeT(Continuation) to do various things. For reasons I won't explain here, the library currently requires you to run the Tree-plus-Continuation bundle using a different sequence of run commands:

We can do nothing:

# C.run_exn TC.(run (distribute C.unit t1)) (fun t -> t);;
- : int T.tree option =
Some
(T.Node
(T.Node (T.Leaf 2, T.Leaf 3),
T.Node (T.Leaf 5, T.Node (T.Leaf 7, T.Leaf 11))))


We can square each leaf:

# C.run_exn TC.(run (distribute C.(fun a -> shift (fun k -> k (a*a))) t1)) (fun t -> t);;
- : int T.tree option =
Some
(T.Node
(T.Node (T.Leaf 4, T.Leaf 9),
T.Node (T.Leaf 25, T.Node (T.Leaf 49, T.Leaf 121))))


The meaning of shift will be explained in CPS and Continuation Operators. Here you should just regard it as a primitive operation in our Continuation monad. In this code you could simply write:

TreeCont.monadize (fun a -> fun k -> k (a*a)) t1 (fun t -> t);;


But because of the way our monad library hides the underlying machinery, here you can no longer just say fun k -> k (a*a); you have to say shift (fun k -> k (a*a)).

Moving on, we can count the leaves:

# C.run_exn TC.(run (distribute C.(fun a -> shift (fun k -> k a >>= fun v -> unit (1+v))) t1)) (fun t -> 0);;
- : int = 5


And we can convert the tree to a list of leaves:

# C.run_exn TC.(run (distribute C.(fun a -> shift (fun k -> k a >>= fun v -> unit (a::v))) t1)) (fun t -> []);;
- : int list = [2; 3; 5; 7; 11]