In Local Capabilities with MTL we seen how to localise or delegate capabilities, such as error handling. This is a follow up to address some of the shortcomings of the approach when a project scales, to explain why people continue to explore alternatives to MTL and why many Haskell developers do not consider application design to be a solved problem. The supporting source code is available in the ffunctor tests.

I should point out that despite these shortcomings, I consider MTL (with records of functions) to be the best way I’ve seen yet to design reliable and maintainable applications, in any programming language.

Let’s say we have an application that can be modularised into several capabilities:

a Logger , for writing out text messages an Http client, for talking to a webserver a Database client, for persisting state a Tracer , for distributed performance monitoring

We could encode these capabilities as typeclasses but to have fine control over which implementation is used in a given situation we are going to use records of functions.

The first 3 are fairly straightforward and may look like:

data Logger m = Logger { debug :: String -> m () , info :: String -> m () , warning :: String -> m () } data Http m = Http { getUsers :: m [String] , postUser :: String -> m () } data Database m = Database { dbHistory :: m [String] , dbAdd :: String -> m () }

The idea behind Tracing is that a server (e.g. Jaeger) receives a message when opt-in computations begin and end across services in a distributed system. Tracing is useful for operations monitoring and performance profiling.

A “trace” is a tree of spans that each contain a start time, an end time, and a name, e.g.

Spans typically have a lot of metadata associated to them but we’ll keep it simple for this example:

data OpenSpan = OpenSpan { spanStart :: UTCTime -- ^ when the span begins , spanName :: String -- ^ user provided , spanId :: Int -- ^ randomly generated , spanParent :: Maybe Int -- ^ the id of the span that caused this }

We can implement the Tracer capability with two low-level operations: creating a new span, and sending the current span to the tracing server, i.e. closing the span:

data Tracer m = Tracer { openSpan :: (Maybe Int) -- ^ id of the parent span -> String -- ^ the name of this span -> m OpenSpan -- ^ the new span , closeSpan :: OpenSpan -> m () }

Tracer isn’t a very practical API to use directly, so we introduce a more convenient function that can handle errors with MonadMask. Before we do that, it is useful to introduce an alias for the ability to read the currently open span, and bracket any errors:

type MonadTraced m = (MonadReader OpenSpan m, MonadMask m)

We can implement tracing very naturally with MonadReader.local and MonadMask.finally, giving a nice API. Use like (tracer & span) "foo" doFoo

span :: MonadTraced m => Tracer m -> String -> m a -> m a span tracer name ma = do OpenSpan{spanId} <- ask child <- (tracer & openSpan) (Just spanId) name local (const child) $ ma `finally` ((tracer & closeSpan) child)

ASIDE: we are using the operator & which just flips the order of its two parameters. (tracer & openSpan) is the same as (openSpan tracer) but gives a visual indication that the openSpan function comes from the tracer record of functions.

Following the pattern from the previous letter, it is useful to be able to declare a requirement with a monad transformer, for situations where we can’t change the constraints

type Traced = ReaderT OpenSpan

An immediate usecase is that we need a way to create “root spans” that don’t have a parent and therefore do not require a MonadReader, e.g. (tracer & rootSpan) "foo" doFoo

rootSpan :: MonadMask m => Tracer m -> String -> (Traced m) a -> m a rootSpan tracer name ma = do child <- (tracer & openSpan) Nothing name (runReaderT ma child) `finally` ((tracer & closeSpan) child)

So far, this is a great application of MTL. But this letter is about when MTL starts to get in the way so let’s see how that can happen… say we have some business logic that grabs the users from the HTTP client and adds everything to the database.

Because we are abstracting over m this will work for anything, whether it is traced, untraced, or a dummy implementation for testing.

doStuff :: Monad m => Http m -> Database m -> m () doStuff http db = do users <- (http & getUsers) void $ traverse (db & dbAdd) users

But what if we only have implementations of Http (Traced m) and Database m ? This might be because our implementation of Http must pass a span’s id via a header, which is very standard. Our database doesn’t have support for tracing ids because the SQL standard doesn’t support it.

data HttpConfig = HttpConfig -- ... mkHttp :: (MonadIO m, MonadTraced m, MonadIO n) => HttpConfig -> n (Http m) mkHttp = undefined data DatabaseConfig = DatabaseConfig -- ... mkDatabase :: (MonadIO m, MonadIO n) => DatabaseConfig -> n (Database m) mkDatabase = undefined

This is where things start to get tricky. The monad types must all align or there will be a compilation error.

We have three choices:

convert Http (Traced m) into a Http m convert Database m into a Database (Traced m) pass around all four versions and mix/match when we need them.

Carrying around all combinations is not scalable, although we can already use mkDatabase to construct both the Databases that we need. We won’t, however, be able to create a Http m .

If we want to conjure the correct types when we need them, we’ll need Data.FFunctor, which allows us to map an (f m) into an (f (t m)). Let’s create some instances for our capabilities, using the ... operator from Universum to reduce the boilerplate

instance FFunctor Logger where ffmap nt (Logger p1 p2 p3) = Logger (nt ... p1) (nt ... p2) (nt ... p3) instance FFunctor Http where ffmap nt (Http p1 p2) = Http (nt ... p1) (nt ... p2) instance FFunctor Database where ffmap nt (Database p1 p2) = Database (nt ... p1) (nt ... p2) instance FFunctor Tracer where ffmap nt (Tracer p1 p2) = Tracer (nt ... p1) (nt ... p2)

Now we can convert a Database m into a Database (Traced m) by calling luft from ffunctor (it is a simple alias for ffmap lift ).

We might also want to opt-in to tracing inside the Database capability and wrap each function call with a span. If we have written one of these we probably always want to use it instead of the luft ed one.

It’s nice that we don’t need to touch the underlying implementation to add tracing.

databaseTraced :: MonadMask m => Tracer (Traced m) -> Database m -> Database (Traced m) databaseTraced tracer db = let db' = luft db span' = tracer & span in Database (span' "Database.history" $ (db' & dbHistory)) (\t -> span' "Database.add" $ (db' & dbAdd) t)

Which is polymorphic…

class TracedCapability f where nachziehen :: MonadMask m => f m -> f (Traced m) instance TracedCapability Database where nachziehen = databaseTraced'

We can convert a traced capability into a capability that looks like it doesn’t do any tracing if we provide a parent span. e.g. convert a Http (Traced m) into a Http m with skizzieren ctx http .

skizzieren :: (FFunctor f, Functor m) => OpenSpan -> f (Traced m) -> f m skizzieren ctx = ffmap (flip runReaderT ctx)

We need to know which Trace to use, and we might get that from a MonadReader. Here’s a convenience for that, but this would mean that we are in a context where we can trace and we want to create capabilities that don’t look like they can trace, which is a bit of a strange situation to be in.

verfolgen :: (FFunctor f, Functor m, MonadReader OpenSpan n) => f (Traced m) -> n (f m) verfolgen t = (\ctx -> ffmap (flip runReaderT ctx) t) <$> ask

It is more likely that we don’t have access to a MonadReader but we have a Tracer capability, and we want some other capability to run within a new root span.

zeichnen :: (FFunctor f, MonadMask m) => Tracer m -> String -> f (Traced m) -> f m zeichnen tracer name = ffmap $ (tracer & rootSpan) name

Let’s Pause

The fact that luft, nachziehen, skizzieren, verfolgen and zeichnen might be needed at all, should be telling us that we’ve wandered into the territory of conceptual overhead. We’re manually aligning and wiring capabilities instead of writing our business logic. That’s not good hackers, that’s not good.

A lot of people pick one monad stack for their application and stick to that. In the case of Tracer, that would mean everything gets a (MonadReader (Maybe OpenSpan)) and there is no need to luft… but we can no longer be sure that we’re adding a span to an existing tree vs creating a new root span. We end up doing what untyped languages do: asserting behaviours with runtime tests.

If we were to use typeclass encodings for Http and Database (i.e. classic MTL) we might be able to write derivation rules that do a lot of the conversions automatically, but it isn’t long before we need to write derivations that make use of advanced ghc extensions (e.g. OverlappingInstances, IncoherentInstances, UndecidableInstances, etc)… and we pay for it with boilerplate in our tests with newtypes and DerivingVia. Or we have orphans and lose the ability to reason about what is running in any given test, which is prone to breakages during refactorings. This can also be a touchy subject as some people take the principled approach that all typeclasses should have laws.

Furthermore, if our application has a lot of capabilities, our business logic can have long parameter lists of capabilities that we have to pass around. Long parameter lists might be an indicator of a bad abstraction that needs more layers, but there always seem to be a few capabilities (like logging and tracing) that end up being needed everywhere.

People create encoding such as makeClassy and makeTypeclass to reduce the boilerplate of passing capabilities, at the cost of the mental overhead of the encodings, and the quality of compiler error messages.

That brings us to another problem with MTL: we can’t have multiple MonadReaders. So if we were to use a “classy” encoding (i.e. put capabilities into a MonadReader) we would not be able to use MonadTraced. A workaround to this is MORE LENSES. Here is an example replacement for MonadReader that uses HasType from generic-lens :

type HasReader r r' m = (MonadReader r' m, HasType r r') ask_ :: HasReader r r' m => m r ask_ = getTyped <$> ask local_ :: HasReader r r' m => (r -> r) -> m a -> m a local_ f = local (\r' -> setTyped (f . getTyped $ r') r')

We would have to redesign the Tracer to use HasReader, which means redundant type parameters (more conceptual overhead) everywhere:

type MonadTraced_ m r' = (HasReader OpenSpan r' m, MonadMask m) span_ :: MonadTraced_ m r' => Tracer m -> String -> m a -> m a span_ tracer name ma = do OpenSpan{spanId} <- ask_ child <- (tracer & openSpan) (Just spanId) name local_ (const child) $ ma `finally` ((tracer & closeSpan) child)

Conclusion

We can use MTL with records of functions to gain a lot of type safety around what our programs are capable of doing, but for non-trivial projects, we will introduce boilerplate, conceptual overhead, and workarounds to deal with the case when the monads don’t align. We encounter similar problems as ReaderT / MonadReader with error handling (ExceptT / MonadError) and single-threaded statefulness (StateT / MonadState).

“Classic” MTL, with typeclasses to encode capabilities, can reduce the boilerplate in the main code but ends up costing just as much when tests are considered. Ultimately, typeclasses are just records of functions with magic wiring that usually do the right thing and sometimes don’t.

The emergence of boilerplate is good news, in a way, because when common patterns emerge, it points to something fundamental… and a new solution usually comes along to solve fundamental problems.