rauhala.info/posts/demobot.md
2019-03-27 21:39:43 +02:00

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---
title: Functional architecture Pt. 1
date: 2018-12-25
---
I'm lucky enough to work with Haskell professionally which gives me some view
to good and maintainable real world architecture. In my opinion, one of the
biggest contributing factors to how your general architecture is defined, is
determined by the base application monad stack you are using.
Our actual product is mostly in the regular `LoggingT (ReaderT app IO)` base
monad with whatever style you would imagine with that base monad in place. It's
not entirely consistent, but close enough.
With all the talk about just having `IO`, `ReaderT app IO`, free monads or
tagless final monads, I thought of trying different styles. For this post I'm
focusing on the tagless final since it's most interesting for me right now.
`IO`
: The most basic style. This is pretty much only suitable for the most basic
of needs.
`ReaderT app IO`
: How we mostly define the base monad. This is a really good way of doing
things, it gives you a lot of leeway on how you can define the rest of your
application.
`Free monads`
: Free monads are a way of having a small constrained DSL or monad stack for
defining your application. By constraining the user, you are also reducing the
area for bugs. There is also some possibility for introspection, but usually
this isn't a usable feature. Also since free monad applications need the full
AST, they're quite a bit slower than the other solutions.
`Tagless final`
: This is something I'm the least familiar with. If I have understood
correctly, free monads and tagless final are more or less equivalent solutions
in their power, but in tagless final you aren't creating the AST anywhere,
which also means that you aren't paying for it either.
That out of the way, I had a small project idea for a bot that's easy to
contribute to, difficult to make errors and easy to reason about. The project
is at most a proof-of-concept and most definitely not production quality.
Still, I hope it's complex enough to showcase the architecture.
The full source code is available [at my git repository](https://git.rauhala.info/MasseR/demobot).
For the architecture to make sense, let me introduce two different actors: a
*core contributor* that's familiar with Haskell and a *external contributor*
that's familiar with programming, not necessarily with Haskell.
The repository is split into two parts, the library and the application.
The library
: Provides the restricted monad classes (tagless final), extension points and
the core bot main loop.
The application
: Provides the implementation for the tagless final type classes, meaning
that the application defines how the networking stack is handled, how database
connectivity is done and so on. It also collects all the extensions for that
specific application.
The *core contributor* is responsible for maintaining the library as well as
the type class instances for the application type. The *external contributor*
is responsible for maintaining one or multiple extensions that are restricted
in their capability and complexity.
I'm restricting the capabilities of the monad in the library and extensions,
meaning that I'm not allowing any IO. For example the networking is handled by
a single `MonadNetwork` type class. This is the most complex type class in the
library right now, using type families for defining a specific extension point
for the messages. This could be something like 'event type' for Flowdock
messages or 'source channel' for IRC messages.
~~~haskell
data Request meta = Request { content :: Text
, meta :: meta }
data Response meta = Response { content :: Text
, meta :: meta }
class Monad m => MonadNetwork m where
type Meta m :: *
recvMsg :: m (Request (Meta m))
putMsg :: Response (Meta m) -> m ()
~~~
Then we have the extension point which is more or less just a `Request -> m (Maybe Response)`. I'm using rank n types here for qualifying the `Meta`
extension point and forcing the allowed type classes to be a subset of the
application monad stack, I don't want extension writers to be able to write
messages to the bot network by themselves.
~~~haskell
data Extension meta =
Extension { act :: forall m. (meta ~ Meta m, MonadExtension m) => Request meta -> m (Maybe (Response meta))
, name :: String }
~~~
Last part of the library is the main loop, which is basically a free monad
(tagless final) waiting for an interpreter. At least in this POC I find this
style to be really good, it's really simplified, easy to read and hides a lot
of the complexity, while bringing forth the core algorithm.
~~~haskell
mainLoop :: forall m. (MonadCatch m, MonadBot m) => [Extension (Meta m)] -> m ()
mainLoop extensions = forever $ catch go handleFail
where
handleFail :: SomeException -> m ()
handleFail e = logError $ tshow e
go :: m ()
go = do
msg <- recvMsg
responses <- catMaybes <$> mapM (`act` msg) extensions
mapM_ putMsg responses
~~~
Then comes the actual application where we write the effectful interpreters. In
this POC the interpreter is just a `LoggingT IO a` with the semantics of
stdin/stdout. This is the only file where we're actually interacting with the
outside world, everything else is just pure code.
~~~haskell
instance MonadNetwork AppM where
type Meta AppM = ()
recvMsg = Request <$> liftIO T.getLine <*> pure ()
putMsg Response{..} = liftIO . T.putStrLn $ content
~~~
Writing the extensions was the responsibility of *external contributors* and we
already saw how the actual extension point was defined above. Using these
extension points is really simple and here we see how the implementation is
just a simple `Request -> m (Maybe Response)`.
~~~haskell
extension :: Extension ()
extension = Extension{..}
where
name = "hello world"
act Request{..} | "hello" `T.isPrefixOf` content = return $ Just $ Response "Hello to you" ()
| otherwise = return Nothing
~~~