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