Haskell Design Patterns: The Handle Pattern

A neat and simple way to build services in Haskell
Published on March 8, 2018 under the tag haskell


I’d like to talk about a design pattern in Haskell that I’ve been calling the Handle pattern. This is far from novel – I’ve mentioned this before and the idea is definitely not mine. As far as I know, in fact, it has been around since basically forever1. Since it is ridiculously close to what we’d call common sense2, it’s often used without giving it any explicit thought.

I first started more consciously using this pattern when I was working together with Simon Meier at Better (aka erudify). Simon did a writeup about this pattern as well. But as I was explaining this idea again at last week’s HaskellerZ meetup, I figured it was time to do an update of that article.

The Handle pattern allows you write stateful applications that interact with external services in Haskell. It complements pure code (e.g. your business logic) well, and it is somewhat the result of iteratively applying the question:

The result is a powerful and simple pattern that does not even require Monads3 or Monad transformers to be useful. This makes it extremely suitable for beginners trying to build their first medium-sized Haskell application. And that does not mean it is beginners-only: this technique has been applied successfully at several Haskell companies as well.

Table of contents

  1. Introduction
  2. Context
  3. The module layout
    1. A Database Handle
    2. Creating a Handle
    3. Destroying a Handle
    4. Reasonable safety
    5. Summary of the module layout
  4. Handle polymorphism
    1. A Handle interface
    2. A Handle implementation
  5. Compared to other approaches


In Haskell, we try to capture ideas in beautiful, pure and mathematically sound patterns, for example Monoids. But at other times, we can’t do that. We might be dealing with some inherently mutable state, or we are simply dealing with external code which doesn’t behave nicely.

In those cases, we need another approach. What we’re going to describe feels suspiciously similar to Object Oriented Programming:

As you can see, it is not exactly the same as Alan Kay’s original definition of OOP4, but it is far from the horrible incidents that permeate our field such as UML, abstract factory factories and broken subtyping.

Before we dig in to the actual code, let’s talk about some disclaimers.

Pretty much any sort of Haskell code can be written in this particular way, but that doesn’t mean that you should. This method relies heavily on IO. Whenever you can write things in a pure way, you should attempt to do that and avoid IO. This pattern is only useful when IO is required.

Secondly, there are many alternatives to this approach: complex monad transformer stacks, interpreters over free monads, uniqueness types, effect systems… I don’t want to claim that this method is better than the others. All of these have advantages and disadvantages, so one must always make a careful trade-off.

The module layout

For this pattern, we’ve got a very well-defined module layout. I believe this helps with recognition which I think is also one of the reasons we use typeclasses like Monoid.

When I’m looking at the documentation of libraries I haven’t used yet, the types will sometimes look a bit bewildering. But then I see that there’s an instance Monoid. That’s an “Aha!” moment for me. I know what a Monoid is. I know how they behave. This allows me to get up to speed with this library much faster!

Using a consistent module layout in a project (and even across projects) provides, I think, very similar benefits to that. It allows new people on the team to learn parts of the codebase they are yet unfamiliar with much faster.

A Database Handle

Anyway, let’s look at the concrete module layout we are proposing with this pattern. As an example, let’s consider a database. The type in which we are encapsulating the state is always called Handle. That is because we design for qualified import.

We might have something like:

module MyApp.Database

data Handle = Handle
    { hPool   :: Pool Postgres.Connection
    , hCache  :: IORef (PSQueue Int Text User)
    , hLogger :: Logger.Handle  -- Another handle!
    , …

The internals of the Handle typically consist of static fields and other handles, MVars, IORefs, TVars, Chans… With our Handle defined, we are able to define functions using it. These are usually straightforward imperative pieces of code and I’ll omit them for brevity5:

module MyApp.Database where

data Handle =

createUser :: Handle -> Text -> IO User
createUser =

getUserMail :: Handle -> User -> IO [Mail]
getUserMail =

Some thoughts on this design:

  1. We call our functions createUser rather than databaseCreateUser. Again, we’re working with qualified imports so there’s no need for “C-style” names.

  2. All functions take the Handle as the first argument. This is very important for consistency, but also for polymorphism and code style.

    With code style, I mean that the Handle is often a syntactically simpler expression (e.g. a name) than the argument (which is often a composed expression). Consider:

    Database.createUser database $ userName <> "@" <> companyDomain


    Database.createUser (userName <> "@" <> companyDomain) database
  3. Other Handles (e.g. Logger.Handle) are stored in a field of our Database.Handle. You could also remove it there and instead have it as an argument wherever it is needed, for example:

    createUser :: Handle -> Logger.Handle -> Text -> IO User
    createUser =

    I usually prefer to put it inside the Handle since that reduces the amount of arguments required for functions such as createUser. However, if the lifetime of a Logger.Handle is very short6, or if you want to reduce the amount of dependencies for new, then you could consider doing the above.

  4. The datatypes such as Mail may be defined in this module may even be specific to this function. I’ve written about ad-hoc datatypes before.

Creating a Handle

I mentioned before that an important advantage of using these patterns is that programmers become “familiar” with it. That is also the goal we have in mind when designing our API for the creation of Handles.

In addition to always having a type called Handle, we’ll require the module to always have a type called Config. This is where we encode our static configuration parameters – and by static I mean that we shouldn’t have any IORefs or the like here: this Config should be easy to create from pure code.

module MyApp.Database where

data Config = Config
    { cPath :: FilePath
    , …

data Handle =

We can also offer some way to create a Config. This really depends on your application. If you use the configurator library, you might have something like:

parseConfig :: Configurator.Config -> IO Config
parseConfig =

On the other hand, if you use aeson or yaml, you could write:

instance Aeson.FromJSON Config where
    parseJSON =

You could even use a Monoid to support loading configurations from multiple places. But I digress – the important part is that there is a type called Config.

Next is a similar pattern: in addition to always having a Config, we’ll also always provide a function called new. The parameters follow a similarly strict pattern:

new :: Config         -- 1. Config
    -> Logger.Handle  -- 2. Dependencies
    ->--    (usually other handles)
    -> IO Handle      -- 3. Result

Inside the new function, we can create some more IORefs, file handles, caches… if required and then store them in the Handle.

Destroying a Handle

We’ve talked about creation of a Handle, and we mentioned the normal functions operating on a Handle (e.g. createUser) before. So now let’s consider the final stage in the lifetime of Handle.

Haskell is a garbage collected language and we can let the runtime system take care of destroying things for us – but that’s not always a great idea. Many resources (file handles in particular come to mind as an example) are scarce.

There is quite a strong correlation between scarce resources and things you would naturally use a Handle for. That’s why I recommend always providing a close as well, even if does nothing. This is a form of forward compatibility in our API: if we later decide to add some sort of log files (which will need to be closed), we can do so without individually mailing all our module users that they now need to add a close to their code.

close :: Handle -> IO ()
close =

Reasonable safety

When you’re given a new and close, it’s often tempting to add an auxiliary function like:

    :: Config            -- 1. Config
    -> Logger.Handle     -- 2. Dependencies
    ->--    (usually other handles)
    -> (Handle -> IO a)  -- 3. Function to apply
    -> IO a              -- 4. Result, handle is closed automatically

I think this is a great idea. In fact, it’s sometimes useful to only provide the withHandle function, and hide new and close in an internal module.

The only caveat is that the naive implementation of this function:

withHandle config dep1 dep2 … depN f = do
    h <- new config dep1 dep2 … depN
    x <- f h
    close h
    return x

Is wrong! In any sort of withXyz function, you should always use bracket to guard against exceptions. This means the correct implementation is:

withHandle config dep1 dep2 … depN f =
    bracket (new config dep1 dep2 … depN) close f

Well, it’s even shorter! In case you want more information on why bracket is necessary, this blogpost gives a good in-depth overview. My summary of it as it relates to this article would be:

  1. Always use bracket to match new and close
  2. You can now use throwIO and killThread safely

It’s important to note that withXyz functions do not provide complete safety against things like use-after-close or double-close. There are many interesting approaches to fix these issues but they are way beyond the scope of this tutorial – things like Monadic Regions and The Linearity Monad come to mind. For now, we’ll rely on bracket to catch common issues and on code reviews to catch team members who are not using bracket.

Summary of the module layout

If we quickly summarise the module layout, we now have:

module MyApp.Database
    ( Config (..)   -- Internals exported
    , parseConfig   -- Or some other way to load a config

    , Handle        -- Internals usually not exported
    , new
    , close
    , withHandle

    , createUser  -- Actual functions on the handle
    , …
    ) where

This is a well-structured, straightforward and easy to learn organisation. Most of the Handles in any application should probably look this way. In the next section, we’ll see how we can build on top of this to create dynamic, customizable Handles.

Handle polymorphism

It’s often important to split between the interface and implementation of a service. There are countless ways to do this in programming languages. For Haskell, there is:

The list is endless. And because Haskell on one hand makes it so easy to abstract over things, and on the other hand makes it possible to abstract over pretty much anything, I’ll start this section with a disclaimer.

Premature abstraction is a real concern in Haskell (and many other high-level programming languages). It’s easy to quickly whiteboard an abstraction or interface and unintentionally end up with completely the wrong thing.

It usually goes like this:

  1. You need to implement a bunch of things that look similar
  2. You write down a typeclass or another interface-capturing abstraction
  3. You start writing the actual implementations
  4. One of them doesn’t quite match the interface so you need to change it two weeks in
  5. You add another parameter, or another method, mostly for one specific interface
  6. This causes some problems or inconsistencies for interfaces
  7. Go back to (4)

What you end up with is a leaky abstraction that is the product of all concrete implementations – where what you really wanted is the greatest common divisor.

There’s no magic bullet to avoid broken abstractions so my advice is usually to first painstakingly do all the different implementations (or at least a few of them). After you have something working and you have emerged victorous from horrible battles with the guts of these implementations, then you could start looking at what the different implementations have in common. At this point, you’ll also be a bit wiser about where they differ – and you’ll be able to take these important details into account, at which point you retire from just being an idiot drawing squares and arrows on a whiteboard.

This is why I recommend sticking with simple Handles until you really need it. But naturally, sometimes we really need the extra power.

A Handle interface

So let’s do the simplest thing that can possibly work. Consider the following definition of the Handle we discussed before:

module MyApp.Database
    ( Handle (..)  -- We now need to export this
    ) where

data Handle = Handle
    { createUser :: Text -> IO User
    , …

What’s the type of createUser now?

createUser :: Handle -> Text -> IO User

It’s exactly the same as before! This is pretty much a requirement: it means we can move our Handles to this approach when we need it, not when we envision that we will need it at some point in the future.

A Handle implementation

We can now create a concrete implementation for this abstract Handle type. We’ll do this in a module like MyApp.Database.Postgres.

module MyApp.Database.Postgres where
import MyApp.Database

data Config =

new :: Config -> Logger.Handle ->-> IO Handle

The Config datatype and the new function have now moved to the implementation module, rather than the interface module.

Since we can have any number of implementation modules, it is worth mentioning that we will have multiple Config types and new functions (exactly one of each per implementation). Configurations are always specific to the concrete implementation. For example, an sqlite database may just have a FilePath in the configuration, but our Postgres implementation will have other details such as port, database, username and password.

In the implementation of new, we simply initialize a Handle:

new config dep1 dep2 … depN = do
    -- Intialization of things inside the handle

    -- Construct record
    return Handle
        { createUser = \name -> do

        , …

Of course, we can manually float out the body of createUser since constructing these large records gets kind of ugly.

Compared to other approaches

We’ve presented an approach to modularize the effectful layer of medium- to large-scaled Haskell applications. There are many other approaches to tackling this, so any comparison I come up with would probably be inexhaustive.

Perhaps the most important advantage of using Handles is that they are first class values that we can freely mix and match. This often does not come for free when using more exotic strategies.

Consider the following type signature from a Hackage package – and I do not mean to discredit the author, the package works fine but simply uses a different approach than my personal preference:

-- | Create JSON-RPC session around conduits from transport layer.
-- When context exits session disappears.
    :: (MonadLoggerIO m, MonadBaseControl IO m)
    => Ver                  -- ^ JSON-RPC version
    -> Bool                 -- ^ Ignore incoming requests/notifs
    -> Sink ByteString m () -- ^ Sink to send messages
    -> Source m ByteString  -- ^ Source to receive messages from
    -> JsonRpcT m a         -- ^ JSON-RPC action
    -> m a                  -- ^ Output of action

I’m a fairly experienced Haskeller and it still takes me a bit of eye-squinting to see how this will fit into my application, especially if I want to use this package with other libraries that do not use the Sink/Source or MonadBaseControl abstractions.

It is somewhat obvious that one running call to runJsonRpcT corresponds to being connected to one JSON-RPC endpoint, since it takes a single sink and source. But what if we want our application to be connected to multiple endpoints at the same time?

What if we need to have hundreds of thousands of these, and we want to store them in some priority queue and only consider the most recent ones in the general case. How would you go about that?

You could consider running a lightweight thread for every runJsonRpcT, but that means you now need to worry about thread overhead, communicating exceptions between threads and killing the threads after you remove them. Whereas with first-class handles, we would just have a HashPSQ Text Int JsonRpc.Handle, which is much easier to reason about.

So, I guess one of the oldest and most widely used approaches is MTL-style monad transformers. This uses a hierarchy of typeclasses to represent access to various subsystems.

I love working with MTL-style transformers in the case of pure code, since they often allow us to express complex ideas concisely. For effectful code, on the other hand, they do not seem to offer many advantages and often make it harder to reason about code.

My personal preference for writing complex effectful code is to reify the effectful operations as a datatype and then write pure code manipulating these effectful operations. An interpreter can then simply use the Handles to perform the effects. For simpler effectful code, we can just use Handles directly.

I have implemented a number of these patterns in the (ever unfinished) example web application fugacious, in case you want to see them in action or if you want a more elaborate example than the short snippets in this blogpost. Finally, I would like to thank Alex Lang and Nicolas Mattia for proofreading, and Titouan Vervack for many corrections and typos.

  1. Well, System.IO.Handle has definitely been around for a while.↩︎

  2. If you’re reading this article and you’re thinking: “What does this guy keep going on about? This is all so obvious!” – Well, that’s the point!↩︎

  3. It does require IO, but we don’t require thinking about IO as a Monad. If this sounds weird – think of lists. We work with lists all the time but we just consider them lists of things, we don’t constantly call them “List Monad” or “The Free Monoid” for that matter.↩︎

  4. And indeed, we will touch on a common way of encoding OOP in Haskell – creating explicit records of functions – but we’ll also explain why this isn’t always necessary.↩︎

  5. If you want to see a full example, you can refer to this repository that I have been using to teach practical Haskell.↩︎

  6. With a short lifetime I mean you would create a new Logger.Handle for every call to createUser. But even in that case you could consider turning Logger.Handle into something like a resource pool, from which you could request a new concrete logging interface to log things. It really depends on your use case in the end…↩︎