Abolish the state! or no? An OCaml Perspective


A rather interesting facet of the OCaml programming language is the variety of paradigms that it supports: functional, imperative and object-oriented. While this certainly increases the flexibility of the language, it also raises the question of how these various factors should be balanced in idiomatic OCaml code.

While I've found that it's fairly established that the "Object" in Object Caml should typically be avoided, and there are a quite a few articles on how mutable references can be used in a local fashion, the issue of how to intermix functional and imperative code at an architectural system-design level is something that is less often spoken about, and has overall left me confused about how to structure OCaml code.

For an example, if you are interfacing with an external API with interior mutability:

type t 
val init: unit -> t
val update_state: t -> int -> unit

Do you simply ignore the external state in your data structures?

type s = { state: t; count: int }
let update (s: s) = update_state s.state s.count; {s with count = s.count + 1;}

Do you make the entire structure mutable to preserve a consistent interface?

type s = {state: t; mutable count: int}
let update (s: s) : unit = update_state s.state s.count; s.count <- s.count + 1

Do you write your code in pure form parameterised over the mutable components, possibly at the cost of additional mutable accesses?

type 'a s = {state: 'a; count: int}
let update (s: 'a s) f = {count = s.count + 1; state = f s.state s.count}

Do you instead pull out the mutable components from the data-structure entirely requiring them as external inputs?

type s = {count: int}
let update (s: s) state = update state s.count; {count = s.count + 1}

I asked this on the OCaml disuss forum, however didn't get any useful response.

This is an issue that I have often encountered in my personal projects, where, coming from a Haskell background, I typically design my systems to be entirely pure, often at great cost to performance.

For example, I recently built a project where most of the computation was done while wrapped in a computation monad:

type ('a, 'b) t = string list -> ('a * string list, 'b) Result.t

let ( >>= ) (comp: ('a, 'e) t) (f:('a -> ('b, 'e) t)) : ('b, 'e) t =
  fun s -> 
  Result.(>>=) (comp s) (fun (value,warnings) ->
      Result.map ((f value) warnings) ~f:(fun (result, warnings) ->
          (result, warnings)))

The idea here was that I wanted to allow components of my codebase to produce error messages that could be accumulated and printed to the user or to a log - to do this, I was explicitly threading this list of error messages through each computation. As the program grew more and more complex, I ended up adding more and more control-flow mechanisms to the monad - things like try-catch or a supress-error, and eventually it seemed like I'd essentially just recreated OCaml's control flow just within my monad. Even worse, as certain parts of the system called out to external components with mutable state, many of the intermediate functions did not adhere to referential transparency.

Overall, after completing this project, I had to question whether this use of a monad was really an idiomatic use of OCaml - my code is less efficient than just using mutable references, and provides roughly the same or fewer guarantees.

As such, to investigate this problem, I have scoured through the source code of a variety of real world open-source OCaml programs, looking at their general structure to evaluate how they choose to balance these two paradigms in their system design.

In rest of this post, I'll present the findings of my research into this question, providing at a series of case studies on real world OCaml projects evaluating with how these imperative concepts should be used at an architectural level.

Case study 1: OCaml-DNS

The OCaml DNS project provides an implementation of a DNS resolver in OCaml. The README states that the project is written in a mostly pure fragment of OCaml. The structure of the project establishes a clear boundary between the pure and the impure components of the library, and most of the imperative code in the executables that it provides is localised around the entry point.

The core of the implementation revolves around a custom data-structure DNS_trie to encode zone file data. The recursive data-structure is composed of two immutable maps, the first maps domain-components to its subdomains (which are also encoded as a DNS_trie) and the second maps resource record types to their values.

Alongside these pure logic implementations, in order to encode IO operations, the OCaml-DNS builds additional APIs that are parameterised over an arbitrary IO monad - for example, to instantiate the API, you would have to provide a module that included, amongst other things, the following operations:

type +'a io
val bind : 'a io -> ('a -> 'b io) -> 'b io
val lift : 'a -> 'a io

In this way, the library is able to achieve a similar "parametericity" to Haskell code using monad/monad transformer type-classes.

Finally, the executable instantiate these modules using various impure forms of IO (Lwt, Unix etc.) and call them from the entry point.

Overall this type of structure seems best suited for command-line like applications, which are intended to have short runtimes, and not to be long-running.

Case study 2: Wanderers

Wanderers is an implementation of a small rougelike game in OCaml interfacing with the SDL library for rendering and input management.

In the entry point of the application, Wanderers starts by imperatively setting up the OpenGL Context, and then uses the input parameters to generate an initial state. This initial state is then passed as a parameter to the recursive main loop function (the main other parameter that is threaded through the main function is the ticks).

Each iteration of the main loop consists of the following steps:

  • (imperative) Retrieve current ticks from SDL library
  • (functional/imperative) Draw game screen from state
    • imperative aspect arises because drawing is done using SDL calls which maintain an implicit context
  • (functional) Simulate changes game state using the elapsed ticks
  • (functional/imperative) Update game state using key presses from user
    • imperative aspect arises because keypresses are obtained from SDL calls which maintain an implicit context

While the main loop does interface heavily with the imperative SDL API, the core logic of the game (the simulation part), is done entirely functionally, with the simulation operation iteratively updating parts of the global state.

The entirety of the game state is encapsulated within this state parameter, and modifications seem to be made in a functional way.

Unlike OCaml-DNS, this project has a less strict boundary between its imperative and functional components, allowing intermixing of these styles at the main loop. However, while at a high level the components may be either imperative or functional, within a component, the chosen style is used consistently.

Case study 3: Unison

Unison is a file-synchronization program written in OCaml that allows synchronizing file directories between hosts.

Unison is quite a large project, so we'll focus on a subset of its modules, but try and generalize the patterns that it uses.

The entrypoint to Unision is in its main module, which is written as a functor parameterised over the rendering method, which allows the program to be built conditionally without linking libraries required for options that are not used.

It parses the user arguments and calls out to imperative functions from various submodules (such as prefs) to update the preferences based on input flags, before running the main program via the instantiated module.

Sub case study 1: Preferences module

The preferences module provides a good representation of the general mix of imperative and functional code used in Unison.

The Preferences module itself is used to group together all the user preferences under a single conceptual profile thing.

It makes liberal use of references, but encapuslates all accesses to the mutable references behind it's module interface.

As an example of this design, consider the following private declaration within the module:

let addresetter f = resetters := f :: !resetters

Each set of user settings adds a callback to this list, which is then invoked when the external API calls to reset settings to defaults.

It makes some even more crazy use of refernce to handle inter-process communication - for example, in order to synchronize user settings across a server and client, two lists of callbacks are setup - one for marhalling stored values and one for loading values.

This use of reference allows for additional dynamism within the program logic - essentially, the prefs module sets up a set of dynamic callback handlers by means of maintaining a mutable map. While the end-user doesn't actually add callbacks, while defining the module, the developer can use this mutable map to easily add callback handlers.

Preferences themselves are represented internally as an element of the following type:

type 'a t =
  { mutable value : 'a; defaultValue : 'a; mutable names : string list;
    mutable setInProfile : bool }

So, in the external API, a property like `shoulddownload` would have the type `bool t`. However, the external users can only access these components by means of (mostly) immutable accessors.

There are also unit returning functions that append to a file.

Finally the preference creating operations are then exported and used throughout the program. Despite this distributed usage, as the functions all mutate the state encapsulated within the module itself, when it comes to printing out the flags/customization options of the program, this can be done by mutating a single source.

Sub case study 2: Xferhint

This module manages comonents of Unison dealing with xfer - an optimization of the file synchronization algorithm to not copy over files when it seems that the two files are present on both systems - identified by a hash colission.

To implement this functionality, the module instantiates a mutable table mapping file paths to hashes. The module then exports methods such as delete, lookup and insert that manipulate the store.

Again as in the preferences module, the functions themselves do not satisfy referential transparency, but all the unsafe manipulations to the state are encapsulated within the boundaries of the module.

Sub case study 3: Tree

This module provides an implementation of a custom labelled tree, where the edges and leaves can be annotated with potentially different types of values.

In contrast to the other modules, the implementation of this module is entirely functional, with all operations treating the datastructure as immutable.

Sub case study 4: Recon

This module implemnts the algorithm used to determine the changes required to reconcile the program, and is primarly implemented in an imperative way, but calls out to the functional Tree datastructure and its operations.

Like the other imperative modules in Unison, Recon imperatively calls out to the Preferences module to register its customization options. Unlike the other imperative modules we've looked at so far, apart from the mutable options, most of the exported API from this module is actually referentially transparent.

General patterns

The general approach to handling state in unison seems to be to encapsulate mutations to the state within the module boundaries - all functions in a given module can be easily understood as they only mutate values within the module. The only exception to this is the pervasive use of the preferences module to register customizations in a single source.

While this discipline provides some rigour to the development processs, as imperative functions inevitably end up calling other imperative functions, reasoning about how a given function changes the state becomes increasingly dificult, as one needs to follow longer and longer function call chains (not to mention callbacks etc.).

One potential way of achieving the best of both worlds would be to use first-class modules to pass around the context explicitly - i.e:

module type S = sig end
module type SM = sig val incr: unit -> int end
module M () = struct let count = ref 0 end
module type Make(S: S) = struct let incr () = S.count := 1; S.count end

In other words, a function making use of any mutable operations (incr in this case), would need to be passed in explicitly a module of module type S, which would then be instatiated to "unlock" the mutable operation.

In contrast to Union's design, this would make functions explicitly indicate the state that they interact with, making reasoning about these programs easier.

Case study 4: Ocsigenserver

Oscigenserver is a OCaml http server and client implemented in OCaml.

Again as with Unison, as this is a large project, we'll look at a subset of the modules to get an understanding of how Oscigen intergrates functional and imperative operations.

Sub case study 1: Oscigen Server

The server starts by imperatively initializing its subcomponents (i.e like seeding its random generator, etc.) - these imperative operations are all encapsulated at the outermost level of the system in a module Ocsigen_server which provides the entrypoint, however are all declared at the toplevel:

let () = Random.self_init ()

let () = Ocsigen_commandline.cmdline

Most of the other code in the system is written in a functional way, with explicit state being passed.

Sub case study 2: Oscigen command

This module uses imperative state to allow dynamically registering a series of handlers for a given prefix. The idea here is that an external client can register a command and a handler callback using a specific register : ('a -> 'b) -> unit function. In order to use these handlers to run a command, the user must retrieve the run operation using an explicit getter get_run: unit -> ('a -> 'b).

The use of imperative components is slightly more principled than in Unison, as no mutable references are declared at the top level, and so any functions that have mutable behaviours are somewhat captured in the type system, due to the fact that the getter function has to be retrieved before use.

Sub case study 3: Http client

Ocsigen also provides a module that implements a http client that can make requests for a given url.

While the action of requesting data from an external server is inherently an IO operation, due to the use of LWT and its monads, this fact is clearly indicated in the type signatures. Besides this, most of the implementation of the core logic is done in a functional style, with the only imperative parts being rather benign irrelevant calls out to a logging utilty.

There are some imperative components in terms of a mutable table system for handling pipelined HTTP connections, but this imperative state is not exposed in any way to the clients of the API (note: unlike in Unison, the use of state even more principled as there are no ways for the user to directly mutate the table), nor does it have significant impacts on the functional behaviours of the exported code - i.e to the end client, the api is simply submit a URL and retrieve a response, but internally the pipelining table may be used to optimize this.

General patterns

Overall, despite being a long running application, Oscigen server makes a very principled use of imperative state in its system design.

Most of the imperative parts of the codebase are either for initialization (i.e initializing the random number generator at the start of a module) or optimization (i.e memoizing results for a complex calculation). While this isn't technically referential transparency, as these side-effects have no impact on the semantics of a given API, reasoning about the behaviours of a given program is still fairly straightforward.

The only exception to this rule is the command module, wherin the ability to mutate references is allowed in order to allow dynamically extending the handlers for a message. Despite the use of mutable state, Oscigen still makes the dynamic behaviour of the API explicit in the interface by not exporting the handler directly, but rather a getter that returns the function.

Conclusion: Abolish the state? Yes or no?

As presented in the case studies, OCaml simultaneously supports a wide variety of programming styles, ranging from the entirely pure to the entirely impure.

Easy access to state is a useful feature of the OCaml language, and allows for an easier development process - however, making unprincipled use of state can make programs harder to reason about.

In general, we can ensure our use of state is principled by making sure that most mutation is done at the edges of the codebase, and then writing the rest of our code in a pure form. This pattern works well with use of mutable structures (such as hashtables etc.), wherein we can make all the mutations to the datastructure at the entrypoint, and then use an pure interface when accessing it from the functional core.

Other forms of dynamic behaviours such as maintaining state within the module structure itself are more nefarious, as they mean that the behaviours of a module are not consistent over time, which quickly propagates and makes reasoning about the behaviours of other functions difficult.

So, abolish the state? ehhh. no.