Bidirectional conversion between Elm and Haskell. Use when migrating projects between these languages in either direction. Extends meta-convert-dev with Elm↔Haskell specific patterns. Use when migrating Elm frontend code to Haskell, translating Elm patterns to idiomatic Haskell, or refactoring Elm codebases. Extends meta-convert-dev with Elm-to-Haskell specific patterns.
Scanned 9/6/2026
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---
name: convert-elm-haskell
description: Bidirectional conversion between Elm and Haskell. Use when migrating projects between these languages in either direction. Extends meta-convert-dev with Elm↔Haskell specific patterns. Use when migrating Elm frontend code to Haskell, translating Elm patterns to idiomatic Haskell, or refactoring Elm codebases. Extends meta-convert-dev with Elm-to-Haskell specific patterns.
---
# Elm ↔ Haskell Conversion
Bidirectional conversion between Elm and Haskell. This skill extends `meta-convert-dev` with Elm↔Haskell specific type mappings, idiom translations, and tooling for migrating functional frontend code to backend or library code.
## This Skill Extends
- `meta-convert-dev` - Foundational conversion patterns (APTV workflow, testing strategies)
For general concepts like the Analyze → Plan → Transform → Validate workflow, testing strategies, and common pitfalls, see the meta-skill first.
## This Skill Adds
- **Type mappings**: Elm types → Haskell types
- **Idiom translations**: The Elm Architecture (TEA) → Haskell patterns
- **Error handling**: Elm Maybe/Result → Haskell Maybe/Either
- **Async patterns**: Elm Cmd/Sub → Haskell IO/concurrency
- **JSON handling**: Elm decoders/encoders → Aeson
## This Skill Does NOT Cover
- General conversion methodology - see `meta-convert-dev`
- Elm language fundamentals - see `lang-elm-dev`
- Haskell language fundamentals - see `lang-haskell-dev`
- Frontend frameworks - Elm's TEA is frontend-specific; backend alternatives vary
---
## Quick Reference
| Elm | Haskell | Notes |
|-----|---------|-------|
| `String` | `String` or `Text` | Use Text for production |
| `Int` | `Int` or `Integer` | Integer for unbounded |
| `Float` | `Double` | Default floating point |
| `Bool` | `Bool` | Direct mapping |
| `List a` | `[a]` | Direct mapping |
| `Maybe a` | `Maybe a` | Same type! |
| `Result err ok` | `Either err ok` | Swap order: Either Left Right |
| `type alias` | `type` or `data` with record | Similar syntax |
| `type` (union) | `data` | Same concept, similar syntax |
| `Cmd msg` | `IO ()` | Side effects |
| `Sub msg` | Event sources | Streams, STM, async |
| `Html msg` | No direct equivalent | Frontend-specific |
| `Json.Decode.Decoder a` | `FromJSON a` | Aeson instance |
| `Json.Encode.Value` | `ToJSON a` | Aeson instance |
## When Converting Code
1. **Analyze source thoroughly** before writing target
2. **Map types first** - Elm and Haskell are very similar
3. **Preserve semantics** over syntax similarity
4. **Adapt TEA patterns** - No direct equivalent; rethink architecture
5. **Handle Cmd/Sub** - Map to IO, concurrency, or events
6. **Test equivalence** - Same inputs → same outputs for pure logic
---
## Type System Mapping
### Primitive Types
| Elm | Haskell | Notes |
|-----|---------|-------|
| `String` | `String` | List of Char (inefficient) |
| `String` | `Text` | **Preferred** for production (from `Data.Text`) |
| `Int` | `Int` | Bounded integer (architecture-dependent) |
| `Int` | `Integer` | Unbounded (arbitrary precision) |
| `Float` | `Float` | Single precision |
| `Float` | `Double` | **Preferred** double precision |
| `Bool` | `Bool` | Direct mapping |
| `()` | `()` | Unit type |
| `Never` | - | No direct equivalent; use polymorphic types |
### Collection Types
| Elm | Haskell | Notes |
|-----|---------|-------|
| `List a` | `[a]` | Identical linked list |
| `Array a` | `Vector a` | Use `Data.Vector` for efficient arrays |
| `Set a` | `Set a` | Use `Data.Set` |
| `Dict k v` | `Map k v` | Use `Data.Map` |
| `( a, b )` | `(a, b)` | Tuple - identical |
| `( a, b, c )` | `(a, b, c)` | Tuples up to any size |
### Composite Types
| Elm | Haskell | Notes |
|-----|---------|-------|
| `type alias User = { name : String }` | `data User = User { name :: String }` | Record syntax |
| `type Msg = Click \| Input String` | `data Msg = Click \| Input String` | Union type / sum type |
| `Maybe a` | `Maybe a` | **Identical** |
| `Result err ok` | `Either err ok` | Same concept, **different order** (Left = error, Right = success) |
### Type Aliases vs Data
**Elm:**
```elm
-- Type alias: Just a synonym
type alias Point = { x : Float, y : Float }
-- Custom type: New type with constructors
type Shape = Circle Float | Rectangle Float Float
```
**Haskell:**
```haskell
-- Type synonym: Just an alias (no constructor)
type Point = (Double, Double)
-- Or with record syntax (creates constructor and accessors)
data Point = Point { x :: Double, y :: Double }
-- Custom type: Algebraic data type
data Shape = Circle Double | Rectangle Double Double
```
**Why this translation:**
- Elm's `type alias` for records creates a constructor; Haskell `type` does not
- Use Haskell `data` with record syntax for Elm record type aliases
- Union types map directly to Haskell algebraic data types
---
## Idiom Translation
### Pattern 1: Maybe Handling
**Elm:**
```elm
findUser : Int -> Maybe User
findUser id =
List.head (List.filter (\u -> u.id == id) users)
displayName : Maybe User -> String
displayName maybeUser =
case maybeUser of
Just user ->
user.name
Nothing ->
"Anonymous"
-- With pipeline
name =
findUser 1
|> Maybe.map .name
|> Maybe.withDefault "Anonymous"
```
**Haskell:**
```haskell
import Data.Maybe (fromMaybe, maybe, listToMaybe)
import Data.List (find)
findUser :: Int -> Maybe User
findUser userId = find (\u -> userId == id u) users
displayName :: Maybe User -> String
displayName maybeUser =
case maybeUser of
Just user -> name user
Nothing -> "Anonymous"
-- With applicative/functor
userName :: Maybe String
userName = name <$> findUser 1
userName' :: String
userName' = fromMaybe "Anonymous" (name <$> findUser 1)
```
**Why this translation:**
- Maybe is identical in both languages
- Elm's `Maybe.withDefault` = Haskell's `fromMaybe`
- Elm's `.field` accessor becomes Haskell function `field`
- Pattern matching syntax is nearly identical
### Pattern 2: Result/Either Error Handling
**Elm:**
```elm
type alias Error = String
parseAge : String -> Result Error Int
parseAge str =
case String.toInt str of
Just age ->
if age >= 0 then
Ok age
else
Err "Age must be non-negative"
Nothing ->
Err "Not a valid number"
validateUser : String -> String -> Result Error User
validateUser ageStr emailStr =
Result.andThen
(\age -> Result.map (User age) (validateEmail emailStr))
(parseAge ageStr)
```
**Haskell:**
```haskell
import Text.Read (readMaybe)
type Error = String
parseAge :: String -> Either Error Int
parseAge str =
case readMaybe str of
Just age ->
if age >= 0
then Right age
else Left "Age must be non-negative"
Nothing ->
Left "Not a valid number"
validateUser :: String -> String -> Either Error User
validateUser ageStr emailStr = do
age <- parseAge ageStr
email <- validateEmail emailStr
return $ User age email
-- Or with Applicative
validateUser' :: String -> String -> Either Error User
validateUser' ageStr emailStr =
User <$> parseAge ageStr <*> validateEmail emailStr
```
**Why this translation:**
- `Result err ok` maps to `Either err ok` (note: Left = error, Right = success)
- Elm's `Result.andThen` = Haskell's `>>=` (monadic bind)
- Haskell's do-notation is more concise for chaining
- Both support applicative style for independent validations
### Pattern 3: List Operations
**Elm:**
```elm
processNumbers : List Int -> Int
processNumbers numbers =
numbers
|> List.filter (\x -> x > 0)
|> List.map (\x -> x * 2)
|> List.foldl (+) 0
-- List comprehension (rare in Elm)
squares : List Int
squares =
List.map (\x -> x * x) (List.range 1 10)
```
**Haskell:**
```haskell
processNumbers :: [Int] -> Int
processNumbers numbers =
foldl (+) 0 $
map (*2) $
filter (>0) numbers
-- Or with function composition
processNumbers' :: [Int] -> Int
processNumbers' = foldl (+) 0 . map (*2) . filter (>0)
-- Or with pipeline using & (from Data.Function)
import Data.Function ((&))
processNumbers'' :: [Int] -> Int
processNumbers'' numbers =
numbers
& filter (>0)
& map (*2)
& foldl (+) 0
-- List comprehension (idiomatic in Haskell)
squares :: [Int]
squares = [x * x | x <- [1..10]]
```
**Why this translation:**
- List operations are nearly identical
- Elm's `|>` pipeline = Haskell's `&` (from Data.Function) or `$` (right-associative)
- Function composition (`.`) is more idiomatic in Haskell
- List comprehensions more common in Haskell than Elm
### Pattern 4: Pattern Matching and Case Expressions
**Elm:**
```elm
describeList : List a -> String
describeList list =
case list of
[] ->
"empty"
[ x ] ->
"singleton"
x :: xs ->
"list with multiple elements"
-- Destructuring in function parameters
head : List a -> Maybe a
head list =
case list of
[] -> Nothing
x :: _ -> Just x
```
**Haskell:**
```haskell
describeList :: [a] -> String
describeList list =
case list of
[] -> "empty"
[x] -> "singleton"
(x:xs) -> "list with multiple elements"
-- Pattern matching in function definition (more idiomatic)
describeList' :: [a] -> String
describeList' [] = "empty"
describeList' [x] = "singleton"
describeList' (x:xs) = "list with multiple elements"
-- Direct pattern matching for head
head' :: [a] -> Maybe a
head' [] = Nothing
head' (x:_) = Just x
```
**Why this translation:**
- Pattern matching is nearly identical
- Haskell allows pattern matching in function definitions (more concise)
- Syntax differences: `x :: xs` (Elm) vs `(x:xs)` (Haskell)
- Both support guards and nested patterns
### Pattern 5: Record Updates
**Elm:**
```elm
type alias User =
{ name : String
, age : Int
, email : String
}
updateAge : Int -> User -> User
updateAge newAge user =
{ user | age = newAge }
updateMultiple : User -> User
updateMultiple user =
{ user | age = user.age + 1, name = "Updated" }
```
**Haskell:**
```haskell
data User = User
{ name :: String
, age :: Int
, email :: String
} deriving (Show, Eq)
updateAge :: Int -> User -> User
updateAge newAge user = user { age = newAge }
updateMultiple :: User -> User
updateMultiple user = user
{ age = age user + 1
, name = "Updated"
}
```
**Why this translation:**
- Record update syntax is nearly identical
- Haskell requires parentheses for field access: `age user` vs Elm's `user.age`
- Both create new values (immutability)
### Pattern 6: Custom Types and Constructors
**Elm:**
```elm
type Msg
= NoOp
| Increment
| Decrement
| SetValue Int
| SetName String
type RemoteData error value
= NotAsked
| Loading
| Success value
| Failure error
```
**Haskell:**
```haskell
data Msg
= NoOp
| Increment
| Decrement
| SetValue Int
| SetName String
deriving (Show, Eq)
data RemoteData error value
= NotAsked
| Loading
| Success value
| Failure error
deriving (Show, Eq, Functor)
```
**Why this translation:**
- Syntax is identical
- Haskell allows deriving type classes (Show, Eq, Functor, etc.)
- Elm auto-derives equality; Haskell requires explicit `deriving Eq`
---
## The Elm Architecture → Haskell Patterns
### TEA Structure
**Elm's TEA:**
```elm
-- MODEL
type alias Model = { count : Int }
init : () -> ( Model, Cmd Msg )
init _ = ( { count = 0 }, Cmd.none )
-- UPDATE
type Msg = Increment | Decrement
update : Msg -> Model -> ( Model, Cmd Msg )
update msg model =
case msg of
Increment -> ( { model | count = model.count + 1 }, Cmd.none )
Decrement -> ( { model | count = model.count - 1 }, Cmd.none )
-- VIEW
view : Model -> Html Msg
view model =
div []
[ button [ onClick Decrement ] [ text "-" ]
, div [] [ text (String.fromInt model.count) ]
, button [ onClick Increment ] [ text "+" ]
]
```
**Haskell Equivalent (no direct frontend):**
For pure logic (testable):
```haskell
-- MODEL
data Model = Model { count :: Int } deriving (Show, Eq)
init :: Model
init = Model { count = 0 }
-- UPDATE
data Msg = Increment | Decrement deriving (Show, Eq)
update :: Msg -> Model -> Model
update msg model =
case msg of
Increment -> model { count = count model + 1 }
Decrement -> model { count = count model - 1 }
-- No VIEW in backend context
-- For testing or CLI:
renderModel :: Model -> String
renderModel model = "Count: " ++ show (count model)
```
For interactive CLI:
```haskell
import Control.Monad (forever)
import System.IO (hFlush, stdout)
-- REPL-style interaction
mainLoop :: Model -> IO ()
mainLoop model = forever $ do
putStrLn $ renderModel model
putStrLn "Commands: + (increment), - (decrement), q (quit)"
putStr "> "
hFlush stdout
input <- getLine
case input of
"+" -> mainLoop (update Increment model)
"-" -> mainLoop (update Decrement model)
"q" -> return ()
_ -> mainLoop model
main :: IO ()
main = mainLoop init
```
**Why this adaptation:**
- Elm's Model/Update pattern translates to pure state machines in Haskell
- `Cmd` becomes `IO` for side effects
- Frontend view logic has no direct backend equivalent
- For web: use Servant, Scotty, or Yesod with separate architecture
### Cmd and Effects
**Elm:**
```elm
type Msg = GotUsers (Result Http.Error (List User))
getUsers : Cmd Msg
getUsers =
Http.get
{ url = "https://api.example.com/users"
, expect = Http.expectJson GotUsers (Json.Decode.list userDecoder)
}
update : Msg -> Model -> ( Model, Cmd Msg )
update msg model =
case msg of
FetchUsers -> ( { model | loading = True }, getUsers )
GotUsers result -> ...
```
**Haskell:**
```haskell
import Network.HTTP.Simple
import Data.Aeson (FromJSON, eitherDecode)
data Msg = GotUsers (Either String [User]) deriving (Show)
getUsers :: IO (Either String [User])
getUsers = do
response <- httpLBS "https://api.example.com/users"
return $ eitherDecode (getResponseBody response)
-- In a real app, you'd use async or STM for event handling
handleMsg :: Msg -> Model -> IO Model
handleMsg msg model =
case msg of
GotUsers (Right users) -> return $ model { users = users, loading = False }
GotUsers (Left err) -> return $ model { error = Just err, loading = False }
-- Async version
import Control.Concurrent.Async
fetchUsersAsync :: (Msg -> IO ()) -> IO ()
fetchUsersAsync dispatch = do
result <- getUsers
dispatch (GotUsers result)
```
**Why this adaptation:**
- Elm's `Cmd` is a managed effect system; Haskell uses `IO` directly
- Elm runtime handles effect execution; Haskell requires explicit async/threading
- Consider using async, STM, or event libraries for complex state management
---
## JSON Handling
### JSON Decoders
**Elm:**
```elm
import Json.Decode as Decode exposing (Decoder)
import Json.Decode.Pipeline exposing (required, optional)
type alias User =
{ name : String
, email : String
, age : Int
}
userDecoder : Decoder User
userDecoder =
Decode.succeed User
|> required "name" Decode.string
|> required "email" Decode.string
|> required "age" Decode.int
```
**Haskell:**
```haskell
{-# LANGUAGE DeriveGeneric #-}
import Data.Aeson
import GHC.Generics
data User = User
{ name :: String
, email :: String
, age :: Int
} deriving (Generic, Show)
-- Automatic derivation (recommended)
instance FromJSON User
instance ToJSON User
-- Manual (for custom field names)
instance FromJSON User where
parseJSON = withObject "User" $ \v -> User
<$> v .: "name"
<*> v .: "email"
<*> v .: "age"
```
**Why this translation:**
- Elm requires explicit decoders; Haskell can auto-derive via `Generic`
- Elm's `Decode.Pipeline` ≈ Haskell's `Applicative` operators (`<$>`, `<*>`)
- Aeson is more concise for simple cases; Elm decoders are more explicit
### JSON Encoders
**Elm:**
```elm
import Json.Encode as Encode
encodeUser : User -> Encode.Value
encodeUser user =
Encode.object
[ ( "name", Encode.string user.name )
, ( "email", Encode.string user.email )
, ( "age", Encode.int user.age )
]
```
**Haskell:**
```haskell
import Data.Aeson
-- Automatic (if using Generic)
encodeUser :: User -> Value
encodeUser = toJSON
-- Manual
instance ToJSON User where
toJSON (User n e a) = object
[ "name" .= n
, "email" .= e
, "age" .= a
]
```
**Why this translation:**
- Both use object/record encoding
- Haskell's `.=` operator is more concise than Elm's tuple syntax
- Generics make simple cases trivial
---
## Concurrency Patterns
Elm uses `Cmd` and `Sub` for managed effects. Haskell requires explicit concurrency handling.
### Subscriptions → Event Streams
**Elm:**
```elm
subscriptions : Model -> Sub Msg
subscriptions model =
Sub.batch
[ Time.every 1000 Tick
, Browser.Events.onResize WindowResized
]
```
**Haskell (using async):**
```haskell
import Control.Concurrent (threadDelay, forkIO)
import Control.Concurrent.STM
import Control.Concurrent.Async
-- Event channel
type EventBus msg = TChan msg
-- Timer subscription
timerSub :: EventBus Msg -> IO ()
timerSub bus = forever $ do
threadDelay 1000000 -- 1 second
atomically $ writeTChan bus Tick
-- Main loop
mainWithSubs :: IO ()
mainWithSubs = do
eventBus <- newTChanIO
async $ timerSub eventBus
forever $ do
msg <- atomically $ readTChan eventBus
-- handle msg
return ()
```
**Why this adaptation:**
- Elm's subscriptions are declarative; Haskell requires imperative setup
- Use STM, async, or event libraries for similar patterns
- Consider libraries like `reactive-banana` for FRP-style event handling
---
## Common Pitfalls
### 1. Assuming Elm's Simplicity Limits Apply
**Problem:** Elm intentionally limits features (no type classes, no laziness control). Haskell has these features.
**Solution:**
- Use type classes for polymorphism (Eq, Show, Functor, etc.)
- Leverage lazy evaluation (but beware space leaks)
- Use advanced type system features when beneficial (GADTs, type families)
### 2. Direct Translation of TEA
**Problem:** The Elm Architecture is frontend-specific. Direct translation to Haskell backend makes no sense.
**Solution:**
- Extract pure business logic (Model + Update) - this translates directly
- Rethink effects: `Cmd` → IO, async, or STM
- For web backends: use Servant, Scotty, or Yesod patterns
### 3. Forgetting Field Accessor Syntax
**Problem:** Elm's `user.name` vs Haskell's `name user`.
**Elm:**
```elm
userName = user.name
```
**Haskell:**
```haskell
userName = name user -- Function application
```
**Solution:** Remember Haskell record fields are functions.
### 4. Result vs Either Argument Order
**Problem:** `Result err ok` vs `Either err ok` - **same order**, but different conventions.
**Elm:**
```elm
type Result error value = Err error | Ok value
```
**Haskell:**
```haskell
data Either a b = Left a | Right b
-- By convention: Left = error, Right = success
```
**Solution:**
- Elm `Ok x` → Haskell `Right x`
- Elm `Err e` → Haskell `Left e`
### 5. Missing Text Import
**Problem:** Using `String` instead of `Text` in production code.
**Solution:**
```haskell
import Data.Text (Text)
import qualified Data.Text as T
-- Use Text for all string data
data User = User { name :: Text } deriving (Show)
```
---
## Tooling
### Transpilers & Converters
| Tool | Direction | Status | Notes |
|------|-----------|--------|-------|
| `haskelm` | Haskell → Elm | Experimental | Template Haskell based |
| `haskell-to-elm` | Haskell → Elm | Active | Type + JSON codec generation |
| `elm-bridge` | Haskell ↔ Elm | Active | Bidirectional type sync |
| `elm-street` | Haskell → Elm | Active | Aeson-compatible codegen |
**Note:** Most tools focus on **Haskell → Elm** for full-stack apps. Manual conversion recommended for Elm → Haskell.
### Type Synchronization Libraries
For full-stack apps (Haskell backend + Elm frontend), these maintain type safety:
```haskell
-- haskell-to-elm example
{-# LANGUAGE DeriveGeneric #-}
import GHC.Generics
import Language.Elm.Pretty (pretty)
import qualified Language.Haskell.To.Elm as Elm
data User = User { name :: Text, age :: Int }
deriving (Generic, Elm.HasElmType, Elm.HasElmEncoder Aeson.Value, Elm.HasElmDecoder Aeson.Value)
-- Generates Elm type + JSON encoders/decoders
```
### Testing Strategy
```haskell
-- HSpec for behavior
import Test.Hspec
spec :: Spec
spec = describe "update function" $ do
it "increments count" $ do
let model = Model { count = 0 }
let result = update Increment model
count result `shouldBe` 1
-- QuickCheck for properties
import Test.QuickCheck
prop_updateIdempotent :: Msg -> Model -> Property
prop_updateIdempotent msg model =
update msg (update msg model) === update msg model
```
---
## Examples
### Example 1: Simple - Type Definitions and Functions
**Before (Elm):**
```elm
type alias Point =
{ x : Float
, y : Float
}
distance : Point -> Point -> Float
distance p1 p2 =
let
dx = p1.x - p2.x
dy = p1.y - p2.y
in
sqrt (dx * dx + dy * dy)
midpoint : Point -> Point -> Point
midpoint p1 p2 =
{ x = (p1.x + p2.x) / 2
, y = (p1.y + p2.y) / 2
}
```
**After (Haskell):**
```haskell
data Point = Point
{ x :: Double
, y :: Double
} deriving (Show, Eq)
distance :: Point -> Point -> Double
distance p1 p2 =
let dx = x p1 - x p2
dy = y p1 - y p2
in sqrt (dx * dx + dy * dy)
midpoint :: Point -> Point -> Point
midpoint p1 p2 = Point
{ x = (x p1 + x p2) / 2
, y = (y p1 + y p2) / 2
}
```
### Example 2: Medium - JSON and Error Handling
**Before (Elm):**
```elm
import Json.Decode as D
import Json.Encode as E
import Http
type alias Config =
{ apiUrl : String
, timeout : Maybe Int
}
configDecoder : D.Decoder Config
configDecoder =
D.map2 Config
(D.field "apiUrl" D.string)
(D.maybe (D.field "timeout" D.int))
encodeConfig : Config -> E.Value
encodeConfig config =
E.object
[ ( "apiUrl", E.string config.apiUrl )
, ( "timeout", Maybe.withDefault E.null (Maybe.map E.int config.timeout) )
]
type alias ApiError = String
loadConfig : String -> (Result ApiError Config -> msg) -> Cmd msg
loadConfig url toMsg =
Http.get
{ url = url
, expect = Http.expectJson toMsg configDecoder
}
```
**After (Haskell):**
```haskell
{-# LANGUAGE DeriveGeneric #-}
{-# LANGUAGE OverloadedStrings #-}
import Data.Aeson
import GHC.Generics
import Network.HTTP.Simple
import Data.Text (Text)
data Config = Config
{ apiUrl :: Text
, timeout :: Maybe Int
} deriving (Generic, Show, Eq)
instance FromJSON Config
instance ToJSON Config where
toJSON (Config url t) = object $
[ "apiUrl" .= url ] ++
maybe [] (\v -> ["timeout" .= v]) t
type ApiError = String
loadConfig :: String -> IO (Either ApiError Config)
loadConfig url = do
response <- httpLBS (parseRequest_ url)
return $ case eitherDecode (getResponseBody response) of
Right config -> Right config
Left err -> Left err
```
### Example 3: Complex - State Machine with Side Effects
**Before (Elm):**
```elm
type Model
= LoggedOut
| LoggingIn { username : String }
| LoggedIn { user : User, token : String }
| Error String
type Msg
= StartLogin String
| LoginSuccess User String
| LoginFailure String
| Logout
update : Msg -> Model -> ( Model, Cmd Msg )
update msg model =
case msg of
StartLogin username ->
( LoggingIn { username = username }
, performLogin username
)
LoginSuccess user token ->
( LoggedIn { user = user, token = token }
, Cmd.none
)
LoginFailure err ->
( Error err
, Cmd.none
)
Logout ->
case model of
LoggedIn _ ->
( LoggedOut, clearSession )
_ ->
( model, Cmd.none )
performLogin : String -> Cmd Msg
performLogin username =
Http.post
{ url = "/api/login"
, body = Http.jsonBody (E.object [ ( "username", E.string username ) ])
, expect = Http.expectJson
(\result ->
case result of
Ok { user, token } -> LoginSuccess user token
Err _ -> LoginFailure "Login failed"
)
loginResponseDecoder
}
```
**After (Haskell):**
```haskell
{-# LANGUAGE DeriveGeneric #-}
{-# LANGUAGE OverloadedStrings #-}
import Data.Aeson
import GHC.Generics
import Network.HTTP.Simple
import Data.Text (Text)
data Model
= LoggedOut
| LoggingIn { username :: Text }
| LoggedIn { user :: User, token :: Text }
| Error String
deriving (Show, Eq)
data Msg
= StartLogin Text
| LoginSuccess User Text
| LoginFailure String
| Logout
deriving (Show, Eq)
-- Pure update (no IO)
update :: Msg -> Model -> Model
update msg model =
case msg of
StartLogin username ->
LoggingIn { username = username }
LoginSuccess usr tok ->
LoggedIn { user = usr, token = tok }
LoginFailure err ->
Error err
Logout ->
case model of
LoggedIn _ -> LoggedOut
_ -> model
-- Effects handled separately
handleEffect :: Msg -> IO (Maybe Msg)
handleEffect (StartLogin username) = do
result <- performLogin username
return $ Just $ case result of
Right (usr, tok) -> LoginSuccess usr tok
Left err -> LoginFailure err
handleEffect Logout = do
clearSession
return Nothing
handleEffect _ = return Nothing
-- HTTP request
performLogin :: Text -> IO (Either String (User, Text))
performLogin username = do
let requestBody = object ["username" .= username]
response <- httpJSON $ setRequestBodyJSON requestBody $ parseRequest_ "/api/login"
return $ case getResponseBody response of
LoginResponse usr tok -> Right (usr, tok)
_ -> Left "Login failed"
clearSession :: IO ()
clearSession = putStrLn "Session cleared"
-- Main loop
mainLoop :: Model -> IO ()
mainLoop model = do
print model
-- Get user input, dispatch msg, handle effects
return ()
```
---
## Limitations
### Elm Features Not in Haskell
- **The Elm Architecture**: No direct equivalent; must design architecture per use case
- **Compiler guarantees**: Elm's "no runtime exceptions" doesn't apply (Haskell has partial functions)
- **Frontend-specific types**: `Html`, `Svg`, `Browser.Events` have no backend equivalents
### Haskell Features Not in Elm
- **Type classes**: Use for polymorphism (Elm uses explicit passing)
- **Lazy evaluation**: Can cause space leaks if not careful
- **Advanced types**: GADTs, type families, existentials
- **Partial functions**: `head`, `tail` can crash (use `Maybe` versions)
### Conversion Challenges
1. **TEA translation**: Requires rethinking application architecture
2. **Cmd/Sub**: No built-in runtime; must use async/STM/events
3. **Frontend UI**: No equivalent; backend conversion only makes sense for business logic
4. **JSON decoders**: More implicit in Haskell (Generics) vs explicit in Elm
---
## See Also
For more examples and patterns, see:
- `meta-convert-dev` - Foundational patterns with cross-language examples
- `lang-elm-dev` - Elm development patterns (TEA, JSON, types)
- `lang-haskell-dev` - Haskell development patterns (monads, type classes, concurrency)
- `convert-typescript-rust` - Similar pure functional language conversion
Cross-cutting pattern skills:
- `patterns-concurrency-dev` - Compare Elm's Cmd/Sub to Haskell's IO/STM/async
- `patterns-serialization-dev` - JSON decoders/encoders across languages
- `patterns-metaprogramming-dev` - Template Haskell vs Elm's limitations
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