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Haskell Anti-Patterns Overview

String Concatenation with ++

-- Anti-pattern: String concatenation with ++
buildMessage :: [String] -> String
buildMessage [] = ""
buildMessage (x:xs) = x ++ " " ++ buildMessage xs  -- O(n²) complexity

-- Better approach: Use a more efficient data structure
import Data.Text (Text)
import qualified Data.Text as T

buildMessage :: [Text] -> Text
buildMessage = T.intercalate (T.pack " ")

-- Or with String but using ShowS for efficiency
buildMessageS :: [String] -> String
buildMessageS xs = foldr (\x acc -> x ++ " " ++ acc) "" xs

Avoid using ++ for repeated string concatenation, as it has O(n²) complexity. Use more efficient data structures like Text or ByteString, or techniques like ShowS or Builder.

Partial Functions

-- Anti-pattern: Partial functions
headOfList :: [a] -> a
headOfList xs = head xs  -- Crashes on empty list

lookupValue :: Eq k => k -> [(k, v)] -> v
lookupValue k xs = fromJust (lookup k xs)  -- Crashes if key not found

-- Better approach: Return Maybe or Either
headOfList :: [a] -> Maybe a
headOfList [] = Nothing
headOfList (x:_) = Just x

lookupValue :: Eq k => k -> [(k, v)] -> Maybe v
lookupValue k xs = lookup k xs

Avoid partial functions like head, tail, fromJust, etc. that can crash on certain inputs. Instead, use pattern matching or return Maybe or Either to handle all possible cases.

Inefficient List Processing

-- Anti-pattern: Inefficient list processing
sumOfSquares :: [Int] -> Int
sumOfSquares xs = sum [x * x | x <- xs, x > 0]  -- Creates intermediate list

-- Better approach: Use foldr/foldl'
sumOfSquares :: [Int] -> Int
sumOfSquares = foldl' (\acc x -> if x > 0 then acc + x * x else acc) 0

Avoid creating intermediate lists when processing data. Use higher-order functions like foldr, foldl', or foldMap for more efficient processing.

Not Using Strictness Annotations

-- Anti-pattern: Not using strictness annotations
data Point = Point Double Double  -- Lazy fields

sumPoints :: [Point] -> Point
sumPoints points = foldl addPoints (Point 0 0) points
  where addPoints (Point x1 y1) (Point x2 y2) = Point (x1 + x2) (y1 + y2)

-- Better approach: Use strictness annotations
data Point = Point !Double !Double  -- Strict fields

sumPoints :: [Point] -> Point
sumPoints = foldl' addPoints (Point 0 0)
  where addPoints (Point x1 y1) (Point x2 y2) = Point (x1 + x2) (y1 + y2)

Use strictness annotations (!) for data fields that should be evaluated eagerly, especially in numeric computations, to avoid space leaks and improve performance.

Using String Instead of Text or ByteString

-- Anti-pattern: Using String for text processing
countLines :: String -> Int
countLines = length . lines

-- Better approach: Use Text or ByteString
import qualified Data.Text as T
import qualified Data.Text.IO as TIO

countLines :: T.Text -> Int
countLines = length . T.lines

main :: IO ()
main = do
  content <- TIO.readFile "file.txt"
  print $ countLines content

Avoid using String (which is a linked list of characters) for text processing. Use Text or ByteString for better performance with large text data.

Not Using Newtypes

-- Anti-pattern: Using type synonyms
type UserId = Int
type Username = String

lookupUser :: UserId -> IO (Maybe Username)
lookupUser uid = -- implementation

-- Prone to errors like this:
someFunction :: Username -> UserId -> IO ()
someFunction uid name = lookupUser name >>= -- Wrong order, but compiles!

-- Better approach: Use newtypes
newtype UserId = UserId Int deriving (Eq, Show)
newtype Username = Username String deriving (Eq, Show)

lookupUser :: UserId -> IO (Maybe Username)
lookupUser (UserId uid) = -- implementation

-- Now this won't compile:
someFunction :: Username -> UserId -> IO ()
someFunction name uid = lookupUser name -- Type error!

Use newtype instead of type for type aliases to get compile-time type checking and avoid mixing up values of the same underlying type but different semantic meanings.

Excessive Use of Point-Free Style

-- Anti-pattern: Excessive point-free style
processData :: [Int] -> [Int]
processData = map (*2) . filter (>0) . takeWhile (<100) . dropWhile (==0)

-- Better approach: More readable style
processData :: [Int] -> [Int]
processData xs = map (*2) $ filter (>0) $ takeWhile (<100) $ dropWhile (==0) xs

-- Or even clearer with named steps
processData :: [Int] -> [Int]
processData xs = map (*2) validNumbers
  where 
    withoutLeadingZeros = dropWhile (==0) xs
    numbersUnder100 = takeWhile (<100) withoutLeadingZeros
    validNumbers = filter (>0) numbersUnder100

Avoid excessive point-free style that makes code hard to read. Use named parameters and intermediate values when it improves clarity.

Not Using Record Syntax

-- Anti-pattern: Not using record syntax
data Person = Person String Int String

getName :: Person -> String
getName (Person name _ _) = name

getAge :: Person -> Int
getAge (Person _ age _) = age

getEmail :: Person -> String
getEmail (Person _ _ email) = email

-- Better approach: Use record syntax
data Person = Person 
  { name :: String
  , age :: Int
  , email :: String
  }

-- Now we get accessor functions for free
-- And can create/update records more clearly
updateEmail :: String -> Person -> Person
updateEmail newEmail person = person { email = newEmail }

Use record syntax for data types with multiple fields to get accessor functions for free and make field access more explicit and maintainable.

Not Using Language Extensions Appropriately

-- Anti-pattern: Not using helpful language extensions
data Maybe a = Nothing | Just a

instance Functor Maybe where
  fmap _ Nothing = Nothing
  fmap f (Just a) = Just (f a)

instance Applicative Maybe where
  pure = Just
  Nothing <*> _ = Nothing
  (Just f) <*> x = fmap f x

instance Monad Maybe where
  return = pure
  Nothing >>= _ = Nothing
  (Just a) >>= f = f a

-- Better approach: Use language extensions
{-# LANGUAGE DeriveFunctor, DeriveFoldable, DeriveTraversable #-}

data Maybe a = Nothing | Just a
  deriving (Functor, Foldable, Traversable)

-- Or even better with more extensions
{-# LANGUAGE DerivingStrategies, GeneralizedNewtypeDeriving #-}

newtype UserId = UserId Int
  deriving stock (Eq, Ord, Show)
  deriving newtype (Num, Enum)

Use appropriate language extensions like DeriveFunctor, RecordWildCards, or OverloadedStrings to make your code more concise and expressive.

Not Using Smart Constructors

-- Anti-pattern: Exposing constructors for invalid states
module Email (Email(..)) where

data Email = Email String

-- Client code can create invalid emails
invalidEmail = Email "not-an-email"

-- Better approach: Use smart constructors
module Email (Email, mkEmail, emailAddress) where

data Email = Email String

emailAddress :: Email -> String
emailAddress (Email addr) = addr

mkEmail :: String -> Maybe Email
mkEmail addr
  | isValidEmail addr = Just (Email addr)
  | otherwise = Nothing

isValidEmail :: String -> Bool
isValidEmail = -- validation logic

Use smart constructors to ensure that invalid states cannot be represented. Hide data constructors and expose only functions that create valid values.

Using IO Unnecessarily

-- Anti-pattern: Using IO unnecessarily
calculateTotal :: [Double] -> IO Double
calculateTotal prices = do
  let subtotal = sum prices
  let tax = subtotal * 0.1
  let total = subtotal + tax
  return total  -- No IO needed here

-- Better approach: Pure function
calculateTotal :: [Double] -> Double
calculateTotal prices = subtotal + tax
  where
    subtotal = sum prices
    tax = subtotal * 0.1

Keep functions pure (without IO) whenever possible. Only use the IO monad when you actually need to perform input/output operations.

Not Using Appropriate Monads

-- Anti-pattern: Explicit error handling everywhere
processItem :: Item -> Either Error Result

processItems :: [Item] -> Either Error [Result]
processItems [] = Right []
processItems (x:xs) = case processItem x of
  Left err -> Left err
  Right result -> case processItems xs of
    Left err -> Left err
    Right results -> Right (result : results)

-- Better approach: Use appropriate monads
import Control.Monad.Except

processItem :: Item -> Either Error Result

processItems :: [Item] -> Either Error [Result]
processItems items = forM items processItem

-- Or with different monads for different concerns
import Control.Monad.Reader
import Control.Monad.Except

processItem :: ReaderT Config (ExceptT Error IO) Result

Use appropriate monads and monad transformers for different concerns like error handling (Either, ExceptT), configuration (Reader), or state (State).

Not Using Lenses for Deep Updates

-- Anti-pattern: Manual nested record updates
data Address = Address { street :: String, city :: String, zipCode :: String }
data Person = Person { name :: String, age :: Int, address :: Address }

updateZipCode :: String -> Person -> Person
updateZipCode newZip person =
  person { address = (address person) { zipCode = newZip } }

-- Better approach: Use lenses
{-# LANGUAGE TemplateHaskell #-}
import Control.Lens

data Address = Address { _street :: String, _city :: String, _zipCode :: String }
data Person = Person { _name :: String, _age :: Int, _address :: Address }

makeLenses ''Address
makeLenses ''Person

updateZipCode :: String -> Person -> Person
updateZipCode newZip = address.zipCode .~ newZip

Use lenses (e.g., from the lens package) for working with nested data structures, especially when you need to update deeply nested fields.

Not Using Type Classes Appropriately

-- Anti-pattern: Duplicated functionality
serializeToJSON :: User -> String
serializeToJSON user = -- implementation

serializeToJSON :: Product -> String
serializeToJSON product = -- implementation

-- Better approach: Use type classes
class ToJSON a where
  toJSON :: a -> String

instance ToJSON User where
  toJSON user = -- implementation

instance ToJSON Product where
  toJSON product = -- implementation

-- Now we can write generic functions
saveToFile :: ToJSON a => FilePath -> a -> IO ()
saveToFile path obj = writeFile path (toJSON obj)

Use type classes to define common interfaces for different types, enabling polymorphic functions and reducing code duplication.

Not Using Proper Error Messages

-- Anti-pattern: Poor error messages
parseConfig :: String -> Config
parseConfig str = case decode str of
  Nothing -> error "Parse failed"  -- Unhelpful message
  Just config -> config

-- Better approach: Descriptive errors
parseConfig :: String -> Either String Config
parseConfig str = case decode str of
  Nothing -> Left $ "Failed to parse config: " ++ str
  Just config -> Right config

-- Even better with custom error types
data ConfigError = InvalidFormat String | MissingField String | InvalidValue String String
  deriving Show

parseConfig :: String -> Either ConfigError Config

Provide descriptive error messages and use structured error types. Avoid using error or undefined in production code.

Using Lazy I/O

-- Anti-pattern: Lazy I/O
processFile :: FilePath -> IO ()
processFile path = do
  contents <- readFile path  -- Lazy I/O
  let lines = lines contents
  -- Process lines
  -- File might still be open here!

-- Better approach: Strict I/O or streaming
import qualified Data.ByteString as BS

processFile :: FilePath -> IO ()
processFile path = do
  contents <- BS.readFile path  -- Strict I/O
  let lines = BS.split 10 contents  -- Split on newline
  -- Process lines
  -- File is definitely closed here

-- Or using streaming libraries
import Streaming.Prelude as S
import qualified Streaming.ByteString as SB

processFile :: FilePath -> IO ()
processFile path = SB.readFile path
  & SB.lines
  & S.map processLine
  & S.stdoutLn

Avoid lazy I/O which can lead to resource leaks and unpredictable performance. Use strict I/O or streaming libraries instead.

Not Using Proper Project Structure

-- Anti-pattern: Everything in one file
-- Main.hs with thousands of lines

-- Better approach: Modular project structure
-- src/
--   MyApp/
--     Types.hs
--     Database.hs
--     API.hs
--     Utils.hs
--   Main.hs

Organize your code into modules with clear responsibilities. Follow a consistent project structure to make your codebase more maintainable.

Not Using Proper Dependency Management

-- Anti-pattern: Manual dependency management
-- Copying code from other projects
-- Using globally installed packages

-- Better approach: Use Cabal or Stack
-- package.yaml (for Stack)
name: my-project
version: 0.1.0.0
dependencies:
  - base >= 4.7 && < 5
  - text
  - aeson
  - containers
library:
  source-dirs: src
executables:
  my-project-exe:
    main: Main.hs
    source-dirs: app
    dependencies:
      - my-project
tests:
  my-project-test:
    main: Spec.hs
    source-dirs: test
    dependencies:
      - my-project
      - hspec

Use proper dependency management tools like Cabal or Stack to manage your project’s dependencies and build process.

Not Using Proper Testing

-- Anti-pattern: Manual testing or no testing
main = do
  let result = myFunction 42
  print result  -- Manual check

-- Better approach: Use testing frameworks
import Test.Hspec
import Test.QuickCheck

main :: IO ()
main = hspec $ do
  describe "myFunction" $ do
    it "returns correct result for specific input" $ do
      myFunction 42 `shouldBe` expectedResult
    
    it "satisfies key property" $ property $
      \x -> myFunction x >= 0  -- Property-based test

Write proper tests using frameworks like HUnit, Hspec, or QuickCheck. Use property-based testing when appropriate.

Not Using Proper Documentation

-- Anti-pattern: Poor or no documentation
processData :: [a] -> [a]
processData xs = -- implementation

-- Better approach: Proper documentation
-- | Process a list of items according to business rules.
-- The function filters out invalid items and transforms the rest.
--
-- >>> processData [1, 2, 3, 4]
-- [2, 4, 6, 8]
--
-- >>> processData []
-- []
processData :: [a] -> [a]
processData xs = -- implementation

Document your code with Haddock comments. Include descriptions, examples, and edge cases to help users understand how to use your functions.

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