Coding/Learn/haskell/haskell higher order functions
Learn Haskell & Pure Functional Programming
01.Introduction to Haskell & GHC
02.Syntax, Comments & Program Layout
03.Basic Types & Immutability
04.Arithmetic, Precedence & Infix Functions
05.Strings, Lists & the Cons Operator (:)
06.Booleans, Equality & Logical Operators
07.Conditional Expressions (if then else)
08.Function Guards (| condition = result)
09.Pattern Matching on Functions
10.Case Expressions (case of)
11.Local Bindings with let ... in
12.Auxiliary Bindings with where Clauses
13.Function Signatures & Referential Transparency
14.Currying & Partial Function Application
15.Anonymous Lambda Expressions (\x -> expr)
16.Higher-Order Functions: map, filter, foldl & foldr
17.Function Composition (.) & Application ($)
18.Recursion Patterns & Tail Recursion
19.Tuples & Pair Operations (fst, snd)
20.List Functions: head, tail, take, drop & null
21.Arithmetic Sequences & List Ranges
22.List Comprehensions
23.Zipping & Combining Lists (zip, zipWith)
24.Lazy Evaluation & Infinite Streams
25.Type Inference & Type Variables
26.Standard Typeclasses: Eq, Ord, Show & Num
27.Defining Custom Typeclasses & Instances
28.Type Synonyms (type) & newtype Wrappers
29.Algebraic Data Types (data ADT)
30.Record Syntax & Named Fields
31.The Maybe Type & Null Safety
32.The Either Type for Detailed Errors
33.Pattern Matching on Maybe & Either
34.Domain Errors & Validation Pipelines
35.Recursive Data Structures: Binary Trees
36.Strictness, seq & Bang Patterns (!)
37.The Functor Typeclass & fmap (<$>)
38.Applicative Functors: pure & (<*>)
39.The Monad Typeclass & Bind Operator (>>=)
40.Do Notation & Monadic Desugaring
41.The Three Monad Laws
42.Monadic Utilities: sequence, mapM, forM & when
43.The IO Monad & Pure/Impure Separation
44.File I/O: Reading & Writing Files
45.Modules, Exports & Qualified Imports
46.Monad Transformers: Reader, Writer & State
47.Concurrency, forkIO & MVars
48.Property-Based Testing with QuickCheck
49.Unit Testing & Test Suites (HUnit / Hspec)
50.Monadic Parsing & Parser Combinators
51.Production Architecture: Cabal & Stack
52.Comprehensive Functional Practice Challenges
53.Final Knowledge Assessment Quiz
54.Capstone Project: Domain Expression Evaluator & AST Engine
55.Verified Haskell Developer Certificate
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LearnHigher-Order Functions: map, filter, foldl & foldr
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Lesson 16 of 55
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Higher-Order Functions: map, filter, foldl & foldr

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In Plain English

Higher-order functions take or return other functions. Master map (transformation), filter (selection), foldl (tail-recursive left reduction), and foldr (lazy right reduction).

Deep Dive: How It Works

map: map f xs applies f to each item in xs.

filter: filter p xs keeps elements satisfying predicate p.

foldl vs foldr: foldl reduces from left to right (accumulator first); foldr reduces from right to left and can work on infinite lists when lazy.

sum and product: sum = foldl (+) 0 and product = foldl (*) 1.

PointCore Rules to Remember

Point star
foldl & foldr: Universal reduction primitives that generalize all list processing algorithms.
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Lazy foldr: foldr can short-circuit and terminate even on infinite lists.

Live Interactive Example

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Folds, Map, and Filter Pipeline
Python 3.12
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Output Console
Click "Run Code" to view the rendered output.
How it works: filter even gives [2, 4, 6] -> map (^2) gives [4, 16, 36] -> foldl (+) gives 56.

Your Turn: Micro Challenge

No pressure! Edit the starter code below and test your solution with instant feedback.

Micro Exercise

Compute Product with foldl

  • PointCompute `foldl (*) 1 [1, 2, 3, 4, 5]` and print `"Product: "` followed by its `show` string.
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Sandbox Output
Click "Run & Check" to test your solution.

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