Advanced Lambda Concepts
Master powerful functional programming patterns and advanced optimizations in Lambda.
Monad Transformers
Stackable Effects
Combine error handling with state management using monad transformers:
const StateMaybe = new StateTransformer(Maybe);
const safeCounter = StateMaybe.of(0)
.map(state => state + 1);
safeCounter.run();
// { state: 1, value: Maybe.Just(1) }
Functor Composition
Map Over Nested Structures
Array(Future(Maybe).of(5))
.map(x => x * 2)
.get(); // Returns 10 or null
Contravariant Functors
const validator = contramap(parseInt)
.compose(String)
.contramap(Date.parse);
📘 Applicative Functors
-
Parallel Validation:
validateUser
andvalidatePassword
can be executed concurrently. - Non-Empty Results: Always returns an array of errors, even if none exist.
- Type-safe Validation: Built-in type guards ensure only valid data is processed.
const ValidationApplicative = Applicative.of(validate);
const validateForm = Applicative.liftA2(
(credentials) => credentials,
ValidationApplicative("email", emailVal),
ValidationApplicative("password", passwordVal)
);
🔍 Lens Combinators
Access Deep Nested Data
const userLens = lens(['profile', 'settings']);
const newUserValue = set(userLens, { theme: 'dark' }, state);
Immutable Updates
const updated = over(
lensPath(['data', 'items']),
item => ({ ...item, status: 'processed' }),
original
);
Validation
const emailLens = lensProp('email');
const validateEmail = compose(
view(emailLens),
formatValidationResult
);
⚡ Performance Optimizations
Smart Memoization
Caches function results based on input types:
const optimizedMap = memoizeWith(
(fn, arr) => typeKey(fn) + hashArray(arr)
);
Tail Recursion Optimization
Prevents stack overflows in complex chains:
const trReduce = (fn, acc, arr) => {
if (arr.length === 0) return acc;
return trReduce(fn, fn(acc, arr[0]), arr.slice(1));
};
Lazy Evaluation
Delay computation until necessary:
const lazy = deferral(() => {
const startTime = Date.now();
while (Date.now() - startTime < 1000) {}
return "Computed Value";
});