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Provides TypeScript functional patterns for ADTs, discriminated unions, Result/Option types, branded types. Use for state machines, type-safe domain models, and error handling.
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Build reliable systems using Algebraic Data Types (ADTs), discriminated unions, Result/Option types, and branded types. These patterns enable the compiler to prove correctness, prevent runtime errors, and make illegal states unrepresentable.
Guides functional domain modeling in server-side TypeScript using discriminated unions, pure functions, Result types for domain models, use cases, repositories, state transitions, business logic.
Guides on advanced TypeScript patterns like conditional types, discriminated unions, branded types, and builders for type-safe APIs, domain models, and state machines.
Implements strict TypeScript practices: eliminates 'any' types with unknown guards, Zod validation, Result types, discriminated unions, branded types, and TS 5.5+ features.
Share bugs, ideas, or general feedback.
Build reliable systems using Algebraic Data Types (ADTs), discriminated unions, Result/Option types, and branded types. These patterns enable the compiler to prove correctness, prevent runtime errors, and make illegal states unrepresentable.
Reliability through types: Use the type system to encode business rules, making invalid states impossible to construct. The compiler becomes your safety net, catching errors at build time rather than runtime.
Key benefits:
For detailed patterns and examples, see:
Model "one of several variants" with exhaustive pattern matching:
type PaymentMethod =
| { kind: "card"; last4: string; brand: string }
| { kind: "ach"; accountNumber: string; routingNumber: string }
| { kind: "wallet"; provider: "apple" | "google" }
function processPayment(method: PaymentMethod): void {
switch (method.kind) {
case "card":
// TypeScript knows: method.last4 and method.brand exist
return processCard(method.last4, method.brand)
case "ach":
// TypeScript knows: method.accountNumber and method.routingNumber exist
return processACH(method.accountNumber, method.routingNumber)
case "wallet":
// TypeScript knows: method.provider exists
return processWallet(method.provider)
default:
assertNever(method) // Compiler error if cases missing
}
}
Explicit handling of "value may be absent":
type Option<T> = { _tag: "None" } | { _tag: "Some"; value: T }
function findUser(id: string): Option<User> {
const user = database.get(id)
return user ? Some(user) : None
}
const result = findUser("123")
switch (result._tag) {
case "Some":
console.log(result.value.name) // Type-safe access
break
case "None":
console.log("User not found")
break
}
Explicit error handling without exceptions:
type Result<T, E> = { _tag: "Ok"; value: T } | { _tag: "Err"; error: E }
function parseConfig(raw: string): Result<Config, ParseError> {
try {
const data = JSON.parse(raw)
return Ok(validateConfig(data))
} catch (e) {
return Err({ message: "Invalid JSON", cause: e })
}
}
const result = parseConfig(rawConfig)
switch (result._tag) {
case "Ok":
startServer(result.value)
break
case "Err":
logger.error(result.error.message)
break
}
Prevent unit confusion and invalid values:
type Brand<K, T> = K & { __brand: T }
type Cents = Brand<number, "Cents">
type Dollars = Brand<number, "Dollars">
const Cents = (n: number): Cents => {
if (!Number.isInteger(n) || n < 0) throw new Error("Invalid cents")
return n as Cents
}
const Dollars = (n: number): Dollars => {
if (n < 0) throw new Error("Invalid dollars")
return n as Dollars
}
// Compiler prevents mixing units:
const price: Cents = Cents(100)
const budget: Dollars = Dollars(10)
const total: Cents = price + budget // Type error! Cannot mix Cents and Dollars
null or undefined checksCopy these into your project to start using functional patterns:
// ============================================
// Option Type
// ============================================
type None = { _tag: "None" }
type Some<T> = { _tag: "Some"; value: T }
type Option<T> = None | Some<T>
const None: None = { _tag: "None" }
const Some = <T>(value: T): Option<T> => ({ _tag: "Some", value })
// Utilities
const isNone = <T>(opt: Option<T>): opt is None => opt._tag === "None"
const isSome = <T>(opt: Option<T>): opt is Some<T> => opt._tag === "Some"
const getOrElse = <T>(opt: Option<T>, defaultValue: T): T =>
opt._tag === "Some" ? opt.value : defaultValue
const map = <T, U>(opt: Option<T>, fn: (value: T) => U): Option<U> =>
opt._tag === "Some" ? Some(fn(opt.value)) : None
const flatMap = <T, U>(opt: Option<T>, fn: (value: T) => Option<U>): Option<U> =>
opt._tag === "Some" ? fn(opt.value) : None
// ============================================
// Result Type
// ============================================
type Ok<T> = { _tag: "Ok"; value: T }
type Err<E> = { _tag: "Err"; error: E }
type Result<T, E> = Ok<T> | Err<E>
const Ok = <T>(value: T): Result<T, never> => ({ _tag: "Ok", value })
const Err = <E>(error: E): Result<never, E> => ({ _tag: "Err", error })
// Utilities
const isOk = <T, E>(result: Result<T, E>): result is Ok<T> => result._tag === "Ok"
const isErr = <T, E>(result: Result<T, E>): result is Err<E> => result._tag === "Err"
const mapResult = <T, U, E>(result: Result<T, E>, fn: (value: T) => U): Result<U, E> =>
result._tag === "Ok" ? Ok(fn(result.value)) : result
const flatMapResult = <T, U, E>(
result: Result<T, E>,
fn: (value: T) => Result<U, E>
): Result<U, E> =>
result._tag === "Ok" ? fn(result.value) : result
// ============================================
// Exhaustiveness Checking
// ============================================
const assertNever = (x: never): never => {
throw new Error(`Unhandled variant: ${JSON.stringify(x)}`)
}
// ============================================
// Branded Types
// ============================================
type Brand<K, T> = K & { __brand: T }
// Example: Cents (integer cents to prevent floating point errors)
type Cents = Brand<number, "Cents">
const Cents = (n: number): Cents => {
if (!Number.isInteger(n)) throw new Error("Cents must be integer")
if (n < 0) throw new Error("Cents cannot be negative")
return n as Cents
}
// Example: Email (validated email address)
type Email = Brand<string, "Email">
const Email = (s: string): Email => {
if (!/^[^\s@]+@[^\s@]+\.[^\s@]+$/.test(s)) throw new Error("Invalid email")
return s as Email
}
// Example: Millis (timestamp in milliseconds)
type Millis = Brand<number, "Millis">
const Millis = (n: number): Millis => {
if (n < 0) throw new Error("Millis cannot be negative")
return n as Millis
}
Always use assertNever in default case for exhaustiveness checking:
switch (variant.kind) {
case "a": return handleA(variant)
case "b": return handleB(variant)
default: assertNever(variant) // Compiler error if cases missing
}
Use discriminant field consistently (kind, type, _tag):
// Good: consistent discriminant
type Result<T, E> = { _tag: "Ok"; value: T } | { _tag: "Err"; error: E }
// Avoid: mixing discriminants
type Bad = { kind: "a" } | { type: "b" } // Inconsistent!
Narrow types early to unlock type safety:
if (result._tag === "Ok") {
// TypeScript knows: result.value exists
return result.value.data
}
Use Option for expected absence:
function findUser(id: string): Option<User>
Use Result for recoverable errors:
function parseConfig(raw: string): Result<Config, ParseError>
Use exceptions for programmer errors:
function unreachable(message: string): never {
throw new Error(`Unreachable: ${message}`)
}
Validate in smart constructor:
const PositiveInt = (n: number): PositiveInt => {
if (!Number.isInteger(n) || n <= 0) throw new Error("Must be positive integer")
return n as PositiveInt
}
Use branded types for domain concepts:
type UserId = Brand<string, "UserId">
type OrderId = Brand<string, "OrderId">
// Compiler prevents: const userId: UserId = orderId
Prevent unit confusion:
type Seconds = Brand<number, "Seconds">
type Millis = Brand<number, "Millis">
// Compiler prevents: const s: Seconds = millis
Start small and expand:
Enable TypeScript strict mode flags:
strictNullChecks: true - Make nullability explicitnoImplicitReturns: true - Ensure all code paths returnstrictFunctionTypes: true - Safer function signaturestype TxnState =
| { kind: "pending"; createdAt: Millis }
| { kind: "settled"; ledgerId: string; settledAt: Millis }
| { kind: "failed"; reason: FailureReason; failedAt: Millis }
| { kind: "reversed"; originalLedgerId: string; reversedAt: Millis }
function canReverse(state: TxnState): boolean {
switch (state.kind) {
case "pending": return false
case "settled": return true
case "failed": return false
case "reversed": return false
default: assertNever(state)
}
}
type ConfigError = { field: string; message: string }
function parsePort(raw: unknown): Result<number, ConfigError> {
if (typeof raw !== "number") {
return Err({ field: "port", message: "must be number" })
}
if (raw < 1 || raw > 65535) {
return Err({ field: "port", message: "must be 1-65535" })
}
return Ok(raw)
}
type Cents = Brand<number, "Cents">
function addCents(a: Cents, b: Cents): Cents {
return Cents(a + b) // Smart constructor validates result
}
function calculateFee(amount: Cents, bps: number): Cents {
const feeAmount = Math.round((amount * bps) / 10000)
return Cents(feeAmount)
}
These patterns are inspired by Why Reliability Demands Functional Programming, ADTs, Safety and Critical Infrastructure by Rastrian. The blog post explores how functional programming techniques and Algebraic Data Types enable building reliable systems in critical infrastructure contexts.
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