From python
Models state machines, discriminated unions, Result/Option types, and branded types in TypeScript for type-safe domain modeling.
How this skill is triggered — by the user, by Claude, or both
Slash command
/python:typescript-functional-patternsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
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.
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.
This skill automatically loads when discussing:
npx claudepluginhub martinffx/atelier --plugin codeProvides advanced TypeScript patterns for type design with discriminated unions and branded types, Zod runtime validation, Result-based error handling, and monorepo configuration with Turborepo/Nx/pnpm.
Guides server-side TypeScript domain modeling with discriminated unions, pure state transitions, Result types, schema-validated boundaries, and PII protection. Triggers on business logic types, use cases, repositories, and error handling.
Teaches practical fp-ts patterns in TypeScript: pipe for chaining, Option for nulls, Either for errors. Use for cleaner functional code without jargon.