Pragmatic Functional Programming

Read this first. This guide cuts through the academic jargon and shows you what actually matters. No category theory. No abstract nonsense. Just patterns that make your code better.

When to Use This Skill

• When starting with fp-ts and need practical guidance
• When writing TypeScript code that handles nullable values, errors, or async operations
• When you want cleaner, more maintainable functional code without the academic overhead
• When refactoring imperative code to functional style

The Golden Rule

If functional programming makes your code harder to read, don't use it.

FP is a tool, not a religion. Use it when it helps. Skip it when it doesn't.

The 80/20 of FP

These five patterns give you most of the benefits. Master these before exploring anything else.

1. Pipe: Chain Operations Clearly

Instead of nesting function calls or creating intermediate variables, chain operations in reading order.

import { pipe } from 'fp-ts/function'

// Before: Hard to read (inside-out)
const result = format(validate(parse(input)))

// Before: Too many variables
const parsed = parse(input)
const validated = validate(parsed)
const result = format(validated)

// After: Clear, linear flow
const result = pipe(
  input,
  parse,
  validate,
  format
)

When to use pipe:

• 3+ transformations on the same data
• You find yourself naming throwaway variables
• Logic reads better top-to-bottom

When to skip pipe:

• Just 1-2 operations (direct call is fine)
• The operations don't naturally chain

2. Option: Handle Missing Values Without null Checks

Stop writing if (x !== null && x !== undefined) everywhere.

import * as O from 'fp-ts/Option'
import { pipe } from 'fp-ts/function'

// Before: Defensive null checking
function getUserCity(user: User | null): string {
  if (user === null) return 'Unknown'
  if (user.address === null) return 'Unknown'
  if (user.address.city === null) return 'Unknown'
  return user.address.city
}

// After: Chain through potential missing values
const getUserCity = (user: User | null): string =>
  pipe(
    O.fromNullable(user),
    O.flatMap(u => O.fromNullable(u.address)),
    O.flatMap(a => O.fromNullable(a.city)),
    O.getOrElse(() => 'Unknown')
  )

Plain language translation:

• O.fromNullable(x) = "wrap this value, treating null/undefined as 'nothing'"
• O.flatMap(fn) = "if we have something, apply this function"
• O.getOrElse(() => default) = "unwrap, or use this default if nothing"

3. Either: Make Errors Explicit

Stop throwing exceptions for expected failures. Return errors as values.

import * as E from 'fp-ts/Either'
import { pipe } from 'fp-ts/function'

// Before: Hidden failure mode
function parseAge(input: string): number {
  const age = parseInt(input, 10)
  if (isNaN(age)) throw new Error('Invalid age')
  if (age < 0) throw new Error('Age cannot be negative')
  return age
}

// After: Errors are visible in the type
function parseAge(input: string): E.Either<string, number> {
  const age = parseInt(input, 10)
  if (isNaN(age)) return E.left('Invalid age')
  if (age < 0) return E.left('Age cannot be negative')
  return E.right(age)
}

// Using it
const result = parseAge(userInput)
if (E.isRight(result)) {
  console.log(`Age is ${result.right}`)
} else {
  console.log(`Error: ${result.left}`)
}

Plain language translation:

• E.right(value) = "success with this value"
• E.left(error) = "failure with this error"
• E.isRight(x) = "did it succeed?"

4. Map: Transform Without Unpacking

Transform values inside containers without extracting them first.

import * as O from 'fp-ts/Option'
import * as E from 'fp-ts/Either'
import * as A from 'fp-ts/Array'
import { pipe } from 'fp-ts/function'

// Transform inside Option
const maybeUser: O.Option<User> = O.some({ name: 'Alice', age: 30 })
const maybeName: O.Option<string> = pipe(
  maybeUser,
  O.map(user => user.name)
)

// Transform inside Either
const result: E.Either<Error, number> = E.right(5)
const doubled: E.Either<Error, number> = pipe(
  result,
  E.map(n => n * 2)
)

// Transform arrays (same concept!)
const numbers = [1, 2, 3]
const doubled = pipe(
  numbers,
  A.map(n => n * 2)
)

5. FlatMap: Chain Operations That Might Fail

When each step might fail, chain them together.

import * as E from 'fp-ts/Either'
import { pipe } from 'fp-ts/function'

const parseJSON = (s: string): E.Either<string, unknown> =>
  E.tryCatch(() => JSON.parse(s), () => 'Invalid JSON')

const extractEmail = (data: unknown): E.Either<string, string> => {
  if (typeof data === 'object' && data !== null && 'email' in data) {
    return E.right((data as { email: string }).email)
  }
  return E.left('No email field')
}

const validateEmail = (email: string): E.Either<string, string> =>
  email.includes('@') ? E.right(email) : E.left('Invalid email format')

// Chain all steps - if any fails, the whole thing fails
const getValidEmail = (input: string): E.Either<string, string> =>
  pipe(
    parseJSON(input),
    E.flatMap(extractEmail),
    E.flatMap(validateEmail)
  )

// Success path: Right('user@example.com')
// Any failure: Left('specific error message')

Plain language: flatMap means "if this succeeded, try the next thing"

When NOT to Use FP

Functional programming is not always the answer. Here's when to keep it simple.

Simple Null Checks

// Just use optional chaining - it's built into the language
const city = user?.address?.city ?? 'Unknown'

// DON'T overcomplicate it
const city = pipe(
  O.fromNullable(user),
  O.flatMap(u => O.fromNullable(u.address)),
  O.flatMap(a => O.fromNullable(a.city)),
  O.getOrElse(() => 'Unknown')
)

Simple Loops

// A for loop is fine when you need early exit or complex logic
function findFirst(items: Item[], predicate: (i: Item) => boolean): Item | null {
  for (const item of items) {
    if (predicate(item)) return item
  }
  return null
}

// DON'T force FP when it doesn't help
const result = pipe(
  items,
  A.findFirst(predicate),
  O.toNullable
)

Performance-Critical Code

// For hot paths, imperative is faster (no intermediate arrays)
function sumLarge(numbers: number[]): number {
  let sum = 0
  for (let i = 0; i < numbers.length; i++) {
    sum += numbers[i]
  }
  return sum
}

// fp-ts creates intermediate structures
const sum = pipe(numbers, A.reduce(0, (acc, n) => acc + n))

When Your Team Doesn't Know FP

If you're the only one who can read the code, it's not good code.

// If your team knows this pattern
async function getUser(id: string): Promise<User | null> {
  try {
    const response = await fetch(`/api/users/${id}`)
    if (!response.ok) return null
    return await response.json()
  } catch {
    return null
  }
}

// Don't force this on them
const getUser = (id: string): TE.TaskEither<Error, User> =>
  pipe(
    TE.tryCatch(() => fetch(`/api/users/${id}`), E.toError),
    TE.flatMap(r => r.ok ? TE.right(r) : TE.left(new Error('Not found'))),
    TE.flatMap(r => TE.tryCatch(() => r.json(), E.toError))
  )

Quick Wins: Easy Changes That Improve Code Today

1. Replace Nested Ternaries with pipe + fold

// Before: Nested ternary nightmare
const message = user === null
  ? 'No user'
  : user.isAdmin
    ? `Admin: ${user.name}`
    : `User: ${user.name}`

// After: Clear case handling
const message = pipe(
  O.fromNullable(user),
  O.fold(
    () => 'No user',
    (u) => u.isAdmin ? `Admin: ${u.name}` : `User: ${u.name}`
  )
)

2. Replace try-catch with tryCatch

// Before: try-catch everywhere
let config
try {
  config = JSON.parse(rawConfig)
} catch {
  config = defaultConfig
}

// After: One-liner
const config = pipe(
  E.tryCatch(() => JSON.parse(rawConfig), () => 'parse error'),
  E.getOrElse(()