skills/fp-data-transforms/SKILL.md
Everyday data transformations using functional patterns - arrays, objects, grouping, aggregation, and null-safe access
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This skill covers the data transformations you do every day: working with arrays, reshaping objects, normalizing API responses, grouping data, and safely accessing nested values. Each section shows the imperative approach first, then the functional equivalent, with honest assessments of when each approach shines.
Array operations are the bread and butter of data transformation. Let's replace verbose loops with expressive, chainable operations.
The Task: Convert an array of prices from cents to dollars.
const pricesInCents = [999, 1499, 2999, 4999];
function convertToDollars(prices: number[]): number[] {
const result: number[] = [];
for (let i = 0; i < prices.length; i++) {
result.push(prices[i] / 100);
}
return result;
}
const dollars = convertToDollars(pricesInCents);
// [9.99, 14.99, 29.99, 49.99]
const pricesInCents = [999, 1499, 2999, 4999];
const toDollars = (cents: number): number => cents / 100;
const dollars = pricesInCents.map(toDollars);
// [9.99, 14.99, 29.99, 49.99]
Why functional is better here: The intent is immediately clear. map says "transform each element." The transformation logic (toDollars) is named and reusable. No index management, no manual array building.
The Task: Get all active users from a list.
interface User {
id: string;
name: string;
isActive: boolean;
}
function getActiveUsers(users: User[]): User[] {
const result: User[] = [];
for (const user of users) {
if (user.isActive) {
result.push(user);
}
}
return result;
}
const isActive = (user: User): boolean => user.isActive;
const activeUsers = users.filter(isActive);
// Or inline for simple predicates
const activeUsers = users.filter(user => user.isActive);
Why functional is better here: The predicate (isActive) is separated from the iteration logic. You can reuse, test, and compose predicates independently.
The Task: Calculate the total price of items in a cart.
interface CartItem {
name: string;
price: number;
quantity: number;
}
function calculateTotal(items: CartItem[]): number {
let total = 0;
for (const item of items) {
total += item.price * item.quantity;
}
return total;
}
const calculateTotal = (items: CartItem[]): number =>
items.reduce(
(total, item) => total + item.price * item.quantity,
0
);
// Or break out the line total calculation
const lineTotal = (item: CartItem): number => item.price * item.quantity;
const calculateTotal = (items: CartItem[]): number =>
items.map(lineTotal).reduce((a, b) => a + b, 0);
Honest assessment: For simple sums, the imperative loop is actually quite readable. The functional version shines when you need to compose the accumulation with other transformations, or when the reduction logic is complex enough to benefit from being named.
The Task: Get the names of all active premium users, sorted alphabetically.
interface User {
id: string;
name: string;
isActive: boolean;
tier: 'free' | 'premium';
}
function getActivePremiumNames(users: User[]): string[] {
const result: string[] = [];
for (const user of users) {
if (user.isActive && user.tier === 'premium') {
result.push(user.name);
}
}
result.sort((a, b) => a.localeCompare(b));
return result;
}
const getActivePremiumNames = (users: User[]): string[] =>
users
.filter(user => user.isActive)
.filter(user => user.tier === 'premium')
.map(user => user.name)
.sort((a, b) => a.localeCompare(b));
// Or with named predicates for reuse
const isActive = (user: User): boolean => user.isActive;
const isPremium = (user: User): boolean => user.tier === 'premium';
const getName = (user: User): string => user.name;
const alphabetically = (a: string, b: string): number => a.localeCompare(b);
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