fp-data-transforms_skill

Overview

This skill teaches everyday data transformations using practical functional patterns: arrays, objects, grouping, aggregation, and null-safe access. It presents imperative examples then shows clearer, composable functional alternatives and honest trade-offs. The focus is on patterns that work in real TypeScript/Node.js projects, with fp-ts where it adds value.

How this skill works

The content inspects common tasks — map/filter/reduce, pick/omit/merge, deep merge, immutable updates, data normalization, grouping/aggregation, and null-safe access — and shows how to replace loops and mutation with expressive, composable functions. It illustrates utilities and fp-ts helpers (Option, Array, pipe) to make transformations safer and easier to test. Each pattern includes concise examples and when each approach is preferable.

When to use it

• Transform arrays (map/filter/reduce) for clear, single-responsibility steps.
• Reshape objects (pick/omit/merge) when removing sensitive fields or combining defaults.
• Normalize API responses into flat indexed state for efficient lookups and caching.
• Perform grouping and aggregation to compute summaries from lists of records.
• Apply null-safe access or Option types when nested values may be missing.
• Use fp-ts utilities when composition, type-safety, and error handling matter.

Best practices

• Prefer small, named functions for predicates and transforms to improve reuse and readability.
• Use spread and simple merge for shallow defaults; use targeted deep merge utilities for nested configs.
• Normalize server responses into byId/allIds shape to simplify updates and references.
• Favor immutable updates; adopt helper functions or libraries (immer, lenses) for deep nesting.
• Introduce Option/TaskEither from fp-ts for explicit null handling and async error flow.

Example use cases

• Convert raw API orders into normalized state with orders, customers, and products indices.
• Filter and map user lists to produce sorted lists of active premium customer names.
• Sanitize objects before logging by omitting sensitive keys with a reusable omit utility.
• Merge user settings with defaults and apply deep overrides for nested configuration.
• Safely access first element or lookup by index using fp-ts Option to avoid runtime errors.