tsentials/record

To transform object lookup tables functionally, you can filter plain object maps by applying predicate functions to exclude unwanted fields and return deterministic derived subsets without writing imperative loops.

Mapping object values while remapping keys is done by passing mapper functions that define new key-value pairs, allowing you to convert lookup tables into new view models and derived shapes deterministically.

Partitioning objects based on predicates splits a plain object map into separate grouped results, enabling you to compute aggregates and divisions for reporting and business logic requirements.

Yes, you can select or exclude fields from objects using mutation-style utilities like pick and omit, which handle upsert, remove, and select operations to produce derived objects without manual loop boilerplate.

Yes, this approach requires a plain object input and predicate or mapper functions to operate, applying deterministic functional query, map, filter, and reduce operations to shape the data into new outputs.

You should use functional object utilities when converting lookup tables to view models, selecting or excluding fields, or computing aggregates, as it avoids error-prone imperative boilerplate and ensures deterministic transformed outputs.