effect-collections-datastructs

Value-based data structures use structural equality to compare data by content rather than identity. This Skill provides Data.struct and Equal APIs within Effect workflows, enabling predictable comparisons of structured data without reference checks, critical for pipelines that need reliable equality semantics.

Effect provides immutable collections including Chunk, HashSet, and tuple/array wrappers that maintain structural equality. This Skill exposes high-performance APIs for these data structures, allowing safe, value-based membership testing and data handling without mutation side effects.

HashSet membership operates on value-based semantics when paired with Equal implementations. This Skill enables structural equality for custom types, so HashSet correctly identifies members by content rather than object identity, supporting robust set operations in data pipelines.

Chunk abstracts sequential data into immutable segments with structural comparison support. This Skill provides the Chunk API and Equal integration, letting you safely compare, process, and pipeline chunked data without equality surprises in high-performance workflows.

Reference-based equality fails when pipelines need consistent behavior across equivalent data structures. This Skill solves that by providing immutable, value-based data structures—Data.struct, Data.tuple, Data.array—that guarantee predictable comparisons and structural equality throughout your Effect workflow.