PlyDtype

PlyDtype is a formal type descriptor used within the Ply data processing framework to describe the shape, constraints, and memory representation of values in Ply data streams and files. It serves as the bridge between data schemas and runtime validation, enabling type-safe ingestion, transformation, and serialization across components and languages.

Originating as part of the Ply specification for data interchange, PlyDtype is designed to be extensible and pluggable. It defines a hierarchy of types, from primitive builders such as integers and floating-point numbers to composite constructs like records, arrays, and unions. The goal is to provide a single, portable description that can be interpreted by different Ply runtimes without losing semantic meaning.

Key features of PlyDtype include explicit nullability, default values, and constraints (for example range checks or pattern matching). It supports both fixed and variable-length structures, versioned schemas for evolution, and the ability to declare optional fields and discriminated unions. PlyDtype descriptions can also specify memory layout hints to optimize zero-copy access when the producer and consumer share the same layout.

In practice, PlyDtype definitions are embedded in Ply schemas and used by validators, serializers, and data adapters. At runtime, PlyDtype enforces type correctness, guides data transformation, and optionally enables streaming processing for large datasets. The approach aims for interoperability across languages by using a common binary or text wire format.

Adoption and ecosystem: PlyDtype is employed in Ply data pipelines and allied tools, with community libraries providing validators, code generators, and schema editors. Its design emphasizes backward compatibility and clear error reporting to aid debugging and data governance.

Limitations: As a relatively new or niche feature, tooling and documentation can be uneven across projects. Complex or evolving schemas may require careful version management to avoid breaking consumers.

See also: Ply, data type system, schema evolution, serialization formats.