2 个仓库
Parsing input that may arrive in multiple formats into a unified structure.
Distinct from Polymorphic Data Modeling: Distinct from Polymorphic Data Modeling: focuses on the deserialization logic for mixed-type input.
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This project is a framework for the efficient serialization and deserialization of data structures. It provides a unified, macro-based interface that automates the conversion of complex internal objects into standardized formats and reconstructs them from raw input streams or buffers. By leveraging compile-time code generation, the library minimizes manual implementation overhead while ensuring consistent logic across diverse data types. The framework distinguishes itself through a format-agnostic data model and a visitor-based parsing architecture that decouples data structures from specific
Parses input that may arrive as either a simple string or a complex object into a single unified data structure.
msgspec is a high-performance data modeling, serialization, and schema validation toolkit for Python. It serves as a type-safe serialization framework that integrates schema enforcement and data parsing into a single pass, functioning as both a data serialization library and a schema validation system based on standard Python type annotations. The project distinguishes itself through high-performance structural primitives, including compilation-based routine generation and zero-copy buffer parsing. It optimizes memory usage via garbage collection-aware layouts and reduces processing overhead
Maps input to the correct object representation using tags to distinguish between multiple types in a union.