Introduction

Adapters is a high-performance, developer-friendly, and schema-driven data validation, serialization, and transformation library designed for modern Rust.

By bridging the gap between dynamic formats (like JSON or raw key-value objects) and Rust's strictly typed domain models, Adapters allows you to validate dynamic data payloads before instantiation, serialize/deserialize with full bounds checking, and easily map types between different API boundaries.

Key Pillars of the Library

The library is designed around three distinct, yet highly interconnected layers:

  • Unified Schema & Validation Layer: Instead of validating data after parsing it into structured models (which can cause panics or silent errors on invalid types), Adapters defines a declarative, dynamic schema tree. Inbound payloads are verified at the dynamic level first, matching strict type names, number ranges, string lengths, custom regexes, and complex formats (e.g., Email or URLs).

  • High-Performance Serialization & Deserialization: Adapters implements a zero-dependency serialization and deserialization model. Every primitive type (including newly added char, i128, u128, and standard network addresses like IpAddr, Ipv4Addr, and Ipv6Addr), option, vector, and map is fully supported, allowing seamless, safe round-trips from dynamic values back into complex Rust structures.

  • Functional Data Transformation: Domain models often diverge between different contexts (e.g., Database Models vs. API Presentation Models). Using Pipeline and FieldMapper classes, you can map, rename, and transform data trees programmatically in a highly functional manner.

Why Use Adapters?

  • Zero-Dependency Core Parser: Comes with a built-in recursive-descent JSON engine, avoiding bloated dependencies and guaranteeing high compilation speed.
  • Detailed Error Accumulation: The validator evaluates all constraint rules rather than short-circuiting, gathering all errors across your nested fields into a comprehensive error list in a single pass.
  • Safe Native Numeric Types: Distinct floating-point and integer tracking prevents type coercion bugs before they make it into your business logic.
  • Ergonomic Macros: Instantly implement all necessary traits for your types using simple struct tags via the #[derive(Schema)] proc-macro.

Authors & Sponsorship

Adapters is maintained by Muhammad Fiaz.