jspg/GEMINI.md

JSPG: JSON Schema Postgres

JSPG is a high-performance PostgreSQL extension for in-memory JSON Schema validation, specifically targeting Draft 2020-12.

It is designed to serve as the validation engine for the "Punc" architecture, where the database is the single source of truth for all data models and API contracts.

🎯 Goals

1. Draft 2020-12 Compliance: Attempt to adhere to the official JSON Schema Draft 2020-12 specification.
2. Ultra-Fast Validation: Compile schemas into an optimized in-memory representation for near-instant validation during high-throughput workloads.
3. Connection-Bound Caching: Leverage the PostgreSQL session lifecycle to maintain a per-connection schema cache, eliminating the need for repetitive parsing.
4. Structural Inheritance: Support object-oriented schema design via Implicit Keyword Shadowing and virtual .family schemas.
5. Punc Integration: validation is aware of the "Punc" context (request/response) and can validate cue objects efficiently.

🔌 API Reference

The extension exposes the following functions to PostgreSQL:

cache_json_schemas(enums jsonb, types jsonb, puncs jsonb) -> jsonb

Loads and compiles the entire schema registry into the session's memory, atomically replacing the previous validator.

• Inputs:
  • enums: Array of enum definitions.
  • types: Array of type definitions (core entities).
  • puncs: Array of punc (function) definitions with request/response schemas.
• Behavior:
  • Parses all inputs into an internal schema graph.
  • Resolves all internal references ($ref).
  • Generates virtual .family schemas for type hierarchies.
  • Compiles schemas into validators.
• Returns: {"response": "success"} or an error object.

mask_json_schema(schema_id text, instance jsonb) -> jsonb

Validates a JSON instance and returns a new JSON object with unknown properties removed (pruned) based on the schema.

• Inputs:
  • schema_id: The $id of the schema to mask against.
  • instance: The JSON data to mask.
• Returns:
  • On success: A Drop containing the masked data.
  • On failure: A Drop containing validation errors.

validate_json_schema(schema_id text, instance jsonb) -> jsonb

Validates a JSON instance against a pre-compiled schema.

• Inputs:
  • schema_id: The $id of the schema to validate against (e.g., person, save_person.request).
  • instance: The JSON data to validate.
• Returns:
  • On success: {"response": "success"}
  • On failure: A JSON object containing structured errors (e.g., {"errors": [...]}).

json_schema_cached(schema_id text) -> bool

Checks if a specific schema ID is currently present in the cache.

clear_json_schemas() -> jsonb

Clears the current session's schema cache, freeing memory.

show_json_schemas() -> jsonb

Returns a debug dump of the currently cached schemas (for development/debugging).

✨ Custom Features & Deviations

JSPG implements specific extensions to the Draft 2020-12 standard to support the Punc architecture's object-oriented needs.

1. Implicit Keyword Shadowing

Standard JSON Schema composition (allOf) is additive (Intersection), meaning constraints can only be tightened, not replaced. However, JSPG treats $ref differently when it appears alongside other properties to support object-oriented inheritance.

• Inheritance ($ref + properties): When a schema uses $ref and defines its own properties, JSPG implements Smart Merge (or Shadowing). If a property is defined in the current schema, its constraints take precedence over the inherited constraints for that specific keyword.

  • Example: If Entity defines type: { const: "entity" } and Person (which refs Entity) defines type: { const: "person" }, validation passes for "person". The local const shadows the inherited const.
  • Granularity: Shadowing is per-keyword. If Entity defined type: { const: "entity", minLength: 5 }, Person would shadow const but still inherit minLength: 5.

• Composition (allOf): When using allOf, standard intersection rules apply. No shadowing occurs; all constraints from all branches must pass. This is used for mixins or interfaces.

2. Virtual Family Schemas (.family)

To support polymorphic fields (e.g., a field that accepts any "User" type), JSPG generates virtual schemas representing type hierarchies.

• Mechanism: When caching types, if a type defines a hierarchy (e.g., ["entity", "organization", "person"]), JSPG generates a schema like organization.family which is a oneOf containing refs to all valid descendants.

3. Strict by Default & Extensibility

JSPG enforces a "Secure by Default" philosophy. All schemas are treated as if unevaluatedProperties: false (and unevaluatedItems: false) is set, unless explicitly overridden.

• Strictness: By default, any property or array item in the instance data that is not explicitly defined in the schema causes a validation error. This prevents clients from sending undeclared fields or extra array elements.
• Extensibility (extensible: true): To allow a free-for-all of additional, undefined properties or extra array items, you must add "extensible": true to the schema. This globally disables the strictness check for that object or array, useful for types designed to be completely open.
• Structured Additional Properties (additionalProperties: {...}): Instead of a boolean free-for-all, you can define additionalProperties as a schema object (e.g., {"type": "string"}). This maintains strictness (no arbitrary keys) but allows any extra keys as long as their values match the defined structure.
• Ref Boundaries: Strictness is reset when crossing $ref boundaries. The referenced schema's strictness is determined by its own definition (strict by default unless extensible: true), ignoring the caller's state.
• Inheritance: Strictness is inherited. A schema extending a strict parent will also be strict unless it declares itself extensible: true. Conversely, a schema extending a loose parent will also be loose unless it declares itself extensible: false.

4. Format Leniency for Empty Strings

To simplify frontend form logic, the format validators for uuid, date-time, and email explicitly allow empty strings (""). This treats an empty string as "present but unset" rather than "invalid format".

5. Masking (Constructive Validation)

JSPG supports a "Constructive Validation" mode via mask_json_schema. This is designed for high-performance API responses where the schema dictates the exact shape of the returned data.

• Mechanism: The validator traverses the instance against the schema.
• Valid Fields: Kept in the output.
• Unknown/Extra Fields: Silently removed (pruned) if extensible: false (default).
• Invalid Fields: Still trigger standard validation errors.

This allows the database to return "raw" joined rows (e.g. SELECT * FROM person JOIN organization ...) and have JSPG automatically shape the result into the expected API response, removing any internal or unrelated columns not defined in the schema.

🏗️ Architecture

The extension is written in Rust using pgrx and structures its schema parser to mirror the Punc Generator's design:

• Single Schema Struct: A unified struct representing the exact layout of a JSON Schema object, including standard keywords and custom vocabularies (form, display, etc.).
• Compiler Phase: schema JSONs are parsed into this struct, linked (references resolved), and then compiled into an efficient validation tree.
• Validation Phase: The compiled validators traverse the JSON instance using serde_json::Value.

Concurrency & Threading ("Atomic Swap")

To support high-throughput validation while allowing for runtime schema updates (e.g., during development or hot-reloading), JSPG uses an Atomic Swap pattern.

1. Immutable Validator: The Validator struct immutably owns the Registry. Once created, a validator instance (and its registry) never changes.
2. Global Pointer: A global RwLock<Option<Arc<Validator>>> holds the current active validator.
3. Lock-Free Reads: Validation requests acquire a read lock just long enough to clone the Arc (incrementing a reference count), then release the lock immediately. Validation proceeds on the snapshot, ensuring no blocking during schema updates.
4. Atomic Updates: When schemas are reloaded (cache_json_schemas), a new Registry and Validator are built entirely on the stack. The global pointer is then atomically swapped to the new instance under a write lock.

🧪 Testing

Testing is driven by standard Rust unit tests that load JSON fixtures.

• Isolation: Each test file runs with its own isolated Registry and Validator instance, created on the stack. This eliminates global state interference and allows tests to run in parallel.
• Fixtures: The tests are located in tests/fixtures/*.json and are executed via cargo test.