everit-org/json-schema
Json Schema
This project is a Java library designed to validate JSON documents against defined schema specifications. It functions as a standards-compliant engine that ensures data integrity by checking structural compliance and enforcing business rules within Java applications.
The library distinguishes itself through its flexible validation strategies, allowing developers to inject custom logic and pattern-matching engines to handle specialized data formats. It supports configurable execution modes, enabling users to either halt validation immediately upon the first error or collect all violations for comprehensive reporting. Furthermore, the engine includes built-in capabilities for type coercion and the injection of default values, which helps normalize incoming data during the validation process.
Beyond standard structural checks, the system provides advanced features for managing complex data dependencies and security constraints. It includes a local registry for resolving schema references without network access and supports the enforcement of read-only or write-only access patterns. The library also offers observability tools, such as event-driven hooks that allow external systems to monitor the internal validation process.
Features
- Structural Data Validators - Validates JSON documents against defined schema specifications to ensure structural integrity.
- JSON Schema Validation - Provides a standards-compliant engine for validating JSON documents against defined schema specifications.
- Request Data Integrity - Validates incoming JSON payloads against schema specifications to ensure data integrity before backend processing.
- Java Validation Libraries - Offers a Java-native library for enforcing structural constraints and data integrity through configurable validation rules.
- Pluggable Body Validators - Allows developers to inject custom validation logic and pattern-matching engines to extend standard schema enforcement.
- Data Normalization Utilities - Normalizes incoming data by coercing types and injecting default values to ensure consistent internal data models.
- Data Type Coercion - Automatically transforms string-encoded inputs into primitive types during validation to ensure schema compatibility.
- First Matching Item Retrievers with Error Handling - Halts the validation process immediately upon encountering the first schema violation to save processing time.
- Violation Reporters - Collects all schema errors found during validation into a single report for comprehensive data analysis.
- Fail-Fast Execution Controls - Supports configurable execution modes to either halt immediately upon the first violation or collect all errors.
- JSON Schema Reference Resolvers - Resolves schema references locally to simplify dependency tracking and avoid unnecessary network calls.
- Schema Tree Traversers - Processes nested data structures by recursively walking the schema tree and applying validation rules at each node.
- Schema Reference Resolution - Manages relative identifiers and external dependencies through a local registry to resolve complex data structures without network access.
- Custom Format Validators - Allows registration of custom validation logic and pattern matching to handle specialized data formats.
- Input Type Parsing - Transforms string-based inputs into numeric or boolean formats automatically during validation.
- Strict Object Validation - Enforces strict object validation to ensure data conforms to defined schema requirements.
- Schema Default Values - Fills missing properties in an input document with predefined default values from a schema during validation.
- Validation Error Reporters - Generates detailed reports that pinpoint specific schema violations and provide exact locations of errors.
- JSON Schema Implementations - Implements the official JSON Schema specification, including support for complex reference resolution.
- Write-Only Access Modes - Validates objects against read-only or write-only constraints to ensure data access patterns align with schema permissions.
- Primitive Type Schemas - Accepts string-encoded numbers or booleans to accommodate loosely typed input data.
