Julian/jsonschema
Jsonschema
This project is a Python implementation of the JSON Schema specification, providing a library for verifying that data instances conform to defined schemas. It serves as a data validation framework capable of validating both the data itself and the schemas against official meta-schemas to ensure structural correctness.
The library features a schema reference resolver that maps URIs to definitions, enabling the resolution of internal and remote references for modular schema management. It is designed for extensibility, allowing for the definition of custom keywords, custom type-checking logic, and the registration of new validation functions for specialized string formats.
The system provides comprehensive error reporting that identifies all violations in a data instance and organizes them into a tree-structured hierarchy. This allows for programmatic querying of validation failures, diagnostic metadata extraction, and the identification of primary errors based on the data hierarchy.
The implementation supports multiple specification drafts through version-specific validator classes and schema dialect specifications.
Features
- Data Validation Schemas - Provides a full framework for verifying that data instances conform to defined JSON Schema specifications.
- JSON Schema Validation - Provides a full implementation for verifying that JSON data conforms to a defined schema.
- Meta-Schema Validations - Provides recursive validation of schemas against official meta-schemas to ensure structural correctness.
- JSON Schema Reference Resolvers - Implements a mechanism for fetching and mapping remote schemas via URIs to enable modular data definitions.
- Schema Reference Resolution - Maps unique identifiers to schema definitions to resolve internal and remote references during validation.
- External Schema Resolution - Fetches schema definitions from external network URIs or file systems using custom retrieval functions.
- Data Type Validation - Determines if specific data values match the types defined within a JSON schema.
- Data Validation Frameworks - Provides a system for defining custom keywords, formats, and type-checking rules to verify complex data structures.
- Schema URI Mappings - Associates schemas with unique identifiers so they can be reliably referenced by other schemas.
- JSON Schema Implementations - Implements the JSON Schema specification to resolve references and validate data against official drafts.
- JSON Schema Specifications - Supports multiple JSON Schema specification drafts by associating schemas with their corresponding version dialect.
- Schema Modularization - Organizes complex data definitions by resolving remote references and mapping schemas to unique identifiers.
- API Payload Constraint Validators - Verifies that API payloads follow a strict schema to prevent errors in backend processing.
- Violation Reporters - Collects and reports all validation violations in a data instance instead of stopping at the first error.
- Schema Type Dispatchers - Translates schema type definitions into concrete Python type checks using a configurable mapping.
- Runtime Contract Enforcement - Ensures incoming data matches a predefined specification during program execution to prevent downstream errors.
- Custom Validation Rules - Extends standard JSON Schema rules with custom keywords and format checkers for specialized business logic.
- Custom Validation Functions - Maps specific schema keywords to custom Python callables for implementing specialized business validation rules.
- Custom Format Validators - Allows the registration of custom validation functions to verify specialized string formats.
- Validation Error Reporters - Extracts detailed metadata for failed validations, including human-readable messages and the exact offending path.
- Hierarchical Error Trees - Organizes validation failures into a nested structure that mirrors the data path for programmatic querying.
- Keyword Validation Mappings - Implements a mapping system that connects schema keywords to Python functions for executing validation logic.
- Pluggable Format Checkers - Features a registry of validation functions to verify string patterns like emails and IP addresses.
- Versioned Validator Implementations - Implements different specification drafts through distinct classes that encapsulate rules for each schema version.
- Validation Error Utilities - Organizes validation errors into a tree structure for programmatic querying of failed dataset elements.
- String Format Validators - Verifies that strings conform to predefined standard formats such as email addresses or IP addresses.
- Data Validation - Implementation of JSON Schema validation.
