What is JSON Schema Generation?
Automatically create validation rules and structural definitions from sample JSON data. Generate comprehensive schemas for API validation, data contracts, and type definitions with smart type inference and constraint detection.
โก Quick Start
- Paste your sample JSON data
- Select schema draft version
- Configure generation options
- Generate and download schema
๐ฏ Best For
- API contract definition
- Data validation rules
- Type definition generation
- Form validation schemas
Step-by-Step Schema Generation
๐ Sample Data Preparation
Use comprehensive, representative JSON examples that cover your data's full range and complexity for accurate schema generation.
{"user": {"id": 123, "name": "John", "email": "john@example.com", "active": true}}
๐ฏ Schema Draft Versions
- Draft 7: Latest stable with enhanced validation (recommended)
- Draft 6: Introduced const, contains keywords
- Draft 4: Widely supported foundation version
โ๏ธ Generation Options
- Required Fields: Configure mandatory vs optional properties
- Type Inference: Set strict or permissive type detection
- Constraints: Include string patterns and numeric ranges
- Validation: Test schema against sample data
Real-World Applications
๐ API Contract Definition
Generate schemas from API response examples to create formal contracts between services. Perfect for microservices architectures and OpenAPI documentation.
Example: REST API response โ JSON Schema for request/response validation
๐ Data Pipeline Validation
Ensure data consistency in ETL processes and transformations. Validate configuration files and form inputs against generated schemas.
Example: Configuration JSON โ Schema for environment validation
๐ป Type Definition Generation
Create TypeScript interfaces, Flow types, or model classes for various programming languages from JSON structures.
Example: User profile JSON โ TypeScript interface for frontend application
Frequently Asked Questions
๐ฏ Which JSON Schema draft version should I use?
Draft 7 is recommended for new projects as it's the latest stable version with enhanced validation features. Use Draft 4 if you need maximum compatibility with older tools.
๐ Why is my generated schema too restrictive?
Use more diverse sample data that covers edge cases and variations. Switch to permissive inference mode or make fields optional that vary across examples.
๐ง How do I handle array types correctly?
Ensure your sample arrays contain representative items. For mixed-type arrays, the schema will use oneOf or anyOf constructs to handle different item types.
๐ Can I customize the generated schema?
Yes! The generated schema is a starting point. You can edit it to add custom validation rules, descriptions, examples, and business-specific constraints.
๐พ How do I use the generated schema for validation?
Use JSON Schema validation libraries like Ajv (JavaScript), jsonschema (Python), or json-schema (Ruby) to validate data against your generated schema.