JSON to Code Converter

Convert JSON objects into typed code for various programming languages

JSON Input
Paste your JSON object here to convert it to typed code
Generated Code
TypeScript Interface generated from your JSON
typescript
Usage Examples
Common JSON patterns and their generated code equivalents

Simple Object

{
  "name": "John",
  "age": 30,
  "active": true
}

With Arrays

{
  "tags": ["react", "ts"],
  "scores": [95, 87, 92]
}

Nested Objects

{
  "user": {
    "profile": {
      "name": "Jane"
    }
  }
}
Why Use This JSON to Code Converter?

Writing TypeScript interfaces, Zod schemas, or Python dataclasses from JSON samples is tedious and error-prone. Our converter generates strongly-typed code automatically from JSON input, saving hours of manual typing and eliminating mistakes in complex nested structures.

⚡ Instant generation - TypeScript interfaces, Zod schemas, Python dataclasses

🎯 Type inference - Automatically detects types, arrays, optional fields

🔄 Nested structure support - Handles deeply nested objects perfectly

📋 Copy-ready code - Generated code works immediately

🎨 Syntax highlighting - Color-coded output for readability

🔧 Multiple formats - Choose target language and library

Code Generation Tips

Provide Complete Samples

Use JSON with all fields populated for accurate type inference. Empty objects {} or null values may generate overly generic types. Include representative data for arrays and nested objects.

TypeScript Interfaces

Use generated interfaces for API response types, Redux state, and form data. This catches type errors at compile time. Update interfaces when API changes to maintain type safety across application.

Zod for Runtime Validation

Zod schemas validate data at runtime, catching invalid API responses or user input. Generate Zod from JSON, then use it for form validation, API parsing, and database input sanitization.

Python Dataclasses

Dataclasses provide structured data in Python with type hints. Use generated dataclasses for API clients, configuration parsing, and database models. Combine with Pydantic for runtime validation.

Refine Generated Code

Generated code is a starting point. Add doc strings, custom validation, computed properties, and better naming. Treat generated code as scaffolding, not final implementation, for production applications.