How the JSON to Code Generator Works

What the Tool Does

The JSON to Code generator converts JSON objects into type definitions, classes, and structs for various programming languages. This tool generates TypeScript interfaces, Go structs, Python classes, Java classes, C# classes, and Swift structs from JSON data. When you need to create type definitions from API responses, configuration files, or data structures, this generator creates code that matches your JSON structure. The tool supports multiple languages and various code generation options, allowing you to customize the output to match your project's coding style and conventions.

Common Developer Use Cases

Developers use JSON to Code generators when working with APIs, creating type definitions from API responses, or generating data models from JSON schemas. Many developers need to convert JSON responses from REST APIs into TypeScript interfaces or Go structs for type-safe API clients. The generator is valuable when building SDKs, creating data models from API documentation, or generating type definitions for configuration files. Before generating code, you may want to format your JSON using the JSON Formatter for better readability. The generator helps when prototyping, creating type definitions quickly, or generating boilerplate code from JSON data structures.

Supported Languages and Features

The generator supports multiple programming languages, each with specific features: TypeScript supports interfaces and type aliases, Go generates structs with JSON tags, Python supports TypedDict and classes, Java generates classes with getters and setters, C# generates classes with properties, and Swift generates structs conforming to Codable. Each language has specific conventions: TypeScript uses camelCase, Go uses PascalCase with JSON tags, Python uses snake_case, Java uses PascalCase with getters/setters, C# uses PascalCase with properties, and Swift uses camelCase with Codable conformance. The generator handles nested objects, arrays, and various data types, converting them appropriately for each language.

Common Pitfalls and Edge Cases

One common issue is that the generator requires JSON objects (not arrays or primitives) as input. Another pitfall is handling of null values: different languages handle nullability differently (TypeScript uses union types, Go uses pointers, Python uses Optional, etc.). Array types are inferred from the first element, so empty arrays may result in generic types like unknown[]. Nested objects are converted to nested types/classes, which may require additional imports or type definitions. The generator doesn't handle complex JSON Schema features like unions, enums, or custom validations—it focuses on basic type inference from JSON data. When generating code, review the output to ensure it matches your project's conventions and add any necessary imports or additional type definitions.

When to Use This Tool vs Code

Use this generator for quick type definition creation, prototyping, or one-off code generation from JSON data. It's ideal for creating initial type definitions from API responses, generating boilerplate code, or exploring data structures. For production code, use specialized tools like JSON Schema validators, OpenAPI generators, or code generation tools that provide more comprehensive type generation, validation, and integration with your build system. Browser tools excel at ad-hoc code generation and exploration, while specialized tools provide better type inference, validation, and integration with development workflows.