JSON to Code

Generate TypeScript, C# or Java classes from sample JSON

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Sample JSON

export interface Root {
  id: number;
  name: string;
  isActive: boolean;
  tags: string[];
  address: Address;
  projects: Projects[];
}

export interface Address {
  city: string;
  zip: string;
}

export interface Projects {
  title: string;
  year: number;
}

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About this tool

Generate ready-to-use class/model definitions - in TypeScript, C#, or Java - directly from a sample piece of JSON data, inferring field names and types automatically. It saves the tedious, error-prone work of manually writing out a matching class definition every time you need to consume a new API response shape.

How to use this tool

  1. Paste sample JSONProvide a realistic API payload with representative fields and nested objects.
  2. Choose target languageSelect TypeScript, C#, or Java based on your project stack.
  3. Generate modelsCreate inferred classes/interfaces with types mapped from JSON values.
  4. Review and refineAdjust naming, nullability, and optional fields to match project conventions.

Getting accurate types from sample JSON

Types are inferred from the sample, so give it a realistic one: include optional fields, use real values instead of nulls, and include at least one item in every array. A field that is null in the sample cannot tell the generator its real type.

In C# and Java, keep the JSON field names with attributes such as [JsonPropertyName] or @JsonProperty when you rename properties to match your naming style.

Key features

  • Saves time on repetitive model/class boilerplate writing.
  • Reduces manual typing mistakes in nested object structures.
  • Supports common backend and frontend language targets.
  • Useful starting point for API integration workflows.

Common uses

  • Bootstrapping DTOs from new API responses.
  • Generating initial models for mobile/web app clients.
  • Speeding up prototyping when API schema changes frequently.
  • Teaching juniors how payload shape maps to typed code.

Tips for better results

  • Use multiple payload samples to catch optional and nullable variants.
  • Rename generated symbols to match your codebase style guide.
  • Validate number vs string assumptions for IDs and timestamps.
  • Keep generated code under version control for easy diff review.

Mistakes to avoid

  • Generating models from an incomplete sample and assuming full schema coverage.
  • Skipping nullability review for fields that vary across endpoints.
  • Trusting inferred types blindly without backend contract validation.
  • Mixing generated naming conventions with existing project patterns.

Frequently asked questions

Types are inferred from the values present in your sample JSON, so they're accurate to that specific example - fields that could be null, optional, or have different types in other API responses won't be reflected unless your sample includes those variations.

TypeScript, C#, and Java class/interface definitions are supported, covering common backend and frontend use cases.

Yes - it's meant as a working starting point; review naming conventions and nullability to match your project's specific style before relying on it long-term.

The generator infers types from the values it sees, so a field that is null in the sample cannot be typed precisely. Use a sample where every field has a real value, then mark optional fields as nullable in the generated code.

If your code style renames camelCase JSON fields, add attributes such as [JsonPropertyName("field")] in C# or @JsonProperty("field") in Java so serialisation still maps to the original keys.

Use an interface or type for data that only travels through your app, such as API responses; use a class when you need methods or runtime checks like instanceof. Interfaces add nothing to the compiled JavaScript.

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