[{"data":1,"prerenderedAt":54},["ShallowReactive",2],{"tool-guide:json-model-generator":3},{"overview":4,"whatIs":5,"useCases":6,"steps":12,"commonMistakes":18,"relatedStandards":24,"example":34,"limitations":38,"faq":41},"JSON Model Generator infers a deterministic object shape and emits starting-point types for TypeScript, Dart, C#, Java, or Python from representative JSON.","When integrating with a REST API or processing JSON data, the first step is defining types that match the response structure. Writing these types by hand from API documentation is tedious and error-prone, especially for deeply nested objects with dozens of fields. A JSON-to-model generator automates this: paste a sample JSON response, select your target language, and get a type-safe model definition. The generator examines every value to infer its type (string, number, boolean, null, nested object, or array) and produces idiomatic code: TypeScript interfaces, Python dataclasses with type hints, C# records, Java POJOs, or Dart classes. For nested objects, it creates separate named types and references them. For arrays, it inspects the elements to determine the element type. This is a starting point — a single sample cannot capture every possible shape (missing optional fields, union types, or polymorphic responses), so the generated code should always be reviewed against the actual API contract.",[7,8,9,10,11],"API integration — paste a sample API response to generate TypeScript interfaces or Python dataclasses, then refine optional fields and union types.","Prototyping — quickly generate type definitions from JSON fixtures to get type safety during early development before the API contract is finalized.","Code migration — convert a JSON schema to types in a new language when porting a service from one stack to another.","Documentation — generate type definitions to include in technical documentation or README files alongside API examples.","Testing — create type-safe test fixtures from JSON samples to catch deserialization issues in unit tests.",[13,14,15,16,17],"Paste a representative JSON object or array into the input editor.","Choose the target language: TypeScript, Dart, C#, Java, or Python.","Enter the root type name (e.g., UserResponse, OrderItem).","Generate the model. Nested objects produce separate named types automatically.","Review inferred optionality and types against your API documentation, then copy the code.",[19,20,21,22,23],"Trusting a single sample — one JSON response may omit optional fields, show null where a string is expected, or represent a union type as only one variant. Always cross-check with the API schema.","Ignoring null values — a field with a null value could be nullable or simply absent in this sample. The generator may infer any? or object? where you need string? or number?.","Wrong root type name — the generator uses your chosen name for the top-level type and derives nested type names from field names. A generic name like \"Data\" produces less readable code.","Array element inference — if an array contains objects with different shapes (a polymorphic list), the generator merges them into a single type with optional fields. Use discriminated unions instead.","Copying without review — generated types are a starting point. Add validation, default values, and documentation before using them in production code.",[25,28,31],{"title":26,"url":27},"TypeScript — Interfaces","https:\u002F\u002Fwww.typescriptlang.org\u002Fdocs\u002Fhandbook\u002F2\u002Fobjects.html",{"title":29,"url":30},"Python — dataclasses module","https:\u002F\u002Fdocs.python.org\u002F3\u002Flibrary\u002Fdataclasses.html",{"title":32,"url":33},"JSON Schema — Describing JSON structure","https:\u002F\u002Fjson-schema.org\u002Funderstanding-json-schema",{"label":35,"input":36,"output":37},"Infer a service record","{\"name\":\"ledger\",\"retries\":3,\"enabled\":true}","interface Service {\n  name: string\n  retries: number\n  enabled: boolean\n}",[39,40],"One sample cannot prove every production variant or nullable field.","Generated code is a starting point and should be reviewed against the real API contract.",[42,45,48,51],{"question":43,"answer":44},"Which languages are supported?","TypeScript interfaces, Dart classes, C# records, Java POJOs, and Python dataclasses. Each output follows the language's idiomatic naming conventions.",{"question":46,"answer":47},"Does it handle nested objects and arrays?","Yes. Nested objects produce separate named types, and arrays are typed by the element shape inferred from the sample.",{"question":49,"answer":50},"Is my JSON sent to a server?","No. Type inference and code generation run entirely in your browser. Your data stays local.",{"question":52,"answer":53},"How does it handle null values?","A null value is inferred as a nullable type (e.g., string | null in TypeScript, Optional in Python). Review these carefully — the field may have a more specific type in other samples.",1788868140461]