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JSON to TypeScript, Zod, Python & Go Struct Converter

Generate TypeScript interfaces, Zod validation schemas, Python Pydantic models, Go structs and JSON Schema from any JSON payload.

Runs 100% in your browser Free, no sign-up Updated

0 types 0 fields TypeScript
by ProWebLook

How to use the JSON to TypeScript, Zod, Python & Go

  1. Paste a JSON object or array (such as a REST API response) into the left editor, or click “Load sample”.
  2. Choose your target output: TypeScript Interfaces, TypeScript Types, Zod Schema, Python Pydantic v2, Python TypedDict, Go Structs, or JSON Schema.
  3. Set the root type name and toggle options like optional properties, readonly modifiers, or exported declarations.
  4. Copy the generated type definitions to your clipboard or download the source file directly.

Why generate static types and runtime schemas from JSON?

When integrating REST APIs, webhooks, or third-party SDKs, writing boilerplate type declarations by hand for deeply nested JSON responses is tedious and error-prone. A single misspelled property name or overlooked null union can trigger runtime crashes in production. This JSON to TypeScript, Zod, Python & Go Struct Converter inspects any sample JSON document, merges array item shapes, and outputs ready-to-paste type definitions in five popular formats.

Everything runs 100% locally in your browser using an AST-style structural type inference engine — your proprietary API payloads, authentication responses, and database fixtures are never uploaded to any server.

Supported output languages and schema formats

  • TypeScript Interfaces: Generates clean, modular export interface definitions with proper quoting for special keys, optional/readonly modifiers, and merged union types for heterogeneous arrays.
  • Zod Schemas (TypeScript runtime validation): Produces composable z.object({...}) declarations alongside z.infer<typeof Schema> exports so your application validates untrusted JSON at the network boundary before trusting its types.
  • Python (Pydantic v2, TypedDict & dataclasses): Creates idiomatic Python 3.10+ classes with Optional[...], List[...], and Field(alias=...) annotations when JSON keys are not valid Python identifiers or use camelCase/kebab-case.
  • Go Structs: Emits idiomatic PascalCase Go type ... struct declarations with accurate `json:"key_name,omitempty"` struct tags and initialism casing (such as ID, URL, IP, and API).
  • JSON Schema (Draft 2020-12): Builds a standard type, properties, and required JSON Schema specification suitable for OpenAPI 3.1 contracts, Ajv validation, or LLM structured-output function calling.

How the structural type inference engine works

Unlike naive converters that only inspect the first element of an array, this generator scans every object inside an array to build a unified schema. If a property appears in some array elements but is omitted in others, the generator automatically marks that field as optional (?: in TypeScript, .optional() in Zod, omitempty in Go, and Optional[...] in Python). If a field holds both a value and null across array items, it infers a nullable union type automatically.

Developer workflow tips

  • Capture a real response first: Convert a curl command into fetch or Python code with our cURL to Code Converter, paste the JSON response here, and generate your client models in seconds.
  • Compare schema changes across versions: Before regenerating types after an API upgrade, run both payloads through the JSON Diff Viewer to spot added, removed, or renamed properties.
  • Converting YAML or CSV instead? Transform your configuration or tabular file with the YAML to JSON Converter or CSV to JSON Converter first, then paste the resulting JSON here.

Frequently asked questions

How does the converter handle arrays of objects with inconsistent keys?
When an array contains multiple JSON objects, the type inference engine merges all object shapes across every element. Keys that appear in some elements but not others are automatically marked as optional (? in TypeScript, .optional() in Zod, Optional[...] in Python, and omitempty in Go).
How are null values and mixed types inferred?
A field whose value is null (or both a primitive and null across array items) is typed as nullable (for example string | null in TypeScript, z.string().nullable() in Zod, or pointer/interface types in Go). Mixed primitive arrays generate union types.
Does it handle nested objects and invalid identifier keys?
Yes. Nested JSON objects are extracted into named child interfaces, structs, or models automatically. Keys containing hyphens, spaces, or leading digits are quoted in TypeScript/Zod and mapped with Field(alias=...) in Pydantic or json:"..." struct tags in Go.
What version of Zod and Pydantic does it target?
The Zod generator outputs modern Zod v3/v4-compatible schemas along with z.infer<typeof Schema> type exports. The Python Pydantic generator targets Pydantic v2 (BaseModel and Field).
Is my JSON payload uploaded to any server?
No. Parsing and AST code generation run 100% in your browser. Proprietary API schemas, customer payloads, and internal data structures never leave your machine.

Last updated . Launched with TypeScript interfaces/types, Zod schemas, Python Pydantic/TypedDict, Go structs, and JSON Schema Draft 2020-12 generation.

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