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Generating Strongly-Typed Backend Models from JSON

Learn how to generate strongly-typed Go structs, Rust Serde structs, and Python Pydantic models from raw JSON payloads with client-side privacy.

Generating Strongly-Typed Backend Models

When consuming external REST APIs in statically typed languages like Go, Rust, or Python Pydantic, writing boilerplate model structs manually is time-consuming and error-prone. Automated type inference creates clean, idiomatic struct definitions directly from sample JSON responses.

Supported Language Targets:

  • Go (Golang): Generates PascalCase struct fields with json:"key" struct field tags.
  • Rust (Serde): Generates snake_case struct fields with #[derive(Serialize, Deserialize)] and #[serde(rename)] attributes.
  • Python (Pydantic): Generates BaseModel classes with type hints (int, float, str, List[...], Optional[...]).
json
// Generated Go Struct
type AutoGenerated struct {
	ID       int      `json:"id"`
	Name     string   `json:"name"`
	IsActive bool     `json:"is_active"`
	Roles    []string `json:"roles"`
}

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Frequently Asked Questions

Does it handle nested JSON arrays?

Yes. Nested arrays and objects are recursively parsed into sub-structs and sub-classes.

Is Pydantic v2 supported for Python?

Yes. Generated Python code uses standard Pydantic BaseModel definitions compatible with Pydantic v1 and v2.

Related JSON Topics & Reference Articles