Question 1

Are my JSON data payloads or API keys sent to your servers?

Accepted Answer

No. The entire type inference engine executes directly inside your web browser. Your JSON payloads, internal object structures, and test data never leave your local machine.

Question 2

Which version of Pydantic is targeted by the Python output?

Accepted Answer

The generated Python code uses modern PEP 585 standard typing (list[str], dict[str, Any]) and inherits from pydantic.BaseModel, making it fully compatible with both Pydantic v1 and Pydantic v2.

Question 3

How are numbers differentiated between integer and floating-point types?

Accepted Answer

The engine checks whether the numerical value satisfies Number.isInteger(). Whole integers are typed as int, while decimal numbers are typed as float (Python) or float64 (Go).

Question 4

How does the Go generator format struct tags?

Accepted Answer

The Go generator converts JSON property names into exported PascalCase struct identifiers while preserving the exact original JSON key in the backtick struct tag: `json:"original_key"`.

Question 5

What happens if an array in my JSON is empty?

Accepted Answer

If an array contains no elements, the engine cannot infer the underlying type and safely defaults to unknown[] in TypeScript, list[Any] in Python, and []any in Go. Providing a sample with at least one representative item yields exact types.

Turn JSON into TypeScript, Python, or Go types

Static schema inference

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