Free JSON to Type Generator

JSON to Types is a free online tool that converts JSON data into type definitions for TypeScript interfaces, Go structs, Rust types, and other languages.

Yes, it is completely free with no registration required. All conversion happens client-side in your browser.

JSON to Types generates type definitions for TypeScript, Go, Rust, Python (dataclasses), and other statically-typed languages.

Absolutely. The JSON to Type Generator processes everything client-side in your browser. No data is uploaded to or stored on any server. Your content remains private on your device at all times.

Yes, the JSON to Type Generator is fully responsive and works on smartphones and tablets. You can use it on any device with a modern web browser -- no app download required.

No account or registration is needed. Simply open the JSON to Type Generator in your browser and start using it immediately. There are no sign-up walls or usage restrictions.

Simply enter your input in the provided field, adjust any settings to your preference, and the tool will process it instantly. You can then copy the result to your clipboard or download it.

The JSON to Type Generator works in all modern browsers including Chrome, Firefox, Safari, Edge, and Opera. For the best experience, use the latest version of your preferred browser.

The converter inspects each numeric value and splits it intelligently rather than treating all numbers the same. A whole number like 42 is mapped to that language's integer type — int64 in Go, i64 in Rust, and int in Python — while a value with a decimal point like 19.99 becomes a float or double. This matters because JSON itself has only one number type, so the generated struct or interface would otherwise lose that distinction and force you to fix it by hand. Keep in mind the decision is based on the sample you paste, so if a field can hold both 5 and 5.5, feed an example that shows the decimal to get the wider type. Paste a representative payload above and the inferred integer and float types appear instantly.

A TypeScript interface is a compile-time type: it tells the compiler the shape of your data but disappears at runtime, so it never actually checks an incoming payload. A Zod schema is a runtime validator — it inspects real data as your code runs and throws if a field is missing or the wrong type, and it can infer a matching TypeScript type for you. Use the interface output when you trust the source and just want editor autocomplete and compile checks; choose the Zod output when you are parsing untrusted API responses or form input and need an actual guard at the boundary. Both are available as separate targets here, so you can generate one or the other from the same JSON. Paste your sample and pick TypeScript or Zod to compare them.

When an array contains more than one kind of value, the tool inspects every element instead of collapsing to a vague catch-all type. In the TypeScript output it expresses the result as a union — an array holding strings and numbers becomes (string | number)[] rather than any[] — so you keep real type safety. For a uniform array of objects it does something smarter still: it builds one reusable element type and singularizes the field name to label it, so a tags array yields a Tag type referenced by the parent. This keeps the generated definitions clean and idiomatic instead of inlining duplicate shapes. Because inference is based on the elements actually present, include an example of each variant in your sample for the most accurate union. Paste a mixed array above to see the union generated automatically.

The Optional nulls toggle controls how fields that hold null in your sample are expressed in the output. When it is on, each null field is marked optional using whatever idiom the target language prefers: a ? modifier on TypeScript properties, Optional[...] in Python, Option<...> in Rust, and a ,omitempty tag in Go. When it is off, the field keeps a plain non-optional type. Turning it on is useful when a key may legitimately be absent or null in real responses, since it stops the type from forcing a value that might not be there. Note the tool only knows a field is nullable if the sample you paste actually shows null for it, so include those cases in your example. Toggle Optional nulls above and watch the output update live for the language you selected.

Rather than inlining a nested object inside its parent, the converter extracts it into its own named type. A profile object sitting inside a user becomes a standalone Profile definition that the parent references, which keeps each type small and reusable. Names are derived from the JSON keys and then adjusted per language: type names are PascalCased, while field names are rewritten to each ecosystem's convention — snake_case for Rust and Python, camelCase elsewhere. Crucially, the original JSON key is preserved in a serialization tag or rename attribute, such as Go's json:"..." tag or Swift's CodingKeys, so encoding and decoding still round-trip correctly even after renaming. You can also set a root type name to label the top-level type. Paste a nested object above to see the named child types generated for you.