Free Online JSON to TypeScript Converter
Convert JSON to TypeScript interfaces, Go structs, Python Pydantic models, Rust structs, and SQL tables in your browser. Private, instant, no signup.
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Quick answer
Paste JSON into the KaviForge converter and open the TypeScript, Go, Python, Rust, or SQL tab. The tool infers nested types, optional fields, and nulls in your browser, then you copy or download the code. Your JSON is never uploaded.
Turn a JSON object or array into TypeScript interfaces, Go structs, Python Pydantic models or dataclasses, Rust structs, and a SQL table sketch. Paste an API response, pick a language, and copy code that matches the shape of your data — including nested objects, arrays, and fields that only show up on some items.
Conversion runs entirely in your browser. The JSON is parsed and mapped to types locally, so payloads, tokens, and customer records never leave the page.
How to Convert JSON to TypeScript, Go, Python, Rust, or SQL
- 1Paste JSON into the left editor, upload a .json file, or load the sample.
- 2Choose a language tab: TypeScript, Go, Python, Rust, or SQL.
- 3Set the root type name. On the Python tab, pick Pydantic models or dataclasses.
- 4Review the generated code on the right. Nested objects become their own types, and keys missing from some array items become optional.
- 5Click Copy to Clipboard or download the file. Nothing is uploaded.
Features
Five languages
TypeScript interfaces, Go structs, Python Pydantic models or dataclasses, Rust structs, and SQL CREATE TABLE statements from the same JSON.
Nested objects and arrays
Objects inside objects become named types. Arrays of objects are merged into one shape, and primitive arrays become lists or child tables.
Optional and nullable fields
Keys missing from some array items are optional. JSON null is preserved as a nullable type instead of being dropped.
Syntax highlighting
The output editor highlights the selected language so you can scan types before you copy them.
Copy and download
Copy the generated source to the clipboard or download a .ts, .go, .py, .rs, or .sql file.
Private by design
Parsing and code generation run locally. Refreshing the page clears the input. There is no account and no upload.
When to Use the JSON to Code Converter
Type an API response
Paste a sample payload and copy TypeScript interfaces instead of writing them by hand for a fetch call or SDK.
Scaffold a backend model
Generate Go structs or Rust types with the original JSON keys preserved in tags, or Python models that parse the same object.
Draft tables from a document
Turn a nested JSON document into a first-pass SQL schema with related tables for nested objects and arrays.
How JSON Becomes Typed Code
JSON only describes values, not types. A converter infers a type by walking the document: objects become structs or interfaces, arrays become lists, and values that differ across array items are merged. A number that is sometimes whole and sometimes decimal becomes a float. A key that is missing on some objects becomes optional. A JSON null becomes a nullable field.
That inference is what “JSON to TypeScript” tools do when they emit an interface, and the same walk produces Go structs with json tags, Python models, Rust structs with serde renames, and SQL tables. Nested objects become their own named types. Arrays of objects become a child type, and in SQL they become a related table.
The mapping is a sketch of the sample you pasted, not a guarantee for every future payload. A field that is only null in this document stays loosely typed until you paste an example that includes a real value. Generated SQL is a portable starting point for SQLite and PostgreSQL, not a migration.
JSON to Code Converter FAQs
How does JSON to TypeScript conversion work?
The tool parses your JSON in the browser and walks the value. Each object becomes an interface, each array becomes a list, and primitive values become string, number, boolean, or null. Nested objects get their own interface named from the key. If an array contains objects, every item is merged: shared keys are required, keys that appear on only some items are optional, and mixed numbers become a single number type. The right-hand panel then prints exportable TypeScript interfaces you can copy into a project.
Is my data secure when converting JSON?
Yes. Conversion is 100% client-side. Your JSON is parsed and turned into code in the browser tab, and it is not uploaded, stored, or sent to a server. Refreshing or closing the page clears the editors. Do not paste secrets you would not want in local browser memory, but nothing leaves your machine as part of this tool.
Can I convert nested JSON structures?
Yes. Nested objects become separate named types, and arrays of objects are merged into one type so optional fields are preserved. A document with an address object and an orders array produces a root type plus types for the address and each order. The same nesting is reflected in Go, Python, Rust, and SQL, where nested objects and arrays become related tables.
Which languages can I generate?
TypeScript interfaces, Go structs with json tags, Python Pydantic models or dataclasses, Rust structs with serde attributes, and a SQL schema. Switch tabs to regenerate from the same input without pasting it again. Python field names stay aligned with your JSON keys when they are valid identifiers, so the models can parse the original object.
How are arrays, nulls, and missing keys handled?
An array of strings becomes a string list. An array of objects uses one struct for every item. A key that is absent on some items is optional (for example paid?: boolean in TypeScript, or a pointer with omitempty in Go). A value that is JSON null is nullable. A field that is only ever null becomes null in TypeScript and a loose type in Python and Rust, because the sample never shows a real value.
Does the SQL output run on every database?
It is a portable sketch aimed at SQLite and PostgreSQL: one table per object, a row_id primary key, foreign keys for nested objects, and child tables for arrays. Reserved names are quoted. Treat it as a first draft and adjust types, constraints, and indexes before you migrate a production database.
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