We use cookies.This website uses essential cookies to operate core features. With your consent, we also use analytics cookies to understand traffic and improve the service. For more details, see our .
We use cookies.This website uses essential cookies to operate core features. With your consent, we also use analytics cookies to understand traffic and improve the service. For more details, see our .
Was this tool helpful to use?
Your feedback helps us make it better
Instantly convert JSON data into Rust struct code for seamless API integration, data processing, and model definitions.
Overview
Understand what the tool solves, how it works, and the boundaries of its data.
This converter reads one JSON sample and generates Rust code describing the object shapes and value types it finds. JSON objects become named fields, nested objects become related types, and arrays are represented using collection types. The root type name can be changed to fit the role of the data in your program. A Rust struct groups named fields under one type, so the result gives you a starting model for a response, configuration file, or other JSON document.
Inference reflects the values present in that sample, not a complete service contract. A sample cannot reveal fields that were absent, every possible value a field may take, or rules that exist only in documentation. If you need to model several variants, inspect representative examples and decide how the Rust types should express those differences.
Rust-specific settings let you choose normal or dense formatting, field visibility (private, crate, or public), and whether to derive Debug, Clone, and PartialEq. Common inference settings can also affect how values such as enums, date-time strings, UUIDs, and maps are recognized. The generated text can be copied or downloaded as an .rs file.
Serde derives are available for serialization and deserialization. They are Rust macros that generate trait implementations; your Cargo project still needs compatible Serde dependencies and any project-specific attributes or imports. The Rust Book explains named struct fields, while Serde documents the derive setup.
Guide
Follow the workflow and verify inputs and outputs with practical examples.
Use an object or array that reflects the data shape you need to handle. If you have different response types, test representative samples separately and compare the generated models.
Set the top-level Rust type name before using the code. Expand the Rust options to choose field visibility, code density, and derives; review common inference settings if a string-like value needs special treatment.
Review field names, nested types, numeric types, arrays, and any Serde attributes. Copy the result or download the .rs file, then adapt it to your module and crate conventions.
For API work, compare the generated definitions with the API documentation and examples for successful, empty, and error responses. Keep only the derives and visibility your application uses.
Use cases
See how the tool fits into real work and everyday tasks.
A developer can turn a sanitized response example into an initial Rust model, then check optional fields and alternate responses against the API contract before relying on it.
A Rust application maintainer can use a representative JSON configuration to draft nested structs, then add defaults, validation, and application-specific behavior by hand.
Q&A
Find concise answers to common questions and confusing cases.
No. A field missing from the sample is invisible to the converter. Use examples and the data contract to determine whether fields can be absent or null, then adjust the model and deserialization rules accordingly.
It may need project setup and edits. Add compatible Serde dependencies with the required derive feature, check imports and module visibility, and compile it in your crate.
Yes. The input may be an array; its elements inform the generated model. With a single sample, the output still reflects only the values and structures represented there.
Notes
Review scope, result limitations, and important precautions before use.
Generated code is a draft inferred from the current JSON sample and settings. It does not know unseen fields, business rules, lifetimes, validation requirements, or all possible variants. Confirm number ranges, missing and null values, naming, and Serde behavior against representative data, then compile and test it in your project. Avoid pasting sensitive production data into a service unless its handling is appropriate for that data.
Related
Discover related tools, collections, and available API capabilities.