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Automatically map JSON data structures to C++ class or struct definitions for rapid generation of data models used in APIs and configuration files.
Overview
Understand what the tool solves, how it works, and the boundaries of its data.
This converter reads a JSON example and infers C++ types for the values and nested structure it sees. JSON objects group named properties, while arrays hold ordered values; strings, numbers, booleans, and null are the basic value kinds defined by the JSON format. The output is a starting point for a model or data-transfer type, not a complete JSON reader or writer.
For example, an object containing a name, an active flag, and an address object gives the generator evidence for text, boolean, and nested types. An array of objects can inform a collection type and the element declaration. The sample is the evidence: a field omitted from it cannot be inferred just because it exists in a larger API contract.
You can name the root type and adjust C++ generation options such as namespace, struct versus getter/setter form, type-name style, and include location. These choices change generated declarations. Review the result for project conventions, especially property names, includes, and how nested types are named.
JSON numbers do not carry a C++ width or business meaning. A value like 30 may look integral in one sample, but the contract may allow a larger value or a fraction. Likewise, a sample cannot establish whether a field is optional, nullable, an enum, or constrained to a particular range.
Guide
Follow the workflow and verify inputs and outputs with practical examples.
Use a real response or configuration sample that includes the nested objects and arrays you need to represent. Standard JSON requires quoted property names and strings; comments and trailing commas are not part of its syntax.
Enter the name you want for the top-level C++ type. The default is Root; choose a project-specific name before copying the result.
Select the available C++ style options to match your namespace, declaration form, naming style, and include layout. The preview regenerates as input or options change.
Compare every property and nesting level with the source JSON. Then copy the code or download the generated C++ file and integrate it into your project.
Use cases
See how the tool fits into real work and everyday tasks.
When building a client for an API, generate an initial type from a representative response, then compare it with the published schema and add fields or variants absent from that example.
For a nested JSON configuration, use the output to map the visible hierarchy into C++ declarations. Decide separately how your application handles defaults, validation, and optional settings.
A developer can share a generated draft with teammates to discuss names and structure before formalizing the contract. Treat it as a review aid, then compile and test the finished code in the target project.
Q&A
Find concise answers to common questions and confusing cases.
No. It generates C++ declarations from the sample; it does not add runtime serialization or deserialization behavior. Connect the types to the JSON library and conversion code your application uses.
No. A single example only shows the values present in that sample. Check the API schema or collect examples for different response branches, then explicitly model absent, nullable, and variant fields.
Check that property names and strings use double quotes, values are separated by commas, and there are no comments or trailing commas. If the text parses elsewhere as a JavaScript object literal, convert it to standard JSON first.
Notes
Review scope, result limitations, and important precautions before use.
Inferred types are estimates from example values, not proof of the full API contract. Review integer width, floating-point precision, nullability, optional properties, enum values, and naming collisions. Include larger and alternate examples when the service can return different shapes.
The generated declarations are not guaranteed to compile unchanged in every project. Check includes and language-standard requirements, add parsing or serialization support separately, and compile and test the result where it will be used. Do not put secrets or private production payloads into a sample unless you are comfortable using that data in this workflow.
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