JSON to Flow Class Converter

JSON to Flow Class Converter: Core Features and Principles

Manually writing data model classes during development is time-consuming and error-prone. This tool automatically generates corresponding Flow class code by parsing your JSON structure. Flow classes are data structure definitions used for static type checking, commonly found in type systems like Flow or TypeScript. The tool analyzes key-value pairs in the JSON, infers field types (such as string, number, boolean, arrays, or nested objects), and generates class code containing property definitions and type declarations. It is ideal for API response parsing, data binding, and model building.

Why Choose Our JSON to Flow Converter?

• Supports custom root class names and property naming conventions (e.g., camelCase or snake_case) to fit different coding standards.
• Automatically handles nested objects and arrays, generating nested class definitions and List<Type> structures.
• Purely client-side processing—no data is uploaded, ensuring your privacy and security.

How to Use

1. Paste a valid JSON string into the input box.
2. Set the root class name (e.g., ApiResponse) and property naming convention.
3. Click the convert button to generate the Flow class code.
4. Copy the output and use it in your project.

Frequently Asked Questions (FAQ)

Q: What input formats does the JSON to Flow converter support?
A: It supports standard JSON objects or arrays as the root node. Please ensure the format is valid.

Q: Can the generated code be used directly in TypeScript?
A: Yes. The output is a generic class structure, so it can be adapted for TypeScript with minor syntax adjustments (such as replacing 'class' with 'interface').

Important Notes

The input JSON must be properly formatted; highly complex structures may impact performance. The tool relies on type inference, so special values (like null or mixed types) might require manual adjustment. Avoid inputting sensitive data.

Technical Notes & Best Practices

For API development, we recommend using sample JSON to generate a base model, then manually adding optional properties (using the ?: syntax) or union types. Example: Inputting {"name":"John","age":30} outputs class Root { string name; int age; }.