JSON to Pydantic
Generate starter Pydantic models with nested classes and Python type annotations.
Generate starter Pydantic models with nested classes and Python type annotations.
JSON to Pydantic creates starter Python BaseModel classes from a JSON example. It generates type annotations for common scalar values, nested models for objects, and list types for arrays, making it easier to begin validating API payloads with Pydantic.
A generated model is a starting point: compare it with several real responses and add optional fields, aliases, constraints, and validators where your application needs them. The conversion is performed in the browser and your JSON sample stays local.
Model names and field annotations are inferred from the sample keys, so review identifiers that contain punctuation or reserved words. Add defaults and optional annotations for fields that may be absent in later API responses.
For production applications, add field descriptions, constraints, aliases, and version-specific behavior after generation. A small representative input is useful for bootstrapping, but a complete model should reflect the full set of responses your service can return.
Use the copy control to move a checked result into another local development workflow.
This makes the output easy to review before it is copied into a script, test, configuration file, or API workflow.
Use a result as a starting point, then edit it for the audience and context in which it will appear. Generate more than one option when you need variety, and review names, claims, or references before publishing them. The tool is designed for quick ideation rather than authoritative research or final editorial review.