json-schema-parser 1.0.1

Convert between JSON schema definitions and Pydantic models

json-schema-parser

A Python library for converting between JSON schema definitions and Pydantic models.

Features

• Parse a JSON schema dict into a validated Pydantic model
• Generate a JSON schema dict from any Python type or Pydantic model
• Supports all common types: integer, float, string, boolean, json, uuid, datetime
• Supports list (is_many) and optional (is_optional) variants of every type
• Nested object schemas via ComplexTypeInput

Installation

pip install json-schema-parser

Usage

Parse a JSON schema into a Pydantic model

from json_schema_parser import JsonSchemaParser

schema = {
    "__config": {"field_type": "json", "is_many": False, "is_optional": False, "field_default_value": None, "description": ""},
    "name": {"field_type": "string", "is_many": False, "is_optional": False, "field_default_value": None, "description": "User name"},
    "age":  {"field_type": "integer", "is_many": False, "is_optional": True, "field_default_value": None, "description": "User age"},
}

parser = JsonSchemaParser.model_validate(schema)
Model = parser.generate_pydantic_model("User")

user = Model.model_validate({"name": "Alice", "age": 30})

Generate a JSON schema from a Python type

from json_schema_parser import JsonSchemaParser
from pydantic import BaseModel
from typing import Optional, List

class Address(BaseModel):
    street: str
    city: str

schema = JsonSchemaParser.generate_json_schema_from_data_type(Address)

Supported field types

field_type value	Python type
"integer"	int
"float"	float
"string"	str
"boolean"	bool
"uuid"	UUID
"datetime"	datetime
"json"	dict / nested model

Set is_many: true to get a List[T], and is_optional: true to get Optional[T].

License

MIT