protobuf-to-pydantic

import sys from typing import Type from pydantic import BaseModel, Field from google.protobuf.message import Message from google.protobuf import descriptor_pool, descriptor_pb2 from protobuf_to_pydantic import msg_to_pydantic_model # Simulate a generated protobuf message `demo_pb2.UserMessage` # In a real scenario, this would come from `import demo_pb2` pool = descriptor_pool.Default() descriptor = descriptor_pb2.DescriptorProto() descriptor.name = 'UserMessage' descriptor.field.add(name='uid', number=1, type=descriptor_pb2.FieldDescriptorProto.TYPE_STRING) descriptor.field.add(name='age', number=2, type=descriptor_pb2.FieldDescriptorProto.TYPE_INT32) descriptor.field.add(name='user_name', number=3, type=descriptor_pb2.FieldDescriptorProto.TYPE_STRING) pool.Add(descriptor) # Create a mock Message class based on the descriptor class UserMessage(Message): def __init__(self, uid='', age=0, user_name='', **kwargs): super().__init__(**kwargs) self.uid = uid self.age = age self.user_name = user_name DESCRIPTOR = pool.FindMessageTypeByName('UserMessage') # Convert the Protobuf Message object to a Pydantic BaseModel UserModel: Type[BaseModel] = msg_to_pydantic_model(UserMessage) # Example usage of the generated Pydantic model user_data = UserModel(uid='123', age=30, user_name='John Doe') print(user_data.model_dump_json(indent=2)) # Access field info # print({k: v.field_info for k, v in UserModel.__fields__.items()}) # For Pydantic v1 print({k: v.json_schema_extra for k, v in UserModel.model_fields.items()}) # For Pydantic v2+