Pydantic

You can use Pydantic to define your API for Python backends.

To declare a data type called ChatRoom, put the following in a .py file:

from pydantic import BaseModel
from typing import Optional
from reboot.api import (
    API,
    Field,
    Methods,
    Reader,
    Writer,
    StateModel,
    Type,
)

class ChatRoomState(StateModel):
    messages: Optional[list[str]] = Field(tag=1)

class MessagesResponse(BaseModel):
    messages: list[str] = Field(tag=1)

class SendRequest(BaseModel):
    message: str = Field(tag=1)

ChatRoomMethods = Methods(
    messages=Reader(
        request=None,
        response=MessagesResponse,
    ),
    send=Writer(
        request=SendRequest,
        response=None,
    ),
)

api = API(
    ChatRoom=Type(
        state=ChatRoomState,
        methods=ChatRoomMethods,
    ),
)

Reboot uses standard Pydantic BaseModel, with StateModel as the base class for your durable state types.

In addition to defining the data type, you'll also need to define operations for that type. In the example above, ChatRoomMethods defines the operations for the ChatRoom type.

Naming conventions

Your state class should end in State, e.g., ChatRoomState. Your Methods variable should end in Methods, e.g., ChatRoomMethods. Your API types are composed of state and methods and should be descriptive of the interface, e.g., ChatRoom.

Depending on its kind, a method might be able to only read (e.g., Reader) or both read and write (e.g., Writer) the state.

In the example above, ChatRoom has just one Reader and one Writer method, but it can have any number of Reader, Writer, Transaction, and Workflow methods.

important

All Pydantic fields must include a tag parameter using Field(tag=N). This is required for safe backwards compatibility.

To learn more about how you implement each data type's methods see Implement your API.