Schema Generation

To allow for python typing of documents, we define them as TypedDict in event_model.documents.

from typing import Any, Dict

from typing_extensions import Annotated, TypedDict

from .generate.type_wrapper import Field, add_extra_schema

DATUM_EXTRA_SCHEMA = {"additionalProperties": False}


@add_extra_schema(DATUM_EXTRA_SCHEMA)
class Datum(TypedDict):
    """Document to reference a quanta of externally-stored data"""

    datum_id: Annotated[
        str,
        Field(
            description="Globally unique identifier for this Datum (akin to 'uid' "
            "for other Document types), typically formatted as '<resource>/<integer>'"
        ),
    ]
    datum_kwargs: Annotated[
        Dict[str, Any],
        Field(
            description="Arguments to pass to the Handler to "
            "retrieve one quanta of data",
        ),
    ]
    resource: Annotated[
        str, Field(description="The UID of the Resource to which this Datum belongs")
    ]

We then use pydantic to convert these python types into the jsonschema in event_model.schemas.

After changing any of the documents it’s necessary to regenerate the schemas. This can be done by running:

regenerate-schema

which is a python environment script in a dev install of event-model.

This ensures we can have accurate typing across the bluesky codebase, but also doesn’t limit us to python for validating documents.