Use narrower string type hints in the pydantic models

[themattmorris]

Love the work your team is doing on this standard! Our team is really getting a lot out of it.

The json schema uses enum where applicable, but the models in this project use str | None annotations. Since you're already using pydantic, I thought it would be beneficial to either use typing.Literal (likely preferred) or Enum annotations so that these can be validated upfront that they conform to the json schema.

I'm not sure if model.py was generated with any tools (i.e. datamodel-code-generator), but would you be open to a PR that makes the type hints narrower for the fields that have enums?

• OpenDataContractStandard.kind
• OpenDataContractStandard.apiVersion
• Server.type
• SchemaObject.logicalType
• SchemaProperty.logicalType
• DataQuality.dimension
• DataQuality.type
• DataQuality.metric
• Relationship.type

For example:

Current

class DataQuality(pyd.BaseModel):
    ...
    metric: str | None = None

Proposed

class DataQuality(pyd.BaseModel):
    ...
    metric: typing.Literal["nullValues", "missingValues", "invalidValues", "duplicateValues", "rowCount"] | None = None

I'd be happy to submit a PR if you're onboard with this idea. Thanks!