I'm using Pydantic v2 to validate Excel sheets in a workbook. I'm trying to dynamically generate acceptable values for certain fields as follows:

class IdFields(BaseModel):
    FacilityName: str = Field(..., max_length=200)
    FacilityCode: str = Field(None, max_length=30)
    #Year: int = Field(..., ge=2020)

class EquipmentType(IdFields):

    excel_sheet_name: ClassVar[str] = "Equipment"
    
    Count: int = Field(..., ge=0)
    Type: _options_to_literal(options_dict, 2023, 
       excel_sheet_name, "Type")

Elsewhere I've defined _options_to_literal to dynamically return a Literal object containing valid options for that field. So passing the dict name, year, excel_sheet_name, and field name, I might get something like Literal['Heater', 'Tank', 'Vacuum'].

I'd like to read in year from a JSON string passed to IdFields so its subclass can use that value to get the appropriate Literal:

test_data = {
   "FacilityName": "test",
   "FacilityCode": "123",
   "Year": 2023,
   "Count": 2,
   "Type": "Heater",
}
test_instance = EquipmentType(*test_data)

I can pass year just fine if I define it as a global variable but that seems ugly to me. I'm not sure if this is the best method anyways so your help is greatly appreciated.