Context

I'm trying to validate/parse some data with pydantic.

I want to specify that the dict can have a key daytime, or not. If it does, I want the value of daytime to include both sunrise and sunset.

e.g. These should be allowed:

{
   'type': 'solar',
   'daytime': {
      'sunrise': 4, # 4am
      'sunset': 18 # 6pm
   }
}

And

{
   'type': 'wind'
   # daytime key is omitted
}

And

{
   'type': 'wind',
   'daytime': None
}

But I want to fail validation for

{
   'type': 'solar',
   'daytime': {
      'sunrise': 4
   }
}

Because this has a daytime value, but no sunset value.

MWE

I've got some code that does this. If I run this script, it executes successfully.

from pydantic import BaseModel, ValidationError
from typing import List, Optional, Dict

class DayTime(BaseModel):
    sunrise: int
    sunset: int
    
class Plant(BaseModel):
    daytime: Optional[DayTime] = None
    type: str

p = Plant.parse_obj({'type': 'wind'})
p = Plant.parse_obj({'type': 'wind', 'daytime': None})
p = Plant.parse_obj({
    'type': 'solar', 
    'daytime': {
        'sunrise': 5, 
        'sunset': 18
    }})
    
try:
    p = Plant.parse_obj({
        'type': 'solar', 
        'daytime': {
            'sunrise': 5
        }})
except ValidationError:
    pass
else:
    raise AssertionError("Should have failed")

Question

What I'm wondering is, is this how you're supposed to use pydantic for nested data?

I have lots of layers of nesting, and this seems a bit verbose.

Is there any way to do something more concise, like:

class Plant(BaseModel):
    daytime: Optional[Dict[('sunrise', 'sunset'), int]] = None
    type: str