How to generate test samples with Hypothesis directly from dataclasses?

I have lets say two dataclasses where one is used inside the other like this :

@dataclass(frozen=True)
class SensorModel:
    sensor_id: int
    type: str 
    health_status: bool 

@dataclass
class SamplingModel:
    trigger: str
    priority: str = field(init=False)
    time: datetime
    sensors: List[SensorModel]

how can I use hypothesis to generate sample for my testing from this?

I have found in the docs that hypothesis strategies support dataclasses natively hypothesis but no examples ANYWHERE about how to do it in a simple case like the one described.

Ok so I found an answer, its turns out it is really simple you can use the from_type generator from_type documentation

In the simple example I described above one could do something like

from hypothesis import given
from hypothesis.strategies import from_type

@dataclass(frozen=True)
class SensorModel:
    sensor_id: int
    type: str 
    health_status: bool 

@dataclass
class SamplingModel:
    trigger: str
    priority: str = field(init=False)
    time: datetime
    sensors: List[SensorModel]

@given(sample=from_type(SamplingModel))
def test_samples(sample):
    assert sample.trigger == sample.trigger #point-less test replace with your logic