@Marvin Can you provide an example of a prefect flow that uses a Pydantic class for its parameters, where one of the attributes is a union of two subclasses, defined with discriminator option?

To create a Prefect flow using a Pydantic class for parameters, you can define a Pydantic model with attributes, including a union of subclasses using the discriminator option. Here's a basic example: First, ensure you have the necessary imports:

python
from prefect import flow
from pydantic import BaseModel, Field
from typing import Union, Literal

# Define your subclasses
class Cat(BaseModel):
    type: Literal['cat']
    meow_volume: int

class Dog(BaseModel):
    type: Literal['dog']
    bark_volume: int

# Define the main model using a discriminator
class Pet(BaseModel):
    pet: Union[Cat, Dog] = Field(..., discriminator='type')

# Define your Prefect flow
@flow
def my_flow(pet: Pet):
    if pet.pet.type == 'cat':
        print(f"A cat with meow volume {pet.pet.meow_volume}")
    elif pet.pet.type == 'dog':
        print(f"A dog with bark volume {pet.pet.bark_volume}")

# Example usage
my_flow(pet=Pet(pet={"type": "cat", "meow_volume": 5}))

### Key Points: - Pydantic Models: You can use Pydantic models to enforce and validate flow parameters. - Union with Discriminator: The

discriminator

field allows Pydantic to determine which subclass to use based on a specified field (

type

in this example). For more information on using Pydantic with Prefect, you can refer to the Prefect documentation.