Define the inputs to a workflow by adding parameters to the function definition.
from prefect import flow
@flow
def my_workflow(name: str = "World"):
return f"Hello, {name}!"
Pass arguments to the function call to provide inputs to the workflow.
my_workflow(name="Marvin")
By default, Prefect will validate the types of inputs to your workflow.
from prefect import flow
@flow
def my_workflow(name: str = "World"):
return f"Hello, {name}!"
my_workflow(name=1) # This will fail with a type validation error
To turn off type validation, set the validate_parameters parameter to False:
from prefect import flow
@flow(validate_parameters=False)
def my_workflow(name: str = "World"):
return f"Hello, {name}!"
my_workflow(name=1)
If you use pydantic, parameters typed with a BaseModel subclass will be coerced to the appropriate types and validated.
from prefect import flow
from pydantic import BaseModel
class Model(BaseModel):
a: int
b: str
@flow
def flow_that_validates_parameters(model: Model): ...
flow_that_validates_parameters(
model={"a": "WRONG", "b": "fine"}
)
