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Hi all, is there a proper guide on how to use `pul...
# python
g
Hi all, is there a proper guide on how to use 
pulumi.input_type
decorator to define internal datatypes. I'm trying to use Pydantic + pulumi.input_type decorator to create schemas with validation + the ability to resolve nested Output attributes. But it looks like, the decorator is tampering the attributes which results in some weird behavior for pydantic models.
g
I'm not aware of a specific guide, but I also don't see this content in the docs, so perhaps the design doc that's embedded in the SDK might help? https://github.com/pulumi/pulumi/blob/master/sdk/python/lib/pulumi/_types.py#L15-L266
It has a bunch of examples
g
I'm using pydantic as well and I do not think you'll be able to resolve the Ouput because it's being executed in an async io event loop that you do not have access to from your pulumi code. So you'll have to rely on dicts (maybe typed dicts to the rescue). - This problem goes partially away in TypeScript where pulumi works with interfaces. Please let me know if you find a good solution for this. Because having to remember the structure is painful. Otherwise I just do this:
Copy code
from typing import Sequence, TypeVar, Union
from pydantic import BaseModel
import pulumi


T = TypeVar("T")
PulumiSequenceInputLike = Union[Sequence[T], pulumi.Output[T]]
PulumiInputLike = Union[T, pulumi.Output[T]]

class AutoScalingArgs(BaseModel):
    """Fargate autoscaling arguments."""

    memory_target_value: PulumiInputLike[int] = 60
    """Scale up when memory usage  exceeds the value [%]."""
    cpu_target_value: PulumiInputLike[int] = 60
    """Scale up when CPU usage  exceeds the value [%]."""
    max_tasks: PulumiInputLike[int] = 4
    min_tasks: PulumiInputLike[int] = 1
    desired_count: PulumiInputLike[int] = 1

    class Config:
        arbitrary_types_allowed = True
g
@great-sunset-355 did you find a solution? The 
pulumi.input_type
decorator is messing up the pydantic attributes
which causes default values to not work
g
Do you have any code with the problem? Simply is not possible to specify 
Input
type, you need to use 
Output
as a type
g
you can use input type, and I manage to get it to unwrap nested Input/Output attributes
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@pulumi.runtime.test
def test_person_with_default():
    from pydantic import BaseModel
    from typing import TypeVar, Union, Optional

    T = TypeVar("T")
    Input = Union[T, pulumi.Output[T]]

    class PulumiBaseModel(BaseModel):
        class Config:
            arbitrary_types_allowed = True

    @pulumi.input_type
    class Person(PulumiBaseModel):
        name: Optional[Input[str]] = "John Doe"

    a = Person()

    def check(a):
        assert a.name == "John Doe"

    return pulumi.Output.from_input(a).apply(check)
but the decorator breaks the default value in the pydantic model
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test_person_with_default Failed: [undefined]TypeError: __create_fn__.<locals>.__init__() missing 1 required keyword-only argument: 'name'
removing the decorator fixes this, but I can no longer easily unwrap nested outputs
g
Did you try to use post init or ovrride the init? There are some docs about it in pydantic. Else check issues/discussions. Another option is to drop pydantic and try dataclasses or attrs
g
I've cracked it! 😄
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