The existing @experimental decorator doesn't work particularly well when
trying to decorate a class. Previously, for vanilla class decorations,
things would mostly work:
foo = Foo()
ExperimentalWarning: "Foo" is an experimental function.
That error is mostly correct except for the fact that `Foo` is supposed
to be an experimental `class` and not an experimental `function`. But
it's more than just a copy error - becuase the `@experimental` decorator
is returning an `_inner` function, `Foo` truly is of type `function`.
The most immediate consequence is that nothing can property subclass
E TypeError: function() argument 'code' must be code, not str
It's a bit of a cryptic error but it's throwing because you can't
subclass a function. https://bugs.python.org/issue6829
An interesting Dagster-specific consequence is that you can't mark
anything that subclasses `ConfigurableClass` as `@experimental`:
E TypeError: issubclass() arg 1 must be a class
It's throwing because `issubclass` expects its first argument to
be a `class` and we're giving it a `function`:
One option is to take the approach that we took when introducing
`@experimental_decorator` - we could add a new `@experimental_class` and
leave it up to the author to correctly decide when to decorate with
`@experimental` and when to decorate with `@experimental_class`.
Instead, I've decided to conditionally switch on whether the callable
being decorated is a `function` or a `class`. If it's a `function`, we
do the same wrapping behavior we've always done. If it's a `class`, we
augment `__init__` to also include an `experimental_class_warning` but
we still return a `class`.