Hi Ethan,

You have the right idea with mocking the decorator. In order for it to work, you could use monkeypatch to override the decorator with its mock and use importlib.reload to ensure that the changes are reflected (module caching appears to be the reason for which your mock isn't applying as expected.

E.g
You have a function that substracts 2 from a provided value, and a decorator defined in mydecorator.py that adds 4 to the value:

from mydecorator import add_four_decorator

@add_four_decorator
def subtract(a):
    return a - 2

Mocking add_four_decorator in the unit test would look like the following:

import calculator

def do_nothing(func):
    def wrapper(*args, **kwargs):
        return func(*args, **kwargs)
    return wrapper
    
def test_calculator_subtract(monkeypatch):
    monkeypatch.setattr('mydecorator.add_four_decorator', do_nothing)
    import importlib
    importlib.reload(calculator)
    res = calculator.subtract(12)
    assert res == 10

Above we are grabbing the monkeypatch fixture and using monkeypatch.setattr to pass in the <file_path>.<function_name> of the decorator, and the decorator to replace it with as the second parameter. We are then using importlib.relead to import the module again (rather than using the cached file) to ensure the mock is applied.

The same idea would apply with ajax here and your test_func_to_be_tested would contain something like this:

from q2_sdk.core import web
async def test_func_to_be_tested(mock_success_class):
...
monkeypatch.setattr('q2_sdk.core.web.ajax', mock_decorator)
import importlib
importlib.reload(web)
actual = await handler.func_to_be_tested()
assert isinstance(actual, type(mock_success))