Testing a function with a #cache.memoize gives PicklingError - flask

Question

I have some tests for functions that use cache, for example:
Function:
#retry(stop=stop_after_attempt(3))
#cache.cached(timeout=60, key_prefix='resouce_group_list')
def get_azure_resource_groups():
data = []
resource_client = get_azure_resource_client()
for item in resource_client.resource_groups.list():
data.append(item)
return data
Test:
#patch("dev_maintenance.machines.get_azure_resource_client")
def test_get_azure_list_rg(get_azure_resource_client):
cache.clear()
data = []
with app.app_context():
ret = get_azure_resource_groups()
get_azure_resource_client.assert_called_once()
expected = get_azure_resource_client.return_value.resource_groups.list.return_value
assert len(get_azure_resource_client.return_value.method_calls) == 1
for item in expected:
data.append(item)
assert ret == data
cache.clear()
The above test works fine, it passes, no errors and the test is using cache.
But i got other tests, and the decorator here does not matter, it will give the same error if i change the decorator to #cache.cache:
Function:
#retry(stop=stop_after_attempt(3))
#cache.memoize(60)
def get_azure_machine_info(rg_name, machine_name, expand="instanceView"):
try:
compute_client = get_azure_compute_client()
return compute_client.virtual_machines.get(rg_name, machine_name, expand=expand)
except CloudError:
return None
Test:
#patch("dev_maintenance.machines.get_azure_compute_client")
def test_get_azure_machine_info (get_azure_compute_client):
cache.delete_memoized(get_azure_machine_info)
with app.app_context():
ret = get_azure_machine_info("rg1", "m1")
print(ret)
get_azure_compute_client.assert_called_once()
assert len(get_azure_compute_client.return_value.method_calls) == 1
assert (
ret == get_azure_compute_client.return_value.virtual_machines.get.return_value
)
get_azure_compute_client.return_value.virtual_machines.get.assert_called_once_with(
"rg1", "m1", expand="instanceView"
)
cache.delete_memoized(get_azure_machine_info)
Now here the test fails with the error on this line ret = get_azure_machine_info("rg1", "m1"):
value = None, from_value = PicklingError("Can't pickle <class 'unittest.mock.MagicMock'>: it's not the same object as unittest.mock.MagicMock")
> ???
E tenacity.RetryError: RetryError[<Future at 0x105c7c3d0 state=finished raised PicklingError>]
<string>:3: RetryError
I tried to mock the cache passing a patch decorator like:
#patch("dev_maintenance.machines.cache") or #patch("dev_maintenance.cache")
I tried to set the CACHE_TYPE to null in the test case, instantiating the cache object and passing the config:
cache = Cache()
cache.init_app(app, config={"CACHE_TYPE": "redis"})
but no success so far, any help?

Answer 1

This is a reference to an old answer, but I think that generally MagicMock objects aren't meant to be pickled: https://github.com/thadeusb/flask-cache/issues/52
That error message is different though, and this is more similar to what you are seeing:
Is there a way to make python pickle ignore "it's not the same object " errors
Maybe you could replace the domain prefix to the class like the answer above, but I am not sure it will overcome the other difficulties of pickling a MagicMock class:
`#patch("__main__.get_azure_compute_client")`

Answer 2

I'am writing the answer here for people that need to test functions that are cached with flask-caching and have the same error then me.
What i needed was to create an Object inside the test and make the mock_value = Object like this:
First i create a simple class:
class MachineInfo(object):
pass
Then in my test:
#patch("dev_maintenance.machines.get_azure_compute_client")
def test_get_azure_machine_info (get_azure_compute_client):
cache.clear()
expected_res = MachineInfo()
expected_res.id = "id"
expected_res.name = "machine1"
expected_res.location = "location"
expected_res.hardware_profile = "hardware"
expected_res.storage_profile = "storage"
expected_res.network_profile = "network_profile"
get_azure_compute_client.return_value.virtual_machines.get.return_value = expected_res
res = get_azure_machine_info("rg1", "m1")
assert res == expected_res
cache.clear()
Then i could assert function_call() == Object or function_call() == mock.return_value
This simulates what the actual azure returns, an object, so i just make the mock return the object that i created so i can simulate the function itself.