dima

on software
Posts from blog by tag testing:

The Hidden Cost of Test Inheritance

I'm subscribed to Adam Johnson's blog and usually really enjoy his writing - it's practical, deep, and no-bullshit. But one recent post, Python: sharing common tests in unittest, caught me off guard.

It describes a "neat" pattern: write reusable test logic in a base class, subclass it to test multiple objects, hiding the base class from unittest discovery. While the intent is fine - DRYing out duplicated test code - the result is fragile, confusing, and just not worth it.

Here's why.

The Pattern: DRY Tests via Subclassing

# Sample units to test
class Armadillo:
    def speak(self) -> str:
        return "Hrrr!"

class Okapi:
    def speak(self) -> str:
        return "Gronk!"

# Test module
class BaseAnimalTests(TestCase):
    animal_class: type

    def test_speak(self):
        sound = self.animal_class().speak()
        self.assertIsInstance(sound, str)
        self.assertGreater(len(sound), 0)

class ArmadilloTests(BaseAnimalTests):
    animal_class = Armadillo

class OkapiTests(BaseAnimalTests):
    animal_class = Okapi

del BaseAnimalTests

Yes, it works and it reduces duplication. But it comes at the cost of everything else that makes tests maintainable.

The Problems

IDE and DX Pain

IDE

When a test fails, I want to jump to it in my IDE, set a breakpoint, and debug. With this pattern - good luck.

The method doesn't exist in ArmadilloTests, it's buried in a deleted parent class. You have to manually hunt it down, re-declare the test method just to put a breakpoint and debug it, and pray the animal_class setup matches what failed:

class ArmadilloTests(TestCase):
    animal_class = Armadillo

    def test_speak(self):
        super().test_speak()

breakpoint

It's tedious and wastes time. All this to avoid writing a 3-line test twice?

class ArmadilloTests(TestCase):
    def test_speak(self):
        sound = Armadillo().speak()
        self.assertIsInstance(sound, str)
        self.assertGreater(len(sound), 0)

Clear, simple, debug-friendly. Worth the few extra lines.

CI Failures Are Confusing

If a shared test fails in CI, you get something like:

test_speak (tests.ArmadilloTests.test_speak) ... FAIL
...
Traceback (most recent call last):
  File ".../tests.py", line 20, in test_speak
    self.assertGreater(len(sound), 0)
AssertionError: 0 not greater than 0

But the method isn't defined in ArmadilloTests, and Search everywhere won't help at all:

nothing found

So now you have to reverse-engineer which base class it came from and how to recreate it locally.

This isn't clever. It's just fragile.

When It Kinda Makes Sense

There are rare cases:

  • dozens of classes implementing the same interface
  • you're the only one maintaining the codebase
  • you run everything headless in CI

But even then, you're building test framework plumbing to save what, a hundred lines?

The Clean Alternative: Parametrize It

Pytest Style

@pytest.mark.parametrize('animal_class', [Armadillo, Okapi])
def test_speak(animal_class):
    sound = animal_class().speak()
    assert isinstance(sound, str)
    assert len(sound) > 0

You see all the parameters. You see where the test lives. Failures are explicit:

test_speak[Armadillo] FAILED
test_speak[Okapi] PASSED

You can re-run just the failing test. You can debug with a conditional breakpoint. You don't need to explain how the tests are wired together - because they're not.

unittest Style (Optional, Not Ideal)

from parameterized import parameterized_class

@parameterized_class([
    {'animal_class': Armadillo},
    {'animal_class': Okapi},
], class_name_func=get_class_name)
class AnimalTests(TestCase):
    def test_speak(self):
        sound = self.animal_class().speak()
        self.assertIsInstance(sound, str)
        self.assertGreater(len(sound), 0)

Using parameterized_class from parameterized is still better than inheritance, but clunkier. Output is readable if you customize class_name_func. IDE support isn't great. Pytest remains the better option for anything dynamic.

Final Verdict

Tests should fail clearly, debug easily, and be readable years later. This pattern fails all three.

DRY is good. But in tests, visible duplication beats invisible abstraction.

Adam's trick technically works, but in practice, it makes tests harder to navigate, harder to trust, and harder to work with.

Stick to the boring version - you'll thank yourself later.

Why Django's override_settings Sometimes Fails (and How reload + patch Saved Me)

Sometimes @override_settings just doesn’t cut it.

I ran into a nasty issue while testing a Django module that relies on global state initialized during import. The usual test approach didn’t work. Here’s what happened and how I solved it.

The Setup

We had a module that builds a global dictionary from Django settings at import time. Let’s call it dragon.py, which takes settings.PUT_EGGS, which is False by default:

from django.conf import settings

DRAGON = {}
...
if settings.PUT_EGGS:
    DRAGON["eggs"] = "spam"

Another module uses DRAGON for core logic, e.g. mario.py:

from myproject.dragon import DRAGON

def find_eggs():
    if "eggs" in DRAGON:
        return "Found eggs!"
    return "Eggs not found"

Now I wanted to write a test that tweaks DRAGON and expects the logic to behave differently. Easy, right?

@override_settings(PUT_EGGS=True)
def test_find_eggs():
    assert find_eggs() == "Found eggs!"

Wrong. The test failed.

The Problem

override_settings works, but only for code that reads settings at runtime.

In my case, DRAGON was already built at import time , before the override kicked in. So it used the old value of PUT_EGGS, no matter what I did in the test.

This is the classic trap of global state baked during import. Welcome to pain town.

The Fix: reload + patch

Here's how I got out:

import importlib
from django.test import override_settings
from unittest.mock import patch
from myproject.mario import find_eggs

@override_settings(PUT_EGGS=True)
def test_find_eggs():
    # Reload the dragon module so DRAGON is rebuilt
    # with updated settings
    from myproject import dragon
    new_dragon = importlib.reload(dragon)

    # Patch the logic module to use the reloaded DRAGON
    with patch('myproject.mario.DRAGON', new_dragon.DRAGON):
        result = find_eggs()
        assert result == "Found eggs!"

Why This Works

  • importlib.reload(dragon) forces a fresh import of dragon, rebuilding DRAGON with the overridden settings;
  • dragon.DRAGON is updated in the scope of the test only, i.e. mario module still has the stale version of DRAGON;
  • patch(...) solves this problem by swapping the old DRAGON in mario with the freshly rebuilt one.

This is surgical. Ugly, but effective.

Lessons Learned

  • Avoid putting non-trivial logic at module scope, especially if it depends on Django settings. Wrap it in a function or lazy loader.
  • If you're stuck with global state, reload() and patch() give you a way out - just be careful about cascading dependencies.

If you’ve ever had a test mysteriously fail after overriding settings, this might be why.