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How do I share fixtures between classes in pytest?

I am trying to share class scope and method scope fixtures across different classes using pytest. Currently, I get a syntax error if I try to add a fixture from another class as shown below.
I am aware that one way to work around this is to not have the fixture enclosed by a class. However, enclosing the fixtures makes sense for what I am trying to do.
import pytest
class Test_example1(object):
#classmethod
#pytest.fixture(scope='class')
def example1_fixture(self):
print("example1_fixture setup")
yield
print("example1_fixture teardown")
def test_1(self, example1_fixture):
print("class example1::test_1")
# This works if I comment out the code causing errors
#pytest.fixture(scope='class')
def global_example_fixture():
print("global_example_fixture setup")
yield
print("global_example_fixture teardown")
class Test_example2(object):
#pytest.fixture(scope='class')
def example2_fixture(self):
print("example2_fixture setup")
yield
print("example2_fixture teardown")
# Results in fixture not found error
def test_1(self, example1_fixture):
print("class example2::test_1")
# Results in syntax error
def test_2(self, Test_example1.example1_fixture, global_example_fixture):
print("class example2::test_1")
# This works...
def test_2(self, example2_fixture, global_example_fixture):
print("class example2::test_2")
I expect to be able to call the class level and method level fixtures across classes.

Is it possible to run a single test method from a python unittest.TestCase with a reference to the method?

Suppose I have the following TestCase
class TestSomething(unittest.TestCase):
def test_a(self):
# Do some testing
def test_b(self):
# Do some other testing
Is it possible for me to run TestSomething.test_a if I have a reference to that test? What I am looking to do is something like:
def run_test(test):
# Somehow runs the test
# HERE IS THE PART I AM REALLY STUCK ON
run_test(TestSomething.test_a)
I know that it's an awkward thing to do for normal unit testing. What I am trying to do is provide a test to be run as an argument to a function decorator. Essentially:
#corresponding_test(TestSomething.test_a)
def my_function_a():
# Something here
And then in the decorator basically check if the test for that function passes before running the function.

OP clearly stated that the real world use case is more involved, but this still needs saying:
Disclaimer: This is not a good, standard way to run unit tests. If you use this code to run unit tests, you're [probably] doing it wrong.
That said, your question intrigued me, so I went ahead and wrote a working demo for you:
"""
The `only_if_test_passes` decorator can be used to run a function if and
only if the argument test (unbound `TestCase` method) passes.
"""
import inspect
from unittest import TestCase, TestResult
class TestError(Exception):
pass
class MyTests(TestCase):
def test_pass(self):
# This passes because nothing went wrong
pass
def test_fail(self):
self.fail('This test will always fail')
def only_if_test_passes(test_method):
# Comments are computed values when passed MyTests.test_pass
test_case_class = inspect._findclass(test_method) # MyTests
test_case_name = test_case_class.__name__ # 'MyTests'
test_name = test_method.__name__ # 'test_pass'
# Introspection for Python 2:
# test_case_class = test_method.im_class
# test_case_name = test_case_class.__name__ # Same as for Python 3
# test_name = test_method.if_func.func_name
def decorator(fn):
def decorated(*args, **kwargs):
test_result = TestResult()
case = test_case_class(test_name) # MyTests('test_pass')
case(test_result)
if test_result.wasSuccessful():
return fn(*args, **kwargs)
else:
raise TestError('Unit test failed: {}.{}'.format(
test_case_name, test_name))
return decorated
return decorator
#only_if_test_passes(MyTests.test_pass)
def this_will_run():
print('This should output')
#only_if_test_passes(MyTests.test_fail)
def this_wont_ever_run():
print("Don't bother; you'll never see this.")
if __name__ == "__main__":
this_will_run()
this_wont_ever_run()
gist
The introspection will be a little different in Python 2.
See also: unittest.TestCase docs

Passing different values to decorators for unit tests in Python

I have a situation where I'm trying to modify the arguments passed to a decorator on one of my class methods. The code looks something like this:
class MyClass(object):
#tryagain(retries=3)
def mymethod(self, arg):
... do stuff ...
My problem is I'd like to alter the "retries" variable to something less than 3 when running my unit tests, but keep it at "3" for the production code. Unfortunately, it doesn't look like I can do something like this:
#tryagain(retries=self.retries)
def mymethod(self, arg):
... do stuff ...
or
#tryagain(retries=MyClass.retries)
def mymethod(self, arg):
... do stuff ...
because the class isn't defined at the point the arguments are passed to the decorator (as near as I can tell).
I also tried to add the variable within the module like so:
retries = 1
def MyClass(object):
#tryagain(retries=retries)
def mymethod(self, arg):
... do stuff ...
but then I can't seem to modify the value of "retries" from within my unit tests. Is there another way to accomplish what I'm trying to do?

I assume you try to reduce the number of retrials to increase test speed.
If so, modifying the number of retries variable doesn't seem to be the best approach. Instead, you could unit test the function mymethod without decorator first, and then create a mock function of mymethod. Let's call it mock_mymethod, decorate it with #tryagain and test if the logic of `tryagain actually works.
Check the mock module to see how to create a mock instance, this article about mock is also worth reading.

You could use an environment variable, set from your calling code (it might be good to put a default in here
import os
# ...
class MyClass(object):
#tryagain(retries=int(os.environ['project_num_retries']))
def mymethod(self, arg):
print("mymethod")
Or use a "globals"-type module, for example: project_settings.py containing:
num_retries = 3
Then
import project_settings
class MyClass(object):
#tryagain(retries=project_settings.num_retries)
def mymethod(self, arg):
print("mymethod")
But I'm not sure decorating your code with test information is how you really should go about it -- what about:
class MyClass(object):
def mymethod(self, arg):
print("mymethod")
Then in something like unittests.py:
DEV_TESTS = True # Change to False for production
num_retries = 3 if not DEV_TESTS else 1
import <your class>
class UnitTests():
def __init__(self):
self.c = <your_class>.MyClass()
#tryagain(retries=num_retries)
def test_mymethod(self):
self.c.mymethod("Foo")
t = UnitTests()
t.test_mymethod()
If you were so inclined, this unittests.py could be used with something like python's unittest package with:
DEV_TESTS = True # Change to False for production
num_retries = 3 if not DEV_TESTS else 1
import unittest
import <your class>
class UnitTests(unittest.TestCase):
def setUp(self):
self.c = <your class>.MyClass()
#tryagain(retries=num_retries)
def test_mymethod(self):
self.c.mymethod("Foo")
Note, I used the following simple example of a #tryagain decorator, yours may be more complicated and require some tuning of the examples:
def tryagain(retries):
def wrap(f):
def wrapped_f(*args,**kwargs):
for _ in xrange(retries):
f(*args,**kwargs)
return wrapped_f
return wrap

Append the nose #attr to the test name

I am able to setup nose tests to run with the #attr tag. I am now interested in know if I can append to the end of the test name, the #attr tag? What we are trying to do is add a tag if our tests run into an issue and we write up a defect for it, we would then put the defect number as an #attr tag. Then when we run we could easily identify which tests have open defects against them.
Just wondering if this is even possible, and where to go to see how to set it up?
EDIT RESULTS RUNNING WITH ANSWER:
Test Results:
So I sort of know what is going on, if I have the #fancyattr() at the class level it picks it up and changes the name of the class. When I put the #fancyattr() at the test level it is not changing the name of the test, which is what I need for it to do.
For example - Changes the name of the class:
#dms_attr('DMSTEST')
#attr('smoke_login', 'smoketest', priority=1)
class TestLogins(BaseSmoke):
"""
Just logs into the system and then logs off
"""
def setUp(self):
BaseSmoke.setUp(self)
def test_login(self):
print u"I can login -- taking a nap now"
sleep(5)
print u"Getting off now"
def tearDown(self):
BaseSmoke.tearDown(self)
This is what I need and it isn't working:
#attr('smoke_login', 'smoketest', priority=1)
class TestLogins(BaseSmoke):
"""
Just logs into the system and then logs off
"""
def setUp(self):
BaseSmoke.setUp(self)
#dms_attr('DMSTEST')
def test_login(self):
print u"I can login -- taking a nap now"
sleep(5)
print u"Getting off now"
def tearDown(self):
BaseSmoke.tearDown(self)
Updated screenshot with what I am seeing with __doc__:

Here is how to do it with args type attributes:
rename_test.py:
import unittest
from nose.tools import set_trace
def fancy_attr(*args, **kwargs):
"""Decorator that adds attributes to classes or functions
for use with the Attribute (-a) plugin. It also renames functions!
"""
def wrap_ob(ob):
for name in args:
setattr(ob, name, True)
#using __doc__ instead of __name__ works for class methods tests
ob.__doc__ = '_'.join([ob.__name__, name])
#ob.__name__ = '_'.join([ob.__name__, name])
return ob
return wrap_ob
class TestLogins(unittest.TestCase):
#fancy_attr('slow')
def test_method():
assert True
#fancy_attr('slow')
def test_func():
assert True
Running test:
$ nosetests rename_test.py -v
test_method_slow ... ok
test_func_slow ... ok
----------------------------------------------------------------------
Ran 2 tests in 0.003s
OK
EDIT: For xunit reporting to work, test renaming should take place before running the test. You can do it on import, here is untested hack showing how to do it:
rename_test.py:
import unittest
def fancy_attr(*args, **kwargs):
"""Decorator that adds attributes to classes or functions
for use with the Attribute (-a) plugin. It also renames functions!
"""
def wrap_ob(ob):
for name in args:
setattr(ob, name, True)
ob.__doc__ = '_'.join([ob.__name__, name])
return ob
return wrap_ob
class TestLogins(unittest.TestCase):
#fancy_attr('slow')
def test_method(self):
assert True
def make_name(orig, attrib):
return '_'.join([orig, attrib])
def rename(cls):
methods = []
for key in cls.__dict__:
method = getattr(cls, key)
if method:
if hasattr(cls.__dict__[key], '__dict__'):
if 'slow' in cls.__dict__[key].__dict__:
methods.append(key)
print methods
for method in methods:
setattr(cls, make_name(method, 'slow'), cls.__dict__[key])
delattr(cls, method)
rename(TestLogins)
#fancy_attr('slow')
def test_func():
assert True

How can I define one setup function for all nosetests tests?

I'm using google app engine with python and want to run some tests using nosetest.
I want each test to run the same setup function. I have already a lot of tests, so I don't want to go through them all and copy&paste the same function. can I define somewhere one setup function and each test would run it first?
thanks.

You can write your setup function and apply it using the with_setup decorator:
from nose.tools import with_setup
def my_setup():
...
#with_setup(my_setup)
def test_one():
...
#with_setup(my_setup)
def test_two():
...
If you want to use the same setup for several test-cases you can use a similar method.
First you create the setup function, then you apply it to all the TestCases with a decorator:
def my_setup(self):
#do the setup for the test-case
def apply_setup(setup_func):
def wrap(cls):
cls.setup = setup_func
return cls
return wrap
#apply_setup(my_setup)
class MyTestCaseOne(unittest.TestCase):
def test_one(self):
...
def test_two(self):
...
#apply_setup(my_setup)
class MyTestCaseTwo(unittest.TestCase):
def test_one(self):
...
Or another way could be to simply assign your setup:
class MyTestCaseOne(unittest.TestCase):
setup = my_setup