I want to test a file called ninja.py wrote in Python3.6.
# File ninja.py
def what_to_do_result(result):
# Send a mail, write something in a file, play a song or whatever
def my_function(a, b):
# Step 1
result = a + b
# Step 2
if result == 3:
what_to_do_result(result)
elif result == 5:
what_to_do_result(result + 1)
else:
return True
I have started writing a test file called test_ninjapy and wrote some unittest. I do use Pytest.
import pytest
class MyTestException(Exception):
pass
def run_side_effect(*args, **kwargs):
raise MyTestException(kwargs["result"])
#pytest.fixture(name="resource")
def setup_fixture():
# Some code here
class TestNinja:
#staticmethod
def setup_method():
# Function called before each test
#staticmethod
def teardown_method():
# Function called after each test
#staticmethod
def test_my_function(mocker, resource):
# How to do this ???
mocker.patch("ninja.what_to_do_result", return_value=None, side_effect=run_side_effect)
# Then the test
assert 1 == 1 # -> This works
with pytest.raises(MyTestException):
ninja_function(a=1, b=2)
assert ninja_function(a=5, b=10)
The point is that I want to mock the function ninja.what_to_do_result and apply a side effect (= run a function).
I want the side effect to use the parameter (kwargs) or the function what_to_do_result.
But I don't know how to do this.
For example:
Because there are multiple possibilities (in the step 2, the call of what_to_do_result could be with 3 & 5, which are linked with 2 differents use cases I wxant to test.
Can you help me?
I did not found the related section in the documentation below.
Link to the documentation: https://github.com/pytest-dev/pytest-mock
Related
I had created a simple example to illustrate my issue. First is the setup say mydummy.py:
class TstObj:
def __init__(self, name):
self.name = name
def search(self):
return self.name
MyData = {}
MyData["object1"] = TstObj("object1")
MyData["object2"] = TstObj("object2")
MyData["object3"] = TstObj("object3")
def getObject1Data():
return MyData["object1"].search()
def getObject2Data():
return MyData["object2"].search()
def getObject3Data():
return MyData["object3"].search()
def getExample():
res = f"{getObject1Data()}{getObject2Data()}{getObject3Data()}"
return res
Here is the test that failed.
def test_get_dummy1():
dummy.MyData = MagicMock()
mydummy.MyData["object1"].search.side_effect = ["obj1"]
mydummy.MyData["object2"].search.side_effect = ["obj2"]
mydummy.MyData["object3"].search.side_effect = ["obj3"]
assert mydummy.getExample() == "obj1obj2obj3"
The above failed with run time error:
/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/unittest/mock.py:1078: StopIteration
Here is the test that passed:
def test_get_dummy2():
dummy.MyData = MagicMock()
mydummy.MyData["object1"].search.side_effect = ["obj1", "obj2", "obj3"]
assert mydummy.getExample() == "obj1obj2obj3"
Am I missing something? I would have expected test_get_dummy1() to work and test_get_dummy2() to fail and not vice versa. Where and how can I find/learn more information about mocking to explain what is going on...
MyData["object1"] is converted to this function call: MyData.__getitem__("object1"). When you call your getExample method, the __getitem__ method is called 3 times with 3 parameters ("object1", "object2", "object3").
To mock the behavior you could have written your test like so:
def test_get_dummy_alternative():
mydummy.MyData = MagicMock()
mydummy.MyData.__getitem__.return_value.search.side_effect = ["obj1", "obj2", "obj3"]
assert mydummy.getExample() == "obj1obj2obj3"
Note the small change from your version: mydummy.MyData["object1"]... became: mydummy.MyData.__getitem__.return_value.... This is the regular MagicMock syntax - we want to to change the return value of the __getitem__ method.
BONUS:
I often struggle with mock syntax and understanding what's happening under the hood. This is why I wrote a helper library: the pytest-mock-generator. It can show you the actual calls made to the mock object.
To use it in your case you could have added this "exploration test":
def test_get_dummy_explore(mg):
mydummy.MyData = MagicMock()
mydummy.getExample()
mg.generate_asserts(mydummy.MyData, name='mydummy.MyData')
When you execute this test, the following output is printed to the console, which contains all the asserts to the actual calls to the mock:
from mock import call
mydummy.MyData.__getitem__.assert_has_calls(calls=[call('object1'),call('object2'),call('object3'),])
mydummy.MyData.__getitem__.return_value.search.assert_has_calls(calls=[call(),call(),call(),])
mydummy.MyData.__getitem__.return_value.search.return_value.__str__.assert_has_calls(calls=[call(),call(),call(),])
You can easily derive from here what has to be mocked.
I currently have the following basic Python class that I want to test:
class Example:
def run_steps(self):
self.steps = 0
while self.steps < 4:
self.step()
def step(self):
# some expensive API call
print("wasting time...")
time.sleep(1000)
self.steps += 1
As you can see, the step() method contains an expensive API call so I want to mock it with another function that avoids the expensive API call but still increments self.steps. I found that this is possible by doing this (as seen from here):
def mock_step(self):
print("skip the wasting time")
self.steps += 1
# This code works!
def test(mocker):
example = Example()
mocker.patch.object(Example, 'step', mock_step)
example.run_steps()
I simply create a function called mock_step(self) that avoids the API call, and I patch the original slow step() method with the new mock_step(self) function.
However, this causes a new problem. Since the mock_step(self) function is not a Mock object, I can't call any of the Mock methods on it (such as assert_called() and call_count()):
def test(mocker):
example = Example()
mocker.patch.object(Example, 'step', mock_step)
example.run_steps()
# this line doesn't work
assert mock_step.call_count == 4
To solve this issue, I have tried to wrap mock_step with a Mock object using the wraps parameter:
def test(mocker):
example = Example()
# this doesn't work
step = mocker.Mock(wraps=mock_step)
mocker.patch.object(Example, 'step', step)
example.run_steps()
assert step.call_count == 4
but then I get a different error saying mock_step() missing 1 required positional argument: 'self'.
So from this stage I am not sure how I can assert that step() has been called exactly 4 times in run_steps().
There are several solutions to this, the simplest is probably using a standard mock with a side effect:
def mock_step(self):
print("skip the wasting time")
self.steps += 1
def test_step(mocker):
example = Example()
mocked = mocker.patch.object(Example, 'step')
mocked.side_effect = lambda: mock_step(example)
example.run_steps()
assert mocked.call_count == 4
side_effect can take a callable, so you can both use a standard mock and the patched method.
import unittest.mock as mock
from functools import partial
def fake_step(self):
print("faked")
self.steps += 1
def test_api():
api = Example()
with mock.patch.object(api, attribute="step", new=partial(fake_step, self=api)):
# we need to use `partial` to emulate that a real method has its `self` parameter bound at instantiation
api.run_steps()
assert api.steps == 4
Correctly outputs "faked" 4 times.
I'm having some issue while creating unittest for internal parameter.
My structure is:
[1] my_animal.py contains Myclass and method: do_bite()
my_animal.py
class Myclass():
def do_bite(self):
return 1
[2] my_module.py contains jobMain("") which is using the method from my_animal.py
my_module.py
import sys
from someclass import Myclass
def jobMain(directoryPath):
flag = -1
result = Myclass()
if result.do_bite() is None:
flag = 0
if result.do_bite() is 1:
flag = 1
if result.do_bite() is 2:
flag = 2
[3] my_test.py contains the unittest to test jobMain in my_module.py
my_test.py
# Mock Myclass.dobite to None
#pytest.fixture
def mock_dobite0():
with mock.patch('my_module.Myclass') as mocked_animal:
mocked_animal.return_value.do_bite.return_value = None
yield
# Mock Myclass.dobite to 1
#pytest.fixture
def mock_dobite1():
with mock.patch('my_module.Myclass') as mocked_animal:
mocked_animal.return_value.do_bite.return_value = 1
yield
# Mock Myclass.dobite to 2
#pytest.fixture
def mock_dobite2():
with mock.patch('my_module.Myclass') as mocked_animal:
mocked_animal.return_value.do_bite.return_value = 2
yield
# My unittest to test dobite() method
def test_dobite0(mock_Myclass, mock_dobite0):
jobMain("")
def test_dobite1(mock_Myclass, mock_dobite1):
jobMain("")
def test_dobite2(mock_Myclass, mock_dobite2):
jobMain("")
My question is: How to test 'flag' parameter inside JobMain?
'flag' para must be assigned the correct value.( eg: dobite = 1 => flag = 1)
The variable para only exists in the scope of jobMain. If you want to use the variable outside jobMain the most common ways are
1) return the value
This is quite obvious. Since jobMain is a function, it returns a value. Without an explicit return statement you return None. You could just
def jobmain(pth):
# do stuff and assign flag
return flag
# and inside tests
assert jobmain("") == 1
2) Use a class instead
If you want the jobMain to remember some state, then it is common practice to use objects. Then flag would be attribute of the object and could be accessed from outside, after you call any method (function) of JobMain. For example
class JobMain:
def __init__(self):
self.flag = -1
def run(self, pth):
result = Myclass()
if result.do_bite() is None:
self.flag = 0
if result.do_bite() is 1:
self.flag = 1
if result.do_bite() is 2:
self.flag = 2
# and inside test
job = JobMain()
job.run()
assert job.flag == 1
Note
I just copy-pasted your code for setting the flag. Note that you call do_bite() many times, if the resulting value is None or 1. Also, when testing against a number, one should use == instead of is.
How to test 'flag' parameter inside JobMain?
You don't. It's an internal variable. Testing it would be glass-box testing; the test will break if the implementation changes.
Instead, test the effect of flag. This is black-box testing. Only the interface is tested. If the implementation changes the test still works allowing the code to be aggressively refactored.
Note: If you don't hard code result = Myclass() you don't need to mock. Pass it in as an argument with the default being Myclass().
def jobMain(directoryPath, result=Myclass()):
Then you don't need to patch Myclass(). Instead, pass in a mock object.
# I don't know unittest.mock very well, but something like this.
mock = Mock(Myclass)
mock.do_bite.return_value = 2
jobMain('', result=mock)
This also makes the code more flexible outside of testing.
report.py
if __name__ == "__main__":
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter, description = "CHECK-ACCESS REPORTING.")
parser.add_argument('--input','-i', help='Filepath containing the Active Directory userlist')
parser.add_argument('--timestamp', '-t', nargs='?',const="BLANK", help='filepath with environement varible set')
args, unknownargs = parser.parse_known_args(sys.argv[1:])
timestampchecker(args.timestamp)
#checking the value of cons.DISPLAYRESULT is TRUE
main()
timestampchecker function :
def timestampchecker(status):
""" Check if the timestamp is to display or not from command line"""
if status is not None:
cons.DISPLAY_TIME_STAMP = True
This function checks if the user have set the -t arguments. If it is set I have defined one constant called cons.DISPLAYRESULT to true.
The function is working great and turning the constant value to True.
But in the main function I have implemented this decorators which is not taking the true value but false
timer.py
def benchmarking(timestaus):
def wrapper(funct):
def timercheck(*args, **kwarg):
if timestaus is True:
starttime=time.time()
funct(*args, **kwarg)
if timestaus is True:
print('Time Taken:',round(time.time()-starttime, 4))
return timercheck
return wrapper
I have decorated some method in main() method of report.py with the decorators above. For example This is the class being used in report.py and being decorated with above decorators
class NotAccountedReport:
def __init__(self, pluginoutputpath):
""" Path where the plugins result are stored need these files"""
self.pluginoutputpath = pluginoutputpath
#benchmarking(cons.DISPLAY_TIME_STAMP)
def makeNotAccountableReport():
#some functionality
here I have passed the constant value to the argument decorator which
when tested though before called is converted to True is taking false
and thus the decorators not being implemented. Where is the problem
cant figure out
You didn't post a complete minimal verifiable example so there might be something else too, but if your point is that when calling NotAccountedReport().makeNotAccountableReport() you don't get your "Time taken" printed then it's really not a surprise - the benchmarking decorator is applied when the function is defined (when the module is imported), well before the if __name__ == '__main__' clause is executed, so at that time cons.DISPLAY_TIME_STAMP has not been updated by your command line args.
If you want a runtime flag to activate / deactivate your decorator's behaviour the obvious solution is to check cons.DISPLAY_TIME_STAMP within the decorator instead of passing it as argument, ie:
def benchmarking(func):
def timercheck(*args, **kwarg):
if cons.DISPLAY_TIME_STAMP:
starttime=time.time()
result = func(*args, **kwarg)
if cons.DISPLAY_TIME_STAMP:
logger.debug('Time Taken: %s',round(time.time()-starttime, 4))
return result
return timercheck
class NotAccountedReport(object):
#benchmarking
def makeNotAccountableReport():
#some functionality
Like ruby, how to pass code block and get it executed (yield) where you pass it. I am trying to achieve same thing in python 3.5
This is what my pseudo code looks like. How to achieve what I am trying to do. What changes would I have to make?
# Calculate all
# I want this function should yield whatever method passed to it
# THIS MUST BE A CLASS
class Calculator:
def __init__(self):
self.prefix = "hello"
def calculate(self, function_name)
local_val = 10
print("executing {} function with {}".format(function_name, self.prefix))
result = function_name(local_val)
print(result)
return result
# I want to pass these functions to Calculator().calculate() method
def add_one(x):
return x+1
def minus_one(x):
return x-1
def divide_in_half(x):
return x/2
Calculator().calculate(add_one(?))
# expect this to print:
# executing add_one function with hello
# 11
Calculator().calculate(minus_one(?))
# expect this to print:
# executing minus_one function with hello
# 9
Calculator().calculate(divide_in_half(?))
# expect this to print:
# executing divide_in_half function with hello
# 5
Functions are objects in Python, so you can just do this:
Calculator().calculate(add_one)
Calculator().calculate(minus_one)
Calculator().calculate(divide_in_half)
Note that this passes the function itself and not the name of the function. (In your code, you would have to access function_name.func_name to obtain the function's name, so I would suggest renaming function_name to fn, which is short for "function.")
You don't even need to declare predefined functions. You can use the lambda syntax to pass an anonymous callable on the fly:
# Instead of add_one, for example:
Calculator().calculate(lambda x: x + 1)
Initially, fix your __init__ so it doesn't complain when called with no args:
def __init__(self, prefix="hello")
use the function __name__ in the call to format done in calculate:
msg = "executing {} function with {}"
print(msg.format(function_name.__name__, self.prefix))
then pass the function objects along:
Calculator().calculate(add_one)
# expect this to print:
# executing add_one function with hello
# 11
Calculator().calculate(minus_one)
# expect this to print:
# executing minus_one function with hello
# 9
Calculator().calculate(divide_in_half)
# expect this to print:
# executing divide_in_half function with hello
# 5