I have the class with .upload method. This method is wrapped using the decorator:
#retry(tries=3)
def upload(self, xml_file: BytesIO):
self.client.upload(self._compress(xml_file))
I need to test if it runs 3 times if some exception occurs.
My test looks like:
#mock.patch("api.exporter.jumbo_uploader.JumboZipUploader.upload")
def test_upload_xml_fail(self, mock_upload):
"""Check if decorator called the compress function 3 times"""
generator = BrandBankXMLGenerator()
file = generator.generate()
uploader = JumboZipUploader()
uploader.upload = retry(mock_upload)
mock_upload.side_effect = Exception("Any exception")
uploader.upload(file)
self.assertEqual(mock_upload.call_count, 3)
I have read that the default behavior of python decorators assumes that the function inside the test will be unwrapped and I need to wrap it manually.
I did that trick, but the code fails with AssertionError: 0 != 3.
So, what is the right way here to wrap the decorated method properly?
Related
So I am quite new to mocking. I think I need to mock two functions.
Function under test
def get_text_from_pdf(next_pdfs_path):
# TODO test this function
"""
pulls all text from a PDF document and returns as a string.
Parameters:
next_pdfs_path (str): file path use r"" around path.
Returns:
text (str): string of text
"""
if os.path.isfile(next_pdfs_path): # check file is a real file/filepath
try:
text = ''
with fitz.open(next_pdfs_path) as doc: # using PyMuPDF
for page in doc:
text += page.getText()
return text
except (RuntimeError, IOError):
pass
pass
test code first try
from unittest import mock
#mock.patch("content_production.fitz.open", return_value='fake_file.csv', autospec=True)
def test_get_text_from_pdf(mock_fitz_open):
assert cp.get_text_from_pdf('fake_file.csv') == 'fake_file.csv'
error
E AssertionError: assert None == 'fake_file.csv'
E + where None = <function get_text_from_pdf at 0x00000245EDF8CAF0>('fake_file.csv')
E + where <function get_text_from_pdf at 0x00000245EDF8CAF0> = cp.get_text_from_pdf
Do I need to mock both fitz.open and os.path.isfile? How could that be done if yes?
EDIT
Following njriasan feedback I have tried this
#mock.patch("content_production.os.path.isfile", return_value=True, autospec=True)
#mock.patch("content_production.fitz.Page.getText")
#mock.patch("content_production.fitz.open")
def test_get_text_from_pdf(mock_fitz_open, mock_path_isfile, mock_gettext):
mock_fitz_open.return_value.__enter__.return_value = 'test'
assert cp.get_text_from_pdf('test') == 'test'
But now getting this error.
> text += page.getText()
E AttributeError: 'str' object has no attribute 'getText'
I think there are a couple issues with what you are doing. The first problem I see is that I think you are mocking the wrong function. By mocking fitz.open(next_pdfs_path) you are still expecting:
for page in doc:
text += page.getText()
to execute properly. I'd suggest that you wrap this entire with statement and text result updating in a helper function and then mock that. If the file path doesn't actually exist on your system then you will also need to mock os.path.isfile. I believe that can be done by adding a second decorator (I don't think there is any limit).
I have a python file (a.py) which defines a function, and a class which uses it as a default parameter in it's init method and initializes another imported class. This is my a.py
import OtherClass
def useful_default_func():
//do something useful
class MyClass(object):
def __init__(self, def_func=useful_default_func):
self.other_class = OtherClass(def_func())
//do something useful
I am trying to mock the useful_default_func in my test file.
class TestMyClass(unittest.TestCase):
#patch('a.useful_default_func')
#patch('a.OtherClass')
test_init(self, mock_other_class, mock_default_func):
myc= MyClass()
mock_other_class.assert_called_once_with(mock_default_func)
// further tests
However, the mock_default_func is not patching and my test fails saying,
Expected: OtherClass(<MagicMock id='xxx'>)
Actual: OtherClass(<function useful_default_func at 0x7f155858b378>)
Fairly new to the python mock lib, so not really sure, what is happening here or what I am doing wrong or how should I be approaching it?
Something like this could work:
def mocked_fct():
return 42
class TestMyClass(unittest.TestCase):
#mock.patch.object(a.MyClass.__init__, '__defaults__', (mocked_fct,))
#patch('a.OtherClass')
def test_init(self, mock_other_class):
myc = MyClass()
mock_other_class.assert_called_once_with(mocked_fct)
I didn't use a mock for the mocked default function here, this can be changed if needed. The main point is that you can mock the function defaults.
Note: this assumes that you call
self.other_class = OtherClass(def_func)
instead of
self.other_class = OtherClass(def_func())
If this was not a typo, your assertion would not be correct. In this case, you could instead use:
mock_other_class.assert_called_once_with(mocked_fct())
mock_other_class.assert_called_once_with(42) # same as above
def fixed_given(self):
return #given(
test_df=data_frames(
columns=columns(
["float_col1"],
dtype=float,
),
rows=tuples(
floats(allow_nan=True, allow_infinity=True)),
)
)(self)
#pytest.fixture()
#fixed_given
def its_a_fixture(test_df):
obj = its_an_class(test_df)
return obj
#pytest.fixture()
#fixed_given
def test_1(test_df):
#use returned object from my fixture here
#pytest.fixture()
#fixed_given
def test_2(test_df):
#use returned object from my fixture here
Here, I am creating my test dataframe in a seperate function to use it commonly across all functions.
And then creating a pytest fixture to instantiate a class by passing the test dataframe generated by a fixed given function.
I am finding a way to get a return value from this fixture.
But the problem i am using a given decorator, its doesn't allow return values.
is there a way to return even after using given decorator?
It's not clear what you're trying to acheive here, but reusing inputs generated by Hypothsis gives up most of the power of the framework (including minimal examples, replaying failures, settings options, etc.).
Instead, you can define a global variable for your strategy - or write a function that returns a strategy with #st.composite - and use that in each of your tests, e.g.
MY_STRATEGY = data_frames(columns=[
column(name="float_col1", elements=floats(allow_nan=True, allow_infinity=True))
])
#given(MY_STRATEGY)
def test_foo(df): ...
#given(MY_STRATEGY)
def test_bar(df): ...
Specifically to answer the question you asked, you cannot get a return value from a function decorated with #given.
Instead of using fixtures to instantiate your class, try using the .map method of a strategy (in this case data_frames(...).map(its_an_class)), or the builds() strategy (i.e. builds(my_class, data_frames(...), ...)).
I am writing a python class and trying to call a function from another function in the class but I am running into an error.NameError: name 'bobfunction' is not defined. My call to the class works, even the call to method/function job works. When job tries to call bobfunction I get the error message. removing the call to bobfunction works. So how do I call the bobfunction from the job function?
class stuff():
def __init__(self):
#setup stuff
def bobfunction(self,junk):
print("should work")
return ''
def job(self,data):
bobfunction('test data')
return 'other junk'
Run it with self.bobfunction("test data")
Python uses the keyword self to refer to class methods and variables of the same class. It is similar to this keyword in other languages. (Not the same though) . If you end up defining a variable in your __init__ function , you can also use it with self.variable_name in other functions.
You should try to run it with stuff.bobfunction(self,"test data")
Because bobfunction was situated in class stuff, you need to write class' name before function's name.
Self in parentheses must send the name of self.
I have a use case where I need to mock a member variable but I want it to return a different value every time it is accessed.
Example;
def run_test():
myClass = MyDumbClass()
for i in range(2):
print(myClass.response)
class MyDumbClass():
def __init__(self):
self.response = None
#pytest.mark.parametrize("responses", [[200,201]])
#patch("blah.MyDumbClass")
def test_stuff(mockMyDumbClass, responses)
run_test()
assert stuff
What I am hoping for here is in the run_test method the first iteration will print 200 then the next will print 201. Is this possible, been looking through unittest and pytest documentation but can't find anything about mocking a member variable in this fashion.
Just started learning pytest and unittest with python3 so forgive me if the style isn't the best.
If you wrap myDumbClass.response in a get function - say get_response() then you can use the side_effect parameter of the mock class.
side_effect sets the return_value of the mocked method to an iterator returning a different value each time you call the mocked method.
For example you can do
def run_test():
myClass = MyDumbClass()
for i in range(2):
print(myClass.get_response())
class MyDumbClass():
def __init__(self):
self.response = None
def get_response(self):
return self.response
#pytest.mark.parametrize("responses", [([200,201])])
def test_stuff( responses):
with mock.patch('blah.MyDumbClass.get_response', side_effect=responses):
run_test()
assert False
Result
----------------------------------- Captured stdout call ------------------------------------------------------------
200
201
Edit
No need to patch via context manager e.g with mock.patch. You can patch via decorator in pretty much the same way. For example this works fine
#patch('blah.MyDumbClass.get_response',side_effect=[200,100])
def test_stuff(mockMyDumbClass):
run_test()
assert False
----------------------------------- Captured stdout call ------------------------------------------------------------
200
201