Let's say I want to set functions for each classes in module Named 'MacroMethods'. So I've set up singledispatch after seeing it in 'Fluent Python' like this:
#singledispatch
def addMethod(self, obj):
print(f'Wrong Object {str(obj)} supplied.')
return obj
...
#addMethod.register(MacroMethods.Wait)
def _(self, obj):
print('adding object wait')
obj.delay = self.waitSpin.value
obj.onFail = None
obj.onSuccess = None
return obj
Desired behavior is - when instance of class 'MacroMethods.Wait' is given as argument, singledispatch runs registered function with that class type.
Instead, it runs default function rather than registered one.
>>> Wrong Object <MacroMethods.Wait object at 0x0936D1A8> supplied.
However, type() clearly shows instance is class 'MacroMethods.Wait', and dict_keys property also contains it.
>>> dict_keys([<class 'object'>, ..., <class 'MacroMethods.Wait'>])
I suspect all custom classes I made count as 'object' type and don't run desired functions in result.
Any way to solve this problem? Entire codes are here.
Update
I've managed to mimic singledispatch's actions as following:
from functools import wraps
def state_deco(func_main):
"""
Decorator that mimics singledispatch for ease of interaction expansions.
"""
# assuming no args are needed for interaction functions.
func_main.dispatch_list = {} # collect decorated functions
#wraps(func_main)
def wrapper(target):
# dispatch target to destination interaction function.
nonlocal func_main
try:
# find and run callable for target
return func_main.dispatch_list[type(target)]()
except KeyError:
# If no matching case found, main decorated function will run instead.
func_main()
def register(target):
# A decorator that register decorated function to main decorated function.
def decorate(func_sub):
nonlocal func_main
func_main.dispatch_list[target] = func_sub
def register_wrapper(*args, **kwargs):
return func_sub(*args, **kwargs)
return register_wrapper
return decorate
wrapper.register = register
return wrapper
Used like:
#state_deco
def general():
return "A's reaction to undefined others."
#general.register(StateA)
def _():
return "A's reaction of another A"
#general.register(StateB)
def _():
return "A's reaction of B"
But still it's not singledispatch, so I find this might be inappropriate to post this as answer.
I wanted to do similar and had the same trouble. Looks like we have bumped into a python bug. Found a write-up that describes this situation.
Here is the link to the Python Bug Tracker.
Python 3.7 breaks on singledispatch_function.register(pseudo_type), which Python 3.6 accepted
Related
I am interested in patching the a classmethod called _validate in a Schema class and in a replaced fn using the value of cls and the other arguments.
For context ArrayHoldingAnyType inherits from Schema and _validate is called when it is instantiated.
When I try it with the below code, the value for cls is not a class. How do I fix the cls variable?
def test_validate_called_n_times(self):
def replacement_validate(cls, *args):
# code which will return the correct values
with patch.object(Schema, '_validate', new=replacement_validate) as mock_validate:
path_to_schemas = ArrayHoldingAnyType(['a'])
# I will check that the mock was called a certain number of times here with specific inputs
So the problem here was that the classmethod decorator was missing from replacement_validate.
This fixes it:
def test_validate_called_n_times(self):
#classmethod
def replacement_validate(cls, *args):
# code which will return the correct values
with patch.object(Schema, '_validate', new=replacement_validate) as mock_validate:
path_to_schemas = ArrayHoldingAnyType(['a'])
# I will check that the mock was called a certain number of times here with specific inputs
Using Python3, I am trying to call the members of a class which contain is_ or has_. Their returns are hard coded to True.
Here's what I've implemented, I don't know how to actually call the stored members using the black_magic method. Can anybody please help? Many thanks.
import inspect
import unittest
class Foo:
def is_bar(self):
print(bar)
return True
def is_baz(self):
print(baz)
return True
class MyTest(unittest.TestCase):
def setUp(self):
self.object=Foo()
self.object_members=inspect.getmembers(self.object)
def test_assertions_when_typical(self):
self.assertEqual(True,True)
for member in self.object_members:
member_name, member_address = member
if "is_" in member_name or "has_" in member_name:
result=black_magic(member)
self.assertEqual(result,True)
if __name__=='__main__':
unittest.main()
I'm invoking this with:
python3 -m unittest test_python_reflection_minimal_example.py
You can use the following implementation, which works locally:
def black_magic(self, objectClass, member):
return getattr(objectClass, member[0])()
and call it using result=self.black_magic(self.object, member).
Explanation: member is a tuple containing the method name and method reference. We then use this name and invoke the method on the self.object.
I want to mock a method of a class and use wraps, so that it is actually called, but I can inspect the arguments passed to it. I have seen at several places (here for example) that the usual way to do that is as follows (adapted to show my point):
from unittest import TestCase
from unittest.mock import patch
class Potato(object):
def foo(self, n):
return self.bar(n)
def bar(self, n):
return n + 2
class PotatoTest(TestCase):
spud = Potato()
#patch.object(Potato, 'foo', wraps=spud.foo)
def test_something(self, mock):
forty_two = self.spud.foo(n=40)
mock.assert_called_once_with(n=40)
self.assertEqual(forty_two, 42)
However, this instantiates the class Potato, in order to bind the mock to the instance method spud.foo.
What I need is to mock the method foo in all instances of Potato, and wrap them around the original methods. I.e, I need the following:
from unittest import TestCase
from unittest.mock import patch
class Potato(object):
def foo(self, n):
return self.bar(n)
def bar(self, n):
return n + 2
class PotatoTest(TestCase):
#patch.object(Potato, 'foo', wraps=Potato.foo)
def test_something(self, mock):
self.spud = Potato()
forty_two = self.spud.foo(n=40)
mock.assert_called_once_with(n=40)
self.assertEqual(forty_two, 42)
This of course doesn't work. I get the error:
TypeError: foo() missing 1 required positional argument: 'self'
It works however if wraps is not used, so the problem is not in the mock itself, but in the way it calls the wrapped function. For example, this works (but of course I had to "fake" the returned value, because now Potato.foo is never actually run):
from unittest import TestCase
from unittest.mock import patch
class Potato(object):
def foo(self, n):
return self.bar(n)
def bar(self, n):
return n + 2
class PotatoTest(TestCase):
#patch.object(Potato, 'foo', return_value=42)#, wraps=Potato.foo)
def test_something(self, mock):
self.spud = Potato()
forty_two = self.spud.foo(n=40)
mock.assert_called_once_with(n=40)
self.assertEqual(forty_two, 42)
This works, but it does not run the original function, which I need to run because the return value is used elsewhere (and I cannot fake it from the test).
Can it be done?
Note The actual reason behind my needs is that I'm testing a rest api with webtest. From the tests I perform some wsgi requests to some paths, and my framework instantiates some classes and uses their methods to fulfill the request. I want to capture the parameters sent to those methods to do some asserts about them in my tests.
In short, you can't do this using Mock instances alone.
patch.object creates Mock's for the specified instance (Potato), i.e. it replaces Potato.foo with a single Mock the moment it is called. Therefore, there is no way to pass instances to the Mock as the mock is created before any instances are. To my knowledge getting instance information to the Mock at runtime is also very difficult.
To illustrate:
from unittest.mock import MagicMock
class MyMock(MagicMock):
def __init__(self, *a, **kw):
super(MyMock, self).__init__(*a, **kw)
print('Created Mock instance a={}, kw={}'.format(a,kw))
with patch.object(Potato, 'foo', new_callable=MyMock, wrap=Potato.foo):
print('no instances created')
spud = Potato()
print('instance created')
The output is:
Created Mock instance a=(), kw={'name': 'foo', 'wrap': <function Potato.foo at 0x7f5d9bfddea0>}
no instances created
instance created
I would suggest monkey-patching your class in order to add the Mock to the correct location.
from unittest.mock import MagicMock
class PotatoTest(TestCase):
def test_something(self):
old_foo = Potato.foo
try:
mock = MagicMock(wraps=Potato.foo, return_value=42)
Potato.foo = lambda *a,**kw: mock(*a, **kw)
self.spud = Potato()
forty_two = self.spud.foo(n=40)
mock.assert_called_once_with(self.spud, n=40) # Now needs self instance
self.assertEqual(forty_two, 42)
finally:
Potato.foo = old_foo
Note that you using called_with is problematic as you are calling your functions with an instance.
Do you control creation of Potato instances, or at least have access to these instances after creating them? You should, else you'd not be able to check particular arg lists.
If so, you can wrap methods of individual instances using
spud = dig_out_a_potato()
with mock.patch.object(spud, "foo", wraps=spud.foo) as mock_spud:
# do your thing.
mock_spud.assert_called...
Your question looks identical to python mock - patching a method without obstructing implementation to me. https://stackoverflow.com/a/72446739/9230828 implements what you want (except that it uses a with statement instead of a decorator). wrap_object.py:
# Copyright (C) 2022, Benjamin Drung <bdrung#posteo.de>
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
import contextlib
import typing
import unittest.mock
#contextlib.contextmanager
def wrap_object(
target: object, attribute: str
) -> typing.Generator[unittest.mock.MagicMock, None, None]:
"""Wrap the named member on an object with a mock object.
wrap_object() can be used as a context manager. Inside the
body of the with statement, the attribute of the target is
wrapped with a :class:`unittest.mock.MagicMock` object. When
the with statement exits the patch is undone.
The instance argument 'self' of the wrapped attribute is
intentionally not logged in the MagicMock call. Therefore
wrap_object() can be used to check all calls to the object,
but not differentiate between different instances.
"""
mock = unittest.mock.MagicMock()
real_attribute = getattr(target, attribute)
def mocked_attribute(self, *args, **kwargs):
mock.__call__(*args, **kwargs)
return real_attribute(self, *args, **kwargs)
with unittest.mock.patch.object(target, attribute, mocked_attribute):
yield mock
Then you can write following unit test:
from unittest import TestCase
from wrap_object import wrap_object
class Potato:
def foo(self, n):
return self.bar(n)
def bar(self, n):
return n + 2
class PotatoTest(TestCase):
def test_something(self):
with wrap_object(Potato, 'foo') as mock:
self.spud = Potato()
forty_two = self.spud.foo(n=40)
mock.assert_called_once_with(n=40)
self.assertEqual(forty_two, 42)
I'm trying to wrap all methods of an existing Class (not of my creation) into a try/except suite. It could be any Class, but I'll use the pandas.DataFrame class here as a practical example.
So if the invoked method succeeds, we simply move on. But if it should generate an exception, it is appended to a list for later inspection/discovery (although the below example just issues a print statement for simplicity).
(Note that the kinds of data-related exceptions that can occur when a method on the instance is invoked, isn't yet known; and that's the reason for this exercise: discovery).
This post was quite helpful (particularly #martineau Python-3 answer), but I'm having trouble adapting it. Below, I expected the second call to the (wrapped) info() method to emit print output but, sadly, it doesn't.
#!/usr/bin/env python3
import functools, types, pandas
def method_wrapper(method):
#functools.wraps(method)
def wrapper(*args, **kwargs): #Note: args[0] points to 'self'.
try:
print('Calling: {}.{}()... '.format(args[0].__class__.__name__,
method.__name__))
return method(*args, **kwargs)
except Exception:
print('Exception: %r' % sys.exc_info()) # Something trivial.
#<Actual code would append that exception info to a list>.
return wrapper
class MetaClass(type):
def __new__(mcs, class_name, base_classes, classDict):
newClassDict = {}
for attributeName, attribute in classDict.items():
if type(attribute) == types.FunctionType: # Replace it with a
attribute = method_wrapper(attribute) # decorated version.
newClassDict[attributeName] = attribute
return type.__new__(mcs, class_name, base_classes, newClassDict)
class WrappedDataFrame2(MetaClass('WrappedDataFrame',
(pandas.DataFrame, object,), {}),
metaclass=type):
pass
print('Unwrapped pandas.DataFrame().info():')
pandas.DataFrame().info()
print('\n\nWrapped pandas.DataFrame().info():')
WrappedDataFrame2().info()
print()
This outputs:
Unwrapped pandas.DataFrame().info():
<class 'pandas.core.frame.DataFrame'>
Index: 0 entries
Empty DataFrame
Wrapped pandas.DataFrame().info(): <-- Missing print statement after this line.
<class '__main__.WrappedDataFrame2'>
Index: 0 entries
Empty WrappedDataFrame2
In summary,...
>>> unwrapped_object.someMethod(...)
# Should be mirrored by ...
>>> wrapping_object.someMethod(...)
# Including signature, docstring, etc. (i.e. all attributes); except that it
# executes inside a try/except suite (so I can catch exceptions generically).
long time no see. ;-) In fact it's been such a long time you may no longer care, but in case you (or others) do...
Here's something I think will do what you want. I've never answered your question before now because I don't have pandas installed on my system. However, today I decided to see if there was a workaround for not having it and created a trivial dummy module to mock it (only as far as I needed). Here's the only thing in it:
mockpandas.py:
""" Fake pandas module. """
class DataFrame:
def info(self):
print('pandas.DataFrame.info() called')
raise RuntimeError('Exception raised')
Below is code that seems to do what you need by implementing #Blckknght's suggestion of iterating through the MRO—but ignores the limitations noted in his answer that could arise from doing it that way). It ain't pretty, but as I said, it seems to work with at least the mocked pandas library I created.
import functools
import mockpandas as pandas # mock the library
import sys
import traceback
import types
def method_wrapper(method):
#functools.wraps(method)
def wrapper(*args, **kwargs): # Note: args[0] points to 'self'.
try:
print('Calling: {}.{}()... '.format(args[0].__class__.__name__,
method.__name__))
return method(*args, **kwargs)
except Exception:
print('An exception occurred in the wrapped method {}.{}()'.format(
args[0].__class__.__name__, method.__name__))
traceback.print_exc(file=sys.stdout)
# (Actual code would append that exception info to a list)
return wrapper
class MetaClass(type):
def __new__(meta, class_name, base_classes, classDict):
""" See if any of the base classes were created by with_metaclass() function. """
marker = None
for base in base_classes:
if hasattr(base, '_marker'):
marker = getattr(base, '_marker') # remember class name of temp base class
break # quit looking
if class_name == marker: # temporary base class being created by with_metaclass()?
return type.__new__(meta, class_name, base_classes, classDict)
# Temporarily create an unmodified version of class so it's MRO can be used below.
TempClass = type.__new__(meta, 'TempClass', base_classes, classDict)
newClassDict = {}
for cls in TempClass.mro():
for attributeName, attribute in cls.__dict__.items():
if isinstance(attribute, types.FunctionType):
# Convert it to a decorated version.
attribute = method_wrapper(attribute)
newClassDict[attributeName] = attribute
return type.__new__(meta, class_name, base_classes, newClassDict)
def with_metaclass(meta, classname, bases):
""" Create a class with the supplied bases and metaclass, that has been tagged with a
special '_marker' attribute.
"""
return type.__new__(meta, classname, bases, {'_marker': classname})
class WrappedDataFrame2(
with_metaclass(MetaClass, 'WrappedDataFrame', (pandas.DataFrame, object))):
pass
print('Unwrapped pandas.DataFrame().info():')
try:
pandas.DataFrame().info()
except RuntimeError:
print(' RuntimeError exception was raised as expected')
print('\n\nWrapped pandas.DataFrame().info():')
WrappedDataFrame2().info()
Output:
Unwrapped pandas.DataFrame().info():
pandas.DataFrame.info() called
RuntimeError exception was raised as expected
Wrapped pandas.DataFrame().info():
Calling: WrappedDataFrame2.info()...
pandas.DataFrame.info() called
An exception occurred in the wrapped method WrappedDataFrame2.info()
Traceback (most recent call last):
File "test.py", line 16, in wrapper
return method(*args, **kwargs)
File "mockpandas.py", line 9, in info
raise RuntimeError('Exception raised')
RuntimeError: Exception raised
As the above illustrates, the method_wrapper() decoratored version is being used by methods of the wrapped class.
Your metaclass only applies your decorator to the methods defined in classes that are instances of it. It doesn't decorate inherited methods, since they're not in the classDict.
I'm not sure there's a good way to make it work. You could try iterating through the MRO and wrapping all the inherited methods as well as your own, but I suspect you'd get into trouble if there were multiple levels of inheritance after you start using MetaClass (as each level will decorate the already decorated methods of the previous class).
Let's say I have a code like this:
class NewTestCase(unittest.TestCase, CommonMethods):
def setUp(self):
self.shortDescription()
def test_01_sample test(self):
"""Testing something"""
self.create_account(self.arg['account'])
assert ...
...
class CommonMethods():
def create_account(self, account):
"""Creating account"""
...
if __name__ == '__main__':
unittest.main(verbosity=2, warnings='ignore')
I want to show the docstrings of all methods defined / created by me ('Testing something' and 'Creating account'), but the execution shows 'Testing something' only. Any tip?
Maybe there is an option for that in the unittest module, but I doubt it; otherwise, how would that module distinguish between your methods and functions and all sorts of library functions?
What you could do is to use another function to modify the existing functions to print their Docstring and/or other useful information whenever they are called. You could make this a decorator, or just call the function manually before running the tests.
This one should 'verbosify' all the methods of a given class (only slightly tested!), and you could make similar ones for individual functions or entire modules.
def verbosify(clazz):
for name in dir(clazz):
attr = getattr(clazz, name)
if not name.startswith("__") and callable(attr):
def attr_verbose(*args, **kwargs):
print("Calling", name, args, kwargs)
print(attr.__doc__)
return attr(*args, **kwargs)
setattr(clazz, name, attr_verbose)
Just call verbosify(CommonMethods) in your main block.