I started a python project and attempted to have it OOP.
I used a script to call function from classes, in the following way:
class Object():
def function(input):
print(input)
The command Object.Object.function("example") used to work fine.
I had to reinstall pycharm, and now when running the same code I get the error of not sending enough input.
This can be solved by changing the call to Object.Object().function("example"),
and the function definition to def function(a,input):
Where the variable a is never used. This however causes new problems when using libraries.
How can I use the previous configuration?
Object.Object.function("example") and Object.Object().function("example") are different beasts entirely. The first run invokes the method function on the class Object.Object, while in the latter, Object.Object() creates an instance of type Object.Object and invokes function on that instance (which fails as you must provide the instance itself as the first parameter to the method). It sounds like you are trying to make something like a staticmethod,
class A:
#staticmethod
def f(input):
print(input)
for which both A.f and A().f will act as print.
Related
Introduction:
We know that, in python, a function is a class. To some extent, We can look at it as a data type which can be called and return a value. So it is a callable. We also know that Python classes are callables. When they are called, we are actually making objects as their instances.
My implementation: In a current task, I have defined the following class with two methods:
class SomeClass():
def some_method_1():
some_code
def some_method_2():
some_code
self.some_method_1()
some_code
To describe the code above, some_method_2 is using some_method_1 inside it.
Now I am seeking to test some_method_2. In this case, I need to replace some_method_1 with a mock object and specify the mock object to return what I define:
from unittest.mock import Mock
import unittest
class TestSomeClass(unittest.TestCase):
some_object=Some_Class()
some_object.some_method_1 = Mock(return_value=foo)
self.assertEqual(an_expected_value, some_object.some_method_2())
This works totally fine and the script runs without error and the test result is also ok.
A fast Intro about Mypy: Mypy is a python type checking tool which can run and check if the script is written correctly based on variable types. It does this process by some criteria such as type annotations, variable assignments and libraries stub files. This process is done without interpreting and running the code.
What is the Problem?
When I try to check my code with mypy, it gives error for this line:
some_object.some_method_1 = Mock(return_value=foo)
The error indicates that I am not allowed to assign an object to a callable in python. Sometimes mypy does not report real errors and I doubt if this is the case. Especially because I can run my code with no problem.
Now, my question is, have I done my job wrong or just the mypy report is wrong? If I have done wrong, how can I implement the same scenario in a correct manner?
del methods in python class has two different output in different text editors
class test:
def __init__(self) :
print("init")
def __del__(self):
print("del")
a=test()
outpuu in vs code :
init
del
out put in jupyter :
init
When you run the Python script in the terminal (which is similar as in vscode), after the last line has been executed, the script terminates. When a script terminates, the desctructor of the class test() is called. A desctructor is defined in __del__() method in a class.
In Jupyter notebook, the script does not terminate and is up for your next code chunk (apols the terminology might be slightly off here). The __del__() method is not called.
It is explicitely stated in Python Language Reference. Data model / Special method names / Basic customization says (emphasize mine):
object.del(self)
Called when the instance is about to be destroyed...
It is not guaranteed that del() methods are called for objects that still exist when the interpreter exits.
That means that different environments may have different usage regarding the calling of __del__
Using Django 1.10 and python 3.5.1.
I'm trying to mock 'call_command' function to throw an exception. The problem is that seems like the moment it gets the 'side_effect' function - it keeps to it also for other tests. What am I doing wrong or how can I 'revert' the side_effect from that function?
In this example, after running one of the tests, all other tests that run afterwards will throw the same exception even if it's not supposed to throw exception in that test.
def test_run_migrations_raise_exception(self):
with mock.patch('django.core.management.call_command', return_value=None, side_effect=Exception('e message')):
self.check_migrations_called(MigrationTracker.objects.all(), data_migrations_settings_in_db)
call_command('run_data_migrations')
self.check_migrations_called(MigrationTracker.objects.all(), data_migrations_settings_in_db)
def test_run_migrations_raise_flow_exception(self):
with mock.patch('django.core.management.call_command', return_value=None, side_effect=FlowException(500, 'fe message', {'a': 1})):
self.check_migrations_called(MigrationTracker.objects.all(), data_migrations_settings_in_db)
call_command('run_data_migrations')
self.check_migrations_called(MigrationTracker.objects.all(), data_migrations_settings_in_db)
You should not patch a function that is in your module-local (i.e. Python's "global" - which is actually "module") namespace.
When in Python you do
from module.that import this
this becomes a variable on the module that contains the import statement. Any changes to "module.that.this" will affect the object pointed in the other module, but using only this will still reefer to the original object.
Perhaps your code is not exactly as you show us, or maybe "mock.pacth" can find out that the module-local call_command is pointing to django.core.management.call_command in the other module when it makes the patch - but not when reversing the patch. The fact is your module-local name call_command is being changed.
You can fix that by simply changing your code to not bind a module variable directly to the function you want to change:
from django.core import management
def test_run_migrations_raise_exception(self):
with mock.patch('django.core.management.call_command', return_value=None, side_effect=Exception('e message')):
self.check_migrations_called(MigrationTracker.objects.all(), data_migrations_settings_in_db)
management.call_command('run_data_migrations')
self.check_migrations_called(MigrationTracker.objects.all(), data_migrations_settings_in_db)
I hope you can understand that and solve this problem. Now, that said, this use of mock makes no sense at all: the idea of using mock is that some callable used indirectly by code you call within the code-block that applies the patch does not have the original effect - so the intermetiate code can run and be tested. You are calling directly the mock object - so it will have none of the original code - calling call_command('run_data_migrations') runs no code on your code base at all, and thus, there is nothing there to test. It just calls the mocked instance, and it will not change the status of anything that could be detected with check_migrations_called.
I have an architecture, where I use wrapper for calling functions from package module. Inside the module there is a function that calls another three. I need to override one of them in run-time. Exactly I need to change parameters that are forwarded to another set of functions being called.
Here is a case sample:
a.py
import b_wrapper as wrapper
def foo():
if wrapper.bar(parameter):
"""some more code goes here"""
b_wrapper.py
import some.package.module as module
def bar(parameter):
return module.baz(veryImportantParameter, parameter)
file.py
def functionThree(par): # needs to be overwritten
"""more functions called forwarding par as a parameter"""
def baz(veryImportantParameter, parameter)
functionOne(veryImportantParameter, otherParameters)
functionTwo(veryImportantParameter, someMoreParameters)
functionThree(veryImportantParameter, parameterToChange, evenMoreParameters)
What I tried to do is overriding in wrapper file, didn't work out, as other functions are interfering with it. As reference used this post.
I'm not quite sure that this is doable, because of unique functions that are called inside this module, also looking for alternatives that won't require overriding portion of module.
Edit: mixing up arguments and parameters is intentional for demonstration purpose only.
I need to create a function to rotate a given matrix (list of lists) clockwise, and I need to use it in my Table class. Where should I put this utility function (called rotateMatrixClockwise) so I can call it easily from within a function in my Table class?
Make it a static function...
add the #staticmethod decorator
don't include 'self' as the first argument
Your definition would be:
#staticmethod
def rotateMatrixClockwise():
# enter code here...
Which will make it callable everywhere you imported 'table' by calling:
table.rotateMatrixClockwise()
The decorator is only necessary to tell python that no implicit first argument is expected. If you wanted to make method definitions act like C#/Java where self is always implicit you could also use the '#classmethod' decorator.
Here's the documentation for this coming directly from the python manual.
Note: I'd recommend using Utility classes only where their code can't be coupled directly to a module because they generally violate the 'Single Responsibility Principle' of OOP. It's almost always best to tie the functionality of a class as a method/member to the class.
If you don't want to make it a member of the Table class you could put it into a utilities module.