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Not sure why MyMock.env["key1"].search.side_effect=["a", "b"] works but MyMock.env["key1"] = ["a"] with MyMock.env["key2"] = ["b"] does not work

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.

Trying to test a function but in test it returns None?

I Have this function that I wish to test, this is how it looks like.
def myfunction():
response = requests.post(url,params=params,headers=headers,data=data)
response = response.json()
return response["Findme"].lower()
My test script:
#mock.patch('requests.post',return_value="{'Findme': 'test'}")
def test_myfunction(mocked_post):
**assert myfunction() == "test"**
When i run the test, i keep getting None for myfunction(), but when i remove the response.json() it works?
Please can anyone assist me.

As mentioned by Deep Space, your returned object does not have a json method, as it is of type str. If you want to have the same behavior as in the tested function, you have to provide an object with that method:
class MockResponse:
"""Mocks relevant part of requests.Response"""
def __init__(self, s):
self.json_string = s
def json(self):
return json.loads(self.json_string)
#mock.patch("requests.post", return_value=MockResponse('{"Findme": "test"}'))
def test_myfunction(mocked_post):
assert myfunction() == "test"
This way, an object of type MockResponse is returned from the mocked post function, that can be deserialized using json().
You could also mock the return value of json directly instead of mocking the return value of post, if you want to do this. In this case you wouldn't need an extra class:
#mock.patch("requests.post")
def test_myfunction(mocked_post):
mocked_post.return_value.json.return_value = {"Findme": "test"}
assert myfunction() == "test"

How to use Decorator on function which was created from a the return value of a closure? [duplicate]

This question already has an answer here:
Is it possible to programmatically decorate a function/method at runtime?
(1 answer)
Closed last year.
I have got the following decorators:
def msg_factory(*, prefix: str, **styles: Dict[str, Any]):
def decorator_msg_factory(func):
#functools.wraps(func)
def wrapper_msg_factory(*args, **kwargs):
msg = func(*args, **kwargs)
return typer.echo(f"{typer.style(prefix, **styles)}: {msg}")
return wrapper_msg_factory
return decorator_msg_factory
error_msg = msg_factory(prefix="ERROR", fg=typer.colors.BLACK, bg=typer.colors.RED)
warn_msg = msg_factory(prefix="WARN", fg=typer.colors.BLACK, bg=typer.colors.YELLOW)
info_msg = msg_factory(prefix="INFO", fg=typer.colors.BLACK, bg=typer.colors.GREEN)
I can use it like this:
#info_msg
def init_template_created_successfully() -> str:
msg_0 = "sdasdasd:\n\n"
msg_1 = "1. dasdasd\n"
return msg_0 + msg_1
This works fine, but I want to use a factory function for the messages like this:
def create_multiline_message_function(*messages: str) -> str:
def multiline_string():
return "\n".join(messages)
return multiline_string
init_template_created_successfully = create_multiline_message_function(
"1. sdasda",
"2. sdasda"
)
This does not work unfortunately and results in a syntax Error. It my approach possible? If yes, how ?
#info_msg
init_template_created_successfully

Python decorators are syntax-sugar, so
#mydecorator
def myfunction():
...
is equivalent to
def myfunction():
...
myfunction = mydecorator(myfunction)
as you might observe latter might be applied independetly from def. For futher discussion see PEP 318.

Loop through functions in a Class in Python

I have the following simplified code:
class States:
def __init__(self):
pass
def state1(self):
a = 2*10
return a
def state2(self):
a = 50/10
return a
class Results:
def __init__(self):
pass
def result(self):
states = States()
x = []
for i in [state1,state2]:
state_result = states.i()
x.append(state_result)
return x
I want to loop through every function in the class "States". Of course
for i in [state1,state2]
will return "name 'state1' is not defined", but I hope it gives an idea what I try to achieve.

You can use dir() to get the name of the functions of a class. You can then use getattr() to call the function.
class States:
def __init__(self):
pass
def state1(self):
a = 2*10
return a
def state2(self):
a = 50/10
return a
state = States()
for func in dir(States):
if func.startswith('__'):
continue
print(func)
print(getattr(state, func)())
Will output
state1
20
state2
5.0

You can do this tho:
def result(self):
states = States()
x = []
for i in [states.state1,states.state2]: # changed state1 to states.state1 and so on
state_result = i()
x.append(state_result)
return x

I think you can use lambda. Here, i made a simple example for you.
def foo(text):
print(text)
a = [lambda: foo("hey"), lambda: foo("boo")]
for i in a:
i()
Result:
hey
boo
In your case, you should come over with this:
for i in [lambda: state1(), lambda:state2()]:
state_result = i()
x.append(state_result)
But if you ask my opinion, it's important to inform you that calling functions through a list is not a healthy way. A software languge usually has a solution for many cases; but in this case, i think your point of view is wrong. Doing work by messing with built-in techniques and trying to find some secret tricks is is not a suggested thing.

The clean way to do this is to "register" your state methods. SOmething like this:
class States():
states = []
def register_state(cache):
def inner(fn):
cache.append(fn)
return inner
#register_state(states)
def state1(self):
a = 2*10
return a
#register_state(states)
def state2(self):
a = 50/10
return a
Then your Results class can do
class Results:
def __init__(self):
pass
def result(self):
states = States()
x = []
for i in states.states:
state_result = i(states)
x.append(state_result)
return x

You can get the members of class States via the class' dict as:
States.__dict__
Which'll give you all the attributes and function of your class as:
{'__module__': '__main__', '__init__': <function States.__init__ at 0x00000183066F0A60>, 'state1': <function States.state1 at 0x00000183066F0AF0>, 'state2': <function States.state2 at 0x000001830 ...
You can filter this into a list comprehension dict to not include dunders as:
[funcname for funcname in States.__dict__ if not (str.startswith('__') and str.endswith('__'))]
This will return you a list of member functions as:
['state1', 'state2']
Then create an object of States as:
states = States()
get the whole calculation done as:
for funcname in [funcname for funcname in States.__dict__ if not (funcname.startswith('__') and funcname.endswith('__'))]:
x.append(States.__dict__[funcname](states))
Better yet, make it a comprehension as:
[States.__dict__[funcname](states) for funcname in States.__dict__ if not (funcname.startswith('__') and funcname.endswith('__'))]
Your answer after applying this approach is: [20, 5.0]
or get the dict of functionName and returnValues as a comprehension:
{funcname: States.__dict__[funcname](states) for funcname in States.__dict__ if not (funcname.startswith('__') and funcname.endswith('__'))}
Which'll give you an output as:
{'state1': 20, 'state2': 5.0}

How to run a specific function using a code within python [duplicate]

I am trying to use functional programming to create a dictionary containing a key and a function to execute:
myDict={}
myItems=("P1","P2","P3",...."Pn")
def myMain(key):
def ExecP1():
pass
def ExecP2():
pass
def ExecP3():
pass
...
def ExecPn():
pass
Now, I have seen a code used to find the defined functions in a module, and I need to do something like this:
for myitem in myItems:
myDict[myitem] = ??? #to dynamically find the corresponding function
So my question is, How do I make a list of all the Exec functions and then assign them to the desired item using the a dictionary? so at the end I will have myDict["P1"]() #this will call ExecP1()
My real problem is that I have tons of those items and I making a library that will handle them so the final user only needs to call myMain("P1")
I think using the inspect module, but I am not so sure how to do it.
My reason to avoid:
def ExecPn():
pass
myDict["Pn"]=ExecPn
is that I have to protect code as I am using it to provide a scripting feature within my application.

Simplify, simplify, simplify:
def p1(args):
whatever
def p2(more args):
whatever
myDict = {
"P1": p1,
"P2": p2,
...
"Pn": pn
}
def myMain(name):
myDict[name]()
That's all you need.
You might consider the use of dict.get with a callable default if name refers to an invalid function—
def myMain(name):
myDict.get(name, lambda: 'Invalid')()
(Picked this neat trick up from Martijn Pieters)

Simplify, simplify, simplify + DRY:
tasks = {}
task = lambda f: tasks.setdefault(f.__name__, f)
#task
def p1():
whatever
#task
def p2():
whatever
def my_main(key):
tasks[key]()

Not proud of it, but:
def myMain(key):
def ExecP1():
pass
def ExecP2():
pass
def ExecP3():
pass
def ExecPn():
pass
locals()['Exec' + key]()
I do however recommend that you put those in a module/class whatever, this is truly horrible.
If you are willing to add a decorator for each function, you can define a decorator which adds each function to a dictionary:
def myMain(key):
tasks = {}
def task(task_fn):
tasks[task_fn.__name__] = task_fn
#task
def ExecP1():
print(1)
#task
def ExecP2():
print(2)
#task
def ExecP3():
print(3)
#task
def ExecPn():
print(4)
tasks['Exec' + key]()
Another option is to place all the functions under a class (or in a different module) and use getattr:
def myMain(key):
class Tasks:
def ExecP1():
print(1)
def ExecP2():
print(2)
def ExecP3():
print(3)
def ExecPn():
print(4)
task = getattr(Tasks, 'Exec' + key)
task()

# index dictionary by list of key names
def fn1():
print "One"
def fn2():
print "Two"
def fn3():
print "Three"
fndict = {"A": fn1, "B": fn2, "C": fn3}
keynames = ["A", "B", "C"]
fndict[keynames[1]]()
# keynames[1] = "B", so output of this code is
# Two

You can just use
myDict = {
"P1": (lambda x: function1()),
"P2": (lambda x: function2()),
...,
"Pn": (lambda x: functionn())}
myItems = ["P1", "P2", ..., "Pn"]
for item in myItems:
myDict[item]()

This will call methods from dictionary
This is python switch statement with function calling
Create few modules as per the your requirement.
If want to pass arguments then pass.
Create a dictionary, which will call these modules as per requirement.
def function_1(arg):
print("In function_1")
def function_2(arg):
print("In function_2")
def function_3(fileName):
print("In function_3")
f_title,f_course1,f_course2 = fileName.split('_')
return(f_title,f_course1,f_course2)
def createDictionary():
dict = {
1 : function_1,
2 : function_2,
3 : function_3,
}
return dict
dictionary = createDictionary()
dictionary[3](Argument)#pass any key value to call the method

#!/usr/bin/python
def thing_a(arg=None):
print 'thing_a', arg
def thing_b(arg=None):
print 'thing_b', arg
ghetto_switch_statement = {
'do_thing_a': thing_a,
'do_thing_b': thing_b
}
ghetto_switch_statement['do_thing_a']("It's lovely being an A")
ghetto_switch_statement['do_thing_b']("Being a B isn't too shabby either")
print "Available methods are: ", ghetto_switch_statement.keys()

Often classes are used to enclose methods and following is the extension for answers above with default method in case the method is not found.
class P:
def p1(self):
print('Start')
def p2(self):
print('Help')
def ps(self):
print('Settings')
def d(self):
print('Default function')
myDict = {
"start": p1,
"help": p2,
"settings": ps
}
def call_it(self):
name = 'start'
f = lambda self, x : self.myDict.get(x, lambda x : self.d())(self)
f(self, name)
p = P()
p.call_it()

class CallByName():
def method1(self):
pass
def method2(self):
pass
def method3(self):
pass
def get_method(self, method_name):
method = getattr(self, method_name)
return method()
callbyname = CallByName()
method1 = callbyname.get_method(method_name)
```

def p1( ):
print("in p1")
def p2():
print("in p2")
myDict={
"P1": p1,
"P2": p2
}
name=input("enter P1 or P2")
myDictname

You are wasting your time:
You are about to write a lot of useless code and introduce new bugs.
To execute the function, your user will need to know the P1 name anyway.
Etc., etc., etc.
Just put all your functions in the .py file:
# my_module.py
def f1():
pass
def f2():
pass
def f3():
pass
And use them like this:
import my_module
my_module.f1()
my_module.f2()
my_module.f3()
or:
from my_module import f1
from my_module import f2
from my_module import f3
f1()
f2()
f3()
This should be enough for starters.