I am trying to create a nested class to perform sum or multiplication of the arguments passed in each subclass.
The below example helps me perform action within the class, however I am unable to find any documentation which would help me with inheriting the attributes from the Parent Class to child.
Recently I came across an article which highlights "nested classes can't access any members of their outer classes at compile-time.". Is there a better way to pass the values between Classes? I tried using global variables, but would like to avoid setting many global variables while I scale this logic to extract my entire datacenter's inventory, perform some calculations and again pass to another class.
class Class1:
firstnumber=0
def __init__(self,arg):
self.firstnumber=arg
class Class2:
def __init__(self,arg):
self.secondnumber=arg
def sumit(self):
return Class1.firstnumber+Class1.Class2.secondnumber
print(Class1(5).firstnumber)
print(Class1(6).Class2(4).secondnumber)
print(Class1(4).Class2(10).sumit())
I would like to perform calculations with
Class1(variable1).Class2(variable2).Class3(variable3).sum() or
Class1(variable1).Class2(variable2).Class3(variable3).multiple() and eventually be able to do following
Datacenter('DC1').GetServer('ServerName').GetStorageCapacity('NFS').Used()
Datacenter('DC1').GetServer('ServerName').GetStorageCapacity('NFS').Free()
http://momentaryfascinations.com/programming/bound.inner.classes.for.python.html
i may be wrong but to my understanding anything you put in between the class() and the init statement is permanent and unchangable. you shouldn't need to create seperate classes for each number. create different instances of the same class.
class numbers:
def __init__(self,arg):
self.arg = arg
c1 = numbers(3)
c2 = numbers(5)
i don't know how you would add the arg variables together maybe someone else can fill in what i'm missing.
Related
I've built a class to ask a user a question, based on a type.
class Question:
def __init__(self, subject):
self.subject = subject
self.question = f"Enter the {subject} to be created. You may end this by typing 'DONE':\n"
self.still_needed = True
def ask_question(self):
ans_list = []
running = True
while running:
var = input(f"Enter {self.subject}?\n")
if var.lower() == 'done':
running = False
else:
ans_list.append(var)
return ans_list
The idea is to have a question model, to create lists of items.
This seems to work well with the following code in main.
roles = Question(subject="role").ask_question()
This creates a list from the Queue Class and uses it's method ask question to generate the list. As far as I can tell the object is then destroyed, as it's not saved to a variable.
My question, being new to Python and OOP is, does this seem like a solid and non-confusing way, or should I refractor? If so, what does the community suggest?
MY OPINION
I guess it depends on you. For one, one of the main purposes of using a class is to create an instance with it later on. Classes are objects ,or "categories" as I like to call them, that you use when there are distinctive types of instances in your project.
Given your code snippet, I can't really suggest anything, I don't know the usage of self.question and self.still_needed. However, if I were to base my opinion on just this part: roles = Question(subject="role").ask_question(), then I'd definitely go with using a function instead. As you've said,
As far as I can tell the object is then destroyed, as it's not saved
to a variable.
ALTERNATIVE SOLUTION
Use decorators → the one with # symbol
In this case, #staticmethod is the way to go!
What are staticmethods? The staticmethod decorator is a way to create a function in a class. So instead of it becoming a method, it can be treated as a function (without self parameter). This also means that a static method bounds to the class rather than its object. Consequently, static methods do not depend on objects (hence, you don't need to create an object for you to use it). Example:
class SomeMathStuff():
#staticmethod
def AddSomeNumbers(iterable):
return sum(iterable)
result = SomeMathStuff.AddSomeNumbers([1, 2, 3])
# result = 6
As you can see, I did not need to create an object, instead I just needed to call its class to use it. Word of warning, most Python programmers argue that this is the un-Pythonic way, but I wouldn't worry too much about it. Hell, even I use these methods sometimes. In my defense, this is a good and efficient way to organize your project. With this, you can apply class methods globally and you can "categorize" them in certain classes you find suitable.
Anyway, this is all I have! I apologize if I misinformed you in any way.
ADDITIONAL INFROMATION ... in case I wasn't the best teacher
https://www.programiz.com/python-programming/methods/built-in/staticmethod
Difference between staticmethod and classmethod
https://softwareengineering.stackexchange.com/questions/171296/staticmethod-vs-module-level-function
I am building a Python application which calculates sales, stock available and parts required which first asks a user to choose their department from a combobox.
What design should I use to best inform all classes within the application of the choice of department? Once the department is chosen it remains used throughout the application and for the lifecycle of the application instance.
class Sales:
def __init__(self, departmentname):
self.departmentname = departmentname
self.conn = pyodbc.connect(jsonhandler.get_json('connections.json'))
def calculate_sales(self):
with self.conn:
departmentsalesvalues = pd.read_sql_query(f"""SELECT productcode, quantity, salesprice
FROM salestable
WHERE department = ?""", self.conn,
params=(self.departmentname))
return departmentsalesvalues
This works but it seems clumsy/a poor design. I believe I am missing a concept/pattern which would be useful in all programming languages. Can someone point me in the right direction please?
The questions I have asked myself:
Should I create a Department class? But because the department is not similar to the other classes in any way inheritance seems to be out of the question.
Should I pass this information around in a Main/App class? (Which is what i am currently doing.)
Should I have an 'orchestrator' class which interfaces with the Main/App class?
I am quite new to building scalable applications but I find this sort of design question occurring more and more in my projects.
For a variable that is used everywhere and for the life of the application I see two ways that will accomplish the task.
A) Create a global variable (I know.. globals variables are bad. But for this particular scenario, when all you need is the department and you need it everywhere, a global variable is better than rewriting all of your classes to accept a constructor value)
B) Create a 'Context' class that has the department choice as a variable. The context item gets passed to all of your functions when they are called and you can add more information to the context class if need be.
For scalable applications, you would store this information in a 'configuration' file or in a special table in the database.
You would then have context and middleware.
Context is a dictionary that is passed to all of your business functions.
Middleware is a list of classes that alter the context in some way.
You would have a middleware class called "UserChoices" that has a function:
def alterContext(context={}):
context["DepartmentChoice"] = readDBvalue()
return context
Then you would get the context like so
def getContext():
context ={}
for m in middlewares:
context = m(context)
return context
And then you can use your business functions like so
def businessFunc(context):
return stuff
businessFunc(getContext())
Given the following example:
class Container:
def __init__(self, var):
self.var = var
class Test:
def __init__(self):
self.var = Container("123")
Is it possible to overload the type() method such as type(Test().var) would yield string rather than Container ?
EDIT : I am using the Container class in order to place restrictions on Test.var.
The idea is that Test is a class that contains many variables, some of witch have similar names. The Container class is there to ensure that the right types are used ( __eq__(), __str__(), __add__(), ... are overloaded in order to make the Container class as discreet as possible ) so that issues are diagnosed as fast as possible ( the code will by used by people with a very wide variety of expertise in python )
The other solution would have been to use the #property but as there are many variables, the code ends up being way bigger than it would otherwise and not as simple to maintain ( there is close to a hundred classes witch will have to implement the properties )
I would like to overload type(Test().var) in order to return type(Test().var.var) so that it would be as easy to use as possible
The short answer is "no."
From this official Python doc, it states:
Every object has an identity, a type and a value... The type() function returns an object’s type (which is an object itself). Like its identity, an object’s type is also unchangeable.
I am currently developing a piece of software where the I have class instamces that are generated from dictionaries. The way these dictionariea file are structured is as follows:
layer_dict = {
"layer_type": "Conv2D",
"name": "conv1",
"kernel_size": 3,
...
}
Then, the following code is ran
def create_layer(layer_dict):
LayerType = getattr(layers, layer_dict['layer_type']
del layer_dict['layer_type']
return LayerType(**layer_dict)
Now, I want to support the creation of new layer types (by subclassing the BaseLayer class). I've thought of a few ways to do this and thought I'd ask which way is best and why as I don't have much experience developing software (finishing an MSc in comp bio).
Method 1: Metaclasses
The first method I thought of was to have a metaclass that registers every subclass of BaseLayer in a dict and do a simple lookup of this dict instead of using getattr.
class MetaLayer(type)
layers = {}
def __init__(cls, name, bases, dct):
if name in MetaLayer.layers:
raise ValueError('Cannot have more than one layer with the same name')
MetaLayer.layers[name] = cls
Benefit: The metaclass can make sure that no two classes have the same name. The user doesn't need to think about anything but subclassing when creating new layers.
Downside: Metaclasses are difficult to understand and often frowned upon
Method 2: Traversing the __subclasses__ tree
The second method I thought of was to use the __subclassess__ function of BaseLayer to get a list of all subclasses, then create a dict with Layer.__name__ as keys and Layer as values. See example code below:
def get_subclasses(cls):
"""Returns all classes that inherit from `cls`
"""
subclasses = {
sub.__name__: sub for sub in cls.__subclasses__()
}
subsubclasses = (
get_subclasses(sub) for sub in subclasses.values()
)
subsubclasses = {
name: sub for subs in subsubclasses for name, sub in subs.items()
}
return {**subclasses, ** subsubclasses}
Benefit: Easy to explain how this works.
Downside: We might end up with two layers having the same name.
Method 3: Using a class decorator
The final method is my favourite as it doesn't hide any implementation details in a metaclass, and still manages to prevent multiple classes with the same name.
Here the layers module has a global variable named layers and a decorator named register_layer, which simply adds the decorated classes to the layers dict. See code below.
layers = {}
def register_layer(cls):
if cls.__name__ in layers:
raise ValueError('Cannot have two layers with the same name')
layers[cls.__name__] = cls
return cls
Benefit: No metaclasses and no way of having two layers with the same name.
Downside: Requires a global variable, which is often frowned upon.
So, my question is, which method is preferable? And more importantly, why?
Actually - that is the kind of things metaclases are designed for. As you can see from the options you stated above, it is the simpler and more straightforward design.
They are sometimes "frowned upon" because of two things: (1) people don't understand then and don't care for understanding; (2) people misuse then when they are actually not needed; (3) they are hard to combine - so if any of your classes is to be used with a mixn that have a different metaclass (say abc.ABC), you have also to produce a combining metaclass.
Method 4: __init_subclass__
Now, that said, from Python 3.6, there is a new feature that can cover your usecase without the need for metaclasses: the class __init_subclass__ method:
it is called as a classmethod on the base class when subclasses of it are created.
All you need is to write a proper __init_subclass__ method on your BaseLayer class and have all the benefits you'd have from the implementation in the metaclasses and none of the downsides
Like you, I like the class decorator approach as it is more readable.
You can avoid using a global variable by making the class decorator itself a class, and making layers a class variable instead. You can also avoid possible name collision by joining the target class' name with its module name:
class register_layer:
layers = {}
def __new__(cls, target):
cls.layers['.'.join((target.__module__, target.__name__))] = target
return target
I'm trying to figure out how to serialize an object with Pickle to a save file. My example is an object called World and this object has a list (named objects) of potentially hundreds of instantiated objects of different class types.
The problem is that Pickle won't let me serialize the items within the World.objects list because they aren't instantiated as attributes of World.
When I attempt to serialize with:
with open('gsave.pkl', 'wb') as output:
pickle.dump(world.objects, output, pickle.DEFAULT_PROTOCOL)
I get the following error:
_pickle.PicklingError: Can't pickle <class 'world.LargeHealthPotion'>:
attribute lookup LargeHealthPotion on world failed
So, my question is: what is an alternative way of storing the world.objects list items so that they are attributes of world rather than list items that don't get saved?
UPDATE
I think my issue isn't where the objects are stored; but rather that the class LargeHealthPotion (and many others) are dynamically created within the World class by operations such as this:
def __constructor__(self, n, cl, d, c, h, l):
# initialize super of class type
super(self.__class__, self).__init__(name=n, classtype=cl, description=d, cost=c,
hp=h, level=l)
# create the object class dynamically, utilizing __constructor__ for __init__ method
item = type(item_name,
(eval("{}.{}".format(name,row[1].value)),),
{'__init__':__constructor__})
# add new object to the global _objects object to be used throughout the world
self._objects[item_name] = item(obj_name, obj_classtype, obj_description, obj_cost,
obj_hp, obj_level)
When this finishes, I will have a new object like <world.LargeHealthPotion object at 0x103690ac8>. I do this dynamically because I don't want to explicitly have to create hundreds of different types of classes for each different type of object in my world. Instead, I create the class dynamically while iterating over the item name (with it's stats) that I want to create.
This introduces a problem though, because when pickling, it can't find the static reference to the class in order to deconstruct, or reconstruct the object...so it fails.
What else can I do? (Besides creating literal class references for each, and every, type of object I'm going to instantiate into my world.)
Pickle does not pickle classes, it instead relies on references to classes which doesn't work if the class was dynamically generated. (this answer has appropriate exert and bolding from documentation)
So pickle assumes that if your object is from the class called world.LargeHealthPotion then it check that that name actually resolves to the class that it will be able to use when unpickling, if it doesn't then you won't be able to reinitialize the object since it doesn't know how to reference the class. There are a few ways of getting around this:
Define __reduce__ to reconstruct object
I'm not sure how to demo this method to you, I'd need much more information about your setup to suggest how to implement this but I can describe it:
First you'd make a function or classmethod that could recreate one object based on the arguments (probably take class name, instance variables etc.) Then define __reduce__ on the object base class that would return that function along with the arguments needed to pass to it when unpickling.
Put the dynamic classes in the global scope
This is the quick and dirty solution. Assuming the class names do not conflict with other things defined in the world module you could theoretically insert the classes into the global scope by doing globals()[item_name] = item_type, but I do not recommend this as long term solution since it is very bad practice.
Don't use dynamic classes
This is definitely the way to go in my opinion, instead of using the type constructor, just define your own class named something like ObjectType that:
Is not a subclass of type so the instances would be pickle-able.
When an instance is it called constructs a new game-object that has a reference to the object type.
So assuming you have a class called GameObject that takes cls=<ObjectType object> you could setup the ObjectType class something like this:
class ObjectType:
def __init__(self, name, description):
self.item_name = name
self.base_item_description = description
#other qualities common to all objects of this type
def __call__(self, cost, level, hp):
#other qualities that are specific to each item
return GameObject(cls=self, cost=cost, level=level, hp=hp)
Here I am using the __call__ magic method so it uses the same notation as classes cls(params) to create instances, the cls=self would indicate to the (abstracted) GameObject constructor that the class (type) of GameObject is based on the ObjectType instance self. It doesn't have to be a keyword argument, but I'm not sure how else to make a coherent example code without knowing more about your program.