Extending superclass, calling on subclasses in Python - python

I'm a newbie in writing OO program, and I cannot find any good solution of the problem I'm facing. May anyone please help?
I'm sourcing some modules which I cannot freely modify it, and I would like to add a method on a superclass so that I can call on instances of subclasses. So in my module:
import externalLib as myLib
class Superclass(myLib.Superclass):
def myNewMethod(self):
print(self.name) # Print a member variable
def __main__():
obj = myLib.Subclass(args)
obj.myNewMethod() # Expect prints the same member variable in subclass
Result: "Subclass" has no attribute or method named "myNewMethod".
Extending all the subclass is not possible to me, as there are too
many subclasses.
I could solve the problem by defining the function
under my module instead of the Superclass, but I just think that way
is not like an OO-architecture.
Is there any better solution? Or any keywords or OO design concept can I refer to?
Thanks!

Yes, there is one keyword - "wrong". OO is model, where what you want to do should NOT be done.
If you have REALLY good reason for that, you can do it much simpler:
import externalLib as myLib
def myNewMethod(self):
print(self.name)
myLib.Superclass.myNewMethod = myNewMethod
Why didn't your code work?
When you defined Superclass inheriting from myLib.Superclass, it stayed ONLY in this module. When you defined your Superclass, name "Superclass" was bind with your new class only in global scope, but old value didn't change, co Superclass in myLib/externalLib scope stayed the same. I can see how you got impression that it may work, if you worked with classic-OO languages like Java or C++.
Little known fact - Java/C++ OO model is not really object-oriented. It does such impression, but OOP model is REALLY implemented in Smalltalk.

You are looking to monkeypatch the original class. Because methods are just attributes on a class, you can always add more:
import externalLib as myLib
def myNewMethod(self):
print(self.name)
myLib.Superclas.myNewMethod = myNewMethod

Related

Using a metaclass to substitute a class definition?

Python 3.6
I'm trying to modify the behavior of a third party library.
I don't want to directly change the source code.
Considering this code below:
class UselessObject(object):
pass
class PretendClassDef(object):
"""
A class to highlight my problem
"""
def do_something(self):
# Allot of code here
result = UselessObject()
return result
I'd like to substitute my own class for UselessObject
I'd like to know if using a metaclass in my module to intercept the creation of UselessObject is a valid idea?
EDIT
This answer posted by Ashwini Chaudhary on the same question, may be of use to others. As well as the below answer.
P.S. I also discovered that 'module' level __metaclass__ does't work in python 3. So my initial question of it 'being a valid idea' is False
FWIW, here's some code that illustrates Rawing's idea.
class UselessObject(object):
def __repr__(self):
return "I'm useless"
class PretendClassDef(object):
def do_something(self):
return UselessObject()
# -------
class CoolObject(object):
def __repr__(self):
return "I'm cool"
UselessObject = CoolObject
p = PretendClassDef()
print(p.do_something())
output
I'm cool
We can even use this technique if CoolObject needs to inherit UselessObject. If we change the definition of CoolObject to:
class CoolObject(UselessObject):
def __repr__(self):
s = super().__repr__()
return "I'm cool, but my parent says " + s
we get this output:
I'm cool, but my parent says I'm useless
This works because the name UselessObject has its old definition when the CoolObject class definition is executed.
This is not a job for metaclasses.
Rather, Python allows you to do this through a technique called "Monkeypatching", in which you, at run time, substitute one object for another in run time.
In this case, you'd be changing the thirdyparty.UselessObject for your.CoolObject before calling thirdyparty.PretendClassDef.do_something
The way to do that is a simple assignment.
So, supposing the example snippet you gave on the question is the trirdyparty module, on the library, your code would look like:
import thirdyparty
class CoolObject:
# Your class definition here
thirdyparty.UselesObject = Coolobject
Things you have to take care of: that you change the object pointed by UselessObject in the way it is used in your target module.
If for example, your PretendedClassDef and UselessObject are defined in different modules, you have to procees in one way if UselessObject is imported with from .useless import UselessObject (in this case the example above is fine), and import .useless and later uses it as useless.UselessObject - in this second case, you have to patch it on the useless module.
Also, Python's unittest.mock has a nice patch callable that can properly perform a monkeypatching and undo it if by some reason you want the modification to be valid in a limited scope, like inside a function of yours, or inside a with block. That might be the case if you don't want to change the behavior of the thirdyparty module in other sections of your program.
As for metaclasses, they only would be of any use if you would need to change the metaclass of a class you'd be replacing in this way - and them they only could have any use if you'd like to insert behavior in classes that inherit from UselessObject. In that case it would be used to create the local CoolObject and you'd still perform as above, but taking care that you'd perform the monkeypatching before Python would run the class body of any of the derived classes of UselessObject, taking extreme care when doing any imports from the thirdparty library (that would be tricky if these subclasses were defined on the same file)
This is just building on PM 2Ring's and jsbueno's answers with more contexts:
If you happen to be creating a library for others to use as a third-party library (rather than you using the third-party library), and if you need CoolObject to inherit UselessObject to avoid repetition, the following may be useful to avoid an infinite recursion error that you might get in some circumstances:
module1.py
class Parent:
def __init__(self):
print("I'm the parent.")
class Actor:
def __init__(self, parent_class=None):
if parent_class!=None: #This is in case you don't want it to actually literally be useless 100% of the time.
global Parent
Parent=parent_class
Parent()
module2.py
from module1 import *
class Child(Parent):
def __init__(self):
print("I'm the child.")
class LeadActor(Actor): #There's not necessarily a need to subclass Actor, but in the situation I'm thinking, it seems it would be a common thing.
def __init__(self):
Actor.__init__(self, parent_class=Child)
a=Actor(parent_class=Child) #prints "I'm the child." instead of "I'm the parent."
l=LeadActor() #prints "I'm the child." instead of "I'm the parent."
Just be careful that the user knows not to set a different value for parent_class with different subclasses of Actor. I mean, if you make multiple kinds of Actors, you'll only want to set parent_class once, unless you want it to change for all of them.

Instance variables in methods outside the constructor (Python) -- why and how?

My questions concern instance variables that are initialized in methods outside the class constructor. This is for Python.
I'll first state what I understand:
Classes may define a constructor, and it may also define other methods.
Instance variables are generally defined/initialized within the constructor.
But instance variables can also be defined/initialized outside the constructor, e.g. in the other methods of the same class.
An example of (2) and (3) -- see self.meow and self.roar in the Cat class below:
class Cat():
def __init__(self):
self.meow = "Meow!"
def meow_bigger(self):
self.roar = "Roar!"
My questions:
Why is it best practice to initialize the instance variable within the constructor?
What general/specific mess could arise if instance variables are regularly initialized in methods other than the constructor? (E.g. Having read Mark Lutz's Tkinter guide in his Programming Python, which I thought was excellent, I noticed that the instance variable used to hold the PhotoImage objects/references were initialized in the further methods, not in the constructor. It seemed to work without issue there, but could that practice cause issues in the long run?)
In what scenarios would it be better to initialize instance variables in the other methods, rather than in the constructor?
To my knowledge, instance variables exist not when the class object is created, but after the class object is instantiated. Proceeding upon my code above, I demonstrate this:
>> c = Cat()
>> c.meow
'Meow!'
>> c.roar
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'Cat' object has no attribute 'roar'
>>> c.meow_bigger()
>>> c.roar
'Roar!'
As it were:
I cannot access the instance variable (c.roar) at first.
However, after I have called the instance method c.meow_bigger() once, I am suddenly able to access the instance variable c.roar.
Why is the above behaviour so?
Thank you for helping out with my understanding.
Why is it best practice to initialize the instance variable within the
constructor?
Clarity.
Because it makes it easy to see at a glance all of the attributes of the class. If you initialize the variables in multiple methods, it becomes difficult to understand the complete data structure without reading every line of code.
Initializing within the __init__ also makes documentation easier. With your example, you can't write "an instance of Cat has a roar attribute". Instead, you have to add a paragraph explaining that an instance of Cat might have a "roar" attribute, but only after calling the "meow_louder" method.
Clarity is king. One of the smartest programmers I ever met once told me "show me your data structures, and I can tell you how your code works without seeing any of your code". While that's a tiny bit hyperbolic, there's definitely a ring of truth to it. One of the biggest hurdles to learning a code base is understanding the data that it manipulates.
What general/specific mess could arise if instance variables are
regularly initialized in methods other than the constructor?
The most obvious one is that an object may not have an attribute available during all parts of the program, leading to having to add a lot of extra code to handle the case where the attribute is undefined.
In what scenarios would it be better to initialize instance variables
in the other methods, rather than in the constructor?
I don't think there are any.
Note: you don't necessarily have to initialize an attribute with it's final value. In your case it's acceptable to initialize roar to None. The mere fact that it has been initialized to something shows that it's a piece of data that the class maintains. It's fine if the value changes later.
Remember that class members in "pure" Python are just a dictionary. Members aren't added to an instance's dictionary until you run the function in which they are defined. Ideally this is the constructor, because that then guarantees that your members will all exist regardless of the order that your functions are called.
I believe your example above could be translated to:
class Cat():
def __init__(self):
self.__dict__['meow'] = "Meow!"
def meow_bigger(self):
self.__dict__['roar'] = "Roar!"
>>> c = Cat() # c.__dict__ = { 'meow': "Meow!" }
>>> c.meow_bigger() # c.__dict__ = { 'meow': "Meow!", 'roar': "Roar!" }
To initialize instance variables within the constructor, is - as you already pointed out - only recommended in python.
First of all, defining all instance variables within the constructor is a good way to document a class. Everybody, seeing the code, knows what kind of internal state an instance has.
Secondly, order matters. if one defines an instance variable V in a function A and there is another function B also accessing V, it is important to call A before B. Otherwise B will fail since V was never defined. Maybe, A has to be invoked before B, but then it should be ensured by an internal state, which would be an instance variable.
There are many more examples. Generally it is just a good idea to define everything in the __init__ method, and set it to None if it can not / should not be initialized at initialization.
Of course, one could use hasattr method to derive some information of the state. But, also one could check if some instance variable V is for example None, which can imply the same then.
So in my opinion, it is never a good idea to define an instance variable anywhere else as in the constructor.
Your examples state some basic properties of python. An object in Python is basically just a dictionary.
Lets use a dictionary: One can add functions and values to that dictionary and construct some kind of OOP. Using the class statement just brings everything into a clean syntax and provides extra stuff like magic methods.
In other languages all information about instance variables and functions are present before the object was initialized. Python does that at runtime. You can also add new methods to any object outside the class definition: Adding a Method to an Existing Object Instance
3.) But instance variables can also be defined/initialized outside the constructor, e.g. in the other methods of the same class.
I'd recommend providing a default state in initialization, just so its clear what the class should expect. In statically typed languages, you'd have to do this, and it's good practice in python.
Let's convey this by replacing the variable roar with a more meaningful variable like has_roared.
In this case, your meow_bigger() method now has a reason to set has_roar. You'd initialize it to false in __init__, as the cat has not roared yet upon instantiation.
class Cat():
def __init__(self):
self.meow = "Meow!"
self.has_roared = False
def meow_bigger(self):
print self.meow + "!!!"
self.has_roared = True
Now do you see why it often makes sense to initialize attributes with default values?
All that being said, why does python not enforce that we HAVE to define our variables in the __init__ method? Well, being a dynamic language, we can now do things like this.
>>> cat1 = Cat()
>>> cat2 = Cat()
>>> cat1.name = "steve"
>>> cat2.name = "sarah"
>>> print cat1.name
... "steve"
The name attribute was not defined in the __init__ method, but we're able to add it anyway. This is a more realistic use case of setting variables that aren't defaulted in __init__.
I try to provide a case where you would do so for:
3.) But instance variables can also be defined/initialized outside the constructor, e.g. in the other methods of the same class.
I agree it would be clear and organized to include instance field in the constructor, but sometimes you are inherit other class, which is created by some other people and has many instance fields and api.
But if you inherit it only for certain apis and you want to have your own instance field for your own apis, in this case, it is easier for you to just declare extra instance field in the method instead override the other's constructor without bothering to deep into the source code. This also support Adam Hughes's answer, because in this case, you will always have your defined instance because you will guarantee to call you own api first.
For instance, suppose you inherit a package's handler class for web development, you want to include a new instance field called user for handler, you would probability just declare it directly in the method--initialize without override the constructor, I saw it is more common to do so.
class BlogHandler(webapp2.RequestHandler):
def initialize(self, *a, **kw):
webapp2.RequestHandler.initialize(self, *a, **kw)
uid = self.read_cookie('user_id') #get user_id by read cookie in the browser
self.user = User.by_id(int(uid)) #run query in data base find the user and return user
These are very open questions.
Python is a very "free" language in the sense that it tries to never restrict you from doing anything, even if it looks silly. This is why you can do completely useless things such as replacing a class with a boolean (Yes you can).
The behaviour that you mention follows that same logic: if you wish to add an attribute to an object (or to a function - yes you can, too) dynamically, anywhere, not necessarily in the constructor, well... you can.
But it is not because you can that you should. The main reason for initializing attributes in the constructor is readability, which is a prerequisite for maintenance. As Bryan Oakley explains in his answer, class fields are key to understand the code as their names and types often reveal the intent better than the methods.
That being said, there is now a way to separate attribute definition from constructor initialization: pyfields. I wrote this library to be able to define the "contract" of a class in terms of attributes, while not requiring initialization in the constructor. This allows you in particular to create "mix-in classes" where attributes and methods relying on these attributes are defined, but no constructor is provided.
See this other answer for an example and details.
i think to keep it simple and understandable, better to initialize the class variables in the class constructor, so they can be directly called without the necessity of compiling of a specific class method.
class Cat():
def __init__(self,Meow,Roar):
self.meow = Meow
self.roar = Roar
def meow_bigger(self):
return self.roar
def mix(self):
return self.meow+self.roar
c=Cat("Meow!","Roar!")
print(c.meow_bigger())
print(c.mix())
Output
Roar!
Roar!
Meow!Roar!

Class attributes in Python

Is there any difference in the following two pieces of code? If not, is one preferred over the other? Why would we be allowed to create class attributes dynamically?
Snippet 1
class Test(object):
def setClassAttribute(self):
Test.classAttribute = "Class Attribute"
Test().setClassAttribute()
Snippet 2
class Test(object):
classAttribute = "Class Attribute"
Test()
First, setting a class attribute on an instance method is a weird thing to do. And ignoring the self parameter and going right to Test is another weird thing to do, unless you specifically want all subclasses to share a single value.*
* If you did specifically want all subclasses to share a single value, I'd make it a #staticmethod with no params (and set it on Test). But in that case it isn't even really being used as a class attribute, and might work better as a module global, with a free function to set it.
So, even if you wanted to go with the first version, I'd write it like this:
class Test(object):
#classmethod
def setClassAttribute(cls):
cls.classAttribute = "Class Attribute"
Test.setClassAttribute()
However, all that being said, I think the second is far more pythonic. Here are the considerations:
In general, getters and setters are strongly discouraged in Python.
The first one leaves a gap during which the class exists but has no attribute.
Simple is better than complex.
The one thing to keep in mind is that part of the reason getters and setters are unnecessary in Python is that you can always replace an attribute with a #property if you later need it to be computed, validated, etc. With a class attribute, that's not quite as perfect a solution—but it's usually good enough.
One last thing: class attributes (and class methods, except for alternate constructor) are often a sign of a non-pythonic design at a higher level. Not always, of course, but often enough that it's worth explaining out loud why you think you need a class attribute and making sure it makes sense. (And if you've ever programmed in a language whose idioms make extensive use of class attributes—especially if it's Java—go find someone who's never used Java and try to explain it to him.)
It's more natural to do it like #2, but notice that they do different things. With #2, the class always has the attribute. With #1, it won't have the attribute until you call setClassAttribute.
You asked, "Why would we be allowed to create class attributes dynamically?" With Python, the question often is not "why would we be allowed to", but "why should we be prevented?" A class is an object like any other, it has attributes. Objects (generally) can get new attributes at any time. There's no reason to make a class be an exception to that rule.
I think #2 feels more natural. #1's implementation means that the attribute doesn't get set until an actual instance of the class gets created, which to me seems counterintuitive to what a class attribute (vs. object attribute) should be.

python metaclasses at module level

I read What is a metaclass in Python?
and I tried to replicate the upper metaclass from the example and found that this doesn't work in all cases:
def upper(cls_name, cls_parents, cls_attr):
""" Make all class attributes uppper case """
attrs = ((name, value) for name, value in cls_attr.items()
if not name.startswith('__'))
upper_atts = dict((name.upper(), value) for name, value in attrs)
return type(cls_name, cls_parents, upper_atts)
__metaclass__ = upper #Module level
class Foo:
bar = 1
f = Foo()
print(f.BAR) #works in python2.6
The above fails (with an attribute error) in python3 which I think is natural because all classes in python3 already have object as their parent and metaclass resolution goes into the object class.
The question:
How do I make a module level metaclass in python3?
The module level metaclass isn't really "module level", it has to do with how class initialization worked. The class creation would look for the variable "__metaclass__" when creating the class, and if it wasn't in the local environment it would look in the global. Hence, if you had a "module level" __metaclass__ that would be used for every class afterwards, unless they had explicit metaclasses.
In Python 3, you instead specify the metaclass with a metaclass= in the class definition. Hence there is no module level metaclasses.
So what do you do? Easy: You specify it explicitly for each class.
It's really not much extra work, and you can even do it with a nice regexp search and replace if you really have hundreds of classes and don't want to do it manually.
If you want to change all the attributes to upper case, you should probably use the __init__ method to do so, than use a metaclass.
Metaclasses are deeper magic than 99% of users should ever worry about. If you wonder whether you need them, you don't (the people who actually need them know with certainty that they need them, and don't need an explanation about why).
-- Python Guru Tim Peters
If you need something deeper, you should also evaluate using Class Decorators.
Using MetaClasses and understanding how the classes are created is so unnecessary as long as you want to do something that you can do using class decorators or initialization.
That said, if you really want to use a Metaclass tho' pass that as a keyword argument to the class.
class Foo(object, metaclass=UpperCaseMetaClass)
where UpperCaseMetaClass is a class that extends type and not a method.
class UpperCaseMetaClass(type):
def __new__():
#Do your Magic here.

Python grab class in class definition

I don't even know how to explain this, so here is the code I'm trying.
from couchdb.schema import Document, TextField
class Base(Document):
type = TextField(default=self.__name__)
#self doesn't work, how do I get a reference to Base?
class User(Base):
pass
#User.type be defined as TextField(default="Test2")
The reason I'm even trying this is I'm working on creating a base class for an orm I'm using. I want to avoid defining the table name for every model I have. Also knowing what the limits of python is will help me avoid wasting time trying impossible things.
The class object does not (yet) exist while the class body is executing, so there is no way for code in the class body to get a reference to it (just as, more generally, there is no way for any code to get a reference to any object that does not exist). Test2.__name__, however, already does what you're specifically looking for, so I don't think you need any workaround (such as metaclasses or class decorators) for your specific use case.
Edit: for the edited question, where you don't just need the name as a string, a class decorator is the simplest way to work around the problem (in Python 2.6 or later):
def maketype(cls):
cls.type = TextField(default=cls.__name__)
return cls
and put #maketype in front of each class you want to decorate that way. In Python 2.5 or earlier, you need instead to say maketype(Base) after each relevant class statement.
If you want this functionality to get inherited, then you have to define a custom metaclass that performs the same functionality in its __init__ or __new__ methods. Personally, I would recommend against defining custom metaclasses unless they're really indispensable -- instead, I'd stick with the simpler decorator approach.
You may want to check out the other question python super class relection
In your case, Test2.__base__ will return the base class Test. If it doesn't work, you may use the new style: class Test(object)

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