I am new to python.I was doing following code and I met an undesired outcome. Please look onto my code and let me know what am I doing wrong:
class TestClass(object):
#classmethod
def __init__(self, val):
self.val = val
#classmethod
def value(self):
return self.val
def Test():
a = TestClass(9)
b = TestClass(8)
c = TestClass(7)
print(a.value(), b.value(), c.value())
expecting output as
9 8 7
but getting output as
7 7 7
what is wrong with my code.
Setting __init__ as a classmethod means you're actually passing the class to __init__ and self.val is actually set as a class variable, not an instance variable.
The final "initialization" you perform will override all the other values you've set.
Removing the #classmethods fixes the issue.
You have attached #classmethod to the __init__ function. As a result, if you call the __init__ (something you do at construction), self will not reference to the object you are about to construct, but to the class, so TestClass. Therefore there is only one value: attached to TestClass.
So TestClass(3) will be equivalent to something like TestClass.__init__(TestClass,3)...
You can solve the issue by removing the #classmethod decorator:
class TestClass(object):
def __init__(self, val): # no #classmethod
self.val = val
def value(self): # no #classmethod
return self.val
def Test():
a = TestClass(9)
b = TestClass(8)
c = TestClass(7)
print(a.value(), b.value(), c.value())
It is actually rather weird to use a #classmethod on an __init__ method. If you want to add attributes to the class, you can use type(..). So:
#classmethod
def __init__(cls, val):
cls.val = val
Is equivalent to:
def __init__(self, val):
type(self).val = val
Related
Imagine having this class:
class Foo:
def __init__(self):
self.nr = 0
Imagine further Foo being widely used. Several scripts and users use the variable Foo.nr to read and write its value.
Now suppose the developer wants to change the name of .nr to .val.
class Foo:
def __init__(self):
self.val = 0
In order to not force the users to update their code, is it somehow possible to make them access .val by writing .nr? Like this:
f1 = Foo()
print(f1.nr)
I came up with properties and getter and setter methods but I don't see how they might help.
class Foo:
def __init__(self):
self.val = 0
#property
def nr(self):
return self.val
#nr.setter
def nr(self, value):
self.val = value
f1 = Foo()
print(f1.nr)
would give 0 as expected.
I am trying to find a good way for returning a (new) class object in class method that can be extended as well.
I have a class (classA) which has among other methods, a method that returns a new classA object after some processing
class classA:
def __init__(): ...
def methodX(self, **kwargs):
process data
return classA(new params)
Now, I am extending this class to another classB. I need methodX to do the same, but return classB this time, instead of classA
class classB(classA):
def __init__(self, params):
super().__init__(params)
self.newParams = XYZ
def methodX(self, **kwargs):
???
This may be something trivial but I simply cannot figure it out. In the end I dont want to rewrite the methodX each time the class gets extended.
Thank you for your time.
Use the __class__ attribute like this:
class A:
def __init__(self, **kwargs):
self.kwargs = kwargs
def methodX(self, **kwargs):
#do stuff with kwargs
return self.__class__(**kwargs)
def __repr__(self):
return f'{self.__class__}({self.kwargs})'
class B(A):
pass
a = A(foo='bar')
ax = a.methodX(gee='whiz')
b = B(yee='haw')
bx = b.methodX(cool='beans')
print(a)
print(ax)
print(b)
print(bx)
class classA:
def __init__(self, x):
self.x = x
def createNew(self, y):
t = type(self)
return t(y)
class classB(classA):
def __init__(self, params):
super().__init__(params)
a = classA(1)
newA = a.createNew(2)
b = classB(1)
newB = b.createNew(2)
print(type(newB))
# <class '__main__.classB'>
I want to propose what I think is the cleanest approach, albeit similar to existing answers. The problem feels like a good fit for a class method:
class A:
#classmethod
def method_x(cls, **kwargs):
return cls(<init params>)
Using the #classmethod decorator ensures that the first input (traditionally named cls) will refer to the Class to which the method belongs, rather than the instance.
(usually we call the first method input self and this refers to the instance to which the method belongs)
Because cls refers to A, rather than an instance of A, we can call cls() as we would call A().
However, in a class that inherits from A, cls will instead refer to the child class, as required:
class A:
def __init__(self, x):
self.x = x
#classmethod
def make_new(cls, **kwargs):
y = kwargs["y"]
return cls(y) # returns A(y) here
class B(A):
def __init__(self, x):
super().__init__(x)
self.z = 3 * x
inst = B(1).make_new(y=7)
print(inst.x, inst.z)
And now you can expect that print statement to produce 7 21.
That inst.z exists should confirm for you that the make_new call (which was only defined on A and inherited unaltered by B) has indeed made an instance of B.
However, there's something I must point out. Inheriting the unaltered make_new method only works because the __init__ method on B has the same call signature as the method on A. If this weren't the case then the call to cls might have had to be altered.
This can be circumvented by allowing **kwargs on the __init__ method and passing generic **kwargs into cls() in the parent class:
class A:
def __init__(self, **kwargs):
self.x = kwargs["x"]
#classmethod
def make_new(cls, **kwargs):
return cls(**kwargs)
class B(A):
def __init__(self, x, w):
super().__init__(x=x)
self.w = w
inst = B(1,2).make_new(x="spam", w="spam")
print(inst.x, inst.w)
Here we were able to give B a different (more restrictive!) signature.
This illustrates a general principle, which is that parent classes will typically be more abstract/less specific than their children.
It follows that, if you want two classes that substantially share behaviour but which do quite specific different things, it will be better to create three classes: one rather abstract one that defines the behaviour-in-common, and two children that give you the specific behaviours you want.
I want to make a method to be called from class or instance.
For example :
class SomeClass:
a = 10
def __init__(self, val):
self.a = val
def print_a(self):
print(self.a)
SomeClass(20).print_a() # 20
SomeClass.print_a() # Error!
Here I want to make print_a can be called by class either.
If I use classmethod, the result is wrong.
class SomeClass:
a = 10
def __init__(self, val):
self.a = val
#classmethod
def print_a(cls):
print(cls.a)
SomeClass(20).print_a() # 10 (wrong!)
SomeClass.print_a() # 10
I hope the result is like this:
SomeClass(20).print_a() # 20
SomeClass.print_a() # 10
How can I achieve this?
classmethod is simply a descriptor object, you can read about how it could be implemented using pure python in the Descriptor HOWTO. Using that implementation as an inspiration:
from types import MethodType
class HybridMethod:
def __init__(self, f):
self.f = f
def __get__(self, obj, cls=None):
if obj is None:
return MethodType(self.f, cls)
else:
return MethodType(self.f, obj)
class SomeClass:
a = 10
def __init__(self, val):
self.a = val
#HybridMethod
def print_a(self):
print(self.a)
SomeClass(20).print_a()
SomeClass.print_a()
I am trying to make a python decorator that adds attributes to methods of a class so that I can access and modify those attributes from within the method itself. The decorator code is
from types import MethodType
class attribute(object):
def __init__(self, **attributes):
self.attributes = attributes
def __call__(self, function):
class override(object):
def __init__(self, function, attributes):
self.__function = function
for att in attributes:
setattr(self, att, attributes[att])
def __call__(self, *args, **kwargs):
return self.__function(*args, **kwargs)
def __get__(self, instance, owner):
return MethodType(self, instance, owner)
retval = override(function, self.attributes)
return retval
I tried this decorator on the toy example that follows.
class bar(object):
#attribute(a=2)
def foo(self):
print self.foo.a
self.foo.a = 1
Though I am able to access the value of attribute 'a' from within foo(), I can't set it to another value. Indeed, when I call bar().foo(), I get the following AttributeError.
AttributeError: 'instancemethod' object has no attribute 'a'
Why is this? More importantly how can I achieve my goal?
Edit
Just to be more specific, I am trying to find a simple way to implement static variable that are located within class methods. Continuing from the example above, I would like instantiate b = bar(), call both foo() and doo() methods and then access b.foo.a and b.doo.a later on.
class bar(object):
#attribute(a=2)
def foo(self):
self.foo.a = 1
#attribute(a=4)
def doo(self):
self.foo.a = 3
The best way to do this is to not do it at all.
First of all, there is no need for an attribute decorator; you can just assign it yourself:
class bar(object):
def foo(self):
print self.foo.a
self.foo.a = 1
foo.a = 2
However, this still encounters the same errors. You need to do:
self.foo.__dict__['a'] = 1
You can instead use a metaclass...but that gets messy quickly.
On the other hand, there are cleaner alternatives.
You can use defaults:
def foo(self, a):
print a[0]
a[0] = 2
foo.func_defaults = foo.func_defaults[:-1] + ([2],)
Of course, my preferred way is to avoid this altogether and use a callable class ("functor" in C++ words):
class bar(object):
def __init__(self):
self.foo = self.foo_method(self)
class foo_method(object):
def __init__(self, bar):
self.bar = bar
self.a = 2
def __call__(self):
print self.a
self.a = 1
Or just use classic class attributes:
class bar(object):
def __init__(self):
self.a = 1
def foo(self):
print self.a
self.a = 2
If it's that you want to hide a from derived classes, use whatever private attributes are called in Python terminology:
class bar(object):
def __init__(self):
self.__a = 1 # this will be implicitly mangled as __bar__a or similar
def foo(self):
print self.__a
self.__a = 2
EDIT: You want static attributes?
class bar(object):
a = 1
def foo(self):
print self.a
self.a = 2
EDIT 2: If you want static attributes visible to only the current function, you can use PyExt's modify_function:
import pyext
def wrap_mod(*args, **kw):
def inner(f):
return pyext.modify_function(f, *args, **kw)
return inner
class bar(object):
#wrap_mod(globals={'a': [1]})
def foo(self):
print a[0]
a[0] = 2
It's slightly ugly and hackish. But it works.
My recommendation would be just to use double underscores:
class bar(object):
__a = 1
def foo(self):
print self.__a
self.__a = 2
Although this is visible to the other functions, it's invisible to anything else (actually, it's there, but it's mangled).
FINAL EDIT: Use this:
import pyext
def wrap_mod(*args, **kw):
def inner(f):
return pyext.modify_function(f, *args, **kw)
return inner
class bar(object):
#wrap_mod(globals={'a': [1]})
def foo(self):
print a[0]
a[0] = 2
foo.a = foo.func_globals['a']
b = bar()
b.foo() # prints 1
b.foo() # prints 2
# external access
b.foo.a[0] = 77
b.foo() # prints 77
While You can accomplish Your goal by replacing self.foo.a = 1 with self.foo.__dict__['a'] = 1 it is generally not recommended.
If you are using Python2 - (and not Python3) - whenever you retrieve a method from an instance, a new instance method object is created which is a wrapper to the original function defined in the class body.
The instance method is a rather transparent proxy to the function - you can retrieve the function's attributes through it, but not set them - that is why setting an item in self.foo.__dict__ works.
Alternatively you can reach the function object itself using: self.foo.im_func - the im_func attribute of instance methods point the underlying function.
Based on other contributors's answers, I came up with the following workaround. First, wrap a dictionnary in a class resolving non-existant attributes to the wrapped dictionnary such as the following code.
class DictWrapper(object):
def __init__(self, d):
self.d = d
def __getattr__(self, key):
return self.d[key]
Credits to Lucas Jones for this code.
Then implement a addstatic decorator with a statics attribute that will store the static attributes.
class addstatic(object):
def __init__(self, **statics):
self.statics = statics
def __call__(self, function):
class override(object):
def __init__(self, function, statics):
self.__function = function
self.statics = DictWrapper(statics)
def __call__(self, *args, **kwargs):
return self.__function(*args, **kwargs)
def __get__(self, instance, objtype):
from types import MethodType
return MethodType(self, instance)
retval = override(function, self.statics)
return retval
The following code is an example of how the addstatic decorator can be used on methods.
class bar(object):
#attribute(a=2, b=3)
def foo(self):
self.foo.statics.a = 1
self.foo.statics.b = 2
Then, playing with an instance of the bar class yields :
>>> b = bar()
>>> b.foo.statics.a
2
>>> b.foo.statics.b
3
>>> b.foo()
>>> b.foo.statics.a
3
>>> b.foo.statics.b
5
The reason for using this statics dictionnary follows jsbueno's answer which suggest that what I want would require overloading the dot operator of and instance method wrapping the foo function, which I am not sure is possible. Of course, the method's attribute could be set in self.foo.__dict__, but since it not recommended (as suggested by brainovergrow), I came up with this workaround. I am not certain this would be recommended either and I guess it is up for comments.
I want to define a class containing read and write methods, which can be called as follows:
instance.read
instance.write
instance.device.read
instance.device.write
To not use interlaced classes, my idea was to overwrite the __getattr__ and __setattr__ methods and to check, if the given name is device to redirect the return to self. But I encountered a problem giving infinite recursions. The example code is as follows:
class MyTest(object):
def __init__(self, x):
self.x = x
def __setattr__(self, name, value):
if name=="device":
print "device test"
else:
setattr(self, name, value)
test = MyTest(1)
As in __init__ the code tried to create a new attribute x, it calls __setattr__, which again calls __setattr__ and so on. How do I need to change this code, that, in this case, a new attribute x of self is created, holding the value 1?
Or is there any better way to handle calls like instance.device.read to be 'mapped' to instance.read?
As there are always questions about the why: I need to create abstractions of xmlrpc calls, for which very easy methods like myxmlrpc.instance,device.read and similar can be created. I need to 'mock' this up to mimic such multi-dot-method calls.
You must call the parent class __setattr__ method:
class MyTest(object):
def __init__(self, x):
self.x = x
def __setattr__(self, name, value):
if name=="device":
print "device test"
else:
super(MyTest, self).__setattr__(name, value)
# in python3+ you can omit the arguments to super:
#super().__setattr__(name, value)
Regarding the best-practice, since you plan to use this via xml-rpc I think this is probably better done inside the _dispatch method.
A quick and dirty way is to simply do:
class My(object):
def __init__(self):
self.device = self
Or you can modify self.__dict__ from inside __setattr__():
class SomeClass(object):
def __setattr__(self, name, value):
print(name, value)
self.__dict__[name] = value
def __init__(self, attr1, attr2):
self.attr1 = attr1
self.attr2 = attr2
sc = SomeClass(attr1=1, attr2=2)
sc.attr1 = 3
You can also use object.
class TestClass:
def __init__(self):
self.data = 'data'
def __setattr__(self, name, value):
print("Attempt to edit the attribute %s" %(name))
object.__setattr__(self, name, value)
or you can just use #property:
class MyTest(object):
def __init__(self, x):
self.x = x
#property
def device(self):
return self
If you don't want to specify which attributes can or cannot be set, you can split the class to delay the get/set hooks until after initialization:
class MyTest(object):
def __init__(self, x):
self.x = x
self.__class__ = _MyTestWithHooks
class _MyTestWithHooks(MyTest):
def __setattr__(self, name, value):
...
def __getattr__(self, name):
...
if __name__ == '__main__':
a = MyTest(12)
...
As noted in the code you'll want to instantiate MyTest, since instantiating _MyTestWithHooks will result in the same infinite recursion problem as before.