Being from OOPS background, It looks strange to see below code from link
def f():
f.beencalled = True
return 0
My question:
1)
From the above code,
Is f a reference variable pointing to an object f of class 'function'?
2)
We add a new attribute beencalled to an object f, so now 'function' class does not have this attribute beencalled defined and we say that object f is an object of class 'function'? Does it make sense?
1) Yes:
>>> def f():
print(type(f))
>>> f()
>>> <class 'function'>
2) The function class does not have a new attribute, but the object f does. Adding or removing attributes to/from an object does not affect which attributes other objects of that class will have:
>>> class A: pass
>>> a = A()
>>> a.var = 7
>>> b = A()
>>> b.var
Traceback (most recent call last):
File "<pyshell#19>", line 1, in <module>
b.newvar
AttributeError: 'A' object has no attribute 'var'
Classes are much more flexible in python than in Java or C++. Objects can have attributes not defined in their class, or even lack attributes that were defined in their class! Look at this:
>>> class A:
def __init__(self, a):
self.var = a
>>> obj = A(7)
>>> del obj.var #deletes the var attribute from obj, does not change the A class
>>> obj.var
Traceback (most recent call last):
File "<pyshell#28>", line 1, in <module>
obj.var
AttributeError: 'A' object has no attribute 'var'
>>> obj2 = A(6)
>>> obj2.var #obj2 is a new object, so the fact we deleted var from obj doesn't affect it
6
EDIT: after a bit of searching I found an explanation for why this behavior was chosen (source):
To implement user-defined objects, I settled on the simplest possible
design; a scheme where objects were represented by a new kind of
built-in object that stored a class reference pointing to a "class
object" shared by all instances of the same class, and a dictionary,
dubbed the "instance dictionary", that contained the instance
variables.
In this implementation, the instance dictionary would contain the
instance variables of each individual object whereas the class object
would contain stuff shared between all instances of the same class--in
particular, methods. In implementing class objects, I again chose the
simplest possible design; the set of methods of a class were stored in
a dictionary whose keys are the method names. This, I dubbed the class
dictionary. To support inheritance, class objects would additionally
store a reference to the class objects corresponding to the base
classes. At the time, I was fairly naïve about classes, but I knew
about multiple inheritance, which had recently been added to C++. I
decided that as long as I was going to support inheritance, I might as
well support a simple-minded version of multiple inheritance. Thus,
every class object could have one or more base classes.
In this implementation, the underlying mechanics of working with
objects are actually very simple. Whenever changes are made to
instance or class variables, those changes are simply reflected in the
underlying dictionary object. For example, setting an instance
variable on an instance updates its local instance dictionary.
Likewise, when looking up the value of a instance variable of an
object, one merely checks its instance dictionary for the existence of
that variable. If the variable is not found there, things become a
little more interesting. In that case, lookups are performed in the
class dictionary and then in the class dictionaries of each of the
base classes.
On a slightly different note, you can change this behavior for custom classes.
class FooBar(object):
__slots__ = ["foo","bar","baz"]
# if you don't define __slots__, you can add attr to the object as needed
# if you do, the object can only contain those attributes.
def __init__(self,foo=None,bar=None,baz=None):
self.foo = foo
self.bar = bar
self.baz = baz
def __str__(self):
return "I'm a FooBar with id {0} with foo: {1.foo}, bar: {1.bar}, baz: {1.baz}".format(id(self),self)
>>> a = FooBar("a","B","CCC")
>>> print(a)
I'm a FooBar with id 47260256 with foo: a, bar: B, baz: CCC
>>> a.spam = "eggs"
Traceback (most recent call last):
File "<pyshell#13>", line 1, in <module>
a.spam = "eggs"
AttributeError: 'FooBar' object has no attribute 'spam'
Alternately, without defining __slots__:
class BooFar(object):
def __str__(self):
return "I'm a BooFar with the following attributes:\n{}".format(self.__dict__)
>>> b = BooFar()
>>> print(b)
I'm a BooFar with the following attributes:
{}
>>> b.spam = "eggs"
>>> print(b)
I'm a BooFar with the following attributes:
{'spam': 'eggs'}
f() in just an instance of types.FunctionType, and instances can have their own attributes.
Adding an attribute to an instance won't affect its class unless you've overridden the __setattr__ method of that class and doing something evil there.
>>> import types
>>> def func(): pass
>>> isinstance(func, types.FunctionType)
True
Related
Let's say we have this simple Python code
class MyClass(object):
class_var = 1
def __init__(self, i_var):
self.i_var = i_var
Correct me if I get any of this wrong:
Class_Var is a class variable that is the same for all instances of MyClass object.
I_Var is an instance variable that only exists in instances of the MyClass object
foo = MyClass(2)
bar = MyClass(3)
foo.class_var, foo.i_var
## 1, 2
bar.class_var, bar.i_var
## 1, 3
Class variables are also properties of the class itself.
MyClass.class_var ##
## 1
MyClass.I_var should error out, correct?
Does that mean that class variables can be considered like instance variables of the class object itself (since all classes are objects) ?
MyClass.new_attribute = 'foo'
print(hasattr(ObjectCreator, 'new_attribute'))
That should return true. And
print (MyClass.new_attribute)
should return foo.
How come we can create a new class variable that was not defined in the original definition for that class?
Is
MyClass.new_attribute = 'foo'
the exact same thing as creating that class attribute in the original definition?
class MyClass(object):
class_var = 1
new_attribute = 'foo'
So we can create new class attributes at runtime? How does that not interfere with the init constructor that creates the class object and has those class variables as instance variables of the class object?
A class object is just an instance of yet another type, usually type (though you can change this using the metaclass parameter to the class statement).
Like most other instances, you can add arbitrary instance attributes to a class object at any time.
Class attributes and instance attributes are wholly separate; the former are stored on the class object, the latter on instances of the class.
There's nothing particularly special about __init__; it's just another method that, among other things, can attached new attributes to an object. What is special is that __init__ is called automatically when you create a new instance of the class by calling the class. foo = MyClass(2) is equivalent to
foo = MyClass.__new__(MyClass, 2)
foo.__init__(2)
The class statement
class MyClass(object):
class_var = 1
def __init__(self, i_var):
self.i_var = i_var
is roughly equivalent to
def my_class_init(self, i_var):
self.i_var = i_var
MyClass = type('MyClass', (object,), {'class_var': 1, '__init__: my_class_init})
The 3-argument form of type lets you pass a dict that creates class attributes when you first create the class, but you can always assign attributes after the fact as well:
MyClass = type('MyClass', (object,), {})
MyClass.class_var = 1
MyClass.__init__ = my_class_init
Just to blow your mind a little bit more, the call to type can be though of as
MyClass = type.__new__(type, 'MyClass', (object,), {...})
MyClass.__init__('MyClass', (object,), {...})
though unless you define a custom metaclass (by subclassing type), you never have to think about type itself having __new__ and __init__ methods.
Does that mean that class variables can be considered like instance variables of the class object itself (since all classes are objects) ?
Yes.
How come we can create a new class variable that was not defined in the original definition for that class?
Because Python is a dynamic language. A class can be created at run time - in fact, it is created at run time when you run Python interactively.
So we can create new class attributes at runtime?
Yes, unless the metaclass (the class of the class) has forbidden it.
How does that not interfere with the init constructor that creates the class object and has those class variables as instance variables of the class object?
The only rule is that you cannot use something that has not yet be defined or something that has been deleted:
>>> class MyClass(object):
class_var = 1
def __init__(self, i_var):
self.i_var = i_var
self.j_var = self.class_var + 1
>>> a = MyClass(2)
>>> del MyClass.class_var
>>> b = MyClass(3)
Traceback (most recent call last):
File "<pyshell#39>", line 1, in <module>
b = MyClass(3)
File "<pyshell#36>", line 6, in __init__
self.j_var = self.class_var + 1
AttributeError: 'MyClass' object has no attribute 'class_var'
There is no magic here: anything can only exists between its definition point and its destruction point. Python allows you to add attributes to objects at any time, except that some classes (for example object) forbid it.
With the previous a object of class MyClass, you could do:
a.z_var = 12
from that point, z_var will be an attribute of a but others objects of same class will not have it.
Simply object forbids that:
>>> o = object()
>>> o.x=1
Traceback (most recent call last):
File "<pyshell#41>", line 1, in <module>
o.x=1
AttributeError: 'object' object has no attribute 'x'
I'm wondering weather it is necessary to define class instance variable within class declarations.
I tried assigning a new instance variable after the object (class instance) was already created, and looks like there is no difference. Are there any caveats in this approach?
class Context():
def __init__(self, extension):
self.extension = extension
c = Context('extension+')
print(f"before: {c.__dict__}")
c.new_var = 'new_var_content'
print(c.extension + c.new_var)
print(f"after: {c.__dict__}")
printed:
before: {'extension': 'extension+'}
extension+new_var_content
after: {'extension': 'extension+', 'new_var': 'new_var_content'}
There is no difference between declaring self.foo within a def __init__(self, <arguments>): definition, and declaring it after an object has been instantiated.
Both assignments have instance-level scope.
Given -
class Context:
i_am_a_class_variable = 'class_string'
def __init__(self, bar):
self.bar = bar
See -
class attributes can be accessed without instantiating an object.
>>> Context.i_am_a_class_variable
'class_string'
instance attributes can be assigned during instantiation using the __init__(self) function.
>>> Context.bar
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-4-8be0704da5be> in <module>
----> 1 Context.bar
>>> instance = Context('bar')
>>> instance.bar
'bar'
instance attributes can be assigned after instantiation, directly
>>> instance = Context('bar')
>>> instance.foo = 'foo'
>>> instance.foo
'foo'
Speaking in terms of whether you can assign a value to the property or create a new property, there is no difference if you do it within init or anywhere else after the object is created as in both cases it gets added in dict of the object(unless you use slots)
However, if you want your class to be initialized with desired state (i.e, having some mandatory variables with default/preset values) , you should put it in init. Since init is called implicitly as soon as object is created, you object will be having desired state.
It is fairly easy to use the __getattr__ special method on Python classes to handle either missing properties or functions, but seemingly not both at the same time.
Consider this example which handles any property requested which is not defined explicitly elsewhere in the class...
class Props:
def __getattr__(self, attr):
return 'some_new_value'
>>> p = Props()
>>> p.prop # Property get handled
'some_new_value'
>>> p.func('an_arg', kw='keyword') # Function call NOT handled
Traceback (most recent call last):
File "<console>", line 1, in <module>
TypeError: 'str' object is not callable
Next, consider this example which handles any function call not defined explicitly elsewhere in the class...
class Funcs:
def __getattr__(self, attr):
def fn(*args, **kwargs):
# Do something with the function name and any passed arguments or keywords
print attr
print args
print kwargs
return
return fn
>>> f = Funcs()
>>> f.prop # Property get NOT handled
<function fn at 0x10df23b90>
>>> f.func('an_arg', kw='keyword') # Function call handled
func
('an_arg',)
{'kw': 'keyword'}
The question is how to handle both types of missing attributes in the same __getattr__? How to detect if the attribute requested was in property notation or in method notation with parentheses and return either a value or a function respectively? Essentially I want to handle SOME missing property attributes AND SOME missing function attributes and then resort to default behavior for all the other cases.
Advice?
How to detect if the attribute requested was in property notation or in method notation with parentheses and return either a value or a function respectively?
You can't. You also can't tell whether a requested method is an instance, class, or static method, etc. All you can tell is that someone is trying to retrieve an attribute for read access. Nothing else is passed into the getattribute machinery, so nothing else is available to your code.
So, you need some out-of-band way to know whether to create a function or some other kind of value. This is actually pretty common—you may actually be proxying for some other object that does have a value/function distinction (think of ctypes or PyObjC), or you may have a naming convention, etc.
However, you could always return an object that can be used either way. For example, if your "default behavior" is to return attributes are integers, or functions that return an integer, you can return something like this:
class Integerizer(object):
def __init__(self, value):
self.value = value
def __int__(self):
return self.value
def __call__(self, *args, **kw):
return self.value
There is no way to detect how the returned attribute was intended to be used. Everything on python objects are attributes, including the methods:
>>> class Foo(object):
... def bar(self): print 'bar called'
... spam='eggs'
...
>>> Foo.bar
<unbound method Foo.bar>
>>> Foo.spam
'eggs'
Python first looks up the attribute (bar or spam), and if you meant to call it (added parenthesis) then Python invokes the callable after lookup up the attribute:
>>> foo = Foo()
>>> fbar = foo.bar
>>> fbar()
'bar called'
In the above code I separated the lookup of bar from calling bar.
Since there is no distinction, you cannot detect in __getattr__ what the returned attribute will be used for.
__getattr__ is called whenever normal attribute access fails; in the following example monty is defined on the class, so __getattr__ is not called; it is only called for bar.eric and bar.john:
>>> class Bar(object):
... monty = 'python'
... def __getattr__(self, name):
... print 'Attribute access for {0}'.format(name)
... if name == 'eric':
... return 'idle'
... raise AttributeError(name)
...
>>> bar = Bar()
>>> bar.monty
'python'
>>> bar.eric
Attribute access for eric
'idle'
>>> bar.john
Attribute access for john
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 7, in __getattr__
AttributeError: john
Note that functions are not the only objects that you can invoke (call); any custom class that implements the __call__ method will do:
>>> class Baz(object):
... def __call__(self, name):
... print 'Baz sez: "Hello {0}!"'.format(name)
...
>>> baz = Baz()
>>> baz('John Cleese')
Baz sez: "Hello John Cleese!"
You could use that return objects from __getattr__ that can both be called and used as a value in different contexts.
What I am asking may look weird, but here is an example:
I have a class 'A'
class A:
a=1
other I have class 'B'
class B:
def __init__(self, obj):
self.obj = obj # obj is any object
Now I use:
first = A()
second = B(first)
isinstance(second, A)
I want step 3 to be true. i.e. whatever object class B is taking, it should add instance of that object type to object.
Is something like this possible in Python?
You can of course override the __new__ and derive your object from type instead of object effectively creating a class factory...
What you end up doing is very similar to:
b = type('B', (A,), {'obj': A()})
Which generates a class B derived from A, containing that instance of A() - since this is a function you can pass whatever you fancy in for whatever reason you wish to do so.
Using inheritance, yes:
class B(A):
def __init__(self, obj):
self.obj = obj # obj is any object
2 Possibilities
instead of isinstance(second, A) do isinstance(second.obj, A)
Second... more hackish way is to do something like this:
class B:
def __init__(self, obj):
self.obj = obj # obj is any object
self.__class__ = obj.__class__
This is hackish as it basically fools the interpreter into into thinking the instance is a different class. That is isinstance(second, B) will return False
To answer the question posed below: the interpreter will basically act as if second is a class A and nothing defined at the class level in B will remain. eg if you do something like
class B:
b=2 #Won't be visible
def __init__(self, obj):
self.obj = obj # obj is any object
self.b2 = 5 #Instance variable will be visible
self.__class__ = obj.__class__
def someFunc(self): #Won't be visible
return 3
Using the same code as you used above for initialization here is what will happen with some calls using the interpreter. In general any class variables or methods will be removed and instead use A'a, however any instance variables will be remembered. Because of this doing self.obj = obj is a bit redundant. Basically instantiating B(obj) will more or less return an object of the same class as obj. Though it won't call obj's __init__, for that you will need some more voodoo/magic (if you're interested just post).
>>> isinstance(second, A)
True
>>> isinstance(second, B)
False
>>> second.a
1
>>> second.b
Traceback (most recent call last):
File "<pyshell#15>", line 1, in <module>
second.b
AttributeError: A instance has no attribute 'b'
>>> second.someFunc()
Traceback (most recent call last):
File "<pyshell#16>", line 1, in <module>
second.someFunc()
AttributeError: A instance has no attribute 'someFunc'
>>> second.b2
5
>>> second.obj
<__main__.A instance at 0x0123CAF8>
I'd be tempted to suggest that this is highly unlikely to be a good idea even if it's possible in a non-hackish way. (Edit: Jon Clements' suggestion strikes me as the best/least hackish way but I still suggest the rest of my post is relevant.) I'd further hazard to suggest this is conflating/confusing an "is-a" relationship with what should probably be a "has-a" relationship. Impossible to know for sure unless more details are posted about what the OP is trying to achieve.
Anyway, someone (Kent Beck I think) once said (paraphrasing as I remember it) that inheritance creates very powerful coupling between bodies of code with attendant difficulties in maintenance and enhancement and that therefore inheritance should really be pretty deep down in your bag of tricks and shouldn't be used lightly. Put differently: Prefer composition (or aggregation) over inheritance where at all possible.
If I have the following class, what's the best way of getting the exact list of variables and methods, excluding those from the superclass?
class Foo(Bar):
var1 = 3.14159265
var2 = Baz()
#property
def var3(self):
return 42
def meth1(self, var):
return var
I want the tuple ('var1','var2','var3','meth1') with minimum overhead. This is being run in a Django environment, which seems to be putting some of it's class instance variables in the read-only __dict__ variable; a feat which I can't find a way to replicate.
Here's what I'm seeing while playing with it, any suggestions beyond trimming out the __* from the dir() or manually listing them?
>>> a=Foo()
>>> a
<__main__.Foo instance at 0x7f48c1e835f0>
>>> dict(a)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: iteration over non-sequence
>>> dir(a)
['__doc__', '__module__', 'meth1', 'var1', 'var2', 'var3']
>>> a.__dict__
{}
If the class and its superclasses are known, something like:
tuple(set(dir(Foo)) - set(dir(Bar)))
If you want it to be more generic, you can get a list of the base classes using something like
bases = Foo.mro()
...and then use that list to subtract out attributes from all the base classes.
In your example, a is an instance, its __dict__ will include all variables set in its __init__ function. To get all class variables, use a.__class__.__dict__
A third answer is the inspect module which does the same as above
def getVariablesClass(inst):
var = []
cls = inst.__class__
for v in cls.__dict__:
if not callable(getattr(cls, v)):
var.append(v)
return var
if you want exclude inline variables check names on the __ at the start and the end of variable
If you want to introspect your own classes, you can do it on class definition and cache it by the way:
class Bar:
parent_prop = 0
class Foo(Bar):
my_prop1 = 1
my_prop2 = 2
def method1(self):
pass
SYMBOLS = [k for k in locals().keys() if not k.startswith('_')]
if __name__ == '__main__':
print(Foo.SYMBOLS)
Output:
['my_prop1', 'my_prop2', 'method1']