Develop Reference

Create instances from just a class without anithing else [duplicate]

Is there a way to circumvent the constructor __init__ of a class in python?
Example:
class A(object):
def __init__(self):
print "FAILURE"
def Print(self):
print "YEHAA"
Now I would like to create an instance of A. It could look like this, however this syntax is not correct.
a = A
a.Print()
EDIT:
An even more complex example:
Suppose I have an object C, which purpose it is to store one single parameter and do some computations with it. The parameter, however, is not passed as such but it is embedded in a huge parameter file. It could look something like this:
class C(object):
def __init__(self, ParameterFile):
self._Parameter = self._ExtractParamterFile(ParameterFile)
def _ExtractParamterFile(self, ParameterFile):
#does some complex magic to extract the right parameter
return the_extracted_parameter
Now I would like to dump and load an instance of that object C. However, when I load this object, I only have the single variable self._Parameter and I cannot call the constructor, because it is expecting the parameter file.
#staticmethod
def Load(file):
f = open(file, "rb")
oldObject = pickle.load(f)
f.close()
#somehow create newObject without calling __init__
newObject._Parameter = oldObject._Parameter
return newObject
In other words, it is not possible to create an instance without passing the parameter file. In my "real" case, however, it is not a parameter file but some huge junk of data I certainly not want to carry around in memory or even store it to disc.
And since I want to return an instance of C from the method Load I do somehow have to call the constructor.
OLD EDIT:
A more complex example, which explains why I am asking the question:
class B(object):
def __init__(self, name, data):
self._Name = name
#do something with data, but do NOT save data in a variable
#staticmethod
def Load(self, file, newName):
f = open(file, "rb")
s = pickle.load(f)
f.close()
newS = B(???)
newS._Name = newName
return newS
As you can see, since data is not stored in a class variable I cannot pass it to __init__. Of course I could simply store it, but what if the data is a huge object, which I do not want to carry around in memory all the time or even save it to disc?

You can circumvent __init__ by calling __new__ directly. Then you can create a object of the given type and call an alternative method for __init__. This is something that pickle would do.
However, first I'd like to stress very much that it is something that you shouldn't do and whatever you're trying to achieve, there are better ways to do it, some of which have been mentioned in the other answers. In particular, it's a bad idea to skip calling __init__.
When objects are created, more or less this happens:
a = A.__new__(A, *args, **kwargs)
a.__init__(*args, **kwargs)
You could skip the second step.
Here's why you shouldn't do this: The purpose of __init__ is to initialize the object, fill in all the fields and ensure that the __init__ methods of the parent classes are also called. With pickle it is an exception because it tries to store all the data associated with the object (including any fields/instance variables that are set for the object), and so anything that was set by __init__ the previous time would be restored by pickle, there's no need to call it again.
If you skip __init__ and use an alternative initializer, you'd have a sort of a code duplication - there would be two places where the instance variables are filled in, and it's easy to miss one of them in one of the initializers or accidentally make the two fill the fields act differently. This gives the possibility of subtle bugs that aren't that trivial to trace (you'd have to know which initializer was called), and the code will be more difficult to maintain. Not to mention that you'd be in an even bigger mess if you're using inheritance - the problems will go up the inheritance chain, because you'd have to use this alternative initializer everywhere up the chain.
Also by doing so you'd be more or less overriding Python's instance creation and making your own. Python already does that for you pretty well, no need to go reinventing it and it will confuse people using your code.
Here's what to best do instead: Use a single __init__ method that is to be called for all possible instantiations of the class that initializes all instance variables properly. For different modes of initialization use either of the two approaches:
Support different signatures for __init__ that handle your cases by using optional arguments.
Create several class methods that serve as alternative constructors. Make sure they all create instances of the class in the normal way (i.e. calling __init__), as shown by Roman Bodnarchuk, while performing additional work or whatever. It's best if they pass all the data to the class (and __init__ handles it), but if that's impossible or inconvenient, you can set some instance variables after the instance was created and __init__ is done initializing.
If __init__ has an optional step (e.g. like processing that data argument, although you'd have to be more specific), you can either make it an optional argument or make a normal method that does the processing... or both.

Use classmethod decorator for your Load method:
class B(object):
def __init__(self, name, data):
self._Name = name
#store data
#classmethod
def Load(cls, file, newName):
f = open(file, "rb")
s = pickle.load(f)
f.close()
return cls(newName, s)
So you can do:
loaded_obj = B.Load('filename.txt', 'foo')
Edit:
Anyway, if you still want to omit __init__ method, try __new__:
>>> class A(object):
... def __init__(self):
... print '__init__'
...
>>> A()
__init__
<__main__.A object at 0x800f1f710>
>>> a = A.__new__(A)
>>> a
<__main__.A object at 0x800f1fd50>

Taking your question literally I would use meta classes :
class MetaSkipInit(type):
def __call__(cls):
return cls.__new__(cls)
class B(object):
__metaclass__ = MetaSkipInit
def __init__(self):
print "FAILURE"
def Print(self):
print "YEHAA"
b = B()
b.Print()
This can be useful e.g. for copying constructors without polluting the parameter list.
But to do this properly would be more work and care than my proposed hack.

Not really. The purpose of __init__ is to instantiate an object, and by default it really doesn't do anything. If the __init__ method is not doing what you want, and it's not your own code to change, you can choose to switch it out though. For example, taking your class A, we could do the following to avoid calling that __init__ method:
def emptyinit(self):
pass
A.__init__ = emptyinit
a = A()
a.Print()
This will dynamically switch out which __init__ method from the class, replacing it with an empty call. Note that this is probably NOT a good thing to do, as it does not call the super class's __init__ method.
You could also subclass it to create your own class that does everything the same, except overriding the __init__ method to do what you want it to (perhaps nothing).
Perhaps, however, you simply wish to call the method from the class without instantiating an object. If that is the case, you should look into the #classmethod and #staticmethod decorators. They allow for just that type of behavior.
In your code you have put the #staticmethod decorator, which does not take a self argument. Perhaps what may be better for the purpose would a #classmethod, which might look more like this:
#classmethod
def Load(cls, file, newName):
# Get the data
data = getdata()
# Create an instance of B with the data
return cls.B(newName, data)
UPDATE: Rosh's Excellent answer pointed out that you CAN avoid calling __init__ by implementing __new__, which I was actually unaware of (although it makes perfect sense). Thanks Rosh!

I was reading the Python cookbook and there's a section talking about this: the example is given using __new__ to bypass __init__()
>>> class A:
def __init__(self,a):
self.a = a
>>> test = A('a')
>>> test.a
'a'
>>> test_noinit = A.__new__(A)
>>> test_noinit.a
Traceback (most recent call last):
File "", line 1, in
test_noinit.a
AttributeError: 'A' object has no attribute 'a'
>>>
However I think this only works in Python3. Below is running under 2.7
>>> class A:
def __init__(self,a):
self.a = a
>>> test = A.__new__(A)
Traceback (most recent call last):
File "", line 1, in
test = A.__new__(A)
AttributeError: class A has no attribute '__new__'
>>>

As I said in my comment you could change your __init__ method so that it allows creation without giving any values to its parameters:
def __init__(self, p0, p1, p2):
# some logic
would become:
def __init__(self, p0=None, p1=None, p2=None):
if p0 and p1 and p2:
# some logic
or:
def __init__(self, p0=None, p1=None, p2=None, init=True):
if init:
# some logic

Can a dynamically added function access the owner object in python?

I'm making a program in python in which specific instances of an object must be decorated with new functions built at runtime.
I've seen very simple examples of adding functions to objects through MethodType:
import types
def foo():
print("foo")
class A:
bar = "bar"
a = A()
a.foo = types.MethodType(foo, a)
But none of the examples I've seen show how a function added in this manner can reference to the new owner's attributes. As far as I know, even though this binds the foo() function to the instance a, foo() must still be a pure function, and cannot contain references to anything local.
In my case, I need functions to change attributes of the object they are added to. Here are two examples of the kind of thing I need to be able to do:
class A:
foo = "foo"
def printme():
print(foo)
def nofoo():
foo = "bar"
def printBar():
if foo != "foo"
self.printme()
I would then need a way to add a copy of a nofoo() or printBar() to an A object in such a way that they can access the object attributes named foo and the function named printme() correctly.
So, is this possible? Is there a way to do this kind of programming in vanilla Python? or at least Is there a programming pattern that achieves this kind of behavior?
P.S.: In my system, I also add attributes dynamically to objects. Your first thought then might be "How can I ever be sure that the object I'm adding the nofoo() function to actually has an attribute named foo?", but I also have a fairly robust tag system that makes sure that I never try to add a nofoo() function to an object that hasn't a foo variable. The reason I mention this is that solutions that look at the class definition aren't very useful to me.

As said in the comments, your function actually must take at least one parameter: self, the instance the method is being called on. The self parameter can be used as it would be used in a normal instance method. Here is an example:
>>> from types import MethodType
>>>
>>> class Class:
def method(self):
print('method run')
>>> cls = Class()
>>>
>>> def func(self): # must accept one argument, `self`
self.method()
>>> cls.func = MethodType(func, cls)
>>> cls.func()
method run
>>>
Without your function accepting self, an exception would be raised:
>>> def func():
self.method()
>>> cls.func = MethodType(func, cls)
>>> cls.func()
Traceback (most recent call last):
File "<pyshell#21>", line 1, in <module>
cls.func()
TypeError: func() takes 0 positional arguments but 1 was given
>>>

class A:
def __init__(self):
self.foo = "foo"
def printme(self):
print(self.foo)
def nofoo(self):
self.foo = "bar"
a.nofoo = types.MethodType(nofoo, a)
a.nofoo()
a.printme()
prints
bar

It's not entirely clear what you're trying to do, and I'm worried that whatever it is may be a bad idea. However, I can explain how to do what you're asking, even if it isn't what you want, or should want. I'll point out that it's very uncommon to want to do the second version below, and even rarer to want to do the third version, but Python does allow them both, because "even rarer than very uncommon" still isn't "never". And, in the same spirit…
The short answer is "yes". A dynamically-added method can access the owner object exactly the same way a normal method can.
First, here's a normal, non-dynamic method:
class C:
def meth(self):
return self.x
c = C()
c.x = 3
c.meth()
Obviously, with a normal method like this, when you call c.meth(), the c ends up as the value of the self parameter, so self.x is c.x, which is 3.
Now, here's how you dynamically add a method to a class:
class C:
pass
c = C()
c.x = 3
def meth(self):
print(self.x)
C.meth = meth
c.meth()
This is actually doing exactly the same thing. (Well, we've left another name for the same function object sitting around in globals, but that's the only difference) If C.meth is the same function it was in the first version, then obviously whatever magic made c.meth() work in the first version will do the exact same thing here.
(This used to be slightly more complicated in Python 2, because of unbound methods, and classic classes too… but fortunately you don't have to worry about that.)
Finally, here's how you dynamically add a method to an instance:
class C:
pass
c = C()
c.x = 3
def meth(self):
print(self.x)
c.meth = types.MethodType(meth, c)
c.meth()
Here, you actually have to know the magic that makes c.meth() work in the first two cases. So read the Descriptor HOWTO. After that, it should be obvious.
But if you just want to pretend that Guido is a wizard (Raymond definitely is a wizard) and it's magic… Well, in the first two versions, Guido's magic wand creates a special bound method object whenever you ask for c.meth, but even he isn't magical enough to do that when C.meth doesn't exist. But we can painstakingly create that same bound method object and store it as c.meth. After that, we're going to get the same thing we stored whenever we ask for c.meth, which we explicitly built as the same thing we got in the first two examples, so it'll obviously do the same thing.
But what if we did this:
class C:
pass
c = C()
c.x = 3
def meth(self):
print(self.x)
c.meth = meth
c.meth(c)
Here, you're not letting Guido do his descriptor magic to create c.meth, and you're not doing it manually, you're just sticking a regular function there. Which means if you want anything to show up as the self parameter, you have to explicitly pass it as an argument, as in that silly c.meth(c) line at the end. But if you're willing to do that, then even this one works. No matter how self ends up as c, self.x is going to be c.x.

Why we need corresponding class function with each method in python?

I am learning OOP in python and following this and this stackoverflow answers and this post
I understood how class works and how method called and all things but i have some doubts:
Consider this fragment of code:
class Point(object):
def __init__(self,x,y):
self.x = x
self.y = y
def distance(self):
print (self.x)
def bye(self):
print(self.y)
a=Point(1,2)
a.distance()
a.bye()
As i read in tutorial :
when we call a method with some arguments, the corresponding class
function is called by placing the method's object before the first
argument. So, anything like obj.meth(args) becomes Class.meth(obj,
args).
when ObjectA.methodA(arg1, arg2) is called, python internally converts
it for you as:
ClassA.methodA(ObjectA, arg1, arg2)
Now my confusion is why program need to call class with each method ?
Class.meth(obj, args) ??
like when we call a.distance it become Point.distance(a) causes of "self"
when we called a.bye it become Point.bye(a) causes of "self" .
when Point class is necessery with each method if we don't use Point class with each method what will happen?
why can't simply meth(obj, args) works ?
My main doubt is why its called class.some_method with each method when we called with attribute of method . why its needs calls with each one?
#if i am understanding right then its necessary because so that each method can access other methods data like variables and stuff?

The key is
python internally converts it for you
From your standpoint:
meth(self, args) is the syntax you use to define member functions; and
obj.meth(args) is the syntax you use to call member functions.
The meth(obj,args) option is the way procedural languages work. That is often how the implementation works, but expressing the call as obj.meth(args) keeps focus on the object and makes it easier to read which data values (object instances) are being used.
Edit 1 If I understand your question correctly, you are asking why Python needs to know the class when it already has the instance available, and instances know their own types. In fact, Python fetches methods based on the instance all the time. I think the point the tutorial is making is that in Python, the class is the primary place the functions are defined. This is different from some object-oriented languages, in which each instance has its own methods, and they may be completely different from each other. So the tutorial is contrasting the usual approach in Python:
class Foo:
def bar(self):
pass
with an alternative (possible in Python, but not typical):
foo = object() # an empty instance
foo.bar = lambda self: pass
Edit 2 Python methods normally live in the classes, not in the instances. Even if you create 1000 Point objects, there is only one copy of the actual instruction bytes for Point.distance. Those instruction bytes are executed anytime <some point variable>.distance() is called. You are correct that the self parameter is how those instruction bytes know what instance to work on, and how the method can access other data in the passed instance.
Edit 3 self isn't exactly a namespace in the way that local vs. global is. However, it is fair to say that self.foo refers to a foo that is indeed accessible to all the methods of this instance of the current class. Given
a = Point(1,2)
b = Point(3,4)
inside a Point.distance call, self refers to a or b, but not both. So when you call a.distance(), the self.x will be a.x, not b.x. But all methods of Point can access self.x to get whatever the current point's x is.
Edit 4 Suppose you weren't using objects, but instead dictionaries:
a = {'x':1, 'y':2} # make a "point"
b = {'x':3, 'y':4} # make another
def point_distance(point):
print (point['x'])
then you could say:
point_distance(a)
to get the effect of
print (a['x'])
Classes do basically that, with cleaner syntax and some nice benefits. But just as the point parameter to point_distance() refers to one and only one point-like dictionary each time you call point_distance(), the self parameter to Point.distance() refers to one and only one Point instance each time you call <whatever point>.distance().

Because you can have the same method name in different classes, and it needs to call the appropriate one. So if you have
class Class1:
def meth():
print "This is Class 1"
class Class2:
def meth():
print "This is Class 2"
c1 = Class1()
c2 = Class2()
c1.meth() # equivalent to Class1.meth(c1)
c2.meth() # equivalent to Class2.meth(c2)
If it translated c1.meth() to meth(c1), there's no way for the system to know which meth() function to call.

Classes define what is common to all instances of them. Usually this is the code comprising each of its methods. To apply this code to the correct instance object, the language interprets
instance.method(arg1, arg2, ...)
as
class_of_instance.method(instance, arg1, arg2, ...)
so the code is applied to the proper class instance.

Function for class exemplar

I have something like that in my python code
class A:
__mess = "Yeap!"
def doSome(self):
self.FN()
def FN(self):
pass
def myFN(self):
print self.__mess
b = A()
b.FN = myFN
b.doSome()
But this doesn't work. Where am I wrong?
python 2.6.5
upd: I want to redefine method (FN) only for one exemplar (b).
upd2:
import new
class A:
__mess = "Yeap!"
def doSome(self):
self.FN()
def FN(self):
pass
def myFN(self):
print self.__mess
b = A()
b.FN = new.instancemethod(myFN, b, A)
b.doSome()
Doesn't work too.
Traceback (most recent call last):
File "", line 1, in
File "", line 4, in doSome
File "", line 2, in myFN
AttributeError: A instance has no
attribute '__mess'

myLoopFN is a function, not an instance method. Do
import new
b.loopFN = new.instancemethod( myLoopFN, b, A )
The problem is that Python treats instance methods very slightly differently to regular functions: they get the instance upon which they are run as the default first argument. If you define a method inside a class definition it automagically becomes an instance method, so that when you instantiate the class it gets passed the instance. However, when you define myLoopFN you do it outside the class definition, so that it is an ordinary function instead of an instance method. You fix this by explicitly declaring it as an instance method.
...
BUT
This is icky because it's not something you should do; changing instance methods at runtime will lead to problems. You'll never be sure whether your A is an original A or a modified one, and you won't be able to debug it because you can't tell whether you've changed loopFN or not. This will give you the kind of bugs that Nyarlathotep himself would be proud of.
The right way to do this is to subclass A and override the method, so that you can distinguish between the different classes.
class myA( A ):
def loopFN(self):
#put modified function here
This way, you can instantiate the modified class and be certain of its methods.
Edit
You are using a double-underscore variable name, __mess. You (almost certainly) don't want to do this. For some reason known only to our Benevolent Dictator for Life and a select few others, Python automatically mangles these __ names to _<class-name>__, to serve as a sort-of faux private variable. This is horrible, and besides there's no reason to call it __mess instead of (the much nicer) mess.
If you absolutely must call it __mess, you can refer to it as follows:
def myFN(self):
print( self._A__mess )
(mutatis mutandis when you change the name of A). This is nasty and unPythonic.

Regarding the second error (with __mess):
Change
print self.__mess
to
print self._mess
And change
class A:
__mess = "Yeap!"
to
class A:
_mess = "Yeap!"
Double underscores tell Python to use name-mangling.
An alternative is to change
def myFN(self):
print self.__mess
to
def myFN(self):
print self._A__mess

is it ever useful to define a class method with a reference to self not called 'self' in Python?

I'm teaching myself Python and I see the following in Dive into Python section 5.3:
By convention, the first argument of any Python class method (the reference to the current instance) is called self. This argument fills the role of the reserved word this in C++ or Java, but self is not a reserved word in Python, merely a naming convention. Nonetheless, please don't call it anything but self; this is a very strong convention.
Considering that self is not a Python keyword, I'm guessing that it can sometimes be useful to use something else. Are there any such cases? If not, why is it not a keyword?

No, unless you want to confuse every other programmer that looks at your code after you write it. self is not a keyword because it is an identifier. It could have been a keyword and the fact that it isn't one was a design decision.

As a side observation, note that Pilgrim is committing a common misuse of terms here: a class method is quite a different thing from an instance method, which is what he's talking about here. As wikipedia puts it, "a method is a subroutine that is exclusively associated either with a class (in which case it is called a class method or a static method) or with an object (in which case it is an instance method).". Python's built-ins include a staticmethod type, to make static methods, and a classmethod type, to make class methods, each generally used as a decorator; if you don't use either, a def in a class body makes an instance method. E.g.:
>>> class X(object):
... def noclass(self): print self
... #classmethod
... def withclass(cls): print cls
...
>>> x = X()
>>> x.noclass()
<__main__.X object at 0x698d0>
>>> x.withclass()
<class '__main__.X'>
>>>
As you see, the instance method noclass gets the instance as its argument, but the class method withclass gets the class instead.
So it would be extremely confusing and misleading to use self as the name of the first parameter of a class method: the convention in this case is instead to use cls, as in my example above. While this IS just a convention, there is no real good reason for violating it -- any more than there would be, say, for naming a variable number_of_cats if the purpose of the variable is counting dogs!-)

The only case of this I've seen is when you define a function outside of a class definition, and then assign it to the class, e.g.:
class Foo(object):
def bar(self):
# Do something with 'self'
def baz(inst):
return inst.bar()
Foo.baz = baz
In this case, self is a little strange to use, because the function could be applied to many classes. Most often I've seen inst or cls used instead.

I once had some code like (and I apologize for lack of creativity in the example):
class Animal:
def __init__(self, volume=1):
self.volume = volume
self.description = "Animal"
def Sound(self):
pass
def GetADog(self, newvolume):
class Dog(Animal):
def Sound(this):
return self.description + ": " + ("woof" * this.volume)
return Dog(newvolume)
Then we have output like:
>>> a = Animal(3)
>>> d = a.GetADog(2)
>>> d.Sound()
'Animal: woofwoof'
I wasn't sure if self within the Dog class would shadow self within the Animal class, so I opted to make Dog's reference the word "this" instead. In my opinion and for that particular application, that was more clear to me.

Because it is a convention, not language syntax. There is a Python style guide that people who program in Python follow. This way libraries have a familiar look and feel. Python places a lot of emphasis on readability, and consistency is an important part of this.

I think that the main reason self is used by convention rather than being a Python keyword is because it's simpler to have all methods/functions take arguments the same way rather than having to put together different argument forms for functions, class methods, instance methods, etc.
Note that if you have an actual class method (i.e. one defined using the classmethod decorator), the convention is to use "cls" instead of "self".