Why does the following class declaration inherit from object?
class MyClass(object):
...
Is there any reason for a class declaration to inherit from object?
In Python 3, apart from compatibility between Python 2 and 3, no reason. In Python 2, many reasons.
Python 2.x story:
In Python 2.x (from 2.2 onwards) there's two styles of classes depending on the presence or absence of object as a base-class:
"classic" style classes: they don't have object as a base class:
>>> class ClassicSpam: # no base class
... pass
>>> ClassicSpam.__bases__
()
"new" style classes: they have, directly or indirectly (e.g inherit from a built-in type), object as a base class:
>>> class NewSpam(object): # directly inherit from object
... pass
>>> NewSpam.__bases__
(<type 'object'>,)
>>> class IntSpam(int): # indirectly inherit from object...
... pass
>>> IntSpam.__bases__
(<type 'int'>,)
>>> IntSpam.__bases__[0].__bases__ # ... because int inherits from object
(<type 'object'>,)
Without a doubt, when writing a class you'll always want to go for new-style classes. The perks of doing so are numerous, to list some of them:
Support for descriptors. Specifically, the following constructs are made possible with descriptors:
classmethod: A method that receives the class as an implicit argument instead of the instance.
staticmethod: A method that does not receive the implicit argument self as a first argument.
properties with property: Create functions for managing the getting, setting and deleting of an attribute.
__slots__: Saves memory consumptions of a class and also results in faster attribute access. Of course, it does impose limitations.
The __new__ static method: lets you customize how new class instances are created.
Method resolution order (MRO): in what order the base classes of a class will be searched when trying to resolve which method to call.
Related to MRO, super calls. Also see, super() considered super.
If you don't inherit from object, forget these. A more exhaustive description of the previous bullet points along with other perks of "new" style classes can be found here.
One of the downsides of new-style classes is that the class itself is more memory demanding. Unless you're creating many class objects, though, I doubt this would be an issue and it's a negative sinking in a sea of positives.
Python 3.x story:
In Python 3, things are simplified. Only new-style classes exist (referred to plainly as classes) so, the only difference in adding object is requiring you to type in 8 more characters. This:
class ClassicSpam:
pass
is completely equivalent (apart from their name :-) to this:
class NewSpam(object):
pass
and to this:
class Spam():
pass
All have object in their __bases__.
>>> [object in cls.__bases__ for cls in {Spam, NewSpam, ClassicSpam}]
[True, True, True]
So, what should you do?
In Python 2: always inherit from object explicitly. Get the perks.
In Python 3: inherit from object if you are writing code that tries to be Python agnostic, that is, it needs to work both in Python 2 and in Python 3. Otherwise don't, it really makes no difference since Python inserts it for you behind the scenes.
Python 3
class MyClass(object): = New-style class
class MyClass: = New-style class (implicitly inherits from object)
Python 2
class MyClass(object): = New-style class
class MyClass: = OLD-STYLE CLASS
Explanation:
When defining base classes in Python 3.x, you’re allowed to drop the object from the definition. However, this can open the door for a seriously hard to track problem…
Python introduced new-style classes back in Python 2.2, and by now old-style classes are really quite old. Discussion of old-style classes is buried in the 2.x docs, and non-existent in the 3.x docs.
The problem is, the syntax for old-style classes in Python 2.x is the same as the alternative syntax for new-style classes in Python 3.x. Python 2.x is still very widely used (e.g. GAE, Web2Py), and any code (or coder) unwittingly bringing 3.x-style class definitions into 2.x code is going to end up with some seriously outdated base objects. And because old-style classes aren’t on anyone’s radar, they likely won’t know what hit them.
So just spell it out the long way and save some 2.x developer the tears.
Yes, this is a 'new style' object. It was a feature introduced in python2.2.
New style objects have a different object model to classic objects, and some things won't work properly with old style objects, for instance, super(), #property and descriptors. See this article for a good description of what a new style class is.
SO link for a description of the differences: What is the difference between old style and new style classes in Python?
History from Learn Python the Hard Way:
Python's original rendition of a class was broken in many serious
ways. By the time this fault was recognized it was already too late,
and they had to support it. In order to fix the problem, they needed
some "new class" style so that the "old classes" would keep working
but you can use the new more correct version.
They decided that they would use a word "object", lowercased, to be
the "class" that you inherit from to make a class. It is confusing,
but a class inherits from the class named "object" to make a class but
it's not an object really its a class, but don't forget to inherit
from object.
Also just to let you know what the difference between new-style classes and old-style classes is, it's that new-style classes always inherit from object class or from another class that inherited from object:
class NewStyle(object):
pass
Another example is:
class AnotherExampleOfNewStyle(NewStyle):
pass
While an old-style base class looks like this:
class OldStyle():
pass
And an old-style child class looks like this:
class OldStyleSubclass(OldStyle):
pass
You can see that an Old Style base class doesn't inherit from any other class, however, Old Style classes can, of course, inherit from one another. Inheriting from object guarantees that certain functionality is available in every Python class. New style classes were introduced in Python 2.2
Yes, it's historical. Without it, it creates an old-style class.
If you use type() on an old-style object, you just get "instance". On a new-style object you get its class.
The syntax of the class creation statement:
class <ClassName>(superclass):
#code follows
In the absence of any other superclasses that you specifically want to inherit from, the superclass should always be object, which is the root of all classes in Python.
object is technically the root of "new-style" classes in Python. But the new-style classes today are as good as being the only style of classes.
But, if you don't explicitly use the word object when creating classes, then as others mentioned, Python 3.x implicitly inherits from the object superclass. But I guess explicit is always better than implicit (hell)
Reference
Related
This question already has answers here:
Why do Python classes inherit object?
(6 answers)
Closed 1 year ago.
I have found that both of the following work:
class Foo():
def a(self):
print "hello"
class Foo(object):
def a(self):
print "hello"
Should all Python classes extend object? Are there any potential problems with not extending object?
In Python 2, not inheriting from object will create an old-style class, which, amongst other effects, causes type to give different results:
>>> class Foo: pass
...
>>> type(Foo())
<type 'instance'>
vs.
>>> class Bar(object): pass
...
>>> type(Bar())
<class '__main__.Bar'>
Also the rules for multiple inheritance are different in ways that I won't even try to summarize here. All good documentation that I've seen about MI describes new-style classes.
Finally, old-style classes have disappeared in Python 3, and inheritance from object has become implicit. So, always prefer new style classes unless you need backward compat with old software.
In Python 3, classes extend object implicitly, whether you say so yourself or not.
In Python 2, there's old-style and new-style classes. To signal a class is new-style, you have to inherit explicitly from object. If not, the old-style implementation is used.
You generally want a new-style class. Inherit from object explicitly. Note that this also applies to Python 3 code that aims to be compatible with Python 2.
In python 3 you can create a class in three different ways & internally they are all equal (see examples). It doesn't matter how you create a class, all classes in python 3 inherits from special class called object. The class object is fundamental class in python and provides lot of functionality like double-underscore methods, descriptors, super() method, property() method etc.
Example 1.
class MyClass:
pass
Example 2.
class MyClass():
pass
Example 3.
class MyClass(object):
pass
Yes, all Python classes should extend (or rather subclass, this is Python here) object. While normally no serious problems will occur, in some cases (as with multiple inheritance trees) this will be important. This also ensures better compatibility with Python 3.
As other answers have covered, Python 3 inheritance from object is implicit. But they do not state what you should do and what is convention.
The Python 3 documentation examples all use the following style which is convention, so I suggest you follow this for any future code in Python 3.
class Foo:
pass
Source: https://docs.python.org/3/tutorial/classes.html#class-objects
Example quote:
Class objects support two kinds of operations: attribute references
and instantiation.
Attribute references use the standard syntax used for all attribute
references in Python: obj.name. Valid attribute names are all the
names that were in the class’s namespace when the class object was
created. So, if the class definition looked like this:
class MyClass:
"""A simple example class"""
i = 12345
def f(self):
return 'hello world'
Another quote:
Generally speaking, instance variables are for data unique to each
instance and class variables are for attributes and methods shared by
all instances of the class:
class Dog:
kind = 'canine' # class variable shared by all instances
def __init__(self, name):
self.name = name # instance variable unique to each instance
in python3 there isn't a differance, but in python2 not extending object gives you an old-style classes; you'd like to use a new-style class over an old-style class.
I tried to understand how Zope interface work. I know Interface is just an instance of InterfaceClass which is just an ordinary Class. But if Interface is just a class instance, why it can be used as a base class to be inherited from?
e.g.
Class IFoo(Interface):
pass
Could you give me some insights? Thank you.
Python is inherently flexible, and any object can be a base class as long as it looks like a base class. As is always the case with Python, that means implementing some attributes that are expected to be found on a Python classes.
The Interface class (or it's bases Specification and Element) sets several. Look for any variables set starting with a double underscore (__) to gain an understanding:
__module__: A string containing the python path module.
__name__: The name under which the class was defined.
__bases__: The base classes of this class.
__doc__: (optional) The docstring of the class.
In addition, the InterfaceClass __init__ method will be called when used as a base class; Python basically treats base classes as metaclasses, and a new instance of the base class's class (metaclass) will be created whenever we use it in a class definition. This means that the __init__ method will be passed the new __name__ and __bases__ values, as well as all the new class attributes as keyword arguments (including __module__ and an optional __doc__).
This is all documented in the Standard type hierarchy section of the Python Data Model document (look for the 'classes' paragraph on special attributes), and in the same document, in the Customizing class creation section (base classes with a __class__ attribute are deemed a type).
So, any python instance that defines at least __module__, __name__ and __bases__ attributes, and a suitable __init__ method will work as a base class for other classes. Python does the rest.
why if I do:
class C(): pass
type(C())
I got: <type 'instance'>, but if I do:
class C(object): pass
type(c())
I got: <class '__main__.c'> ?
The first is not very userfull
Look up the difference between old-style and new-style classes. The former are the default, and the latter inherit explicitly from object.
All old-style objects were implemented with the built-in type instance. The fact that they are still the default and their type remains 'instance' is a result of retro-compatibility precautions.
This is extracted from the Python docs (http://docs.python.org/reference/datamodel.html)
3.3. New-style and classic classes Classes and instances come in two
flavors: old-style (or classic) and
new-style.
Up to Python 2.1, old-style classes
were the only flavour available to the
user. The concept of (old-style) class
is unrelated to the concept of type:
if x is an instance of an old-style
class, then x.class designates the
class of x, but type(x) is always
. This reflects the
fact that all old-style instances,
independently of their class, are
implemented with a single built-in
type, called instance.
New-style classes were introduced in
Python 2.2 to unify classes and types.
A new-style class is neither more nor
less than a user-defined type. If x is
an instance of a new-style class, then
type(x) is typically the same as
x> .class (although this is not
guaranteed - a new-style class
instance is permitted to override the
value returned for x.class).
The major motivation for introducing
new-style classes is to provide a
unified object model with a full
meta-model. It also has a number of
practical benefits, like the ability
to subclass most built-in types, or
the introduction of “descriptors”,
which enable computed properties.
For compatibility reasons, classes are
still old-style by default. New-style
classes are created by specifying
another new-style class (i.e. a type)
as a parent class, or the “top-level
type” object if no other parent is
needed. The behaviour of new-style
classes differs from that of old-style
classes in a number of important
details in addition to what type()
returns. Some of these changes are
fundamental to the new object model,
like the way special methods are
invoked. Others are “fixes” that could
not be implemented before for
compatibility concerns, like the
method resolution order in case of
multiple inheritance.
While this manual aims to provide
comprehensive coverage of Python’s
class mechanics, it may still be
lacking in some areas when it comes to
its coverage of new-style classes.
Please see
http://www.python.org/doc/newstyle/
for sources of additional information.
Old-style classes are removed in
Python 3.0, leaving only the semantics
of new-style classes.of new-style classes.
I know class foo(object) is an old school way of defining a class. But I would like to understand in more detail the difference between these two.
Prior to python 2.2 there were essentially two different types of class: Those defined by C extensions and C coded builtins (types) and those defined by python class statements (classes). This led to problems when you wanted to mix python-types and builtin types. The most common reason for this is subclassing. If you wanted to subclass the list type in python code, you were out of luck, and so various workarounds were used instead, such as subclassing the pure python implementation of lists (in the UserList module) instead.
This was a fairly ugly, so in 2.2 there was a move to unify python and builtin types, including the ability to inherit from them. The result is "new style classes". These do have some incompatible differences to old-style classes however, so for backward compatability the bare class syntax creates an old-style class, while the new behaviour is obtained by inheriting from object. The most visible behaviour differences are:
The method resolution order (MRO). There is a difference in behaviour in diamond-shaped inheritance hierarchies (where A inherits from both B and C, which both inherit from a common base class D. Previously, methods were looked up left-to right, depth first (ie A B D C D) However if C overloads a member of D, it won't be used by A (as it finds D's implementation first) This is bad for various styles of programming (eg. using mixin classes). New style classes will treat this situation as A B C D, (look at the __mro__ attribute of a class to see the order it will search)
The __new__ constructor is added, which allows the class to act as a factory method, rather than return a new instance of the class. Useful for returning particular subclasses, or reusing immutable objects rather than creating new ones without having to change the creation interface.
Descriptors. These are the feature behind such things as properties, classmethods, staticmethods etc. Essentially, they provide a way to control what happens when you access or set a particular attribute on a (new style) class.
class foo(object): is the 'new' way of declaring classes.
This change was made in python 2.2, see this PEP for an explanation of the differences.
Subclassing object yields a new-style class. Two well known advantages of new-style classes are:
Metaclasses (like class factories, but works transparently)
Properties (getters & setters...)
Referring to this
The object in class Foo(object) is meant to make your python 3 code compatible with python 2 and 3.
What is the difference between abstract class and interface in Python?
What you'll see sometimes is the following:
class Abstract1:
"""Some description that tells you it's abstract,
often listing the methods you're expected to supply."""
def aMethod(self):
raise NotImplementedError("Should have implemented this")
Because Python doesn't have (and doesn't need) a formal Interface contract, the Java-style distinction between abstraction and interface doesn't exist. If someone goes through the effort to define a formal interface, it will also be an abstract class. The only differences would be in the stated intent in the docstring.
And the difference between abstract and interface is a hairsplitting thing when you have duck typing.
Java uses interfaces because it doesn't have multiple inheritance.
Because Python has multiple inheritance, you may also see something like this
class SomeAbstraction:
pass # lots of stuff - but missing something
class Mixin1:
def something(self):
pass # one implementation
class Mixin2:
def something(self):
pass # another
class Concrete1(SomeAbstraction, Mixin1):
pass
class Concrete2(SomeAbstraction, Mixin2):
pass
This uses a kind of abstract superclass with mixins to create concrete subclasses that are disjoint.
What is the difference between abstract class and interface in Python?
An interface, for an object, is a set of methods and attributes on that object.
In Python, we can use an abstract base class to define and enforce an interface.
Using an Abstract Base Class
For example, say we want to use one of the abstract base classes from the collections module:
import collections
class MySet(collections.Set):
pass
If we try to use it, we get an TypeError because the class we created does not support the expected behavior of sets:
>>> MySet()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: Can't instantiate abstract class MySet with abstract methods
__contains__, __iter__, __len__
So we are required to implement at least __contains__, __iter__, and __len__. Let's use this implementation example from the documentation:
class ListBasedSet(collections.Set):
"""Alternate set implementation favoring space over speed
and not requiring the set elements to be hashable.
"""
def __init__(self, iterable):
self.elements = lst = []
for value in iterable:
if value not in lst:
lst.append(value)
def __iter__(self):
return iter(self.elements)
def __contains__(self, value):
return value in self.elements
def __len__(self):
return len(self.elements)
s1 = ListBasedSet('abcdef')
s2 = ListBasedSet('defghi')
overlap = s1 & s2
Implementation: Creating an Abstract Base Class
We can create our own Abstract Base Class by setting the metaclass to abc.ABCMeta and using the abc.abstractmethod decorator on relevant methods. The metaclass will be add the decorated functions to the __abstractmethods__ attribute, preventing instantiation until those are defined.
import abc
For example, "effable" is defined as something that can be expressed in words. Say we wanted to define an abstract base class that is effable, in Python 2:
class Effable(object):
__metaclass__ = abc.ABCMeta
#abc.abstractmethod
def __str__(self):
raise NotImplementedError('users must define __str__ to use this base class')
Or in Python 3, with the slight change in metaclass declaration:
class Effable(object, metaclass=abc.ABCMeta):
#abc.abstractmethod
def __str__(self):
raise NotImplementedError('users must define __str__ to use this base class')
Now if we try to create an effable object without implementing the interface:
class MyEffable(Effable):
pass
and attempt to instantiate it:
>>> MyEffable()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: Can't instantiate abstract class MyEffable with abstract methods __str__
We are told that we haven't finished the job.
Now if we comply by providing the expected interface:
class MyEffable(Effable):
def __str__(self):
return 'expressable!'
we are then able to use the concrete version of the class derived from the abstract one:
>>> me = MyEffable()
>>> print(me)
expressable!
There are other things we could do with this, like register virtual subclasses that already implement these interfaces, but I think that is beyond the scope of this question. The other methods demonstrated here would have to adapt this method using the abc module to do so, however.
Conclusion
We have demonstrated that the creation of an Abstract Base Class defines interfaces for custom objects in Python.
Python >= 2.6 has Abstract Base Classes.
Abstract Base Classes (abbreviated
ABCs) complement duck-typing by
providing a way to define interfaces
when other techniques like hasattr()
would be clumsy. Python comes with
many builtin ABCs for data structures
(in the collections module), numbers
(in the numbers module), and streams
(in the io module). You can create
your own ABC with the abc module.
There is also the Zope Interface module, which is used by projects outside of zope, like twisted. I'm not really familiar with it, but there's a wiki page here that might help.
In general, you don't need the concept of abstract classes, or interfaces in python (edited - see S.Lott's answer for details).
In a more basic way to explain:
An interface is sort of like an empty muffin pan.
It's a class file with a set of method definitions that have no code.
An abstract class is the same thing, but not all functions need to be empty. Some can have code. It's not strictly empty.
Why differentiate:
There's not much practical difference in Python, but on the planning level for a large project, it could be more common to talk about interfaces, since there's no code. Especially if you're working with Java programmers who are accustomed to the term.
Python doesn't really have either concept.
It uses duck typing, which removed the need for interfaces (at least for the computer :-))
Python <= 2.5:
Base classes obviously exist, but there is no explicit way to mark a method as 'pure virtual', so the class isn't really abstract.
Python >= 2.6:
Abstract base classes do exist (http://docs.python.org/library/abc.html). And allow you to specify methods that must be implemented in subclasses. I don't much like the syntax, but the feature is there. Most of the time it's probably better to use duck typing from the 'using' client side.
In general, interfaces are used only in languages that use the single-inheritance class model. In these single-inheritance languages, interfaces are typically used if any class could use a particular method or set of methods. Also in these single-inheritance languages, abstract classes are used to either have defined class variables in addition to none or more methods, or to exploit the single-inheritance model to limit the range of classes that could use a set of methods.
Languages that support the multiple-inheritance model tend to use only classes or abstract base classes and not interfaces. Since Python supports multiple inheritance, it does not use interfaces and you would want to use base classes or abstract base classes.
http://docs.python.org/library/abc.html
Abstract classes are classes that contain one or more abstract methods. Along with abstract methods, Abstract classes can have static, class and instance methods.
But in case of interface, it will only have abstract methods not other. Hence it is not compulsory to inherit abstract class but it is compulsory to inherit interface.
For completeness, we should mention PEP3119
where ABC was introduced and compared with interfaces,
and original Talin's comment.
The abstract class is not perfect interface:
belongs to the inheritance hierarchy
is mutable
But if you consider writing it your own way:
def some_function(self):
raise NotImplementedError()
interface = type(
'your_interface', (object,),
{'extra_func': some_function,
'__slots__': ['extra_func', ...]
...
'__instancecheck__': your_instance_checker,
'__subclasscheck__': your_subclass_checker
...
}
)
ok, rather as a class
or as a metaclass
and fighting with python to achieve the immutable object
and doing refactoring
...
you'll quite fast realize that you're inventing the wheel
to eventually achieve
abc.ABCMeta
abc.ABCMeta was proposed as a useful addition of the missing interface functionality,
and that's fair enough in a language like python.
Certainly, it was able to be enhanced better whilst writing version 3, and adding new syntax and immutable interface concept ...
Conclusion:
The abc.ABCMeta IS "pythonic" interface in python