Instance of Python class that responds to all method calls - python

Is there a way to create a class which instances respond to arbitrary method calls?
I know there is a the special method __getattr__(self, attr) which would be called when someone is trying to access an attribute of an instance. I am searching for something similar that enables me to intercept method calls, too. The desired behavior would look something like this:
class A(object):
def __methodintercept__(self, method, *args, **kwargs): # is there a special method like this??
print(str(method))
>>> a = A()
>>> a.foomatic()
foomatic
EDIT
The other suggested questions do not address my case: I do not want to wrap another class or change the metaclass of a second class or similar. I just want to have a class that responds to arbitrary method calls.
Thanks to jonrshape I now know that __getattr__(self, attr) will also be called when a method is called in the same way as it would be when an attribute is accessed. But how do i distinguish in __getattr__ if attr comes from a method call or an attribute access and how to get the parameters of a potential method call?

This is something I came up with, which will behave exactly as if the method exists.
First let's establish one thing: You cannot distinguish in __getattr__ if attr comes from a function call or an "attribute access", because a class method is an attribute of your class. So someone can access that method even if they don't intend to call it, as in:
class Test:
def method(self):
print "Hi, I am method"
>> t = Test()
>> t.method # just access the method "as an attribute"
<bound method Test.method of <__main__.Test instance at 0x10a970c68>>
>> t.method() # actually call the method
Hi, I am method
Therefore, the closest thing I could think of is this behavior:
Create a class A, such that:
When we try to access an attribute / method, which already exists in that class, act normal and just return the requested attribute / method.
When we try to access something that doesn't exist in the class definition, treat it as a class method and have 1 global handler for all such methods.
I will first write the class definition and then show how accessing a method that doesn't exist behaves exactly like accessing one that exists, whether you are just accessing it, or actually calling it.
Class definition:
class A(object):
def __init__(self):
self.x = 1 # set some attribute
def __getattr__(self,attr):
try:
return super(A, self).__getattr__(attr)
except AttributeError:
return self.__get_global_handler(attr)
def __get_global_handler(self, name):
# Do anything that you need to do before simulating the method call
handler = self.__global_handler
handler.im_func.func_name = name # Change the method's name
return handler
def __global_handler(self, *args, **kwargs):
# Do something with these arguments
print "I am an imaginary method with name %s" % self.__global_handler.im_func.func_name
print "My arguments are: " + str(args)
print "My keyword arguments are: " + str(kwargs)
def real_method(self, *args, **kwargs):
print "I am a method that you actually defined"
print "My name is %s" % self.real_method.im_func.func_name
print "My arguments are: " + str(args)
print "My keyword arguments are: " + str(kwargs)
I added the method real_method just so I have something that actually exists in the class to compare its behavior with that of an 'imaginary method'
Here's the result:
>> a = A()
>> # First let's try simple access (no method call)
>> a.real_method # The method that is actually defined in the class
<bound method A.real_method of <test.A object at 0x10a9784d0>>
>> a.imaginary_method # Some method that is not defined
<bound method A.imaginary_method of <test.A object at 0x10a9784d0>>
>> # Now let's try to call each of these methods
>> a.real_method(1, 2, x=3, y=4)
I am a method that you actually defined
My name is real_method
My arguments are: (1, 2)
My keyword arguments are: {'y': 4, 'x': 3}
>> a.imaginary_method(1, 2, x=3, y=4)
I am an imaginary method with name imaginary_method
My arguments are: (1, 2)
My keyword arguments are: {'y': 4, 'x': 3}
>> # Now let's try to access the x attribute, just to make sure that 'regular' attribute access works fine as well
>> a.x
1

unittest.mock.Mock does this by default.
from unittest.mock import Mock
a = Mock()
a.arbitrary_method() # No error
a.arbitrary_method.called # True
a.new_method
a.new_method.called # False
a.new_method("some", "args")
a.new_method.called # True
a.new_method.assert_called_with("some", "args") # No error
a.new_method_assert_called_with("other", "args") # AssertionError

This is the solution I was looking for when coming across this question:
class Wrapper:
def __init__(self):
self._inner = [] # or whatever type you want to wrap
def foo(self, x):
print(x)
def __getattr__(self, attr):
if attr in self.__class__.__dict__:
return getattr(self, attr)
else:
return getattr(self._inner, attr)
t = Test()
t.foo('abc') # prints 'abc'
t.append('x') # appends 'x' to t._inner
Criticisms very welcome. I wanted to add methods to the Browser class in the Splinter package, but it only exposes a function to return an instance, not the class itself. This approach permitted pseudo-inheritance, which meant I could declaratively decouple DOM code from website-specific code. (A better approach in hindsight might have been to use Selenium directly.)

Method calls aren't any different from attribute access. __getattr__() or __getattribute__() is the way to respond to arbitrary attribute requests.
You cannot know if the access comes from "just retrieval" or "method call".
It works like this: first, attribute retrieval, then, call on the retrieved object (in Python, call is just another operator: anything can be called and will throw an exception if it isn't callable). One doesn't, and shouldn't, know about the other (well, you can analyze the code up the call stack, but that's totally not the thing to do here).
One of the reasons is - functions are first-class objects in Python, i.e. a function (or, rather, a reference to it) is no different from any other data type: I can get the reference, save it and pass it around. I.e. there's completely no difference between requesting a data field and a method.
Elaborate on what you need this for for us to suggest a better solution.
E.g., if you need the "method" to be able to be called with different signatures, *args and **kwargs is the way to go.

The follow will respond to all undefined method calls:
class Mock:
def __init__(self, *args, **kwargs):
pass
def __getattr__(self, attr):
def func(*args, **kwargs):
pass
return func
Or just use unittest.mock.Mock.

Related

Deciding to use class itself or class method [duplicate]

What is the difference between a method decorated with #staticmethod and one decorated with #classmethod?
Maybe a bit of example code will help: Notice the difference in the call signatures of foo, class_foo and static_foo:
class A(object):
def foo(self, x):
print(f"executing foo({self}, {x})")
#classmethod
def class_foo(cls, x):
print(f"executing class_foo({cls}, {x})")
#staticmethod
def static_foo(x):
print(f"executing static_foo({x})")
a = A()
Below is the usual way an object instance calls a method. The object instance, a, is implicitly passed as the first argument.
a.foo(1)
# executing foo(<__main__.A object at 0xb7dbef0c>, 1)
With classmethods, the class of the object instance is implicitly passed as the first argument instead of self.
a.class_foo(1)
# executing class_foo(<class '__main__.A'>, 1)
You can also call class_foo using the class. In fact, if you define something to be
a classmethod, it is probably because you intend to call it from the class rather than from a class instance. A.foo(1) would have raised a TypeError, but A.class_foo(1) works just fine:
A.class_foo(1)
# executing class_foo(<class '__main__.A'>, 1)
One use people have found for class methods is to create inheritable alternative constructors.
With staticmethods, neither self (the object instance) nor cls (the class) is implicitly passed as the first argument. They behave like plain functions except that you can call them from an instance or the class:
a.static_foo(1)
# executing static_foo(1)
A.static_foo('hi')
# executing static_foo(hi)
Staticmethods are used to group functions which have some logical connection with a class to the class.
foo is just a function, but when you call a.foo you don't just get the function,
you get a "partially applied" version of the function with the object instance a bound as the first argument to the function. foo expects 2 arguments, while a.foo only expects 1 argument.
a is bound to foo. That is what is meant by the term "bound" below:
print(a.foo)
# <bound method A.foo of <__main__.A object at 0xb7d52f0c>>
With a.class_foo, a is not bound to class_foo, rather the class A is bound to class_foo.
print(a.class_foo)
# <bound method type.class_foo of <class '__main__.A'>>
Here, with a staticmethod, even though it is a method, a.static_foo just returns
a good 'ole function with no arguments bound. static_foo expects 1 argument, and
a.static_foo expects 1 argument too.
print(a.static_foo)
# <function static_foo at 0xb7d479cc>
And of course the same thing happens when you call static_foo with the class A instead.
print(A.static_foo)
# <function static_foo at 0xb7d479cc>
A staticmethod is a method that knows nothing about the class or instance it was called on. It just gets the arguments that were passed, no implicit first argument. It is basically useless in Python -- you can just use a module function instead of a staticmethod.
A classmethod, on the other hand, is a method that gets passed the class it was called on, or the class of the instance it was called on, as first argument. This is useful when you want the method to be a factory for the class: since it gets the actual class it was called on as first argument, you can always instantiate the right class, even when subclasses are involved. Observe for instance how dict.fromkeys(), a classmethod, returns an instance of the subclass when called on a subclass:
>>> class DictSubclass(dict):
... def __repr__(self):
... return "DictSubclass"
...
>>> dict.fromkeys("abc")
{'a': None, 'c': None, 'b': None}
>>> DictSubclass.fromkeys("abc")
DictSubclass
>>>
Basically #classmethod makes a method whose first argument is the class it's called from (rather than the class instance), #staticmethod does not have any implicit arguments.
To decide whether to use #staticmethod or #classmethod you have to look inside your method. If your method accesses other variables/methods in your class then use #classmethod. On the other hand, if your method does not touches any other parts of the class then use #staticmethod.
class Apple:
_counter = 0
#staticmethod
def about_apple():
print('Apple is good for you.')
# note you can still access other member of the class
# but you have to use the class instance
# which is not very nice, because you have repeat yourself
#
# For example:
# #staticmethod
# print('Number of apples have been juiced: %s' % Apple._counter)
#
# #classmethod
# print('Number of apples have been juiced: %s' % cls._counter)
#
# #classmethod is especially useful when you move your function to another class,
# you don't have to rename the referenced class
#classmethod
def make_apple_juice(cls, number_of_apples):
print('Making juice:')
for i in range(number_of_apples):
cls._juice_this(i)
#classmethod
def _juice_this(cls, apple):
print('Juicing apple %d...' % apple)
cls._counter += 1
Official python docs:
#classmethod
A class method receives the class as
implicit first argument, just like an
instance method receives the instance.
To declare a class method, use this
idiom:
class C:
#classmethod
def f(cls, arg1, arg2, ...): ...
The #classmethod form is a function
decorator – see the description of
function definitions in Function
definitions for details.
It can be called either on the class
(such as C.f()) or on an instance
(such as C().f()). The instance is
ignored except for its class. If a
class method is called for a derived
class, the derived class object is
passed as the implied first argument.
Class methods are different than C++
or Java static methods. If you want
those, see staticmethod() in this
section.
#staticmethod
A static method does not receive an
implicit first argument. To declare a
static method, use this idiom:
class C:
#staticmethod
def f(arg1, arg2, ...): ...
The #staticmethod form is a function
decorator – see the description of
function definitions in Function
definitions for details.
It can be called either on the class
(such as C.f()) or on an instance
(such as C().f()). The instance is
ignored except for its class.
Static methods in Python are similar
to those found in Java or C++. For a
more advanced concept, see
classmethod() in this section.
Here is a short article on this question
#staticmethod function is nothing more than a function defined inside a class. It is callable without instantiating the class first. It’s definition is immutable via inheritance.
#classmethod function also callable without instantiating the class, but its definition follows Sub class, not Parent class, via inheritance. That’s because the first argument for #classmethod function must always be cls (class).
What is the difference between #staticmethod and #classmethod in Python?
You may have seen Python code like this pseudocode, which demonstrates the signatures of the various method types and provides a docstring to explain each:
class Foo(object):
def a_normal_instance_method(self, arg_1, kwarg_2=None):
'''
Return a value that is a function of the instance with its
attributes, and other arguments such as arg_1 and kwarg2
'''
#staticmethod
def a_static_method(arg_0):
'''
Return a value that is a function of arg_0. It does not know the
instance or class it is called from.
'''
#classmethod
def a_class_method(cls, arg1):
'''
Return a value that is a function of the class and other arguments.
respects subclassing, it is called with the class it is called from.
'''
The Normal Instance Method
First I'll explain a_normal_instance_method. This is precisely called an "instance method". When an instance method is used, it is used as a partial function (as opposed to a total function, defined for all values when viewed in source code) that is, when used, the first of the arguments is predefined as the instance of the object, with all of its given attributes. It has the instance of the object bound to it, and it must be called from an instance of the object. Typically, it will access various attributes of the instance.
For example, this is an instance of a string:
', '
if we use the instance method, join on this string, to join another iterable,
it quite obviously is a function of the instance, in addition to being a function of the iterable list, ['a', 'b', 'c']:
>>> ', '.join(['a', 'b', 'c'])
'a, b, c'
Bound methods
Instance methods can be bound via a dotted lookup for use later.
For example, this binds the str.join method to the ':' instance:
>>> join_with_colons = ':'.join
And later we can use this as a function that already has the first argument bound to it. In this way, it works like a partial function on the instance:
>>> join_with_colons('abcde')
'a:b:c:d:e'
>>> join_with_colons(['FF', 'FF', 'FF', 'FF', 'FF', 'FF'])
'FF:FF:FF:FF:FF:FF'
Static Method
The static method does not take the instance as an argument.
It is very similar to a module level function.
However, a module level function must live in the module and be specially imported to other places where it is used.
If it is attached to the object, however, it will follow the object conveniently through importing and inheritance as well.
An example of a static method is str.maketrans, moved from the string module in Python 3. It makes a translation table suitable for consumption by str.translate. It does seem rather silly when used from an instance of a string, as demonstrated below, but importing the function from the string module is rather clumsy, and it's nice to be able to call it from the class, as in str.maketrans
# demonstrate same function whether called from instance or not:
>>> ', '.maketrans('ABC', 'abc')
{65: 97, 66: 98, 67: 99}
>>> str.maketrans('ABC', 'abc')
{65: 97, 66: 98, 67: 99}
In python 2, you have to import this function from the increasingly less useful string module:
>>> import string
>>> 'ABCDEFG'.translate(string.maketrans('ABC', 'abc'))
'abcDEFG'
Class Method
A class method is a similar to an instance method in that it takes an implicit first argument, but instead of taking the instance, it takes the class. Frequently these are used as alternative constructors for better semantic usage and it will support inheritance.
The most canonical example of a builtin classmethod is dict.fromkeys. It is used as an alternative constructor of dict, (well suited for when you know what your keys are and want a default value for them.)
>>> dict.fromkeys(['a', 'b', 'c'])
{'c': None, 'b': None, 'a': None}
When we subclass dict, we can use the same constructor, which creates an instance of the subclass.
>>> class MyDict(dict): 'A dict subclass, use to demo classmethods'
>>> md = MyDict.fromkeys(['a', 'b', 'c'])
>>> md
{'a': None, 'c': None, 'b': None}
>>> type(md)
<class '__main__.MyDict'>
See the pandas source code for other similar examples of alternative constructors, and see also the official Python documentation on classmethod and staticmethod.
I started learning programming language with C++ and then Java and then Python and so this question bothered me a lot as well, until I understood the simple usage of each.
Class Method: Python unlike Java and C++ doesn't have constructor overloading. And so to achieve this you could use classmethod. Following example will explain this
Let's consider we have a Person class which takes two arguments first_name and last_name and creates the instance of Person.
class Person(object):
def __init__(self, first_name, last_name):
self.first_name = first_name
self.last_name = last_name
Now, if the requirement comes where you need to create a class using a single name only, just a first_name, you can't do something like this in Python.
This will give you an error when you will try to create an object (instance).
class Person(object):
def __init__(self, first_name, last_name):
self.first_name = first_name
self.last_name = last_name
def __init__(self, first_name):
self.first_name = first_name
However, you could achieve the same thing using #classmethod as mentioned below
class Person(object):
def __init__(self, first_name, last_name):
self.first_name = first_name
self.last_name = last_name
#classmethod
def get_person(cls, first_name):
return cls(first_name, "")
Static Method: This is rather simple, it's not bound to instance or class and you can simply call that using class name.
So let's say in above example you need a validation that first_name should not exceed 20 characters, you can simply do this.
#staticmethod
def validate_name(name):
return len(name) <= 20
and you could simply call using class name
Person.validate_name("Gaurang Shah")
Only the first argument differs:
normal method: the current object is automatically passed as an (additional) first argument
classmethod: the class of the current object is automatically passed as an (additional) fist argument
staticmethod: no extra arguments are automatically passed. What you passed to the function is what you get.
In more detail...
normal method
The "standard" method, as in every object oriented language. When an object's method is called, it is automatically given an extra argument self as its first argument. That is, method
def f(self, x, y)
must be called with 2 arguments. self is automatically passed, and it is the object itself. Similar to the this that magically appears in eg. java/c++, only in python it is shown explicitly.
actually, the first argument does not have to be called self, but it's the standard convention, so keep it
class method
When the method is decorated
#classmethod
def f(cls, x, y)
the automatically provided argument is not self, but the class of self.
static method
When the method is decorated
#staticmethod
def f(x, y)
the method is not given any automatic argument at all. It is only given the parameters that it is called with.
usages
classmethod is mostly used for alternative constructors.
staticmethod does not use the state of the object, or even the structure of the class itself. It could be a function external to a class. It only put inside the class for grouping functions with similar functionality (for example, like Java's Math class static methods)
class Point
def __init__(self, x, y):
self.x = x
self.y = y
#classmethod
def frompolar(cls, radius, angle):
"""The `cls` argument is the `Point` class itself"""
return cls(radius * cos(angle), radius * sin(angle))
#staticmethod
def angle(x, y):
"""this could be outside the class, but we put it here
just because we think it is logically related to the class."""
return atan(y, x)
p1 = Point(3, 2)
p2 = Point.frompolar(3, pi/4)
angle = Point.angle(3, 2)
I think a better question is "When would you use #classmethod vs #staticmethod?"
#classmethod allows you easy access to private members that are associated to the class definition. this is a great way to do singletons, or factory classes that control the number of instances of the created objects exist.
#staticmethod provides marginal performance gains, but I have yet to see a productive use of a static method within a class that couldn't be achieved as a standalone function outside the class.
Static Methods:
Simple functions with no self argument.
Work on class attributes; not on instance attributes.
Can be called through both class and instance.
The built-in function staticmethod()is used to create them.
Benefits of Static Methods:
It localizes the function name in the classscope
It moves the function code closer to where it is used
More convenient to import versus module-level functions since each method does not have to be specially imported
#staticmethod
def some_static_method(*args, **kwds):
pass
Class Methods:
Functions that have first argument as classname.
Can be called through both class and instance.
These are created with classmethod in-built function.
#classmethod
def some_class_method(cls, *args, **kwds):
pass
#decorators were added in python 2.4 If you're using python < 2.4 you can use the classmethod() and staticmethod() function.
For example, if you want to create a factory method (A function returning an instance of a different implementation of a class depending on what argument it gets) you can do something like:
class Cluster(object):
def _is_cluster_for(cls, name):
"""
see if this class is the cluster with this name
this is a classmethod
"""
return cls.__name__ == name
_is_cluster_for = classmethod(_is_cluster_for)
#static method
def getCluster(name):
"""
static factory method, should be in Cluster class
returns a cluster object for the given name
"""
for cls in Cluster.__subclasses__():
if cls._is_cluster_for(name):
return cls()
getCluster = staticmethod(getCluster)
Also observe that this is a good example for using a classmethod and a static method,
The static method clearly belongs to the class, since it uses the class Cluster internally.
The classmethod only needs information about the class, and no instance of the object.
Another benefit of making the _is_cluster_for method a classmethod is so a subclass can decide to change it's implementation, maybe because it is pretty generic and can handle more than one type of cluster, so just checking the name of the class would not be enough.
Let me tell the similarity between a method decorated with #classmethod vs #staticmethod first.
Similarity: Both of them can be called on the Class itself, rather than just the instance of the class. So, both of them in a sense are Class's methods.
Difference: A classmethod will receive the class itself as the first argument, while a staticmethod does not.
So a static method is, in a sense, not bound to the Class itself and is just hanging in there just because it may have a related functionality.
>>> class Klaus:
#classmethod
def classmthd(*args):
return args
#staticmethod
def staticmthd(*args):
return args
# 1. Call classmethod without any arg
>>> Klaus.classmthd()
(__main__.Klaus,) # the class gets passed as the first argument
# 2. Call classmethod with 1 arg
>>> Klaus.classmthd('chumma')
(__main__.Klaus, 'chumma')
# 3. Call staticmethod without any arg
>>> Klaus.staticmthd()
()
# 4. Call staticmethod with 1 arg
>>> Klaus.staticmthd('chumma')
('chumma',)
#staticmethod just disables the default function as method descriptor. classmethod wraps your function in a container callable that passes a reference to the owning class as first argument:
>>> class C(object):
... pass
...
>>> def f():
... pass
...
>>> staticmethod(f).__get__(None, C)
<function f at 0x5c1cf0>
>>> classmethod(f).__get__(None, C)
<bound method type.f of <class '__main__.C'>>
As a matter of fact, classmethod has a runtime overhead but makes it possible to access the owning class. Alternatively I recommend using a metaclass and putting the class methods on that metaclass:
>>> class CMeta(type):
... def foo(cls):
... print cls
...
>>> class C(object):
... __metaclass__ = CMeta
...
>>> C.foo()
<class '__main__.C'>
Another consideration with respect to staticmethod vs classmethod comes up with inheritance. Say you have the following class:
class Foo(object):
#staticmethod
def bar():
return "In Foo"
And you then want to override bar() in a child class:
class Foo2(Foo):
#staticmethod
def bar():
return "In Foo2"
This works, but note that now the bar() implementation in the child class (Foo2) can no longer take advantage of anything specific to that class. For example, say Foo2 had a method called magic() that you want to use in the Foo2 implementation of bar():
class Foo2(Foo):
#staticmethod
def bar():
return "In Foo2"
#staticmethod
def magic():
return "Something useful you'd like to use in bar, but now can't"
The workaround here would be to call Foo2.magic() in bar(), but then you're repeating yourself (if the name of Foo2 changes, you'll have to remember to update that bar() method).
To me, this is a slight violation of the open/closed principle, since a decision made in Foo is impacting your ability to refactor common code in a derived class (ie it's less open to extension). If bar() were a classmethod we'd be fine:
class Foo(object):
#classmethod
def bar(cls):
return "In Foo"
class Foo2(Foo):
#classmethod
def bar(cls):
return "In Foo2 " + cls.magic()
#classmethod
def magic(cls):
return "MAGIC"
print Foo2().bar()
Gives: In Foo2 MAGIC
Also: historical note: Guido Van Rossum (Python's creator) once referred to staticmethod's as "an accident": https://mail.python.org/pipermail/python-ideas/2012-May/014969.html
we all know how limited static methods are. (They're basically an accident -- back in the Python 2.2 days when I was inventing new-style classes and descriptors, I meant to implement class methods but at first I didn't understand them and accidentally implemented static methods first. Then it was too late to remove them and only provide class methods.
Also: https://mail.python.org/pipermail/python-ideas/2016-July/041189.html
Honestly, staticmethod was something of a mistake -- I was trying to do something like Java class methods but once it was released I found what was really needed was classmethod. But it was too late to get rid of staticmethod.
The definitive guide on how to use static, class or abstract methods in Python is one good link for this topic, and summary it as following.
#staticmethod function is nothing more than a function defined inside a class. It is callable without instantiating the class first. It’s definition is immutable via inheritance.
Python does not have to instantiate a bound-method for object.
It eases the readability of the code, and it does not depend on the state of object itself;
#classmethod function also callable without instantiating the class, but its definition follows Sub class, not Parent class, via inheritance, can be overridden by subclass. That’s because the first argument for #classmethod function must always be cls (class).
Factory methods, that are used to create an instance for a class using for example some sort of pre-processing.
Static methods calling static methods: if you split a static methods in several static methods, you shouldn't hard-code the class name but use class methods
I will try to explain the basic difference using an example.
class A(object):
x = 0
def say_hi(self):
pass
#staticmethod
def say_hi_static():
pass
#classmethod
def say_hi_class(cls):
pass
def run_self(self):
self.x += 1
print self.x # outputs 1
self.say_hi()
self.say_hi_static()
self.say_hi_class()
#staticmethod
def run_static():
print A.x # outputs 0
# A.say_hi() # wrong
A.say_hi_static()
A.say_hi_class()
#classmethod
def run_class(cls):
print cls.x # outputs 0
# cls.say_hi() # wrong
cls.say_hi_static()
cls.say_hi_class()
1 - we can directly call static and classmethods without initializing
# A.run_self() # wrong
A.run_static()
A.run_class()
2- Static method cannot call self method but can call other static and classmethod
3- Static method belong to class and will not use object at all.
4- Class method are not bound to an object but to a class.
The difference occurs when there is inheritance.
Suppose that there are two classes-- Parent and Child. If one wants to use #staticmethod, print_name method should be written twice because the name of the class should be written in the print line.
class Parent:
_class_name = "Parent"
#staticmethod
def print_name():
print(Parent._class_name)
class Child(Parent):
_class_name = "Child"
#staticmethod
def print_name():
print(Child._class_name)
Parent.print_name()
Child.print_name()
However, for #classmethod, it is not required to write print_name method twice.
class Parent:
_class_name = "Parent"
#classmethod
def print_name(cls):
print(cls._class_name)
class Child(Parent):
_class_name = "Child"
Parent.print_name()
Child.print_name()
Python comes with several built-in decorators. The big three are:
#classmethod
#staticmethod
#property
First let's note that any function of a class can be called with instance of this class (after we initialized this class).
#classmethod is the way to call function not only as an instance of a class but also directly by the class itself as its first argument.
#staticmethod is a way of putting a function into a class (because it logically belongs there), while indicating that it does not require access to the class (so we don't need to use self in function definition).
Let's consider the following class:
class DecoratorTest(object):
def __init__(self):
pass
def doubler(self, x):
return x*2
#classmethod
def class_doubler(cls, x): # we need to use 'cls' instead of 'self'; 'cls' reference to the class instead of an instance of the class
return x*2
#staticmethod
def static_doubler(x): # no need adding 'self' here; static_doubler() could be just a function not inside the class
return x*2
Let's see how it works:
decor = DecoratorTest()
print(decor.doubler(5))
# 10
print(decor.class_doubler(5)) # a call with an instance of a class
# 10
print(DecoratorTest.class_doubler(5)) # a direct call by the class itself
# 10
# staticmethod could be called in the same way as classmethod.
print(decor.static_doubler(5)) # as an instance of the class
# 10
print(DecoratorTest.static_doubler(5)) # or as a direct call
# 10
Here you can see some use cases for those methods.
Bonus: you can read about #property decorator here
Instance Method:
+ Can modify object instance state
+ Can modify class state
Class Method:
- Can't modify object instance state
+ Can modify class state
Static Method:
- Can't modify object instance state
- Can't modify class state
class MyClass:
'''
Instance method has a mandatory first attribute self which represent the instance itself.
Instance method must be called by a instantiated instance.
'''
def method(self):
return 'instance method called', self
'''
Class method has a mandatory first attribute cls which represent the class itself.
Class method can be called by an instance or by the class directly.
Its most common using scenario is to define a factory method.
'''
#classmethod
def class_method(cls):
return 'class method called', cls
'''
Static method doesn’t have any attributes of instances or the class.
It also can be called by an instance or by the class directly.
Its most common using scenario is to define some helper or utility functions which are closely relative to the class.
'''
#staticmethod
def static_method():
return 'static method called'
obj = MyClass()
print(obj.method())
print(obj.class_method()) # MyClass.class_method()
print(obj.static_method()) # MyClass.static_method()
output:
('instance method called', <__main__.MyClass object at 0x100fb3940>)
('class method called', <class '__main__.MyClass'>)
static method called
The instance method we actually had access to the object instance , right so this was an instance off a my class object whereas with the class method we have access to the class itself. But not to any of the objects, because the class method doesn't really care about an object existing. However you can both call a class method and static method on an object instance. This is going to work it doesn't really make a difference, so again when you call static method here it's going to work and it's going to know which method you want to call.
The Static methods are used to do some utility tasks, and class methods are used for factory methods. The factory methods can return class objects for different use cases.
And finally, a short example for better understanding:
class Student:
def __init__(self, first_name, last_name):
self.first_name = first_name
self.last_name = last_name
#classmethod
def get_from_string(cls, name_string: str):
first_name, last_name = name_string.split()
if Student.validate_name(first_name) and Student.validate_name(last_name):
return cls(first_name, last_name)
else:
print('Invalid Names')
#staticmethod
def validate_name(name):
return len(name) <= 10
stackoverflow_student = Student.get_from_string('Name Surname')
print(stackoverflow_student.first_name) # Name
print(stackoverflow_student.last_name) # Surname
#classmethod : can be used to create a shared global access to all the instances created of that class..... like updating a record by multiple users....
I particulary found it use ful when creating singletons as well..:)
#static method: has nothing to do with the class or instance being associated with ...but for readability can use static method
My contribution demonstrates the difference amongst #classmethod, #staticmethod, and instance methods, including how an instance can indirectly call a #staticmethod. But instead of indirectly calling a #staticmethod from an instance, making it private may be more "pythonic." Getting something from a private method isn't demonstrated here but it's basically the same concept.
#!python3
from os import system
system('cls')
# % % % % % % % % % % % % % % % % % % % %
class DemoClass(object):
# instance methods need a class instance and
# can access the instance through 'self'
def instance_method_1(self):
return 'called from inside the instance_method_1()'
def instance_method_2(self):
# an instance outside the class indirectly calls the static_method
return self.static_method() + ' via instance_method_2()'
# class methods don't need a class instance, they can't access the
# instance (self) but they have access to the class itself via 'cls'
#classmethod
def class_method(cls):
return 'called from inside the class_method()'
# static methods don't have access to 'cls' or 'self', they work like
# regular functions but belong to the class' namespace
#staticmethod
def static_method():
return 'called from inside the static_method()'
# % % % % % % % % % % % % % % % % % % % %
# works even if the class hasn't been instantiated
print(DemoClass.class_method() + '\n')
''' called from inside the class_method() '''
# works even if the class hasn't been instantiated
print(DemoClass.static_method() + '\n')
''' called from inside the static_method() '''
# % % % % % % % % % % % % % % % % % % % %
# >>>>> all methods types can be called on a class instance <<<<<
# instantiate the class
democlassObj = DemoClass()
# call instance_method_1()
print(democlassObj.instance_method_1() + '\n')
''' called from inside the instance_method_1() '''
# # indirectly call static_method through instance_method_2(), there's really no use
# for this since a #staticmethod can be called whether the class has been
# instantiated or not
print(democlassObj.instance_method_2() + '\n')
''' called from inside the static_method() via instance_method_2() '''
# call class_method()
print(democlassObj.class_method() + '\n')
''' called from inside the class_method() '''
# call static_method()
print(democlassObj.static_method())
''' called from inside the static_method() '''
"""
# whether the class is instantiated or not, this doesn't work
print(DemoClass.instance_method_1() + '\n')
'''
TypeError: TypeError: unbound method instancemethod() must be called with
DemoClass instance as first argument (got nothing instead)
'''
"""
A class method receives the class as implicit first argument, just like an instance method receives the instance. It is a method which is bound to the class and not the object of the class.It has access to the state of the class as it takes a class parameter that points to the class and not the object instance. It can modify a class state that would apply across all the instances of the class. For example it can modify a class variable that will be applicable to all the instances.
On the other hand, a static method does not receive an implicit first argument, compared to class methods or instance methods. And can’t access or modify class state. It only belongs to the class because from design point of view that is the correct way. But in terms of functionality is not bound, at runtime, to the class.
as a guideline, use static methods as utilities, use class methods for example as factory . Or maybe to define a singleton. And use instance methods to model the state and behavior of instances.
Hope I was clear !
You might want to consider the difference between:
class A:
def foo(): # no self parameter, no decorator
pass
and
class B:
#staticmethod
def foo(): # no self parameter
pass
This has changed between python2 and python3:
python2:
>>> A.foo()
TypeError
>>> A().foo()
TypeError
>>> B.foo()
>>> B().foo()
python3:
>>> A.foo()
>>> A().foo()
TypeError
>>> B.foo()
>>> B().foo()
So using #staticmethod for methods only called directly from the class has become optional in python3. If you want to call them from both class and instance, you still need to use the #staticmethod decorator.
The other cases have been well covered by unutbus answer.
Class methods, as the name suggests, are used to make changes to classes and not the objects. To make changes to classes, they will modify the class attributes(not object attributes), since that is how you update classes.
This is the reason that class methods take the class(conventionally denoted by 'cls') as the first argument.
class A(object):
m=54
#classmethod
def class_method(cls):
print "m is %d" % cls.m
Static methods on the other hand, are used to perform functionalities that are not bound to the class i.e. they will not read or write class variables. Hence, static methods do not take classes as arguments. They are used so that classes can perform functionalities that are not directly related to the purpose of the class.
class X(object):
m=54 #will not be referenced
#staticmethod
def static_method():
print "Referencing/calling a variable or function outside this class. E.g. Some global variable/function."
I think giving a purely Python version of staticmethod and classmethod would help to understand the difference between them at language level (Refers to Descriptor Howto Guide).
Both of them are non-data descriptors (It would be easier to understand them if you are familiar with descriptors first).
class StaticMethod(object):
"Emulate PyStaticMethod_Type() in Objects/funcobject.c"
def __init__(self, f):
self.f = f
def __get__(self, obj, objtype=None):
return self.f
class ClassMethod(object):
"Emulate PyClassMethod_Type() in Objects/funcobject.c"
def __init__(self, f):
self.f = f
def __get__(self, obj, cls=None):
def inner(*args, **kwargs):
if cls is None:
cls = type(obj)
return self.f(cls, *args, **kwargs)
return inner
Analyze #staticmethod literally providing different insights.
A normal method of a class is an implicit dynamic method which takes the instance as first argument.
In contrast, a staticmethod does not take the instance as first argument, so is called 'static'.
A staticmethod is indeed such a normal function the same as those outside a class definition.
It is luckily grouped into the class just in order to stand closer where it is applied, or you might scroll around to find it.
One pretty important practical difference occurs when subclassing. If you don't mind, I'll hijack #unutbu's example:
class A:
def foo(self, x):
print("executing foo(%s, %s)" % (self, x))
#classmethod
def class_foo(cls, x):
print("executing class_foo(%s, %s)" % (cls, x))
#staticmethod
def static_foo(x):
print("executing static_foo(%s)" % x)
class B(A):
pass
In class_foo, the method knows which class it is called on:
A.class_foo(1)
# => executing class_foo(<class '__main__.A'>, 1)
B.class_foo(1)
# => executing class_foo(<class '__main__.B'>, 1)
In static_foo, there is no way to determine whether it is called on A or B:
A.static_foo(1)
# => executing static_foo(1)
B.static_foo(1)
# => executing static_foo(1)
Note that this doesn't mean you can't use other methods in a staticmethod, you just have to reference the class directly, which means subclasses' staticmethods will still reference the parent class:
class A:
#classmethod
def class_qux(cls, x):
print(f"executing class_qux({cls}, {x})")
#classmethod
def class_bar(cls, x):
cls.class_qux(x)
#staticmethod
def static_bar(x):
A.class_qux(x)
class B(A):
pass
A.class_bar(1)
# => executing class_qux(<class '__main__.A'>, 1)
B.class_bar(1)
# => executing class_qux(<class '__main__.B'>, 1)
A.static_bar(1)
# => executing class_qux(<class '__main__.A'>, 1)
B.static_bar(1)
# => executing class_qux(<class '__main__.A'>, 1)
tldr;
A staticmethod is essentially a function bound to a class (and consequently its instances)
A classmethod is essentially an inheritable staticmethod.
For details, see the excellent answers by others.
First let's start with an example code that we'll use to understand both concepts:
class Employee:
NO_OF_EMPLOYEES = 0
def __init__(self, first_name, last_name, salary):
self.first_name = first_name
self.last_name = last_name
self.salary = salary
self.increment_employees()
def give_raise(self, amount):
self.salary += amount
#classmethod
def employee_from_full_name(cls, full_name, salary):
split_name = full_name.split(' ')
first_name = split_name[0]
last_name = split_name[1]
return cls(first_name, last_name, salary)
#classmethod
def increment_employees(cls):
cls.NO_OF_EMPLOYEES += 1
#staticmethod
def get_employee_legal_obligations_txt():
legal_obligations = """
1. An employee must complete 8 hours per working day
2. ...
"""
return legal_obligations
Class method
A class method accepts the class itself as an implicit argument and -optionally- any other arguments specified in the definition. It’s important to understand that a class method, does not have access to object instances (like instance methods do). Therefore, class methods cannot be used to alter the state of an instantiated object but instead, they are capable of changing the class state which is shared amongst all the instances of that class.
Class methods are typically useful when we need to access the class itself — for example, when we want to create a factory method, that is a method that creates instances of the class. In other words, class methods can serve as alternative constructors.
In our example code, an instance of Employee can be constructed by providing three arguments; first_name , last_name and salary.
employee_1 = Employee('Andrew', 'Brown', 85000)
print(employee_1.first_name)
print(employee_1.salary)
'Andrew'
85000
Now let’s assume that there’s a chance that the name of an Employee can be provided in a single field in which the first and last names are separated by a whitespace. In this case, we could possibly use our class method called employee_from_full_name that accepts three arguments in total. The first one, is the class itself, which is an implicit argument which means that it won’t be provided when calling the method — Python will automatically do this for us:
employee_2 = Employee.employee_from_full_name('John Black', 95000)
print(employee_2.first_name)
print(employee_2.salary)
'John'
95000
Note that it is also possible to call employee_from_full_name from object instances although in this context it doesn’t make a lot of sense:
employee_1 = Employee('Andrew', 'Brown', 85000)
employee_2 = employee_1.employee_from_full_name('John Black', 95000)
Another reason why we might want to create a class method, is when we need to change the state of the class. In our example, the class variable NO_OF_EMPLOYEES keeps track of the number of employees currently working for the company. This method is called every time a new instance of Employee is created and it updates the count accordingly:
employee_1 = Employee('Andrew', 'Brown', 85000)
print(f'Number of employees: {Employee.NO_OF_EMPLOYEES}')
employee_2 = Employee.employee_from_full_name('John Black', 95000)
print(f'Number of employees: {Employee.NO_OF_EMPLOYEES}')
Number of employees: 1
Number of employees: 2
Static methods
On the other hand, in static methods neither the instance (i.e. self) nor the class itself (i.e. cls) is passed as an implicit argument. This means that such methods, are not capable of accessing the class itself or its instances.
Now one could argue that static methods are not useful in the context of classes as they can also be placed in helper modules instead of adding them as members of the class. In object oriented programming, it is important to structure your classes into logical chunks and thus, static methods are quite useful when we need to add a method under a class simply because it logically belongs to the class.
In our example, the static method named get_employee_legal_obligations_txt simply returns a string that contains the legal obligations of every single employee of a company. This function, does not interact with the class itself nor with any instance. It could have been placed into a different helper module however, it is only relevant to this class and therefore we have to place it under the Employee class.
A static method can be access directly from the class itself
print(Employee.get_employee_legal_obligations_txt())
1. An employee must complete 8 hours per working day
2. ...
or from an instance of the class:
employee_1 = Employee('Andrew', 'Brown', 85000)
print(employee_1.get_employee_legal_obligations_txt())
1. An employee must complete 8 hours per working day
2. ...
References
What's the difference between static and class methods in Python?

Python: Regular method and static method with same name

Introduction
I have a Python class, which contains a number of methods. I want one of those methods to have a static counterpart—that is, a static method with the same name—which can handle more arguments. After some searching, I have found that I can use the #staticmethod decorator to create a static method.
Problem
For convenience, I have created a reduced test case which reproduces the issue:
class myclass:
#staticmethod
def foo():
return 'static method'
def foo(self):
return 'public method'
obj = myclass()
print(obj.foo())
print(myclass.foo())
I expect that the code above will print the following:
public method
static method
However, the code prints the following:
public method
Traceback (most recent call last):
File "sandbox.py", line 14, in <module>
print(myclass.foo())
TypeError: foo() missing 1 required positional argument: 'self'
From this, I can only assume that calling myclass.foo() tries to call its non-static counterpart with no arguments (which won't work because non-static methods always accept the argument self). This behavior baffles me, because I expect any call to the static method to actually call the static method.
I've tested the issue in both Python 2.7 and 3.3, only to receive the same error.
Questions
Why does this happen, and what can I do to fix my code so it prints:
public method
static method
as I would expect?
While it's not strictly possible to do, as rightly pointed out, you could always "fake" it by redefining the method on instantiation, like this:
class YourClass(object):
def __init__(self):
self.foo = self._instance_foo
#staticmethod
def foo():
print "Static!"
def _instance_foo(self):
print "Instance!"
which would produce the desired result:
>>> YourClass.foo()
Static!
>>> your_instance = YourClass()
>>> your_instance.foo()
Instance!
A similar question is here: override methods with same name in python programming
functions are looked up by name, so you are just redefining foo with an instance method. There is no such thing as an overloaded function in Python. You either write a new function with a separate name, or you provide the arguments in such a way that it can handle the logic for both.
In other words, you can't have a static version and an instance version of the same name. If you look at its vars you'll see one foo.
In [1]: class Test:
...: #staticmethod
...: def foo():
...: print 'static'
...: def foo(self):
...: print 'instance'
...:
In [2]: t = Test()
In [3]: t.foo()
instance
In [6]: vars(Test)
Out[6]: {'__doc__': None, '__module__': '__main__', 'foo': <function __main__.foo>}
Because attribute lookup in Python is something within the programmer's control, this sort of thing is technically possible. If you put any value into writing code in a "pythonic" way (using the preferred conventions and idioms of the python community), it is very likely the wrong way to frame a problem / design. But if you know how descriptors can allow you to control attribute lookup, and how functions become bound functions (hint: functions are descriptors), you can accomplish code that is roughly what you want.
For a given name, there is only one object that will be looked up on a class, regardless of whether you are looking the name up on an instance of the class, or the class itself. Thus, the thing that you're looking up has to deal with the two cases, and dispatch appropriately.
(Note: this isn't exactly true; if an instance has a name in its attribute namespace that collides with one in the namespace of its class, the value on the instance will win in some circumstances. But even in those circumstances, it won't become a "bound method" in the way that you probably would wish it to.)
I don't recommend designing your program using a technique such as this, but the following will do roughly what you asked. Understanding how this works requires a relatively deep understanding of python as a language.
class StaticOrInstanceDescriptor(object):
def __get__(self, cls, inst):
if cls is None:
return self.instance.__get__(self)
else:
return self.static
def __init__(self, static):
self.static = static
def instance(self, instance):
self.instance = instance
return self
class MyClass(object):
#StaticOrInstanceDescriptor
def foo():
return 'static method'
#foo.instance
def foo(self):
return 'public method'
obj = MyClass()
print(obj.foo())
print(MyClass.foo())
which does print out:
% python /tmp/sandbox.py
static method
public method
Ended up here from google so thought I would post my solution to this "problem"...
class Test():
def test_method(self=None):
if self is None:
print("static bit")
else:
print("instance bit")
This way you can use the method like a static method or like an instance method.
When you try to call MyClass.foo(), Python will complain since you did not pass the one required self argument. #coderpatros's answer has the right idea, where we provide a default value for self, so its no longer required. However, that won't work if there are additional arguments besides self. Here's a function that can handle almost all types of method signatures:
import inspect
from functools import wraps
def class_overload(cls, methods):
""" Add classmethod overloads to one or more instance methods """
for name in methods:
func = getattr(cls, name)
# required positional arguments
pos_args = 1 # start at one, as we assume "self" is positional_only
kwd_args = [] # [name:str, ...]
sig = iter(inspect.signature(func).parameters.values())
next(sig)
for s in sig:
if s.default is s.empty:
if s.kind == s.POSITIONAL_ONLY:
pos_args += 1
continue
elif s.kind == s.POSITIONAL_OR_KEYWORD:
kwd_args.append(s.name)
continue
break
#wraps(func)
def overloaded(*args, **kwargs):
# most common case: missing positional arg or 1st arg is not a cls instance
isclass = len(args) < pos_args or not isinstance(args[0], cls)
# handle ambiguous signatures, func(self, arg:cls, *args, **kwargs);
# check if missing required positional_or_keyword arg
if not isclass:
for i in range(len(args)-pos_args,len(kwd_args)):
if kwd_args[i] not in kwargs:
isclass = True
break
# class method
if isclass:
return func(cls, *args, **kwargs)
# instance method
return func(*args, **kwargs)
setattr(cls, name, overloaded)
class Foo:
def foo(self, *args, **kwargs):
isclass = self is Foo
print("foo {} method called".format(["instance","class"][isclass]))
class_overload(Foo, ["foo"])
Foo.foo() # "foo class method called"
Foo().foo() # "foo instance method called"
You can use the isclass bool to implement the different logic for class vs instance method.
The class_overload function is a bit beefy and will need to inspect the signature when the class is declared. But the actual logic in the runtime decorator (overloaded) should be quite fast.
There's one signature that this solution won't work for: a method with an optional, first, positional argument of type Foo. It's impossible to tell if we are calling the static or instance method just by the signature in this case. For example:
def bad_foo(self, other:Foo=None):
...
bad_foo(f) # f.bad_foo(None) or Foo.bad_foo(f) ???
Note, this solution may also report an incorrect isclass value if you pass in incorrect arguments to the method (a programmer error, so may not be important to you).
We can get a possibly more robust solution by doing the reverse of this: first start with a classmethod, and then create an instance method overload of it. This is essentially the same idea as #Dologan's answer, though I think mine is a little less boilerplatey if you need to do this on several methods:
from types import MethodType
def instance_overload(self, methods):
""" Adds instance overloads for one or more classmethods"""
for name in methods:
setattr(self, name, MethodType(getattr(self, name).__func__, self))
class Foo:
def __init__(self):
instance_overload(self, ["foo"])
#classmethod
def foo(self, *args, **kwargs):
isclass = self is Foo
print("foo {} method called:".format(["instance","class"][isclass]))
Foo.foo() # "foo class method called"
Foo().foo() # "foo instance method called"
Not counting the code for class_overload or instance_overload, the code is equally succinct. Often signature introspection is touted as the "pythonic" way to do these kinds of things. But I think I'd recommend using the instance_method solution instead; isclass will be correct for any method signature, including cases where you call with incorrect arguments (a programmer error).

Difference between #classmethod and a method in python [duplicate]

This question already has answers here:
What's an example use case for a Python classmethod?
(7 answers)
Closed 9 years ago.
What is the difference between #classmethod and a 'classic' method in python,
When should I use the #classmethod and when should I use a 'classic' method in python.
Is the classmethod must be an method who is referred to the class (I mean it's only a method who handle the class) ?
And I know what is the difference between a #staticmethod and classic method
Thx
Let's assume you have a class Car which represents the Car entity within your system.
A classmethod is a method that works for the class Car not on one of any of Car's instances. The first parameter to a function decorated with #classmethod, usually called cls, is therefore the class itself. Example:
class Car(object):
colour = 'red'
#classmethod
def blue_cars(cls):
# cls is the Car class
# return all blue cars by looping over cls instances
A function acts on a particular instance of the class; the first parameter usually called self is the instance itself:
def get_colour(self):
return self.colour
To sum up:
use classmethod to implement methods that work on a whole class (and not on particular class instances):
Car.blue_cars()
use instance methods to implement methods that work on a particular instance:
my_car = Car(colour='red')
my_car.get_colour() # should return 'red'
If you define a method inside a class, it is handled in a special way: access to it wraps it in a special object which modifies the calling arguments in order to include self, a reference to the referred object:
class A(object):
def f(self):
pass
a = A()
a.f()
This call to a.f actually asks f (via the descriptor protocol) for an object to really return. This object is then called without arguments and deflects the call to the real f, adding a in front.
So what a.f() really does is calling the original f function with (a) as arguments.
In order to prevent this, we can wrap the function
with a #staticmethod decorator,
with a #classmethod decorator,
with one of other, similiar working, self-made decorators.
#staticmethod turns it into an object which, when asked, changes the argument-passing behaviour so that it matches the intentions about calling the original f:
class A(object):
def method(self):
pass
#staticmethod
def stmethod():
pass
#classmethod
def clmethod(cls):
pass
a = A()
a.method() # the "function inside" gets told about a
A.method() # doesn't work because there is no reference to the needed object
a.clmethod() # the "function inside" gets told about a's class, A
A.clmethod() # works as well, because we only need the classgets told about a's class, A
a.stmethod() # the "function inside" gets told nothing about anything
A.stmethod() # works as well
So #classmethod and #staticmethod have in common that they "don't care about" the concrete object they were called with; the difference is that #staticmethod doesn't want to know anything at all about it, while #classmethod wants to know its class.
So the latter gets the class object the used object is an instance of. Just replace self with cls in this case.
Now, when to use what?
Well, that is easy to handle:
If you have an access to self, you clearly need an instance method.
If you don't access self, but want to know about its class, use #classmethod. This may for example be the case with factory methods. datetime.datetime.now() is such an example: you can call it via its class or via an instance, but it creates a new instance with completely different data. I even used them once for automatically generating subclasses of a given class.
If you need neither self nor cls, you use #staticmethod. This can as well be used for factory methods, if they don't need to care about subclassing.
#classmethod takes the class as first argument while function takes instance of the class
>>> class Test(object):
... def func(self):
... print self
... #classmethod
... def meth(self):
... print self
>>> t = Test()
>>> t.func()
<__main__.Test object at 0x00000000027238D0>
>>> t.meth()
<class '__main__.Test'>
I've used self argument in meth intentionally so it would be very close in syntax to the func. But usually you'd better use cls as argument:
... #classmethod
... def meth(cls):
... print cls

How can I access attributes of a lazy variable class?

I've made myself a lazy variable class, and used it in another class. How can I then access the attributes of the lazy variable class? I have tried __getattr__ without luck. Here's an example:
class lazyobject(object):
def __init__(self,varname,something='This is the something I want to access'):
self.varname = varname
self.something = something
def __get__(self, obj, type=None):
if obj.__dict__.has_key(self.varname):
print "Already computed %s" % self.varname
return obj.__dict__[self.varname]
else:
print "computing %s" % self.varname
obj.__dict__[self.varname] = "something else"
return obj.__dict__[self.varname]
class lazyobject2(lazyobject):
def __getattr__(self):
return self.something
class dummy(object):
def __init__(self):
setattr(self.__class__, 'lazy', lazyobject('lazy'))
class dummy2(object):
def __init__(self):
setattr(self.__class__, 'lazy', lazyobject2('lazy'))
d1 = dummy()
d2 = dummy2()
try:
print "d1.lazy.something - no getattr: ",d1.lazy.something
except:
print "d2.lazy is already computed - can't get its .something because it's now a string!"
print "d1.lazy - no getattr: ",d1.lazy
try:
print "d2.lazy.something - has getattr: ",d2.lazy.something
except:
print "d2.lazy is already computed - can't get its .something because it's now a string!"
print "d2.lazy - no getattr: ",d2.lazy
This prints:
d1.lazy.something - no getattr: computing lazy
d2.lazy is already computed - can't get its .something because it's now a string!
d1.lazy - no getattr: something else
d2.lazy.something - has getattr: computing lazy
d2.lazy is already computed - can't get its .something because it's now a string!
d2.lazy - no getattr: something else
What I would like it to print:
d1.lazy.something - no getattr: This is the something I want to access
computing lazy
d1.lazy - no getattr: something else
The above example is contrived but I hope gets the point across. Another way to phrase my question is: How can I bypass the __get__ method when accessing a class attribute?
The way to bypass __get__ when accessing a class attribute is to look it up via the class dictionary rather than using dotted access.
This is easy to demonstrate using function objects. For example:
>>> class A(object):
def f(self):
pass
>>> A.f # dotted access calls f.__get__
<unbound method A.f>
>>> vars(A)['f'] # dict access bypasses f.__get__
<function f at 0x101723500>
>>> a = A()
>>> a.f # dotted access calls f.__get__
<bound method A.f of <__main__.A object at 0x10171e810>>
>>> vars(a.__class__)['f'] # dict access bypasses f.__get__
<function f at 0x101723500>
The other piece of information you were missing is that the inherited __get__ runs before the __getattr__ which only runs if no attribute is found. This logic is controlled by __getattribute__ which is inherited from object. So, if you want to bypass __get__ you will either need to write a new __get__ in the subclass or change the lookup logic by defining __getattribute__ in the subclass.
To fix the lazyobject2 class, replace the __getattr__ with:
class lazyobject2(lazyobject):
def __getattribute__(self, key):
# bypass __get__
return object.__getattribute__(self, '__dict__')[key]
In summary, the key pieces of knowledge used to solve this problem are:
object.__getattribute__ controls the lookup logic.
It first looks for __get__ whether defined in the current class or inherited.
Only if nothing is found, does it attempt to call object.__getattr__.
The above three steps only happen for dotted lookup.
Those step can be bypassed by directly accessing the dict via __dict__ or vars().
The full details of descriptor logic can be found in this writeup or in this presentation.

Why is getattr() not working like I think it should? I think this code should print 'sss'

the next is my code:
class foo:
def __init__(self):
self.a = "a"
def __getattr__(self,x,defalut):
if x in self:
return x
else:return defalut
a=foo()
print getattr(a,'b','sss')
i know the __getattr__ must be 2 argument,but i want to get a default attribute if the attribute is no being.
how can i get it, thanks
and
i found if defined __setattr__,my next code is also can't run
class foo:
def __init__(self):
self.a={}
def __setattr__(self,name,value):
self.a[name]=value
a=foo()#error ,why
hi alex,
i changed your example:
class foo(object):
def __init__(self):
self.a = {'a': 'boh'}
def __getattr__(self, x):
if x in self.a:
return self.a[x]
raise AttributeError
a=foo()
print getattr(a,'a','sss')
it print {'a': 'boh'},not 'boh'
i think it will print self.a not self.a['a'], This is obviously not want to see
why ,and Is there any way to avoid it
Your problem number one: you're defining an old-style class (we know you're on Python 2.something, even though you don't tell us, because you're using print as a keyword;-). In Python 2:
class foo:
means you're defining an old-style, aka legacy, class, whose behavior can be rather quirky at times. Never do that -- there's no good reason! The old-style classes exist only for compatibility with old legacy code that relies on their quirks (and were finally abolished in Python 3). Use new style classes instead:
class foo(object):
and then the check if x in self: will not cause a recursive __getattr__ call. It will however cause a failure anyway, because your class does not define a __contains__ method and therefore you cannot check if x is contained in an instance of that class.
If what you're trying to do is whether x is defined in the instance dict of self, don't bother: __getattr__ doesn't even get called in that case -- it's only called when the attribute is not otherwise found in self.
To support three-arguments calls to the getattr built-in, just raise AttributeError in your __getattr__ method if necessary (just as would happen if you had no __getattr__ method at all), and the built-in will do its job (it's the built-in's job to intercept such cases and return the default if provided). That's the reason one never ever calls special methods such as __getattr__ directly but rather uses built-ins and operators which internally call them -- the built-ins and operators provide substantial added value.
So to give an example which makes somewhat sense:
class foo(object):
def __init__(self):
self.blah = {'a': 'boh'}
def __getattr__(self, x):
if x in self.blah:
return self.blah[x]
raise AttributeError
a=foo()
print getattr(a,'b','sss')
This prints sss, as desired.
If you add a __setattr__ method, that one intercepts every attempt to set attributes on self -- including self.blah = whatever. So -- when you need to bypass the very __setattr__ you're defining -- you must use a different approach. For example:
class foo(object):
def __init__(self):
self.__dict__['blah'] = {}
def __setattr__(self, name, value):
self.blah[name] = value
def __getattr__(self, x):
if x in self.blah:
return self.blah[x]
raise AttributeError
a=foo()
print getattr(a,'b','sss')
This also prints sss. Instead of
self.__dict__['blah'] = {}
you could also use
object.__setattr__(self, 'blah', {})
Such "upcalls to the superclass's implementation" (which you could also obtain via the super built-in) are one of the rare exceptions to the rules "don't call special methods directly, call the built-in or use the operator instead" -- here, you want to specifically bypass the normal behavior, so the explicit special-method call is a possibility.
You are confusing the getattr built-in function, which retrieves some attribute binding of an object dynamically (by name), at runtime, and the __getattr__ method, which is invoked when you access some missing attribute of an object.
You can't ask
if x in self:
from within __getattr__, because the in operator will cause __getattr__ to be invoked, leading to infinite recursion.
If you simply want to have undefined attributes all be defined as some value, then
def __getattr__(self, ignored):
return "Bob Dobbs"

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