I want to call some function depend on event code how can I do it in Python?
I made such code but it not works and I am user that only one step to make it working.
class Thing(object):
#classmethod
def do1(cls):
print 'do1'
#classmethod
def do2(cls):
print 'do2'
eventToMethod = {'1': do1,
'2': do2}
#classmethod
def onEvent(cls, name):
method = cls.eventToMethod.get(name)
if method != None:
method()
Thing.onEvent('1')
Whatever I get such errors and has not idea how to call classmethods in Python way.
TypeError: 'classmethod' object is not callable
Can you help with this simple problem?
You need to make some changes to changes to eventToMethod first, don't assign do1, do2 to it, better assign strings. You can always access class attributes using strings. The problem with storing references to do1 and do2 in dictionary is that they are not bound methods yet(they're simply classmethod objects(non-data descriptors)) when you store them in dictionary, it's only after the completion of class definition that they're converted to fully bound class methods.
eventToMethod = {'1': 'do1',
'2': 'do2'}
And then use getaattr to get the method:
#classmethod
def onEvent(cls, name):
method = getattr(cls, cls.eventToMethod.get(name))
...
Note that you can also directly pass 'do1' to onEvent instead of keeping a dictionary to store names and then simply use:
method = getattr(cls, name)
You can still get away with your current approach if you call __get__ method of do1, do2 descriptors explicitly.:
method = cls.eventToMethod.get(name)
if method != None:
method.__get__(None, cls)()
This works because this is exactly what Python does under the hood, classmethod is a non-data descriptor and when you do Thing.do1 Python actually calls __get__ method of do1 with first agument as None and second as type:
>>> Thing.do1.__get__(None, Thing)
<bound method type.do1 of <class '__main__.Thing'>>
>>> Thing.do1.__get__(None, Thing)
<bound method type.do1 of <class '__main__.Thing'>>
>>> Thing.do1
<bound method type.do1 of <class '__main__.Thing'>>
>>> Thing.eventToMethod['1'].__get__(None, Thing) #Using OP's code.
<bound method type.do1 of <class '__main__.Thing'>>
While I understand that this doesn't answer your question directly, I thought it might be useful to see an alternative.
Often it's possible to use reflection to calculate the correct method at runtime. For example:
#classmethod
def onEvent(cls, name):
try:
method = getattr(cls, 'do%s'%name)
except AttributeError:
return
method()
This approach may be useful if you are able to follow a strict naming convention in your methods (as in the example, where you seem to prefix them with 'do'). It's similar to how PyUnit detects the set of test cases to run.
This avoids the need to maintain a dict, which may get out of sync with the actual methods on the object. It also arguably leads to clearer code.
It's worth pointing out as well that if you are attempting to do some kine of event-driven programming -- There are libraries/frameworks that help facilitate this:
Example:
#!/usr/bin/env python
from circuits import Component, Event
class Thing(Component):
def do1(self):
print("do1")
def do2(self):
print("do2")
def started(self, manager):
self.fire(Event.create("do1"))
self.fire(Event.create("do2"))
raise SystemExit(0)
Thing().run()
Output:
$ python foo.py
do1
do2
Disclaimer: I'm the author of circuits
Related
This question already has answers here:
Difference between #staticmethod and #classmethod
(35 answers)
Why do we use #staticmethod?
(4 answers)
Closed last month.
I ran into unbound method error in python with this code:
import random
class Sample(object):
def drawSample(samplesize, List):
sample = random.sample(List, samplesize)
return sample
Choices=range(100)
print(Sample.drawSample(5, Choices))
I was able to fix the problem by adding #staticmethod to the method. However, I don't really understand the situation.
What is the point of using "static" methods? Why does it solve the problem in this code, and why are they ever necessary? Conversely, why would I ever not want to do it (i.e., why is extra code needed to make the method static)?
See this article for detailed explanation.
TL;DR
1.It eliminates the use of self argument.
2.It reduces memory usage because Python doesn't have to instantiate a bound-method for each object instiantiated:
>>>RandomClass().regular_method is RandomClass().regular_method
False
>>>RandomClass().static_method is RandomClass().static_method
True
>>>RandomClass.static_method is RandomClass().static_method
True
3.It improves code readability, signifying that the method does not depend on state of the object itself.
4.It allows for method overriding in that if the method were defined at the module-level (i.e. outside the class) a subclass would not be able to override that method.
Static methods have limited use, because they don't have access to the attributes of an instance of a class (like a regular method does), and they don't have access to the attributes of the class itself (like a class method does).
So they aren't useful for day-to-day methods.
However, they can be useful to group some utility function together with a class - e.g. a simple conversion from one type to another - that doesn't need access to any information apart from the parameters provided (and perhaps some attributes global to the module.)
They could be put outside the class, but grouping them inside the class may make sense where they are only applicable there.
You can also reference the method via an instance or the class, rather than the module name, which may help the reader understand to what instance the method is related.
This is not quite to the point of your actual question, but since you've said you are a python newbie perhaps it will be helpful, and no one else has quite come out and said it explicitly.
I would never have fixed the above code by making the method a static method. I would either have ditched the class and just written a function:
def drawSample(samplesize,List):
sample=random.sample(List,samplesize)
return sample
Choices=range(100)
print drawSample(5,Choices)
If you have many related functions, you can group them in a module - i.e, put them all in the same file, named sample.py for example; then
import sample
Choices=range(100)
print sample.drawSample(5,Choices)
Or I would have added an __init__ method to the class and created an instance that had useful methods:
class Sample(object):
'''This class defines various methods related to the sample'''
def __init__(self, thelist):
self.list = thelist
def draw_sample(self, samplesize):
sample=random.sample(self.list,samplesize)
return sample
choices=Sample(range(100))
print choices.draw_sample(5)
(I also changed the case conventions in the above example to match the style recommended by PEP 8.)
One of the advantages of Python is that it doesn't force you to use classes for everything. You can use them only when there is data or state that should be associated with the methods, which is what classes are for. Otherwise you can use functions, which is what functions are for.
Why one would want to define static methods?
Suppose we have a class called Math then
nobody will want to create object of class Math
and then invoke methods like ceil and floor and fabs on it.
So we make them static.
For example doing
>> Math.floor(3.14)
is much better than
>> mymath = Math()
>> mymath.floor(3.14)
So they are useful in some way. You need not create an instance of a class to use them.
Why are not all methods defined as static methods?
They don't have access to instance variables.
class Foo(object):
def __init__(self):
self.bar = 'bar'
def too(self):
print self.bar
#staticmethod
def foo():
print self.bar
Foo().too() # works
Foo.foo() # doesn't work
That is why we don't make all the methods static.
The alternatives to a staticmethod are: classmethod, instancemethod, and function. If you don't know what these are, scroll down to the last section. If a staticmethod is better than any of these alternatives, depends on for what purpose it is written.
advantages of the Python static method
If you don't need access to the attributes or methods of the class or instance, a staticmethod is better than a classmethod or instancemethod. That way it is clear (from the #staticmethod decorator) that the class' and instance's state is not read or modified. However, using a function makes that distinction even clearer (see disadvantages).
The call signature of a staticmethod is the same as that of a classmethod or instancemethod, namely <instance>.<method>(<arguments>). Hence it can easily be replaced by one of the three if that is needed later on or in a derived class. You can't do that with a simple function.
A staticmethod can be used instead of a function to make clear that it subjectively belongs to a class and to prevent namespace conflicts.
disadvantages of the Python static method
It cannot access attributes or methods of the instance or class.
The call signature of a staticmethod is the same as that of a classmethod or instancemethod. This masks the fact that the staticmethod does not actually read or modify any object information. This makes code harder to read. Why not just use a function?
A staticmethod is difficult to re-use if you ever need to call it from outside the class/instance where it was defined. If there is any potential for re-use, a function is the better choice.
The staticmethod is seldom used, so people reading code that includes one may take a little longer to read it.
alternatives to a static method in Python
To address discuss the advantages of the staticmethod, we need to know what the alternatives are and how they differ from each other.
The staticmethod belongs to a class but cannot access or modify any instance or class information.
There are three alternatives to it:
The classmethod has access to the caller's class.
The instancemethod has access to the caller's instance and its class.
The function has nothing to do with classes. It is the closest in capability to the staticmethod.
Here's what this looks like in code:
# function
# has nothing to do with a class
def make_cat_noise(asker_name):
print('Hi %s, mieets mieets!' % asker_name)
# Yey, we can make cat noises before we've even defined what a cat is!
make_cat_noise('JOey') # just a function
class Cat:
number_of_legs = 4
# special instance method __init__
def __init__(self, name):
self.name = name
# instancemethod
# the instance (e.g. Cat('Kitty')) is passed as the first method argument
def tell_me_about_this_animal(self, asker_name):
print('Hi %s, This cat has %d legs and is called %s'
% (asker_name, self.number_of_legs, self.name))
# classmethod
# the class (e.g. Cat) is passed as the first method argument
# by convention we call that argument cls
#classmethod
def tell_me_about_cats(cls, asker_name):
print("Hi %s, cats have %d legs."
% (asker_name, cls.number_of_legs))
# cls.name # AttributeError because only the instance has .name
# self.name # NameError because self isn't defined in this namespace
# staticmethod
# no information about the class or the instance is passed to the method
#staticmethod
def make_noise(asker_name):
print('Hi %s, meooow!' % asker_name)
# class and instance are not accessible from here
# one more time for fun!
make_cat_noise('JOey') # just a function
# We just need the class to call a classmethod or staticmethod:
Cat.make_noise('JOey') # staticmethod
Cat.tell_me_about_cats('JOey') # classmethod
# Cat.tell_me_about_this_animal('JOey') # instancemethod -> TypeError
# With an instance we can use instancemethod, classmethod or staticmethod
mycat = Cat('Kitty') # mycat is an instance of the class Cat
mycat.make_noise('JOey') # staticmethod
mycat.tell_me_about_cats('JOey') # classmethod
mycat.tell_me_about_this_animal('JOey') # instancemethod
When you call a function object from an object instance, it becomes a 'bound method' and gets the instance object itself is passed in as a first argument.
When you call a classmethod object (which wraps a function object) on an object instance, the class of the instance object gets passed in as a first argument.
When you call a staticmethod object (which wraps a function object), no implicit first argument is used.
class Foo(object):
def bar(*args):
print args
#classmethod
def baaz(*args):
print args
#staticmethod
def quux(*args):
print args
>>> foo = Foo()
>>> Foo.bar(1,2,3)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unbound method bar() must be called with Foo instance as first argument (got int instance instead)
>>> Foo.baaz(1,2,3)
(<class 'Foo'>, 1, 2, 3)
>>> Foo.quux(1,2,3)
(1, 2, 3)
>>> foo.bar(1,2,3)
(<Foo object at 0x1004a4510>, 1, 2, 3)
>>> foo.baaz(1,2,3)
(<class 'Foo'>, 1, 2, 3)
>>> foo.quux(1,2,3)
(1, 2, 3)
static methods are great because you don't have to declare an instance of the object to which the method belongs.
python's site has some great documentation on static methods here:
http://docs.python.org/library/functions.html#staticmethod
In my estimation, there is no single performance benefit of using #staticmethods compared to just defining the function outside of and separate from the class it would otherwise be a #staticmethod of.
The only thing I would say justifies their existence is convenience. Static methods are common in other popular programming languages, so why not python? If you want to create a function with behavior that is very closely associated with the class you are creating it for but it doesn't actually access/modify the internal data of an instance of the class in a way that justifies conceptualizing it as a typical method of that class then slap a #staticmethod above it and anyone reading your code will immediately learn a lot about the nature of the method and its relationship to the class.
One thing I occasionally like to do is place functionality that my class uses internally a lot into private #staticmethods. That way I do not clutter the API exposed by my module with methods that no one using my module would ever need to see let alone use.
Static methods have almost no reason-to-be in Python. You use either instance methods or class methods.
def method(self, args):
self.member = something
#classmethod
def method(cls, args):
cls.member = something
#staticmethod
def method(args):
MyClass.member = something
# The above isn't really working
# if you have a subclass
Because namespacing functions is nice (as was previously pointed out):
When I want to be explicit about methods that don't change the state of the object, I use static methods. This discourages people on my team to start changing the object's attributes in those methods.
When i refactor really rotten code, I start by trying to make as many methods #staticmethod as possible. This allows me then to extract these methods into a class - though I agree, this is rarely something I use, it did came in helpful a few times.
I am writing a framework, and I want my base class to use different functions for renaming in the child classes. I figured the best way would be to use a class attribute, like in case of A, but I got TypeErrors when running it like in rename_columns(). However it worked with implementation like B
import pandas as pd
class A:
my_func_mask = str.lower
foo = 'bar'
def rename_columns(self, data):
return data.rename(columns=self.my_func_mask)
class B(A):
def rename_columns(self, data):
return data.rename(columns=self.__class__.my_func_mask)
So I experimented with the above a bit, and I get the following:
a = A()
a.foo # Works fine, gives back 'bar'
a.__class__.my_func_mask # Works as expected `a.__class__.my_func_mask is str.lower` is true
a.my_func_mask # throws TypeError: descriptor 'lower' for 'str' objects doesn't apply to 'A' object
My questions would be why can I use regular typed (int, str, etc.) values as class attributes and access them on the instance as well, while I cannot do that for functions?
What happens during the attribute lookup in these cases? What is the difference in the attribute resolution process?
Actually both foo and my_func_mask is in __class__.__dict__ so I am a bit puzzled. Thanks for the clarifications!
You are storing an unbound built-in method on your class, meaning it is a descriptor object. When you then try to access that on self, descriptor binding applies but the __get__ method called to complete the binding tells you that it can't be bound to your custom class instances, because the method would only work on str instances. That's a strict limitation of most methods of built-in types.
You need to store it in a different manner; putting it inside another container, such as a list or dictionary, would avoid binding. Or you could wrap it in a staticmethod descriptor to have it be bound and return the original. Another option is to not store this as a class attribute, and simply create an instance attribute in __init__.
But in this case, I'd not store str.lower as an attribute value, at all. I'd store None and fall back to str.lower when you still encounter None:
return data.rename(columns=self.my_func_mask or str.lower)
Setting my_func_mask to None is a better indicator that a default is going to be used, clearly distinguishable from explicitly setting str.lower as the mask.
You need to declare staticmethod.
class A:
my_func_mask = staticmethod(str.lower)
foo = 'bar'
>>> A().my_func_mask is str.lower
>>> True
Everything that is placed in the class definition is bound to the class, but you can't bind a built-in to your own class.
Essentially, all code that you place in a class is executed when the class is created. All items in locals() are then bound to your class at the end of the class. That's why this also works to bind a method to your class:
def abc(self):
print('{} from outside the class'.format(self))
class A:
f1 = abc
f2 = lambda self: print('{} from lambda'.format(self))
def f3(self):
print('{} from method'.format(self))
To not have the function bound to your class, you have to place it in the __init__ method of your class:
class A:
def __init__(self):
self.my_func_mask = str.lower
In Python, if you call a method that doesn't exist it throws an AttributeError. Ex
>>> class A:
... def yo(self):
... print(1)
...
>>> a = A()
>>> a.yo()
1
>>> a.hello()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'A' object has no attribute 'hello'
In the below code, MagicMock class doesn't have a function named hello or no patch was created for a method hello. Still below code doesn't throw an AttributeError
>>> from unittest.mock import MagicMock
>>> obj = MagicMock()
>>> obj.hello()
<MagicMock name='mock.hello()' id='4408758568'>
How is MagicMock able to do this? How can I create a class that can perform an action when any method (which might not be defined) is called on it?
The Python datamodel documents a hook, __getattr__, which shall be called when attribute access fails to resolve in the usual ways. Mocks use it to return a new mock instance - i.e. mocks define unknown attributes as factories.
Reproducing mock's implementation in a simpler way, you would just turn __getattr__ and __call__ into factory functions:
class M:
def __call__(self):
return M()
def __getattr__(self, name):
return M()
Example usage:
>>> mock = M()
>>> mock.potato
<__main__.M at 0xdeadbeef>
>>> mock.potato()
<__main__.M at 0xcafef00d>
How is MagicMock able to do this?
This part is not specific to MagicMock, an ordinary Mock will do the same (the "magic" in the name is just referring to additional features allowing better mocking of magic methods). MagicMock inherits such behavior from one of the base classes:
>>> MagicMock.mro()
[unittest.mock.MagicMock,
unittest.mock.MagicMixin,
unittest.mock.Mock,
unittest.mock.CallableMixin,
unittest.mock.NonCallableMock, # <--- this one overrides __getattr__!
unittest.mock.Base,
object]
How can I create a class that can perform an action when any method (which might not be defined) is called on it?
It depends if you want to be in front of, or behind, a normal attribute access. If you want to get in front, you should define __getattribute__, it's called unconditionally to implement attribute accesses before searching the class/instance namespaces. However, if you want to take a lower precedence to normal attributes (i.e. those living in the object __dict__) and to descriptors, then you should define __getattr__ as previously discussed.
I don't actually know how specifically MagicMock works (I've never used it, but I've Heard Good Things), but this part of the behaviour can be replicated (along with probably multiple other possible solutions) by hijacking __getattr__ in a way that it returns a callable that creates a new mock instance when called:
class MM:
def __init__(self, name=None):
# store a name, TODO: random id, etc.
self.name = name
def __repr__(self):
# make it pretty
if self.name:
r = f'<MM name={self.name}>'
else:
r = f'<MM>'
return r
def __getattr__(self, attrname):
# we want a factory for a mock instance with a name corresponding to attrname
def magicattr():
return MM(name=f"'mock.{attrname}()'")
return magicattr
When executed, we see the following:
>>> MM()
<MM>
>>> MM().hello()
<MM name='mock.hello()'>
I didn't go overboard with defining an id and whatnot, but the basic trick can be seen on the above stripped-down example.
The way the above works is that accessing .hello or any other attribute goes through our custom __getattr__ which gives us a chance to generate a fake (mocked) method on the fly, with whatever properties we want to. As I understand one of the many benefits of MagicMock is exactly that we don't have to worry about AttributeErrors being thrown by default, it just works.
From here, if you define some objects like that:
class Mixin1(object):
def test(self):
print "Mixin1"
class Mixin2(object):
def test(self):
print "Mixin2"
class BaseClass(object):
pass
class MyClass(Mixin2, Mixin1, BaseClass):
pass
You'll get:
>>> obj = MyClass()
>>> obj.test()
Mixin2
Is there a way to call Mixin1 test() method?
Call it explicitly:
Mixin1.test(obj)
The attribute process in Python is relatively complex. For your given example, this is the process for finding the value of obj.test:
First, look at the instance itself. In this case, the instance does not have a test attribute.
Look at the class which obj is an instance of: MyClass. MyClass does not have a test attribute.
Start looking at the classes in the method resolution order of MyClass. In this case, MyClass.__mro__ tells you to look first at Mixin2, then Mixin1, then object.
Mixin2 has a test attribute, so we finally have a match.
Mixin2.test is a function with a __get__ method, so that is called and the return value is used.
You can safely ignore step 5 here, and just assume that Mixin2.test is a method. One that is returned, you can see that obj.test() calls Mixin2.test.
This might help explain why I asked the question I did in a comment. There is a wide variety of ways you can fiddle with the program to get obj.test() to produce a call to Mixin1.test() instead. You can patch the object, you can fiddle with MyClass.__mro__, you can tweak what Mixin2.test actually does, etc.
Override the test method and call Mixin1.test explicitly:
class MyClass(Mixin2, Mixin1, BaseClass):
def test(self):
Mixin1.test(self)
This question already has answers here:
Difference between #staticmethod and #classmethod
(35 answers)
Why do we use #staticmethod?
(4 answers)
Closed last month.
I ran into unbound method error in python with this code:
import random
class Sample(object):
def drawSample(samplesize, List):
sample = random.sample(List, samplesize)
return sample
Choices=range(100)
print(Sample.drawSample(5, Choices))
I was able to fix the problem by adding #staticmethod to the method. However, I don't really understand the situation.
What is the point of using "static" methods? Why does it solve the problem in this code, and why are they ever necessary? Conversely, why would I ever not want to do it (i.e., why is extra code needed to make the method static)?
See this article for detailed explanation.
TL;DR
1.It eliminates the use of self argument.
2.It reduces memory usage because Python doesn't have to instantiate a bound-method for each object instiantiated:
>>>RandomClass().regular_method is RandomClass().regular_method
False
>>>RandomClass().static_method is RandomClass().static_method
True
>>>RandomClass.static_method is RandomClass().static_method
True
3.It improves code readability, signifying that the method does not depend on state of the object itself.
4.It allows for method overriding in that if the method were defined at the module-level (i.e. outside the class) a subclass would not be able to override that method.
Static methods have limited use, because they don't have access to the attributes of an instance of a class (like a regular method does), and they don't have access to the attributes of the class itself (like a class method does).
So they aren't useful for day-to-day methods.
However, they can be useful to group some utility function together with a class - e.g. a simple conversion from one type to another - that doesn't need access to any information apart from the parameters provided (and perhaps some attributes global to the module.)
They could be put outside the class, but grouping them inside the class may make sense where they are only applicable there.
You can also reference the method via an instance or the class, rather than the module name, which may help the reader understand to what instance the method is related.
This is not quite to the point of your actual question, but since you've said you are a python newbie perhaps it will be helpful, and no one else has quite come out and said it explicitly.
I would never have fixed the above code by making the method a static method. I would either have ditched the class and just written a function:
def drawSample(samplesize,List):
sample=random.sample(List,samplesize)
return sample
Choices=range(100)
print drawSample(5,Choices)
If you have many related functions, you can group them in a module - i.e, put them all in the same file, named sample.py for example; then
import sample
Choices=range(100)
print sample.drawSample(5,Choices)
Or I would have added an __init__ method to the class and created an instance that had useful methods:
class Sample(object):
'''This class defines various methods related to the sample'''
def __init__(self, thelist):
self.list = thelist
def draw_sample(self, samplesize):
sample=random.sample(self.list,samplesize)
return sample
choices=Sample(range(100))
print choices.draw_sample(5)
(I also changed the case conventions in the above example to match the style recommended by PEP 8.)
One of the advantages of Python is that it doesn't force you to use classes for everything. You can use them only when there is data or state that should be associated with the methods, which is what classes are for. Otherwise you can use functions, which is what functions are for.
Why one would want to define static methods?
Suppose we have a class called Math then
nobody will want to create object of class Math
and then invoke methods like ceil and floor and fabs on it.
So we make them static.
For example doing
>> Math.floor(3.14)
is much better than
>> mymath = Math()
>> mymath.floor(3.14)
So they are useful in some way. You need not create an instance of a class to use them.
Why are not all methods defined as static methods?
They don't have access to instance variables.
class Foo(object):
def __init__(self):
self.bar = 'bar'
def too(self):
print self.bar
#staticmethod
def foo():
print self.bar
Foo().too() # works
Foo.foo() # doesn't work
That is why we don't make all the methods static.
The alternatives to a staticmethod are: classmethod, instancemethod, and function. If you don't know what these are, scroll down to the last section. If a staticmethod is better than any of these alternatives, depends on for what purpose it is written.
advantages of the Python static method
If you don't need access to the attributes or methods of the class or instance, a staticmethod is better than a classmethod or instancemethod. That way it is clear (from the #staticmethod decorator) that the class' and instance's state is not read or modified. However, using a function makes that distinction even clearer (see disadvantages).
The call signature of a staticmethod is the same as that of a classmethod or instancemethod, namely <instance>.<method>(<arguments>). Hence it can easily be replaced by one of the three if that is needed later on or in a derived class. You can't do that with a simple function.
A staticmethod can be used instead of a function to make clear that it subjectively belongs to a class and to prevent namespace conflicts.
disadvantages of the Python static method
It cannot access attributes or methods of the instance or class.
The call signature of a staticmethod is the same as that of a classmethod or instancemethod. This masks the fact that the staticmethod does not actually read or modify any object information. This makes code harder to read. Why not just use a function?
A staticmethod is difficult to re-use if you ever need to call it from outside the class/instance where it was defined. If there is any potential for re-use, a function is the better choice.
The staticmethod is seldom used, so people reading code that includes one may take a little longer to read it.
alternatives to a static method in Python
To address discuss the advantages of the staticmethod, we need to know what the alternatives are and how they differ from each other.
The staticmethod belongs to a class but cannot access or modify any instance or class information.
There are three alternatives to it:
The classmethod has access to the caller's class.
The instancemethod has access to the caller's instance and its class.
The function has nothing to do with classes. It is the closest in capability to the staticmethod.
Here's what this looks like in code:
# function
# has nothing to do with a class
def make_cat_noise(asker_name):
print('Hi %s, mieets mieets!' % asker_name)
# Yey, we can make cat noises before we've even defined what a cat is!
make_cat_noise('JOey') # just a function
class Cat:
number_of_legs = 4
# special instance method __init__
def __init__(self, name):
self.name = name
# instancemethod
# the instance (e.g. Cat('Kitty')) is passed as the first method argument
def tell_me_about_this_animal(self, asker_name):
print('Hi %s, This cat has %d legs and is called %s'
% (asker_name, self.number_of_legs, self.name))
# classmethod
# the class (e.g. Cat) is passed as the first method argument
# by convention we call that argument cls
#classmethod
def tell_me_about_cats(cls, asker_name):
print("Hi %s, cats have %d legs."
% (asker_name, cls.number_of_legs))
# cls.name # AttributeError because only the instance has .name
# self.name # NameError because self isn't defined in this namespace
# staticmethod
# no information about the class or the instance is passed to the method
#staticmethod
def make_noise(asker_name):
print('Hi %s, meooow!' % asker_name)
# class and instance are not accessible from here
# one more time for fun!
make_cat_noise('JOey') # just a function
# We just need the class to call a classmethod or staticmethod:
Cat.make_noise('JOey') # staticmethod
Cat.tell_me_about_cats('JOey') # classmethod
# Cat.tell_me_about_this_animal('JOey') # instancemethod -> TypeError
# With an instance we can use instancemethod, classmethod or staticmethod
mycat = Cat('Kitty') # mycat is an instance of the class Cat
mycat.make_noise('JOey') # staticmethod
mycat.tell_me_about_cats('JOey') # classmethod
mycat.tell_me_about_this_animal('JOey') # instancemethod
When you call a function object from an object instance, it becomes a 'bound method' and gets the instance object itself is passed in as a first argument.
When you call a classmethod object (which wraps a function object) on an object instance, the class of the instance object gets passed in as a first argument.
When you call a staticmethod object (which wraps a function object), no implicit first argument is used.
class Foo(object):
def bar(*args):
print args
#classmethod
def baaz(*args):
print args
#staticmethod
def quux(*args):
print args
>>> foo = Foo()
>>> Foo.bar(1,2,3)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unbound method bar() must be called with Foo instance as first argument (got int instance instead)
>>> Foo.baaz(1,2,3)
(<class 'Foo'>, 1, 2, 3)
>>> Foo.quux(1,2,3)
(1, 2, 3)
>>> foo.bar(1,2,3)
(<Foo object at 0x1004a4510>, 1, 2, 3)
>>> foo.baaz(1,2,3)
(<class 'Foo'>, 1, 2, 3)
>>> foo.quux(1,2,3)
(1, 2, 3)
static methods are great because you don't have to declare an instance of the object to which the method belongs.
python's site has some great documentation on static methods here:
http://docs.python.org/library/functions.html#staticmethod
In my estimation, there is no single performance benefit of using #staticmethods compared to just defining the function outside of and separate from the class it would otherwise be a #staticmethod of.
The only thing I would say justifies their existence is convenience. Static methods are common in other popular programming languages, so why not python? If you want to create a function with behavior that is very closely associated with the class you are creating it for but it doesn't actually access/modify the internal data of an instance of the class in a way that justifies conceptualizing it as a typical method of that class then slap a #staticmethod above it and anyone reading your code will immediately learn a lot about the nature of the method and its relationship to the class.
One thing I occasionally like to do is place functionality that my class uses internally a lot into private #staticmethods. That way I do not clutter the API exposed by my module with methods that no one using my module would ever need to see let alone use.
Static methods have almost no reason-to-be in Python. You use either instance methods or class methods.
def method(self, args):
self.member = something
#classmethod
def method(cls, args):
cls.member = something
#staticmethod
def method(args):
MyClass.member = something
# The above isn't really working
# if you have a subclass
Because namespacing functions is nice (as was previously pointed out):
When I want to be explicit about methods that don't change the state of the object, I use static methods. This discourages people on my team to start changing the object's attributes in those methods.
When i refactor really rotten code, I start by trying to make as many methods #staticmethod as possible. This allows me then to extract these methods into a class - though I agree, this is rarely something I use, it did came in helpful a few times.