It seems that an acceptable answer to the question
What is a method?
is
A method is a function that's a member of a class.
I disagree with this.
class Foo(object):
pass
def func():
pass
Foo.func = func
f = Foo()
print "fine so far"
try:
f.func()
except TypeError:
print "whoops! func must not be a method after all"
Is func a member of Foo?
Is func a method of Foo?
I am well aware that this would work if func had a self argument. That's obvious. I'm interested in if it's a member of foo and in if it's a method as presented.
You're just testing it wrong:
>>> class Foo(object): pass
...
>>> def func(self): pass
...
>>> Foo.func = func
>>> f = Foo()
>>> f.func()
>>>
You error of forgetting to have in the def the self argument has absolutely nothing to do with f.func "not being a method", of course. The peculiar conceit of having the def outside the class instead of inside it (perfectly legal Python of course, but, as I say, peculiar) has nothing to do with the case either: if you forget to have a first argument (conventionally named self) in your def statements for methods, you'll get errors in calling them, of course (a TypeError is what you get, among other cases, whenever the actual arguments specified in the call can't match the formal arguments accepted by the def, of course).
The type error wouldn't be thrown if func had a self argument, like any other instance method.
That's because when you evaluate f.func, you're actually binding f to the first argument of the function -- it then becomes a partial application which you can provide further arguments to.
If you want it to be a static method, then you need the staticmethod decorator which just throws away the first parameter and passes the rest into the original function.
So 2 ways of making it work:
def func(self): pass
-- or --
Foo.func = staticmethod(func)
depending on what you're aiming for.
As written, func is a member of Foo and a method of Foo instances such as your f. However, it can't be successfully called because it doesn't accept at least one argument.
func is in f's namespace and has a _call_() method. In other words, it is enough of a method that Python tries to call it like one when you invoke it like one. If it quacks like a duck, in other words...
That this call doesn't succeed is neither here nor there, in my opinion.
But perhaps a proper response to "But Doctor! When I don't accept any arguments in a function defined in a class, I get confused about whether it's really a method or not!" is simply "Don't do that." :-)
Related
How to use instance as a parameter in the python member function decorators.
The following is an example.
def foo(func):
def wrap(s):
func()
s.ma()
return wrap
class A:
def ma(self):
print "this is ma"
#foo(self) #error.name 'self' is not defined
def mb(self):
print "this is mb"
It's not clear what you're looking for, but if you want to be able to use the reference to the instance inside your decorator:
def foo(func):
def wrap(s): # I'd call this 'self' instead of 's' to remind us it's a reference to an instance
func(s) # This is a function, not a method yet - so we need to pass in the reference
s.ma() # This is a method, because you use attribute lookup on the object s to get it
return wrap
class A:
def ma(self):
print "this is ma"
#foo # if the way foo wraps mb doesn't depend on some arg, don't use args here
def mb(self):
print "this is mb"
I think you're confused here about the difference between methods and functions in Python – you seem to expect func will work like a method, when in fact it will still be a function when it is being decorated. It is the decorated function that will, at attribute lookup on the instance, be turned into a method; this means you still need the explicit self when you call func in your wrapper function.
See the terrific answer to How to make a chain of function decorators? for a better explanation of what's going on.
For the error:
TypeError: takes exactly 1 argument (2 given)
With the following class method:
def extractAll(tag):
...
and calling it:
e.extractAll("th")
The error seems very odd when I'm giving it 1 argument, the method should take only 1 argument, but it's saying I'm not giving it 1 argument....I know the problem can be fixed by adding self into the method prototype but I wanted to know the reasoning behind the error.
Am I getting it because the act of calling it via e.extractAll("th") also passes in self as an argument? And if so, by removing the self in the call, would I be making it some kind of class method that can be called like Extractor.extractAll("th")?
The call
e.extractAll("th")
for a regular method extractAll() is indeed equivalent to
Extractor.extractAll(e, "th")
These two calls are treated the same in all regards, including the error messages you get.
If you don't need to pass the instance to a method, you can use a staticmethod:
#staticmethod
def extractAll(tag):
...
which can be called as e.extractAll("th"). But I wonder why this is a method on a class at all if you don't need to access any instance.
If a non-static method is member of a class, you have to define it like that:
def Method(self, atributes..)
So, I suppose your 'e' is instance of some class with implemented method that tries to execute and has too much arguments.
Am I getting it because the act of calling it via e.extractAll("th") also passes in self as an argument?
Yes, that's precisely it. If you like, the first parameter is the object name, e that you are calling it with.
And if so, by removing the self in the call, would I be making it some kind of class method that can be called like Extractor.extractAll("th")?
Not quite. A classmethod needs the #classmethod decorator, and that accepts the class as the first paramater (usually referenced as cls). The only sort of method that is given no automatic parameter at all is known as a staticmethod, and that again needs a decorator (unsurprisingly, it's #staticmethod). A classmethod is used when it's an operation that needs to refer to the class itself: perhaps instantiating objects of the class; a staticmethod is used when the code belongs in the class logically, but requires no access to class or instance.
But yes, both staticmethods and classmethods can be called by referencing the classname as you describe: Extractor.extractAll("th").
Yes, when you invoke e.extractAll(foo), Python munges that into extractAll(e, foo).
From http://docs.python.org/tutorial/classes.html
the special thing about methods is
that the object is passed as the first
argument of the function. In our
example, the call x.f() is exactly
equivalent to MyClass.f(x). In
general, calling a method with a list
of n arguments is equivalent to
calling the corresponding function
with an argument list that is created
by inserting the method’s object
before the first argument.
Emphasis added.
Summary (Some examples of how to define methods in classes in python)
#!/usr/bin/env python # (if running from bash)
class Class1(object):
def A(self, arg1):
print arg1
# this method requires an instance of Class1
# can access self.variable_name, and other methods in Class1
#classmethod
def B(cls, arg1):
cls.C(arg1)
# can access methods B and C in Class1
#staticmethod
def C(arg1):
print arg1
# can access methods B and C in Class1
# (i.e. via Class1.B(...) and Class1.C(...))
Example
my_obj=Class1()
my_obj.A("1")
# Class1.A("2") # TypeError: method A() must be called with Class1 instance
my_obj.B("3")
Class1.B("4")
my_obj.C("5")
Class1.C("6")`
try using:
def extractAll(self,tag):
attention to self
[Updated]: Answer inline below question
I have an inspecting program and one objective is for logic in a decorator to know whether the function it is decorating is a class method or regular function. This is failing in a strange way. Below is code run in Python 2.6:
def decorate(f):
print 'decorator thinks function is', f
return f
class Test(object):
#decorate
def test_call(self):
pass
if __name__ == '__main__':
Test().test_call()
print 'main thinks function is', Test().test_call
Then on execution:
decorator thinks function is <function test_call at 0x10041cd70>
main thinks function is <bound method Test.test_call of <__main__.Test object at 0x100425a90>>
Any clue on what's going wrong, and if it is possible for #decorate to correctly infer that test_call is a method?
[Answer]
carl's answer below is nearly perfect. I had a problem when using the decorator on a method that subclasses call. I adapted his code to include a im_func comparison on superclass members:
ismethod = False
for item in inspect.getmro(type(args[0])):
for x in inspect.getmembers(item):
if 'im_func' in dir(x[1]):
ismethod = x[1].im_func == newf
if ismethod:
break
else:
continue
break
As others have said, a function is decorated before it is bound, so you cannot directly determine whether it's a 'method' or 'function'.
A reasonable way to determine if a function is a method or not is to check whether 'self' is the first parameter. While not foolproof, most Python code adheres to this convention:
import inspect
ismethod = inspect.getargspec(method).args[0] == 'self'
Here's a convoluted way that seems to automatically figure out whether the method is a bound or not. Works for a few simple cases on CPython 2.6, but no promises. It decides a function is a method if the first argument to is an object with the decorated function bound to it.
import inspect
def decorate(f):
def detect(*args, **kwargs):
try:
members = inspect.getmembers(args[0])
members = (x[1].im_func for x in members if 'im_func' in dir(x[1]))
ismethod = detect in members
except:
ismethod = False
print ismethod
return f(*args, **kwargs)
return detect
#decorate
def foo():
pass
class bar(object):
#decorate
def baz(self):
pass
foo() # prints False
bar().baz() # prints True
No, this is not possible as you have requested, because there is no inherent difference between bound methods and functions. A method is simply a function wrapped up to get the calling instance as the first argument (using Python descriptors).
A call like:
Test.test_call
which returns an unbound method, translates to
Test.__dict__[ 'test_call' ].__get__( None, spam )
which is an unbound method, even though
Test.__dict__[ 'test_call' ]
is a function. This is because functions are descriptors whose __get__ methods return methods; when Python sees one of these in the lookup chain it calls the __get__ method instead of continuing up the chain.
In effect, the 'bound-methodiness' of a function is determined at runtime, not at define-time!
The decorator simply sees the function as it is defined, without looking it up in a __dict__, so cannot tell whether it is looking at a bound method.
It might be possible to do this with a class decorator that modifies __getattribute__, but that's a particularly nasty hack. Why must you have this functionality? Surely, since you have to place the decorator on the function yourself, you could pass it an argument that says whether said function is defined within a class?
class Test:
#decorate( method = True )
def test_call:
...
#decorate( method = False )
def test_call:
...
Your decorator is run before the function becomes a method. def keyword inside a class defines a function line in any other place, then the functions defined in the body of a class are added to the class as methods. Decorator operates on the function before it is processed by the class that is why your code 'fails'.
There is no way for the #decorate to see the function is actually a method. A workaround for that would be to decorate the function whatever it is (e.g. adding an attribute do_something_about_me_if_I_am_a_method ;-)) and then process it again after the class is computed (iterating over the class members and doing whatever you want with those decorated).
I tried a slightly different example, with one decorated method and one undecorated method.
def decorate(f):
print 'decorator thinks function is', f
return f
class Test(object):
#decorate
def test_call(self):
pass
def test_call_2(self):
pass
if __name__ == '__main__':
print 'main thinks function is', Test.test_call
print 'main thinks function 2 is', Test.test_call_2
Then the output is:
decorator thinks function is <function test_call at 0x100426b18>
main thinks function is <unbound method Test.test_call>
main thinks function 2 is <unbound method Test.test_call_2>
Thus, the decorator saw a different type than the main function did, but the decorator did not change the function's type, or it would be different from the undecorated function.
I've got a bunch of functions (outside of any class) where I've set attributes on them, like funcname.fields = 'xxx'. I was hoping I could then access these variables from inside the function with self.fields, but of course it tells me:
global name 'self' is not defined
So... what can I do? Is there some magic variable I can access? Like __this__.fields?
A few people have asked "why?". You will probably disagree with my reasoning, but I have a set of functions that all must share the same signature (accept only one argument). For the most part, this one argument is enough to do the required computation. However, in a few limited cases, some additional information is needed. Rather than forcing every function to accept a long list of mostly unused variables, I've decided to just set them on the function so that they can easily be ignored.
Although, it occurs to me now that you could just use **kwargs as the last argument if you don't care about the additional args. Oh well...
Edit: Actually, some of the functions I didn't write, and would rather not modify to accept the extra args. By "passing in" the additional args as attributes, my code can work both with my custom functions that take advantage of the extra args, and with third party code that don't require the extra args.
Thanks for the speedy answers :)
self isn't a keyword in python, its just a normal variable name. When creating instance methods, you can name the first parameter whatever you want, self is just a convention.
You should almost always prefer passing arguments to functions over setting properties for input, but if you must, you can do so using the actual functions name to access variables within it:
def a:
if a.foo:
#blah
a.foo = false
a()
see python function attributes - uses and abuses for when this comes in handy. :D
def foo():
print(foo.fields)
foo.fields=[1,2,3]
foo()
# [1, 2, 3]
There is nothing wrong with adding attributes to functions. Many memoizers use this to cache results in the function itself.
For example, notice the use of func.cache:
from decorator import decorator
#decorator
def memoize(func, *args, **kw):
# Author: Michele Simoniato
# Source: http://pypi.python.org/pypi/decorator
if not hasattr(func, 'cache'):
func.cache = {}
if kw: # frozenset is used to ensure hashability
key = args, frozenset(kw.iteritems())
else:
key = args
cache = func.cache # attribute added by memoize
if key in cache:
return cache[key]
else:
cache[key] = result = func(*args, **kw)
return result
You can't do that "function accessing its own attributes" correctly for all situations - see for details here how can python function access its own attributes? - but here is a quick demonstration:
>>> def f(): return f.x
...
>>> f.x = 7
>>> f()
7
>>> g = f
>>> g()
7
>>> del f
>>> g()
Traceback (most recent call last):
File "<interactive input>", line 1, in <module>
File "<interactive input>", line 1, in f
NameError: global name 'f' is not defined
Basically most methods directly or indirectly rely on accessing the function object through lookup by name in globals; and if original function name is deleted, this stops working. There are other kludgey ways of accomplishing this, like defining class, or factory - but thanks to your explanation it is clear you don't really need that.
Just do the mentioned keyword catch-all argument, like so:
def fn1(oneArg):
// do the due
def fn2(oneArg, **kw):
if 'option1' in kw:
print 'called with option1=', kw['option1']
//do the rest
fn2(42)
fn2(42, option1='something')
Not sure what you mean in your comment of handling TypeError - that won't arise when using **kw. This approach works very well for some python system functions - check min(), max(), sort(). Recently sorted(dct,key=dct.get,reverse=True) came very handy to me in CodeGolf challenge :)
Example:
>>> def x(): pass
>>> x
<function x at 0x100451050>
>>> x.hello = "World"
>>> x.hello
"World"
You can set attributes on functions, as these are just plain objects, but I actually never saw something like this in real code.
Plus. self is not a keyword, just another variable name, which happens to be the particular instance of the class. self is passed implicitly, but received explicitly.
if you want globally set parameters for a callable 'thing' you could always create a class and implement the __call__ method?
There is no special way, within a function's body, to refer to the function object whose code is executing. Simplest is just to use funcname.field (with funcname being the function's name within the namespace it's in, which you indicate is the case -- it would be harder otherwise).
This isn't something you should do. I can't think of any way to do what you're asking except some walking around on the call stack and some weird introspection -- which isn't something that should happen in production code.
That said, I think this actually does what you asked:
import inspect
_code_to_func = dict()
def enable_function_self(f):
_code_to_func[f.func_code] = f
return f
def get_function_self():
f = inspect.currentframe()
code_obj = f.f_back.f_code
return _code_to_func[code_obj]
#enable_function_self
def foo():
me = get_function_self()
print me
foo()
While I agree with the the rest that this is probably not good design, the question did intrigue me. Here's my first solution, which I may update once I get decorators working. As it stands, it relies pretty heavily on being able to read the stack, which may not be possible in all implementations (something about sys._getframe() not necessarily being present...)
import sys, inspect
def cute():
this = sys.modules[__name__].__dict__.get(inspect.stack()[0][3])
print "My face is..." + this.face
cute.face = "very cute"
cute()
What do you think? :3
You could use the following (hideously ugly) code:
class Generic_Object(object):
pass
def foo(a1, a2, self=Generic_Object()):
self.args=(a1,a2)
print "len(self.args):", len(self.args)
return None
... as you can see it would allow you to use "self" as you described. You can't use an "object()" directly because you can't "monkey patch(*)" values into an object() instance. However, normal subclasses of object (such as the Generic_Object() I've shown here) can be "monkey patched"
If you wanted to always call your function with a reference to some object as the first argument that would be possible. You could put the defaulted argument first, followed by a *args and optional **kwargs parameters (through which any other arguments or dictionaries of options could be passed during calls to this function).
This is, as I said hideously ugly. Please don't ever publish any code like this or share it with anyone in the Python community. I'm only showing it here as a sort of strange educational exercise.
An instance method is like a function in Python. However, it exists within the namespace of a class (thus it must be accessed via an instance ... myobject.foo() for example) and it is called with a reference to "self" (analagous to the "this" pointer in C++) as the first argument. Also there's a method resolution process which causes the interpreter to search the namespace of the instance, then it's class, and then each of the parent classes and so on ... up through the inheritance tree.
An unbound function is called with whatever arguments you pass to it. There can't bee any sort of automatically pre-pended object/instance reference to the argument list. Thus, writing a function with an initial argument named "self" is meaningless. (It's legal because Python doesn't place any special meaning on the name "self." But meaningless because callers to your function would have to manually supply some sort of object reference to the argument list and it's not at all clear what that should be. Just some bizarre "Generic_Object" which then floats around in the global variable space?).
I hope that clarifies things a bit. It sounds like you're suffering from some very fundamental misconceptions about how Python and other object-oriented systems work.
("Monkey patching" is a term used to describe the direct manipulation of an objects attributes -- or "instance variables" by code that is not part of the class hierarchy of which the object is an instance).
As another alternative, you can make the functions into bound class methods like so:
class _FooImpl(object):
a = "Hello "
#classmethod
def foo(cls, param):
return cls.a + param
foo = _FooImpl.foo
# later...
print foo("World") # yes, Hello World
# and if you have to change an attribute:
foo.im_self.a = "Goodbye "
If you want functions to share attribute namespaecs, you just make them part of the same class. If not, give each its own class.
What exactly are you hoping "self" would point to, if the function is defined outside of any class? If your function needs some global information to execute properly, you need to send this information to the function in the form of an argument.
If you want your function to be context aware, you need to declare it within the scope of an object.
I've noticed a discrepancy in the way that python parameters are called. In every other language I've dealt with, you either have
foo()
meaning either no parameters, or as many parameters as you like, or
foo(arg1, arg2,...,argn)
where you pass in the same number of parameters to define the function and call it. In python however, I've noticed that the function definitions, and when the function is called, can have two different parameters sets, this usually consists of:
class foo(object):
def bar(self, arg1, arg2):
pass
However, when I want to call the function, all I have to do is:
zoo = foo()
zoo.bar(arg1, arg2)
Where did the self parameter go?
Thank you.
Where did the self parameter go?
It's in front of the dot when you call the function, i.e. in your case it's zoo.
Note that you can also call the function as foo.bar(zoo, arg1, arg2). Basically in python object.method(arguments) is a shortcut for objects_class.method(object, arguments).
zoo is the self parameter.
In C++, for example, you get the object passed implicitly as the this pointer. In Python, this parameter is explicit.
zoo is implicitly passed as the first parameter in your example.
As I remember, "zoo.bar" gives you just an attribute "bar" of object "zoo" that can be called. All magic is done at construction where all methods of class is binded to that object while dictionary of attributes is populated.
Consider next example:
zoo = foo()
xbar = zoo.bar
xbar(arg1, arg2)