object of type A and Is there a way to programatically wrap a class object?
Given
class A(object):
def __init__(self):
## ..
def f0(self, a):
## ...
def f1(self, a, b):
## ..
I want another class that wraps an A, such as
class B(object):
def __init__(self):
self.a = A()
def f0(self,a):
try:
a.f0(a)
except (Exception),ex:
## ...
def f1(self, a, b):
try:
a.f1(a,b)
except (Exception),ex:
## ...
Is there a way to do create B.f0 & B.f1 by reflection/inspection of class A?
If you want to create class B by calling a function on a predefined class A, you can simply do B = wrap_class(A) with a function wrap_class that looks like this:
import copy
def wrap_class(cls):
'Wraps a class so that exceptions in its methods are caught.'
# The copy is necessary so that mutable class attributes are not
# shared between the old class cls and the new class:
new_cls = copy.deepcopy(cls)
# vars() is used instead of dir() so that the attributes of base classes
# are not modified, but one might want to use dir() instead:
for (attr_name, value) in vars(cls).items():
if isinstance(value, types.FunctionType):
setattr(new_cls, attr_name, func_wrapper(value))
return new_cls
B = wrap_class(A)
As Jürgen pointed out, this creates a copy of the class; this is only needed, however, if you really want to keep your original class A around (like suggested in the original question). If you don't care about A, you can simply decorate it with a wrapper that does not perform any copy, like so:
def wrap_class(cls):
'Wraps a class so that exceptions in its methods are caught.'
# vars() is used instead of dir() so that the attributes of base classes
# are not modified, but one might want to use dir() instead:
for (attr_name, value) in vars(cls).items():
if isinstance(value, types.FunctionType):
setattr(cls, attr_name, func_wrapper(value))
return cls
#wrap_class
class A(object):
… # Original A class, with methods that are not wrapped with exception catching
The decorated class A catches exceptions.
The metaclass version is heavier, but its principle is similar:
import types
def func_wrapper(f):
'Returns a version of function f that prints an error message if an exception is raised.'
def wrapped_f(*args, **kwargs):
try:
return f(*args, **kwargs)
except Exception, ex:
print "Function", f, "raised", ex
return wrapped_f
class ExceptionCatcher(type):
'Metaclass that wraps methods with func_wrapper().'
def __new__(meta, cname, bases, cdict):
# cdict contains the attributes of class cname:
for (attr_name, value) in cdict.items():
if isinstance(value, types.FunctionType): # Various attribute types can be wrapped differently
cdict[attr_name] = func_wrapper(value)
return super(meta, ExceptionCatcher).__new__(meta, cname, bases, cdict)
class B(object):
__metaclass__ = ExceptionCatcher # ExceptionCatcher will be used for creating class A
class_attr = 42 # Will not be wrapped
def __init__(self):
pass
def f0(self, a):
return a*10
def f1(self, a, b):
1/0 # Raises a division by zero exception!
# Test:
b = B()
print b.f0(3.14)
print b.class_attr
print b.f1(2, 3)
This prints:
31.4
42
Function <function f1 at 0x107812d70> raised integer division or modulo by zero
None
What you want to do is in fact typically done by a metaclass, which is a class whose instances are a class: this is a way of building the B class dynamically based on its parsed Python code (the code for class A, in the question). More information on this can be found in the nice, short description of metaclasses given in Chris's Wiki (in part 1 and parts 2-4).
Meta classes are an option, but generally hard to understand. As is too much reflection
if not needed in simple cases, because it is easy to catch too many (internal) functions. If the wrapped functions are a stable known set, and B might gain other functions, you can delegate explicitly function by function and still keep your error handling code in one place:
class B(object):
def __init__(self):
a = A()
self.f0 = errorHandler(a.f0)
self.f1 = errorHandler(a.f1)
You might do the assignments in a loop if they are many, using getattr/setattr.
The errorhandler function will need to return a function which wraps its argument with
error handling code.
def errorHandler(f):
def wrapped(*args, **kw):
try:
return f(*args, **kw)
except:
# log or something
return wrapped
You can also use errorhandler as decorator on new functions not delegating to the A instance.
def B(A):
...
#errorHandler
def f_new(self):
...
This solution keeps B simple and it is quite explicit what's going on.
You could try it old-school with __getattr__:
class B(object):
def __init__(self):
self.a = A()
def __getattr__(self, name):
a_method = getattr(a, name, None)
if not callable(a_method):
raise AttributeError("Unknown attribute %r" % name)
def wrapper(*args, **kwargs):
try:
return a_method(*args, **kwargs)
except Exception, ex:
# ...
return wrapper
Or with updating B's dict:
class B(object):
def __init__(self):
a = A()
for attr_name in dir(a):
attr = getattr(a, attr_name)
if callable(attr):
def wrapper(*args, **kwargs):
try:
return attr(*args, **kwargs)
except Exception, ex:
# ...
setattr(self, attr_name, wrapper) # or try self.__dict__[x] = y
Related
Is it possible to create a "constructor".. or rather "Initializer" to each function, instead of having to manually write it at the top of each function in class?
So, each time a function in a class is called, the other assigned function (unknown to caller) is always called first (called pre_check in below example).
An example using super(), but I then have to manually copy it inside each function.
class Helper():
def pre_check(self):
print("Helper fcn")
class Parent(Helper):
def __init__(self):
print("Initializer")
def foo(self):
super().pre_check() # <---- new code
# ... existing code here ...
def bar(self):
super().pre_check() # <---- new code
# ... existing code here ...
def many_more_functions(self):
super().pre_check() # <---- new code
# ... existing code here ...
m = Parent()
m.foo()
m.bar()
Note how __init__ in Parent is not supposed to run pre_check.
You can use a decorator for the class that will in turn decorate all public methods defined in the class:
def addhelper(helpmethod):
def deco(cls):
def decomethod(method):
def inner(self, *args, **kwargs):
helpmethod(self)
return method(self, *args, **kwargs)
# copy signature, doc and names from the original method
inner.__signature__ = inspect.signature(method)
inner.__doc__ = method.__doc__
inner.__name__ = method.__name__
inner.__qualname__ = method.__qualname__
return inner
# search all methods declared in cls with a name not starting with _
for name, meth in inspect.getmembers(
cls,lambda x: inspect.isfunction(x)
and not x.__name__.startswith('_')
and x.__qualname__.startswith(cls.__name__)):
# replace each method with its decoration
setattr(cls, name, decomethod(meth))
return cls
return deco
class Helper():
def pre_check(self):
print("Helper fcn")
#addhelper(Helper.pre_check)
class Parent(Helper):
def __init__(self):
print("Initializer")
def foo(self):
# super().pre_check() # <----
print('in foo')
def bar(self):
# super().pre_check() # <----
print('in bar')
def many_more_functions(self):
# super().pre_check() # <----
print('in many_more_functions')
We can now use it:
>>> p = Parent()
Initializer
>>> p.foo()
Helper fcn
in foo
>>> p.bar()
Helper fcn
in bar
>>> p.many_more_functions()
Helper fcn
in many_more_functions
Use __init_subclass__ to change subclasses as they are created. You can wrap the methods of subclasses:
class Helper():
def __init_subclass__(cls):
for field, value in cls.__dict__.items():
# add additional checks as desired, e.g. exclude __special_methods__
if inspect.isfunction(value) and not getattr(value, 'checked', False):
setattr(cls, field, cls._check(value)) # wrap method
#classmethod
def _check(cls, fcn):
"""Create a wrapper to inspect the arguments passed to methods"""
#functools.wraps(fcn)
def checked_fcn(*args, **kwargs):
print(fcn, "got", args, kwargs)
return fcn(*args, **kwargs)
return checked_fcn
class Parent(Helper):
def __init__(self):
print("Initializer")
def foo(self):
print("Foo")
Note that this will wrap all methods, including special methods such as __init__:
>>> Parent().foo()
<function Parent.__init__ at 0x1029b2378> got (<__main__.Parent object at 0x102c09080>,) {}
Initializer
<function Parent.foo at 0x1029b2158> got (<__main__.Parent object at 0x102c09080>,) {}
Foo
You can extend the check in __init_subclass__ with arbitrary rules to filter out functions. For example, field[:2] == field[-2:] == "__" excludes special methods.
You can use metaclass and define a decorator for each method in the instance of that metaclass
Code :
def decorate(f):
def do_something(self, a):
if (f(self, a) > 18) :
return ("Eligible to vote")
else :
return ("Not eligible to vote")
return do_something
class Meta(type):
def __new__(cls, name, bases, namespace, **kwds):
namespace = {k: v if k.startswith('__') else decorate(v) for k, v in namespace.items()}
return type.__new__(cls, name, bases, namespace)
class MetaInstance(metaclass=Meta):
def foo1(self, val):
return val + 15
def foo2(self, val):
return val + 9
obj1 = MetaInstance()
print(obj1.foo1(5))
print(obj1.foo2(2))
I have given up memoization of a class as a bag-of-worms that I didn't want to explore and here is one example of why. The question I ask is "how does one extend or inherit from a memoized class" but it's very possible I have made a mistake. The memoize class below is a cut-down version of the one by brandizzi in How can I memoize a class instantiation in Python? and googling the subject finds more involved such classes.
class memoize(object):
def __init__(self, cls):
self.cls = cls
# I didn't understand why this was needed
self.__dict__.update(cls.__dict__)
# bit about static methods not needed
def __call__(self, *args):
try:
self.cls.instances
except:
self.cls.instances = {}
key = '//'.join(map(str, args))
if key not in self.cls.instances:
self.cls.instances[key] = self.cls(*args)
return self.cls.instances[key]
class Foo():
def __init__(self,val):
self.val = val
def __repr__(self):
return "{}<{},{}>".format(self.__class__.__name__,self.val,id(self))
class Bar(Foo):
def __init__(self,val):
super().__init__(val)
f1,f2,f3 = [Foo(i) for i in (0,0,1)]
print([f1,f2,f3])
b1,b2,b3 = [Bar(i) for i in (0,0,1)]
print([b1,b2,b3])
# produces exactly what I expect
# [Foo<0,3071981964>, Foo<0,3071982092>, Foo<1,3071982316>]
# [Bar<0,3071983340>, Bar<0,3071983404>, Bar<1,3071983436>]
Foo = memoize(Foo)
f1,f2,f3 = [Foo(i) for i in (0,0,1)]
print([f1,f2,f3])
b1,b2,b3 = [Bar(i) for i in (0,0,1)]
print([b1,b2,b3])
# and now Foo has been memoized so Foo(0) always produces the same object
# [Foo<0,3071725804>, Foo<0,3071725804>, Foo<1,3071726060>]
# [Bar<0,3071711916>, Bar<0,3071711660>, Bar<1,3071725644>]
# this produces a compilation error that I don't understand
class Baz(Foo):
def __init__(self,val):
super().__init__(val)
# Traceback (most recent call last):
# File "/tmp/foo.py", line 49, in <module>
# class Baz(Foo):
# TypeError: __init__() takes 2 positional arguments but 4 were given
This "recipe" is indeed a very bad idea - once you rebind Foo to memoize(Foo), Foo is a memoize instance and not class Foo anymore. This breaks all expectations wrt/ python's type and the whole object model. In this case, it about how the class statement works. Actually, this:
class Titi():
x = 42
def toto(self):
print(self.x)
is syntactic sugar for:
def toto(self):
print(self.x)
Titi = type("Titi", (object,), {x:42, toto:toto})
del toto
Note that this happens at runtime (like everything in Python except parsing / bytecode compilation), and that type is a class so calling type creates a new class which is a type instance (this is named a 'metaclass' - the class of a class - and type is the default metaclass).
So with Foo being now a memoize instance instead of a Type instance, and since memoize is not a proper metaclass (it's __init__ methods signature is incompatible), the whole thing just cannot work.
To get this to work, you'd have to make memoize a proper metaclass (this is a simplified example assuming a single arg named param but it can be generalized if you want to):
class FooType(type):
def __new__(meta, name, bases, attrs):
if "_instances" not in attrs:
attrs["_instances"] = dict()
return type.__new__(meta, name, bases, attrs)
def __call__(cls, param):
if param not in cls._instances:
cls._instances[param] = super(FooType, cls).__call__(param)
return cls._instances[param]
class Foo(metaclass=FooType):
def __init__(self, param):
self._param = param
print("%s init(%s)" % (self, param))
def __repr__(self):
return "{}<{},{}>".format(self.__class__.__name__, self._param, id(self))
class Bar(Foo):
pass
f1,f2,f3 = [Foo(i) for i in (0,0,1)]
print([f1,f2,f3])
b1,b2,b3 = [Bar(i) for i in (0,0,1)]
print([b1,b2,b3])
When using classmethod to dynamic change the method in subclass, how to dynamic change signatures of method?
example
import inspect
class ModelBase(object):
#classmethod
def method_one(cls, *args):
raise NotImplementedError
#classmethod
def method_two(cls, *args):
return cls.method_one(*args) + 1
class SubClass(ModelBase):
#staticmethod
def method_one(a, b):
return a + b
test = SubClass()
try:
print(inspect.signature(test.method_two))
except AttributeError:
print(inspect.getargspec(test.method_two).args)
I want test.method_two to get the signatures of test.method_one. How to rewrite parent class ModelBase?
I have read about Preserving signatures of decorated functions. In python3.4 +, functools.wraps helps to preserve signatures of decorated functions. I want to apply it to class method.
when uses functools.wraps, I need to assign decorated method's name. But how to access decorated method outside classmethod in this situation?
from functools import wraps
class ModelBase(object):
#classmethod
def method_one(cls, *args):
raise NotImplementedError
#classmethod
def method_two(cls):
#wraps(cls.method_one)
def fun(*args):
return cls.method_one(*args) + 1
return fun
method_two returns a wrapped function, but I must use it with test.method_two()(*arg). This method is not directly.
If this is only for introspection purpose you could override __getattribute__ on ModelBase and every time method_two is accessed we return a function that has the signature of method_one.
import inspect
def copy_signature(frm, to):
def wrapper(*args, **kwargs):
return to(*args, **kwargs)
wrapper.__signature__ = inspect.signature(frm)
return wrapper
class ModelBase(object):
#classmethod
def method_one(cls, *args):
raise NotImplementedError
#classmethod
def method_two(cls, *args):
return cls.method_one(*args) + 1
def __getattribute__(self, attr):
value = object.__getattribute__(self, attr)
if attr == 'method_two':
value = copy_signature(frm=self.method_one, to=value)
return value
class SubClass(ModelBase):
#staticmethod
def method_one(a, b):
return a + b
class SubClass2(ModelBase):
#staticmethod
def method_one(a, b, c, *arg):
return a + b
Demo:
>>> test1 = SubClass()
>>> print(inspect.signature(test1.method_two))
(a, b)
>>> test2 = SubClass2()
>>> print(inspect.signature(test2.method_two))
(a, b, c, *arg)
This question already has answers here:
Using property() on classmethods
(19 answers)
Closed 3 years ago.
In python I can add a method to a class with the #classmethod decorator. Is there a similar decorator to add a property to a class? I can better show what I'm talking about.
class Example(object):
the_I = 10
def __init__( self ):
self.an_i = 20
#property
def i( self ):
return self.an_i
def inc_i( self ):
self.an_i += 1
# is this even possible?
#classproperty
def I( cls ):
return cls.the_I
#classmethod
def inc_I( cls ):
cls.the_I += 1
e = Example()
assert e.i == 20
e.inc_i()
assert e.i == 21
assert Example.I == 10
Example.inc_I()
assert Example.I == 11
Is the syntax I've used above possible or would it require something more?
The reason I want class properties is so I can lazy load class attributes, which seems reasonable enough.
Here's how I would do this:
class ClassPropertyDescriptor(object):
def __init__(self, fget, fset=None):
self.fget = fget
self.fset = fset
def __get__(self, obj, klass=None):
if klass is None:
klass = type(obj)
return self.fget.__get__(obj, klass)()
def __set__(self, obj, value):
if not self.fset:
raise AttributeError("can't set attribute")
type_ = type(obj)
return self.fset.__get__(obj, type_)(value)
def setter(self, func):
if not isinstance(func, (classmethod, staticmethod)):
func = classmethod(func)
self.fset = func
return self
def classproperty(func):
if not isinstance(func, (classmethod, staticmethod)):
func = classmethod(func)
return ClassPropertyDescriptor(func)
class Bar(object):
_bar = 1
#classproperty
def bar(cls):
return cls._bar
#bar.setter
def bar(cls, value):
cls._bar = value
# test instance instantiation
foo = Bar()
assert foo.bar == 1
baz = Bar()
assert baz.bar == 1
# test static variable
baz.bar = 5
assert foo.bar == 5
# test setting variable on the class
Bar.bar = 50
assert baz.bar == 50
assert foo.bar == 50
The setter didn't work at the time we call Bar.bar, because we are calling
TypeOfBar.bar.__set__, which is not Bar.bar.__set__.
Adding a metaclass definition solves this:
class ClassPropertyMetaClass(type):
def __setattr__(self, key, value):
if key in self.__dict__:
obj = self.__dict__.get(key)
if obj and type(obj) is ClassPropertyDescriptor:
return obj.__set__(self, value)
return super(ClassPropertyMetaClass, self).__setattr__(key, value)
# and update class define:
# class Bar(object):
# __metaclass__ = ClassPropertyMetaClass
# _bar = 1
# and update ClassPropertyDescriptor.__set__
# def __set__(self, obj, value):
# if not self.fset:
# raise AttributeError("can't set attribute")
# if inspect.isclass(obj):
# type_ = obj
# obj = None
# else:
# type_ = type(obj)
# return self.fset.__get__(obj, type_)(value)
Now all will be fine.
If you define classproperty as follows, then your example works exactly as you requested.
class classproperty(object):
def __init__(self, f):
self.f = f
def __get__(self, obj, owner):
return self.f(owner)
The caveat is that you can't use this for writable properties. While e.I = 20 will raise an AttributeError, Example.I = 20 will overwrite the property object itself.
[answer written based on python 3.4; the metaclass syntax differs in 2 but I think the technique will still work]
You can do this with a metaclass...mostly. Dappawit's almost works, but I think it has a flaw:
class MetaFoo(type):
#property
def thingy(cls):
return cls._thingy
class Foo(object, metaclass=MetaFoo):
_thingy = 23
This gets you a classproperty on Foo, but there's a problem...
print("Foo.thingy is {}".format(Foo.thingy))
# Foo.thingy is 23
# Yay, the classmethod-property is working as intended!
foo = Foo()
if hasattr(foo, "thingy"):
print("Foo().thingy is {}".format(foo.thingy))
else:
print("Foo instance has no attribute 'thingy'")
# Foo instance has no attribute 'thingy'
# Wha....?
What the hell is going on here? Why can't I reach the class property from an instance?
I was beating my head on this for quite a while before finding what I believe is the answer. Python #properties are a subset of descriptors, and, from the descriptor documentation (emphasis mine):
The default behavior for attribute access is to get, set, or delete the
attribute from an object’s dictionary. For instance, a.x has a lookup chain
starting with a.__dict__['x'], then type(a).__dict__['x'], and continuing
through the base classes of type(a) excluding metaclasses.
So the method resolution order doesn't include our class properties (or anything else defined in the metaclass). It is possible to make a subclass of the built-in property decorator that behaves differently, but (citation needed) I've gotten the impression googling that the developers had a good reason (which I do not understand) for doing it that way.
That doesn't mean we're out of luck; we can access the properties on the class itself just fine...and we can get the class from type(self) within the instance, which we can use to make #property dispatchers:
class Foo(object, metaclass=MetaFoo):
_thingy = 23
#property
def thingy(self):
return type(self).thingy
Now Foo().thingy works as intended for both the class and the instances! It will also continue to do the right thing if a derived class replaces its underlying _thingy (which is the use case that got me on this hunt originally).
This isn't 100% satisfying to me -- having to do setup in both the metaclass and object class feels like it violates the DRY principle. But the latter is just a one-line dispatcher; I'm mostly okay with it existing, and you could probably compact it down to a lambda or something if you really wanted.
If you use Django, it has a built in #classproperty decorator.
from django.utils.decorators import classproperty
For Django 4, use:
from django.utils.functional import classproperty
I think you may be able to do this with the metaclass. Since the metaclass can be like a class for the class (if that makes sense). I know you can assign a __call__() method to the metaclass to override calling the class, MyClass(). I wonder if using the property decorator on the metaclass operates similarly.
Wow, it works:
class MetaClass(type):
def getfoo(self):
return self._foo
foo = property(getfoo)
#property
def bar(self):
return self._bar
class MyClass(object):
__metaclass__ = MetaClass
_foo = 'abc'
_bar = 'def'
print MyClass.foo
print MyClass.bar
Note: This is in Python 2.7. Python 3+ uses a different technique to declare a metaclass. Use: class MyClass(metaclass=MetaClass):, remove __metaclass__, and the rest is the same.
As far as I can tell, there is no way to write a setter for a class property without creating a new metaclass.
I have found that the following method works. Define a metaclass with all of the class properties and setters you want. IE, I wanted a class with a title property with a setter. Here's what I wrote:
class TitleMeta(type):
#property
def title(self):
return getattr(self, '_title', 'Default Title')
#title.setter
def title(self, title):
self._title = title
# Do whatever else you want when the title is set...
Now make the actual class you want as normal, except have it use the metaclass you created above.
# Python 2 style:
class ClassWithTitle(object):
__metaclass__ = TitleMeta
# The rest of your class definition...
# Python 3 style:
class ClassWithTitle(object, metaclass = TitleMeta):
# Your class definition...
It's a bit weird to define this metaclass as we did above if we'll only ever use it on the single class. In that case, if you're using the Python 2 style, you can actually define the metaclass inside the class body. That way it's not defined in the module scope.
def _create_type(meta, name, attrs):
type_name = f'{name}Type'
type_attrs = {}
for k, v in attrs.items():
if type(v) is _ClassPropertyDescriptor:
type_attrs[k] = v
return type(type_name, (meta,), type_attrs)
class ClassPropertyType(type):
def __new__(meta, name, bases, attrs):
Type = _create_type(meta, name, attrs)
cls = super().__new__(meta, name, bases, attrs)
cls.__class__ = Type
return cls
class _ClassPropertyDescriptor(object):
def __init__(self, fget, fset=None):
self.fget = fget
self.fset = fset
def __get__(self, obj, owner):
if self in obj.__dict__.values():
return self.fget(obj)
return self.fget(owner)
def __set__(self, obj, value):
if not self.fset:
raise AttributeError("can't set attribute")
return self.fset(obj, value)
def setter(self, func):
self.fset = func
return self
def classproperty(func):
return _ClassPropertyDescriptor(func)
class Bar(metaclass=ClassPropertyType):
__bar = 1
#classproperty
def bar(cls):
return cls.__bar
#bar.setter
def bar(cls, value):
cls.__bar = value
bar = Bar()
assert Bar.bar==1
Bar.bar=2
assert bar.bar==2
nbar = Bar()
assert nbar.bar==2
I happened to come up with a solution very similar to #Andrew, only DRY
class MetaFoo(type):
def __new__(mc1, name, bases, nmspc):
nmspc.update({'thingy': MetaFoo.thingy})
return super(MetaFoo, mc1).__new__(mc1, name, bases, nmspc)
#property
def thingy(cls):
if not inspect.isclass(cls):
cls = type(cls)
return cls._thingy
#thingy.setter
def thingy(cls, value):
if not inspect.isclass(cls):
cls = type(cls)
cls._thingy = value
class Foo(metaclass=MetaFoo):
_thingy = 23
class Bar(Foo)
_thingy = 12
This has the best of all answers:
The "metaproperty" is added to the class, so that it will still be a property of the instance
Don't need to redefine thingy in any of the classes
The property works as a "class property" in for both instance and class
You have the flexibility to customize how _thingy is inherited
In my case, I actually customized _thingy to be different for every child, without defining it in each class (and without a default value) by:
def __new__(mc1, name, bases, nmspc):
nmspc.update({'thingy': MetaFoo.services, '_thingy': None})
return super(MetaFoo, mc1).__new__(mc1, name, bases, nmspc)
If you only need lazy loading, then you could just have a class initialisation method.
EXAMPLE_SET = False
class Example(object):
#classmethod
def initclass(cls):
global EXAMPLE_SET
if EXAMPLE_SET: return
cls.the_I = 'ok'
EXAMPLE_SET = True
def __init__( self ):
Example.initclass()
self.an_i = 20
try:
print Example.the_I
except AttributeError:
print 'ok class not "loaded"'
foo = Example()
print foo.the_I
print Example.the_I
But the metaclass approach seems cleaner, and with more predictable behavior.
Perhaps what you're looking for is the Singleton design pattern. There's a nice SO QA about implementing shared state in Python.
Disclaimer:
This article is more a recipe than a question, but I found the subject quite interesting, with almost no references in the Web.
If there is any better place on StackOverflow to publish this kind of articles, please let me know.
Subject:
How can I force Python to invoke different function depending on the type of attribute access (using class or instance) - e.g. force Python to invoke different method for MyClass.my_method() and MyClass().my_method()?
Usecase:
Let's say, we have custom Enum implementation (based on Python36 Enum, but with some customization). As a user of this Enum, we want to create a CustomEnum, inherit not just from Enum, but also from str: class MyEnum(str, Enum).We also want to add encoding and decoding feature. Our idea is to use MyEnum.encode to encode any object, that includes our enum members, but leave the original str.encode in power for instances of our enum class.
In short: MyEnum.encode invoke our custom encoding function, and have perfectly sens, from this point of view. MyEnum() is a string, so MyEnum().encode should invoke encode function inherited from str class.
Solution:
Write a descriptor, which will work as a switch.
Full answer in my first post.
Solution:
As far as I know, descriptors are the only objects, that can distinguish, if they are invoke for class or instance, because of the __get__ function signature: __get__(self, instance, instance_type). This property allows us to build a switch on top of it.
class boundmethod(object):
def __init__(self, cls_method=None, instance_method=None, doc=None):
self._cls_method = cls_method
self._instance_method = instance_method
if cls_method:
self._method_name = cls_method.__name__
elif instance_method:
self._method_name = instance_method.__name__
if doc is None and cls_method is not None:
doc = cls_method.__doc__
self.__doc__ = doc
self._method = None
self._object = None
def _find_method(self, instance, instance_type, method_name):
for base in instance_type.mro()[1:]:
method = getattr(base, method_name, None)
if _is_descriptor(method):
method = method.__get__(instance, base)
if method and method is not self:
try:
return method.__func__
except AttributeError:
return method
def __get__(self, instance, instance_type):
if instance is None:
self._method = self._cls_method or self._find_method(instance, instance_type, self._method_name)
self._object = instance_type
else:
self._method = self._instance_method or self._find_method(instance, instance_type, self._method_name)
self._object = instance
return self
#staticmethod
def cls_method(obj=None):
def constructor(cls_method):
if obj is None:
return boundmethod(cls_method, None, cls_method.__doc__)
else:
return type(obj)(cls_method, obj._instance_method, obj.__doc__)
if isinstance(obj, FunctionType):
return boundmethod(obj, None, obj.__doc__)
else:
return constructor
#staticmethod
def instance_method(obj=None):
def constructor(instance_method):
if obj is None:
return boundmethod(None, instance_method, instance_method.__doc__)
else:
return type(obj)(obj._cls_method, instance_method, obj.__doc__)
if isinstance(obj, FunctionType):
return boundmethod(None, obj, obj.__doc__)
else:
return constructor
def __call__(self, *args, **kwargs):
if self._method:
try:
return self._method(self._object, *args, **kwargs)
except TypeError:
return self._method(*args, **kwargs)
return None
Example:
>>> class Walkmen(object):
... #boundmethod.cls_method
... def start(self):
... return 'Walkmen start class bound method'
... #boundmethod.instance_method(start)
... def start(self):
... return 'Walkmen start instance bound method'
>>> print Walkmen.start()
Walkmen start class bound method
>>> print Walkmen().start()
Walkmen start instance bound method
I hope it will help some o you guys.
Best.
I actually just asked this question (Python descriptors and inheritance I hadn't seen this question). My solution uses descriptors and a metaclass for inheritance.
from my answer:
class dynamicmethod:
'''
Descriptor to allow dynamic dispatch on calls to class.Method vs obj.Method
fragile when used with inheritence, to inherit and then overwrite or extend
a dynamicmethod class must have dynamicmethod_meta as its metaclass
'''
def __init__(self, f=None, m=None):
self.f = f
self.m = m
def __get__(self, obj, objtype=None):
if obj is not None and self.f is not None:
return types.MethodType(self.f, obj)
elif objtype is not None and self.m is not None:
return types.MethodType(self.m, objtype)
else:
raise AttributeError('No associated method')
def method(self, f):
return type(self)(f, self.m)
def classmethod(self, m):
return type(self)(self.f, m)
def make_dynamicmethod_meta(meta):
class _dynamicmethod_meta(meta):
def __prepare__(name, bases, **kwargs):
d = meta.__prepare__(name, bases, **kwargs)
for base in bases:
for k,v in base.__dict__.items():
if isinstance(v, dynamicmethod):
if k in d:
raise ValueError('Multiple base classes define the same dynamicmethod')
d[k] = v
return d
return _dynamicmethod_meta
dynamicmethod_meta=make_dynamicmethod_meta(type)
class A(metaclass=dynamicmethod_meta):
#dynamicmethod
def a(self):
print('Called from obj {} defined in A'.format(self))
#a.classmethod
def a(cls)
print('Called from class {} defined in A'.format(cls))
class B(A):
#a.method
def a(self):
print('Called from obj {} defined in B'.format(self))
A.a()
A().a()
B.a()
B().a()
results in:
Called from class <class 'A'> defined in A
Called from obj <A object at ...> defined in A
Called from class <class 'B'> defined in A
Called from obj <B object at ...> defined in B