I need to perform certain operations everytime the methods of a particular class is called (for example log the method name). How can this be achieved in Python in a generic way?
Decorate callable attributes from within a metaclass:
from functools import wraps
def _log_method(val):
#wraps(val)
def wrapper(*a, **ka):
print(val.__name__, 'is called')
val(*a, **ka)
return wrapper
class LogMethodCalls(type):
def __new__(cls, cls_name, bases, attrs):
for name, attr in attrs.items():
if callable(attr):
attrs[name] = _log_method(attr)
return type.__new__(cls, cls_name, bases, attrs)
class Foo(metaclass=LogMethodCalls):
def my_method(self):
pass
Foo().my_method() # my_method is called
Warning: This code only works for instance methods, methods that were decorated with #classmethod or #staticmethod will not be logged (because classmethod and staticmethod objects are not callable - they're just non-data descriptors).
The following works for class methods and static methods as well:
from functools import wraps
def _log_method(val):
#wraps(val)
def wrapper(*a, **ka):
print('calling', val.__name__)
val(*a, **ka)
return wrapper
class LogMethodCalls(type):
def __new__(cls, cls_name, bases, attrs):
for name, attr in attrs.items():
if callable(attr):
attrs[name] = _log_method(attr)
elif isinstance(attr, (classmethod, staticmethod)):
attrs[name] = type(attr)(_log_method(attr.__func__))
return type.__new__(cls, cls_name, bases, attrs)
class Foo(metaclass=LogMethodCalls):
def my_instance_method(self):
pass
#classmethod
def my_class_method(cls):
pass
#staticmethod
def my_static_method():
pass
Foo().my_instance_method() # calling my_instance_method
Foo.my_class_method() # calling my_class_method
Foo.my_static_method() # calling my_static_method
They have __func__ attributes that we can decorate.
Note that you'll need to use
class Foo(object):
__metaclass__ = LogMethodCalls
in Python 2.
Taken from this answer. You can use the inspect module to look at the stack for the function name to create a simple logging function. Seems like kind of a hack, but I suppose it answers the question.
import inspect
def log_call():
print(inspect.stack()[1][3])
def my_func():
log_call()
# do stuff
my_func()
This will print my_func.
You could implement a decorator:
from functools import wraps
def print_function_name(function):
#wraps(function)
def do_it():
print function.__name__
function()
return do_it
Usage:
class MyClass(object):
#print_function_name
def some_function(self):
pass
For example:
>>> my_object = MyClass()
>>> my_object.some_function()
some_function
The use of functools.wraps makes sure the function keeps its documentation and name, instead of becoming do_it.
Taken from https://stackoverflow.com/a/5103895/5270581:
The following method of object class is called on each access to an attribute of an object, including method calls:
__get_attribute__
So I suggest to override it by simply adding a call to a logging function inside.
See https://stackoverflow.com/a/5103895/5270581 (go to last answer) for code example.
This is my answer from this post here
It can be done many different ways. I will show how to make it through meta-class, class decorator and inheritance.
by changing meta class
import functools
class Logger(type):
#staticmethod
def _decorator(fun):
#functools.wraps(fun)
def wrapper(*args, **kwargs):
print(fun.__name__, args, kwargs)
return fun(*args, **kwargs)
return wrapper
def __new__(mcs, name, bases, attrs):
for key in attrs.keys():
if callable(attrs[key]):
# if attrs[key] is callable, then we can easily wrap it with decorator
# and substitute in the future attrs
# only for extra clarity (though it is wider type than function)
fun = attrs[key]
attrs[key] = Logger._decorator(fun)
# and then invoke __new__ in type metaclass
return super().__new__(mcs, name, bases, attrs)
class A(metaclass=Logger):
def __init__(self):
self.some_val = "some_val"
def method_first(self, a, b):
print(a, self.some_val)
def another_method(self, c):
print(c)
#staticmethod
def static_method(d):
print(d)
b = A()
# __init__ (<__main__.A object at 0x7f852a52a2b0>,) {}
b.method_first(5, b="Here should be 5")
# method_first (<__main__.A object at 0x7f852a52a2b0>, 5) {'b': 'Here should be 5'}
# 5 some_val
b.method_first(6, b="Here should be 6")
# method_first (<__main__.A object at 0x7f852a52a2b0>, 6) {'b': 'Here should be 6'}
# 6 some_val
b.another_method(7)
# another_method (<__main__.A object at 0x7f852a52a2b0>, 7) {}
# 7
b.static_method(7)
# 7
Also, will show two approaches how to make it without changing meta information of class (through class decorator and class inheritance). The first approach through class decorator put_decorator_on_all_methods accepts decorator to wrap all member callable objects of class.
def logger(f):
#functools.wraps(f)
def wrapper(*args, **kwargs):
print(f.__name__, args, kwargs)
return f(*args, **kwargs)
return wrapper
def put_decorator_on_all_methods(decorator, cls=None):
if cls is None:
return lambda cls: put_decorator_on_all_methods(decorator, cls)
class Decoratable(cls):
def __init__(self, *args, **kargs):
super().__init__(*args, **kargs)
def __getattribute__(self, item):
value = object.__getattribute__(self, item)
if callable(value):
return decorator(value)
return value
return Decoratable
#put_decorator_on_all_methods(logger)
class A:
def method(self, a, b):
print(a)
def another_method(self, c):
print(c)
#staticmethod
def static_method(d):
print(d)
b = A()
b.method(5, b="Here should be 5")
# >>> method (5,) {'b': 'Here should be 5'}
# >>> 5
b.method(6, b="Here should be 6")
# >>> method (6,) {'b': 'Here should be 6'}
# >>> 6
b.another_method(7)
# >>> another_method (7,) {}
# >>> 7
b.static_method(8)
# >>> static_method (8,) {}
# >>> 8
And, recently, I've come across on the same problem, but I couldn't put decorator on class or change it in any other way, except I was allowed to add such behavior through inheritance only (I am not sure that this is the best choice if you can change codebase as you wish though).
Here class Logger forces all callable members of subclasses to write information about their invocations, see code below.
class Logger:
def _decorator(self, f):
#functools.wraps(f)
def wrapper(*args, **kwargs):
print(f.__name__, args, kwargs)
return f(*args, **kwargs)
return wrapper
def __getattribute__(self, item):
value = object.__getattribute__(self, item)
if callable(value):
decorator = object.__getattribute__(self, '_decorator')
return decorator(value)
return value
class A(Logger):
def method(self, a, b):
print(a)
def another_method(self, c):
print(c)
#staticmethod
def static_method(d):
print(d)
b = A()
b.method(5, b="Here should be 5")
# >>> method (5,) {'b': 'Here should be 5'}
# >>> 5
b.method(6, b="Here should be 6")
# >>> method (6,) {'b': 'Here should be 6'}
# >>> 6
b.another_method(7)
# >>> another_method (7,) {}
# >>> 7
b.static_method(7)
# >>> static_method (7,) {}
# >>> 7
Or more abstractly, you can instantiate base class based on some decorator.
def decorator(f):
#functools.wraps(f)
def wrapper(*args, **kwargs):
print(f.__name__, args, kwargs)
return f(*args, **kwargs)
return wrapper
class Decoratable:
def __init__(self, dec):
self._decorator = dec
def __getattribute__(self, item):
value = object.__getattribute__(self, item)
if callable(value):
decorator = object.__getattribute__(self, '_decorator')
return decorator(value)
return value
class A(Decoratable):
def __init__(self, dec):
super().__init__(dec)
def method(self, a, b):
print(a)
def another_method(self, c):
print(c)
#staticmethod
def static_method(d):
print(d)
b = A(decorator)
b.method(5, b="Here should be 5")
# >>> method (5,) {'b': 'Here should be 5'}
# >>> 5
b.method(6, b="Here should be 6")
# >>> method (6,) {'b': 'Here should be 6'}
# >>> 6
b.another_method(7)
# >>> another_method (7,) {}
# >>> 7
b.static_method(7)
# >>> static_method (7,) {}
# >>> 7
Related
Can one write something like:
class Test(object):
def _decorator(self, foo):
foo()
#self._decorator
def bar(self):
pass
This fails: self in #self is unknown
I also tried:
#Test._decorator(self)
which also fails: Test unknown
I would like to temporarily change some instance variables
in the decorator and then run the decorated method, before
changing them back.
Would something like this do what you need?
class Test(object):
def _decorator(foo):
def magic( self ) :
print "start magic"
foo( self )
print "end magic"
return magic
#_decorator
def bar( self ) :
print "normal call"
test = Test()
test.bar()
This avoids the call to self to access the decorator and leaves it hidden in the class namespace as a regular method.
>>> import stackoverflow
>>> test = stackoverflow.Test()
>>> test.bar()
start magic
normal call
end magic
>>>
edited to answer question in comments:
How to use the hidden decorator in another class
class Test(object):
def _decorator(foo):
def magic( self ) :
print "start magic"
foo( self )
print "end magic"
return magic
#_decorator
def bar( self ) :
print "normal call"
_decorator = staticmethod( _decorator )
class TestB( Test ):
#Test._decorator
def bar( self ):
print "override bar in"
super( TestB, self ).bar()
print "override bar out"
print "Normal:"
test = Test()
test.bar()
print
print "Inherited:"
b = TestB()
b.bar()
print
Output:
Normal:
start magic
normal call
end magic
Inherited:
start magic
override bar in
start magic
normal call
end magic
override bar out
end magic
What you're wanting to do isn't possible. Take, for instance, whether or not the code below looks valid:
class Test(object):
def _decorator(self, foo):
foo()
def bar(self):
pass
bar = self._decorator(bar)
It, of course, isn't valid since self isn't defined at that point. The same goes for Test as it won't be defined until the class itself is defined (which its in the process of). I'm showing you this code snippet because this is what your decorator snippet transforms into.
So, as you can see, accessing the instance in a decorator like that isn't really possible since decorators are applied during the definition of whatever function/method they are attached to and not during instantiation.
If you need class-level access, try this:
class Test(object):
#classmethod
def _decorator(cls, foo):
foo()
def bar(self):
pass
Test.bar = Test._decorator(Test.bar)
import functools
class Example:
def wrapper(func):
#functools.wraps(func)
def wrap(self, *args, **kwargs):
print("inside wrap")
return func(self, *args, **kwargs)
return wrap
#wrapper
def method(self):
print("METHOD")
wrapper = staticmethod(wrapper)
e = Example()
e.method()
This is one way to access(and have used) self from inside a decorator defined inside the same class:
class Thing(object):
def __init__(self, name):
self.name = name
def debug_name(function):
def debug_wrapper(*args):
self = args[0]
print 'self.name = ' + self.name
print 'running function {}()'.format(function.__name__)
function(*args)
print 'self.name = ' + self.name
return debug_wrapper
#debug_name
def set_name(self, new_name):
self.name = new_name
Output (tested on Python 2.7.10):
>>> a = Thing('A')
>>> a.name
'A'
>>> a.set_name('B')
self.name = A
running function set_name()
self.name = B
>>> a.name
'B'
The example above is silly, but it works.
Here's an expansion on Michael Speer's answer to take it a few steps further:
An instance method decorator which takes arguments and acts on a function with arguments and a return value.
class Test(object):
"Prints if x == y. Throws an error otherwise."
def __init__(self, x):
self.x = x
def _outer_decorator(y):
def _decorator(foo):
def magic(self, *args, **kwargs) :
print("start magic")
if self.x == y:
return foo(self, *args, **kwargs)
else:
raise ValueError("x ({}) != y ({})".format(self.x, y))
print("end magic")
return magic
return _decorator
#_outer_decorator(y=3)
def bar(self, *args, **kwargs) :
print("normal call")
print("args: {}".format(args))
print("kwargs: {}".format(kwargs))
return 27
And then
In [2]:
test = Test(3)
test.bar(
13,
'Test',
q=9,
lollipop=[1,2,3]
)
start magic
normal call
args: (13, 'Test')
kwargs: {'q': 9, 'lollipop': [1, 2, 3]}
Out[2]:
27
In [3]:
test = Test(4)
test.bar(
13,
'Test',
q=9,
lollipop=[1,2,3]
)
start magic
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-3-576146b3d37e> in <module>()
4 'Test',
5 q=9,
----> 6 lollipop=[1,2,3]
7 )
<ipython-input-1-428f22ac6c9b> in magic(self, *args, **kwargs)
11 return foo(self, *args, **kwargs)
12 else:
---> 13 raise ValueError("x ({}) != y ({})".format(self.x, y))
14 print("end magic")
15 return magic
ValueError: x (4) != y (3)
I found this question while researching a very similar problem. My solution is to split the problem into two parts. First, you need to capture the data that you want to associate with the class methods. In this case, handler_for will associate a Unix command with handler for that command's output.
class OutputAnalysis(object):
"analyze the output of diagnostic commands"
def handler_for(name):
"decorator to associate a function with a command"
def wrapper(func):
func.handler_for = name
return func
return wrapper
# associate mount_p with 'mount_-p.txt'
#handler_for('mount -p')
def mount_p(self, slurped):
pass
Now that we've associated some data with each class method, we need to gather that data and store it in a class attribute.
OutputAnalysis.cmd_handler = {}
for value in OutputAnalysis.__dict__.itervalues():
try:
OutputAnalysis.cmd_handler[value.handler_for] = value
except AttributeError:
pass
I use this type of decorator in some debugging situations, it allows overriding class properties by decorating, without having to find the calling function.
class myclass(object):
def __init__(self):
self.property = "HELLO"
#adecorator(property="GOODBYE")
def method(self):
print self.property
Here is the decorator code
class adecorator (object):
def __init__ (self, *args, **kwargs):
# store arguments passed to the decorator
self.args = args
self.kwargs = kwargs
def __call__(self, func):
def newf(*args, **kwargs):
#the 'self' for a method function is passed as args[0]
slf = args[0]
# replace and store the attributes
saved = {}
for k,v in self.kwargs.items():
if hasattr(slf, k):
saved[k] = getattr(slf,k)
setattr(slf, k, v)
# call the method
ret = func(*args, **kwargs)
#put things back
for k,v in saved.items():
setattr(slf, k, v)
return ret
newf.__doc__ = func.__doc__
return newf
Note: because I've used a class decorator you'll need to use #adecorator() with the brackets on to decorate functions, even if you don't pass any arguments to the decorator class constructor.
The simple way to do it.
All you need is to put the decorator method outside the class.
You can still use it inside.
def my_decorator(func):
#this is the key line. There's the aditional self parameter
def wrap(self, *args, **kwargs):
# you can use self here as if you were inside the class
return func(self, *args, **kwargs)
return wrap
class Test(object):
#my_decorator
def bar(self):
pass
Declare in inner class.
This solution is pretty solid and recommended.
class Test(object):
class Decorators(object):
#staticmethod
def decorator(foo):
def magic(self, *args, **kwargs) :
print("start magic")
foo(self, *args, **kwargs)
print("end magic")
return magic
#Decorators.decorator
def bar( self ) :
print("normal call")
test = Test()
test.bar()
The result:
>>> test = Test()
>>> test.bar()
start magic
normal call
end magic
>>>
Decorators seem better suited to modify the functionality of an entire object (including function objects) versus the functionality of an object method which in general will depend on instance attributes. For example:
def mod_bar(cls):
# returns modified class
def decorate(fcn):
# returns decorated function
def new_fcn(self):
print self.start_str
print fcn(self)
print self.end_str
return new_fcn
cls.bar = decorate(cls.bar)
return cls
#mod_bar
class Test(object):
def __init__(self):
self.start_str = "starting dec"
self.end_str = "ending dec"
def bar(self):
return "bar"
The output is:
>>> import Test
>>> a = Test()
>>> a.bar()
starting dec
bar
ending dec
I have a Implementation of Decorators that Might Help
import functools
import datetime
class Decorator(object):
def __init__(self):
pass
def execution_time(func):
#functools.wraps(func)
def wrap(self, *args, **kwargs):
""" Wrapper Function """
start = datetime.datetime.now()
Tem = func(self, *args, **kwargs)
end = datetime.datetime.now()
print("Exection Time:{}".format(end-start))
return Tem
return wrap
class Test(Decorator):
def __init__(self):
self._MethodName = Test.funca.__name__
#Decorator.execution_time
def funca(self):
print("Running Function : {}".format(self._MethodName))
return True
if __name__ == "__main__":
obj = Test()
data = obj.funca()
print(data)
You can decorate the decorator:
import decorator
class Test(object):
#decorator.decorator
def _decorator(foo, self):
foo(self)
#_decorator
def bar(self):
pass
Given a class and a set of its methods - how can you determine from within that class which methods have been decorated with a certain decorator?
My goal is to basically get the actual values of the methods that are decorated, so something like:
class A():
def get_values(self):
...
# returned {'a-special-name': 1, 'b': 2}
#my_dec('a-special-name') # Ideally be able to also put optional name
def a(self):
return 1
#my_dec
def b(self):
return 2
Any idea on how to accomplish this?
Edit: this should also work on parent classes, that is, if A is a subclass of:
class B():
#my_dec
def c(self):
return 3
then get_values() of A instance should return {'a-special-name': 1, 'b': 2, 'c': 3} (order is irrelevant of course)
Edit: class based decorator that works but not with inheritance. Any idea how to make it work with inheritance but without having to decorate the class itself?
class my_dec(object):
def __init__(self, func, name=None):
self.func = func
self.name = name or func.__name__
self.func._some_flag = True
def __get__(self, instance, cls=None):
if instance is None:
return self
return self.func(instance)
If you can define the decorator yourself, then simply have it "mark" the method object in some way:
def my_dec(method):
method._this_be_decorated = True
return method
The class can then look for those marked methods; something like:
from inspect import isfunction
class A:
def get_values(self):
return filter(lambda i: isfunction(i) and hasattr(i, '_this_be_decorated'),
vars(type(self)).values())
This will return an iterable of function objects which you can process further as needed.
def my_dec(name):
if callable(name):
# name is callable – take its name
func = name # no make the code more readable
func.special_name = func.__name__
return func
else:
# name is the name to give – add an inner layer of functions
def inner(function_object):
function_object.special_name = name
return function_object
return inner
class A():
def get_values(self):
# return a dict of special name to call result mapping for every class member that has a special_name.
return {func.special_name: func(self) for func in self.__class__.__dict__.values() if hasattr(func, 'special_name')}
# returned {'a-special-name': 1, 'b': 2}
#my_dec('a-special-name') # Ideally be able to also put optional name
def a(self):
return 1
#my_dec
def b(self):
return 2
def no_dec(self):
return 42
should do what you want.
As deceze mentions, decorators can do whatever they want so there's no reliable generic answer. If you "own" the decorator you can add special properties to it's return value ie (Q&D py2.7 example):
def mydec(name=''):
# py27 hack - for py3 you want nonlocal instead
n = [name]
def innerdec(func):
# py27 hack - for py3 you want nonlocal instead
name = n[0] or func.__name__
def wrapper(*args, **kw):
print("in mydec.wrapper for {}".format(name))
return func(*args, **kw)
wrapper.ismydec = True # so we know this is decorated by mydec
wrapper.func = func # so we can get the original func
wrapper.name = name
return wrapper
return innerdec
def collect_dec(cls):
decorated = {}
for attname in dir(cls):
obj = getattr(cls, attname)
if getattr(obj, "ismydec", False):
decorated[obj.name] = obj.func
cls._decorated_funcs = decorated
return cls
#collect_dec
class A():
def get_values(self):
return {
name:func(self) for name, func in self._decorated_funcs.items()
}
#mydec('a-special-name') # Ideally be able to also put optional name
def a(self):
return 1
#mydec() # no name
def b(self):
return 2
a = A()
print(a.get_values())
Which outputs:
{'a-special-name': 1, 'b': 2}
I'm trying to decorate all methods in class and i succeded with this code, but i'm also trying to log calls to operators like * + - / , is there any way to decorate them or something like getattr(self,"*") to log the calls ?
class Logger(object):
def __init__(self, bool):
self.bool = bool
def __call__(self, cls):
class DecoratedClass(cls):
def __init__(cls, *args, **kwargs):
super().__init__(*args, **kwargs)
if not(self.bool):
return
methods = [func for func in dir(cls)
if callable(getattr(cls, func))
and not func.startswith("__class")]
for func in methods:
old_func = getattr(cls, func)
def decorated_function(fname, fn):
def loggedFunction(*args, **kwargs):
print("Calling {0} from {3} with params {1} and kwargs {2}".format(fname.upper(), args, kwargs, cls))
return fn(*args, **kwargs)
return loggedFunction
setattr(cls, func, decorated_function(func, old_func))
return DecoratedClass
#Logger(True)
class DummyClass():
def __init__(self,foo):
self.foo = foo
def bar(self):
print(self.foo)
def __mul__(self,other):
print("Hello",other)
if __name__ == '__main__':
a = DummyClass('hola')
a.method()
a.__mul__(a) #this is logged
print(a*a) #this is not logged by decorator
Thanks to Łukasz, here is a working script.
A difficulty I encountered is to handle multiple instances and avoid to decorate multiple times the same class methods. To handle this problem, I keep track of the decorated class methods (cls.__logged).
Another difficulty is to deal with the magic methods like __setattr__, __getattribute__, __repr__, ... My solution is to ignore them, except for a list that you must define at start (loggable_magic_methods).
from functools import wraps
loggable_magic_methods = ['__mul__',]
def is_magic_method(method):
return method.startswith('__')
class Logger(object):
def __init__(self, bool):
self.bool = bool
def __call__(self, cls):
class LoggedClass(cls):
cls.__logged = []
def __init__(instance, *args, **kwargs):
super().__init__(*args, **kwargs)
if not(self.bool):
return
methods = [funcname for funcname in dir(instance)
if callable(getattr(instance, funcname))
and (funcname in loggable_magic_methods or not is_magic_method(funcname))]
def logged(method):
#wraps(method)
def wrapper(*args, **kwargs):
print (method.__name__, args, kwargs, cls)
return method(*args, **kwargs)
return wrapper
for funcname in methods:
if funcname in cls.__logged:
continue
if is_magic_method(funcname):
setattr(cls, funcname, logged(getattr(cls, funcname)))
cls.__logged.append(funcname)
else:
setattr(instance, funcname, logged(getattr(instance, funcname)))
return LoggedClass
#Logger(True)
class DummyClass():
def __init__(self, foo, coef):
self.foo = foo
self.coef = coef
def bar(self):
print(self.foo)
def __mul__(self, other):
print(self.foo)
print(other.foo)
return self.coef * other.coef
if __name__ == '__main__':
a = DummyClass('hola', 1)
a.bar()
print()
print(a.__mul__(a))
print()
print(a*a)
print()
b = DummyClass('gracias', 2)
b.bar()
print()
print(b.__mul__(a))
print()
print(b*a)
Currently you are patching values on instance. Your usage of cls in __init__ signature is false friend - actually it's old plain self in this case.
If you want to override magic methods, interpreter looks for them on class objects, not on instances.
Minimal example:
class DummyClass:
def __init__(self, foo):
self.foo = foo
def __mul__(self, other):
return self.foo * other.foo
def logged(method):
def wrapper(*args, **kwargs):
print (method.__name__, args, kwargs)
return method(*args, **kwargs)
return wrapper
DummyClass.__mul__ = logged(DummyClass.__mul__)
a = DummyClass(1)
b = DummyClass(2)
assert a * a == 1
assert a * b == 2
assert b * b == 4
Each call is logged.
>>> a = DummyClass(1)
>>> b = DummyClass(2)
>>> assert a * a == 1
__mul__ (<__main__.DummyClass object at 0x00000000011BFEB8>, <__main__.DummyClass object at 0x00000000011BFEB8>) {}
>>> assert a * b == 2
__mul__ (<__main__.DummyClass object at 0x00000000011BFEB8>, <__main__.DummyClass object at 0x00000000011BF080>) {}
>>> assert b * b == 4
__mul__ (<__main__.DummyClass object at 0x00000000011BF080>, <__main__.DummyClass object at 0x00000000011BF080>) {}
I'll leave a task of rewriting monkey-patching approach to you.
I am defining a base class in python like
class Base(object):
def __init__(self):
self._changed = False
and some derived classes:
class Car(Base):
def set_type(self, type_):
# do something
def set_mileage(self, mileage):
# do something
class Flower(base):
def set_name(self, name):
# do something
In this example I now want to set the attribute '_changed' to Truewhenever I call a set method of one of the derived classes. I simply could add the line
self._changed = True
to every set method, or use a decorator, but I am looking for a more convenient and automatic way to do this whenever a method is called whose name starts with 'set_'. I am thinking using __getattribute__ like in the following not tried (and not working example:
def __getattribute__(self, name):
if name.startswith('set_'):
self._changed = True
return self.__getattribute__(name)
So how to implement this in the correct way?
Update: A fully working example this time using a metaclass and descriptor with both setter and a getter:
class Field(object):
def __get__(self, ins, type):
return getattr(ins, self.field_name, None)
def __set__(self, ins, val):
setattr(ins, self.field_name, val)
ins._changed = True
class Meta(type):
def __new__(cls, clsname, bases, dct):
for k, v in dct.items():
if isinstance(v, Field):
v.field_name = '_' + k
return type.__new__(cls, clsname, bases, dct)
class Base(object):
__metaclass__ = Meta
def __init__(self):
self._changed = False
class Car(Base):
type = Field()
mileage = Field()
class Flower(Base):
name = Field()
Demo:
>>> c = Car()
>>> c._changed
False
>>> c.type = "4X4"
>>> c._changed
True
>>> c1 = Car()
>>> c1._changed
False
>>> c1.mileage = 100
>>> c1._changed
True
>>> c.type
'4X4'
>>> c1.mileage
100
>>> f = Flower()
>>> f._changed
False
>>> f.name = "Rose"
>>> f._changed
True
>>> f.name
'Rose'
I would use a decorator for this. Something like this (not tested):
def isGet(func):
def newFunc(self, var):
self._changed = True
func(self, var)
return
return newFunc
And then in any get method you want this behaviour, you simply do
#isGet
def set_mileage(self, mileage):
# dosomething
A metaclass would work here:
from types import FunctionType
from functools import wraps
class Setter(type):
def __new__(cls, clsname, bases, dct):
for item in dct:
if item.startswith("set_") and isinstance(dct[item], FunctionType):
dct[item] = cls.changer(dct[item])
return super(Setter, cls).__new__(cls, clsname, bases, dct)
#staticmethod
def changer(func):
#wraps(func)
def wrapper(self, *args, **kwargs):
self._changed = True
return func(self, *args, **kwargs)
return wrapper
class Base(object):
__metaclass__ = Setter
def __init__(self):
self._changed = False
Then just inherit from Base like you normally would.
Sample usage:
>>> from meta import Car
>>> c = Car()
>>> c._changed
False
>>> c.set_type("blah")
ok
>>> c._changed
True
The metaclass is just automatically decorating any method in your class' __dict__ that starts with set_.
It seems that mymethod is not yet a method when the decorator is called.
import inspect
class decorator(object):
def __call__(self, call):
if inspect.ismethod(call): #Not working yet
obj = "method"
args = inspect.getargspec(call)[0][1:]
elif inspect.isfunction(call):
obj = "function"
args = inspect.getargspec(call)[0]
elif inspect.isclass(call):
obj = "class"
args = inspect.getargspec(call.__init__)[0][1:]
args="(%s)" % repr(args)[1:-1].replace("'","")
print "Decorate %s %s%s" % (obj, call.__name__, args)
return call
#decorator()
def myfunction (a,b): pass
#decorator()
class myclass():
def __init__(self, a, b): pass
#decorator()
def mymethod(self, a, b): pass
if inspect.isfunction(myclass.mymethod):
print "mymethod is a function"
if inspect.ismethod(myclass.mymethod):
print "mymethod is a method"
Output:
Decorate function myfunction(a, b)
Decorate function mymethod(self, a, b)
Decorate class myclass(a, b)
mymethod is a method
I would know if the first argument is 'self', but there will be a less dirty solution?
Edit: Why?
I want to populate a list of callables and their arguments, if it is a function or a class, and I can pass the expected arguments, then I call it, but if it is a method, I have no "self" argument to pass. Something like:
import inspect
class ToDo(object):
calls=[]
def do(self, **kwargs):
for call in self.calls:
if 'self' in call.args:
print "This will fail."
args = {}
for arg in call.args:
args[arg]=kwargs.get(arg, None)
call.call(**args)
TODO = ToDo()
class decorator(object):
def __call__(self, call):
if inspect.isfunction(call):
args = inspect.getargspec(call)[0]
elif inspect.isclass(call):
args = inspect.getargspec(call.__init__)[0][1:]
self.call = call
self.args = args
TODO.calls.append(self)
return call
TODO.do(a=1, b=2)
You can't really make that distinction. Here's an example:
>>> class A(object):
... pass
...
>>> def foo(x): return 3
...
>>> A.foo = foo
>>> type(foo)
<type 'function'>
>>> type(A.foo)
<type 'instancemethod'>
As you can see, your decorator could apply to foo, since it is a function. But you can then simply create a class attribute that references the function to create a decorated method.
(This example is from Python 2.7; I'm not sure if anything has changed in Python 3 to make the above behave differently.)
You cannot tell method from function but you can check if first argument looks like self:
def __call__(self, func):
def new_func(*args, **kw):
if len(args) and hasattr(args[0], '__dict__') \
and '__class__' in dir(args[0]) and func.__name__ in dir(args[0])\
and '__func__' in dir(getattr(args[0], func.__name__))\
and getattr(args[0], func.__name__).__func__ == self.func:
return my_func(*args[1:], **kw)
else:
return my_func(*args, **kw)
self.func = new_func
return new_func
But that won't work for nested decorators - next decorator will change the function and comparison with self.func won't work.
Another approach - to check if first argument's name of decorated function is self - this is
very strong convention in Python so may be good enough:
def __call__(self, func):
def new_func(*args, **kw):
if len(inspect.getfullargspec(func).args)\
and inspect.getfullargspec(func).args[0] == 'self':
return my_func(*args[1:], **kw)
else:
return my_func(*args, **kw)
self.func = new_func
return new_func