Currently when I want to define a setter and leave getter alone I do this:
#property
def my_property(self):
return self._my_property
#my_property.setter
def my_property(self, value):
value.do_some_magic()
self._my_property = value
Is there any way to make it shorter? I'd like to skip this part as it always look the same:
#property
def my_property(self):
return self._my_property
There's no out of the box solution, but you can try something like this:
def defprop(name):
def getter(self):
return getattr(self, name)
return property(getter)
class C(object):
# ...
my_dictionary = defprop('_my_dictionary')
# ...
That does not save you that many keystrokes though, you still have to duplicate the attribute name. Besides it's less explicit.
Update: after thinking a bit, I've come up with this descriptor-based hackish trick (disclaimer: this is done just for a demonstration, I don't imply it's a good practice unless you have a damn good reason to do so):
class with_default_getter(object):
def __init__(self, func):
self._attr_name = '_{0.__name__}'.format(func)
self._setter = func
def __get__(self, obj, type):
return getattr(obj, self._attr_name)
def __set__(self, obj, value):
return self._setter(obj, value)
Usage:
class C(object):
#with_default_getter
def my_property(self, value):
print 'setting %s'
self._my_property = value
>>> c = C()
>>> c.my_property = 123
setting 123
>>> c.my_property
123
This is pretty much the same as #georg suggests, just unfolds the implementation down to descriptors.
You can make a decorator that auto-creates the getter, following the underscores convention:
def setter(fn):
def _get(self):
return getattr(self, '_' + fn.__name__)
def _set(self, val):
return fn(self, val)
return property(_get, _set)
or more concisely, if you like this style more:
def setter(fn):
return property(
lambda self: getattr(self, '_' + fn.__name__),
fn)
Usage:
class X(object):
#setter
def my_property(self, value):
self._my_property = value + 1
x = X()
x.my_property = 42
print x.my_property # 43
There is no shortcut that I am aware of- remember explicit is better than implicit (from the Zen of python).
It could be that in your code so far, a property is always like that - but you could at some point write a a property getter which fetches an entirely calculated value - in which case your property getter and setter wont look like that at all.
Haveing said that you could write a wrapper which provides those simple default methods as part of the wrapper, if you wish.
def set_my_property(self, value):
value.do_some_magic()
self._my_property = value
my_property = property(fset=set_my_property)
Related
So I have a class with a method, which takes string. Somethinkg like this:
class A():
def func(self, name):
# do some stuff with it
I have finite number of possible values, [val1, val2, val2] for example, All strings. I want to use them like this:
a = A()
a.val1() # actually a.func(val1)
I tried to combine decorators and setattr:
class A():
def func(self, val):
# do some stuff with it
def register(self, val):
def wrapper(self):
self.func(val)
setattr(self, val, wrapper)
So I can iterate through all possible values in run-time:
a = A()
for val in vals:
a.register(val)
And it has zero effect. Usually setattr adds new attribute with value None, but in this case nothing happens. Can somebody explain why it is this way and what can I do?
register() isn't a decorator, it's mostly just a "function factory" with side-effects. Also, as I said in a comment, setattr() needs to know what name to assigned to the value.
Here's a way to get your code to work:
class A():
def func(self, val):
# do some stuff with it
print('func({}) called'.format(val))
def register(self, val, name):
def wrapper():
self.func(val)
wrapper.__name__ = name
setattr(self, name, wrapper)
vals = 10, 20, 30
a = A()
for i, val in enumerate(vals, 1):
a.register(val, 'val'+str(i)) # Creates name argument.
a.val1() # -> func(10) called
a.val2() # -> func(20) called
I have a class in which a method first needs to verify that an attribute is present and otherwise call a function to compute it. Then, ensuring that the attribute is not None, it performs some operations with it. I can see two slightly different design choices:
class myclass():
def __init__(self):
self.attr = None
def compute_attribute(self):
self.attr = 1
def print_attribute(self):
if self.attr is None:
self.compute_attribute()
print self.attr
And
class myclass2():
def __init__(self):
pass
def compute_attribute(self):
self.attr = 1
return self.attr
def print_attribute(self):
try:
attr = self.attr
except AttributeError:
attr = self.compute_attribute()
if attr is not None:
print attr
In the first design, I need to make sure that all the class attributes are set to None in advance, which can become verbose but also clarify the structure of the object.
The second choice seems to be the more widely used one. However, for my purposes (scientific computing related to information theory) using try except blocks everywhere can be a bit of an overkill given that this class doesn't really interact with other classes, it just takes data and computes a bunch of things.
Firstly, you can use hasattr to check if an object has an attribute, it returns True if the attribute exists.
hasattr(object, attribute) # will return True if the object has the attribute
Secondly, You can customise attribute access in Python, you can read more about it here: https://docs.python.org/2/reference/datamodel.html#customizing-attribute-access
Basically, you override the __getattr__ method to achieve this, so something like:
class myclass2():
def init(self):
pass
def compute_attr(self):
self.attr = 1
return self.attr
def print_attribute(self):
print self.attr
def __getattr__(self, name):
if hasattr(self, name) and getattr(self, name)!=None:
return getattr(self, name):
else:
compute_method="compute_"+name;
if hasattr(self, compute_method):
return getattr(self, compute_method)()
Make sure you only use getattr to access the attribute within __getattr__ or you'll end up with infinite recursion
Based on the answer jonrsharpe linked, I offer a third design choice. The idea here is that no special conditional logic is required at all either by the clients of MyClass or by code within MyClass itself. Instead, a decorator is applied to a function that does the (hypothetically expensive) computation of the property, and then that result is stored.
This means that the expensive computation is done lazily (only if a client tries to access the property) and only performed once.
def lazyprop(fn):
attr_name = '_lazy_' + fn.__name__
#property
def _lazyprop(self):
if not hasattr(self, attr_name):
setattr(self, attr_name, fn(self))
return getattr(self, attr_name)
return _lazyprop
class MyClass(object):
#lazyprop
def attr(self):
print('Generating attr')
return 1
def __repr__(self):
return str(self.attr)
if __name__ == '__main__':
o = MyClass()
print(o.__dict__, end='\n\n')
print(o, end='\n\n')
print(o.__dict__, end='\n\n')
print(o)
Output
{}
Generating attr
1
{'_lazy_attr': 1}
1
Edit
Application of Cyclone's answer to OP's context:
class lazy_property(object):
'''
meant to be used for lazy evaluation of an object attribute.
property should represent non-mutable data, as it replaces itself.
'''
def __init__(self, fget):
self.fget = fget
self.func_name = fget.__name__
def __get__(self, obj, cls):
if obj is None:
return None
value = self.fget(obj)
setattr(obj, self.func_name, value)
return value
class MyClass(object):
#lazy_property
def attr(self):
print('Generating attr')
return 1
def __repr__(self):
return str(self.attr)
if __name__ == '__main__':
o = MyClass()
print(o.__dict__, end='\n\n')
print(o, end='\n\n')
print(o.__dict__, end='\n\n')
print(o)
The output is identical to above.
I want to build various setter and getter. Fot not copy and paste the code, I thought something to solve it. Can decorator do it?
#property
def !!variable_name!!(self):
return self.__!!variable_name!!
#!!variable_name!!.setter
def !!variable_name!!(self, input):
self.__!!variable_name!! = input
Is it possible like macro in C?
It's unclear why you would want to do something like this—create a property with setter that ignores its value argument—but the answer is "Yes", you can do it by creating a function that returns a custom property object:
However you can't use # syntax to apply it. Instead you have to utilize it as shown:
def attribute_property(name, input_value):
STORAGE_NAME = '_' + name
#property
def prop(self):
return getattr(self, STORAGE_NAME)
#prop.setter
def prop(self, ignored):
setattr(self, STORAGE_NAME, input_value)
return prop
# EXAMPLE USAGE
class Person(object):
name = attribute_property('name', 'Monty')
def __init__(self, name, age):
self.name = name # ignores value of passed "name" argument!
self.age = age
user = Person('Rodrigo', 42)
print('user.name: {!r}'.format(user.name))
print('user.age: {!r}'.format(user.age))
Output:
user.name: 'Monty'
user.age: 42
Simple answer: Yes, that's possible using the descriptor protocol. For example you want to save variables with a leading underscore and access them without the leading underscore such a descriptor would work:
from six import string_types
class DescriptorSingleLeadingUnderscore(object):
def __init__(self, attr, doc=""):
if not isinstance(attr, string_types):
# Not a string so take the documentation (if avaiable) and name
# from the method.
if attr.__doc__:
doc = attr.__doc__
attr = attr.__name__
self.__doc__ = doc # Set the documentation of the instance.
self.attr = '_' + attr # Add leading underscore to the attribute name
def __get__(self, instance, owner=None):
if instance is None:
return self
return getattr(instance, self.attr, None)
def __set__(self, instance, value):
setattr(instance, self.attr, value)
def __delete__(self, instance):
delattr(instance, self.attr)
class X(object):
someproperty = DescriptorSingleLeadingUnderscore('someproperty')
someproperty1 = DescriptorSingleLeadingUnderscore('someproperty1')
someproperty2 = DescriptorSingleLeadingUnderscore('someproperty2')
someproperty3 = DescriptorSingleLeadingUnderscore('someproperty3')
#DescriptorSingleLeadingUnderscore
def it_also_works_as_decorator(self):
pass # this code is never executed!
And a test case:
>>> x = X()
>>> x.someproperty = 100
>>> x.someproperty
100
>>> x._someproperty
100
>>> x.it_also_works_as_decorator = 100
>>> x.it_also_works_as_decorator
100
>>> x._it_also_works_as_decorator
100
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.
I want to create a decorator that works like a property, only it calls the decorated function only once, and on subsequent calls always return the result of the first call. An example:
def SomeClass(object):
#LazilyInitializedProperty
def foo(self):
print "Now initializing"
return 5
>>> x = SomeClass()
>>> x.foo
Now initializing
5
>>> x.foo
5
My idea was to write a custom decorator for this. So i started, and this is how far I came:
class LazilyInitializedProperty(object):
def __init__(self, function):
self._function = function
def __set__(self, obj, value):
raise AttributeError("This property is read-only")
def __get__(self, obj, type):
# problem: where to store the value once we have calculated it?
As you can see, I do not know where to store the cached value. The simplest solution seems to be to just maintain a dictionary, but I am wondering if there is a more elegant solution for this.
EDIT Sorry for that, I forgot to mention that I want the property to be read-only.
Denis Otkidach's CachedAttribute is a method decorator which makes attributes lazy (computed once, accessible many). To make it also read-only, I added a __set__ method. To retain the ability to recalculate (see below) I added a __delete__ method:
class ReadOnlyCachedAttribute(object):
'''Computes attribute value and caches it in the instance.
Source: Python Cookbook
Author: Denis Otkidach https://stackoverflow.com/users/168352/denis-otkidach
This decorator allows you to create a property which can be computed once and
accessed many times. Sort of like memoization
'''
def __init__(self, method, name=None):
self.method = method
self.name = name or method.__name__
self.__doc__ = method.__doc__
def __get__(self, inst, cls):
if inst is None:
return self
elif self.name in inst.__dict__:
return inst.__dict__[self.name]
else:
result = self.method(inst)
inst.__dict__[self.name]=result
return result
def __set__(self, inst, value):
raise AttributeError("This property is read-only")
def __delete__(self,inst):
del inst.__dict__[self.name]
For example:
if __name__=='__main__':
class Foo(object):
#ReadOnlyCachedAttribute
# #read_only_lazyprop
def bar(self):
print 'Calculating self.bar'
return 42
foo=Foo()
print(foo.bar)
# Calculating self.bar
# 42
print(foo.bar)
# 42
try:
foo.bar=1
except AttributeError as err:
print(err)
# This property is read-only
del(foo.bar)
print(foo.bar)
# Calculating self.bar
# 42
One of the beautiful things about CachedAttribute (and
ReadOnlyCachedAttribute) is that if you del foo.bar, then the next time you
access foo.bar, the value is re-calculated. (This magic is made possible by
the fact that del foo.bar removes 'bar' from foo.__dict__ but the property
bar remains in Foo.__dict__.)
If you don't need or don't want this ability to recalculate,
then the following (based on Mike Boers' lazyprop) is a simpler way to make a read-only lazy property.
def read_only_lazyprop(fn):
attr_name = '_lazy_' + fn.__name__
#property
def _lazyprop(self):
if not hasattr(self, attr_name):
setattr(self, attr_name, fn(self))
return getattr(self, attr_name)
#_lazyprop.setter
def _lazyprop(self,value):
raise AttributeError("This property is read-only")
return _lazyprop