I have a class like:
class MyClass:
Foo = 1
Bar = 2
Whenever MyClass.Foo or MyClass.Bar is invoked, I need a custom method to be invoked before the value is returned. Is it possible in Python? I know it is possible if I create an instance of the class and I can define my own __getattr__ method. But my scnenario involves using this class as such without creating any instance of it.
Also I need a custom __str__ method to be invoked when str(MyClass.Foo) is invoked. Does Python provide such an option?
__getattr__() and __str__() for an object are found on its class, so if you want to customize those things for a class, you need the class-of-a-class. A metaclass.
class FooType(type):
def _foo_func(cls):
return 'foo!'
def _bar_func(cls):
return 'bar!'
def __getattr__(cls, key):
if key == 'Foo':
return cls._foo_func()
elif key == 'Bar':
return cls._bar_func()
raise AttributeError(key)
def __str__(cls):
return 'custom str for %s' % (cls.__name__,)
class MyClass(metaclass=FooType):
pass
# # in python 2:
# class MyClass:
# __metaclass__ = FooType
print(MyClass.Foo)
print(MyClass.Bar)
print(str(MyClass))
printing:
foo!
bar!
custom str for MyClass
And no, an object can't intercept a request for a stringifying one of its attributes. The object returned for the attribute must define its own __str__() behavior.
Updated 2023-02-20 for Python 3.x default implementation (python 2 as a comment).
(I know this is an old question, but since all the other answers use a metaclass...)
You can use the following simple classproperty descriptor:
class classproperty(object):
""" #classmethod+#property """
def __init__(self, f):
self.f = classmethod(f)
def __get__(self, *a):
return self.f.__get__(*a)()
Use it like:
class MyClass(object):
#classproperty
def Foo(cls):
do_something()
return 1
#classproperty
def Bar(cls):
do_something_else()
return 2
For the first, you'll need to create a metaclass, and define __getattr__() on that.
class MyMetaclass(type):
def __getattr__(self, name):
return '%s result' % name
class MyClass(object):
__metaclass__ = MyMetaclass
print MyClass.Foo
For the second, no. Calling str(MyClass.Foo) invokes MyClass.Foo.__str__(), so you'll need to return an appropriate type for MyClass.Foo.
Surprised no one pointed this one out:
class FooType(type):
#property
def Foo(cls):
return "foo!"
#property
def Bar(cls):
return "bar!"
class MyClass(metaclass=FooType):
pass
Works:
>>> MyClass.Foo
'foo!'
>>> MyClass.Bar
'bar!'
(for Python 2.x, change definition of MyClass to:
class MyClass(object):
__metaclass__ = FooType
)
What the other answers say about str holds true for this solution: It must be implemented on the type actually returned.
Depending on the case I use this pattern
class _TheRealClass:
def __getattr__(self, attr):
pass
LooksLikeAClass = _TheRealClass()
Then you import and use it.
from foo import LooksLikeAClass
LooksLikeAClass.some_attribute
This avoid use of metaclass, and handle some use cases.
Related
Consider this class:
class foo(object):
pass
The default string representation looks something like this:
>>> str(foo)
"<class '__main__.foo'>"
How can I make this display a custom string?
See How to print instances of a class using print()? for the corresponding question about instances of the class.
In fact, this question is really a special case of that one - because in Python, classes are themselves also objects belonging to their own class - but it's not directly obvious how to apply the advice, since the default "class of classes" is pre-defined.
Implement __str__() or __repr__() in the class's metaclass.
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object):
__metaclass__ = MC
print(C)
Use __str__ if you mean a readable stringification, use __repr__ for unambiguous representations.
Edit: Python 3 Version
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object, metaclass=MC):
pass
print(C)
class foo(object):
def __str__(self):
return "representation"
def __unicode__(self):
return u"representation"
If you have to choose between __repr__ or __str__ go for the first one, as by default implementation __str__ calls __repr__ when it wasn't defined.
Custom Vector3 example:
class Vector3(object):
def __init__(self, args):
self.x = args[0]
self.y = args[1]
self.z = args[2]
def __repr__(self):
return "Vector3([{0},{1},{2}])".format(self.x, self.y, self.z)
def __str__(self):
return "x: {0}, y: {1}, z: {2}".format(self.x, self.y, self.z)
In this example, repr returns again a string that can be directly consumed/executed, whereas str is more useful as a debug output.
v = Vector3([1,2,3])
print repr(v) #Vector3([1,2,3])
print str(v) #x:1, y:2, z:3
Ignacio Vazquez-Abrams' approved answer is quite right. It is, however, from the Python 2 generation. An update for the now-current Python 3 would be:
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object, metaclass=MC):
pass
print(C)
If you want code that runs across both Python 2 and Python 3, the six module has you covered:
from __future__ import print_function
from six import with_metaclass
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(with_metaclass(MC)):
pass
print(C)
Finally, if you have one class that you want to have a custom static repr, the class-based approach above works great. But if you have several, you'd have to generate a metaclass similar to MC for each, and that can get tiresome. In that case, taking your metaprogramming one step further and creating a metaclass factory makes things a bit cleaner:
from __future__ import print_function
from six import with_metaclass
def custom_class_repr(name):
"""
Factory that returns custom metaclass with a class ``__repr__`` that
returns ``name``.
"""
return type('whatever', (type,), {'__repr__': lambda self: name})
class C(with_metaclass(custom_class_repr('Wahaha!'))): pass
class D(with_metaclass(custom_class_repr('Booyah!'))): pass
class E(with_metaclass(custom_class_repr('Gotcha!'))): pass
print(C, D, E)
prints:
Wahaha! Booyah! Gotcha!
Metaprogramming isn't something you generally need everyday—but when you need it, it really hits the spot!
Just adding to all the fine answers, my version with decoration:
from __future__ import print_function
import six
def classrep(rep):
def decorate(cls):
class RepMetaclass(type):
def __repr__(self):
return rep
class Decorated(six.with_metaclass(RepMetaclass, cls)):
pass
return Decorated
return decorate
#classrep("Wahaha!")
class C(object):
pass
print(C)
stdout:
Wahaha!
The down sides:
You can't declare C without a super class (no class C:)
C instances will be instances of some strange derivation, so it's probably a good idea to add a __repr__ for the instances as well.
Because you need a metaclass to do this, but you need the metaclass itself to have a parameter, you can do it with a metaclass that captures the name via lexical scope.
I find this a bit easier to read / follow than some of the alternatives.
class type_: pass
def create_type(name):
# we do this so that we can print the class type out
# otherwise we must instantiate it to get a proper print out
class type_metaclass(type):
def __repr__(self):
return f'<{name}>'
class actual_type(type_, metaclass=type_metaclass):
pass
return actual_type
my_type = create_type('my_type')
print(my_type)
# prints "<my_type>"
Another answer, with:
decorator
types (so you keep auto-complete in IDEs)
works as of v3.10
import typing
class ClassReprMeta(type):
def __repr__(self):
attrs_str = ", ".join(
f"{key}={getattr(self, key)}"
for key in dir(self)
if not key.startswith("_")
)
return f"{self.__name__}({attrs_str})"
T = typing.TypeVar("T")
def printable_class(cls: T) -> T:
"""Decorator to make a class object printable"""
return ClassReprMeta(cls.__name__, cls.__bases__, dict(cls.__dict__))
#printable_class
class CONFIG:
FIRST = 1
SECOND = 2
print(CONFIG) # CONFIG(FIRST=1, SECOND=2)
Consider this class:
class foo(object):
pass
The default string representation looks something like this:
>>> str(foo)
"<class '__main__.foo'>"
How can I make this display a custom string?
See How to print instances of a class using print()? for the corresponding question about instances of the class.
In fact, this question is really a special case of that one - because in Python, classes are themselves also objects belonging to their own class - but it's not directly obvious how to apply the advice, since the default "class of classes" is pre-defined.
Implement __str__() or __repr__() in the class's metaclass.
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object):
__metaclass__ = MC
print(C)
Use __str__ if you mean a readable stringification, use __repr__ for unambiguous representations.
Edit: Python 3 Version
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object, metaclass=MC):
pass
print(C)
class foo(object):
def __str__(self):
return "representation"
def __unicode__(self):
return u"representation"
If you have to choose between __repr__ or __str__ go for the first one, as by default implementation __str__ calls __repr__ when it wasn't defined.
Custom Vector3 example:
class Vector3(object):
def __init__(self, args):
self.x = args[0]
self.y = args[1]
self.z = args[2]
def __repr__(self):
return "Vector3([{0},{1},{2}])".format(self.x, self.y, self.z)
def __str__(self):
return "x: {0}, y: {1}, z: {2}".format(self.x, self.y, self.z)
In this example, repr returns again a string that can be directly consumed/executed, whereas str is more useful as a debug output.
v = Vector3([1,2,3])
print repr(v) #Vector3([1,2,3])
print str(v) #x:1, y:2, z:3
Ignacio Vazquez-Abrams' approved answer is quite right. It is, however, from the Python 2 generation. An update for the now-current Python 3 would be:
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object, metaclass=MC):
pass
print(C)
If you want code that runs across both Python 2 and Python 3, the six module has you covered:
from __future__ import print_function
from six import with_metaclass
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(with_metaclass(MC)):
pass
print(C)
Finally, if you have one class that you want to have a custom static repr, the class-based approach above works great. But if you have several, you'd have to generate a metaclass similar to MC for each, and that can get tiresome. In that case, taking your metaprogramming one step further and creating a metaclass factory makes things a bit cleaner:
from __future__ import print_function
from six import with_metaclass
def custom_class_repr(name):
"""
Factory that returns custom metaclass with a class ``__repr__`` that
returns ``name``.
"""
return type('whatever', (type,), {'__repr__': lambda self: name})
class C(with_metaclass(custom_class_repr('Wahaha!'))): pass
class D(with_metaclass(custom_class_repr('Booyah!'))): pass
class E(with_metaclass(custom_class_repr('Gotcha!'))): pass
print(C, D, E)
prints:
Wahaha! Booyah! Gotcha!
Metaprogramming isn't something you generally need everyday—but when you need it, it really hits the spot!
Just adding to all the fine answers, my version with decoration:
from __future__ import print_function
import six
def classrep(rep):
def decorate(cls):
class RepMetaclass(type):
def __repr__(self):
return rep
class Decorated(six.with_metaclass(RepMetaclass, cls)):
pass
return Decorated
return decorate
#classrep("Wahaha!")
class C(object):
pass
print(C)
stdout:
Wahaha!
The down sides:
You can't declare C without a super class (no class C:)
C instances will be instances of some strange derivation, so it's probably a good idea to add a __repr__ for the instances as well.
Because you need a metaclass to do this, but you need the metaclass itself to have a parameter, you can do it with a metaclass that captures the name via lexical scope.
I find this a bit easier to read / follow than some of the alternatives.
class type_: pass
def create_type(name):
# we do this so that we can print the class type out
# otherwise we must instantiate it to get a proper print out
class type_metaclass(type):
def __repr__(self):
return f'<{name}>'
class actual_type(type_, metaclass=type_metaclass):
pass
return actual_type
my_type = create_type('my_type')
print(my_type)
# prints "<my_type>"
Another answer, with:
decorator
types (so you keep auto-complete in IDEs)
works as of v3.10
import typing
class ClassReprMeta(type):
def __repr__(self):
attrs_str = ", ".join(
f"{key}={getattr(self, key)}"
for key in dir(self)
if not key.startswith("_")
)
return f"{self.__name__}({attrs_str})"
T = typing.TypeVar("T")
def printable_class(cls: T) -> T:
"""Decorator to make a class object printable"""
return ClassReprMeta(cls.__name__, cls.__bases__, dict(cls.__dict__))
#printable_class
class CONFIG:
FIRST = 1
SECOND = 2
print(CONFIG) # CONFIG(FIRST=1, SECOND=2)
Consider this class:
class foo(object):
pass
The default string representation looks something like this:
>>> str(foo)
"<class '__main__.foo'>"
How can I make this display a custom string?
See How to print instances of a class using print()? for the corresponding question about instances of the class.
In fact, this question is really a special case of that one - because in Python, classes are themselves also objects belonging to their own class - but it's not directly obvious how to apply the advice, since the default "class of classes" is pre-defined.
Implement __str__() or __repr__() in the class's metaclass.
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object):
__metaclass__ = MC
print(C)
Use __str__ if you mean a readable stringification, use __repr__ for unambiguous representations.
Edit: Python 3 Version
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object, metaclass=MC):
pass
print(C)
class foo(object):
def __str__(self):
return "representation"
def __unicode__(self):
return u"representation"
If you have to choose between __repr__ or __str__ go for the first one, as by default implementation __str__ calls __repr__ when it wasn't defined.
Custom Vector3 example:
class Vector3(object):
def __init__(self, args):
self.x = args[0]
self.y = args[1]
self.z = args[2]
def __repr__(self):
return "Vector3([{0},{1},{2}])".format(self.x, self.y, self.z)
def __str__(self):
return "x: {0}, y: {1}, z: {2}".format(self.x, self.y, self.z)
In this example, repr returns again a string that can be directly consumed/executed, whereas str is more useful as a debug output.
v = Vector3([1,2,3])
print repr(v) #Vector3([1,2,3])
print str(v) #x:1, y:2, z:3
Ignacio Vazquez-Abrams' approved answer is quite right. It is, however, from the Python 2 generation. An update for the now-current Python 3 would be:
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object, metaclass=MC):
pass
print(C)
If you want code that runs across both Python 2 and Python 3, the six module has you covered:
from __future__ import print_function
from six import with_metaclass
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(with_metaclass(MC)):
pass
print(C)
Finally, if you have one class that you want to have a custom static repr, the class-based approach above works great. But if you have several, you'd have to generate a metaclass similar to MC for each, and that can get tiresome. In that case, taking your metaprogramming one step further and creating a metaclass factory makes things a bit cleaner:
from __future__ import print_function
from six import with_metaclass
def custom_class_repr(name):
"""
Factory that returns custom metaclass with a class ``__repr__`` that
returns ``name``.
"""
return type('whatever', (type,), {'__repr__': lambda self: name})
class C(with_metaclass(custom_class_repr('Wahaha!'))): pass
class D(with_metaclass(custom_class_repr('Booyah!'))): pass
class E(with_metaclass(custom_class_repr('Gotcha!'))): pass
print(C, D, E)
prints:
Wahaha! Booyah! Gotcha!
Metaprogramming isn't something you generally need everyday—but when you need it, it really hits the spot!
Just adding to all the fine answers, my version with decoration:
from __future__ import print_function
import six
def classrep(rep):
def decorate(cls):
class RepMetaclass(type):
def __repr__(self):
return rep
class Decorated(six.with_metaclass(RepMetaclass, cls)):
pass
return Decorated
return decorate
#classrep("Wahaha!")
class C(object):
pass
print(C)
stdout:
Wahaha!
The down sides:
You can't declare C without a super class (no class C:)
C instances will be instances of some strange derivation, so it's probably a good idea to add a __repr__ for the instances as well.
Because you need a metaclass to do this, but you need the metaclass itself to have a parameter, you can do it with a metaclass that captures the name via lexical scope.
I find this a bit easier to read / follow than some of the alternatives.
class type_: pass
def create_type(name):
# we do this so that we can print the class type out
# otherwise we must instantiate it to get a proper print out
class type_metaclass(type):
def __repr__(self):
return f'<{name}>'
class actual_type(type_, metaclass=type_metaclass):
pass
return actual_type
my_type = create_type('my_type')
print(my_type)
# prints "<my_type>"
Another answer, with:
decorator
types (so you keep auto-complete in IDEs)
works as of v3.10
import typing
class ClassReprMeta(type):
def __repr__(self):
attrs_str = ", ".join(
f"{key}={getattr(self, key)}"
for key in dir(self)
if not key.startswith("_")
)
return f"{self.__name__}({attrs_str})"
T = typing.TypeVar("T")
def printable_class(cls: T) -> T:
"""Decorator to make a class object printable"""
return ClassReprMeta(cls.__name__, cls.__bases__, dict(cls.__dict__))
#printable_class
class CONFIG:
FIRST = 1
SECOND = 2
print(CONFIG) # CONFIG(FIRST=1, SECOND=2)
What's the best practice to define an abstract instance attribute, but not as a property?
I would like to write something like:
class AbstractFoo(metaclass=ABCMeta):
#property
#abstractmethod
def bar(self):
pass
class Foo(AbstractFoo):
def __init__(self):
self.bar = 3
Instead of:
class Foo(AbstractFoo):
def __init__(self):
self._bar = 3
#property
def bar(self):
return self._bar
#bar.setter
def setbar(self, bar):
self._bar = bar
#bar.deleter
def delbar(self):
del self._bar
Properties are handy, but for simple attribute requiring no computation they are an overkill. This is especially important for abstract classes which will be subclassed and implemented by the user (I don't want to force someone to use #property when he just could have written self.foo = foo in the __init__).
Abstract attributes in Python question proposes as only answer to use #property and #abstractmethod: it doesn't answer my question.
The ActiveState recipe for an abstract class attribute via AbstractAttribute may be the right way, but I am not sure. It also only works with class attributes and not instance attributes.
A possibly a bit better solution compared to the accepted answer:
from better_abc import ABCMeta, abstract_attribute # see below
class AbstractFoo(metaclass=ABCMeta):
#abstract_attribute
def bar(self):
pass
class Foo(AbstractFoo):
def __init__(self):
self.bar = 3
class BadFoo(AbstractFoo):
def __init__(self):
pass
It will behave like this:
Foo() # ok
BadFoo() # will raise: NotImplementedError: Can't instantiate abstract class BadFoo
# with abstract attributes: bar
This answer uses same approach as the accepted answer, but integrates well with built-in ABC and does not require boilerplate of check_bar() helpers.
Here is the better_abc.py content:
from abc import ABCMeta as NativeABCMeta
class DummyAttribute:
pass
def abstract_attribute(obj=None):
if obj is None:
obj = DummyAttribute()
obj.__is_abstract_attribute__ = True
return obj
class ABCMeta(NativeABCMeta):
def __call__(cls, *args, **kwargs):
instance = NativeABCMeta.__call__(cls, *args, **kwargs)
abstract_attributes = {
name
for name in dir(instance)
if getattr(getattr(instance, name), '__is_abstract_attribute__', False)
}
if abstract_attributes:
raise NotImplementedError(
"Can't instantiate abstract class {} with"
" abstract attributes: {}".format(
cls.__name__,
', '.join(abstract_attributes)
)
)
return instance
The nice thing is that you can do:
class AbstractFoo(metaclass=ABCMeta):
bar = abstract_attribute()
and it will work same as above.
Also one can use:
class ABC(ABCMeta):
pass
to define custom ABC helper. PS. I consider this code to be CC0.
This could be improved by using AST parser to raise earlier (on class declaration) by scanning the __init__ code, but it seems to be an overkill for now (unless someone is willing to implement).
2021: typing support
You can use:
from typing import cast, Any, Callable, TypeVar
R = TypeVar('R')
def abstract_attribute(obj: Callable[[Any], R] = None) -> R:
_obj = cast(Any, obj)
if obj is None:
_obj = DummyAttribute()
_obj.__is_abstract_attribute__ = True
return cast(R, _obj)
which will let mypy highlight some typing issues
class AbstractFooTyped(metaclass=ABCMeta):
#abstract_attribute
def bar(self) -> int:
pass
class FooTyped(AbstractFooTyped):
def __init__(self):
# skipping assignment (which is required!) to demonstrate
# that it works independent of when the assignment is made
pass
f_typed = FooTyped()
_ = f_typed.bar + 'test' # Mypy: Unsupported operand types for + ("int" and "str")
FooTyped.bar = 'test' # Mypy: Incompatible types in assignment (expression has type "str", variable has type "int")
FooTyped.bar + 'test' # Mypy: Unsupported operand types for + ("int" and "str")
and for the shorthand notation, as suggested by #SMiller in the comments:
class AbstractFooTypedShorthand(metaclass=ABCMeta):
bar: int = abstract_attribute()
AbstractFooTypedShorthand.bar += 'test' # Mypy: Unsupported operand types for + ("int" and "str")
Just because you define it as an abstractproperty on the abstract base class doesn't mean you have to make a property on the subclass.
e.g. you can:
In [1]: from abc import ABCMeta, abstractproperty
In [2]: class X(metaclass=ABCMeta):
...: #abstractproperty
...: def required(self):
...: raise NotImplementedError
...:
In [3]: class Y(X):
...: required = True
...:
In [4]: Y()
Out[4]: <__main__.Y at 0x10ae0d390>
If you want to initialise the value in __init__ you can do this:
In [5]: class Z(X):
...: required = None
...: def __init__(self, value):
...: self.required = value
...:
In [6]: Z(value=3)
Out[6]: <__main__.Z at 0x10ae15a20>
Since Python 3.3 abstractproperty is deprecated. So Python 3 users should use the following instead:
from abc import ABCMeta, abstractmethod
class X(metaclass=ABCMeta):
#property
#abstractmethod
def required(self):
raise NotImplementedError
If you really want to enforce that a subclass define a given attribute, you can use metaclasses:
class AbstractFooMeta(type):
def __call__(cls, *args, **kwargs):
"""Called when you call Foo(*args, **kwargs) """
obj = type.__call__(cls, *args, **kwargs)
obj.check_bar()
return obj
class AbstractFoo(object):
__metaclass__ = AbstractFooMeta
bar = None
def check_bar(self):
if self.bar is None:
raise NotImplementedError('Subclasses must define bar')
class GoodFoo(AbstractFoo):
def __init__(self):
self.bar = 3
class BadFoo(AbstractFoo):
def __init__(self):
pass
Basically the meta class redefine __call__ to make sure check_bar is called after the init on an instance.
GoodFoo() # ok
BadFoo () # yield NotImplementedError
As Anentropic said, you don't have to implement an abstractproperty as another property.
However, one thing all answers seem to neglect is Python's member slots (the __slots__ class attribute). Users of your ABCs required to implement abstract properties could simply define them within __slots__ if all that's needed is a data attribute.
So with something like,
class AbstractFoo(abc.ABC):
__slots__ = ()
bar = abc.abstractproperty()
Users can define sub-classes simply like,
class Foo(AbstractFoo):
__slots__ = 'bar', # the only requirement
# define Foo as desired
def __init__(self):
self.bar = ...
Here, Foo.bar behaves like a regular instance attribute, which it is, just implemented differently. This is simple, efficient, and avoids the #property boilerplate that you described.
This works whether or not ABCs define __slots__ at their class' bodies. However, going with __slots__ all the way not only saves memory and provides faster attribute accesses but also gives a meaningful descriptor instead of having intermediates (e.g. bar = None or similar) in sub-classes.1
A few answers suggest doing the "abstract" attribute check after instantiation (i.e. at the meta-class __call__() method) but I find that not only wasteful but also potentially inefficient as the initialization step could be a time-consuming one.
In short, what's required for sub-classes of ABCs is to override the relevant descriptor (be it a property or a method), it doesn't matter how, and documenting to your users that it's possible to use __slots__ as implementation for abstract properties seems to me as the more adequate approach.
1 In any case, at the very least, ABCs should always define an empty __slots__ class attribute because otherwise sub-classes are forced to have __dict__ (dynamic attribute access) and __weakref__ (weak reference support) when instantiated. See the abc or collections.abc modules for examples of this being the case within the standard library.
The problem isn't what, but when:
from abc import ABCMeta, abstractmethod
class AbstractFoo(metaclass=ABCMeta):
#abstractmethod
def bar():
pass
class Foo(AbstractFoo):
bar = object()
isinstance(Foo(), AbstractFoo)
#>>> True
It doesn't matter that bar isn't a method! The problem is that __subclasshook__, the method of doing the check, is a classmethod, so only cares whether the class, not the instance, has the attribute.
I suggest you just don't force this, as it's a hard problem. The alternative is forcing them to predefine the attribute, but that just leaves around dummy attributes that just silence errors.
I've searched around for this for awhile but didn't see anything I like. As you probably know if you do:
class AbstractFoo(object):
#property
def bar(self):
raise NotImplementedError(
"Subclasses of AbstractFoo must set an instance attribute "
"self._bar in it's __init__ method")
class Foo(AbstractFoo):
def __init__(self):
self.bar = "bar"
f = Foo()
You get an AttributeError: can't set attribute which is annoying.
To get around this you can do:
class AbstractFoo(object):
#property
def bar(self):
try:
return self._bar
except AttributeError:
raise NotImplementedError(
"Subclasses of AbstractFoo must set an instance attribute "
"self._bar in it's __init__ method")
class OkFoo(AbstractFoo):
def __init__(self):
self._bar = 3
class BadFoo(AbstractFoo):
pass
a = OkFoo()
b = BadFoo()
print a.bar
print b.bar # raises a NotImplementedError
This avoids the AttributeError: can't set attribute but if you just leave off the abstract property all together:
class AbstractFoo(object):
pass
class Foo(AbstractFoo):
pass
f = Foo()
f.bar
You get an AttributeError: 'Foo' object has no attribute 'bar' which is arguably almost as good as the NotImplementedError. So really my solution is just trading one error message from another .. and you have to use self._bar rather than self.bar in the init.
Following https://docs.python.org/2/library/abc.html you could do something like this in Python 2.7:
from abc import ABCMeta, abstractproperty
class Test(object):
__metaclass__ = ABCMeta
#abstractproperty
def test(self): yield None
def get_test(self):
return self.test
class TestChild(Test):
test = None
def __init__(self, var):
self.test = var
a = TestChild('test')
print(a.get_test())
Consider this class:
class foo(object):
pass
The default string representation looks something like this:
>>> str(foo)
"<class '__main__.foo'>"
How can I make this display a custom string?
See How to print instances of a class using print()? for the corresponding question about instances of the class.
In fact, this question is really a special case of that one - because in Python, classes are themselves also objects belonging to their own class - but it's not directly obvious how to apply the advice, since the default "class of classes" is pre-defined.
Implement __str__() or __repr__() in the class's metaclass.
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object):
__metaclass__ = MC
print(C)
Use __str__ if you mean a readable stringification, use __repr__ for unambiguous representations.
Edit: Python 3 Version
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object, metaclass=MC):
pass
print(C)
class foo(object):
def __str__(self):
return "representation"
def __unicode__(self):
return u"representation"
If you have to choose between __repr__ or __str__ go for the first one, as by default implementation __str__ calls __repr__ when it wasn't defined.
Custom Vector3 example:
class Vector3(object):
def __init__(self, args):
self.x = args[0]
self.y = args[1]
self.z = args[2]
def __repr__(self):
return "Vector3([{0},{1},{2}])".format(self.x, self.y, self.z)
def __str__(self):
return "x: {0}, y: {1}, z: {2}".format(self.x, self.y, self.z)
In this example, repr returns again a string that can be directly consumed/executed, whereas str is more useful as a debug output.
v = Vector3([1,2,3])
print repr(v) #Vector3([1,2,3])
print str(v) #x:1, y:2, z:3
Ignacio Vazquez-Abrams' approved answer is quite right. It is, however, from the Python 2 generation. An update for the now-current Python 3 would be:
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(object, metaclass=MC):
pass
print(C)
If you want code that runs across both Python 2 and Python 3, the six module has you covered:
from __future__ import print_function
from six import with_metaclass
class MC(type):
def __repr__(self):
return 'Wahaha!'
class C(with_metaclass(MC)):
pass
print(C)
Finally, if you have one class that you want to have a custom static repr, the class-based approach above works great. But if you have several, you'd have to generate a metaclass similar to MC for each, and that can get tiresome. In that case, taking your metaprogramming one step further and creating a metaclass factory makes things a bit cleaner:
from __future__ import print_function
from six import with_metaclass
def custom_class_repr(name):
"""
Factory that returns custom metaclass with a class ``__repr__`` that
returns ``name``.
"""
return type('whatever', (type,), {'__repr__': lambda self: name})
class C(with_metaclass(custom_class_repr('Wahaha!'))): pass
class D(with_metaclass(custom_class_repr('Booyah!'))): pass
class E(with_metaclass(custom_class_repr('Gotcha!'))): pass
print(C, D, E)
prints:
Wahaha! Booyah! Gotcha!
Metaprogramming isn't something you generally need everyday—but when you need it, it really hits the spot!
Just adding to all the fine answers, my version with decoration:
from __future__ import print_function
import six
def classrep(rep):
def decorate(cls):
class RepMetaclass(type):
def __repr__(self):
return rep
class Decorated(six.with_metaclass(RepMetaclass, cls)):
pass
return Decorated
return decorate
#classrep("Wahaha!")
class C(object):
pass
print(C)
stdout:
Wahaha!
The down sides:
You can't declare C without a super class (no class C:)
C instances will be instances of some strange derivation, so it's probably a good idea to add a __repr__ for the instances as well.
Because you need a metaclass to do this, but you need the metaclass itself to have a parameter, you can do it with a metaclass that captures the name via lexical scope.
I find this a bit easier to read / follow than some of the alternatives.
class type_: pass
def create_type(name):
# we do this so that we can print the class type out
# otherwise we must instantiate it to get a proper print out
class type_metaclass(type):
def __repr__(self):
return f'<{name}>'
class actual_type(type_, metaclass=type_metaclass):
pass
return actual_type
my_type = create_type('my_type')
print(my_type)
# prints "<my_type>"
Another answer, with:
decorator
types (so you keep auto-complete in IDEs)
works as of v3.10
import typing
class ClassReprMeta(type):
def __repr__(self):
attrs_str = ", ".join(
f"{key}={getattr(self, key)}"
for key in dir(self)
if not key.startswith("_")
)
return f"{self.__name__}({attrs_str})"
T = typing.TypeVar("T")
def printable_class(cls: T) -> T:
"""Decorator to make a class object printable"""
return ClassReprMeta(cls.__name__, cls.__bases__, dict(cls.__dict__))
#printable_class
class CONFIG:
FIRST = 1
SECOND = 2
print(CONFIG) # CONFIG(FIRST=1, SECOND=2)