1)元类有什么用以及何时使用它?
元类对于类就像类对于对象一样。它们是类的类(因此称为“元”)。
元类通常适用于您想要在 OOP 的正常约束之外工作的情况。
2)元类和继承之间有什么区别/相似之处?
元类不是对象类层次结构的一部分,而基类则是。所以当一个对象这样做时obj.some_method()
它不会在元类中搜索此方法,但是元类可能在类或对象的创建过程中创建了它。
在下面的示例中,元类MetaCar
给对象一个defect
基于随机数的属性。这defect
属性未在任何对象的基类或类本身中定义。然而,这可以仅使用类来实现。
然而(与类不同),这个元类还重新路由对象创建;在里面some_cars
列表中,所有丰田汽车都是使用Car
班级。元类检测到Car.__init__
包含一个make
参数与该名称的预先存在的类相匹配,因此返回该类的对象。
此外,您还会注意到,在some_cars
list, Car.__init__
被称为make="GM"
. A GM
此时程序评估中尚未定义类。元类检测到 make 参数中不存在该名称的类,因此它创建一个类并更新全局命名空间(因此它不需要使用返回机制)。然后它使用新定义的类创建对象并返回它。
import random
class CarBase(object):
pass
class MetaCar(type):
car_brands = {}
def __init__(cls, cls_name, cls_bases, cls_dict):
super(MetaCar, cls).__init__(cls_name, cls_bases, cls_dict)
if(not CarBase in cls_bases):
MetaCar.car_brands[cls_name] = cls
def __call__(self, *args, **kwargs):
make = kwargs.get("make", "")
if(MetaCar.car_brands.has_key(make) and not (self is MetaCar.car_brands[make])):
obj = MetaCar.car_brands[make].__call__(*args, **kwargs)
if(make == "Toyota"):
if(random.randint(0, 100) < 2):
obj.defect = "sticky accelerator pedal"
elif(make == "GM"):
if(random.randint(0, 100) < 20):
obj.defect = "shithouse"
elif(make == "Great Wall"):
if(random.randint(0, 100) < 101):
obj.defect = "cancer"
else:
obj = None
if(not MetaCar.car_brands.has_key(self.__name__)):
new_class = MetaCar(make, (GenericCar,), {})
globals()[make] = new_class
obj = new_class(*args, **kwargs)
else:
obj = super(MetaCar, self).__call__(*args, **kwargs)
return obj
class Car(CarBase):
__metaclass__ = MetaCar
def __init__(self, **kwargs):
for name, value in kwargs.items():
setattr(self, name, value)
def __repr__(self):
return "<%s>" % self.description
@property
def description(self):
return "%s %s %s %s" % (self.color, self.year, self.make, self.model)
class GenericCar(Car):
def __init__(self, **kwargs):
kwargs["make"] = self.__class__.__name__
super(GenericCar, self).__init__(**kwargs)
class Toyota(GenericCar):
pass
colours = \
[
"blue",
"green",
"red",
"yellow",
"orange",
"purple",
"silver",
"black",
"white"
]
def rand_colour():
return colours[random.randint(0, len(colours) - 1)]
some_cars = \
[
Car(make="Toyota", model="Prius", year=2005, color=rand_colour()),
Car(make="Toyota", model="Camry", year=2007, color=rand_colour()),
Car(make="Toyota", model="Camry Hybrid", year=2013, color=rand_colour()),
Car(make="Toyota", model="Land Cruiser", year=2009, color=rand_colour()),
Car(make="Toyota", model="FJ Cruiser", year=2012, color=rand_colour()),
Car(make="Toyota", model="Corolla", year=2010, color=rand_colour()),
Car(make="Toyota", model="Hiace", year=2006, color=rand_colour()),
Car(make="Toyota", model="Townace", year=2003, color=rand_colour()),
Car(make="Toyota", model="Aurion", year=2008, color=rand_colour()),
Car(make="Toyota", model="Supra", year=2004, color=rand_colour()),
Car(make="Toyota", model="86", year=2013, color=rand_colour()),
Car(make="GM", model="Camaro", year=2008, color=rand_colour())
]
dodgy_vehicles = filter(lambda x: hasattr(x, "defect"), some_cars)
print dodgy_vehicles
3)应该在哪里使用元类或继承?
正如这个答案和评论中提到的,在进行 OOP 时几乎总是使用继承。元类用于在这些限制之外工作(请参阅示例),并且几乎总是不必要的,但是一些非常先进和极其动态程序流程可以用它们来实现。这既是他们的力量,也是他们的danger.