Python MetaClasses - GeeksforGeeks

18 Aug, 2020
The key concept of python is objects. Almost everything in python is an object, which includes functions and as well as classes. As a result, functions and classes can be passed as arguments, can exist as an instance, and so on. Above all, the concept of objects let the classes in generating other classes.
The classes that generate other classes are defined as metaclasses. In this section, we will discuss the concept of metaclasses and the specific ways to use them. In this section, we will cover the following topics:
type
Writing Metaclasses
Metaclass Usecases
A class defines the properties and available actions of its object and also it acts as a factory for object creation. Let’s understand the process by creating a class using type directly. The exact class that is used for class instantiation is called type. Normally, we define a class using a special syntax called the class keyword, but this syntax is a substitute for type class. Let’s illustrate with an example:
 First of all, we look into the scenario of creating a class using the class keyword. Let’s check the below code:
Python3
class FoodType(object):  def __init__(self, ftype):    self.ftype = ftype        def getFtype(self):    return self.ftype      def main():  fType = FoodType(ftype = 'Vegetarian')  print(fType.getFtype())    main()
Vegetarian




Here we have created a class called FoodType using the class keyword. This class keyword acts as a substitute for type syntax. Now let’s look into, how to use type keyword. Let’s go through the below code:
Python3
def init(self, ftype):    self.ftype = ftype  def getFtype(self):    return self.ftype   FoodType = type('FoodType', (object, ), {    '__init__': init,    'getFtype' : getFtype,    })  fType = FoodType(ftype ='Vegetarian')print(fType.getFtype())
Vegetarian




Let’s focus on type. It has three arguments they are as follows:
The first argument is a string – FoodType. This string is assigned as the class name.
The second argument is a tuple – (object, ). This tells that the FoodType class inherits from the object class. Here, the trailing comma helps the python interpreter to recognize it as a tuple.
Here, the third argument is a dictionary that mentions the attribute of a class. In this case, the class has two methods – init and getFtype.
Let’s look into the normal scenario of creating a subclass, i.e., using the class keyword. Here, we will create a subclass VegType in which the main class is FoodType.
Python3
class FoodType(object):  def __init__(self, ftype):    self.ftype = ftype        def getFtype(self):    return self.ftype    class VegType(FoodType):  def vegFoods(self):    return {'Spinach', 'Bitter Guard'}    def main():  vType = VegType(ftype = 'Vegetarian')  print(vType.getFtype())  print(vType.vegFoods())    main()
Vegetarian
{'Spinach', 'Bitter Guard'}




Now let’s see how to convert the above code using type.  For the FoodType class, the second argument of the type is the object class –  the superclass –, i.e., FoodType is the subclass of the Object class. Similarly, the VegType class is the subclass of FoodType, and hence while creating the VegType class, the second argument of type refers to the FoodType class. 
Python3
def init(self, ftype):    self.ftype = ftype  def getFtype(self):    return self.ftype   FoodType = type('FoodType', (object, ), {    '__init__': init,    'getFtype' : getFtype,    })  def vegFoods(self):    return {'Spinach', 'Bitter Guard'}   ## creating subclass using typeVegType = type('VegType', (FoodType, ), {    'vegFoods' : vegFoods,    })    vType = VegType(ftype ='Vegetarian')print(vType.getFtype())print(vType.vegFoods())
Vegetarian
{'Spinach', 'Bitter Guard'}




Metaclasses are classes that inherit directly from type. The method that custom metaclasses should implement is the __new__ method. The arguments mentioned in the __new__  method of metaclasses reflects in the __new__ method of type class. It has four positional arguments. They are as follows:
The first argument is the metaclass itself.The second argument is the class name.The third argument is the  superclasses (in the form of tuple)The fourth argument is the attributes of class (in the form of dictionary)
The first argument is the metaclass itself.
The second argument is the class name.
The third argument is the  superclasses (in the form of tuple)
The fourth argument is the attributes of class (in the form of dictionary)
 Let’s have a look at the below code.
Python3
class MetaCls(type):    """A sample metaclass without any functionality"""    def __new__(cls, clsname, superclasses, attributedict):        print("clsname:", clsname)        print("superclasses:", superclasses)        print("attrdict:", attributedict)        return super(MetaCls, cls).__new__(cls, \                       clsname, superclasses, attributedict)  C = MetaCls('C', (object, ), {})print("class type:", type(C))
clsname: C
superclasses: (<class 'object'>, )
attrdict: {}
class type: <class '__main__.MetaCls'>




You can note that the type of class C is a metaclass – MetaCls. Let’s check the type of a normal class.
Python3
class S(object):  pass  print(type(S))
<class 'type'>




Let’s see, how to inherit from metaclasses.
Python3
class MetaCls(type):    """A sample metaclass without any functionality"""    def __new__(cls, clsname, supercls, attrdict):                  return super(MetaCls, cls).__new__(cls, clsname, supercls, attrdict)  C = MetaCls('C', (object, ), {})## class A inherits from MetaCls       class A(C):  pass  print(type(A))
<class '__main__.MetaCls'>




In this case, you can see that class A is an instance of a metaclass. This is because its superclass C is an instance of a metaclass. Now we will consider the scenario where class subclasses with two or more distinct classes. Let’s look into the below sample code:
Python3
class MetaCls(type):    """A sample metaclass without any functionality"""    def __new__(cls, clsname, supercls, attrdict):                  return super(MetaCls, cls).__new__(cls, clsname, supercls, attrdict)  ## a class of the type metclassA = MetaCls('A', (object, ), {})print('Type of class A:', type(A))  class B(object):    passprint('Type of class B:', type(B))  ## class C inherits from both the class, A and Bclass C(A, B):    passprint('Type of class C:', type(C))
Type of class A: <class '__main__.MetaCls'>
Type of class B: <class 'type'>
Type of class C: <class '__main__.MetaCls'>




Here, you can see class C is inherited from class A (metaclass) and class B ( type class). But here the type of class C is a metaclass. This is because when Python interpreter checked the superclasses, it found that the metaclass is a subclass of the type itself. So it considered metaclass as the type of class C to avoid any conflict.  
Let’s look into another sample code where a class inherits from two different metaclasses.
Python3
class MetaCls(type):    """A sample metaclass without any functionality"""    def __new__(cls, clsname, supercls, attrdict):                  return super(MetaCls, cls).__new__(cls, clsname, supercls, attrdict)  A = MetaCls('A', (object, ), {})    class NewMetaCls(type):    """A sample metaclass without any functionality"""    def __new__(cls, clsname, supercls, attrdict):                  return super(NewMetaCls, cls).__new__(cls, clsname, supercls, attrdict)  NewA = NewMetaCls('NewA', (object, ), {})  class C(A, NewA):  pass
Here you will get the below error message while trying to inherit from two different metaclasses.
Traceback (most recent call last):
  File "/home/eb81e4ecb05868f83d5f375ffc78e237.py", line 18, in <module>
    class C(A, NewA):
TypeError: metaclass conflict: the metaclass of a derived class must be a (non-strict) 
subclass of the metaclasses of all its bases



This is because Python can only have one metaclass for a class. Here, class C can’t inherit from two metaclasses, which results in ambiguity.
In most cases, we don’t need to go for a metaclass, normal code will fit with the class and object. The pointless use of metaclasses increases the complexity of coding. But there are scenarios where metaclass provides clear and efficient solutions. Let’s look into a few use cases. 
If you need to design a class that agrees to a particular interface, then a metaclass is the right solution. We can consider a sample code where a class requires either one of the attributes to be set. Let’s go through the code.
Python3
class MainClass(type):    def __new__(cls, name, bases, attrs):        if 'foo' in attrs and 'bar' in attrs:            raise TypeError('Class % s cannot contain both foo and bar \attributes.' % name)        if 'foo' not in attrs and 'bar' not in attrs:            raise TypeError('Class % s must provide either a foo \attribute or a bar attribute.' % name)        else:          print('Success')                        return super(MainClass, cls).__new__(cls, name, bases, attrs)  class SubClass(metaclass = MainClass):    foo = 42    bar = 34    subCls = SubClass()
Here we tried to set two attributes. Hence, the design prevented it from setting and raised the below error. 
Traceback (most recent call last):
  File "/home/fe76a380911f384c4517f07a8de312a4.py", line 13, in <module>
    class SubClass(metaclass = MainClass):
  File "/home/fe76a380911f384c4517f07a8de312a4.py", line 5, in __new__
    attributes.' %name)
TypeError: Class SubClass cannot both foo and bar attributes.



You may think, using decorators you can easily make a class that agrees to a particular standard. But the disadvantage of using class decorator is that it must be explicitly applied to each subclass. 
A metaclass is an efficient tool to prevent sub class from inheriting certain class functions. This scenario can be best explained in the case of Abstract classes. While creating abstract classes, it is not required to run the functionality of the class. Let’s have a look at the below code.  
Python3
class MetaCls(type):    def __new__(cls, name, bases, attrs):        # If abstract class, then skip the metaclass function        if attrs.pop('abstract', False):            print('Abstract Class:', name)            return super(MetaCls, cls).__new__(cls, name, bases, attrs)                  # metaclass functionality        if 'foo' in attrs and 'bar' in attrs:            raise TypeError('Class % s cannot contain both foo and bar \attributes.' % name)        if 'foo' not in attrs and 'bar' not in attrs:            raise TypeError('Class % s must provide either a foo \attribute or a bar attribute.' % name)        print('Normal Class:', name)        return super(MetaCls, cls).__new__(cls, name, bases, attrs)  class AbsCls(metaclass = MetaCls):    abstract = True        class NormCls(metaclass = MetaCls):    foo = 42
Abstract Class: AbsCls
Normal Class: NormCls




The dynamic generation of classes opens up a lot of possibilities. Let’s see how to generate classes dynamically using type.
Python3
class FoodType(object):    events = []      def __init__(self, ftype, items):        self.ftype = ftype        self.items = items        FoodType.events.append(self)      def run(self):        print("Food Type: % s" %(self.ftype))        print("Food Menu:", self.items)       @staticmethod    def run_events():        for e in FoodType.events:            e.run()  def sub_food(ftype):    class_name = ftype.capitalize()    def __init__(self, items):        FoodType.__init__(self, ftype, items)    # dynamic class creation and defining it as a global attribute        globals()[class_name] = \    type(class_name, (FoodType, ), dict(__init__ = __init__))                      if __name__ == "__main__":    foodType = ["Vegetarian", "Nonvegetarian"]    foodItems = "Vegetarian(['Spinach', 'Bitter Guard']);\Nonvegetarian(['Meat', 'Fish'])"    # invoking method for dynamic class creation.    [sub_food(ftype) for ftype in foodType]    # executing dynamic classes.    exec(foodItems)    FoodType.run_events()
Food Type: Vegetarian
Food Menu: ['Spinach', 'Bitter Guard']
Food Type: Nonvegetarian
Food Menu: ['Meat', 'Fish']




In this case, we create two subclasses – Vegetarian and NonVegetarian – dynamically, which inherits from the FoodType class.
Normal classes that are designed using class keyword have type as their metaclasses, and type is the primary metaclass. Metaclasses are a powerful tool in Python that can overcome many limitations. But most of the developers have a misconception that metaclasses are difficult to grasp.
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