Table of Contents
1. Use metaclass to verify subclasses
2. Register subclasses with metaclasses
3. Use metaclasses to annotate class attributes
Home Backend Development Python Tutorial Detailed explanation of metaclasses and their usage in Python

Detailed explanation of metaclasses and their usage in Python

Jul 20, 2017 am 09:30 AM
python

1. Use metaclass to verify subclasses

Whenever we define a new class, the metaclass will run Yazheng code to ensure that the new class conforms to the specified specifications.
After the Python system has processed the class statement of the subclass, it will call the __new__ method of the metaclass. The metaclass can obtain the name, parent and attributes of the subclass and grandchild class through the __new__ method.
This eliminates the need for us to put the verification code in the __init__ method of this class and wait until the object is built before verifying.

In the following example, a subclass with less than 3 edges is defined. Once the class statement ends, the metaclass verification code will reject the class.

class ValidatePolygon(type):
    def __new__(meta, name, bases, class_dict):
        # Don't validate the abstract Polygon class
        if bases != (object,):
            if class_dict['sides'] < 3:
                raise ValueError('Polygons need 3+ sides')
        return type.__new__(meta, name, bases, class_dict)

class Polygon(object, metaclass=ValidatePolygon):
    sides = None  # Specified by subclasses

    @classmethod
    def interior_angles(cls):
        return (cls.sides - 2) * 180

class Triangle(Polygon):
    sides = 3

print(Triangle.interior_angles())
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2. Register subclasses with metaclasses

Every time you inherit a subclass from a base class, the metaclass of the base class can automatically run the registration code.
This is useful when a 'reverse lookup' is required to establish a mapping between a simple identifier and the corresponding class.
Still used is that after the class statement is executed, the __new__ method of the metaclass is automatically called.

import json 

registry = {}

def register_class(target_class):
    registry[target_class.__name__] = target_class

def deserialize(data):
    params = json.loads(data)
    name = params['class']
    target_class = registry[name]
    return target_class(*params['args'])


class Meta(type):
    def __new__(meta, name, bases, class_dict):
        cls = type.__new__(meta, name, bases, class_dict)
        register_class(cls)
        return cls


class Serializable(object):
    def __init__(self, *args):
        self.args = args

    def serialize(self):
        return json.dumps({
            'class': self.__class__.__name__,
            'args': self.args,
        })

    def __repr__(self):
        return '%s(%s)' % (
            self.__class__.__name__,
            ', '.join(str(x) for x in self.args))


class RegisteredSerializable(Serializable, metaclass=Meta):
    pass


class Vector3D(RegisteredSerializable):
    def __init__(self, x, y, z):
        super().__init__(x, y, z)
        self.x, self.y, self.z = x, y, z


v3 = Vector3D(10, -7, 3)
print('Before:    ', v3)
data = v3.serialize()
print('Serialized:', data)
print('After:     ', deserialize(data))

print(registry)
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3. Use metaclasses to annotate class attributes

Using metaclasses is like placing a hook on the class statement. After the class statement is processed, the hook will be triggered immediately.
In the following, Filed.name and Filed.name are set with the help of metaclasses.

class Field(object):
    def __init__(self):
        # These will be assigned by the metaclass.
        self.name = None
        self.internal_name = None
        
    def __get__(self, instance, instance_type):
        if instance is None: return self
        return getattr(instance, self.internal_name, '')

    def __set__(self, instance, value):
        setattr(instance, self.internal_name, value)


class Meta(type):
    def __new__(meta, name, bases, class_dict):
        for key, value in class_dict.items():
            if isinstance(value, Field):
                value.name = key
                value.internal_name = '_' + key
        cls = type.__new__(meta, name, bases, class_dict)
        return cls


class DatabaseRow(object, metaclass=Meta):
    pass


class BetterCustomer(DatabaseRow):
    first_name = Field()
    last_name = Field()
    prefix = Field()
    suffix = Field()


foo = BetterCustomer()
print('Before:', repr(foo.first_name), foo.__dict__)
foo.first_name = 'Euler'
print('After: ', repr(foo.first_name), foo.__dict__)
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The metaclass summary ends here, and I don’t fully understand it.
I hope pythoners who have a deep understanding of this can leave a message.

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