A metaclass is a "class that creates a class", and its core lies in interfering with the class creation process by inheriting the type and overwriting the __new__ or __init__ methods. 1. Metaclasses allow modification of behavior when class generation, such as adding properties, checking method naming, etc.; 2. Custom metaclasses are usually implemented by rewriting __new__, such as forcing the class to contain specific methods; 3. Common uses include ORM frameworks, interface verification, automatic registration of subclasses, etc.; 4. When using it, you need to pay attention to avoid overuse, ensure readability, debugging complexity, and conflicts in multiple inheritance.

Python's metaclasses and type customization sound like advanced topics, but their core ideas are not difficult to understand. If you have used class and type() , then you are only one layer of window paper away from mastering metaclasses.

Simply put, metaclasses are "classes that create classes". The class we usually write, such as class Person: , is actually the default metaclass of type . Metaclasses allow you to modify or enhance the behavior of the class before or when it is created.

What is metaclass?

In Python, everything is an object. Including int , str , and classes you write yourself are all objects. So how did these classes come from? The answer is: created from metaclasses.

The most basic metaclass is the built-in type . You can create a class manually like this:

 MyClass = type('MyClass', (), {})

This line of code is equivalent to:

 class MyClass:
    pass

So, type is the default metaclass for all classes . If you want to do something when a class is created - such as automatically adding properties, checking method naming, and registering subclasses - you can do it by customizing metaclasses.

How to customize metaclass?

To customize a metaclass, just inherit type and then override its __new__ or __init__ methods. The difference between these two methods is:

• __new__ is responsible for creating class objects
• __init__ is responsible for initializing class objects

It is usually recommended to use __new__ first, because what you want to change is the generation process of the class.

To give a simple example: force each class to have a required_method method.

 class MyMeta(type):
    def __new__(cls, name, bases, attrs):
        if 'required_method' not in attrs:
            raise TypeError("required_method method must be implemented")
        return super().__new__(cls, name, bases, attrs)

class MyClass(metaclass=MyMeta):
    def required_method(self):
        pass

If you try to define a class without required_method , an exception will be thrown.

What are the common uses of metaclasses?

While not every project requires metaclasses, it is very useful in some scenarios:

• ORM framework : Use metaclasses like Django or SQLAlchemy to automatically generate database field maps.
• Interface Verification : Ensure that the class implements a specific method collection.
• Automatically register subclasses : Used to automatically collect all subclasses in plug-in systems or factory mode.
• Modify class attributes/methods : such as adding logs, decorators, version numbers and other information in a unified manner.

For example, automatically register all subclasses:

 class PluginMeta(type):
    registry = {}
    def __new__(cls, name, bases, attrs):
        new_class = super().__new__(cls, name, bases, attrs)
        # Ignore the base class if name != 'BasePlugin':
            cls.registry[name] = new_class
        return new_class

class BasePlugin(metaclass=PluginMeta):
    pass

class PluginA(BasePlugin):
    pass

class PluginB(BasePlugin):
    pass

print(PluginMeta.registry) # Output {&#39;PluginA&#39;: <class ...>, &#39;PluginB&#39;: <class ...>}

What should I pay attention to when using metaclasses?

Metaclasses are powerful, but they are also prone to overuse. Here are some precautions for use:

• Don’t use metaclasses for the sake of showing off your skills : problems that can be solved with decorators or ordinary inheritance, there is no need to use metaclasses.
• Readability is important : metaclasses will change the logic of the creation of the class, which may not be easy for others to understand when reading the code.
• Debugging difficulty increases : If a metaclass error occurs, tracking problems may be more troublesome.
• Be careful when combining with multiple inheritance : multiple metaclasses may conflict and the inheritance relationship of the metaclass needs to be explicitly specified.

In addition, the execution order of metaclasses also needs to be noted: if a class has multiple parent classes at the same time and each of them specifies different metaclasses, you need to provide a common metaclass, otherwise an error will be reported.

Basically that's it. Metaclasses are not magic, they just help you control how classes are created. Master type and __new__ and you can already start trying to solve problems with metaclasses.

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