What are metaclasses in Python? [Answered]

Metaclasses in Python explained:

Classes as objects

Before understanding metaclasses, you need to master classes in Python. And Python has a very peculiar idea of what classes are, borrowed from the Smalltalk language.

In most languages, classes are just pieces of code that describe how to produce an object. That’s kinda true in Python too:

>>> class ObjectCreator(object):
...       pass
...

>>> my_object = ObjectCreator()
>>> print(my_object)
<__main__.ObjectCreator object at 0x8974f2c>

But classes are more than that in Python. Classes are objects too.

Yes, objects.

As soon as you use the keyword class, Python executes it and creates an object. The instruction

>>> class ObjectCreator(object):
...       pass
...

creates in memory an object with the name ObjectCreator.

This object (the class) is itself capable of creating objects (the instances), and this is why it’s a class.

But still, it’s an object, and therefore:

  • you can assign it to a variable
  • you can copy it
  • you can add attributes to it
  • you can pass it as a function parameter

e.g.:

>>> print(ObjectCreator) # you can print a class because it's an object
<class '__main__.ObjectCreator'>
>>> def echo(o):
...       print(o)
...
>>> echo(ObjectCreator) # you can pass a class as a parameter
<class '__main__.ObjectCreator'>
>>> print(hasattr(ObjectCreator, 'new_attribute'))
False
>>> ObjectCreator.new_attribute = 'foo' # you can add attributes to a class
>>> print(hasattr(ObjectCreator, 'new_attribute'))
True
>>> print(ObjectCreator.new_attribute)
foo
>>> ObjectCreatorMirror = ObjectCreator # you can assign a class to a variable
>>> print(ObjectCreatorMirror.new_attribute)
foo
>>> print(ObjectCreatorMirror())
<__main__.ObjectCreator object at 0x8997b4c>

Creating classes dynamically

Since classes are objects, you can create them on the fly, like any object.

First, you can create a class in a function using class:

>>> def choose_class(name):
...     if name == 'foo':
...         class Foo(object):
...             pass
...         return Foo # return the class, not an instance
...     else:
...         class Bar(object):
...             pass
...         return Bar
...
>>> MyClass = choose_class('foo')
>>> print(MyClass) # the function returns a class, not an instance
<class '__main__.Foo'>
>>> print(MyClass()) # you can create an object from this class
<__main__.Foo object at 0x89c6d4c>

But it’s not so dynamic, since you still have to write the whole class yourself.

Since classes are objects, they must be generated by something.

When you use the class keyword, Python creates this object automatically. But as with most things in Python, it gives you a way to do it manually.

Remember the function type? The good old function that lets you know what type an object is:

>>> print(type(1))
<type 'int'>
>>> print(type("1"))
<type 'str'>
>>> print(type(ObjectCreator))
<type 'type'>
>>> print(type(ObjectCreator()))
<class '__main__.ObjectCreator'>

Well, type has a completely different ability, it can also create classes on the fly. type can take the description of a class as parameters, and return a class.

(I know, it’s silly that the same function can have two completely different uses according to the parameters you pass to it. It’s an issue due to backward compatibility in Python)

type works this way:

type(name, bases, attrs)

Where:

  • name: name of the class
  • bases: tuple of the parent class (for inheritance, can be empty)
  • attrs: dictionary containing attributes names and values

e.g.:

>>> class MyShinyClass(object):
...       pass

can be created manually this way:

>>> MyShinyClass = type('MyShinyClass', (), {}) # returns a class object
>>> print(MyShinyClass)
<class '__main__.MyShinyClass'>
>>> print(MyShinyClass()) # create an instance with the class
<__main__.MyShinyClass object at 0x8997cec>

You’ll notice that we use MyShinyClass as the name of the class and as the variable to hold the class reference. They can be different, but there is no reason to complicate things.

type accepts a dictionary to define the attributes of the class. So:

>>> class Foo(object):
...       bar = True

Can be translated to:

>>> Foo = type('Foo', (), {'bar':True})

And used as a normal class:

>>> print(Foo)
<class '__main__.Foo'>
>>> print(Foo.bar)
True
>>> f = Foo()
>>> print(f)
<__main__.Foo object at 0x8a9b84c>
>>> print(f.bar)
True

And of course, you can inherit from it, so:

>>>   class FooChild(Foo):
...         pass

would be:

>>> FooChild = type('FooChild', (Foo,), {})
>>> print(FooChild)
<class '__main__.FooChild'>
>>> print(FooChild.bar) # bar is inherited from Foo
True

Eventually, you’ll want to add methods to your class. Just define a function with the proper signature and assign it as an attribute.

>>> def echo_bar(self):
...       print(self.bar)
...
>>> FooChild = type('FooChild', (Foo,), {'echo_bar': echo_bar})
>>> hasattr(Foo, 'echo_bar')
False
>>> hasattr(FooChild, 'echo_bar')
True
>>> my_foo = FooChild()
>>> my_foo.echo_bar()
True

And you can add even more methods after you dynamically create the class, just like adding methods to a normally created class object.

>>> def echo_bar_more(self):
...       print('yet another method')
...
>>> FooChild.echo_bar_more = echo_bar_more
>>> hasattr(FooChild, 'echo_bar_more')
True

You see where we are going: in Python, classes are objects, and you can create a class on the fly, dynamically.

This is what Python does when you use the keyword class, and it does so by using a metaclass.

What are metaclasses (finally)

Metaclasses are the ‘stuff’ that creates classes.

You define classes in order to create objects, right?

But we learned that Python classes are objects.

Well, metaclasses are what create these objects. They are the classes’ classes, you can picture them this way:

MyClass = MetaClass()
my_object = MyClass()

You’ve seen that type lets you do something like this:

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

It’s because the function type is in fact a metaclass. type is the metaclass Python uses to create all classes behind the scenes.

Now you wonder “why the heck is it written in lowercase, and not Type?”

Well, I guess it’s a matter of consistency with str, the class that creates strings objects, and int the class that creates integer objects. type is just the class that creates class objects.

You see that by checking the __class__ attribute.

Everything, and I mean everything, is an object in Python. That includes integers, strings, functions and classes. All of them are objects. And all of them have been created from a class:

>>> age = 35
>>> age.__class__
<type 'int'>
>>> name = 'bob'
>>> name.__class__
<type 'str'>
>>> def foo(): pass
>>> foo.__class__
<type 'function'>
>>> class Bar(object): pass
>>> b = Bar()
>>> b.__class__
<class '__main__.Bar'>

Now, what is the __class__ of any __class__ ?

>>> age.__class__.__class__
<type 'type'>
>>> name.__class__.__class__
<type 'type'>
>>> foo.__class__.__class__
<type 'type'>
>>> b.__class__.__class__
<type 'type'>

So, a metaclass is just the stuff that creates class objects.

You can call it a ‘class factory’ if you wish.

type is the built-in metaclass Python uses, but of course, you can create your own metaclass.

The __metaclass__ attribute

In Python 2, you can add a __metaclass__ attribute when you write a class (see next section for the Python 3 syntax):

class Foo(object):
    __metaclass__ = something...
    [...]

If you do so, Python will use the metaclass to create the class Foo.

Careful, it’s tricky.

You write class Foo(object) first, but the class object Foo is not created in memory yet.

Python will look for __metaclass__ in the class definition. If it finds it, it will use it to create the object class Foo. If it doesn’t, it will use type to create the class.

Read that several times.

When you do:

class Foo(Bar):
    pass

Python does the following:

Is there a __metaclass__ attribute in Foo?

If yes, create in-memory a class object (I said a class object, stay with me here), with the name Foo by using what is in __metaclass__.

If Python can’t find __metaclass__, it will look for a __metaclass__ at the MODULE level, and try to do the same (but only for classes that don’t inherit anything, basically old-style classes).

Then if it can’t find any __metaclass__ at all, it will use the Bar‘s (the first parent) own metaclass (which might be the default type) to create the class object.

Be careful here that the __metaclass__ attribute will not be inherited, the metaclass of the parent (Bar.__class__) will be. If Bar used a __metaclass__ attribute that created Bar with type() (and not type.__new__()), the subclasses will not inherit that behavior.

Now the big question is, what can you put in __metaclass__?

The answer is something that can create a class.

And what can create a class? type, or anything that subclasses or uses it.

Metaclasses in Python 3

The syntax to set the metaclass has been changed in Python 3:

class Foo(object, metaclass=something):
    ...

i.e. the __metaclass__ attribute is no longer used, in favor of a keyword argument in the list of base classes.

The behavior of metaclasses however stays largely the same.

One thing added to metaclasses in Python 3 is that you can also pass attributes as keyword-arguments into a metaclass, like so:

class Foo(object, metaclass=something, kwarg1=value1, kwarg2=value2):
    ...

Read the section below for how Python handles this.

Custom metaclasses

The main purpose of a metaclass is to change the class automatically, when it’s created.

You usually do this for APIs, where you want to create classes matching the current context.

Imagine a stupid example, where you decide that all classes in your module should have their attributes written in uppercase. There are several ways to do this, but one way is to set __metaclass__ at the module level.

This way, all classes of this module will be created using this metaclass, and we just have to tell the metaclass to turn all attributes to uppercase.

Luckily, __metaclass__ can actually be any callable, it doesn’t need to be a formal class (I know, something with ‘class’ in its name doesn’t need to be a class, go figure… but it’s helpful).

So we will start with a simple example, by using a function.

# the metaclass will automatically get passed the same argument
# that you usually pass to `type`
def upper_attr(future_class_name, future_class_parents, future_class_attrs):
    """
      Return a class object, with the list of its attribute turned
      into uppercase.
    """
    # pick up any attribute that doesn't start with '__' and uppercase it
    uppercase_attrs = {
        attr if attr.startswith("__") else attr.upper(): v
        for attr, v in future_class_attrs.items()
    }

    # let `type` do the class creation
    return type(future_class_name, future_class_parents, uppercase_attrs)

__metaclass__ = upper_attr # this will affect all classes in the module

class Foo(): # global __metaclass__ won't work with "object" though
    # but we can define __metaclass__ here instead to affect only this class
    # and this will work with "object" children
    bar = 'bip'

Let’s check:

>>> hasattr(Foo, 'bar')
False
>>> hasattr(Foo, 'BAR')
True
>>> Foo.BAR
'bip'

Now, let’s do exactly the same, but using a real class for a metaclass:

# remember that `type` is actually a class like `str` and `int`
# so you can inherit from it
class UpperAttrMetaclass(type):
    # __new__ is the method called before __init__
    # it's the method that creates the object and returns it
    # while __init__ just initializes the object passed as parameter
    # you rarely use __new__, except when you want to control how the object
    # is created.
    # here the created object is the class, and we want to customize it
    # so we override __new__
    # you can do some stuff in __init__ too if you wish
    # some advanced use involves overriding __call__ as well, but we won't
    # see this
    def __new__(upperattr_metaclass, future_class_name,
                future_class_parents, future_class_attrs):
        uppercase_attrs = {
            attr if attr.startswith("__") else attr.upper(): v
            for attr, v in future_class_attrs.items()
        }
        return type(future_class_name, future_class_parents, uppercase_attrs)

Let’s rewrite the above, but with shorter and more realistic variable names now that we know what they mean:

class UpperAttrMetaclass(type):
    def __new__(cls, clsname, bases, attrs):
        uppercase_attrs = {
            attr if attr.startswith("__") else attr.upper(): v
            for attr, v in attrs.items()
        }
        return type(clsname, bases, uppercase_attrs)

You may have noticed the extra argument cls. There is nothing special about it: __new__ always receives the class it’s defined in, as the first parameter. Just like you have self for ordinary methods which receive the instance as the first parameter, or the defining class for class methods.

But this is not proper OOP. We are calling type directly and we aren’t overriding or calling the parent’s __new__. Let’s do that instead:

class UpperAttrMetaclass(type):
    def __new__(cls, clsname, bases, attrs):
        uppercase_attrs = {
            attr if attr.startswith("__") else attr.upper(): v
            for attr, v in attrs.items()
        }
        return type.__new__(cls, clsname, bases, uppercase_attrs)

We can make it even cleaner by using super, which will ease inheritance (because yes, you can have metaclasses, inheriting from metaclasses, inheriting from type):

class UpperAttrMetaclass(type):
    def __new__(cls, clsname, bases, attrs):
        uppercase_attrs = {
            attr if attr.startswith("__") else attr.upper(): v
            for attr, v in attrs.items()
        }
        return super(UpperAttrMetaclass, cls).__new__(
            cls, clsname, bases, uppercase_attrs)

Oh, and in Python 3 if you do this call with keyword arguments, like this:

class Foo(object, metaclass=MyMetaclass, kwarg1=value1):
    ...

It translates to this in the metaclass to use it:

class MyMetaclass(type):
    def __new__(cls, clsname, bases, dct, kwargs1=default):
        ...

That’s it. There is really nothing more about metaclasses.

The reason behind the complexity of the code using metaclasses is not because of metaclasses, it’s because you usually use metaclasses to do twisted stuff relying on introspection, manipulating inheritance, vars such as __dict__, etc.

Indeed, metaclasses are especially useful to do black magic, and therefore complicated stuff. But by themselves, they are simple:

  • intercept a class creation
  • modify the class
  • return the modified class

Why would you use metaclasses classes instead of functions?

Since __metaclass__ can accept any callable, why would you use a class since it’s obviously more complicated?

There are several reasons to do so:

  • The intention is clear. When you read UpperAttrMetaclass(type), you know what’s going to follow
  • You can use OOP. Metaclass can inherit from metaclass, override parent methods. Metaclasses can even use metaclasses.
  • Subclasses of a class will be instances of its metaclass if you specified a metaclass-class, but not with a metaclass-function.
  • You can structure your code better. You never use metaclasses for something as trivial as the above example. It’s usually for something complicated. Having the ability to make several methods and group them in one class is very useful to make the code easier to read.
  • You can hook on __new____init__ and __call__. Which will allow you to do different stuff, Even if usually you can do it all in __new__, some people are just more comfortable using __init__.
  • These are called metaclasses, damn it! It must mean something!

Why would you use metaclasses?

Now the big question. Why would you use some obscure error-prone feature?

Well, usually you don’t:

Metaclasses are deeper magic that 99% of users should never worry about it. If you wonder whether you need them, you don’t (the people who actually need them to know with certainty that they need them and don’t need an explanation about why).

Python Guru Tim Peters

The main use case for a metaclass is creating an API. A typical example of this is the Django ORM. It allows you to define something like this:

class Person(models.Model):
    name = models.CharField(max_length=30)
    age = models.IntegerField()

But if you do this:

person = Person(name='bob', age='35')
print(person.age)

It won’t return an IntegerField object. It will return an int, and can even take it directly from the database.

This is possible because models.Model defines __metaclass__ and it uses some magic that will turn the Person you just defined with simple statements into a complex hook to a database field.

Django makes something complex look simple by exposing a simple API and using metaclasses, recreating code from this API to do the real job behind the scenes.

The last word

First, you know that classes are objects that can create instances.

Well, in fact, classes are themselves instances. Of metaclasses.

>>> class Foo(object): pass
>>> id(Foo)
142630324

Everything is an object in Python, and they are all either instance of classes or instances of metaclasses.

Except for type.

type is actually its own metaclass. This is not something you could reproduce in pure Python, and is done by cheating a little bit at the implementation level.

Secondly, metaclasses are complicated. You may not want to use them for very simple class alterations. You can change classes by using two different techniques:

99% of the time you need class alteration, you are better off using these.

But 98% of the time, you don’t need class alteration at all.

What are metaclasses in Python? Answer #2:

A metaclass is the class of a class. A class defines how an instance of the class (i.e. an object) behaves while a metaclass defines how a class behaves. A class is an instance of a metaclass.

While in Python you can use arbitrary callables for metaclasses (like Jerub shows), the better approach is to make it an actual class itself. type is the usual metaclass in Python. type is itself a class, and it is its own type. You won’t be able to recreate something like type purely in Python, but Python cheats a little. To create your own metaclass in Python you really just want to subclass type.

A metaclass is most commonly used as a class-factory. When you create an object by calling the class, Python creates a new class (when it executes the ‘class’ statement) by calling the metaclass. Combined with the normal __init__ and __new__ methods, metaclasses therefore allow you to do ‘extra things’ when creating a class, like registering the new class with some registry or replace the class with something else entirely.

When the class statement is executed, Python first executes the body of the class statement as a normal block of code. The resulting namespace (a dict) holds the attributes of the class-to-be. The metaclass is determined by looking at the baseclasses of the class-to-be (metaclasses are inherited), at the __metaclass__ attribute of the class-to-be (if any) or the __metaclass__ global variable. The metaclass is then called with the name, bases and attributes of the class to instantiate it.

However, metaclasses actually define the type of a class, not just a factory for it, so you can do much more with them. You can, for instance, define normal methods on the metaclass. These metaclass-methods are like classmethods in that they can be called on the class without an instance, but they are also not like classmethods in that they cannot be called on an instance of the class. type.__subclasses__() is an example of a method on the type metaclass. You can also define the normal ‘magic’ methods, like __add____iter__ and __getattr__, to implement or change how the class behaves.

Here’s an aggregated example of the bits and pieces:

def make_hook(f):
    """Decorator to turn 'foo' method into '__foo__'"""
    f.is_hook = 1
    return f

class MyType(type):
    def __new__(mcls, name, bases, attrs):

        if name.startswith('None'):
            return None

        # Go over attributes and see if they should be renamed.
        newattrs = {}
        for attrname, attrvalue in attrs.iteritems():
            if getattr(attrvalue, 'is_hook', 0):
                newattrs['__%s__' % attrname] = attrvalue
            else:
                newattrs[attrname] = attrvalue

        return super(MyType, mcls).__new__(mcls, name, bases, newattrs)

    def __init__(self, name, bases, attrs):
        super(MyType, self).__init__(name, bases, attrs)

        # classregistry.register(self, self.interfaces)
        print "Would register class %s now." % self

    def __add__(self, other):
        class AutoClass(self, other):
            pass
        return AutoClass
        # Alternatively, to autogenerate the classname as well as the class:
        # return type(self.__name__ + other.__name__, (self, other), {})

    def unregister(self):
        # classregistry.unregister(self)
        print "Would unregister class %s now." % self

class MyObject:
    __metaclass__ = MyType


class NoneSample(MyObject):
    pass

# Will print "NoneType None"
print type(NoneSample), repr(NoneSample)

class Example(MyObject):
    def __init__(self, value):
        self.value = value
    @make_hook
    def add(self, other):
        return self.__class__(self.value + other.value)

# Will unregister the class
Example.unregister()

inst = Example(10)
# Will fail with an AttributeError
#inst.unregister()

print inst + inst
class Sibling(MyObject):
    pass

ExampleSibling = Example + Sibling
# ExampleSibling is now a subclass of both Example and Sibling (with no
# content of its own) although it will believe it's called 'AutoClass'
print ExampleSibling
print ExampleSibling.__mro__

Answer #3:

Note, this answer is for Python 2.x as it was written in 2008, metaclasses are slightly different in 3.x.

Metaclasses are the secret sauce that make ‘class’ work. The default metaclass for a new style object is called ‘type’.

class type(object)
  |  type(object) -> the object's type
  |  type(name, bases, dict) -> a new type

Metaclasses take 3 args. ‘name‘, ‘bases‘ and ‘dict

Here is where the secret starts. Look for where name, bases and the dict come from in this example class definition.

class ThisIsTheName(Bases, Are, Here):
    All_the_code_here
    def doesIs(create, a):
        dict

Lets define a metaclass that will demonstrate how ‘class:‘ calls it.

def test_metaclass(name, bases, dict):
    print 'The Class Name is', name
    print 'The Class Bases are', bases
    print 'The dict has', len(dict), 'elems, the keys are', dict.keys()

    return "yellow"

class TestName(object, None, int, 1):
    __metaclass__ = test_metaclass
    foo = 1
    def baz(self, arr):
        pass

print 'TestName = ', repr(TestName)

# output => 
The Class Name is TestName
The Class Bases are (<type 'object'>, None, <type 'int'>, 1)
The dict has 4 elems, the keys are ['baz', '__module__', 'foo', '__metaclass__']
TestName =  'yellow'

And now, an example that actually means something, this will automatically make the variables in the list “attributes” set on the class, and set to None.

def init_attributes(name, bases, dict):
    if 'attributes' in dict:
        for attr in dict['attributes']:
            dict[attr] = None

    return type(name, bases, dict)

class Initialised(object):
    __metaclass__ = init_attributes
    attributes = ['foo', 'bar', 'baz']

print 'foo =>', Initialised.foo
# output=>
foo => None

Note that the magic behaviour that Initialised gains by having the metaclass init_attributes is not passed onto a subclass of Initialised.

Here is an even more concrete example, showing how you can subclass ‘type’ to make a metaclass that performs an action when the class is created. This is quite tricky:

class MetaSingleton(type):
    instance = None
    def __call__(cls, *args, **kw):
        if cls.instance is None:
            cls.instance = super(MetaSingleton, cls).__call__(*args, **kw)
        return cls.instance

class Foo(object):
    __metaclass__ = MetaSingleton

a = Foo()
b = Foo()
assert a is b

Answer #4:

Others have explained how metaclasses work and how they fit into the Python type system. Here’s an example of what they can be used for. In a testing framework I wrote, I wanted to keep track of the order in which classes were defined, so that I could later instantiate them in this order. I found it easiest to do this using a metaclass.

class MyMeta(type):

    counter = 0

    def __init__(cls, name, bases, dic):
        type.__init__(cls, name, bases, dic)
        cls._order = MyMeta.counter
        MyMeta.counter += 1

class MyType(object):              # Python 2
    __metaclass__ = MyMeta

class MyType(metaclass=MyMeta):    # Python 3
    pass

Anything that’s a subclass of MyType then gets a class attribute _order that records the order in which the classes were defined.

Answer #5:

One use for metaclasses is adding new properties and methods to an instance automatically.

For example, if you look at Django models, their definition looks a bit confusing. It looks as if you are only defining class properties:

class Person(models.Model):
    first_name = models.CharField(max_length=30)
    last_name = models.CharField(max_length=30)

However, at runtime the Person objects are filled with all sorts of useful methods. See the source for some amazing metaclassery.

Answer #6:

What are metaclasses? What do you use them for?

TLDR: A metaclass instantiates and defines behavior for a class just like a class instantiates and defines behavior for an instance.

Pseudocode:

>>> Class(...)
instance

The above should look familiar. Well, where does Class come from? It’s an instance of a metaclass (also pseudocode):

>>> Metaclass(...)
Class

In real code, we can pass the default metaclass, type, everything we need to instantiate a class and we get a class:

>>> type('Foo', (object,), {}) # requires a name, bases, and a namespace
<class '__main__.Foo'>

Putting it differently

  • A class is to an instance as a metaclass is to a class.When we instantiate an object, we get an instance:>>> object() # instantiation of class <object object at 0x7f9069b4e0b0> # instance Likewise, when we define a class explicitly with the default metaclass, type, we instantiate it:>>> type('Object', (object,), {}) # instantiation of metaclass <class '__main__.Object'> # instance
  • Put another way, a class is an instance of a metaclass:>>> isinstance(object, type) True
  • Put a third way, a metaclass is a class’s class.>>> type(object) == type True >>> object.__class__ <class 'type'>

When you write a class definition and Python executes it, it uses a metaclass to instantiate the class object (which will, in turn, be used to instantiate instances of that class).

Just as we can use class definitions to change how custom object instances behave, we can use a metaclass class definition to change the way a class object behaves.

What can they be used for? From the docs:

The potential uses for metaclasses are boundless. Some ideas that have been explored include logging, interface checking, automatic delegation, automatic property creation, proxies, frameworks, and automatic resource locking/synchronization.

Nevertheless, it is usually encouraged for users to avoid using metaclasses unless absolutely necessary.

You use a metaclass every time you create a class:

When you write a class definition, for example, like this,

class Foo(object): 
    'demo'

You instantiate a class object.

>>> Foo
<class '__main__.Foo'>
>>> isinstance(Foo, type), isinstance(Foo, object)
(True, True)

It is the same as functionally calling type with the appropriate arguments and assigning the result to a variable of that name:

name = 'Foo'
bases = (object,)
namespace = {'__doc__': 'demo'}
Foo = type(name, bases, namespace)

Note, some things automatically get added to the __dict__, i.e., the namespace:

>>> Foo.__dict__
dict_proxy({'__dict__': <attribute '__dict__' of 'Foo' objects>, 
'__module__': '__main__', '__weakref__': <attribute '__weakref__' 
of 'Foo' objects>, '__doc__': 'demo'})

The metaclass of the object we created, in both cases, is type.

(A side-note on the contents of the class __dict____module__ is there because classes must know where they are defined, and __dict__ and __weakref__ are there because we don’t define __slots__ – if we define __slots__ we’ll save a bit of space in the instances, as we can disallow __dict__ and __weakref__ by excluding them. For example:

>>> Baz = type('Bar', (object,), {'__doc__': 'demo', '__slots__': ()})
>>> Baz.__dict__
mappingproxy({'__doc__': 'demo', '__slots__': (), '__module__': '__main__'})

… but I digress.)

We can extend type just like any other class definition:

Here’s the default __repr__ of classes:

>>> Foo
<class '__main__.Foo'>

One of the most valuable things we can do by default in writing a Python object is to provide it with a good __repr__. When we call help(repr) we learn that there’s a good test for a __repr__ that also requires a test for equality – obj == eval(repr(obj)). The following simple implementation of __repr__ and __eq__ for class instances of our type class provides us with a demonstration that may improve on the default __repr__ of classes:

class Type(type):
    def __repr__(cls):
        """
        >>> Baz
        Type('Baz', (Foo, Bar,), {'__module__': '__main__', '__doc__': None})
        >>> eval(repr(Baz))
        Type('Baz', (Foo, Bar,), {'__module__': '__main__', '__doc__': None})
        """
        metaname = type(cls).__name__
        name = cls.__name__
        parents = ', '.join(b.__name__ for b in cls.__bases__)
        if parents:
            parents += ','
        namespace = ', '.join(': '.join(
          (repr(k), repr(v) if not isinstance(v, type) else v.__name__))
               for k, v in cls.__dict__.items())
        return '{0}(\'{1}\', ({2}), {{{3}}})'.format(metaname, name, parents, namespace)
    def __eq__(cls, other):
        """
        >>> Baz == eval(repr(Baz))
        True            
        """
        return (cls.__name__, cls.__bases__, cls.__dict__) == (
                other.__name__, other.__bases__, other.__dict__)

So now when we create an object with this metaclass, the __repr__ echoed on the command line provides a much less ugly sight than the default:

>>> class Bar(object): pass
>>> Baz = Type('Baz', (Foo, Bar,), {'__module__': '__main__', '__doc__': None})
>>> Baz
Type('Baz', (Foo, Bar,), {'__module__': '__main__', '__doc__': None})

With a nice __repr__ defined for the class instance, we have a stronger ability to debug our code. However, much further checking with eval(repr(Class)) is unlikely (as functions would be rather impossible to eval from their default __repr__‘s).

An expected usage: __prepare__ a namespace

If, for example, we want to know in what order a class’s methods are created in, we could provide an ordered dict as the namespace of the class. We would do this with __prepare__ which returns the namespace dict for the class if it is implemented in Python 3:

from collections import OrderedDict

class OrderedType(Type):
    @classmethod
    def __prepare__(metacls, name, bases, **kwargs):
        return OrderedDict()
    def __new__(cls, name, bases, namespace, **kwargs):
        result = Type.__new__(cls, name, bases, dict(namespace))
        result.members = tuple(namespace)
        return result

And usage:

class OrderedMethodsObject(object, metaclass=OrderedType):
    def method1(self): pass
    def method2(self): pass
    def method3(self): pass
    def method4(self): pass

And now we have a record of the order in which these methods (and other class attributes) were created:

>>> OrderedMethodsObject.members
('__module__', '__qualname__', 'method1', 'method2', 'method3', 'method4')

Note, this example was adapted from the documentation – the new enum in the standard library does this.

So what we did was instantiate a metaclass by creating a class. We can also treat the metaclass as we would any other class. It has a method resolution order:

>>> inspect.getmro(OrderedType)
(<class '__main__.OrderedType'>, <class '__main__.Type'>, <class 'type'>, <class 'object'>)

And it has approximately the correct repr (which we can no longer eval unless we can find a way to represent our functions.):

>>> OrderedMethodsObject
OrderedType('OrderedMethodsObject', (object,), {'method1': <function OrderedMethodsObject.method1 at 0x0000000002DB01E0>, 'members': ('__module__', '__qualname__', 'method1', 'method2', 'method3', 'method4'), 'method3': <function OrderedMet
hodsObject.method3 at 0x0000000002DB02F0>, 'method2': <function OrderedMethodsObject.method2 at 0x0000000002DB0268>, '__module__': '__main__', '__weakref__': <attribute '__weakref__' of 'OrderedMethodsObject' objects>, '__doc__': None, '__d
ict__': <attribute '__dict__' of 'OrderedMethodsObject' objects>, 'method4': <function OrderedMethodsObject.method4 at 0x0000000002DB0378>})

Answer #7:

Python 3 update

There are (at this point) two key methods in a metaclass:

  • __prepare__, and
  • __new__

__prepare__ lets you supply a custom mapping (such as an OrderedDict) to be used as the namespace while the class is being created. You must return an instance of whatever namespace you choose. If you don’t implement __prepare__ a normal dict is used.

__new__ is responsible for the actual creation/modification of the final class.

A bare-bones, do-nothing-extra metaclass would like:

class Meta(type):

    def __prepare__(metaclass, cls, bases):
        return dict()

    def __new__(metacls, cls, bases, clsdict):
        return super().__new__(metacls, cls, bases, clsdict)

A simple example:

Say you want some simple validation code to run on your attributes — like it must always be an int or a str. Without a metaclass, your class would look something like:

class Person:
    weight = ValidateType('weight', int)
    age = ValidateType('age', int)
    name = ValidateType('name', str)

As you can see, you have to repeat the name of the attribute twice. This makes typos possible along with irritating bugs.

A simple metaclass can address that problem:

class Person(metaclass=Validator):
    weight = ValidateType(int)
    age = ValidateType(int)
    name = ValidateType(str)

This is what the metaclass would look like (not using __prepare__ since it is not needed):

class Validator(type):
    def __new__(metacls, cls, bases, clsdict):
        # search clsdict looking for ValidateType descriptors
        for name, attr in clsdict.items():
            if isinstance(attr, ValidateType):
                attr.name = name
                attr.attr = '_' + name
        # create final class and return it
        return super().__new__(metacls, cls, bases, clsdict)

A sample run of:

p = Person()
p.weight = 9
print(p.weight)
p.weight = '9'

produces:

9
Traceback (most recent call last):
  File "simple_meta.py", line 36, in <module>
    p.weight = '9'
  File "simple_meta.py", line 24, in __set__
    (self.name, self.type, value))
TypeError: weight must be of type(s) <class 'int'> (got '9')

Note: This example is simple enough it could have also been accomplished with a class decorator, but presumably an actual metaclass would be doing much more.

The ‘ValidateType’ class for reference:

class ValidateType:
    def __init__(self, type):
        self.name = None  # will be set by metaclass
        self.attr = None  # will be set by metaclass
        self.type = type
    def __get__(self, inst, cls):
        if inst is None:
            return self
        else:
            return inst.__dict__[self.attr]
    def __set__(self, inst, value):
        if not isinstance(value, self.type):
            raise TypeError('%s must be of type(s) %s (got %r)' %
                    (self.name, self.type, value))
        else:
            inst.__dict__[self.attr] = value

Hope you learned something from this post.

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