Python metaclasses demystified

Python metaclasses demystified

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 backwards compatibility in Python)

type works this way:

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

e.g.:

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

It 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')
>>> hasattr(FooChild, 'echo_bar')
True
>>> my_foo = FooChild()
>>> my_foo.echo_bar()
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. There are the classes’ classes, you can picture them this way:

MyClass = MetaClass()
MyObject = 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__ ?

>>> a.__class__.__class__
< type 'type'>
>>> age.__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

You can add a __metaclass__ attribute when you write a class:

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, if 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:

  1. 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__.
  2. If Python can’t find __metaclass__, it will look for a __metaclass__ in Bar (the parent class), and try to do the same.
  3. If Python can’t find __metaclass__ in any parent, it will look for a __metaclass__ at the MODULE level, and try to do the same.
  4. Then if it can’t find any __metaclass__ at all, it will use type to create the class object.

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.

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 <code>type</code>
def upper_attr(future_class_name, future_class_parents, future_class_attr):
    """
      Return a class object, with the list of its attribute turned
      into uppercase.
    """
 
    # pick up any attribute that doesn't start with '__'
    attrs = ((name, value) for name, value in future_class_attr.items() if not name.startswith('__'))
    # turn them into uppercase
    uppercase_attr = dict((name.upper(), value) for name, value in attrs)
 
    # let <code>type</code> do the class creation
    return type(future_class_name, future_class_parents, uppercase_attr)
 
__metaclass__ = upper_attr # this will affect all classes in the module
 
class Foo(object):
    # we can define __metaclass__ here instead to affect only this class
    bar = 'bip'
 
print hasattr(Foo, 'bar')
# Out: False
print hasattr(Foo, 'BAR')
# Out: True
 
f = Foo()
print f.BAR
# Out: 'bip'

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

# remember that <code>type</code> is actually a class like <code>str</code> and <code>int</code>
# 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_attr):
 
      attrs = ((name, value) for name, value in future_class_attr.items() if not name.startswith('__'))
      uppercase_attr = dict((name.upper(), value) for name, value in attrs)
 
      return type(future_class_name, future_class_parents, uppercase_attr)

But this is not really OOP. We call type directly and we don’t override call the parent __new__. Let’s do it:

class UpperAttrMetaclass(type):
 
  def __new__(upperattr_metaclass, future_class_name,
              future_class_parents, future_class_attr):
 
      attrs = ((name, value) for name, value in future_class_attr.items() if not name.startswith('__'))
      uppercase_attr = dict((name.upper(), value) for name, value in attrs)
 
      # reuse the type.__new__ method
      # this is basic OOP, nothing magic in there
      return type.__new__(upperattr_metaclass, future_class_name,
                          future_class_parents, uppercase_attr)

You may have noticed the extra argument upperattr_metaclass. There is nothing special about it: a method always receives the current instance as first parameter. Just like you have self for ordinary methods.

Of course, the names I used here are long for the sake of clarity, but like for self, all the arguments have conventional names. So a real production metaclass would look like this:

class UpperAttrMetaclass(type):
 
  def __new__(cls, name, bases, dct):
 
      attrs = ((name, value) for name, value in dct.items() if not name.startswith('__'))
      uppercase_attr = dict((name.upper(), value) for name, value in attrs)
 
      return type.__new__(cls, name, bases, uppercase_attr)

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, name, bases, dct):
 
      attrs = ((name, value) for name, value in dct.items() if not name.startswith('__'))
      uppercase_attr = dict((name.upper(), value) for name, value in attrs)
 
      return super(UpperAttrMetaclass, cls).__new__(cls, name, bases, uppercase_attr)

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 sutff. 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.
  • 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 the hell would you use metaclasses?

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

Well, usually you don’t:

Metaclasses are deeper magic than 99% of users should ever worry about. If you wonder whether you need them, you don’t (the people who actually need them 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:

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

For the twisted minds…

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 instances 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:

  • monkey patching;
  • class decorators.

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

But 99% of the time, you don’t need class alteration at all :-)

Aiming Python 3?

In Python 3 the metaclass implementation has been cleaned up.

Firstly, the module level __metaclass__ variable is not used anymore.

Secondly, the syntax to use a metaclass is different:

class YouClass(metaclass=YourMetaClass):
    pass

And last but not least, the __prepare__ method make it much easier to populate class attributes, by including the return value (which should be a dict) into __dict__. It’s handy as it’s a very common use case:

class MyMetaClass(type):
    @classmethod
    def __prepare__(cls, name, baseClasses):
        return {'foo':'bar'}
 
class YourClass(metaclass=MyMetaClass):
    pass
 
print(YourClass.foo)
# this ouputs 'bar'

I initially posted this article on Stackoverflow.com, but I think it can get some visibility here. To avoid the copy/paste syndrom, I added some extra informations about the metaclasses in Python 3 and did some clean up.

Edit:

WOW, the article as been translated to Russian.

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