Hi there pythonistas. Recently I was searching about metaclasses in Python and came across a very good explanation about metaclasses on stackoverflow. I found the answer really helpful so I think you should read it as well. Who knows when you might find something useful in there.
Disclaimer: very long post.
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
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
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() 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 ints, 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
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, 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__
in Bar (the parent class), and try to do the same.
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.
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 `type` 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 '__' and uppercase it uppercase_attr = {} for name, val in future_class_attr.items(): if not name.startswith('__'): uppercase_attr[name.upper()] = val else: uppercase_attr[name] = val # let `type` 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(): # 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' 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 `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_attr): uppercase_attr = {} for name, val in future_class_attr.items(): if not name.startswith('__'): uppercase_attr[name.upper()] = val else: uppercase_attr[name] = val 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): uppercase_attr = {} for name, val in future_class_attr.items(): if not name.startswith('__'): uppercase_attr[name.upper()] = val else: uppercase_attr[name] = val # 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, clsname, bases, dct): uppercase_attr = {} for name, val in dct.items(): if not name.startswith('__'): uppercase_attr[name.upper()] = val else: uppercase_attr[name] = val return type.__new__(cls, clsname, 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, clsname, bases, dct): uppercase_attr = {} for name, val in dct.items(): if not name.startswith('__'): uppercase_attr[name.upper()] = val else: uppercase_attr[name] = val return super(UpperAttrMetaclass, cls).__new__(cls, clsname, 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 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. - 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 you 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.
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 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 :-)
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