Summary: in this tutorial, you’ll learn about a Python metaclass example that creates classes with many features.
Introduction to the Python metaclass example
The following defines a Person
class with two attributes name
and age
:
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
@property
def name(self):
return self._name
@name.setter
def name(self, value):
self._name = value
@property
def age(self):
return self._age
@age.setter
def age(self, value):
self._age = value
def __eq__(self, other):
return self.name == other.name and self.age == other.age
def __hash__(self):
return hash(f'{self.name, self.age}')
def __str__(self):
return f'Person(name={self.name},age={self.age})'
def __repr__(self):
return f'Person(name={self.name},age={self.age})'
Code language: Python (python)
Typically, when defining a new class, you need to:
- Define a list of object’s properties.
- Define an
__init__
method to initialize object’s attributes. - Implement the
__str__
and__repr__
methods to represent the objects in human-readable and machine-readable formats. - Implement the
__eq__
method to compare objects by values of all properties. - Implement the
__hash__
method to use the objects of the class as keys of a dictionary or elements of a set.
As you can see, it requires a lot of code.
Imagine you want to define a Person class like this and automagically has all the functions above:
class Person:
props = ['first_name', 'last_name', 'age']
Code language: Python (python)
To do that, you can use a metaclass.
Define a metaclass
First, define the Data
metaclass that inherits from the type
class:
class Data(type):
pass
Code language: Python (python)
Second, override the __new__
method to return a new class object:
class Data(type):
def __new__(mcs, name, bases, class_dict):
class_obj = super().__new__(mcs, name, bases, class_dict)
return class_obj
Code language: Python (python)
Note that the __new__
method is a static method of the Data
metaclass. And you don’t need to use the @staticmethod
decorator because Python treats it special.
Also, the __new__
method creates a new class like the Person
class, not the instance of the Person
class.
Create property objects
First, define a Prop
class that accepts an attribute name and contains three methods for creating a property object(set
, get
, and delete
). The Data
metaclass will use this Prop
class for adding property objects to the class.
class Prop:
def __init__(self, attr):
self._attr = attr
def get(self, obj):
return getattr(obj, self._attr)
def set(self, obj, value):
return setattr(obj, self._attr, value)
def delete(self, obj):
return delattr(obj, self._attr)
Code language: Python (python)
Second, create a new static method define_property()
that creates a property object for each attribute from the props
list:
class Data(type):
def __new__(mcs, name, bases, class_dict):
class_obj = super().__new__(mcs, name, bases, class_dict)
Data.define_property(class_obj)
return class_obj
@staticmethod
def define_property(class_obj):
for prop in class_obj.props:
attr = f'_{prop}'
prop_obj = property(
fget=Prop(attr).get,
fset=Prop(attr).set,
fdel=Prop(attr).delete
)
setattr(class_obj, prop, prop_obj)
return class_obj
Code language: Python (python)
The following defines the Person
class that uses the Data
metaclass:
class Person(metaclass=Data):
props = ['name', 'age']
Code language: Python (python)
The Person
class has two properties name
and age
:
pprint(Person.__dict__)
Code language: Python (python)
Output:
mappingproxy({'__dict__': <attribute '__dict__' of 'Person' objects>,
'__doc__': None,
'__module__': '__main__',
'__weakref__': <attribute '__weakref__' of 'Person' objects>,
'age': <property object at 0x000002213CA92090>,
'name': <property object at 0x000002213C772A90>,
'props': ['name', 'age']})
Code language: Python (python)
Define __init__ method
The following defines an init
static method and assign it to the __init__
attribute of the class object:
class Data(type):
def __new__(mcs, name, bases, class_dict):
class_obj = super().__new__(mcs, name, bases, class_dict)
# create property
Data.define_property(class_obj)
# define __init__
setattr(class_obj, '__init__', Data.init(class_obj))
return class_obj
@staticmethod
def init(class_obj):
def _init(self, *obj_args, **obj_kwargs):
if obj_kwargs:
for prop in class_obj.props:
if prop in obj_kwargs.keys():
setattr(self, prop, obj_kwargs[prop])
if obj_args:
for kv in zip(class_obj.props, obj_args):
setattr(self, kv[0], kv[1])
return _init
# more methods
Code language: Python (python)
The following creates a new instance of the Person
class and initialize its attributes:
p = Person('John Doe', age=25)
print(p.__dict__)
Code language: Python (python)
Output:
{'_age': 25, '_name': 'John Doe'}
Code language: Python (python)
The p.__dict__
contains two attributes _name
and _age
based on the predefined names in the props
list.
Define __repr__ method
The following defines the repr
static method that returns a function and uses it for the __repr__
attribute of the class object:
class Data(type):
def __new__(mcs, name, bases, class_dict):
class_obj = super().__new__(mcs, name, bases, class_dict)
# create property
Data.define_property(class_obj)
# define __init__
setattr(class_obj, '__init__', Data.init(class_obj))
# define __repr__
setattr(class_obj, '__repr__', Data.repr(class_obj))
return class_obj
@staticmethod
def repr(class_obj):
def _repr(self):
prop_values = (getattr(self, prop) for prop in class_obj.props)
prop_key_values = (f'{key}={value}' for key, value in zip(class_obj.props, prop_values))
prop_key_values_str = ', '.join(prop_key_values)
return f'{class_obj.__name__}({prop_key_values_str})'
return _repr
Code language: Python (python)
The following creates a new instance of the Person
class and displays it:
p = Person('John Doe', age=25)
print(p)
Code language: Python (python)
Output:
Person(name=John Doe, age=25)
Code language: Python (python)
Define __eq__ and __hash__ methods
The following defines the eq
and hash
methods and assigns them to the __eq__
and __hash__
of the class object of the metaclass:
class Data(type):
def __new__(mcs, name, bases, class_dict):
class_obj = super().__new__(mcs, name, bases, class_dict)
# create property
Data.define_property(class_obj)
# define __init__
setattr(class_obj, '__init__', Data.init(class_obj))
# define __repr__
setattr(class_obj, '__repr__', Data.repr(class_obj))
# define __eq__ & __hash__
setattr(class_obj, '__eq__', Data.eq(class_obj))
setattr(class_obj, '__hash__', Data.hash(class_obj))
return class_obj
@staticmethod
def eq(class_obj):
def _eq(self, other):
if not isinstance(other, class_obj):
return False
self_values = [getattr(self, prop) for prop in class_obj.props]
other_values = [getattr(other, prop) for prop in other.props]
return self_values == other_values
return _eq
@staticmethod
def hash(class_obj):
def _hash(self):
values = (getattr(self, prop) for prop in class_obj.props)
return hash(tuple(values))
return _hash
Code language: Python (python)
The following creates two instances of the Person and compares them. If the values of all properties are the same, they will be equal. Otherwise, they will not be equal:
p1 = Person('John Doe', age=25)
p2 = Person('Jane Doe', age=25)
print(p1 == p2) # False
p2.name = 'John Doe'
print(p1 == p2) # True
Code language: Python (python)
Put it all together
from pprint import pprint
class Prop:
def __init__(self, attr):
self._attr = attr
def get(self, obj):
return getattr(obj, self._attr)
def set(self, obj, value):
return setattr(obj, self._attr, value)
def delete(self, obj):
return delattr(obj, self._attr)
class Data(type):
def __new__(mcs, name, bases, class_dict):
class_obj = super().__new__(mcs, name, bases, class_dict)
# create property
Data.define_property(class_obj)
# define __init__
setattr(class_obj, '__init__', Data.init(class_obj))
# define __repr__
setattr(class_obj, '__repr__', Data.repr(class_obj))
# define __eq__ & __hash__
setattr(class_obj, '__eq__', Data.eq(class_obj))
setattr(class_obj, '__hash__', Data.hash(class_obj))
return class_obj
@staticmethod
def eq(class_obj):
def _eq(self, other):
if not isinstance(other, class_obj):
return False
self_values = [getattr(self, prop) for prop in class_obj.props]
other_values = [getattr(other, prop) for prop in other.props]
return self_values == other_values
return _eq
@staticmethod
def hash(class_obj):
def _hash(self):
values = (getattr(self, prop) for prop in class_obj.props)
return hash(tuple(values))
return _hash
@staticmethod
def repr(class_obj):
def _repr(self):
prop_values = (getattr(self, prop) for prop in class_obj.props)
prop_key_values = (f'{key}={value}' for key, value in zip(class_obj.props, prop_values))
prop_key_values_str = ', '.join(prop_key_values)
return f'{class_obj.__name__}({prop_key_values_str})'
return _repr
@staticmethod
def init(class_obj):
def _init(self, *obj_args, **obj_kwargs):
if obj_kwargs:
for prop in class_obj.props:
if prop in obj_kwargs.keys():
setattr(self, prop, obj_kwargs[prop])
if obj_args:
for kv in zip(class_obj.props, obj_args):
setattr(self, kv[0], kv[1])
return _init
@staticmethod
def define_property(class_obj):
for prop in class_obj.props:
attr = f'_{prop}'
prop_obj = property(
fget=Prop(attr).get,
fset=Prop(attr).set,
fdel=Prop(attr).delete
)
setattr(class_obj, prop, prop_obj)
return class_obj
class Person(metaclass=Data):
props = ['name', 'age']
if __name__ == '__main__':
pprint(Person.__dict__)
p1 = Person('John Doe', age=25)
p2 = Person('Jane Doe', age=25)
print(p1 == p2) # False
p2.name = 'John Doe'
print(p1 == p2) # True
Code language: Python (python)
Decorator
The following defines a class called Employee
that uses the Data
metaclass:
class Employee(metaclass=Data):
props = ['name', 'job_title']
if __name__ == '__main__':
e = Employee(name='John Doe', job_title='Python Developer')
print(e)
Code language: Python (python)
Output:
Employee(name=John Doe, job_title=Python Developer)
Code language: Python (python)
It works as expected. However, specifying the metaclass is quite verbose. To improve this, you can use a function decorator.
First, define a function decorator that returns a new class which is an instance of the Data
metaclass:
def data(cls):
return Data(cls.__name__, cls.__bases__, dict(cls.__dict__))
Code language: Python (python)
Second, use the @data
decorator for any class that uses the Data
as the metaclass:
@data
class Employee:
props = ['name', 'job_title']
Code language: Python (python)
The following shows the complete code:
class Prop:
def __init__(self, attr):
self._attr = attr
def get(self, obj):
return getattr(obj, self._attr)
def set(self, obj, value):
return setattr(obj, self._attr, value)
def delete(self, obj):
return delattr(obj, self._attr)
class Data(type):
def __new__(mcs, name, bases, class_dict):
class_obj = super().__new__(mcs, name, bases, class_dict)
# create property
Data.define_property(class_obj)
# define __init__
setattr(class_obj, '__init__', Data.init(class_obj))
# define __repr__
setattr(class_obj, '__repr__', Data.repr(class_obj))
# define __eq__ & __hash__
setattr(class_obj, '__eq__', Data.eq(class_obj))
setattr(class_obj, '__hash__', Data.hash(class_obj))
return class_obj
@staticmethod
def eq(class_obj):
def _eq(self, other):
if not isinstance(other, class_obj):
return False
self_values = [getattr(self, prop) for prop in class_obj.props]
other_values = [getattr(other, prop) for prop in other.props]
return self_values == other_values
return _eq
@staticmethod
def hash(class_obj):
def _hash(self):
values = (getattr(self, prop) for prop in class_obj.props)
return hash(tuple(values))
return _hash
@staticmethod
def repr(class_obj):
def _repr(self):
prop_values = (getattr(self, prop) for prop in class_obj.props)
prop_key_values = (f'{key}={value}' for key, value in zip(class_obj.props, prop_values))
prop_key_values_str = ', '.join(prop_key_values)
return f'{class_obj.__name__}({prop_key_values_str})'
return _repr
@staticmethod
def init(class_obj):
def _init(self, *obj_args, **obj_kwargs):
if obj_kwargs:
for prop in class_obj.props:
if prop in obj_kwargs.keys():
setattr(self, prop, obj_kwargs[prop])
if obj_args:
for kv in zip(class_obj.props, obj_args):
setattr(self, kv[0], kv[1])
return _init
@staticmethod
def define_property(class_obj):
for prop in class_obj.props:
attr = f'_{prop}'
prop_obj = property(
fget=Prop(attr).get,
fset=Prop(attr).set,
fdel=Prop(attr).delete
)
setattr(class_obj, prop, prop_obj)
return class_obj
class Person(metaclass=Data):
props = ['name', 'age']
def data(cls):
return Data(cls.__name__, cls.__bases__, dict(cls.__dict__))
@data
class Employee:
props = ['name', 'job_title']
Code language: Python (python)
Python 3.7 provided a @dataclass
decorator specified in the PEP 557 that has some features like the Data
metaclass. Also, the dataclass offers more features that help you save time when working with classes.