How does the @property decorator work in Python?

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How does the @property decorator work in Python?

I would like to understand how the built-in function property works. What confuses me is that property can also be used as a decorator, but it only takes arguments when used as a built-in function and not when used as a decorator.

This example is from the documentation:

class C:
    def __init__(self):
        self._x = None
    def getx(self):
        return self._x
    def setx(self, value):
        self._x = value
    def delx(self):
        del self._x
    x = property(getx, setx, delx, "I'm the 'x' property.")

property‘s arguments are getx, setx, delx and a doc string.

In the code below property is used as a decorator. The object of it is the x function, but in the code above there is no place for an object function in the arguments.

class C:
    def __init__(self):
        self._x = None
    @property
    def x(self):
        """I'm the 'x' property."""
        return self._x
    @x.setter
    def x(self, value):
        self._x = value
    @x.deleter
    def x(self):
        del self._x

How are the x.setter and x.deleter decorators created in this case?

Asked By: ashim

||

Answer #1:

The property() function returns a special descriptor object:

>>> property()
<property object at 0x10ff07940>

It is this object that has extra methods:

>>> property().getter
<built-in method getter of property object at 0x10ff07998>
>>> property().setter
<built-in method setter of property object at 0x10ff07940>
>>> property().deleter
<built-in method deleter of property object at 0x10ff07998>

These act as decorators too. They return a new property object:

>>> property().getter(None)
<property object at 0x10ff079f0>

that is a copy of the old object, but with one of the functions replaced.

Remember, that the @decorator syntax is just syntactic sugar; the syntax:

@property
def foo(self): return self._foo

really means the same thing as

def foo(self): return self._foo
foo = property(foo)

so foo the function is replaced by property(foo), which we saw above is a special object. Then when you use @foo.setter(), what you are doing is call that property().setter method I showed you above, which returns a new copy of the property, but this time with the setter function replaced with the decorated method.

The following sequence also creates a full-on property, by using those decorator methods.

First we create some functions and a property object with just a getter:

>>> def getter(self): print('Get!')
... 
>>> def setter(self, value): print('Set to {!r}!'.format(value))
... 
>>> def deleter(self): print('Delete!')
... 
>>> prop = property(getter)
>>> prop.fget is getter
True
>>> prop.fset is None
True
>>> prop.fdel is None
True

Next we use the .setter() method to add a setter:

>>> prop = prop.setter(setter)
>>> prop.fget is getter
True
>>> prop.fset is setter
True
>>> prop.fdel is None
True

Last we add a deleter with the .deleter() method:

>>> prop = prop.deleter(deleter)
>>> prop.fget is getter
True
>>> prop.fset is setter
True
>>> prop.fdel is deleter
True

Last but not least, the property object acts as a descriptor object, so it has .__get__(), .__set__() and .__delete__() methods to hook into instance attribute getting, setting and deleting:

>>> class Foo: pass
... 
>>> prop.__get__(Foo(), Foo)
Get!
>>> prop.__set__(Foo(), 'bar')
Set to 'bar'!
>>> prop.__delete__(Foo())
Delete!

The Descriptor Howto includes a pure Python sample implementation of the property() type:

class Property:
    "Emulate PyProperty_Type() in Objects/descrobject.c"
    def __init__(self, fget=None, fset=None, fdel=None, doc=None):
        self.fget = fget
        self.fset = fset
        self.fdel = fdel
        if doc is None and fget is not None:
            doc = fget.__doc__
        self.__doc__ = doc
    def __get__(self, obj, objtype=None):
        if obj is None:
            return self
        if self.fget is None:
            raise AttributeError("unreadable attribute")
        return self.fget(obj)
    def __set__(self, obj, value):
        if self.fset is None:
            raise AttributeError("can't set attribute")
        self.fset(obj, value)
    def __delete__(self, obj):
        if self.fdel is None:
            raise AttributeError("can't delete attribute")
        self.fdel(obj)
    def getter(self, fget):
        return type(self)(fget, self.fset, self.fdel, self.__doc__)
    def setter(self, fset):
        return type(self)(self.fget, fset, self.fdel, self.__doc__)
    def deleter(self, fdel):
        return type(self)(self.fget, self.fset, fdel, self.__doc__)
Answered By: Martijn Pieters

Answer #2:

Documentation says it’s just a shortcut for creating readonly properties. So

@property
def x(self):
    return self._x

is equivalent to

def getx(self):
    return self._x
x = property(getx)
Answered By: J0HN

Answer #3:

Here is a minimal example of how @property can be implemented:

class Thing:
    def __init__(self, my_word):
        self._word = my_word
    @property
    def word(self):
        return self._word
>>> print( Thing('ok').word )
'ok'

Otherwise word remains a method instead of a property.

class Thing:
    def __init__(self, my_word):
        self._word = my_word
    def word(self):
        return self._word
>>> print( Thing('ok').word() )
'ok'
Answered By: AlexG

Answer #4:

The first part is simple:

@property
def x(self): ...

is the same as

def x(self): ...
x = property(x)
  • which, in turn, is the simplified syntax for creating a property with just a getter.

The next step would be to extend this property with a setter and a deleter. And this happens with the appropriate methods:

@x.setter
def x(self, value): ...

returns a new property which inherits everything from the old x plus the given setter.

x.deleter works the same way.

Answered By: glglgl

Answer #5:

Below is another example on how @property can help when one has to refactor code which is taken from here (I only summarize it below):

Imagine you created a class Money like this:

class Money:
    def __init__(self, dollars, cents):
        self.dollars = dollars
        self.cents = cents

and an user creates a library depending on this class where he/she uses e.g.

money = Money(27, 12)
print("I have {} dollar and {} cents.".format(money.dollars, money.cents))
# prints I have 27 dollar and 12 cents.

Now let’s suppose you decide to change your Money class and get rid of the dollars and cents attributes but instead decide to only track the total amount of cents:

class Money:
    def __init__(self, dollars, cents):
        self.total_cents = dollars * 100 + cents

If the above mentioned user now tries to run his/her library as before

money = Money(27, 12)
print("I have {} dollar and {} cents.".format(money.dollars, money.cents))

it will result in an error

AttributeError: ‘Money’ object has no attribute ‘dollars’

That means that now everyone who relies on your original Money class would have to change all lines of code where dollars and cents are used which can be very painful… So, how could this be avoided? By using @property!

That is how:

class Money:
    def __init__(self, dollars, cents):
        self.total_cents = dollars * 100 + cents
    # Getter and setter for dollars...
    @property
    def dollars(self):
        return self.total_cents // 100
    @dollars.setter
    def dollars(self, new_dollars):
        self.total_cents = 100 * new_dollars + self.cents
    # And the getter and setter for cents.
    @property
    def cents(self):
        return self.total_cents % 100
    @cents.setter
    def cents(self, new_cents):
        self.total_cents = 100 * self.dollars + new_cents

when we now call from our library

money = Money(27, 12)
print("I have {} dollar and {} cents.".format(money.dollars, money.cents))
# prints I have 27 dollar and 12 cents.

it will work as expected and we did not have to change a single line of code in our library! In fact, we would not even have to know that the library we depend on changed.

Also the setter works fine:

money.dollars += 2
print("I have {} dollar and {} cents.".format(money.dollars, money.cents))
# prints I have 29 dollar and 12 cents.
money.cents += 10
print("I have {} dollar and {} cents.".format(money.dollars, money.cents))
# prints I have 29 dollar and 22 cents.

You can use @property also in abstract classes; I give a minimal example here.

Answered By: Cleb

Answer #6:

This following:

class C(object):
    def __init__(self):
        self._x = None
    @property
    def x(self):
        """I'm the 'x' property."""
        return self._x
    @x.setter
    def x(self, value):
        self._x = value
    @x.deleter
    def x(self):
        del self._x

Is the same as:

class C(object):
    def __init__(self):
        self._x = None
    def _x_get(self):
        return self._x
    def _x_set(self, value):
        self._x = value
    def _x_del(self):
        del self._x
    x = property(_x_get, _x_set, _x_del,
                    "I'm the 'x' property.")

Is the same as:

class C(object):
    def __init__(self):
        self._x = None
    def _x_get(self):
        return self._x
    def _x_set(self, value):
        self._x = value
    def _x_del(self):
        del self._x
    x = property(_x_get, doc="I'm the 'x' property.")
    x = x.setter(_x_set)
    x = x.deleter(_x_del)

Is the same as:

class C(object):
    def __init__(self):
        self._x = None
    def _x_get(self):
        return self._x
    x = property(_x_get, doc="I'm the 'x' property.")
    def _x_set(self, value):
        self._x = value
    x = x.setter(_x_set)
    def _x_del(self):
        del self._x
    x = x.deleter(_x_del)

Which is the same as :

class C(object):
    def __init__(self):
        self._x = None
    @property
    def x(self):
        """I'm the 'x' property."""
        return self._x
    @x.setter
    def x(self, value):
        self._x = value
    @x.deleter
    def x(self):
        del self._x
Answered By: Bimo

Answer #7:

I read all the posts here and realized that we may need a real life example. Why, actually, we have @property?
So, consider a Flask app where you use authentication system.
You declare a model User in models.py:

class User(UserMixin, db.Model):
    __tablename__ = 'users'
    id = db.Column(db.Integer, primary_key=True)
    email = db.Column(db.String(64), unique=True, index=True)
    username = db.Column(db.String(64), unique=True, index=True)
    password_hash = db.Column(db.String(128))
    ...
    @property
    def password(self):
        raise AttributeError('password is not a readable attribute')
    @password.setter
    def password(self, password):
        self.password_hash = generate_password_hash(password)
    def verify_password(self, password):
        return check_password_hash(self.password_hash, password)

In this code we’ve “hidden” attribute password by using @property which triggers AttributeError assertion when you try to access it directly, while we used @property.setter to set the actual instance variable password_hash.

Now in auth/views.py we can instantiate a User with:

...
@auth.route('/register', methods=['GET', 'POST'])
def register():
    form = RegisterForm()
    if form.validate_on_submit():
        user = User(email=form.email.data,
                    username=form.username.data,
                    password=form.password.data)
        db.session.add(user)
        db.session.commit()
...

Notice attribute password that comes from a registration form when a user fills the form. Password confirmation happens on the front end with EqualTo('password', message='Passwords must match') (in case if you are wondering, but it’s a different topic related Flask forms).

I hope this example will be useful

Answered By: Leo Skhrnkv

Answer #8:

Let’s start with Python decorators.

A Python decorator is a function that helps to add some additional functionalities to an already defined function.

In Python, everything is an object. Functions in Python are first-class objects which means that they can be referenced by a variable, added in the lists, passed as arguments to another function etc.

Consider the following code snippet.

def decorator_func(fun):
    def wrapper_func():
        print("Wrapper function started")
        fun()
        print("Given function decorated")
        # Wrapper function add something to the passed function and decorator 
        # returns the wrapper function
    return wrapper_func
def say_bye():
    print("bye!!")
say_bye = decorator_func(say_bye)
say_bye()
# Output:
#  Wrapper function started
#  bye
#  Given function decorated

Here, we can say that decorator function modified our say_hello function and added some extra lines of code in it.

Python syntax for decorator

def decorator_func(fun):
    def wrapper_func():
        print("Wrapper function started")
        fun()
        print("Given function decorated")
        # Wrapper function add something to the passed function and decorator 
        # returns the wrapper function
    return wrapper_func
@decorator_func
def say_bye():
    print("bye!!")
say_bye()

Let’s Concluded everything than with a case scenario, but before that let’s talk about some oops priniciples.

Getters and setters are used in many object oriented programming languages to ensure the principle of data encapsulation(is seen as the bundling of data with the methods that operate on these data.)

These methods are of course the getter for retrieving the data and the setter for changing the data.

According to this principle, the attributes of a class are made private to hide and protect them from other code.

Yup, @property is basically a pythonic way to use getters and setters.

Python has a great concept called property which makes the life of an object-oriented programmer much simpler.

Let us assume that you decide to make a class that could store the temperature in degree Celsius.

class Celsius:
def __init__(self, temperature = 0):
    self.set_temperature(temperature)
def to_fahrenheit(self):
    return (self.get_temperature() * 1.8) + 32
def get_temperature(self):
    return self._temperature
def set_temperature(self, value):
    if value < -273:
        raise ValueError("Temperature below -273 is not possible")
    self._temperature = value

Refactored Code, Here is how we could have achieved it with property.

In Python, property() is a built-in function that creates and returns a property object.

A property object has three methods, getter(), setter(), and delete().

class Celsius:
def __init__(self, temperature = 0):
    self.temperature = temperature
def to_fahrenheit(self):
    return (self.temperature * 1.8) + 32
def get_temperature(self):
    print("Getting value")
    return self.temperature
def set_temperature(self, value):
    if value < -273:
        raise ValueError("Temperature below -273 is not possible")
    print("Setting value")
    self.temperature = value
temperature = property(get_temperature,set_temperature)

Here,

temperature = property(get_temperature,set_temperature)

could have been broken down as,

# make empty property
temperature = property()
# assign fget
temperature = temperature.getter(get_temperature)
# assign fset
temperature = temperature.setter(set_temperature)

Point To Note:

  • get_temperature remains a property instead of a method.

Now you can access the value of temperature by writing.

C = Celsius()
C.temperature
# instead of writing C.get_temperature()

We can further go on and not define names get_temperature and set_temperature as they are unnecessary and pollute the class namespace.

The pythonic way to deal with the above problem is to use @property.

class Celsius:
    def __init__(self, temperature = 0):
        self.temperature = temperature
    def to_fahrenheit(self):
        return (self.temperature * 1.8) + 32
    @property
    def temperature(self):
        print("Getting value")
        return self.temperature
    @temperature.setter
    def temperature(self, value):
        if value < -273:
            raise ValueError("Temperature below -273 is not possible")
        print("Setting value")
        self.temperature = value

Points to Note –

  1. A method which is used for getting a value is decorated with “@property”.
  2. The method which has to function as the setter is decorated with “@temperature.setter”, If the function had been called “x”, we would have to decorate it with “@x.setter”.
  3. We wrote “two” methods with the same name and a different number of parameters “def temperature(self)” and “def temperature(self,x)”.

As you can see, the code is definitely less elegant.

Now,let’s talk about one real-life practical scenerio.

Let’s say you have designed a class as follows:

class OurClass:
    def __init__(self, a):
        self.x = a
y = OurClass(10)
print(y.x)

Now, let’s further assume that our class got popular among clients and they started using it in their programs, They did all kinds of assignments to the object.

And One fateful day, a trusted client came to us and suggested that “x” has to be a value between 0 and 1000, this is really a horrible scenario!

Due to properties it’s easy: We create a property version of “x”.

class OurClass:
    def __init__(self,x):
        self.x = x
    @property
    def x(self):
        return self.__x
    @x.setter
    def x(self, x):
        if x < 0:
            self.__x = 0
        elif x > 1000:
            self.__x = 1000
        else:
            self.__x = x

This is great, isn’t it: You can start with the simplest implementation imaginable, and you are free to later migrate to a property version without having to change the interface! So properties are not just a replacement for getters and setter!

You can check this Implementation here

Answered By: Divyanshu Rawat

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