# Python @property decorator

Python programming provides us with a built-in @property decorator which makes usage of getter and setters much easier in Object-Oriented Programming.

Before going into details on what @property decorator is, let us first build an intuition on why it would be needed in the first place.

## Class Without Getters and Setters

Let us assume that we decide to make a class that stores the temperature in degrees Celsius. And, it would also implement a method to convert the temperature into degrees Fahrenheit.

One way of doing this is as follows:

class Celsius:
def __init__(self, temperature = 0):
self.temperature = temperature

def to_fahrenheit(self):
return (self.temperature * 1.8) + 32

We can make objects out of this class and manipulate the temperature attribute as we wish:

# Basic method of setting and getting attributes in Python
class Celsius:
def __init__(self, temperature=0):
self.temperature = temperature

def to_fahrenheit(self):
return (self.temperature * 1.8) + 32

# Create a new object
human = Celsius()

# Set the temperature
human.temperature = 37

# Get the temperature attribute
print(human.temperature)

# Get the to_fahrenheit method
print(human.to_fahrenheit())

Output

37
98.60000000000001

Here, the extra decimal places when converting into Fahrenheit is due to the Floating Point Arithmetic Error.

So, whenever we assign or retrieve any object attribute like temperature as shown above, Python searches it in the object's built-in __dict__ dictionary attribute as

print(human.__dict__)
# Output: {'temperature': 37}

Therefore, human.temperature internally becomes human.__dict__['temperature'].

## Using Getters and Setters

Suppose we want to extend the usability of the Celsius class defined above. We know that the temperature of any object cannot reach below -273.15 degrees Celsius.

Let's update our code to implement this value constraint.

An obvious solution to the above restriction will be to hide the attribute temperature (make it private) and define new getter and setter methods to manipulate it.

This can be done as follows:

# Making Getters and Setter methods
class Celsius:
def __init__(self, temperature=0):
self.set_temperature(temperature)

def to_fahrenheit(self):
return (self.get_temperature() * 1.8) + 32

# getter method
def get_temperature(self):
return self._temperature

# setter method
def set_temperature(self, value):
if value < -273.15:
raise ValueError("Temperature below -273.15 is not possible.")
self._temperature = value

As we can see, the above method introduces two new get_temperature() and set_temperature() methods.

Furthermore, temperature was replaced with _temperature. An underscore _ at the beginning is used to denote private variables in Python.

Now, let's use this implementation:

# Making Getters and Setter methods
class Celsius:
def __init__(self, temperature=0):
self.set_temperature(temperature)

def to_fahrenheit(self):
return (self.get_temperature() * 1.8) + 32

# getter method
def get_temperature(self):
return self._temperature

# setter method
def set_temperature(self, value):
if value < -273.15:
raise ValueError("Temperature below -273.15 is not possible.")
self._temperature = value

# Create a new object, set_temperature() internally called by __init__
human = Celsius(37)

# Get the temperature attribute via a getter
print(human.get_temperature())

# Get the to_fahrenheit method, get_temperature() called by the method itself
print(human.to_fahrenheit())

# new constraint implementation
human.set_temperature(-300)

# Get the to_fahreheit method
print(human.to_fahrenheit())

Output

37
98.60000000000001
Traceback (most recent call last):
File "<string>", line 30, in <module>
File "<string>", line 16, in set_temperature
ValueError: Temperature below -273.15 is not possible.

This update successfully implemented the new restriction. We are no longer allowed to set the temperature below -273.15 degrees Celsius.

Note: The private variables don't actually exist in Python. There are simply norms to be followed. The language itself doesn't apply any restrictions.

However, the bigger problem with the above update is that all the programs that implemented our previous class have to modify their code from obj.temperature to obj.get_temperature() and all expressions like obj.temperature = val to obj.set_temperature(val).

This refactoring can cause problems while dealing with hundreds of thousands of lines of codes.

All in all, our new update was not backwards compatible. This is where @property comes to rescue.

## The property Class

A pythonic way to deal with the above problem is to use the property class. Here is how we can update our code:

# using property class
class Celsius:
def __init__(self, temperature=0):
self.temperature = temperature

def to_fahrenheit(self):
return (self.temperature * 1.8) + 32

# getter
def get_temperature(self):
print("Getting value...")
return self._temperature

# setter
def set_temperature(self, value):
print("Setting value...")
if value < -273.15:
raise ValueError("Temperature below -273.15 is not possible")
self._temperature = value

# creating a property object
temperature = property(get_temperature, set_temperature)

We added the print() function inside get_temperature() and set_temperature() to clearly observe that they are being executed.

The last line of the code makes a property object temperature. Simply put, property attaches some code (get_temperature and set_temperature) to the member attribute accesses (temperature).

Let's use this update code:

# using property class
class Celsius:
def __init__(self, temperature=0):
self.temperature = temperature

def to_fahrenheit(self):
return (self.temperature * 1.8) + 32

# getter
def get_temperature(self):
print("Getting value...")
return self._temperature

# setter
def set_temperature(self, value):
print("Setting value...")
if value < -273.15:
raise ValueError("Temperature below -273.15 is not possible")
self._temperature = value

# creating a property object
temperature = property(get_temperature, set_temperature)

human = Celsius(37)

print(human.temperature)

print(human.to_fahrenheit())

human.temperature = -300

Output

Setting value...
Getting value...
37
Getting value...
98.60000000000001
Setting value...
Traceback (most recent call last):
File "<string>", line 31, in <module>
File "<string>", line 18, in set_temperature
ValueError: Temperature below -273 is not possible

As we can see, any code that retrieves the value of temperature will automatically call get_temperature() instead of a dictionary (__dict__) look-up.

Similarly, any code that assigns a value to temperature will automatically call set_temperature().

We can even see above that set_temperature() was called even when we created an object.

human = Celsius(37) # prints Setting value...

Can you guess why?

The reason is that when an object is created, the __init__() method gets called. This method has the line self.temperature = temperature. This expression automatically calls set_temperature().

Similarly, any access like c.temperature automatically calls get_temperature(). This is what property does.

By using property, we can see that no modification is required in the implementation of the value constraint. Thus, our implementation is backward compatible.

Note: The actual temperature value is stored in the private _temperature variable. The temperature attribute is a property object which provides an interface to this private variable.

## The @property Decorator

In Python, property() is a built-in function that creates and returns a property object. The syntax of this function is:

property(fget=None, fset=None, fdel=None, doc=None)

Here,

• fget is function to get value of the attribute
• fset is function to set value of the attribute
• fdel is function to delete the attribute
• doc is a string (like a comment)

As seen from the implementation, these function arguments are optional.

A property object has three methods, getter(), setter(), and deleter() to specify fget, fset and fdel at a later point. This means, the line:

temperature = property(get_temperature,set_temperature)

can be broken down as:

# make empty property
temperature = property()

# assign fget
temperature = temperature.getter(get_temperature)

# assign fset
temperature = temperature.setter(set_temperature)

These two pieces of code are equivalent.

Programmers familiar with Python Decorators can recognize that the above construct can be implemented as decorators.

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

For this, we reuse the temperature name while defining our getter and setter functions. Let's look at how to implement this as a decorator:

# Using @property decorator
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):
print("Setting value...")
if value < -273.15:
raise ValueError("Temperature below -273 is not possible")
self._temperature = value

# create an object
human = Celsius(37)

print(human.temperature)

print(human.to_fahrenheit())

coldest_thing = Celsius(-300)

Output

Setting value...
Getting value...
37
Getting value...
98.60000000000001
Setting value...
Traceback (most recent call last):
File "", line 29, in
File "", line 4, in __init__
File "", line 18, in temperature
ValueError: Temperature below -273 is not possible

The above implementation is simple and efficient. It is the recommended way to use property.