Everything is object in Python

Introduction:

Everything in Python is an object. And what every newcomer to Python should quickly learn is that all objects in Python can be either mutable or immutable.

Objects of built-in types like (int, float, bool, str, tuple, unicode) are immutable. Objects of built-in types like (list, set, dict) are mutable. Custom classes are generally mutable. To simulate immutability in a class, one should override attribute setting and deletion to raise exceptions.

Id and type:

The id() function returns the identity of an object as an integer. This corresponds to the location of the object in memory. The function type() returns the type of an object.

''' Example 1 '''
>>> x = "Holberton"
>>> y = "Holberton"
>>> id(x)
140135852055856
>>> id(y)
140135852055856
>>> print(x is y) '''comparing the types'''
True''' Example 2 '''
>>> a = 50
>>> type(a)
<class: ‘int’>
>>> b = "Holberton"
>>> type(b)
<class: 'string'>

Mutable and Immutable Objects:

Mutable objects:

list, dict, set, byte array

Immutable objects:

int, float, complex, string, tuple, frozen set [note: immutable version of set], bytes

How objects are passed to Functions:

Its important for us to know difference between mutable and immutable types and how they are treated when passed onto functions .Memory efficiency is highly affected when the proper objects are used.

For example if a mutable object is called by reference in a function, it can change the original variable itself. Hence to avoid this, the original variable needs to be copied to another variable. Immutable objects can be called by reference because its value cannot be changed anyways.

def updateList(list1):
    list1 += [10]n = [5, 6]
print(id(n))                  # 140312184155336updateList(n)
print(n)                      # [5, 6, 10]
print(id(n))                  # 140312184155336