Mutable, Immutable… everything is an object(Python)!

The first fundamental distinction that Python makes on data is about whether or not the value of an object changes. If the value can change, the object is called mutable, while if the value cannot change, the object is called immutable.

ID and type

Python id() function returns the “identity” of the object. The identity of an object is an integer, which is guaranteed to be unique and constant for this object during its lifetime. Two objects with non-overlapping lifetimes may have the same id() value.

Example

#integers

x = 10
y = 10

print(id(x))
print(id(y))

Output:

4317900064
4317900064

Example

# strings

s1 = ‘ABC’

s2 = ‘ABC’

print(id(s1))

print(id(s2))

Output

4320080816

4320080816

Example

# tuples

tup1 = (‘A’, ‘B’)

print(id(tup1))

tup2 = (‘A’, ‘B’)

print(id(tup2))

Output

4320130056

4320130056

Mutable, immutable objects

Simple put, a mutable object can be changed after it is created, and an immutable object can’t. 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

Mutable objects

list, dict, set, byte array

Immutable objects

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

how differently does Python treat mutable and immutable objects

The values of mutable objects can be changed at any time and place, whether you expect it or not. You can change a single value of a mutable data type and it won’t change its memory address. However, you can’t change a single value of an immutable type. It will throw an error

Arguments are always passed to functions by reference in Python. … This concept behaves differently for both mutable and immutable arguments in Python. In Python, integer , float , string and tuple are immutable objects. list , dict and set fall in the mutable object category.