Mutable and Immutable Data Types in Python | D/W Mutable and Immutable Data Types in Python
In Python, data types can be categorized as mutable and immutable based on whether their values can be changed after they are created.
Mutable Data Types:
Mutable data types are those whose values can be modified after creation.
Common examples include lists, dictionaries, and sets.
When you modify a mutable object (e.g., add or remove elements from a list), it doesn't create a new object; instead, it changes the existing object in memory.
Example with a list:
python
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my_list = [1, 2, 3]
my_list.append(4) # Modifies the original list
Immutable Data Types:
Immutable data types are those whose values cannot be changed once they are created.
Common examples include integers, floats, strings, and tuples.
When you perform an operation that appears to modify an immutable object, it actually creates a new object in memory with the updated value.
Example with a string:
python
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my_string = "Hello"
new_string = my_string + " World" # Creates a new string with the concatenated value
The choice between mutable and immutable data types depends on your specific use case. Mutable types are useful when you need to modify data in place, while immutable types provide benefits like safety and predictability since they cannot be inadvertently changed.
It's important to be aware of these distinctions when working with Python, as they can affect how you manipulate and pass data in your programs.
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