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mutable vs. immutable data types in python: a deep dive

python's data types are categorized as either mutable or immutable. this distinction fundamentally affects how objects behave when modified. understanding this difference is crucial for writing efficient and bug-free python code. this tutorial provides a comprehensive exploration of this concept, complete with code examples and explanations.


*1. what is mutability?*

mutability refers to an object's ability to change its state (its internal data) after it's created. a mutable object can be modified in-place – its contents are altered without creating a new object. an immutable object, on the other hand, cannot be changed once it's created. any operation that appears to modify an immutable object actually creates a new object with the altered values.

*2. immutable data types:*

these types cannot be changed after creation. trying to modify them will result in a new object being created. key examples include:

*numbers (int, float, complex):* you can't directly change the value of an integer or float. assignments like `x = x + 1` actually create a new integer object and assign it to `x`.

*strings (str):* strings are sequences of characters. operations like concatenation (`+`) or slicing (`[:]`) create new string objects.

*tuples (tuple):* tuples are ordered, immutable sequences of items. once a tuple is created, its elements cannot be changed, added, or removed.

*frozen sets (frozenset):* similar to sets but immutable. you can't add or remove elements after creation.


*code examples (immutable):*



*3. mutable data types:*

these types can be modified after creation. changes are made directly to the existing object in memory. key examples include:

*lists (list):* lists are ordered, mutable sequences of items. you can add, remove, or modify elements in place.

*dictionaries (dict):* dictionaries store key-value pairs. you can add, remove, or modify key- ...

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Python data types
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