Benefits of Immutable Objects
- Hashability and Dictionary Keys: Immutable objects can be used as keys in dictionaries because their hash value remains constant, ensuring that the key-value mapping is consistent.
- Memory Efficiency: Since immutable objects cannot change their value, Python can optimize memory usage. Reusing the same immutable object across the program whenever possible reduces memory overhead.
- Thread Safety: Immutability provides inherent thread safety. When multiple threads access the same immutable object, there’s no risk of data corruption due to concurrent modifications.
- Predictability and Debugging: With immutability, you can be confident that a given object’s value will not change unexpectedly, leading to more predictable and easier-to-debug code.
- Performance Optimization: Immutable objects facilitate certain performance optimizations, such as caching hash values for quick dictionary lookups.
Why are Python Strings Immutable?
Strings in Python are “immutable” which means they can not be changed after they are created. Some other immutable data types are integers, float, boolean, etc.
The immutability of Python string is very useful as it helps in hashing, performance optimization, safety, ease of use, etc.
The article will explore the differences between mutable and immutable objects, highlighting the advantages of using immutable objects. It will also compare immutability with mutability, discussing various methods to handle immutability and achieve desired outcomes.
Input: name_1 = "Aarun"
name_1[0] = 'T'
Output: TypeError: 'str' object does not support item assignment
Explanation: We cannot update the string after declaring it means once an immutable the objects instantiated, its value cannot be changed