Mutable data types can be changed after creation (e.g., lists). In other words, the memory location of the object remains the same, but its internal state can change. By contrast, immutable data types cannot (e.g., strings, tuples). Instead, you must create a new object with the desired changes. This immutability ensures that the original object maintains its integrity.
Generators in Python define iterator implementation by yielding expressions in a function. They don’t implement ‘iter’ and ‘next()’ methods, thereby reducing various overheads.
Python offers various built-in data types, including numeric types (int, float, complex), sequence types (string, list, tuple, range), mapping types (dictionary), and set types.
A shallow copy creates a new instance with copied values and is faster, whereas a deep copy stores values that are already copied and takes longer but is more comprehensive.
Polymorphism is a concept that refers to the ability of objects to take on multiple forms. In Python, it allows objects of different classes to be treated as if they belong to a common superclass.
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