What are Python’s built-in data structures?

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Khushi Singh · Answer

Python provides several built-in data structures that make it easy to store and manage different kinds of data efficiently. These structures are optimized for performance and are commonly used in Python programming for a variety of tasks.
Lists:
Lists are ordered, mutable (changeable) collections that can contain elements of different types. They are defined using square brackets
[]. You can add, remove, or change items in a list. Lists are ideal for storing sequences of items where order matters.
Tuples:
Tuples are similar to lists but are immutable, meaning their contents cannot be changed after creation. They are defined using parentheses
(). Tuples are often used when the data should not be altered, such as coordinates or fixed settings.
Dictionaries:
Dictionaries are collections of key-value pairs, defined using curly braces 
{}. They are unordered and mutable. Keys must be unique and immutable (e.g., strings, numbers, or tuples), while values can be of any type. Dictionaries are ideal for mapping relationships between data items.
Sets:
Sets are unordered collections of unique elements, defined using curly braces 
{} or the set() constructor. They are mutable and are particularly useful for membership testing and eliminating duplicate values.
Strings (as sequences):
Although strings are technically not a data structure, they behave like immutable sequences and are commonly used in a similar way to lists and tuples, especially when manipulating text data.
These built-in structures are the foundation of many Python applications. They offer a range of methods and operations that make them powerful tools for managing data in Python programs. Python also provides more advanced structures through the
collections module, such as deque, defaultdict, and
namedtuple.

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What are Python’s built-in data structures?

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