Data Structures Interview Questions
Lists, tuples, sets, dictionaries, comprehensions, and common collection operations.
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Questions (20)
Browse beginner, intermediate, and advanced questions with answers — hide them when you want to self-test.
What are Python built-in data structures?
List, tuple, set, and dictionary are built-in data structures in Python.
What is a list?
A list is an ordered, mutable collection of elements.
What is a tuple?
A tuple is an ordered, immutable collection of elements.
What is a set?
A set is an unordered collection of unique elements.
What is a dictionary?
A dictionary stores key-value pairs.
Difference between list and set?
List allows duplicates and maintains order, set does not allow duplicates.
What is hashing in Python?
Hashing is converting data into fixed-size values for fast lookup.
What is dictionary key requirement?
Keys must be immutable and hashable.
What is list comprehension?
A concise way to create lists using a single line expression.
What is time complexity of list search?
O(n) because it requires linear search.
What is tuple unpacking?
Assigning tuple elements to variables in a single statement.
What is deep copy vs shallow copy?
Shallow copy copies references, deep copy copies actual objects.
What is stack in Python?
Stack is LIFO structure implemented using list.
What is queue in Python?
Queue is FIFO structure implemented using collections.deque.
How do you stay updated on Data Structures changes in Python?
Follow release notes, RFCs or PEPs, official blogs, and reputable courses. Experiment in side projects when new Data Structures-related features ship so you can speak confidently about migration paths.
Which Python built-ins or stdlib modules matter most for Data Structures?
Name concrete modules (collections, itertools, pathlib, typing) and how they support Data Structures. Prefer stdlib before third-party when it is enough.
How do mutable default arguments or late binding bite you with Data Structures?
Explain the classic default-list bug and closures in loops. Show a safe pattern when Data Structures uses defaults or lambdas.
What testing tools would you use for Data Structures logic?
pytest with fixtures, parametrize, and coverage. Mock I/O at boundaries so Data Structures unit tests stay deterministic.
How does typing improve Data Structures maintainability?
Annotate public APIs, use mypy/pyright in CI, and prefer Protocols for duck typing. Catch Data Structures contract breaks before runtime.
When would you choose a generator or comprehension for Data Structures?
Generators save memory for large streams; comprehensions are clear for small transforms. Justify the choice for Data Structures data sizes.
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