Python Interview Questions
Lists, tuples, sets, dictionaries, comprehensions, slicing, unpacking, and the built-in methods that manipulate them.
Ans
A list is an ordered, mutable sequence that can contain objects of different types. It supports indexing, slicing, insertion, deletion, and iteration.
Example
pythonnumbers = [10, 20, 30] numbers.append(40) print(numbers[1])
Important Point
Lists allow duplicate values and are zero-indexed.
Ans
A tuple is an ordered, immutable sequence. It is useful for fixed groups of values and can be used as a dictionary key when all contained values are hashable.
Example
pythonpoint = (10, 20) x, y = point print(x, y)
Important Point
Tuple immutability does not recursively make contained mutable objects immutable.
Ans
Lists are mutable and are suited to collections that change. Tuples are immutable and are useful for fixed records or values that should not be reassigned.
Example
pythonitems = [1, 2] items.append(3) point = (10, 20)
Important Point
Choose based on semantics, not on a blanket claim that tuples are always faster.
Ans
A set is an unordered collection of unique hashable elements. It supports efficient average-case membership testing and mathematical set operations.
Example
pythonskills = {"Java", "Python", "SQL"} skills.add("Git") print("Python" in skills)
Important Point
Set elements must be hashable.
Ans
A frozenset is an immutable set. Because it is immutable and hashable when its elements are hashable, it can itself be used as a dictionary key or set element.
Example
pythonpermissions = frozenset({"read", "write"}) print("read" in permissions)
Important Point
You cannot add or remove elements from a frozenset.
Ans
A dictionary stores key-value pairs and provides average-case constant-time lookup for hashable keys under normal conditions.
Example
pythonstudent = {101: "Rahul", 102: "Amit"} print(student[101])
Important Point
Keys must be hashable and unique; assigning an existing key replaces its value.
Ans
No. Lists are mutable and unhashable, so they cannot be dictionary keys. Immutable hashable alternatives such as tuples can be used when their elements are hashable.
Example
pythonlocations = {(18.52, 73.85): "Pune"} print(locations[(18.52, 73.85)])
Important Point
A tuple containing an unhashable element is also unhashable.
Ans
Dictionary comprehension creates a dictionary from an iterable using an expression and optional condition.
Example
pythonsquares = {n: n*n for n in range(1, 4)} print(squares)
Important Point
Avoid complicated comprehensions when a normal loop is easier to read.
Ans
List comprehension is a concise way to build a list by transforming or filtering values from an iterable.
Example
pythonsquares = [n*n for n in range(5) if n % 2 == 0] print(squares)
Important Point
A comprehension creates the output collection immediately; use a generator expression when lazy evaluation is preferred.
Ans
Slicing extracts part of a sequence using start, stop, and step positions. The stop index is excluded.
Example
pythons = "Python" print(s[1:4]) print(s[::-1])
Important Point
Negative indexes count from the end, and a negative step can traverse backwards.
Ans
Unpacking assigns elements of an iterable to multiple names in one operation.
Example
pythonname, age = ("Amit", 25) print(name, age)
Important Point
The number of targets must normally match the iterable length unless starred unpacking is used.
Ans
A starred target collects remaining values into a list during assignment or expands an iterable when calling or constructing values.
Example
pythonfirst, *middle, last = [1, 2, 3, 4] print(first, middle, last)
Important Point
Only one starred target is allowed in a single assignment target list.
Ans
append() adds one object as a single element. extend() iterates over another iterable and adds its elements individually.
Example
pythona = [1, 2] a.append([3, 4]) print(a) # [1, 2, [3, 4]] b = [1, 2] b.extend([3, 4]) print(b) # [1, 2, 3, 4]
Important Point
This difference is a frequent list interview question.
Ans
remove(x) deletes the first matching value, pop(index) removes and returns an item, and del removes an item, slice, or name binding.
Example
pythona = [10, 20, 30] a.remove(20) x = a.pop() del a[0] print(x, a)
Important Point
`remove()` raises ValueError when the value is absent; `pop()` can raise IndexError.
Ans
list.sort() sorts a list in place and returns None. sorted() accepts any iterable and returns a new list without modifying the original iterable.
Example
pythona = [3, 1, 2] b = sorted(a) print(a, b) a.sort() print(a)
Important Point
Do not write `a = a.sort()` expecting the sorted list; that assigns None.