List Methods, Slicing, and Sorting

Beyond basic add/remove operations, lists support powerful slicing syntax and a rich set of built-in methods for sorting, copying, and transforming data — these are used constantly in real-world Python code and are a favorite area for interview questions.

List Slicing

Slicing extracts a sub-list using the format list[start:stop:step] — exactly the same pattern used for string slicing, with the stop index always exclusive.

numbers = [10, 20, 30, 40, 50, 60]

print(numbers[1:4])    # [20, 30, 40]  — indices 1, 2, 3
print(numbers[:3])     # [10, 20, 30]  — from the start up to index 3
print(numbers[3:])     # [40, 50, 60]  — from index 3 to the end
print(numbers[::2])    # [10, 30, 50]  — every second element
print(numbers[::-1])   # [60, 50, 40, 30, 20, 10] — reversed

Sorting a List

numbers = [5, 2, 9, 1, 7]

numbers.sort()              # modifies numbers directly
print(numbers)                # [1, 2, 5, 7, 9]

original = [5, 2, 9, 1, 7]
new_list = sorted(original)  # original stays untouched
print(original)                # [5, 2, 9, 1, 7]
print(new_list)                 # [1, 2, 5, 7, 9]

A very common bug: writing numbers = numbers.sort() — since .sort() returns None, this silently overwrites the list with None. Use .sort() for its side effect, or sorted() if you need to keep the original list intact.

Sorting With a Custom Key

words = ["banana", "kiwi", "apple", "fig"]
words.sort(key=len)             # sort by string length
print(words)                     # ['fig', 'kiwi', 'apple', 'banana']

words.sort(reverse=True)        # descending alphabetical order
print(words)                     # ['kiwi', 'fig', 'banana', 'apple']

Copying a List Correctly

original = [1, 2, 3]
broken_copy = original          # NOT a real copy — same object!
broken_copy.append(4)
print(original)                  # [1, 2, 3, 4] — original was also changed!

real_copy = original.copy()     # an actual independent copy
real_copy.append(5)
print(original)                  # [1, 2, 3, 4] — unaffected
print(real_copy)                 # [1, 2, 3, 4, 5]

Assigning a list to a new variable name does not copy it — both names point to the exact same list object in memory. Use .copy() or list(original) to create a genuinely independent copy.

List Comprehension — A Concise Way to Build Lists

# Traditional approach
squares = []
for n in range(1, 6):
    squares.append(n ** 2)
print(squares)   # [1, 4, 9, 16, 25]

# Equivalent list comprehension — one line
squares = [n ** 2 for n in range(1, 6)]
print(squares)   # [1, 4, 9, 16, 25]

List Comprehension With a Condition

numbers = range(1, 11)
evens = [n for n in numbers if n % 2 == 0]
print(evens)   # [2, 4, 6, 8, 10]

Other Useful List Methods

numbers = [3, 1, 4, 1, 5, 9, 1]
print(numbers.count(1))    # 3 — appears three times
print(numbers.index(4))    # 2 — first occurrence is at index 2

Interview tip: List comprehensions are heavily favored in modern Python code over manual loops with .append() — interviewers frequently ask you to rewrite a basic for loop as a one-line comprehension to test fluency with idiomatic Python.