Python - List Methods

Overview

Estimated time: 20–30 minutes

Understand and use common list methods effectively, with notes on complexity and when to choose alternative data structures.

Learning Objectives

• Use append, extend, insert, pop, remove, clear, index, count, sort, reverse.
• Know performance characteristics (amortized O(1) append, O(n) insert/remove at front/middle).
• Avoid anti-patterns (e.g., repeatedly using += in loops, using list for membership tests vs set).

Examples

nums = [3, 1, 4]
nums.append(1)
nums.extend([5, 9])
nums.insert(1, 2)    # insert 2 at index 1
print(nums)
print(nums.count(1))
print(nums.index(4))
nums.sort()
print(nums)

Expected Output:

[3, 2, 1, 4, 1, 5, 9]
2
3
[1, 1, 2, 3, 4, 5, 9]

Guidance & Patterns

• Explain stability of Python’s Timsort (list.sort), and key functions via key=.
• Contrast append vs extend, and sorted(list) vs list.sort().
• Show why pop(0) is O(n) and suggest collections.deque for queue patterns.

Best Practices

• For frequent membership tests, prefer set over list.
• For large merges, consider generators and itertools.chain to reduce copies.

Exercises

1. Given a list of names with duplicates, deduplicate preserving order.
2. Sort a list of dicts by two keys: last name, then first name.