ReviseAlgo Logo

Dictionaries

Dictionary Basics

Creating and using dictionaries

Interview: Most important Python data structure — essential for all interviews

Last Updated: June 12, 2026 • 10 min read

Dictionaries are Python's built-in hash map implementation — mutable, unordered (insertion-ordered in 3.7+) collections of key-value pairs. They provide O(1) average-case lookup, insertion, and deletion, making them one of the most important data structures.

Creating Dictionaries

  • Literal: {"key": "value"}
  • Constructor: dict(key="value") or dict([("a", 1)])
  • From zip: dict(zip(keys, values))
  • Comprehension: {k: v for k, v in pairs}
  • Empty: {} or dict()

Key Requirements

  • Keys must be hashable (immutable): strings, numbers, tuples of immutables
  • Keys must be unique: duplicate keys use the last value
  • Values can be any type: including lists, dicts, functions, classes

Performance

  • Lookup: O(1) average, O(n) worst case (hash collisions)
  • Insert/Delete: O(1) average
  • Memory: Higher than lists due to hash table overhead (sparse array)
  • Python 3.6+ dicts maintain insertion order as an implementation detail; guaranteed in 3.7+

Interview Tip

Know the difference between d[key] (raises KeyError) and d.get(key, default) (returns default). Using get() avoids try/except blocks for missing keys.

Use Cases

Key-value storage for configuration and settings

Frequency counting and grouping data

Caching/memoization (mapping inputs to outputs)

Dispatch tables replacing if-elif chains

Common Mistakes

Using d[key] without checking existence (KeyError) — use get() or check with in first

Using mutable objects (lists, dicts) as keys (TypeError: unhashable)

Forgetting that in operator checks keys only, not values

Not knowing that Python 3.7+ dicts maintain insertion order