🗺️ Dictionaries

Why it matters

Hash maps solve a huge class of problems in O(1) average time.

The idea

A dict is a fast lookup table: key → value. Keys must be hashable (so: strings, numbers, tuples — not lists). Since Python 3.7, dicts remember insertion order.

Try it

Build, lookup, default values:

prices = {"apple": 1.0, "banana": 0.5}
prices["cherry"] = 2.5
print(prices)

# .get() returns a default instead of raising KeyError
print(prices.get("grape", 0.0))

# setdefault() inserts if missing, then returns the value
prices.setdefault("date", 3.0)
print(prices)

Counting — the classic “frequency” idiom:

from collections import Counter

text = "mississippi"
counts = Counter(text)
print(counts)
print(counts.most_common(2))

Iterating: items() yields (key, value) tuples — perfect for unpacking.

scores = {"Ada": 95, "Linus": 88, "Margaret": 99}
for name, score in scores.items():
  print(f"{name:>10}: {score}")

# Dict comprehension
inverted = { score: name for name, score in scores.items() }
print(inverted)

Core dict methods (must know)

Grouping pattern

setdefault makes “bucket items by a key” a one-liner:

groups = {}
for item in items:
    groups.setdefault(item[0], []).append(item)

Two Sum pattern

The canonical “remember what you’ve seen” hash trick — O(n) instead of O(n²):

def two_sum(nums, target):
    seen = {}
    for i, x in enumerate(nums):
        need = target - x
        if need in seen:
            return [seen[need], i]
        seen[x] = i

Quick check

• Q: What does dict.get(k) return if the key is missing? A: None (or the default you provide).

Mini drills

• Count characters in a string.
• Find the first repeated number.
• Build a word → count dictionary.

Do’s and don’ts

• Do use in d to test keys.
• Do prefer get for optional access.
• Don’t mutate a dict while iterating over it.
• Don’t use unhashable keys (list, dict, set).

Common mistakes

• Mistake: Accessing missing keys with []. Fix: Use get().
• Mistake: Overwriting values unintentionally. Fix: Inspect keys before assignment.
• Mistake: Using a list as a key. Fix: Use a tuple or frozenset.
• Mistake: Assuming dict.keys() is a list. Fix: Wrap with list(...) when needed.

Key takeaways

• Keys must be hashable; values can be anything.
• dict.get(k, default) avoids KeyError; setdefault inserts-if-missing.
• collections.Counter is the goto for frequency counts.
• Dict comprehensions: {k: v for ... if ...} mirror list comprehensions.
• get, set, in, pop are ~O(1) average; worst case O(n) under heavy collisions.