Hash Maps & Sets

Hash maps

seen = {}\nseen["ama"] = 25\nif "ama" in seen:   # O(1) check\n    print(seen["ama"])

The classic: two-sum

# Find two numbers that add to target\ndef two_sum(nums, target):\n    seen = {}\n    for i, n in enumerate(nums):\n        needed = target - n\n        if needed in seen:\n            return [seen[needed], i]\n        seen[n] = i\n    return []\n\ntwo_sum([2, 7, 11, 15], 9)  # [0, 1]

Sets for dedup

def has_duplicates(nums):\n    return len(nums) != len(set(nums))\n\n# intersection of two lists:\nset_a & set_b\n\n# only unique items:\nlist(set(items))

Counting with Counter

from collections import Counter\n\ncounts = Counter("banana")\n# Counter({'a': 3, 'n': 2, 'b': 1})\n\ncounts.most_common(1)   # [('a', 3)]

Ordered structure

from collections import defaultdict, deque\n\n# defaultdict: auto-initialise missing keys\nword_map = defaultdict(list)\nword_map["a"].append(1)\n\n# deque: fast append/pop at both ends\ndq = deque([1, 2, 3])\ndq.appendleft(0)

When to use which

Tip: When a problem says "find", "contains", "count" — reach for a dict or set first. It is usually the intended solution.