hash-vs-tree

Included with Lifetime

$97 forever

Choose between hash tables and tree structures for lookups, counting, and grouping. Use when deciding between O(1) hash operations and O(log n) ordered operations.

General

What this skill does


## When to use

Use dict/set (hash table, O(1) avg lookup) for: membership testing, frequency counting, deduplication, grouping by key.

## Rules

- Use collections.Counter for frequency counts, defaultdict(list) for grouping
- When you need ordered keys or range queries, use sorted containers or bisect on a sorted list
- For "find if X exists" or "count occurrences," ALWAYS reach for a set or dict first
- NEVER scan a list repeatedly when a set/dict would work
- If the problem involves pairs summing to a target, use a set to check complements in O(n) instead of O(n^2) nested loops

## Complexity

Hash table: O(1) avg lookup. Sorted containers: O(log n) lookup.

## Example

"Two sum" → store complements in a set: `for x in nums: if target - x in seen: return True; seen.add(x)`. O(n) vs O(n²) nested loops.

Files: 1

Size: 1.3 KB

Complexity: 10/100

Category: General

Source: https://github.com/knoopx/pi/tree/main/agent/skills/knowledge/hash-vs-tree

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