Python Level 8: Frequency Maps & Set Optimizations

Why This Matters: Using Python dicts and sets turns O(N²) quadratic loops into O(N) linear time.

## Frequency Counting Pattern

Using hash dictionaries to achieve O(1) average lookup times.

```python
def char_frequency(text: str) -> dict:
    freq = {}
    for char in text:
        freq[char] = freq.get(char, 0) + 1
    return freq

print(char_frequency("growcode"))
```

MENTAL MODEL & MEMORY LAYOUT

FREQUENCY MAP PIPELINE:
"growcode" ──► Iterates chars ──► Dict {'g':1, 'r':1, 'o':2, 'w':1, 'c':1, 'd':1, 'e':1}

COMMON PITFALLS TO AVOID

Accessing missing dictionary key `dict[key]` without using `.get()` or `in` check (raises KeyError).

Duplicate Detection via Hash Set

def has_duplicates(items):
    return len(items) != len(set(items))
print(has_duplicates([1, 2, 3, 1])) # True

Compares list length to unique set length for O(N) duplicate detection.

CONCEPT MASTERY CHECKPOINT

What is the average lookup time complexity for checking `item in my_set` in Python?

NEXT RECOMMENDED LESSON

Python Level 9: Standard Library

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Challenge: Find first non-repeating character index in string.

Python Level 8: Frequency Maps & Set Optimizations

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