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8cce0d463a
As described in #6095, this reduces the chances to observe a O(n^2) complexity. Here, `collection.pop(pivot_index)` is avoided for performance reasons. Fixes: #6095
49 lines
1.4 KiB
Python
49 lines
1.4 KiB
Python
"""
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A pure Python implementation of the quick sort algorithm
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For doctests run following command:
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python3 -m doctest -v quick_sort.py
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For manual testing run:
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python3 quick_sort.py
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"""
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from __future__ import annotations
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from random import randrange
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def quick_sort(collection: list) -> list:
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"""A pure Python implementation of quick sort algorithm
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:param collection: a mutable collection of comparable items
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:return: the same collection ordered by ascending
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Examples:
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>>> quick_sort([0, 5, 3, 2, 2])
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[0, 2, 2, 3, 5]
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>>> quick_sort([])
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[]
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>>> quick_sort([-2, 5, 0, -45])
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[-45, -2, 0, 5]
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"""
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if len(collection) < 2:
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return collection
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pivot_index = randrange(len(collection)) # Use random element as pivot
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pivot = collection[pivot_index]
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greater: list[int] = [] # All elements greater than pivot
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lesser: list[int] = [] # All elements less than or equal to pivot
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for element in collection[:pivot_index]:
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(greater if element > pivot else lesser).append(element)
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for element in collection[pivot_index + 1 :]:
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(greater if element > pivot else lesser).append(element)
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return quick_sort(lesser) + [pivot] + quick_sort(greater)
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if __name__ == "__main__":
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user_input = input("Enter numbers separated by a comma:\n").strip()
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unsorted = [int(item) for item in user_input.split(",")]
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print(quick_sort(unsorted))
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