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* docs: expand bubble sort docstrings with algorithm explanation Add a concise description of how bubble sort works (repeated adjacent comparisons/swaps until a pass makes no swaps) and note time/space complexity for both the iterative and recursive implementations. No behavior changes; all existing doctests pass. * Fix Ruff 0.16 lint failures * S310 --------- Co-authored-by: Christian Clauss <cclauss@me.com>
162 lines
6.2 KiB
Python
162 lines
6.2 KiB
Python
from typing import Any
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def bubble_sort_iterative(collection: list[Any]) -> list[Any]:
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"""Pure implementation of the bubble sort algorithm in Python (iterative).
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Bubble sort works by repeatedly stepping through the collection,
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comparing each pair of adjacent elements and swapping them if they
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are in the wrong order. This process repeats, with each full pass
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"bubbling" the next-largest unsorted element into its correct
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position at the end of the collection, until a full pass completes
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with no swaps, at which point the collection is sorted.
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Time complexity: O(n) best case (already sorted, thanks to the
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early-exit optimization), O(n^2) average and worst case.
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Space complexity: O(1) auxiliary (sorts in place).
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:param collection: some mutable ordered collection with heterogeneous
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comparable items inside
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:return: the same collection ordered in ascending order
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Examples:
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>>> bubble_sort_iterative([0, 5, 2, 3, 2])
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[0, 2, 2, 3, 5]
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>>> bubble_sort_iterative([])
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[]
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>>> bubble_sort_iterative([-2, -45, -5])
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[-45, -5, -2]
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>>> bubble_sort_iterative([-23, 0, 6, -4, 34])
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[-23, -4, 0, 6, 34]
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>>> bubble_sort_iterative([1, 2, 3, 4])
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[1, 2, 3, 4]
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>>> bubble_sort_iterative([3, 3, 3, 3])
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[3, 3, 3, 3]
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>>> bubble_sort_iterative([56])
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[56]
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>>> bubble_sort_iterative([0, 5, 2, 3, 2]) == sorted([0, 5, 2, 3, 2])
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True
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>>> bubble_sort_iterative([]) == sorted([])
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True
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>>> bubble_sort_iterative([-2, -45, -5]) == sorted([-2, -45, -5])
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True
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>>> bubble_sort_iterative([-23, 0, 6, -4, 34]) == sorted([-23, 0, 6, -4, 34])
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True
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>>> bubble_sort_iterative(['d', 'a', 'b', 'e']) == sorted(['d', 'a', 'b', 'e'])
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True
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>>> bubble_sort_iterative(['z', 'a', 'y', 'b', 'x', 'c'])
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['a', 'b', 'c', 'x', 'y', 'z']
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>>> bubble_sort_iterative([1.1, 3.3, 5.5, 7.7, 2.2, 4.4, 6.6])
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[1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7]
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>>> bubble_sort_iterative([1, 3.3, 5, 7.7, 2, 4.4, 6])
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[1, 2, 3.3, 4.4, 5, 6, 7.7]
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>>> import random
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>>> collection_arg = random.sample(range(-50, 50), 100)
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>>> bubble_sort_iterative(collection_arg) == sorted(collection_arg)
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True
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>>> import string
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>>> collection_arg = random.choices(string.ascii_letters + string.digits, k=100)
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>>> bubble_sort_iterative(collection_arg) == sorted(collection_arg)
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True
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"""
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length = len(collection)
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for i in reversed(range(length)):
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swapped = False
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for j in range(i):
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if collection[j] > collection[j + 1]:
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swapped = True
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collection[j], collection[j + 1] = collection[j + 1], collection[j]
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if not swapped:
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break # Stop iteration if the collection is sorted.
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return collection
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def bubble_sort_recursive(collection: list[Any]) -> list[Any]:
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"""Pure implementation of the bubble sort algorithm in Python (recursive).
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Functionally identical to the iterative version: each call makes a
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single pass through the collection, comparing adjacent elements and
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swapping any pair that is out of order. If any swap occurred during
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the pass, the function calls itself again on the (partially sorted)
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collection; once a pass completes with no swaps, the collection is
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sorted and the recursion stops.
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Time complexity: O(n) best case (already sorted), O(n^2) average and
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worst case.
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Space complexity: O(1) auxiliary for the sort itself (sorts in place),
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though the recursion adds O(n) call-stack frames in the worst case.
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:param collection: mutable ordered sequence of elements
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:return: the same list in ascending order
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Examples:
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>>> bubble_sort_recursive([0, 5, 2, 3, 2])
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[0, 2, 2, 3, 5]
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>>> bubble_sort_recursive([])
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[]
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>>> bubble_sort_recursive([-2, -45, -5])
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[-45, -5, -2]
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>>> bubble_sort_recursive([-23, 0, 6, -4, 34])
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[-23, -4, 0, 6, 34]
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>>> bubble_sort_recursive([0, 5, 2, 3, 2]) == sorted([0, 5, 2, 3, 2])
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True
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>>> bubble_sort_recursive([]) == sorted([])
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True
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>>> bubble_sort_recursive([-2, -45, -5]) == sorted([-2, -45, -5])
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True
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>>> bubble_sort_recursive([-23, 0, 6, -4, 34]) == sorted([-23, 0, 6, -4, 34])
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True
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>>> bubble_sort_recursive(['d', 'a', 'b', 'e']) == sorted(['d', 'a', 'b', 'e'])
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True
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>>> bubble_sort_recursive(['z', 'a', 'y', 'b', 'x', 'c'])
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['a', 'b', 'c', 'x', 'y', 'z']
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>>> bubble_sort_recursive([1.1, 3.3, 5.5, 7.7, 2.2, 4.4, 6.6])
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[1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7]
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>>> bubble_sort_recursive([1, 3.3, 5, 7.7, 2, 4.4, 6])
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[1, 2, 3.3, 4.4, 5, 6, 7.7]
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>>> bubble_sort_recursive(['a', 'Z', 'B', 'C', 'A', 'c'])
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['A', 'B', 'C', 'Z', 'a', 'c']
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>>> import random
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>>> collection_arg = random.sample(range(-50, 50), 100)
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>>> bubble_sort_recursive(collection_arg) == sorted(collection_arg)
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True
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>>> import string
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>>> collection_arg = random.choices(string.ascii_letters + string.digits, k=100)
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>>> bubble_sort_recursive(collection_arg) == sorted(collection_arg)
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True
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"""
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length = len(collection)
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swapped = False
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for i in range(length - 1):
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if collection[i] > collection[i + 1]:
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collection[i], collection[i + 1] = collection[i + 1], collection[i]
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swapped = True
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return collection if not swapped else bubble_sort_recursive(collection)
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if __name__ == "__main__":
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import doctest
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from random import sample
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from timeit import timeit
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doctest.testmod()
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# Benchmark: Iterative seems slightly faster than recursive.
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num_runs = 10_000
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unsorted = sample(range(-50, 50), 100)
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timer_iterative = timeit(
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"bubble_sort_iterative(unsorted[:])", globals=globals(), number=num_runs
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)
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print("\nIterative bubble sort:")
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print(*bubble_sort_iterative(unsorted), sep=",")
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print(f"Processing time (iterative): {timer_iterative:.5f}s for {num_runs:,} runs")
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unsorted = sample(range(-50, 50), 100)
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timer_recursive = timeit(
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"bubble_sort_recursive(unsorted[:])", globals=globals(), number=num_runs
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)
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print("\nRecursive bubble sort:")
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print(*bubble_sort_recursive(unsorted), sep=",")
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print(f"Processing time (recursive): {timer_recursive:.5f}s for {num_runs:,} runs")
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