Files
Python/sorts/bubble_sort.py
Ali Satwat KhanandChristian Clauss 948d4cb01e Improve docstrings in sorts/bubble_sort.py (#14924)
* 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>
2026-07-30 20:29:25 -04:00

162 lines
6.2 KiB
Python

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