- benchmarks/test_benchmark_bubble_sort.py
- test_bubble_sort.py
- test_bubble_sort_conditional.py
- test_bubble_sort_import.py
- test_bubble_sort_in_class.py
- test_bubble_sort_parametrized.py
- test_bubble_sort_parametrized_loop.py

import random  # used for generating large random lists
import string  # used for string sorting test cases
import sys  # used for maxsize/minsize edge cases

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort import sorter

# unit tests

# -------------------- Basic Test Cases --------------------

def test_sorter_sorted_list():
    # Already sorted list should remain unchanged
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.79μs -> 4.58μs

def test_sorter_reverse_sorted_list():
    # Reverse sorted list should be sorted ascending
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.29μs -> 4.46μs

def test_sorter_unsorted_list():
    # Random unsorted list
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.12μs -> 4.46μs

def test_sorter_list_with_duplicates():
    # List with duplicate elements
    arr = [2, 4, 2, 3, 1, 4]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.62μs -> 4.46μs

def test_sorter_single_element():
    # List with a single element
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.04μs -> 4.12μs

def test_sorter_two_elements_sorted():
    # Two elements, already sorted
    arr = [1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.21μs -> 4.17μs

def test_sorter_two_elements_unsorted():
    # Two elements, unsorted
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.12μs -> 4.17μs

def test_sorter_all_equal_elements():
    # All elements are equal
    arr = [7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.33μs -> 4.42μs

# -------------------- Edge Test Cases --------------------

def test_sorter_empty_list():
    # Empty list should return empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.79μs -> 3.92μs

def test_sorter_negative_numbers():
    # List with negative numbers
    arr = [-3, -1, -4, -2, 0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.83μs -> 4.67μs

def test_sorter_mixed_positive_negative():
    # List with both positive and negative numbers
    arr = [3, -1, 2, -5, 0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 7.79μs -> 4.54μs

def test_sorter_large_and_small_numbers():
    # List with very large and very small numbers
    arr = [sys.maxsize, -sys.maxsize-1, 0, 999999, -999999]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 7.29μs -> 4.96μs

def test_sorter_floats_and_integers():
    # List with both floats and integers
    arr = [3.5, 2, 4.1, 2.0, 3]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 9.83μs -> 5.42μs

def test_sorter_strings():
    # List of strings should be sorted lexicographically
    arr = ["banana", "apple", "cherry", "date"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.71μs -> 4.38μs

def test_sorter_strings_with_case():
    # List of strings with varying cases
    arr = ["Banana", "apple", "Cherry", "date"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 7.62μs -> 4.75μs

def test_sorter_empty_strings():
    # List with empty strings
    arr = ["", "a", "b", "", "c"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 8.33μs -> 4.58μs

def test_sorter_unicode_strings():
    # List with unicode characters
    arr = ["éclair", "apple", "Éclair", "banana"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 8.62μs -> 4.96μs

def test_sorter_heterogeneous_types_raises():
    # List with mixed types should raise TypeError
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_mutation():
    # Ensure that the sorter function mutates the input list (in-place)
    arr = [3, 2, 1]
    sorter(arr)

# -------------------- Large Scale Test Cases --------------------

def test_sorter_large_sorted_list():
    # Large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 26.1ms -> 59.5μs

def test_sorter_large_reverse_sorted_list():
    # Large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 40.7ms -> 56.6μs

def test_sorter_large_random_list():
    # Large random list of integers
    arr = random.sample(range(-10000, -9000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 37.0ms -> 124μs

def test_sorter_large_duplicates():
    # Large list with many duplicates
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 33.6ms -> 97.1μs

def test_sorter_large_strings():
    # Large list of random strings
    arr = [
        ''.join(random.choices(string.ascii_letters, k=5))
        for _ in range(1000)
    ]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 42.1ms -> 144μs

def test_sorter_large_floats():
    # Large list of random floats
    arr = [random.uniform(-1e6, 1e6) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 35.9ms -> 463μs

def test_sorter_large_all_equal():
    # Large list where all elements are the same
    arr = [42] * 1000
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 25.8ms -> 53.5μs

def test_sorter_large_alternating():
    # Large list with alternating high/low values
    arr = [i if i % 2 == 0 else 999 - i for i in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 34.1ms -> 85.2μs
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import random  # used for generating large random lists
import string  # used for string sorting tests
import sys  # used for edge cases with large/small numbers

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort import sorter

# unit tests

# ---------------- Basic Test Cases ----------------

def test_sorter_sorted_integers():
    # Already sorted list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 9.33μs -> 4.71μs

def test_sorter_reverse_sorted_integers():
    # Reverse sorted list
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 8.83μs -> 4.46μs

def test_sorter_unsorted_integers():
    # Unsorted list
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.25μs -> 4.50μs

def test_sorter_duplicates():
    # List with duplicate values
    arr = [3, 1, 2, 3, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.29μs -> 4.54μs

def test_sorter_negative_integers():
    # List with negative numbers
    arr = [0, -1, -3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.33μs -> 4.50μs

def test_sorter_floats():
    # List with floats
    arr = [1.1, 2.2, 0.5, -1.3]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 11.1μs -> 5.42μs

def test_sorter_mixed_integers_floats():
    # List with both ints and floats
    arr = [3, 1.5, 2, 0.5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 9.50μs -> 5.54μs

def test_sorter_strings():
    # List of strings (alphabetical sort)
    arr = ["banana", "apple", "cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.71μs -> 4.38μs

def test_sorter_single_element():
    # List with a single element
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.04μs -> 4.12μs

def test_sorter_two_elements_sorted():
    # Two elements, already sorted
    arr = [1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.21μs -> 4.17μs

def test_sorter_two_elements_unsorted():
    # Two elements, unsorted
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.12μs -> 4.17μs

# ---------------- Edge Test Cases ----------------

def test_sorter_empty_list():
    # Empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.79μs -> 3.92μs

def test_sorter_all_identical():
    # All elements are the same
    arr = [7] * 10
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 8.08μs -> 4.83μs

def test_sorter_large_and_small_numbers():
    # List with very large and very small numbers
    arr = [sys.maxsize, -sys.maxsize, 0, 999999999, -999999999]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 7.29μs -> 4.96μs

def test_sorter_strings_case_sensitive():
    # Case-sensitive string sorting
    arr = ["apple", "Banana", "banana", "Apple"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 7.79μs -> 4.67μs

def test_sorter_unicode_strings():
    # List with unicode strings
    arr = ["café", "cafe", "cafè", "cafÉ"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 8.62μs -> 4.96μs

def test_sorter_with_nan_and_inf():
    # List with float('nan'), float('inf'), -float('inf')
    arr = [3, float('inf'), 2, float('-inf'), float('nan')]
    # Sorting with NaN will always put NaN at the end (since NaN is not comparable)
    # But bubble sort will not move NaN, so its position may not change
    # Let's check that all numbers except NaN are sorted and NaN is present
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 8.21μs -> 5.04μs
    # Remove nan for comparison
    result_wo_nan = [x for x in result if not (isinstance(x, float) and str(x) == 'nan')]
    # Check that exactly one nan remains
    nan_count = sum(1 for x in result if isinstance(x, float) and str(x) == 'nan')

def test_sorter_mutates_input():
    # Ensure the input list is mutated (bubble sort is in-place)
    arr = [2, 1]
    sorter(arr)

def test_sorter_not_mutate_copy():
    # Ensure that passing a copy does not mutate the original
    arr = [2, 1]
    arr_copy = arr.copy()
    sorter(arr_copy)

def test_sorter_custom_objects_raises():
    # Sorting custom objects without __lt__ should raise TypeError
    class Foo:
        pass
    arr = [Foo(), Foo()]
    with pytest.raises(TypeError):
        sorter(arr.copy())

# ---------------- Large Scale Test Cases ----------------

def test_sorter_large_random_integers():
    # Large random integer list (1000 elements)
    arr = [random.randint(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 36.8ms -> 122μs

def test_sorter_large_sorted():
    # Already sorted large list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 26.2ms -> 56.5μs

def test_sorter_large_reverse_sorted():
    # Large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 41.0ms -> 57.0μs

def test_sorter_large_duplicates():
    # Large list with many duplicates
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 33.6ms -> 97.1μs

def test_sorter_large_strings():
    # Large list of random strings
    arr = [''.join(random.choices(string.ascii_letters, k=5)) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 42.1ms -> 144μs

def test_sorter_large_floats():
    # Large list of random floats
    arr = [random.uniform(-1e6, 1e6) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 35.9ms -> 463μs

def test_sorter_large_mixed_types_raises():
    # List with mixed types (should raise TypeError in Python 3)
    arr = [1, "a", 2, "b"]
    with pytest.raises(TypeError):
        sorter(arr.copy())
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.