⚡️ Speed up function sorter by 172,711%

[codeflash-ai]

📄 172,711% (1,727.11x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 3.37 seconds → 1.95 milliseconds (best of 513 runs)

📝 Explanation and details

Here’s your optimized program. I've replaced the manual bubble sort with Python's highly optimized built-in list.sort() method, which dramatically improves sorting speed and reduces computational overhead. The function signature and print statements are preserved as required. The function still prints exactly the same strings, and returns the sorted list in-place, just as before.

Explanation:

• The original bubble sort was O(n²) and slow for anything but the smallest lists.
• Python’s .sort() uses Timsort, which is O(n log n) and optimized in C.
• The function prints the informational messages at the start and end, as in your original.
• arr is modified and returned for compatibility.

(No original comments were present that needed to be preserved.)

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 20 Passed
🌀 Generated Regression Tests	✅ 62 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Existing Unit Tests Details

• benchmarks/test_benchmark_bubble_sort.py

  • test_sort2: 6.91ms $\textcolor{green}{\rightarrow}$ 16.5μs

• test_bubble_sort.py

  • test_sort: 826ms $\textcolor{green}{\rightarrow}$ 141μs

• test_bubble_sort_conditional.py

  • test_sort: 6.58μs $\textcolor{green}{\rightarrow}$ 3.12μs

• test_bubble_sort_import.py

  • test_sort: 827ms $\textcolor{green}{\rightarrow}$ 139μs

• test_bubble_sort_in_class.py

  • TestSorter.test_sort_in_pytest_class: 830ms $\textcolor{green}{\rightarrow}$ 141μs

• test_bubble_sort_parametrized.py

  • test_sort_parametrized: 507ms $\textcolor{green}{\rightarrow}$ 140μs

• test_bubble_sort_parametrized_loop.py

  • test_sort_loop_parametrized: 102μs $\textcolor{red}{\rightarrow}$ 20.5μs

🌀 Generated Regression Tests Details

import random  # used for generating large random lists
import string  # used for string sorting tests
import sys  # used for edge case 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_empty_list():
    # Test sorting an empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.08μs -> 2.88μs

def test_sorter_single_element():
    # Test sorting a single-element list
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.12μs -> 2.96μs

def test_sorter_already_sorted():
    # Test sorting an already sorted list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.83μs -> 2.96μs

def test_sorter_reverse_sorted():
    # Test sorting a reverse sorted list
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.12μs -> 3.00μs

def test_sorter_unsorted_integers():
    # Test sorting a typical unsorted integer list
    arr = [3, 1, 4, 1, 5, 9, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.54μs -> 3.08μs

def test_sorter_with_duplicates():
    # Test sorting with duplicate values
    arr = [2, 3, 2, 1, 3]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.83μs -> 3.00μs

def test_sorter_negative_numbers():
    # Test sorting with negative numbers
    arr = [-3, -1, -4, -2, 0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.83μs -> 3.00μs

def test_sorter_floats():
    # Test sorting a list of floats
    arr = [3.1, 2.4, 5.6, 1.1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.25μs -> 3.62μs

def test_sorter_mixed_integers_floats():
    # Test sorting a list with both ints and floats
    arr = [1, 2.2, 3, 0.5, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.46μs -> 3.62μs

def test_sorter_strings():
    # Test sorting a list of strings
    arr = ["banana", "apple", "cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.79μs -> 3.08μs

def test_sorter_unicode_strings():
    # Test sorting a list with unicode strings
    arr = ["ápple", "apple", "äpple"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.29μs -> 3.33μs

# -------------------- EDGE TEST CASES --------------------

def test_sorter_all_identical():
    # Test sorting a list where all elements are identical
    arr = [7] * 10
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.12μs -> 3.08μs

def test_sorter_two_elements_sorted():
    # Test sorting a two-element sorted list
    arr = [1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.88μs -> 2.92μs

def test_sorter_two_elements_unsorted():
    # Test sorting a two-element unsorted list
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.29μs -> 2.88μs

def test_sorter_large_and_small_numbers():
    # Test sorting a list with very large and very small numbers
    arr = [sys.maxsize, -sys.maxsize-1, 0, 999999999, -999999999]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.29μs -> 3.46μs

def test_sorter_minimal_difference():
    # Test sorting a list with minimal differences
    arr = [1.000001, 1.0000001, 1.00000001]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.58μs -> 3.75μs

def test_sorter_already_sorted_with_duplicates():
    # Test sorting an already sorted list with duplicates
    arr = [1, 2, 2, 3, 3, 3, 4]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.12μs -> 3.04μs

def test_sorter_reverse_sorted_with_duplicates():
    # Test sorting a reverse sorted list with duplicates
    arr = [4, 3, 3, 3, 2, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.92μs -> 3.08μs

def test_sorter_strings_case_sensitive():
    # Test sorting strings with different cases
    arr = ["apple", "Banana", "banana", "Apple"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.92μs -> 3.21μs

def test_sorter_strings_empty_and_nonempty():
    # Test sorting strings with empty and non-empty strings
    arr = ["", "a", "abc", ""]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.88μs -> 3.12μs

def test_sorter_list_with_none_raises():
    # Test that sorting a list with None and ints raises TypeError
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_list_with_unorderable_types_raises():
    # Test that sorting a list with unorderable types raises TypeError
    arr = [1, "string", 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

# -------------------- LARGE SCALE TEST CASES --------------------

def test_sorter_large_random_integers():
    # Test sorting a large list of random integers (size < 1000)
    arr = [random.randint(-10000, 10000) for _ in range(999)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 28.0ms -> 66.0μs

def test_sorter_large_sorted():
    # Test sorting a large already sorted list
    arr = list(range(999))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 18.5ms -> 29.1μs

def test_sorter_large_reverse_sorted():
    # Test sorting a large reverse sorted list
    arr = list(range(998, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 30.5ms -> 29.2μs

def test_sorter_large_strings():
    # Test sorting a large list of random strings
    arr = [
        ''.join(random.choices(string.ascii_letters, k=10))
        for _ in range(500)
    ]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.86ms -> 52.5μs

def test_sorter_large_floats():
    # Test sorting a large list of random floats
    arr = [random.uniform(-1e6, 1e6) for _ in range(999)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 26.2ms -> 279μs

def test_sorter_large_duplicates():
    # Test sorting a large list with many duplicates
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(999)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 24.6ms -> 49.4μs

def test_sorter_large_alternating_pattern():
    # Test sorting a large list with an alternating pattern
    arr = [i % 2 for i in range(999)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 21.3ms -> 43.7μs

def test_sorter_large_nearly_sorted():
    # Test sorting a large nearly sorted list (one element out of place)
    arr = list(range(999))
    arr[0], arr[-1] = arr[-1], arr[0]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 18.7ms -> 30.6μs
# 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 maxsize edge cases

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

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

def test_sorter_basic_sorted():
    # Already sorted list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.96μs -> 3.12μs

def test_sorter_basic_reverse():
    # Reversed list
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.62μs -> 2.96μs

def test_sorter_basic_random():
    # Random order
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.04μs -> 2.96μs

def test_sorter_basic_duplicates():
    # List with duplicate elements
    arr = [4, 2, 2, 3, 1, 4]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.21μs -> 3.04μs

def test_sorter_basic_single_element():
    # Single element list
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.08μs -> 2.92μs

def test_sorter_basic_two_elements():
    # Two elements, unsorted
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.17μs -> 2.88μs

def test_sorter_basic_two_elements_sorted():
    # Two elements, already sorted
    arr = [1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.00μs -> 2.83μs

def test_sorter_basic_negative_numbers():
    # List with negative numbers
    arr = [-3, -1, -4, -2, 0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.21μs -> 3.04μs

def test_sorter_basic_mixed_signs():
    # List with both positive and negative numbers
    arr = [3, -1, 0, -4, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.96μs -> 3.08μs

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

def test_sorter_edge_empty():
    # Empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.62μs -> 2.92μs

def test_sorter_edge_all_equal():
    # All elements are the same
    arr = [7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.38μs -> 2.96μs

def test_sorter_edge_large_numbers():
    # List with very large and very small integers
    arr = [sys.maxsize, -sys.maxsize-1, 0, 999999999, -999999999]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.42μs -> 3.33μs

def test_sorter_edge_floats():
    # List with floats and negative floats
    arr = [2.5, -1.1, 0.0, 3.3, -2.2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.88μs -> 3.92μs

def test_sorter_edge_floats_and_ints():
    # List with both ints and floats
    arr = [1, 2.2, 0, -3.3, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.33μs -> 3.58μs

def test_sorter_edge_strings():
    # List of strings (should sort lexicographically)
    arr = ["banana", "apple", "cherry", "date"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.25μs -> 3.17μs

def test_sorter_edge_strings_case():
    # List of strings with different cases
    arr = ["Banana", "apple", "Cherry", "date"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.71μs -> 3.12μs

def test_sorter_edge_single_char_strings():
    # List of single character strings
    arr = ["d", "a", "c", "b"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.83μs -> 3.00μs

def test_sorter_edge_unicode_strings():
    # List with unicode characters
    arr = ["éclair", "apple", "Éclair", "banana"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.92μs -> 3.46μs

def test_sorter_edge_mixed_types_raises():
    # List with mixed types should raise TypeError in Python 3
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_edge_bool_values():
    # List with boolean values (False==0, True==1)
    arr = [True, False, True, False]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.83μs -> 3.08μs

def test_sorter_edge_nested_lists_raises():
    # List with nested lists should raise TypeError
    arr = [1, [2], 3]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_edge_none_raises():
    # List with None should raise TypeError when compared to int
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

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

def test_sorter_large_sorted():
    # Large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 18.5ms -> 29.1μs

def test_sorter_large_reverse():
    # Large reversed list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 30.7ms -> 29.8μs

def test_sorter_large_random():
    # Large random list of ints
    arr = random.sample(range(-5000, -4000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 28.0ms -> 62.2μs

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 # 24.6ms -> 49.4μs

def test_sorter_large_strings():
    # Large list of random lowercase strings
    arr = [''.join(random.choices(string.ascii_lowercase, k=5)) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.86ms -> 52.5μs

def test_sorter_large_floats():
    # Large list of random floats
    arr = [random.uniform(-1000, 1000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 26.2ms -> 279μs

def test_sorter_large_all_equal():
    # Large list where all elements are equal
    arr = [42] * 1000
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 18.1ms -> 27.9μs

def test_sorter_large_alternating():
    # Large list alternating between two values
    arr = [0, 1] * 500
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 21.2ms -> 44.0μs

# ---------------------------
# Additional Robustness Test Cases
# ---------------------------

def test_sorter_mutation_does_not_affect_result():
    # Ensure the function does not return a reference to the original list if mutated after
    arr = [3, 1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.92μs -> 3.08μs
    arr[0] = 99

def test_sorter_returns_same_object():
    # Ensure the function returns the same object (in-place sort)
    arr = [2, 1]
    codeflash_output = sorter(arr); result = codeflash_output # 4.29μs -> 2.88μs
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-sorter-mc00qe0c and push.