⚡️ Speed up function sorter by 86,992%

[codeflash-ai]

📄 86,992% (869.92x) speedup for sorter in codeflash/galileo/bubble_sort.py

⏱️ Runtime : 1.21 seconds → 1.39 milliseconds (best of 481 runs)

📝 Explanation and details

Here is a faster implementation of the sorter function. The original code uses a naive bubble sort (O(n^2)), which is very slow for large lists. Instead, this version uses Python’s built-in sort() method, which is implemented using Timsort and is highly optimized (O(n log n)).

All comments are preserved.

This will be significantly faster and more memory-efficient than bubble sort, while preserving all behavior and function output.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 3 Passed
🌀 Generated Regression Tests	✅ 57 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Existing Unit Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
/Users/codeflash/Downloads/codeflash-dev/codeflash/tests/galileo/test_bubble_sort.py::test_sort	857ms	130μs	✅658509%

🌀 Generated Regression Tests and Runtime

import random  # used for generating large random test data
import string  # used for string sorting tests
import sys  # used for edge number tests

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

# unit tests

# ---------------------------
# BASIC TEST CASES
# ---------------------------

def test_sorter_basic_sorted():
    # Already sorted list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.00μs -> 3.25μs (53.8% faster)

def test_sorter_basic_reverse():
    # Reverse sorted list
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.17μs -> 3.17μs (63.2% faster)

def test_sorter_basic_unsorted():
    # Unsorted list
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.62μs -> 3.04μs (52.1% faster)

def test_sorter_basic_duplicates():
    # List with duplicate values
    arr = [2, 3, 2, 1, 4]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.58μs -> 3.00μs (52.8% faster)

def test_sorter_basic_single_element():
    # Single element list
    arr = [42]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 3.58μs -> 2.92μs (22.9% faster)

def test_sorter_basic_two_elements_sorted():
    # Two elements, already sorted
    arr = [1, 2]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 3.54μs -> 3.00μs (18.1% faster)

def test_sorter_basic_two_elements_unsorted():
    # Two elements, unsorted
    arr = [2, 1]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 3.54μs -> 2.96μs (19.7% faster)

def test_sorter_basic_empty():
    # Empty list
    arr = []
    codeflash_output = sorter(arr[:]); result = codeflash_output # 3.50μs -> 2.96μs (18.3% faster)

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

def test_sorter_edge_all_same():
    # All elements are the same
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.25μs -> 3.04μs (39.8% faster)

def test_sorter_edge_negative_numbers():
    # List with negative numbers
    arr = [-3, -1, -2, -5, -4]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.04μs -> 2.96μs (70.4% faster)

def test_sorter_edge_mixed_signs():
    # List with both positive and negative numbers
    arr = [3, -1, 2, -5, 0]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.58μs -> 3.08μs (48.7% faster)

def test_sorter_edge_floats():
    # List with floats
    arr = [3.1, 2.4, 5.6, 1.0, 4.2]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 6.04μs -> 3.92μs (54.3% faster)

def test_sorter_edge_mixed_int_float():
    # List with both ints and floats
    arr = [3, 2.2, 5, 1.1, 4]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.58μs -> 3.58μs (55.8% faster)

def test_sorter_edge_large_numbers():
    # List with very large and very small numbers
    arr = [sys.maxsize, -sys.maxsize-1, 0, 999999999, -999999999]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.79μs -> 3.46μs (67.4% faster)

def test_sorter_edge_strings():
    # List of strings
    arr = ["banana", "apple", "cherry", "date"]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.00μs -> 3.33μs (50.0% faster)

def test_sorter_edge_strings_case():
    # List of strings with mixed case (lexicographical order)
    arr = ["banana", "Apple", "cherry", "Date"]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.79μs -> 3.12μs (53.3% faster)

def test_sorter_edge_empty_strings():
    # List with empty strings
    arr = ["", "a", "b", ""]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.88μs -> 3.08μs (58.1% faster)

def test_sorter_edge_single_char_strings():
    # List of single character strings
    arr = ["d", "a", "c", "b"]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 4.83μs -> 3.08μs (56.7% faster)

def test_sorter_edge_unicode_strings():
    # List of unicode strings
    arr = ["éclair", "banana", "apple", "çava"]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 5.79μs -> 3.46μs (67.4% faster)

def test_sorter_edge_none_raises():
    # List containing None should raise TypeError
    arr = [1, None, 3]
    with pytest.raises(TypeError):
        sorter(arr[:])

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


def test_sorter_large_sorted():
    # Large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr[:]); result = codeflash_output # 19.8ms -> 28.8μs (68566% faster)

def test_sorter_large_reverse():
    # Large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr[:]); result = codeflash_output # 31.4ms -> 28.4μs (110661% faster)

def test_sorter_large_random():
    # Large random list
    arr = list(range(1000))
    random.shuffle(arr)
    codeflash_output = sorter(arr[:]); result = codeflash_output # 28.1ms -> 73.8μs (37934% faster)

def test_sorter_large_duplicates():
    # Large list with many duplicates
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 25.6ms -> 53.6μs (47561% faster)

def test_sorter_large_strings():
    # Large list of random strings
    arr = [''.join(random.choices(string.ascii_letters, k=5)) for _ in range(500)]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 6.98ms -> 45.8μs (15142% faster)

def test_sorter_large_negative_and_positive():
    # Large list with both negative and positive numbers
    arr = [random.randint(-100000, 100000) for _ in range(1000)]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 28.3ms -> 81.0μs (34789% faster)

def test_sorter_large_floats():
    # Large list of floats
    arr = [random.uniform(-1000, 1000) for _ in range(1000)]
    codeflash_output = sorter(arr[:]); result = codeflash_output # 27.4ms -> 264μs (10272% faster)

def test_sorter_large_all_same():
    # Large list where all elements are the same
    arr = [42] * 1000
    codeflash_output = sorter(arr[:]); result = codeflash_output # 19.1ms -> 26.9μs (70840% faster)

# ---------------------------
# ADDITIONAL EDGE CASES
# ---------------------------

def test_sorter_mutation():
    # Ensure the function does not mutate the input list (since it does, this test will fail)
    arr = [3, 2, 1]
    arr_copy = arr[:]
    sorter(arr) # 4.58μs -> 3.12μs (46.7% faster)



import random  # used for generating large random lists
import string  # used for non-integer sorting tests
import sys  # used for testing large/small numbers

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

# unit tests

# 1. BASIC TEST CASES

def test_sorter_empty_list():
    # Test sorting an empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.04μs -> 2.96μs (36.6% faster)

def test_sorter_single_element():
    # Test sorting a list with a single element
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.00μs -> 2.83μs (41.1% faster)

def test_sorter_sorted_list():
    # Test sorting an already sorted list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.71μs -> 3.00μs (56.9% faster)

def test_sorter_reverse_sorted_list():
    # Test sorting a reverse-sorted list
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.08μs -> 3.08μs (64.8% faster)

def test_sorter_unsorted_list():
    # Test sorting a randomly unsorted list
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.83μs -> 3.04μs (58.9% faster)

def test_sorter_duplicates():
    # Test sorting a list with duplicate elements
    arr = [2, 3, 2, 1, 3]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.71μs -> 3.00μs (56.9% faster)

def test_sorter_negative_numbers():
    # Test sorting a list with negative numbers
    arr = [-3, -1, -2, 0, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.58μs -> 3.04μs (50.7% faster)

def test_sorter_mixed_positive_negative():
    # Test sorting a list with both negative and positive numbers
    arr = [-10, 5, 0, -3, 8]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.83μs -> 3.17μs (52.6% faster)

def test_sorter_floats():
    # Test sorting a list with float numbers
    arr = [2.2, 1.1, 3.3, 0.0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.29μs -> 3.62μs (46.0% faster)

def test_sorter_mixed_int_float():
    # Test sorting a list with both integers and floats
    arr = [1, 2.2, 0, 3.3, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.58μs -> 3.71μs (50.6% faster)

# 2. EDGE TEST CASES

def test_sorter_all_equal():
    # Test sorting a list where all elements are equal
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.42μs -> 3.00μs (47.2% faster)

def test_sorter_two_elements_sorted():
    # Test sorting two elements, already sorted
    arr = [1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.75μs -> 2.92μs (28.6% faster)

def test_sorter_two_elements_unsorted():
    # Test sorting two elements, unsorted
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.92μs -> 2.96μs (32.4% faster)

def test_sorter_large_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 # 6.00μs -> 3.54μs (69.4% faster)

def test_sorter_strings():
    # Test sorting a list of strings
    arr = ["banana", "apple", "cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.58μs -> 3.17μs (44.8% faster)

def test_sorter_mixed_case_strings():
    # Test sorting a list of strings with mixed case
    arr = ["Banana", "apple", "Cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.54μs -> 3.25μs (39.7% faster)

def test_sorter_unicode_strings():
    # Test sorting a list of unicode strings
    arr = ["α", "β", "γ", "a", "b"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.29μs -> 4.04μs (55.7% faster)

def test_sorter_empty_strings():
    # Test sorting a list with empty strings
    arr = ["", "a", "b", ""]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.83μs -> 3.12μs (54.7% faster)

def test_sorter_nested_lists_error():
    # Test sorting a list with nested lists (should raise TypeError)
    arr = [1, [2, 3], 4]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_incomparable_types_error():
    # Test sorting a list with incomparable types (should raise TypeError)
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_none_in_list_error():
    # Test sorting a list with None (should raise TypeError)
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

# 3. LARGE SCALE TEST CASES

def test_sorter_large_random_ints():
    # Test sorting a large list of random integers
    arr = random.sample(range(-100000, -99000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 28.6ms -> 60.2μs (47425% faster)

def test_sorter_large_sorted():
    # Test sorting a large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 19.6ms -> 28.4μs (68857% faster)

def test_sorter_large_reverse_sorted():
    # Test sorting a large reverse-sorted list
    arr = list(range(999, -1, -1))
    expected = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 31.5ms -> 28.5μs (110536% faster)

def test_sorter_large_duplicates():
    # Test sorting a 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 # 25.4ms -> 47.8μs (52986% faster)

def test_sorter_large_strings():
    # Test sorting a 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 # 30.2ms -> 88.5μs (34068% faster)

def test_sorter_large_floats():
    # Test sorting a 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 # 26.7ms -> 268μs (9842% faster)
# 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-mcnpygzh and push.