⚡️ Speed up function sorter by 116,847%

[codeflash-ai]

📄 116,847% (1,168.47x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 4.87 seconds → 4.17 milliseconds (best of 60 runs)

📝 Explanation and details

Certainly! Your current implementation is a bubble sort, which is very slow for large arrays due to its O(n²) complexity and inefficient use of Python's strengths.

To maximize performance while keeping the function signature unchanged, the best approach is to replace the custom bubble sort with Python’s built-in list.sort(), which is highly optimized (Timsort, O(n log n)). This will give you a major speed-up, minimize memory use (in-place sorting), and preserve all side-effects and the return value.

Here’s the optimized version.

Justification.

• arr.sort() is implemented in C and is far faster and more memory efficient than any pure Python double for-loop sort.
• All output/return behaviour is identical.
• No additional memory is needed (in-place sort).
• The print statements are preserved as in the original code.

No further optimizations can outperform Python's built-in sort for general-purpose lists in CPython.

---

If you specifically need to write a faster pure Python sort (not using the built-in), let me know!

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 14 Passed
🌀 Generated Regression Tests	✅ 56 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_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

🌀 Generated Regression Tests Details

import random  # used for generating large random lists
import string  # used for string sorting tests
import sys  # used for edge value tests

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

# unit tests

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

def test_empty_list():
    # Test sorting an empty list
    codeflash_output = sorter([]) # 14μs -> 13μs

def test_single_element():
    # Test sorting a list with one element
    codeflash_output = sorter([42]) # 13μs -> 13μs

def test_sorted_list():
    # Test sorting an already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5]) # 16μs -> 13μs

def test_reverse_sorted_list():
    # Test sorting a reverse-sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1]) # 16μs -> 13μs

def test_duplicates():
    # Test sorting a list with duplicate elements
    codeflash_output = sorter([3, 1, 2, 3, 1]) # 16μs -> 13μs

def test_negative_numbers():
    # Test sorting a list with negative numbers
    codeflash_output = sorter([0, -1, -3, 2, 1]) # 18μs -> 13μs

def test_mixed_positive_negative():
    # Test sorting a list with both positive and negative numbers
    codeflash_output = sorter([-2, 99, 0, -42, 17, 4]) # 18μs -> 14μs

def test_floats():
    # Test sorting a list with floats
    codeflash_output = sorter([3.1, 2.2, 5.5, 1.0]) # 20μs -> 15μs

def test_mixed_int_float():
    # Test sorting a list with both ints and floats
    codeflash_output = sorter([1, 2.2, 0, 3.3, 2]) # 19μs -> 14μs

def test_strings():
    # Test sorting a list of strings (lexicographical order)
    codeflash_output = sorter(['banana', 'apple', 'cherry']) # 18μs -> 13μs

def test_mixed_case_strings():
    # Test sorting a list of strings with different cases
    codeflash_output = sorter(['Banana', 'apple', 'Cherry']) # 17μs -> 14μs

def test_all_equal():
    # Test sorting a list where all elements are equal
    codeflash_output = sorter([7, 7, 7, 7]) # 17μs -> 13μs

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

def test_large_negative_and_positive():
    # Test sorting with very large and very small integers
    arr = [sys.maxsize, -sys.maxsize-1, 0, 999999, -999999]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 19μs -> 15μs

def test_all_minimum_values():
    # Test sorting a list of minimum integer values
    arr = [-sys.maxsize-1] * 5
    codeflash_output = sorter(arr.copy()) # 18μs -> 14μs

def test_all_maximum_values():
    # Test sorting a list of maximum integer values
    arr = [sys.maxsize] * 5
    codeflash_output = sorter(arr.copy()) # 18μs -> 15μs

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

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


def test_unicode_strings():
    # Test sorting a list with unicode strings
    arr = ['éclair', 'apple', 'Éclair']
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 18μs -> 14μs

def test_special_characters():
    # Test sorting a list with special characters
    arr = ['!', '@', '#', 'A', 'a']
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 15μs -> 13μs

def test_very_large_numbers():
    # Test sorting a list with very large numbers
    arr = [10**100, 10**10, -10**100, 0]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 19μs -> 14μs

def test_mutation_of_input():
    # Test that the input list is mutated in-place and returned
    arr = [3, 1, 2]
    codeflash_output = sorter(arr); result = codeflash_output

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

def test_large_sorted_list():
    # Test sorting a large already sorted list
    arr = list(range(1000))
    expected = list(range(1000))
    codeflash_output = sorter(arr.copy()) # 27ms -> 69μs

def test_large_reverse_sorted_list():
    # Test sorting a large reverse-sorted list
    arr = list(range(999, -1, -1))
    expected = list(range(1000))
    codeflash_output = sorter(arr.copy()) # 43ms -> 68μs

def test_large_random_list():
    # Test sorting a large random list of integers
    arr = [random.randint(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 39ms -> 134μs

def test_large_list_with_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()) # 35ms -> 107μs

def test_large_string_list():
    # 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()) # 43ms -> 153μs

def test_large_float_list():
    # 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()) # 37ms -> 468μs

def test_large_already_equal():
    # Test sorting a large list where all elements are the same
    arr = [42] * 1000
    expected = [42] * 1000
    codeflash_output = sorter(arr.copy()) # 26ms -> 65μs

def test_large_alternating_pattern():
    # Test sorting a large list with an alternating pattern
    arr = [1, 0] * 500
    expected = [0]*500 + [1]*500
    codeflash_output = sorter(arr.copy()) # 31ms -> 84μs
# 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 case

# 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

def test_sorter_reverse_sorted_list():
    # Reverse sorted list should become sorted
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_random_list():
    # Unsorted list should become sorted
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_with_duplicates():
    # List with duplicate elements should be sorted with duplicates preserved
    arr = [3, 1, 2, 3, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_single_element():
    # Single element list should remain unchanged
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_two_elements():
    # Two element list, unsorted
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

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

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

def test_sorter_floats():
    # List with floating point numbers
    arr = [3.2, 1.5, 2.8, 1.5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

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

def test_sorter_empty_list():
    # Empty list should remain unchanged
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output

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

def test_sorter_all_equal_elements():
    # All elements are the same
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_and_small_ints():
    # 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

def test_sorter_unicode_strings():
    # List with unicode strings
    arr = ["éclair", "apple", "Álgebra", "banana"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

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

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


def test_sorter_mutation():
    # Ensure that the original list is mutated (in-place sort)
    arr = [3, 2, 1]
    sorter(arr)

def test_sorter_object_identity():
    # Ensure the returned list is the same object (in-place)
    arr = [2, 1]
    codeflash_output = sorter(arr); result = codeflash_output

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

def test_sorter_large_random_integers():
    # Large list of random integers
    arr = [random.randint(-100000, 100000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_sorted():
    # Large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output

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

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

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

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

# ---------------- Additional Edge Cases ----------------

def test_sorter_empty_and_nonempty_strings():
    # List with empty and non-empty strings
    arr = ["", "abc", "def", ""]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_long_identical_prefix_strings():
    # Strings with long identical prefixes
    arr = ["aaaab", "aaaac", "aaaaa", "aaaad"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_list_of_booleans():
    # List of booleans (False < True)
    arr = [True, False, True, False]
    codeflash_output = sorter(arr.copy()); result = codeflash_output
# 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-mbk53n7f and push.