⚡️ Speed up function mysorter by 92,240%

[codeflash-ai]

📄 92,240% (922.40x) speedup for mysorter in codeflash/bubble_sort.py

⏱️ Runtime : 1.97 seconds → 2.14 milliseconds (best of 368 runs)

📝 Explanation and details

The optimization replaces a manual bubble sort implementation with Python's built-in arr.sort() method, achieving a 922x speedup by leveraging algorithmic superiority and native C implementation.

Key Changes:

• Algorithm upgrade: Replaced O(n²) bubble sort with O(n log n) Timsort
• Implementation efficiency: Switched from Python bytecode loops to optimized C code
• Eliminated redundant operations: Removed manual swapping and nested iteration

Why This is Faster:

1. Algorithmic complexity: Bubble sort performs ~n²/2 comparisons while Timsort performs ~n log n comparisons
2. Native implementation: Python's sort() is implemented in C, avoiding Python's interpretation overhead
3. Adaptive optimizations: Timsort has special optimizations for already-sorted, reverse-sorted, and partially-sorted data

Performance Benefits by Test Case:

• Small lists (≤10 elements): 15-55% speedup due to reduced overhead
• Large sorted/reverse-sorted lists: 60,000-97,000% speedup as Timsort's adaptive nature excels with ordered data
• Large random lists: 38,000-45,000% speedup from superior algorithmic complexity
• String sorting: 27,000-38,000% speedup as Timsort handles lexicographic comparisons efficiently

The optimization maintains identical behavior (in-place sorting, same return value, preserved output) while dramatically improving performance across all input sizes and patterns.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 3 Passed
🌀 Generated Regression Tests	✅ 55 Passed
⏪ Replay Tests	✅ 2 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Existing Unit Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
test_bubble_sort.py::test_sort	1.42s	248μs	✅571045%

🌀 Generated Regression Tests and Runtime

import random  # used for generating large random lists
import string  # used for string sorting tests

# imports
import pytest  # used for our unit tests
from codeflash.bubble_sort import mysorter

# unit tests

# ------------------------
# 1. Basic Test Cases
# ------------------------

def test_empty_list():
    # Test sorting an empty list
    codeflash_output = mysorter([]) # 5.83μs -> 4.04μs (44.3% faster)

def test_single_element():
    # Test sorting a list with one element
    codeflash_output = mysorter([5]) # 5.21μs -> 4.21μs (23.8% faster)

def test_sorted_list():
    # Test sorting an already sorted list
    codeflash_output = mysorter([1, 2, 3, 4, 5]) # 6.29μs -> 4.33μs (45.2% faster)

def test_reverse_sorted_list():
    # Test sorting a reverse-sorted list
    codeflash_output = mysorter([5, 4, 3, 2, 1]) # 6.54μs -> 4.38μs (49.5% faster)

def test_unsorted_list():
    # Test sorting a typical unsorted list
    codeflash_output = mysorter([3, 1, 4, 1, 5, 9, 2]) # 7.00μs -> 4.58μs (52.7% faster)

def test_list_with_duplicates():
    # Test sorting a list with duplicate elements
    codeflash_output = mysorter([2, 3, 2, 1, 3, 1]) # 6.62μs -> 4.29μs (54.4% faster)

def test_list_with_negative_numbers():
    # Test sorting a list with negative numbers
    codeflash_output = mysorter([-3, -1, -2, 0, 2, 1]) # 6.42μs -> 4.46μs (43.9% faster)

def test_list_with_floats():
    # Test sorting a list with float values
    codeflash_output = mysorter([3.2, 1.5, 2.8, 1.5]) # 7.46μs -> 5.25μs (42.1% faster)

def test_list_with_integers_and_floats():
    # Test sorting a list with both integers and floats
    codeflash_output = mysorter([3, 1.2, 2, 1.2, 0]) # 7.79μs -> 5.17μs (50.8% faster)

def test_list_of_strings():
    # Test sorting a list of strings alphabetically
    codeflash_output = mysorter(["banana", "apple", "cherry"]) # 5.62μs -> 4.42μs (27.4% faster)

def test_list_of_single_char_strings():
    # Test sorting a list of single-character strings
    codeflash_output = mysorter(["c", "a", "b"]) # 5.12μs -> 4.25μs (20.6% faster)

def test_list_with_identical_elements():
    # Test sorting a list where all elements are the same
    codeflash_output = mysorter([7, 7, 7, 7]) # 5.42μs -> 4.17μs (30.0% faster)

def test_list_with_mixed_case_strings():
    # Test sorting a list of strings with mixed case (should be case-sensitive)
    codeflash_output = mysorter(["apple", "Banana", "banana", "Apple"]) # 6.04μs -> 4.54μs (33.1% faster)

# ------------------------
# 2. Edge Test Cases
# ------------------------

def test_large_negative_and_positive_numbers():
    # Test sorting a list with very large and very small numbers
    arr = [2**31-1, -2**31, 0, 999999, -999999]
    codeflash_output = mysorter(arr) # 7.25μs -> 4.75μs (52.6% faster)

def test_list_with_nan_and_inf():
    # Test sorting a list with float('nan'), float('inf'), and float('-inf')
    arr = [float('nan'), 1, float('inf'), -1, float('-inf'), 0]
    # NaN is not comparable, so its position after sorting is not defined by Python's sort.
    # Our bubble sort will push NaN to the end, as comparisons with NaN are always False.
    codeflash_output = mysorter(arr); result = codeflash_output # 7.96μs -> 5.17μs (54.0% faster)

def test_list_with_none_raises():
    # Test that sorting a list with None and numbers raises a TypeError
    with pytest.raises(TypeError):
        mysorter([None, 1, 2]) # 3.50μs -> 2.67μs (31.2% faster)

def test_list_with_different_types_raises():
    # Test that sorting a list with incompatible types raises a TypeError
    with pytest.raises(TypeError):
        mysorter([1, "a", 2]) # 2.96μs -> 2.58μs (14.5% faster)


def test_list_of_dicts_raises():
    # Test that sorting a list of dicts raises a TypeError
    with pytest.raises(TypeError):
        mysorter([{"a": 1}, {"b": 2}]) # 4.04μs -> 2.96μs (36.6% faster)

def test_list_with_empty_strings():
    # Test sorting a list with empty strings
    codeflash_output = mysorter(["", "a", "b", ""]) # 6.58μs -> 4.50μs (46.3% faster)

def test_list_with_unicode_strings():
    # Test sorting a list with unicode characters
    arr = ["éclair", "apple", "Éclair", "banana"]
    # Python's default sort is Unicode codepoint order
    codeflash_output = mysorter(arr) # 7.38μs -> 5.08μs (45.1% faster)

def test_list_with_mutable_elements():
    # Test that sorting a list with mutable but comparable elements (like tuples) works
    arr = [(2, 3), (1, 2), (2, 2)]
    codeflash_output = mysorter(arr) # 6.50μs -> 5.00μs (30.0% faster)

def test_list_with_boolean_values():
    # Test sorting a list with boolean values (False < True)
    arr = [True, False, True, False]
    codeflash_output = mysorter(arr) # 6.00μs -> 4.33μs (38.5% faster)

def test_input_is_not_modified():
    # Test that the input list is sorted in-place and the returned list is the same object
    arr = [3, 2, 1]
    codeflash_output = mysorter(arr); result = codeflash_output # 5.54μs -> 4.08μs (35.7% faster)

# ------------------------
# 3. Large Scale Test Cases
# ------------------------

def test_large_sorted_list():
    # Test sorting a large already sorted list (performance and correctness)
    arr = list(range(1000))
    codeflash_output = mysorter(arr) # 32.5ms -> 52.7μs (61628% faster)

def test_large_reverse_sorted_list():
    # Test sorting a large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = mysorter(arr) # 51.1ms -> 52.3μs (97497% faster)

def test_large_random_list():
    # Test sorting a large list of random integers
    arr = random.sample(range(1000), 1000)  # 1000 unique random numbers
    expected = sorted(arr)
    codeflash_output = mysorter(arr) # 47.1ms -> 113μs (41439% faster)

def test_large_list_with_duplicates():
    # Test sorting a large list with many duplicates
    arr = [random.choice(range(10)) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = mysorter(arr) # 42.2ms -> 96.3μs (43679% faster)

def test_large_list_of_strings():
    # Test sorting a large list of random lowercase strings
    arr = [''.join(random.choices(string.ascii_lowercase, k=5)) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = mysorter(arr) # 51.7ms -> 135μs (38119% faster)

def test_large_list_of_floats():
    # Test sorting a large list of random floats
    arr = [random.uniform(-1000, 1000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = mysorter(arr) # 44.7ms -> 396μs (11176% faster)
# 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 large integer edge cases

# imports
import pytest  # used for our unit tests
from codeflash.bubble_sort import mysorter

# unit tests

# ---------------------------
# 1. Basic Test Cases
# ---------------------------

def test_empty_list():
    """Test sorting an empty list."""
    arr = []
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 4.79μs -> 3.92μs (22.3% faster)

def test_single_element():
    """Test sorting a list with a single element."""
    arr = [42]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 5.12μs -> 4.17μs (23.0% faster)

def test_sorted_list():
    """Test sorting an already sorted list."""
    arr = [1, 2, 3, 4, 5]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 6.17μs -> 4.29μs (43.7% faster)

def test_reverse_sorted_list():
    """Test sorting a reverse-sorted list."""
    arr = [5, 4, 3, 2, 1]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 6.29μs -> 4.21μs (49.5% faster)

def test_unsorted_list():
    """Test sorting a typical unsorted list."""
    arr = [3, 1, 4, 5, 2]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 6.00μs -> 4.29μs (39.8% faster)

def test_duplicates():
    """Test sorting a list with duplicate elements."""
    arr = [2, 3, 2, 1, 3]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 6.12μs -> 4.12μs (48.5% faster)

def test_negative_numbers():
    """Test sorting a list with negative numbers."""
    arr = [-1, -3, 2, 0, -2]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 5.79μs -> 4.33μs (33.6% faster)

def test_all_equal_elements():
    """Test sorting a list where all elements are equal."""
    arr = [7, 7, 7, 7, 7]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 5.33μs -> 4.17μs (28.0% faster)

# ---------------------------
# 2. Edge Test Cases
# ---------------------------

def test_large_integers():
    """Test sorting a list with very large integers."""
    arr = [sys.maxsize, -sys.maxsize, 0, sys.maxsize-1, -sys.maxsize+1]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 7.42μs -> 4.88μs (52.1% faster)

def test_floats():
    """Test sorting a list of floats."""
    arr = [3.1, 2.4, -1.5, 0.0, 2.4]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 7.96μs -> 5.83μs (36.4% faster)

def test_mixed_int_float():
    """Test sorting a list with both ints and floats."""
    arr = [1, 2.2, -3, 4.4, 0]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 7.33μs -> 5.29μs (38.6% faster)

def test_strings():
    """Test sorting a list of strings."""
    arr = ["banana", "apple", "cherry", "date"]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 6.17μs -> 4.54μs (35.8% faster)

def test_strings_with_case():
    """Test sorting a list of strings with mixed case."""
    arr = ["Banana", "apple", "Cherry", "date"]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 5.75μs -> 4.54μs (26.6% faster)

def test_unicode_strings():
    """Test sorting a list of unicode strings."""
    arr = ["éclair", "apple", "Éclair", "banana"]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 6.96μs -> 4.83μs (44.0% faster)

def test_empty_strings():
    """Test sorting a list with empty strings."""
    arr = ["", "a", "b", ""]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 5.88μs -> 4.38μs (34.3% faster)

def test_list_of_lists():
    """Test sorting a list of lists (lexicographically)."""
    arr = [[2, 3], [1], [2, 2], [1, 2]]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 7.08μs -> 5.25μs (34.9% faster)

def test_list_with_none():
    """Test sorting a list containing None should raise TypeError."""
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        mysorter(arr.copy()) # 3.46μs -> 2.75μs (25.7% faster)

def test_heterogeneous_types():
    """Test sorting a list with incomparable types should raise TypeError."""
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        mysorter(arr.copy()) # 2.88μs -> 2.50μs (15.0% faster)

def test_list_with_nan():
    """Test sorting a list containing NaN values."""
    arr = [float('nan'), 1, 2]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 5.54μs -> 4.50μs (23.1% faster)

def test_list_with_infinity():
    """Test sorting a list containing infinity values."""
    arr = [float('inf'), 1, -float('inf'), 0]
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 6.46μs -> 4.62μs (39.7% faster)

# ---------------------------
# 3. Large Scale Test Cases
# ---------------------------

def test_large_sorted_list():
    """Test sorting a large already sorted list."""
    arr = list(range(1000))
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 32.1ms -> 52.5μs (61109% faster)

def test_large_reverse_sorted_list():
    """Test sorting a large reverse-sorted list."""
    arr = list(range(999, -1, -1))
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 51.1ms -> 52.5μs (97317% faster)

def test_large_random_list():
    """Test sorting a large random list of integers."""
    arr = random.sample(range(-10000, -9000), 1000)
    expected = sorted(arr)
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 46.7ms -> 117μs (39784% faster)

def test_large_list_with_duplicates():
    """Test sorting a large list with many duplicate elements."""
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = mysorter(arr.copy()); result = codeflash_output # 41.4ms -> 92.2μs (44869% faster)

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 = mysorter(arr.copy()); result = codeflash_output # 50.9ms -> 136μs (37299% faster)

def test_large_list_of_lists():
    """Test sorting a large list of lists lexicographically."""
    arr = [[random.randint(0, 100) for _ in range(3)] for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = mysorter([x.copy() for x in arr]); result = codeflash_output # 62.0ms -> 396μs (15535% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

⏪ Replay Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
test_codeflashbubble_sort_py__replay_test_0.py::test_codeflash_bubble_sort_mysorter	8.25μs	4.75μs	✅73.7%
test_codeflashbubble_sort_py__replay_test_1.py::test_codeflash_bubble_sort_mysorter	8.38μs	5.04μs	✅66.1%

To edit these changes git checkout codeflash/optimize-mysorter-me65ho9i and push.