⚡️ Speed up function sorter by 9%

[codeflash-ai]

📄 9% (0.09x) speedup for sorter in src/async_examples/concurrency.py

⏱️ Runtime : 1.33 seconds → 1.22 seconds (best of 78 runs)

📝 Explanation and details

The optimization replaces a manual bubble sort implementation with Python's built-in arr.sort() method, delivering significant performance improvements.

Key Changes:

• Algorithm replacement: Eliminated the nested O(n²) bubble sort loops with Python's native arr.sort() which uses Timsort (O(n log n))
• Reduced complexity: From ~7 lines of sorting logic to 1 line
• Maintained behavior: Still sorts in-place and preserves all async functionality, print statements, and return values

Why it's faster:
The line profiler shows the dramatic difference - the original code spent 98.8% of its time in the nested loops (lines with 2M+ hits), while the optimized version completes the sort in just 7.5% of total execution time. Python's Timsort is a highly optimized hybrid stable sorting algorithm implemented in C, making it orders of magnitude faster than a Python-based bubble sort.

Performance characteristics:

• Small lists (5-50 elements): Moderate speedup due to overhead being dominant
• Medium lists (200-500 elements): Significant speedup as algorithmic complexity becomes the bottleneck
• Large datasets: Would show exponentially better performance (bubble sort's O(n²) vs Timsort's O(n log n))
• Already sorted data: Timsort's adaptive nature provides near-optimal performance

The 8% overall speedup in this test suite is conservative because most test cases use small arrays where the async sleep dominates runtime, but the algorithmic improvement provides substantial benefits for any non-trivial data sizes.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 110 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import asyncio  # used to run async functions
import random  # used for generating large random lists
import sys  # used for edge case with sys.maxsize

import pytest  # used for our unit tests
from src.async_examples.concurrency import sorter

# ==============================
# Basic Test Cases
# ==============================

@pytest.mark.asyncio
async def test_sorter_empty_list():
    # Test sorting an empty list
    arr = []
    result = await sorter(arr.copy())

@pytest.mark.asyncio
async def test_sorter_single_element():
    # Test sorting a single-element list
    arr = [42]
    result = await sorter(arr.copy())

@pytest.mark.asyncio
async def test_sorter_sorted_list():
    # Test sorting an already sorted list
    arr = [1, 2, 3, 4, 5]
    result = await sorter(arr.copy())

@pytest.mark.asyncio
async def test_sorter_reverse_sorted_list():
    # Test sorting a reverse-sorted list
    arr = [5, 4, 3, 2, 1]
    result = await sorter(arr.copy())

@pytest.mark.asyncio
async def test_sorter_duplicates():
    # Test sorting a list with duplicate elements
    arr = [3, 1, 2, 3, 2, 1]
    result = await sorter(arr.copy())

@pytest.mark.asyncio
async def test_sorter_negative_numbers():
    # Test sorting a list with negative numbers
    arr = [-3, -1, -2, 0, 2, 1]
    result = await sorter(arr.copy())

@pytest.mark.asyncio
async def test_sorter_mixed_numbers():
    # Test sorting a list with both positive and negative numbers
    arr = [0, -10, 5, -3, 2, 8, -1]
    result = await sorter(arr.copy())

# ==============================
# Edge Test Cases
# ==============================

@pytest.mark.asyncio
async def test_sorter_all_equal():
    # Test sorting a list where all elements are equal
    arr = [7, 7, 7, 7, 7]
    result = await sorter(arr.copy())

@pytest.mark.asyncio
async def test_sorter_large_and_small_integers():
    # Test sorting a list with very large and very small integers
    arr = [sys.maxsize, -sys.maxsize - 1, 0, 123, -456]
    result = await sorter(arr.copy())

@pytest.mark.asyncio
async def test_sorter_floats_and_integers():
    # Test sorting a list with both floats and integers
    arr = [3.5, 2, 4.1, 3, 2.2]
    result = await sorter(arr.copy())

@pytest.mark.asyncio
async def test_sorter_mutation_no_side_effects():
    # Ensure that the original list is not mutated (since sorter returns the same list, this will fail if the function is changed)
    arr = [2, 1, 3]
    arr_copy = arr.copy()
    result = await sorter(arr_copy)

@pytest.mark.asyncio
async def test_sorter_concurrent_execution():
    # Test concurrent execution of sorter on different lists
    arr1 = [5, 3, 1]
    arr2 = [10, 9, 8]
    arr3 = [2, 2, 2]
    results = await asyncio.gather(
        sorter(arr1.copy()),
        sorter(arr2.copy()),
        sorter(arr3.copy())
    )

@pytest.mark.asyncio
async def test_sorter_cancellation():
    # Test that sorter can be cancelled if running too long
    arr = list(range(999, -1, -1))  # 1000 elements in reverse order
    task = asyncio.create_task(sorter(arr.copy()))
    await asyncio.sleep(0.0001)  # Give the task a chance to start
    task.cancel()
    try:
        await task
    except asyncio.CancelledError:
        pass  # Expected

@pytest.mark.asyncio
async def test_sorter_exception_on_non_comparable():
    # Test that sorter raises an exception on non-comparable elements
    arr = [1, "a", 3]
    with pytest.raises(TypeError):
        await sorter(arr.copy())

# ==============================
# Large Scale Test Cases
# ==============================

@pytest.mark.asyncio
async def test_sorter_large_random_list():
    # Test sorting a large random list (under 1000 elements)
    arr = [random.randint(-10000, 10000) for _ in range(500)]
    expected = sorted(arr)
    result = await sorter(arr.copy())

@pytest.mark.asyncio
async def test_sorter_many_concurrent_large_lists():
    # Test concurrent sorting of multiple large lists
    lists = [[random.randint(-10000, 10000) for _ in range(200)] for _ in range(5)]
    expected = [sorted(lst) for lst in lists]
    results = await asyncio.gather(*(sorter(lst.copy()) for lst in lists))

@pytest.mark.asyncio
async def test_sorter_performance_under_concurrent_load():
    # Test performance under concurrent load (timing is not strictly enforced, but function should complete)
    lists = [[random.randint(-1000, 1000) for _ in range(100)] for _ in range(10)]
    try:
        await asyncio.wait_for(asyncio.gather(*(sorter(lst.copy()) for lst in lists)), timeout=2)
    except asyncio.TimeoutError:
        pass

# ==============================
# Async/Await Pattern Tests
# ==============================

@pytest.mark.asyncio
async def test_sorter_returns_coroutine():
    # Test that sorter returns a coroutine and must be awaited
    arr = [3, 2, 1]
    codeflash_output = sorter(arr.copy()); coro = codeflash_output
    result = await coro
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
import asyncio  # used to run async functions
import random  # used for generating large random lists
import sys  # used for edge case with sys.maxsize

import pytest  # used for our unit tests
from src.async_examples.concurrency import sorter

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

@pytest.mark.asyncio
async def test_sorter_empty_list():
    # Test sorting an empty list
    result = await sorter([])

@pytest.mark.asyncio
async def test_sorter_single_element():
    # Test sorting a list with a single element
    result = await sorter([42])

@pytest.mark.asyncio
async def test_sorter_sorted_list():
    # Test sorting an already sorted list
    result = await sorter([1, 2, 3, 4, 5])

@pytest.mark.asyncio
async def test_sorter_reverse_sorted_list():
    # Test sorting a reverse-sorted list
    result = await sorter([5, 4, 3, 2, 1])

@pytest.mark.asyncio
async def test_sorter_unsorted_list():
    # Test sorting a typical unsorted list
    result = await sorter([3, 1, 4, 1, 5, 9, 2])

@pytest.mark.asyncio
async def test_sorter_list_with_duplicates():
    # Test sorting a list with duplicate values
    result = await sorter([2, 3, 2, 1, 3])

@pytest.mark.asyncio
async def test_sorter_list_with_negative_numbers():
    # Test sorting a list with negative numbers
    result = await sorter([-3, -1, -2, 0, 2])

@pytest.mark.asyncio
async def test_sorter_list_with_mixed_signs():
    # Test sorting a list with both positive and negative numbers
    result = await sorter([0, -10, 5, -3, 8])

@pytest.mark.asyncio
async def test_sorter_list_with_all_equal_elements():
    # Test sorting a list where all elements are the same
    result = await sorter([7, 7, 7, 7])

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

@pytest.mark.asyncio
async def test_sorter_large_numbers():
    # Test sorting a list with very large and very small integers
    result = await sorter([sys.maxsize, -sys.maxsize, 0])

@pytest.mark.asyncio
async def test_sorter_mutates_input():
    # Test that the input list is mutated in-place (since the implementation is in-place)
    arr = [3, 2, 1]
    result = await sorter(arr)

@pytest.mark.asyncio
async def test_sorter_with_floats():
    # Test sorting a list with floats and integers
    arr = [3.2, 1, 2.5, -1.1]
    result = await sorter(arr)

@pytest.mark.asyncio
async def test_sorter_with_strings_raises():
    # Test that sorting a list with non-comparable types raises TypeError
    arr = [1, "a", 3]
    with pytest.raises(TypeError):
        await sorter(arr)

@pytest.mark.asyncio
async def test_sorter_with_none_raises():
    # Test that sorting a list containing None and ints raises TypeError
    arr = [None, 2, 1]
    with pytest.raises(TypeError):
        await sorter(arr)

@pytest.mark.asyncio
async def test_sorter_concurrent_execution():
    # Test concurrent execution with different inputs
    arr1 = [5, 3, 1]
    arr2 = [2, 4, 6]
    arr3 = [9, 7, 8]
    results = await asyncio.gather(
        sorter(arr1.copy()),
        sorter(arr2.copy()),
        sorter(arr3.copy())
    )

@pytest.mark.asyncio
async def test_sorter_cancellation():
    # Test that the sorter can be cancelled mid-execution
    arr = [5, 4, 3, 2, 1]
    task = asyncio.create_task(sorter(arr))
    await asyncio.sleep(0.000005)  # Let it start
    task.cancel()
    try:
        await task
    except asyncio.CancelledError:
        pass  # Expected
    else:
        pass

@pytest.mark.asyncio
async def test_sorter_timeout():
    # Test that sorter raises asyncio.TimeoutError if not completed in time
    arr = [5, 4, 3, 2, 1]
    with pytest.raises(asyncio.TimeoutError):
        await asyncio.wait_for(sorter(arr), timeout=0.000001)  # Very short timeout

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

@pytest.mark.asyncio
async def test_sorter_large_random_list():
    # Test sorting a large random list (size ~500)
    random.seed(42)
    arr = [random.randint(-10000, 10000) for _ in range(500)]
    expected = sorted(arr)
    result = await sorter(arr)

@pytest.mark.asyncio
async def test_sorter_concurrent_large_lists():
    # Test concurrent sorting of multiple large lists
    random.seed(123)
    lists = [[random.randint(-1000, 1000) for _ in range(200)] for _ in range(5)]
    expected = [sorted(lst) for lst in lists]
    results = await asyncio.gather(*(sorter(lst) for lst in lists))

@pytest.mark.asyncio
async def test_sorter_many_small_concurrent():
    # Test many concurrent small sorts to check async scalability
    lists = [[random.randint(0, 100) for _ in range(5)] for _ in range(50)]
    expected = [sorted(lst) for lst in lists]
    results = await asyncio.gather(*(sorter(lst) for lst in lists))

@pytest.mark.asyncio
async def test_sorter_stress_mutation_and_concurrency():
    # Test that concurrent sorts on the same list object do not interfere (should not share memory)
    arr = [random.randint(-100, 100) for _ in range(50)]
    arr_copy1 = arr.copy()
    arr_copy2 = arr.copy()
    results = await asyncio.gather(
        sorter(arr_copy1),
        sorter(arr_copy2)
    )
# 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-mfelomug and push.