⚡️ Speed up function sorter by 30,125%

[codeflash-ai-dev]

📄 30,125% (301.25x) speedup for sorter in cli/code_to_optimize/bubble_sort.py

⏱️ Runtime : 9.03 seconds → 29.9 milliseconds (best of 32 runs)

📝 Explanation and details

The given code is implementing the bubble sort algorithm, which is not optimal for sorting. We can significantly increase the speed of this function by switching to a more efficient sorting algorithm like Timsort, which is the default sorting algorithm used in Python. Here's the optimized version.

This utilizes Python's built-in sort method, which is highly efficient with a time complexity of O(n log n).

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 39 Passed
🌀 Generated Regression Tests	✅ 38 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	No coverage data found for sorter

⚙️ Existing Unit Tests Details

- test_bubble_sort.py
- test_bubble_sort__perfinstrumented.py
- test_bubble_sort_conditional.py
- test_bubble_sort_conditional__perfinstrumented.py
- test_bubble_sort_import.py
- test_bubble_sort_import__perfinstrumented.py
- test_bubble_sort_in_class.py
- test_bubble_sort_in_class__perfinstrumented.py
- test_bubble_sort_parametrized.py
- test_bubble_sort_parametrized__perfinstrumented.py
- test_bubble_sort_parametrized_loop.py
- test_bubble_sort_parametrized_loop__perfinstrumented.py
- test_sorter__unit_test_0.py
- test_sorter__unit_test_1.py

🌀 Generated Regression Tests Details

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

# unit tests

def test_already_sorted_list():
    # Test with a list that is already sorted
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter([10, 20, 30])

def test_reverse_sorted_list():
    # Test with a list that is sorted in reverse order
    codeflash_output = sorter([5, 4, 3, 2, 1])
    codeflash_output = sorter([30, 20, 10])

def test_unsorted_list():
    # Test with a list that is unsorted
    codeflash_output = sorter([3, 1, 4, 5, 2])
    codeflash_output = sorter([10, 5, 20, 15])

def test_single_element_list():
    # Test with a list containing a single element
    codeflash_output = sorter([1])
    codeflash_output = sorter([42])

def test_empty_list():
    # Test with an empty list
    codeflash_output = sorter([])

def test_list_with_duplicates():
    # Test with a list containing duplicate elements
    codeflash_output = sorter([2, 3, 2, 1, 3])
    codeflash_output = sorter([5, 5, 5, 5])

def test_list_with_negative_numbers():
    # Test with a list containing negative numbers
    codeflash_output = sorter([-1, -3, -2, 0, 2])
    codeflash_output = sorter([-5, -10, 0, 5, 10])

def test_list_with_mixed_numbers():
    # Test with a list containing both positive and negative numbers
    codeflash_output = sorter([-10, 5, -20, 15, 0])
    codeflash_output = sorter([3, -1, 4, -5, 2])

def test_list_with_floats():
    # Test with a list containing floating point numbers
    codeflash_output = sorter([2.5, 3.1, 1.8, 2.9])
    codeflash_output = sorter([1.1, 1.01, 1.001])

def test_list_with_strings():
    # Test with a list containing strings
    codeflash_output = sorter(["apple", "banana", "cherry"])
    codeflash_output = sorter(["dog", "cat", "bird"])

def test_large_list():
    # Test with a large list to assess performance
    large_list = list(range(1000, 0, -1))
    sorted_large_list = list(range(1, 1001))
    codeflash_output = sorter(large_list)

def test_non_comparable_elements():
    # Test with a list containing non-comparable elements
    with pytest.raises(TypeError):
        sorter([1, "two", 3])
    with pytest.raises(TypeError):
        sorter([None, 1, 2])

def test_stability():
    # Test with a list to check stability (order of equal elements)
    codeflash_output = sorter([1, 2, 2, 3, 3, 1])
    codeflash_output = sorter([5, 3, 3, 5, 1, 1])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort import sorter

# unit tests

# Test basic functionality with sorted list
def test_sorted_list():
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter(['a', 'b', 'c'])

# Test basic functionality with reverse sorted list
def test_reverse_sorted_list():
    codeflash_output = sorter([5, 4, 3, 2, 1])
    codeflash_output = sorter(['z', 'y', 'x'])

# Test basic functionality with unsorted list
def test_unsorted_list():
    codeflash_output = sorter([3, 1, 4, 2, 5])
    codeflash_output = sorter(['b', 'a', 'd', 'c'])

# Test edge case with empty list
def test_empty_list():
    codeflash_output = sorter([])

# Test edge case with single element list
def test_single_element_list():
    codeflash_output = sorter([1])
    codeflash_output = sorter(['a'])

# Test edge case with repeated elements
def test_repeated_elements():
    codeflash_output = sorter([2, 3, 2, 1, 1])
    codeflash_output = sorter(['a', 'b', 'a', 'c', 'b'])

# Test edge case with negative numbers
def test_negative_numbers():
    codeflash_output = sorter([-1, -3, -2, 0, 2])

# Test edge case with mixed positive and negative numbers
def test_mixed_numbers():
    codeflash_output = sorter([3, -1, 2, -3, 0])

# Test special case with all identical elements
def test_identical_elements():
    codeflash_output = sorter([5, 5, 5, 5])

# Test special case with large numbers
def test_large_numbers():
    codeflash_output = sorter([1000000, 500000, 1000001])

# Test performance with large list
def test_large_list():
    large_list = list(range(1000, 0, -1))
    sorted_list = list(range(1, 1001))
    codeflash_output = sorter(large_list)

# Test robustness with non-comparable elements
def test_non_comparable_elements():
    with pytest.raises(TypeError):
        sorter([1, 'a', 3])

# Test edge case with floats
def test_floats():
    codeflash_output = sorter([3.1, 2.2, 5.5, 4.4])

# Test edge case with mixed integers and floats
def test_mixed_integers_floats():
    codeflash_output = sorter([1, 2.2, 3, 0.5])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

📢 Feedback on this optimization?