⚡️ Speed up function sorter by 42,381%

[codeflash-ai-dev]

📄 42,381% (423.81x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 111 milliseconds → 261 microseconds (best of 1008 runs)
📊 Benchmark Performance Details

Benchmark File :: Function	Speedup	Original Runtime	Expected New Runtime
test_benchmark_bubble_sort.py::test_sort	18160.64%	7.85 milliseconds	43.0 microseconds
test_process_and_sort.py::test_compute_and_sort	71.05%	19.3 milliseconds	11.3 milliseconds
test_process_and_sort.py::test_no_func	29947.98%	8.06 milliseconds	26.8 microseconds

📝 Explanation and details

Your initial implementation of the sorter function uses bubble sort, which is not the most efficient sorting algorithm. We can improve the performance by using Python's built-in sorting function, which uses Timsort (a hybrid sorting algorithm derived from merge sort and insertion sort).

The built-in sort() method is optimized and runs in O(n log n) time complexity, making the function significantly faster for large lists compared to the O(n^2) time complexity of bubble sort.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 45 Passed
⏪ Replay Tests	✅ 9 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests Details

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

# unit tests

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

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

def test_already_sorted_list():
    # Test sorting an already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter([-3, -2, -1, 0, 1, 2])

def test_reverse_sorted_list():
    # Test sorting a reverse sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1])
    codeflash_output = sorter([10, 5, 0, -5, -10])

def test_all_elements_identical():
    # Test sorting a list with all identical elements
    codeflash_output = sorter([2, 2, 2, 2, 2])

def test_random_order_list():
    # Test sorting a list with elements in random order
    codeflash_output = sorter([3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5])
    codeflash_output = sorter([8, 3, 7, 4, 1, 2, 6, 5])

def test_list_with_negative_numbers():
    # Test sorting a list with negative numbers
    codeflash_output = sorter([4, -1, 2, -3, 0])
    codeflash_output = sorter([-5, -9, -3, -7, -1])

def test_list_with_floating_point_numbers():
    # Test sorting a list with floating point numbers
    codeflash_output = sorter([3.1, 2.4, 5.6, 1.2, 4.8])
    codeflash_output = sorter([1.1, 1.01, 1.001, 1.0001])

def test_list_with_mixed_data_types():
    # Test sorting a list with mixed data types (integers and floats)
    codeflash_output = sorter([1, 2.2, 3, 4.4, 5])

def test_large_scale():
    # Test sorting a large list with 1000 elements
    large_list = list(range(1000, 0, -1))
    sorted_large_list = list(range(1, 1001))
    codeflash_output = sorter(large_list)

def test_edge_cases():
    # Test sorting a list with all zeroes
    codeflash_output = sorter([0, 0, 0, 0])
    # Test sorting a list with infinity values
    codeflash_output = sorter([float('inf'), 1, float('-inf')])
# 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

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

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

def test_already_sorted_list():
    # Test sorting an already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter(['a', 'b', 'c', 'd'])

def test_reverse_sorted_list():
    # Test sorting a reverse sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1])
    codeflash_output = sorter(['d', 'c', 'b', 'a'])

def test_all_elements_same():
    # Test sorting a list where all elements are the same
    codeflash_output = sorter([1, 1, 1, 1])
    codeflash_output = sorter(['a', 'a', 'a', 'a'])

def test_list_with_negative_numbers():
    # Test sorting a list with negative numbers
    codeflash_output = sorter([-3, -1, -2, -4, -5])
    codeflash_output = sorter([3, -1, 2, -4, 5])

def test_list_with_mixed_positive_and_negative_numbers():
    # Test sorting a list with mixed positive and negative numbers
    codeflash_output = sorter([3, -1, 2, -4, 5])
    codeflash_output = sorter([-10, 0, 10, -5, 5])

def test_list_with_floating_point_numbers():
    # Test sorting a list with floating point numbers
    codeflash_output = sorter([3.1, 2.4, 1.5, 4.8, 5.0])
    codeflash_output = sorter([1.1, -1.1, 0.0, 2.2, -2.2])

def test_list_with_strings_of_different_lengths():
    # Test sorting a list of strings of different lengths
    codeflash_output = sorter(['apple', 'banana', 'cherry', 'date'])
    codeflash_output = sorter(['a', 'aaa', 'aa', 'aaaa'])

def test_list_with_mixed_data_types():
    # Test sorting a list with mixed data types, should raise TypeError
    with pytest.raises(TypeError):
        sorter([1, 'a', 2, 'b'])
    with pytest.raises(TypeError):
        sorter([3.1, 'apple', 2, 'banana'])

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

def test_list_with_duplicates():
    # Test sorting a list with duplicate values
    codeflash_output = sorter([3, 1, 2, 3, 4, 2, 1])
    codeflash_output = sorter(['b', 'a', 'c', 'b', 'a'])

def test_list_with_special_characters():
    # Test sorting a list with special characters
    codeflash_output = sorter(['!', '@', '#', ', '%'])
    codeflash_output = sorter(['apple', 'banana', 'cherry', 'date', 'apple!'])

def test_list_with_non_ascii_characters():
    # Test sorting a list with non-ASCII characters
    codeflash_output = sorter(['é', 'è', 'ê', 'ë', 'e'])
    codeflash_output = sorter(['ñ', 'n', 'ń', 'ň', 'ŋ'])

def test_list_with_nested_lists():
    # Test sorting a list with nested lists, should raise TypeError
    with pytest.raises(TypeError):
        sorter([1, [2, 3], 4, 5])
    with pytest.raises(TypeError):
        sorter([['a', 'b'], 'c', 'd'])
# 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-m8q9dwa9 and push.