⚡️ Speed up function sorter by 430,280%

[codeflash-ai-dev]

📄 430,280% (4,302.80x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 3.87 seconds → 898 microseconds (best of 664 runs)

⚡️ This change will improve the performance of the following benchmarks:

Benchmark File :: Function	Original Runtime	Expected New Runtime	Speedup
/Users/alvinryanputra/cf/codeflash/code_to_optimize/tests/pytest/benchmarks/test_benchmark_bubble_sort.py::test_sort	7.99 milliseconds	37.3 microseconds	21290.29%
/Users/alvinryanputra/cf/codeflash/code_to_optimize/tests/pytest/benchmarks/test_process_and_sort.py::test_compute_and_sort	19.1 milliseconds	10.9 milliseconds	74.44%
/Users/alvinryanputra/cf/codeflash/code_to_optimize/tests/pytest/benchmarks/test_process_and_sort.py::test_no_func	8.00 milliseconds	33.5 microseconds	23764.61%

🔻 This change will degrade the performance of the following benchmarks:

{benchmark_info_degraded}

📝 Explanation and details

Certainly! The given program uses a basic bubble sort algorithm with a time complexity of O(n^2). We can optimize the sorting process by using a more efficient sorting algorithm like Timsort, which is Python's built-in sorting algorithm. Timsort has a time complexity of O(n log n).

Here's the rewritten version of the program.

This code will sort the list much faster, especially on larger datasets. The built-in sort() method in Python is highly optimized and will provide better performance than the original bubble sort implementation.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 20 Passed
🌀 Generated Regression Tests	✅ 46 Passed
⏪ Replay Tests	✅ 2 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Existing Unit Tests Details

- benchmarks/codeflash_replay_tests/test_benchmark_bubble_sort__replay_test_0.py - benchmarks/codeflash_replay_tests/test_process_and_sort__replay_test_0.py - 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 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([-5]) def test_two_elements_list(): """Test sorting a list with two elements""" codeflash_output = sorter([2, 1]) codeflash_output = sorter([1, 2]) 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]) def test_reverse_sorted_list(): """Test sorting a reverse sorted list""" codeflash_output = sorter([5, 4, 3, 2, 1]) codeflash_output = sorter([3, 2, 1, 0, -1]) def test_all_elements_the_same(): """Test sorting a list where all elements are the same""" codeflash_output = sorter([1, 1, 1, 1, 1]) codeflash_output = sorter([0, 0, 0, 0]) def test_list_with_negative_numbers(): """Test sorting a list containing negative numbers""" codeflash_output = sorter([-1, -3, -2, 0, 1]) codeflash_output = sorter([-5, -4, -3, -2, -1]) def test_list_with_duplicates(): """Test sorting a list with duplicate elements""" codeflash_output = sorter([3, 1, 2, 3, 1]) codeflash_output = sorter([4, 5, 4, 5, 4]) def test_list_with_floating_point_numbers(): """Test sorting a list with floating point numbers""" codeflash_output = sorter([1.1, 2.2, 3.3, 2.2, 1.1]) codeflash_output = sorter([0.5, -1.1, 3.3, 2.2]) def test_mixed_positive_and_negative_numbers(): """Test sorting a list with both positive and negative numbers""" codeflash_output = sorter([3, -1, 2, -3, 0]) codeflash_output = sorter([-2, 4, 1, -5, 3]) def test_large_list(): """Test sorting a large list""" codeflash_output = sorter(list(range(1000, 0, -1))) codeflash_output = sorter(list(range(1000))) def test_performance_with_large_random_list(): """Test performance with a large list of random elements""" import random random_list = random.sample(range(1000), 1000) codeflash_output = sorter(random_list) def test_list_with_non_integer_numbers(): """Test sorting a list with non-integer numbers""" codeflash_output = sorter([1.5, 2.3, -0.7, 0.0, 3.3]) codeflash_output = sorter([0.1, 0.01, 0.001, 0.0001]) def test_list_with_large_numbers(): """Test sorting a list with very large numbers""" codeflash_output = sorter([10**10, 10**12, 10**11]) codeflash_output = sorter([10**15, 10**14, 10**13]) # 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 for an empty list def test_sorter_empty_list(): codeflash_output = sorter([]) # Test for a single element list def test_sorter_single_element(): codeflash_output = sorter([1]) # Test for a two elements list def test_sorter_two_elements(): codeflash_output = sorter([2, 1]) codeflash_output = sorter([1, 2]) # Test for a list with multiple elements def test_sorter_multiple_elements(): codeflash_output = sorter([3, 1, 2]) codeflash_output = sorter([1, 2, 3, 4, 5]) codeflash_output = sorter([5, 4, 3, 2, 1]) codeflash_output = sorter([3, 3, 2, 1, 2]) # Test for a list with negative numbers def test_sorter_negative_numbers(): codeflash_output = sorter([-1, -3, -2]) codeflash_output = sorter([-1, 2, -3, 4]) # Test for a large list def test_sorter_large_list(): codeflash_output = sorter(list(range(1000, 0, -1))) codeflash_output = sorter(list(range(1000))) # Test for a list with repeated elements def test_sorter_repeated_elements(): codeflash_output = sorter([1, 1, 1, 1]) codeflash_output = sorter([2, 3, 2, 3, 2, 3]) # Test for a list with large numbers def test_sorter_large_numbers(): codeflash_output = sorter([999999999, 1, -999999999]) # Test for a list with floating point numbers def test_sorter_floating_point_numbers(): codeflash_output = sorter([1.1, 1.01, 1.001]) codeflash_output = sorter([3.14, 2.71, 1.61]) # Test for a list with strings def test_sorter_strings(): codeflash_output = sorter(['banana', 'apple', 'cherry']) codeflash_output = sorter(['a', 'A']) # Test for a list with mixed data types def test_sorter_mixed_data_types(): with pytest.raises(TypeError): sorter([1, 'a', 2]) # 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-m8z6vhdi and push.