⚡️ Speed up function sorter by 394,270%

[codeflash-ai]

📄 394,270% (3,942.70x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 3.58 seconds → 908 microseconds (best of 521 runs)

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

Benchmark File :: Function	Original Runtime	Expected New Runtime	Speedup
code_to_optimize.tests.pytest.benchmarks.test_benchmark_bubble_sort::test_sort	8.30 milliseconds	32.3 microseconds	25570.27%
code_to_optimize.tests.pytest.benchmarks.test_process_and_sort::test_compute_and_sort	18.8 milliseconds	10.8 milliseconds	74.45%
code_to_optimize.tests.pytest.benchmarks.test_process_and_sort::test_no_func	8.07 milliseconds	31.0 microseconds	25931.99%

📝 Explanation and details

The given code implements the Bubble Sort algorithm, which has a time complexity of O(n^2). We can optimize the sorting by using the built-in sort function in Python, which implements Timsort—a hybrid sorting algorithm derived from merge sort and insertion sort with a time complexity of O(n log n).

Here's the optimized version of the program.

The built-in sort method will provide a significant performance boost for large lists compared to the original bubble sort implementation. The functionality and output remain the same, but the efficiency is greatly improved.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 20 Passed
🌀 Generated Regression Tests	✅ 73 Passed
⏪ Replay Tests	✅ 2 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Existing Unit Tests Details

- benchmarks/codeflash_replay_tests_d14m3nr_/test_code_to_optimize_tests_pytest_benchmarks_test_benchmark_bubble_sort__replay_test_0.py - benchmarks/codeflash_replay_tests_d14m3nr_/test_code_to_optimize_tests_pytest_benchmarks_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 # Test empty list def test_empty_list(): codeflash_output = sorter([]) # Test single element list def test_single_element_list(): codeflash_output = sorter([1]) codeflash_output = sorter(['a']) # Test two elements list def test_two_elements_list(): codeflash_output = sorter([2, 1]) codeflash_output = sorter([1, 2]) codeflash_output = sorter(['b', 'a']) codeflash_output = sorter(['a', 'b']) # Test already sorted list def test_already_sorted_list(): codeflash_output = sorter([1, 2, 3, 4, 5]) codeflash_output = sorter(['a', 'b', 'c', 'd']) # Test reverse sorted list def test_reverse_sorted_list(): codeflash_output = sorter([5, 4, 3, 2, 1]) codeflash_output = sorter(['d', 'c', 'b', 'a']) # Test all elements are the same def test_all_elements_same(): codeflash_output = sorter([1, 1, 1, 1]) codeflash_output = sorter(['a', 'a', 'a']) # Test list with negative numbers def test_negative_numbers(): codeflash_output = sorter([-1, -3, -2, 0, 2, 1]) codeflash_output = sorter([-5, -4, -3, -2, -1]) # Test list with mixed positive and negative numbers def test_mixed_positive_negative(): codeflash_output = sorter([3, -1, 2, -3, 0]) codeflash_output = sorter([-2, 4, -1, 3, -3]) # Test list with floats def test_floats(): codeflash_output = sorter([1.1, 2.2, 0.5, 3.3, 2.1]) codeflash_output = sorter([-1.1, -0.5, 0.0, 0.5, 1.1]) # Test list with duplicate elements def test_duplicates(): codeflash_output = sorter([3, 1, 2, 1, 3, 2]) codeflash_output = sorter(['b', 'a', 'b', 'a']) # Test list with strings of different lengths def test_strings_different_lengths(): codeflash_output = sorter(['apple', 'banana', 'cherry', 'date']) codeflash_output = sorter(['a', 'aaa', 'aa', 'aaaa']) # Test list with special characters def test_special_characters(): codeflash_output = sorter(['!', '@', '#', ', '%']) codeflash_output = sorter(['a', '!', 'b', '@', 'c', '#']) # Test list with Unicode characters def test_unicode_characters(): codeflash_output = sorter(['é', 'è', 'ê', 'ë']) codeflash_output = sorter(['α', 'β', 'γ', 'δ']) # Test large list def test_large_list(): codeflash_output = sorter(list(range(1000, 0, -1))) codeflash_output = sorter(list(range(1000))) # 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_unsorted_list_with_distinct_elements(): # Test sorting an unsorted list with distinct elements codeflash_output = sorter([3, 1, 4, 5, 2]) codeflash_output = sorter(['b', 'd', 'a', 'c']) def test_list_with_duplicate_elements(): # Test sorting a list with duplicate elements codeflash_output = sorter([3, 1, 2, 3, 2]) codeflash_output = sorter(['b', 'a', 'c', 'a']) def test_list_with_all_identical_elements(): # Test sorting a list with all identical elements codeflash_output = sorter([2, 2, 2, 2, 2]) 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, 4, -5, 2]) codeflash_output = sorter([-3, -1, -4, -2]) def test_list_with_mixed_positive_and_negative_numbers(): # Test sorting a list with mixed positive and negative numbers codeflash_output = sorter([3, -1, 4, -5, 2, 0]) codeflash_output = sorter([-3, 1, -4, 2]) def test_list_with_floating_point_numbers(): # Test sorting a list with floating point numbers codeflash_output = sorter([3.1, 2.4, 1.5, 4.6, 3.3]) codeflash_output = sorter([1.1, -2.2, 3.3, -4.4]) def test_list_with_mixed_integers_and_floats(): # Test sorting a list with mixed integers and floating point numbers codeflash_output = sorter([3, 2.4, 1, 4.6, 3.3]) codeflash_output = sorter([1.1, 2, 3.3, 4]) def test_list_with_strings_of_different_lengths(): # Test sorting a list with strings of different lengths codeflash_output = sorter(["apple", "banana", "cherry", "date"]) codeflash_output = sorter(["a", "abc", "ab", "abcd"]) def test_large_list(): # Test sorting a large list large_list = list(range(1000, 0, -1)) sorted_large_list = list(range(1, 1001)) codeflash_output = sorter(large_list) def test_list_with_none_values(): # Test sorting a list with None values (should raise TypeError) with pytest.raises(TypeError): sorter([3, None, 2]) with pytest.raises(TypeError): sorter([None, None, 1]) 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', 3.0]) with pytest.raises(TypeError): sorter(['a', None, 2]) 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]) with pytest.raises(TypeError): sorter([['a', 'b'], 'c', 'd']) def test_list_with_special_characters(): # Test sorting a list with special characters codeflash_output = sorter(['a', '!', 'b', '@']) codeflash_output = sorter(['#', ', '%', '&']) def test_list_with_unicode_characters(): # Test sorting a list with unicode characters codeflash_output = sorter(['a', 'á', 'b', 'ç']) codeflash_output = sorter(['你', '好', '世', '界']) def test_list_with_boolean_values(): # Test sorting a list with boolean values codeflash_output = sorter([True, False, True]) codeflash_output = sorter([1, True, 0, False]) def test_list_with_large_integers(): # Test sorting a list with large integers codeflash_output = sorter([12345678901234567890, 98765432109876543210, 1234567890123456789]) codeflash_output = sorter([99999999999999999999, 10000000000000000000, 88888888888888888888]) def test_list_with_special_floating_point_values(): # Test sorting a list with special floating point values codeflash_output = sorter([1.0, float('inf'), 2.0, float('-inf')]) # Note: NaN values are not ordered, so the result may vary codeflash_output = sorter([float('nan'), 1.0, 2.0]) def test_list_with_repeated_patterns(): # Test sorting a list with repeated patterns codeflash_output = sorter([1, 2, 1, 2, 1, 2]) codeflash_output = sorter(['a', 'b', 'a', 'b', 'a', 'b']) def test_list_with_large_number_of_identical_elements(): # Test sorting a list with a large number of identical elements codeflash_output = sorter([1] * 1000) codeflash_output = sorter(['a'] * 1000) # 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-m9d82u44 and push.