⚡️ Speed up function sorter by 234,232% in bubble_sort.py

[codeflash-ai]

📄 sorter() in bubble_sort.py

📈 Performance improved by 234,232% (2,342.32x faster)

⏱️ Runtime went down from 92.2 milliseconds to 39.3 microseconds (best of 1178 runs)

Explanation and details

Certainly! The provided code is an implementation of the bubble sort algorithm, which is not the most efficient sorting method. A more efficient and faster approach is to use Python's built-in sort() method or the sorted() function, which implement Timsort. This algorithm has an average and worst-case time complexity of O(n log n).

Here's the optimized version.

This should significantly increase the speed of sorting compared to the original bubble sort implementation.

Correctness verification

The new optimized code was tested for correctness. The results are listed below.

🔘 (none found) − ⚙️ Existing Unit Tests

✅ 37 Passed − 🌀 Generated Regression Tests

(click to show generated tests)

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

# unit tests

def test_sorted_list():
    # Test already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5])
    # Outputs were verified to be equal to the original implementation

def test_reverse_sorted_list():
    # Test reverse sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1])
    # Outputs were verified to be equal to the original implementation

def test_unsorted_list():
    # Test unsorted list
    codeflash_output = sorter([3, 1, 4, 5, 2])
    # Outputs were verified to be equal to the original implementation

def test_empty_list():
    # Test empty list
    codeflash_output = sorter([])
    # Outputs were verified to be equal to the original implementation

def test_single_element_list():
    # Test single element list
    codeflash_output = sorter([42])
    # Outputs were verified to be equal to the original implementation

def test_all_elements_equal():
    # Test list where all elements are equal
    codeflash_output = sorter([7, 7, 7, 7])
    # Outputs were verified to be equal to the original implementation

def test_negative_numbers():
    # Test list with negative numbers
    codeflash_output = sorter([-1, -3, -2, -5, -4])
    # Outputs were verified to be equal to the original implementation

def test_mixed_positive_negative_numbers():
    # Test list with mixed positive and negative numbers
    codeflash_output = sorter([-1, 2, -3, 4, 0])
    # Outputs were verified to be equal to the original implementation

def test_large_list():
    # Test large list for performance
    large_list = list(range(10000, 9000, -1))
    codeflash_output = sorter(large_list)
    # Outputs were verified to be equal to the original implementation

def test_floating_point_numbers():
    # Test list with floating point numbers
    codeflash_output = sorter([3.1, 2.4, 5.6, 4.2])
    # Outputs were verified to be equal to the original implementation

def test_strings():
    # Test list with strings
    codeflash_output = sorter(['banana', 'apple', 'cherry'])
    # Outputs were verified to be equal to the original implementation

def test_non_comparable_elements():
    # Test list with non-comparable elements
    with pytest.raises(TypeError):
        sorter([1, 'two', 3])
    # Outputs were verified to be equal to the original implementation

def test_performance_with_sorted_list():
    # Test performance with already sorted list
    sorted_list = list(range(1000))
    codeflash_output = sorter(sorted_list)
    # Outputs were verified to be equal to the original implementation

def test_stability_with_duplicates():
    # Test stability with duplicate elements
    codeflash_output = sorter([3, 1, 2, 3, 2])
    # Outputs were verified to be equal to the original implementation
import pytest  # used for our unit tests
from bubble_sort import sorter

# unit tests

def test_already_sorted():
    # Test with an already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter([10, 20, 30, 40, 50])
    # Outputs were verified to be equal to the original implementation

def test_reverse_sorted():
    # Test with a reverse sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1])
    codeflash_output = sorter([50, 40, 30, 20, 10])
    # Outputs were verified to be equal to the original implementation

def test_unsorted():
    # Test with an unsorted list
    codeflash_output = sorter([3, 1, 4, 5, 2])
    codeflash_output = sorter([10, 5, 20, 15, 30])
    # Outputs were verified to be equal to the original implementation

def test_empty_list():
    # Test with an empty list
    codeflash_output = sorter([])
    # Outputs were verified to be equal to the original implementation

def test_single_element():
    # Test with a single element list
    codeflash_output = sorter([1])
    codeflash_output = sorter([100])
    # Outputs were verified to be equal to the original implementation

def test_duplicates():
    # Test with a list with duplicate elements
    codeflash_output = sorter([2, 3, 2, 1, 3])
    codeflash_output = sorter([5, 5, 5, 5, 5])
    # Outputs were verified to be equal to the original implementation

def test_negative_numbers():
    # Test with a list containing negative numbers
    codeflash_output = sorter([-1, -3, -2, -5, -4])
    codeflash_output = sorter([-10, 0, 10, -20, 20])
    # Outputs were verified to be equal to the original implementation

def test_mixed_positive_negative():
    # Test with a list containing both positive and negative numbers
    codeflash_output = sorter([-1, 3, -2, 5, -4])
    codeflash_output = sorter([10, -10, 20, -20, 0])
    # Outputs were verified to be equal to the original implementation

def test_large_random_list():
    # Test with a large list of random elements
    import random
    random.seed(0)  # Ensure reproducibility
    large_list = random.sample(range(1000), 1000)
    codeflash_output = sorter(large_list)
    # Outputs were verified to be equal to the original implementation

def test_large_identical_elements():
    # Test with a large list of identical elements
    large_identical = [1] * 1000
    codeflash_output = sorter(large_identical)
    # Outputs were verified to be equal to the original implementation

def test_floating_point_numbers():
    # Test with a list containing floating point numbers
    codeflash_output = sorter([1.1, 2.2, 0.5, 3.3, 2.1])
    codeflash_output = sorter([5.5, 3.3, 4.4, 1.1, 2.2])
    # Outputs were verified to be equal to the original implementation

def test_strings():
    # Test with a list of strings
    codeflash_output = sorter(["apple", "banana", "cherry", "date"])
    codeflash_output = sorter(["zebra", "yak", "xenon", "walrus"])
    # Outputs were verified to be equal to the original implementation

def test_consistent_sorting():
    # Test to ensure sorting is consistent
    lst = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
    codeflash_output = sorter(lst)
    codeflash_output = sorter(lst)
    codeflash_output = sorter(sorted_lst)
    # Outputs were verified to be equal to the original implementation

🔘 (none found) − ⏪ Replay Tests