⚡️ Speed up function sorter by 223,402%

[codeflash-ai]

📄 223,402% (2,234.02x) speedup for sorter in code_to_optimize/bubble_sort_3.py

⏱️ Runtime : 934 milliseconds → 418 microseconds (best of 184 runs)

📝 Explanation and details

Here's an optimized version of your code.

Major improvements.

• Use Python built-in sort: The original code is an unoptimized bubble sort (O(n^2)), while Python's built-in sort runs in O(n log n) and is highly optimized in C.
• If you must keep the in-place sorting and returning of arr, just use arr.sort().
• All variable swapping is handled internally by Python efficiently.

If you want to keep a manual fast sort (like quicksort), consider.

Why this is faster.

• Removes unnecessary Python for-loops and variable swaps.
• Built-ins leverage C speed and tim-sort algorithm.
• Behavior is identical: sorts arr in-place and returns it.

---

If you need a manual algorithm for educational purposes (not recommended for production), I can provide a fast implementation (e.g., using quicksort or heapsort), but for 99% of use cases, the above is best for speed and memory!

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 47 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import random  # used for generating large random test cases
import string  # used for string sorting tests
import sys  # used for edge cases with sys.maxsize

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort_3 import sorter

# unit tests

# ---------------------------
# 1. Basic Test Cases
# ---------------------------

def test_sorter_empty_list():
    # Test sorting an empty list
    codeflash_output = sorter([]) # 1.21μs -> 478ns (153% faster)

def test_sorter_single_element():
    # Test sorting a list with one element
    codeflash_output = sorter([42]) # 1.33μs -> 465ns (187% faster)

def test_sorter_already_sorted():
    # Test sorting an already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5]) # 2.67μs -> 594ns (350% faster)

def test_sorter_reverse_sorted():
    # Test sorting a reverse-sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1]) # 3.49μs -> 619ns (463% faster)

def test_sorter_duplicates():
    # Test sorting a list with duplicate elements
    codeflash_output = sorter([2, 3, 2, 1, 3]) # 3.13μs -> 681ns (359% faster)

def test_sorter_negative_numbers():
    # Test sorting a list with negative numbers
    codeflash_output = sorter([-3, -1, -2, 0, 2]) # 2.89μs -> 678ns (326% faster)

def test_sorter_mixed_sign_numbers():
    # Test sorting a list with both positive and negative numbers
    codeflash_output = sorter([0, -1, 3, -2, 2]) # 3.11μs -> 718ns (333% faster)

def test_sorter_floats():
    # Test sorting a list with floats
    codeflash_output = sorter([3.1, 2.4, 5.6, 1.1]) # 3.07μs -> 863ns (256% faster)

def test_sorter_mixed_ints_and_floats():
    # Test sorting a list with a mix of ints and floats
    codeflash_output = sorter([3, 2.5, 1, 4.0]) # 3.61μs -> 1.03μs (252% faster)

def test_sorter_strings():
    # Test sorting a list of strings
    codeflash_output = sorter(["banana", "apple", "cherry"]) # 2.68μs -> 626ns (329% faster)

# ---------------------------
# 2. Edge Test Cases
# ---------------------------

def test_sorter_all_equal_elements():
    # Test sorting a list where all elements are the same
    codeflash_output = sorter([7, 7, 7, 7]) # 2.42μs -> 575ns (320% faster)

def test_sorter_two_elements_sorted():
    # Test sorting a two-element list that is already sorted
    codeflash_output = sorter([1, 2]) # 1.59μs -> 530ns (201% faster)

def test_sorter_two_elements_unsorted():
    # Test sorting a two-element list that is not sorted
    codeflash_output = sorter([2, 1]) # 1.81μs -> 553ns (228% faster)

def test_sorter_large_and_small_numbers():
    # Test sorting with very large and very small numbers
    arr = [sys.maxsize, -sys.maxsize - 1, 0, 999999, -999999]
    expected = sorted(arr)
    codeflash_output = sorter(arr) # 4.36μs -> 660ns (561% faster)

def test_sorter_unicode_strings():
    # Test sorting a list of unicode strings
    arr = ["éclair", "apple", "Éclair", "banana"]
    expected = sorted(arr)
    codeflash_output = sorter(arr) # 3.64μs -> 654ns (456% faster)

def test_sorter_empty_strings():
    # Test sorting a list with empty strings
    arr = ["", "a", "", "b"]
    expected = sorted(arr)
    codeflash_output = sorter(arr) # 2.90μs -> 590ns (392% faster)


def test_sorter_mixed_types():
    # Test sorting a list with mixed types (should raise TypeError)
    arr = [1, "two", 3]
    with pytest.raises(TypeError):
        sorter(arr) # 3.19μs -> 2.24μs (42.9% faster)

def test_sorter_none_in_list():
    # Test sorting a list with None (should raise TypeError)
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        sorter(arr) # 3.31μs -> 2.25μs (47.4% faster)

def test_sorter_large_negative_and_positive():
    # Test sorting with large negative and positive numbers
    arr = [10**10, -10**10, 0]
    expected = sorted(arr)
    codeflash_output = sorter(arr) # 2.77μs -> 610ns (354% faster)

# ---------------------------
# 3. Large Scale Test Cases
# ---------------------------

def test_sorter_large_random_ints():
    # Test sorting a large list of random integers
    arr = random.sample(range(-10000, -9000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 78.3ms -> 65.7μs (119047% faster)

def test_sorter_large_duplicates():
    # Test sorting a large list with many duplicate elements
    arr = [5] * 500 + [3] * 300 + [7] * 200
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 62.9ms -> 3.70μs (1700690% faster)

def test_sorter_large_sorted():
    # Test sorting a large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()) # 56.9ms -> 3.13μs (1814298% faster)

def test_sorter_large_reverse_sorted():
    # Test sorting a large reverse sorted list
    arr = list(range(999, -1, -1))
    expected = list(range(1000))
    codeflash_output = sorter(arr.copy()) # 88.6ms -> 3.98μs (2224820% faster)

def test_sorter_large_random_floats():
    # Test sorting a large list of random floats
    arr = [random.uniform(-1e6, 1e6) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 72.9ms -> 71.1μs (102556% faster)

def test_sorter_large_strings():
    # Test sorting a large list of random strings
    arr = [
        ''.join(random.choices(string.ascii_letters, k=10))
        for _ in range(1000)
    ]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 94.2ms -> 110μs (85302% faster)

def test_sorter_large_all_equal():
    # Test sorting a large list where all elements are the same
    arr = [42] * 1000
    codeflash_output = sorter(arr.copy()) # 55.4ms -> 2.94μs (1884690% faster)

def test_sorter_large_alternating():
    # Test sorting a large list with alternating values
    arr = [0, 1] * 500
    expected = [0] * 500 + [1] * 500
    codeflash_output = sorter(arr.copy()) # 62.2ms -> 14.9μs (417058% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import random  # used for generating large random lists

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort_3 import sorter

# unit tests

# ---------------------------
# 1. Basic Test Cases
# ---------------------------

def test_empty_list():
    # Sorting an empty list should return an empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 1.26μs -> 482ns (161% faster)

def test_single_element_list():
    # Sorting a list with one element should return the same list
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 1.35μs -> 460ns (193% faster)

def test_already_sorted():
    # Sorting an already sorted list should return the same list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 2.76μs -> 556ns (396% faster)

def test_reverse_sorted():
    # Sorting a reverse sorted list
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.46μs -> 615ns (462% faster)

def test_unsorted_with_duplicates():
    # Sorting a list with duplicates
    arr = [3, 1, 2, 3, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.26μs -> 667ns (389% faster)

def test_negative_numbers():
    # Sorting a list with negative numbers
    arr = [0, -1, 3, -2, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.42μs -> 663ns (416% faster)

def test_all_equal_elements():
    # Sorting a list where all elements are equal
    arr = [7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 2.34μs -> 565ns (315% faster)

# ---------------------------
# 2. Edge Test Cases
# ---------------------------

def test_large_negative_and_positive():
    # Sorting list with large negative and positive numbers
    arr = [999999, -999999, 0, 123, -456]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.15μs -> 685ns (505% faster)

def test_alternating_high_low():
    # Sorting a list with alternating high and low values
    arr = [10, 1, 9, 2, 8, 3, 7, 4]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.43μs -> 708ns (668% faster)

def test_sorted_with_negatives_and_duplicates():
    # Sorted list with negatives and duplicates
    arr = [-3, -2, -2, 0, 1, 1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.84μs -> 562ns (583% faster)

def test_floats_and_integers():
    # Sorting a list with floats and integers
    arr = [3.2, 1, 2.5, 3, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.97μs -> 1.40μs (256% faster)

def test_minimum_and_maximum_int():
    # Sorting with Python's min and max integer values
    arr = [-(2**63), 0, 2**63 - 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 2.55μs -> 729ns (249% faster)

def test_mutation_of_input():
    # Ensure the function mutates the input list (bubble sort in-place)
    arr = [2, 1]
    sorter(arr) # 1.92μs -> 580ns (231% faster)

def test_non_integer_types():
    # Sorting a list with strings should raise TypeError
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        sorter(arr.copy()) # 3.42μs -> 2.23μs (52.9% faster)

def test_none_in_list():
    # Sorting a list with None should raise TypeError
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        sorter(arr.copy()) # 3.48μs -> 2.23μs (56.1% faster)

# ---------------------------
# 3. Large Scale Test Cases
# ---------------------------

def test_large_sorted_list():
    # Sorting a large already sorted list (performance and correctness)
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 57.4ms -> 3.19μs (1800907% faster)

def test_large_reverse_sorted_list():
    # Sorting a large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 90.8ms -> 3.95μs (2300927% faster)

def test_large_random_list():
    # Sorting a large random list
    arr = [random.randint(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 86.9ms -> 65.4μs (132828% faster)

def test_large_list_with_duplicates():
    # Sorting a large list with many duplicates
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 73.0ms -> 37.9μs (192345% faster)

def test_large_list_all_same_element():
    # Sorting a large list where all elements are the same
    arr = [7] * 1000
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 53.9ms -> 3.00μs (1795889% faster)
# 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-md0disqt and push.