⚡️ Speed up function sorter by 84%

[codeflash-ai]

📄 84% (0.84x) speedup for sorter in code_to_optimize/bubble_sort_3.py

⏱️ Runtime : 933 milliseconds → 507 milliseconds (best of 18 runs)

📝 Explanation and details

Here’s an optimized version of your sorter function. The original is an unoptimized Bubble Sort, which is quite slow. A much faster way in Python is to use the built-in sort() or sorted() functions, but to stay true to the original intent (in-place sort, return the array, don't change function name/signature), I'll use that.

However, if you want to stay as close as possible to the original logic but make it much faster, you can.

1. Avoid repeated len(arr) calls by storing the length.
2. Notice that with each pass, the largest remaining item is at the end, so the inner loop can shrink.
3. Add early exit if no swaps occur (optimization for already nearly-sorted input).

Here's your function rewritten with those optimizations.

Explanation of optimizations:

• n = len(arr) stores length, saving recalculation.
• Inner loop does not consider elements already sorted at the end (n - i - 1).
• swapped flag allows breaking early if the array is sorted before all passes.
• Tuple swap is slightly faster and cleaner than using a temp variable.

If you require the absolute fastest sort, simply call arr.sort() and return arr. If not, this is the fastest idiomatic bubble sort.

Let me know if you want a solution that simply uses arr.sort() (which is based on Timsort and much faster for real data)!

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 52 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import random
import sys

# 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
    codeflash_output = sorter([]) # 1.33μs -> 1.33μs (0.301% faster)

def test_single_element_list():
    # Sorting a single-element list should return the same list
    codeflash_output = sorter([5]) # 1.40μs -> 1.57μs (10.9% slower)

def test_sorted_list():
    # Sorting an already sorted list should return the same list
    codeflash_output = sorter([1, 2, 3, 4, 5]) # 3.12μs -> 2.02μs (54.3% faster)

def test_reverse_sorted_list():
    # Sorting a reverse-sorted list should return a sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1]) # 3.79μs -> 3.52μs (7.59% faster)

def test_unsorted_list():
    # Sorting a randomly unsorted list should return a sorted list
    codeflash_output = sorter([3, 1, 4, 5, 2]) # 3.58μs -> 3.15μs (13.7% faster)

def test_list_with_duplicates():
    # Sorting a list with duplicate values should preserve duplicates in order
    codeflash_output = sorter([3, 1, 2, 3, 2]) # 3.54μs -> 3.03μs (16.7% faster)

def test_list_with_negative_numbers():
    # Sorting a list with negative and positive numbers
    codeflash_output = sorter([0, -1, 5, -10, 3]) # 3.94μs -> 3.61μs (9.03% faster)

def test_list_with_all_equal_elements():
    # Sorting a list where all elements are the same
    codeflash_output = sorter([7, 7, 7, 7]) # 2.47μs -> 1.88μs (31.6% faster)

def test_list_with_floats_and_integers():
    # Sorting a list with both floats and integers
    codeflash_output = sorter([3.5, 2, 1.1, 2.0]) # 3.79μs -> 3.56μs (6.40% faster)

# ---------------------------
# 2. EDGE TEST CASES
# ---------------------------

def test_list_with_large_and_small_numbers():
    # Sorting a list with very large and very small numbers
    arr = [sys.maxsize, -sys.maxsize - 1, 0, 999999999, -999999999]
    expected = [-sys.maxsize - 1, -999999999, 0, 999999999, sys.maxsize]
    codeflash_output = sorter(arr) # 4.37μs -> 3.85μs (13.5% faster)

def test_list_with_min_max_int():
    # Sorting a list with min and max int values
    arr = [0, -2147483648, 2147483647]
    expected = [-2147483648, 0, 2147483647]
    codeflash_output = sorter(arr) # 2.60μs -> 2.46μs (5.53% faster)

def test_list_with_nan_and_infinity():
    # Sorting a list with float('nan'), float('inf'), and float('-inf')
    arr = [float('nan'), 2, float('inf'), -3, float('-inf'), 0]
    # NaN is always placed at the end in Python's sorted(), so we mimic that
    sorted_arr = sorted(arr, key=lambda x: (isinstance(x, float) and (x != x), x))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.33μs -> 4.66μs (14.4% faster)

def test_list_with_strings_raises():
    # Sorting a list with non-comparable types (e.g., int and str) should raise TypeError
    arr = [1, "a", 3]
    with pytest.raises(TypeError):
        sorter(arr) # 3.27μs -> 3.23μs (1.11% faster)

def test_list_with_none_raises():
    # Sorting a list with None and numbers should raise TypeError
    arr = [None, 1, 2]
    with pytest.raises(TypeError):
        sorter(arr) # 3.13μs -> 3.24μs (3.39% slower)

def test_list_with_mutable_elements():
    # Sorting a list of lists should sort by first element of each sublist
    arr = [[3, 4], [1, 2], [2, 3]]
    expected = [[1, 2], [2, 3], [3, 4]]
    codeflash_output = sorter(arr) # 2.83μs -> 2.76μs (2.50% faster)

def test_list_with_empty_lists():
    # Sorting a list containing empty lists and non-empty lists
    arr = [[1], [], [0], []]
    expected = [[], [], [0], [1]]
    codeflash_output = sorter(arr) # 3.37μs -> 3.06μs (9.99% faster)

def test_list_with_boolean_values():
    # Sorting a list with booleans and integers (True==1, False==0)
    arr = [True, False, 2, 1]
    expected = [False, True, 1, 2]
    codeflash_output = sorter(arr) # 2.95μs -> 2.61μs (13.0% faster)

def test_list_is_sorted_in_place():
    # The function should mutate the input list in place
    arr = [3, 2, 1]
    codeflash_output = sorter(arr); result = codeflash_output # 2.50μs -> 2.60μs (3.73% slower)

def test_list_with_custom_objects_raises():
    # Sorting a list with objects that do not support comparison should raise TypeError
    class NoCompare:
        pass
    arr = [NoCompare(), NoCompare()]
    with pytest.raises(TypeError):
        sorter(arr) # 3.02μs -> 3.14μs (3.89% slower)

# ---------------------------
# 3. LARGE SCALE TEST CASES
# ---------------------------

def test_large_random_list():
    # Sorting a large list of random integers
    arr = [random.randint(-100000, 100000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 81.5ms -> 48.2ms (69.1% faster)

def test_large_sorted_list():
    # Sorting a large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()) # 58.8ms -> 59.8μs (98209% faster)

def test_large_reverse_sorted_list():
    # Sorting a large reverse sorted list
    arr = list(range(999, -1, -1))
    expected = list(range(1000))
    codeflash_output = sorter(arr.copy()) # 83.9ms -> 61.1ms (37.3% 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()) # 70.1ms -> 42.0ms (66.7% faster)

def test_large_list_with_floats():
    # Sorting a large list with floats and integers
    arr = [random.uniform(-1000, 1000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 77.5ms -> 47.1ms (64.6% faster)

def test_large_list_with_negatives_and_positives():
    # Sorting a large list with both negative and positive numbers
    arr = [random.randint(-1000000, 1000000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 80.6ms -> 48.9ms (64.9% 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
import string  # used for non-integer test cases
import sys  # used for maxsize/minsize edge cases

# 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([]) # 1.11μs -> 1.25μs (11.3% slower)

def test_sorter_single_element():
    # Test sorting a list with one element
    codeflash_output = sorter([42]) # 1.32μs -> 1.49μs (11.4% slower)

def test_sorter_sorted_list():
    # Test sorting an already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5]) # 2.71μs -> 1.84μs (47.3% faster)

def test_sorter_reverse_sorted_list():
    # Test sorting a reverse sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1]) # 3.45μs -> 3.27μs (5.47% faster)

def test_sorter_unsorted_list():
    # Test sorting a typical unsorted list
    codeflash_output = sorter([3, 1, 4, 5, 2]) # 3.14μs -> 3.00μs (4.49% faster)

def test_sorter_with_duplicates():
    # Test sorting a list with duplicate elements
    codeflash_output = sorter([4, 2, 5, 2, 3, 2]) # 3.70μs -> 3.29μs (12.4% faster)

def test_sorter_negative_numbers():
    # Test sorting a list with negative numbers
    codeflash_output = sorter([-1, -3, 2, 0, -2]) # 3.19μs -> 2.96μs (7.69% faster)

def test_sorter_mixed_positive_negative():
    # Test sorting a list with both positive and negative numbers
    codeflash_output = sorter([0, -10, 5, -7, 3]) # 3.51μs -> 3.26μs (7.79% faster)

def test_sorter_all_equal_elements():
    # Test sorting a list where all elements are equal
    codeflash_output = sorter([7, 7, 7, 7]) # 2.30μs -> 1.81μs (27.1% faster)

def test_sorter_two_elements_sorted():
    # Test sorting a two-element list that is already sorted
    codeflash_output = sorter([1, 2]) # 1.69μs -> 1.59μs (6.16% faster)

def test_sorter_two_elements_unsorted():
    # Test sorting a two-element list that is not sorted
    codeflash_output = sorter([2, 1]) # 1.89μs -> 2.08μs (9.04% slower)

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

def test_sorter_large_and_small_integers():
    # Test sorting a list with very large and very small integers
    arr = [sys.maxsize, -sys.maxsize - 1, 0, 1, -1]
    expected = [-sys.maxsize - 1, -1, 0, 1, sys.maxsize]
    codeflash_output = sorter(arr) # 4.05μs -> 3.65μs (11.1% faster)

def test_sorter_floats_and_integers():
    # Test sorting a list with floats and integers
    arr = [1.1, 2, 0.5, -3.2, 2.0]
    expected = [-3.2, 0.5, 1.1, 2, 2.0]
    codeflash_output = sorter(arr) # 4.49μs -> 4.09μs (9.78% faster)

def test_sorter_negative_zero():
    # Test sorting a list with -0.0 and 0.0
    arr = [-0.0, 0.0, 1, -1]
    # -0.0 == 0.0, but -1 < -0.0 == 0.0 < 1
    expected = [-1, -0.0, 0.0, 1]
    codeflash_output = sorter(arr); result = codeflash_output # 3.51μs -> 3.33μs (5.53% faster)

def test_sorter_strings():
    # Test sorting a list of strings
    arr = ["banana", "apple", "cherry"]
    expected = ["apple", "banana", "cherry"]
    codeflash_output = sorter(arr) # 2.46μs -> 2.52μs (2.50% slower)

def test_sorter_mixed_types_raises():
    # Test sorting a list with mixed types (should raise TypeError)
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        sorter(arr) # 3.10μs -> 3.32μs (6.71% slower)


def test_sorter_none_in_list_raises():
    # Test sorting a list containing None (should raise TypeError)
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        sorter(arr) # 3.63μs -> 3.81μs (4.82% slower)

def test_sorter_unicode_and_ascii_strings():
    # Test sorting strings with unicode and ascii
    arr = ["z", "ä", "a", "ü"]
    expected = ["a", "z", "ä", "ü"]  # Python sorts ASCII before unicode
    codeflash_output = sorter(arr) # 3.46μs -> 3.06μs (13.0% faster)

def test_sorter_boolean_values():
    # Test sorting a list of booleans (False < True)
    arr = [True, False, True, False]
    expected = [False, False, True, True]
    codeflash_output = sorter(arr) # 3.25μs -> 2.83μs (14.9% faster)

def test_sorter_large_identical_elements():
    # Test sorting a list with a large number of identical elements
    arr = [5] * 100
    expected = [5] * 100
    codeflash_output = sorter(arr) # 340μs -> 5.06μs (6628% faster)

def test_sorter_immutable_input():
    # Test that the function does not return a new list (sorts in-place)
    arr = [3, 1, 2]
    codeflash_output = sorter(arr); result = codeflash_output # 2.39μs -> 2.29μs (4.10% faster)

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

def test_sorter_large_random_list():
    # Test sorting a large list of random integers
    arr = [random.randint(-1000, 1000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 80.0ms -> 47.8ms (67.4% faster)

def test_sorter_large_sorted_list():
    # Test sorting a large already sorted list
    arr = list(range(1000))
    expected = list(range(1000))
    codeflash_output = sorter(arr.copy()) # 58.8ms -> 58.3μs (100813% faster)

def test_sorter_large_reverse_sorted_list():
    # Test sorting a large reverse sorted list
    arr = list(range(999, -1, -1))
    expected = list(range(1000))
    codeflash_output = sorter(arr.copy()) # 90.4ms -> 61.0ms (48.2% faster)

def test_sorter_large_duplicates():
    # Test 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()) # 72.6ms -> 42.4ms (71.2% faster)

def test_sorter_large_floats():
    # Test sorting a large list of floats
    arr = [random.uniform(-1e6, 1e6) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 77.5ms -> 47.7ms (62.5% faster)

def test_sorter_large_strings():
    # Test sorting a large list of random lowercase strings
    arr = [''.join(random.choices(string.ascii_lowercase, k=5)) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 100ms -> 60.6ms (66.4% 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-md8wfltw and push.