⚡️ Speed up function sorter by 63%

[codeflash-ai]

📄 63% (0.63x) speedup for sorter in codeflash/bubble_sort.py

⏱️ Runtime : 1.21 seconds → 740 milliseconds (best of 13 runs)

📝 Explanation and details

Here is an optimized version of your function that preserves existing function signature and output. The current implementation uses Bubble Sort, which is O(n^2).
We can make multiple optimizations.

• Use Python's built-in sort for a drastic speedup (Timsort, O(n log n) in practice).
• Retain the print behavior.

Here's the rewritten code.

This will dramatically reduce runtime and memory overhead, since.

• It avoids unnecessary nested loops and swaps.
• Uses highly optimized C code underneath.

Note: If you must keep the swap logic for pedagogical reasons (Bubble Sort), you can still optimize.

• Break early if no swaps were made in a pass (best-case O(n)).
• Decrease inner loop boundary each pass.

Improved Bubble Sort.

Recommendation: Use the first (built-in) version for speed; use the improved bubble sort only if you have a reason not to use .sort().

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 57 Passed
⏪ Replay Tests	✅ 3 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import random  # used for generating large random lists
import string  # used for string sorting tests

# imports
import pytest  # used for our unit tests
from codeflash.bubble_sort import sorter

# unit tests

# -----------------
# BASIC TEST CASES
# -----------------

def test_sorter_empty_list():
    # Test sorting an empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.88μs -> 3.83μs (1.07% faster)

def test_sorter_single_element():
    # Test sorting a single-element list
    arr = [5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.92μs -> 3.75μs (4.45% faster)

def test_sorter_sorted_list():
    # Test sorting an already sorted list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.46μs -> 3.79μs (17.6% faster)

def test_sorter_reverse_sorted_list():
    # Test sorting a reverse sorted list
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.96μs -> 4.79μs (3.49% faster)

def test_sorter_unsorted_list():
    # Test sorting a typical unsorted list
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.88μs -> 4.42μs (10.4% faster)

def test_sorter_with_duplicates():
    # Test sorting a list with duplicate values
    arr = [4, 2, 5, 2, 3, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.17μs -> 4.79μs (7.83% faster)

def test_sorter_negative_numbers():
    # Test sorting a list with negative numbers
    arr = [0, -1, 3, -2, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.83μs -> 4.67μs (3.56% faster)

def test_sorter_floats():
    # Test sorting a list with floating point numbers
    arr = [1.1, 3.3, 2.2, -1.1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.54μs -> 5.38μs (3.09% faster)

def test_sorter_strings():
    # Test sorting a list of strings
    arr = ["banana", "apple", "cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.58μs -> 4.62μs (0.908% slower)

def test_sorter_mixed_case_strings():
    # Test sorting a list of strings with mixed case
    arr = ["banana", "Apple", "cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.38μs -> 4.21μs (3.94% faster)

# -----------------
# EDGE TEST CASES
# -----------------

def test_sorter_all_equal_elements():
    # Test sorting a list where all elements are the same
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.58μs -> 3.88μs (18.3% faster)

def test_sorter_two_elements_sorted():
    # Test sorting a two-element list already sorted
    arr = [1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.75μs -> 3.71μs (1.11% faster)

def test_sorter_two_elements_unsorted():
    # Test sorting a two-element list in reverse order
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.92μs -> 3.50μs (11.9% faster)

def test_sorter_large_negative_and_positive():
    # Test sorting a list with large negative and positive numbers
    arr = [999999, -999999, 0, 123456, -123456]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.62μs -> 5.00μs (12.5% faster)

def test_sorter_empty_strings():
    # Test sorting a list with empty strings
    arr = ["", "a", "b", ""]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.92μs -> 4.42μs (11.3% faster)

def test_sorter_unicode_strings():
    # Test sorting a list with unicode strings
    arr = ["éclair", "apple", "Éclair", "banana"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.75μs -> 5.25μs (9.52% faster)

def test_sorter_mutation():
    # Test that the input list is mutated (in-place sort)
    arr = [3, 2, 1]
    arr_copy = arr.copy()
    codeflash_output = sorter(arr); result = codeflash_output # 4.33μs -> 3.83μs (13.1% faster)

def test_sorter_type_error_on_incomparable():
    # Test sorting a list with incomparable types raises TypeError
    arr = [1, "two", 3]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_boolean_values():
    # Test sorting a list with boolean values
    arr = [True, False, True]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.33μs -> 4.33μs (0.000% faster)

def test_sorter_none_in_list():
    # Test sorting a list with None and numbers (should raise TypeError)
    arr = [None, 1, 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

# -----------------
# LARGE SCALE TEST CASES
# -----------------

def test_sorter_large_sorted_list():
    # Test sorting a large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 18.2ms -> 51.5μs (35211% faster)

def test_sorter_large_reverse_sorted_list():
    # Test sorting a large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 30.4ms -> 19.5ms (55.7% faster)

def test_sorter_large_random_integers():
    # Test sorting a large list of random integers
    arr = [random.randint(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 27.8ms -> 16.1ms (72.3% faster)

def test_sorter_large_random_floats():
    # Test sorting a large list of random floats
    arr = [random.uniform(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 27.3ms -> 15.8ms (73.1% faster)

def test_sorter_large_strings():
    # Test sorting a large list of random strings
    arr = [
        ''.join(random.choices(string.ascii_letters + string.digits, k=10))
        for _ in range(1000)
    ]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 29.3ms -> 17.4ms (68.9% 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()); result = codeflash_output # 24.6ms -> 14.2ms (73.9% faster)

def test_sorter_large_all_equal():
    # Test sorting a large list where all elements are equal
    arr = [42] * 1000
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 17.9ms -> 49.5μs (36096% faster)

def test_sorter_large_alternating():
    # Test sorting a large list with two alternating values
    arr = [0, 1] * 500
    expected = [0]*500 + [1]*500
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 21.3ms -> 9.62ms (122% 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 string sorting tests
import sys  # for maxsize edge case

# imports
import pytest  # used for our unit tests
from codeflash.bubble_sort import sorter

# unit tests

# --------------------------
# BASIC TEST CASES
# --------------------------

def test_empty_list():
    # Sorting an empty list should return an empty list
    codeflash_output = sorter([]) # 3.67μs -> 3.50μs (4.77% faster)

def test_single_element():
    # Sorting a list with one element should return the same list
    codeflash_output = sorter([42]) # 3.75μs -> 3.92μs (4.26% slower)

def test_sorted_list():
    # A list already sorted should remain unchanged
    codeflash_output = sorter([1, 2, 3, 4, 5]) # 4.46μs -> 3.96μs (12.6% faster)

def test_reverse_sorted_list():
    # A reverse-sorted list should be sorted in ascending order
    codeflash_output = sorter([5, 4, 3, 2, 1]) # 4.96μs -> 4.62μs (7.22% faster)

def test_unsorted_list():
    # A typical unsorted list should be sorted correctly
    codeflash_output = sorter([3, 1, 4, 5, 2]) # 4.71μs -> 4.04μs (16.5% faster)

def test_list_with_duplicates():
    # List with duplicate elements should sort all elements
    codeflash_output = sorter([2, 3, 2, 1, 4, 1]) # 5.25μs -> 4.21μs (24.7% faster)

def test_list_with_negative_numbers():
    # List with negative and positive numbers
    codeflash_output = sorter([-3, 1, 0, -1, 2]) # 4.75μs -> 4.08μs (16.3% faster)

def test_list_with_floats():
    # List with floats and integers
    codeflash_output = sorter([2.2, 1.1, 3.3, 2, 1]) # 6.08μs -> 5.79μs (5.04% faster)

def test_list_with_strings():
    # List of strings should be sorted lexicographically
    codeflash_output = sorter(['banana', 'apple', 'cherry']) # 4.25μs -> 4.42μs (3.78% slower)

def test_list_with_booleans():
    # List with booleans should treat False < True
    codeflash_output = sorter([True, False, True, False]) # 4.42μs -> 4.46μs (0.964% slower)

# --------------------------
# EDGE TEST CASES
# --------------------------

def test_list_with_all_equal_elements():
    # List where all elements are equal should remain unchanged
    codeflash_output = sorter([7, 7, 7, 7]) # 3.71μs -> 3.79μs (2.19% slower)

def test_list_with_max_and_min_int():
    # List containing sys.maxsize and -sys.maxsize-1
    arr = [0, sys.maxsize, -sys.maxsize-1, 42]
    codeflash_output = sorter(arr) # 5.29μs -> 5.25μs (0.800% faster)

def test_list_with_mixed_numeric_types():
    # List with ints, floats, and bools (all comparable in Python)
    arr = [True, 3, 2.5, False, 1]
    codeflash_output = sorter(arr) # 6.33μs -> 5.75μs (10.1% faster)

def test_list_with_unicode_strings():
    # List with unicode strings should sort by codepoint order
    arr = ['éclair', 'apple', 'Éclair', 'banana']
    codeflash_output = sorter(arr) # 5.54μs -> 5.12μs (8.14% faster)

def test_list_with_empty_strings():
    # List with empty strings and normal strings
    arr = ['', 'a', 'abc', '', 'b']
    codeflash_output = sorter(arr) # 4.92μs -> 4.79μs (2.63% faster)

def test_list_with_non_comparable_elements():
    # List with elements that can't be compared should raise TypeError
    arr = [1, 'a', 2]
    with pytest.raises(TypeError):
        sorter(arr)

def test_list_with_none():
    # List with None and numbers should raise TypeError
    arr = [None, 1, 2]
    with pytest.raises(TypeError):
        sorter(arr)

def test_input_is_not_a_list():
    # Passing a non-list should raise TypeError
    with pytest.raises(TypeError):
        sorter("not a list") # 2.38μs -> 2.04μs (16.3% faster)
    with pytest.raises(TypeError):
        sorter(123)
    with pytest.raises(TypeError):
        sorter({1, 2, 3})


def test_large_numbers():
    # List with very large and very small numbers
    arr = [10**100, -10**100, 0, 999999999, -999999999]
    codeflash_output = sorter(arr) # 6.92μs -> 6.17μs (12.1% faster)

# --------------------------
# LARGE SCALE TEST CASES
# --------------------------

def test_large_random_list():
    # Sorting a large list of random integers
    arr = [random.randint(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 28.2ms -> 16.2ms (74.1% faster)

def test_large_sorted_list():
    # Sorting a large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()) # 18.5ms -> 51.1μs (36089% 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()) # 31.0ms -> 19.6ms (58.0% faster)

def test_large_list_with_duplicates():
    # 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()) # 24.7ms -> 13.9ms (77.5% faster)

def test_large_list_of_strings():
    # Large list of random strings
    arr = [
        ''.join(random.choices(string.ascii_letters, k=5))
        for _ in range(1000)
    ]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 29.7ms -> 17.6ms (69.3% faster)

def test_large_list_with_floats():
    # Large list of random floats
    arr = [random.uniform(-1000, 1000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 27.3ms -> 15.9ms (71.7% faster)

def test_large_list_with_negatives_and_zeros():
    # Large list with negative numbers, zeros, and positives
    arr = [random.randint(-500, 500) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 29.2ms -> 17.7ms (65.0% faster)

# --------------------------
# DETERMINISTIC/ORDERING TESTS
# --------------------------

def test_stability_with_equal_elements():
    # Sorting should be stable for equal elements (relative order preserved)
    # Bubble sort is stable, so this should pass
    arr = [('a', 1), ('b', 1), ('c', 2), ('d', 2)]
    # Sort by the second element
    arr_sorted = sorted(arr, key=lambda x: x[1])
    # Use a custom key: simulate by sorting tuples by second element
    arr_for_sorter = [x[1] for x in arr]
    codeflash_output = sorter(arr_for_sorter.copy()); result = codeflash_output # 4.33μs -> 4.04μs (7.23% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

⏪ Replay Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
test_tracer_py__replay_test_0.py::test_codeflash_bubble_sort_sorter	823ms	546ms	✅50.8%

To edit these changes git checkout codeflash/optimize-sorter-mcmotqeg and push.