⚡️ Speed up function sorter by 19,254%

[codeflash-ai]

📄 19,254% (192.54x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 443 milliseconds → 2.29 milliseconds (best of 71 runs)

📝 Explanation and details

Here is a faster version of your program using Python's built-in sort() (which uses Timsort and is much faster than bubble sort used in your code).

This produces exactly the same results as your original function, but is much faster and uses less memory and CPU time, especially for large lists. All comments are preserved as per your instruction.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 51 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests Details

import random  # used for generating large random lists
import string  # used for string test cases

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

# unit tests

# ---------------------
# Basic Test Cases
# ---------------------

def test_sorter_simple_sorted():
    # Already sorted list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_simple_reverse():
    # Reverse sorted list
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_simple_unsorted():
    # Unsorted list with distinct values
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_with_duplicates():
    # List with duplicate values
    arr = [3, 1, 2, 3, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_negative_numbers():
    # List with negative and positive numbers
    arr = [0, -1, 3, -2, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_single_element():
    # List with a single element
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_two_elements_sorted():
    # Two elements, already sorted
    arr = [1, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_two_elements_unsorted():
    # Two elements, unsorted
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

# ---------------------
# Edge Test Cases
# ---------------------

def test_sorter_empty_list():
    # Empty list should return empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_all_identical():
    # All elements are identical
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_negative_numbers():
    # Large negative numbers
    arr = [-999999, -1000000, -999998]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_mixed_types_raises():
    # Should raise TypeError if types are not comparable
    arr = [1, 'a', 3]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_floats_and_ints():
    # List with floats and ints
    arr = [3.1, 2, 4.5, 1.0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_strings():
    # List of strings
    arr = ["banana", "apple", "cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_unicode_strings():
    # List of unicode strings
    arr = ["ápple", "apple", "äpple"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_empty_strings():
    # List with empty strings
    arr = ["", "a", " "]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_single_large_value():
    # List with a single very large value
    arr = [10**18]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_and_small_values():
    # List with very large and very small values
    arr = [10**18, -10**18, 0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_list_with_none_raises():
    # None is not comparable, should raise TypeError
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_list_with_nan():
    # NaN values: they should sort to the end (Python's default sort behavior)
    arr = [3, float('nan'), 2]
    # Python's built-in sort puts NaN at the end, but our implementation will not handle NaN specially
    # So, the result may contain NaN in any position, but let's check if the non-NaN values are sorted
    codeflash_output = sorter(arr.copy()); result = codeflash_output
    non_nan = [x for x in result if x == x]

# ---------------------
# Large Scale Test Cases
# ---------------------

def test_sorter_large_sorted():
    # Large sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_reverse():
    # Large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_random():
    # Large random list
    arr = random.sample(range(1000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_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()); result = codeflash_output

def test_sorter_large_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()); result = codeflash_output

def test_sorter_large_floats():
    # Large list of random floats
    arr = [random.uniform(-1e6, 1e6) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_stability():
    # Test stability: identical keys retain order
    class Item:
        def __init__(self, key, value):
            self.key = key
            self.value = value
        def __lt__(self, other):
            return self.key < other.key
        def __eq__(self, other):
            return self.key == other.key and self.value == other.value
        def __repr__(self):
            return f"Item({self.key}, {self.value})"
    arr = [Item(1, 'a'), Item(2, 'b'), Item(1, 'c'), Item(2, 'd')]
    codeflash_output = sorter(arr.copy()); result = codeflash_output
# 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

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

# unit tests

# --- Basic Test Cases ---

def test_sorter_sorted_integers():
    # Already sorted list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_unsorted_integers():
    # Unsorted list of integers
    arr = [5, 3, 1, 4, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_duplicates():
    # List with duplicate values
    arr = [3, 1, 2, 3, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_negative_numbers():
    # List containing negative numbers
    arr = [-1, -3, 2, 0, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_floats():
    # List of floating point numbers
    arr = [1.1, 3.3, 2.2, 0.0, -1.1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_strings():
    # List of strings
    arr = ["banana", "apple", "cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_single_element():
    # Single element list
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_two_elements():
    # Two elements, unsorted
    arr = [2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_empty_list():
    # Empty list
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output

# --- Edge Test Cases ---

def test_sorter_all_identical():
    # All elements are the same
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_reverse_sorted():
    # List sorted in descending order
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_mixed_types_raises():
    # List with mixed types should raise TypeError
    arr = [1, "a", 2]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_large_negative_and_positive():
    # List with large negative and positive values
    arr = [999999, -1000000, 0, 500, -500]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_unicode_strings():
    # List with unicode strings
    arr = ["ápple", "apple", "äpple"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_case_sensitivity():
    # List with mixed case strings
    arr = ["banana", "Apple", "cherry"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_mutates_input():
    # Check that the input list is mutated (since the function sorts in-place)
    arr = [3, 2, 1]
    sorter(arr)

# --- Large Scale Test Cases ---

def test_sorter_large_sorted():
    # Large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_reverse():
    # Large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_random():
    # Large random list
    arr = random.sample(range(1000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_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()); result = codeflash_output

def test_sorter_large_strings():
    # 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()); result = codeflash_output

# --- Additional Edge Cases ---

def test_sorter_min_max_int():
    # List with min and max integer values
    import sys
    arr = [sys.maxsize, -sys.maxsize - 1, 0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_nan_and_inf():
    # List with float('nan'), float('inf'), float('-inf')
    arr = [float('nan'), float('inf'), float('-inf'), 0.0]
    # Sorting with NaN is implementation-defined, but NaN is always 'greater' in comparisons
    codeflash_output = sorter(arr.copy()); result = codeflash_output

def test_sorter_large_single_value():
    # Large list with single repeated value
    arr = [42] * 1000
    codeflash_output = sorter(arr.copy()); result = codeflash_output
# 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-mbeiquij and push.