⚡️ Speed up function sort_from_another_file by 12,636%

[codeflash-ai]

📄 12,636% (126.36x) speedup for sort_from_another_file in code_to_optimize/bubble_sort_from_another_file.py

⏱️ Runtime : 509 milliseconds → 4.00 milliseconds (best of 43 runs)

📝 Explanation and details

Here is a much faster version of your code, optimized for speed while preserving all function signatures and all existing comments (though I have modified a comment where the logic changed). The sort you had was a naive bubble sort. We can greatly speed this up by using Python's built-in efficient sorting or, if you need to keep bubble sort for demonstration, by making it break early if no swaps are performed. For extreme speed, however, I use the built-in sort while preserving your side-effects (print messages and in-place modification).

Explanation of improvements.

• Replaces O(N²) bubble sort with O(N log N) Timsort via the built-in list.sort().
• Preserves in-place sorting, printed messages, and return value exactly as before.
• No unnecessary temporary variables or repeated length calculation.
• All original function signatures and outputs preserved.

If you must use bubble sort for some reason (e.g., assignment, not allowed to sort()), let me know and I can write the fastest bubble sort possible! Otherwise, this rewrite will provide optimal speed for your use-case.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 63 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
import sys  # used for edge test cases with large/small numbers

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort_from_another_file import \
    sort_from_another_file

# unit tests

# 1. Basic Test Cases

def test_sort_basic_sorted_list():
    # Already sorted list should remain unchanged
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sort_from_another_file(arr.copy()) # 19.5μs -> 16.4μs

def test_sort_basic_reverse_sorted():
    # Reverse sorted list should be sorted in ascending order
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sort_from_another_file(arr.copy()) # 17.7μs -> 15.9μs

def test_sort_basic_unsorted():
    # Unsorted list with random order
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sort_from_another_file(arr.copy()) # 16.3μs -> 16.0μs

def test_sort_basic_duplicates():
    # List with duplicate elements
    arr = [2, 3, 2, 1, 3]
    codeflash_output = sort_from_another_file(arr.copy()) # 16.2μs -> 15.8μs

def test_sort_basic_single_element():
    # List with a single element
    arr = [42]
    codeflash_output = sort_from_another_file(arr.copy()) # 14.9μs -> 15.7μs

def test_sort_basic_two_elements_sorted():
    # Two-element list, already sorted
    arr = [1, 2]
    codeflash_output = sort_from_another_file(arr.copy()) # 15.5μs -> 15.6μs

def test_sort_basic_two_elements_unsorted():
    # Two-element list, unsorted
    arr = [2, 1]
    codeflash_output = sort_from_another_file(arr.copy()) # 16.5μs -> 15.5μs

def test_sort_basic_empty():
    # Empty list should return empty list
    arr = []
    codeflash_output = sort_from_another_file(arr.copy()) # 14.5μs -> 15.4μs

# 2. Edge Test Cases

def test_sort_edge_all_equal():
    # All elements are the same
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sort_from_another_file(arr.copy()) # 16.5μs -> 16.0μs

def test_sort_edge_negative_numbers():
    # List with negative numbers
    arr = [-3, -1, -4, -2, 0]
    codeflash_output = sort_from_another_file(arr.copy()) # 18.6μs -> 16.1μs

def test_sort_edge_mixed_signs():
    # List with both negative and positive numbers
    arr = [-2, 3, 0, -1, 2]
    codeflash_output = sort_from_another_file(arr.copy()) # 15.8μs -> 15.9μs

def test_sort_edge_large_numbers():
    # List with very large numbers
    arr = [sys.maxsize, -sys.maxsize-1, 0, 999999999, -999999999]
    expected = [-sys.maxsize-1, -999999999, 0, 999999999, sys.maxsize]
    codeflash_output = sort_from_another_file(arr.copy()) # 19.0μs -> 16.8μs

def test_sort_edge_floats():
    # List with floating point numbers
    arr = [1.1, 2.2, 0.5, -1.5, 2.2]
    codeflash_output = sort_from_another_file(arr.copy()) # 21.0μs -> 17.8μs

def test_sort_edge_integers_and_floats():
    # List with both integers and floats
    arr = [3, 1.5, 2, 4.0, 0]
    codeflash_output = sort_from_another_file(arr.copy()) # 19.6μs -> 16.9μs

def test_sort_edge_strings():
    # List of strings, should sort lexicographically
    arr = ["banana", "apple", "cherry", "date"]
    codeflash_output = sort_from_another_file(arr.copy()) # 15.6μs -> 16.0μs

def test_sort_edge_empty_strings():
    # List with empty strings
    arr = ["", "a", "b", ""]
    codeflash_output = sort_from_another_file(arr.copy()) # 18.4μs -> 15.8μs

def test_sort_edge_unicode_strings():
    # List with unicode strings
    arr = ["éclair", "apple", "Éclair", "banana"]
    # Python's sort is case-sensitive and unicode-aware
    codeflash_output = sort_from_another_file(arr.copy()) # 19.4μs -> 16.6μs

def test_sort_edge_single_character_strings():
    # List with single character strings
    arr = ["d", "a", "c", "b"]
    codeflash_output = sort_from_another_file(arr.copy()) # 18.2μs -> 16.0μs

def test_sort_edge_empty_list():
    # Explicitly test empty list again for edge case coverage
    arr = []
    codeflash_output = sort_from_another_file(arr.copy()) # 17.0μs -> 15.3μs

def test_sort_edge_large_identical_elements():
    # List with many identical elements
    arr = [42] * 100
    codeflash_output = sort_from_another_file(arr.copy()) # 204μs -> 22.4μs

def test_sort_edge_boolean_values():
    # List with boolean values (False < True)
    arr = [True, False, True, False]
    codeflash_output = sort_from_another_file(arr.copy()) # 16.5μs -> 16.0μs

def test_sort_edge_none_in_list():
    # List with None should raise TypeError (cannot compare None and int)
    arr = [1, None, 2]
    with pytest.raises(TypeError):
        sort_from_another_file(arr.copy())

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

# 3. Large Scale Test Cases

def test_sort_large_random_integers():
    # Large list of random integers
    arr = random.sample(range(-10000, -9000), 1000)
    expected = sorted(arr)
    codeflash_output = sort_from_another_file(arr.copy()) # 38.8ms -> 154μs

def test_sort_large_duplicates():
    # Large list with many duplicates
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sort_from_another_file(arr.copy()) # 35.4ms -> 123μs

def test_sort_large_sorted():
    # Already sorted large list
    arr = list(range(1000))
    codeflash_output = sort_from_another_file(arr.copy()) # 26.8ms -> 77.1μs

def test_sort_large_reverse_sorted():
    # Reverse sorted large list
    arr = list(range(999, -1, -1))
    expected = list(range(1000))
    codeflash_output = sort_from_another_file(arr.copy()) # 43.1ms -> 77.0μs

def test_sort_large_strings():
    # Large list of random strings
    arr = [''.join(random.choices(string.ascii_letters, k=5)) for _ in range(500)]
    expected = sorted(arr)
    codeflash_output = sort_from_another_file(arr.copy()) # 10.0ms -> 92.2μs

def test_sort_large_floats():
    # Large list of random floats
    arr = [random.uniform(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sort_from_another_file(arr.copy()) # 38.1ms -> 537μs

def test_sort_large_negative_and_positive():
    # Large list with both negative and positive integers
    arr = [random.randint(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sort_from_another_file(arr.copy()) # 39.0ms -> 153μs

# Mutation testing: ensure function is stable under repeated calls
def test_sort_idempotency():
    # Sorting an already sorted list should not change it
    arr = [random.randint(-100, 100) for _ in range(100)]
    codeflash_output = sort_from_another_file(arr.copy()); sorted_arr = codeflash_output # 203μs -> 22.2μs
    codeflash_output = sort_from_another_file(sorted_arr.copy()); sorted_again = codeflash_output # 203μs -> 22.2μs

# Mutation testing: ensure original input is not mutated (since .copy() is used in tests)
def test_sort_does_not_mutate_input():
    # The input list should not be mutated by the function if a copy is passed
    arr = [3, 2, 1]
    arr_copy = arr.copy()
    sort_from_another_file(arr_copy)
# 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 scale random data
import string  # used for string test cases
import sys  # used for edge cases with large/small numbers

# imports
import pytest  # used for our unit tests
from code_to_optimize.bubble_sort_from_another_file import \
    sort_from_another_file

# unit tests

# ---------------------------
# 1. BASIC TEST CASES
# ---------------------------

def test_single_element():
    # Single element list should return the same list
    codeflash_output = sort_from_another_file([1]) # 13.7μs -> 15.0μs
    codeflash_output = sort_from_another_file(['a']) # 13.7μs -> 15.0μs

def test_already_sorted():
    # Already sorted list should remain unchanged
    codeflash_output = sort_from_another_file([1, 2, 3, 4, 5]) # 14.2μs -> 15.4μs
    codeflash_output = sort_from_another_file(['a', 'b', 'c']) # 14.2μs -> 15.4μs

def test_reverse_sorted():
    # Reverse sorted list should become sorted
    codeflash_output = sort_from_another_file([5, 4, 3, 2, 1]) # 14.2μs -> 15.2μs
    codeflash_output = sort_from_another_file(['z', 'y', 'x']) # 14.2μs -> 15.2μs

def test_unsorted_integers():
    # Unsorted list of integers
    codeflash_output = sort_from_another_file([3, 1, 4, 1, 5, 9, 2]) # 19.3μs -> 15.9μs

def test_unsorted_strings():
    # Unsorted list of strings
    codeflash_output = sort_from_another_file(['banana', 'apple', 'cherry']) # 18.2μs -> 15.9μs

def test_duplicates():
    # List with duplicate elements
    codeflash_output = sort_from_another_file([2, 3, 2, 1, 3]) # 15.9μs -> 15.8μs

def test_negative_numbers():
    # List with negative numbers
    codeflash_output = sort_from_another_file([-1, -3, 2, 0]) # 16.2μs -> 15.8μs

def test_mixed_sign_numbers():
    # List with both positive and negative numbers
    codeflash_output = sort_from_another_file([0, -1, 1, -2, 2]) # 15.2μs -> 15.8μs

def test_floats():
    # List with floating point numbers
    codeflash_output = sort_from_another_file([3.1, 2.4, 5.6, 1.2]) # 20.2μs -> 17.2μs

def test_mixed_int_float():
    # List with both ints and floats
    codeflash_output = sort_from_another_file([1, 2.2, 3, 0.5]) # 19.7μs -> 17.0μs

def test_input_not_mutated():
    # Ensure input list is not mutated
    original = [3, 2, 1]
    codeflash_output = sort_from_another_file(original); _ = codeflash_output # 17.9μs -> 15.5μs

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

def test_empty_list():
    # Empty list should return empty list
    codeflash_output = sort_from_another_file([]) # 16.9μs -> 15.3μs

def test_all_equal_elements():
    # All elements equal
    codeflash_output = sort_from_another_file([7, 7, 7, 7]) # 16.6μs -> 15.6μs

def test_large_and_small_numbers():
    # List with very large and very small (negative) numbers
    arr = [sys.maxsize, -sys.maxsize - 1, 0]
    codeflash_output = sort_from_another_file(arr) # 17.4μs -> 16.1μs

def test_strings_case_sensitivity():
    # Strings with different cases
    arr = ['apple', 'Banana', 'banana', 'Apple']
    expected = ['Apple', 'Banana', 'apple', 'banana']  # Python's default sort is case-sensitive
    codeflash_output = sort_from_another_file(arr) # 17.5μs -> 16.1μs

def test_unicode_strings():
    # List with unicode characters
    arr = ['éclair', 'apple', 'Éclair', 'banana']
    expected = ['Éclair', 'apple', 'banana', 'éclair']  # Python sorts unicode by codepoint
    codeflash_output = sort_from_another_file(arr) # 18.9μs -> 16.8μs

def test_list_of_tuples():
    # Sorting tuples: should sort by first element, then second, etc.
    arr = [(2, 3), (1, 2), (2, 2), (1, 1)]
    expected = [(1, 1), (1, 2), (2, 2), (2, 3)]
    codeflash_output = sort_from_another_file(arr) # 18.4μs -> 17.3μs

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

def test_list_with_incomparable_types_raises():
    # List with incomparable types should raise TypeError
    arr = [1, 'a', 2]
    with pytest.raises(TypeError):
        sort_from_another_file(arr)

def test_long_string_elements():
    # List with long strings
    arr = ['a'*100, 'b'*99, 'a'*101]
    expected = ['a'*100, 'a'*101, 'b'*99]
    codeflash_output = sort_from_another_file(arr) # 16.6μs -> 17.1μs


def test_large_sorted_list():
    # Large already sorted list
    arr = list(range(1000))
    codeflash_output = sort_from_another_file(arr) # 26.8ms -> 76.0μs

def test_large_reverse_sorted_list():
    # Large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sort_from_another_file(arr) # 42.9ms -> 74.7μs

def test_large_random_integers():
    # Large random list of integers
    arr = [random.randint(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sort_from_another_file(arr) # 39.1ms -> 153μs

def test_large_random_floats():
    # Large random list of floats
    arr = [random.uniform(-1e6, 1e6) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sort_from_another_file(arr) # 37.3ms -> 534μs

def test_large_random_strings():
    # Large random list of strings
    arr = [''.join(random.choices(string.ascii_letters, k=10)) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sort_from_another_file(arr) # 43.8ms -> 182μs

def test_large_with_duplicates():
    # Large list with many duplicates
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sort_from_another_file(arr) # 35.3ms -> 122μs

def test_large_mixed_int_float():
    # Large list with a mix of ints and floats
    arr = [random.randint(-1000, 1000) if i % 2 == 0 else random.uniform(-1000, 1000) for i in range(1000)]
    expected = sorted(arr)
    codeflash_output = sort_from_another_file(arr) # 50.9ms -> 460μs
# 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-sort_from_another_file-mbmykkl7 and push.