⚡️ Speed up function sorter by 59,907%

[codeflash-ai]

📄 59,907% (599.07x) speedup for sorter in src/dsa/various.py

⏱️ Runtime : 215 milliseconds → 358 microseconds (best of 866 runs)

📝 Explanation and details

Certainly! The provided code implements bubble sort, which is inefficient (O(N²)). To rewrite this to run much faster but keep the same function signature and semantics, we can use Python’s built-in sort, which uses Timsort (O(N log N)). This both accelerates the operation and preserves the in-place sorting and return behavior.

Here’s the optimized code.

• Explanation: arr.sort() sorts the list in-place in O(N log N) time.
• Semantics: The original arr is sorted in-place and the sorted list is returned, as before.
• Comments: No relevant code comments were present in the original, so none are added.

Let me know if you need to preserve the original sorting algorithm, but for speed, this is optimal.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 36 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests Details

import pytest  # used for our unit tests
from src.dsa.various import sorter

# unit tests

def test_sorted_list():
    # Test with an already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5])

def test_reverse_sorted_list():
    # Test with a reverse sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1])

def test_unsorted_list():
    # Test with a random unsorted list
    codeflash_output = sorter([3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5])

def test_empty_list():
    # Test with an empty list
    codeflash_output = sorter([])

def test_single_element_list():
    # Test with a single element list
    codeflash_output = sorter([42])

def test_two_elements_list():
    # Test with a two-element list
    codeflash_output = sorter([2, 1])

def test_list_with_duplicates():
    # Test with a list containing duplicates
    codeflash_output = sorter([5, 3, 5, 2, 5])

def test_all_elements_same():
    # Test with a list where all elements are the same
    codeflash_output = sorter([7, 7, 7, 7])

def test_integers_and_floats():
    # Test with a list containing integers and floats
    codeflash_output = sorter([1, 2.5, 3, 0.5])

def test_strings():
    # Test with a list of strings
    codeflash_output = sorter(['apple', 'banana', 'cherry'])

def test_large_list():
    # Test with a large list of random integers
    large_list = list(range(10000, 9000, -1))
    sorted_large_list = list(range(1, 1001))
    codeflash_output = sorter(large_list)

def test_max_integer_values():
    # Test with maximum integer values
    codeflash_output = sorter([2147483647, -2147483648, 0])

def test_non_comparable_elements():
    # Test with a list containing non-comparable elements
    with pytest.raises(TypeError):
        sorter([1, 'two', 3])

def test_highly_unsorted_list():
    # Test with a highly unsorted list
    unsorted_list = [9, 7, 5, 3, 1, 2, 4, 6, 8, 0]
    sorted_list = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
    codeflash_output = sorter(unsorted_list)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import pytest  # used for our unit tests
from src.dsa.various import sorter

# unit tests

def test_sorted_list():
    # Test a list that is already sorted
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter([-3, -2, -1, 0, 1])

def test_unsorted_list():
    # Test a list that is unsorted
    codeflash_output = sorter([5, 3, 1, 4, 2])
    codeflash_output = sorter([10, 9, 8, 7, 6])

def test_reverse_sorted_list():
    # Test a list that is sorted in descending order
    codeflash_output = sorter([5, 4, 3, 2, 1])
    codeflash_output = sorter([100, 50, 10, 5, 1])

def test_empty_list():
    # Test an empty list
    codeflash_output = sorter([])

def test_single_element_list():
    # Test a list with a single element
    codeflash_output = sorter([1])
    codeflash_output = sorter([-1])

def test_list_with_duplicates():
    # Test a list with duplicate elements
    codeflash_output = sorter([3, 1, 2, 3, 1])
    codeflash_output = sorter([5, 5, 5, 5, 5])

def test_list_with_negative_numbers():
    # Test a list with negative numbers
    codeflash_output = sorter([-1, -3, -2, 0, 2])
    codeflash_output = sorter([-5, -10, 0, 5, 10])

def test_list_with_floats():
    # Test a list with floating-point numbers
    codeflash_output = sorter([1.1, 2.2, 0.5, 3.3])
    codeflash_output = sorter([-1.1, -2.2, 0.0, 1.1])

def test_list_with_integers_and_floats():
    # Test a list with both integers and floats
    codeflash_output = sorter([1, 2.2, 0.5, 3])
    codeflash_output = sorter([-1, -2.2, 0, 1.1])

def test_large_list():
    # Test a large list of random integers
    large_list = list(range(10000, 9000, -1))
    sorted_large_list = list(range(1, 1001))
    codeflash_output = sorter(large_list)

def test_performance_with_random_data():
    # Test the function's performance with a large list of random data
    random_data = [i % 100 for i in range(1000)]
    sorted_random_data = sorted(random_data)
    codeflash_output = sorter(random_data)

To edit these changes git checkout codeflash/optimize-sorter-ma4f3xwj and push.