⚡️ Speed up function sorter by 814,643%

[codeflash-ai]

📄 814,643% (8,146.43x) speedup for sorter in src/dsa/various.py

⏱️ Runtime : 191 milliseconds → 23.5 microseconds (best of 1138 runs)

📝 Explanation and details

Here is a highly optimized version of your sorter using Python's built-in sort (which is implemented in C and much, much faster than any pure-Python O(n^2) implementation). The function signature and behavior (sorting in-place and returning the array) are preserved. The function's return value will be identical for all inputs.

---

Reasoning

• Algorithmic improvement: The original implementation is a naive bubble sort (O(n^2)). Python's .sort() uses Timsort, which is O(n log n) and much faster for all realistic sizes of input.
• In-place operation: Like your original, the built-in .sort() modifies arr in place.
• Return Value: We continue to return arr at the end for compatibility.

If you want a manual, but still in-place, fast sorting method without using sort.

If you must not use built-in sort (for learning, school, constraints), you could use a faster algorithm like in-place quicksort. However, it’s highly unlikely to beat .sort() in CPython.

Let me know if you need a manual algorithm instead! But for true speed, always use the built-in.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 38 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 already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter(['a', 'b', 'c', 'd'])

def test_reverse_sorted_list():
    # Test reverse sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1])
    codeflash_output = sorter(['z', 'y', 'x', 'w'])

def test_unsorted_list():
    # Test typical unsorted list
    codeflash_output = sorter([3, 1, 4, 5, 2])
    codeflash_output = sorter(['d', 'a', 'c', 'b'])

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

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

def test_two_elements_list():
    # Test two elements list
    codeflash_output = sorter([2, 1])
    codeflash_output = sorter([1, 2])

def test_duplicate_elements():
    # Test list with duplicate elements
    codeflash_output = sorter([2, 3, 2, 1, 3])
    codeflash_output = sorter(['a', 'b', 'a', 'c'])

def test_homogeneous_types():
    # Test list with homogeneous types
    codeflash_output = sorter([1.5, 2.3, 0.7])
    codeflash_output = sorter(['apple', 'banana', 'cherry'])

def test_incompatible_types():
    # Test list with incompatible types should raise TypeError
    with pytest.raises(TypeError):
        sorter([1, 'a', 3])
    with pytest.raises(TypeError):
        sorter([None, 1, 2])

def test_large_list():
    # Test large list for performance
    large_list = list(range(1000, 0, -1))
    codeflash_output = sorter(large_list)

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

def test_zeros():
    # Test list with zeros
    codeflash_output = sorter([0, 1, 0, -1])

def test_alternating_order():
    # Test list with alternating order
    codeflash_output = sorter([1, 100, 2, 99, 3, 98])

def test_all_identical_elements():
    # Test list where all elements are identical
    codeflash_output = sorter([7, 7, 7, 7])
# 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 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 randomly unsorted list
    codeflash_output = sorter([3, 1, 4, 5, 2])

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([1])

def test_identical_elements():
    # Test with a list of identical elements
    codeflash_output = sorter([1, 1, 1, 1])

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

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

def test_negative_numbers():
    # Test with a list containing negative numbers
    codeflash_output = sorter([-3, -1, -4, -2, -5])

def test_mixed_positive_negative():
    # Test with a list containing both positive and negative numbers
    codeflash_output = sorter([-1, 2, -3, 4, -5])

def test_floating_point_numbers():
    # Test with a list containing floating point numbers
    codeflash_output = sorter([1.1, 2.2, 0.5, 3.3, 2.1])

def test_performance_with_duplicates():
    # Test with a list containing many duplicate elements
    duplicates_list = [1] * 500 + [2] * 500
    codeflash_output = sorter(duplicates_list)

def test_performance_with_sorted_sublists():
    # Test with a list containing sorted sublists
    codeflash_output = sorter([1, 2, 3, 7, 6, 5, 4, 8, 9, 10])

def test_non_comparable_elements():
    # Test with a list containing non-comparable elements should raise TypeError
    with pytest.raises(TypeError):
        sorter([1, "two", 3])
    with pytest.raises(TypeError):
        sorter(["a", None, "b"])
# 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-maejkebg and push.