⚡️ Speed up function sorter by 325,341%

[codeflash-ai]

📄 325,341% (3,253.41x) speedup for sorter in code_to_optimize/bubble_sort.py

⏱️ Runtime : 5.37 seconds → 1.65 millisecond (best of 581 runs)

📝 Explanation and details

Certainly! The given program uses a basic and inefficient bubble sort algorithm. We can optimize it by using Python’s built-in sort method which is highly optimized. Here's the rewritten code.

This change will leverage Timsort, the algorithm used in Python's built-in sort, which has an average-case time complexity of O(n log n) and is much faster than bubble sort. The output and functionality remain exactly the same.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	✅ 19 Passed
🌀 Generated Regression Tests	✅ 61 Passed
⏪ Replay Tests	🔘 None Found
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

⚙️ Existing Unit Tests Details

- test_bubble_sort.py
- test_bubble_sort_conditional.py
- test_bubble_sort_import.py
- test_bubble_sort_in_class.py
- test_bubble_sort_parametrized.py
- test_bubble_sort_parametrized_loop.py

🌀 Generated Regression Tests Details

import random  # used for generating large random lists

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

# unit tests

def test_basic_functionality():
    # Simple unsorted list
    codeflash_output = sorter([3, 1, 2])
    codeflash_output = sorter([5, 4, 3, 2, 1])
    # Already sorted list
    codeflash_output = sorter([1, 2, 3])
    codeflash_output = sorter([1, 2, 3, 4, 5])
    # Reverse sorted list
    codeflash_output = sorter([3, 2, 1])
    codeflash_output = sorter([5, 4, 3, 2, 1])

def test_edge_cases():
    # Empty list
    codeflash_output = sorter([])
    # Single element list
    codeflash_output = sorter([1])
    # Two elements list
    codeflash_output = sorter([2, 1])
    codeflash_output = sorter([1, 2])

def test_lists_with_duplicates():
    # All elements the same
    codeflash_output = sorter([1, 1, 1])
    codeflash_output = sorter([2, 2, 2, 2])
    # Some duplicates
    codeflash_output = sorter([3, 1, 2, 1])
    codeflash_output = sorter([4, 5, 4, 3, 2])

def test_lists_with_negative_numbers():
    # All negative numbers
    codeflash_output = sorter([-1, -2, -3])
    codeflash_output = sorter([-3, -1, -2])
    # Mixed positive and negative numbers
    codeflash_output = sorter([3, -1, 2, -2])
    codeflash_output = sorter([-5, 4, -3, 2, -1])

def test_lists_with_mixed_data_types():
    # Integers and floats
    codeflash_output = sorter([1, 2.5, 3, 2.0])
    codeflash_output = sorter([3.1, 2, 1.5, 2.2])

def test_large_scale():
    # Large list of random numbers
    large_list = [random.randint(0, 1000) for _ in range(1000)]
    codeflash_output = sorter(large_list)
    large_list = [random.randint(-1000, 1000) for _ in range(1000)]
    codeflash_output = sorter(large_list)
    # Large list of sorted numbers
    large_list = list(range(1000))
    codeflash_output = sorter(large_list)
    large_list = list(range(1000, 0, -1))
    codeflash_output = sorter(large_list)

def test_lists_with_special_values():
    # List with zero
    codeflash_output = sorter([0, 1, 2, 3])
    codeflash_output = sorter([3, 0, 2, 1])
    # List with large integers
    codeflash_output = sorter([1000000, 999999, 1000001])
    codeflash_output = sorter([2147483647, -2147483648, 0])

def test_lists_with_floating_point_precision():
    # Floating point numbers
    codeflash_output = sorter([1.1, 1.01, 1.001])
    codeflash_output = sorter([3.14, 2.71, 1.41])
# 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 random lists in large scale tests

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

# unit tests

def test_sorted_list():
    # Basic functionality: sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter([10, 20, 30, 40, 50])

def test_reverse_sorted_list():
    # Basic functionality: reverse sorted list
    codeflash_output = sorter([5, 4, 3, 2, 1])
    codeflash_output = sorter([50, 40, 30, 20, 10])

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

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

def test_single_element_list():
    # Edge case: single element list
    codeflash_output = sorter([1])
    codeflash_output = sorter([42])

def test_all_elements_identical():
    # Edge case: all elements identical
    codeflash_output = sorter([2, 2, 2, 2, 2])
    codeflash_output = sorter([7, 7, 7, 7, 7, 7, 7, 7, 7])

def test_multiple_duplicates():
    # Lists with duplicate elements: multiple duplicates
    codeflash_output = sorter([4, 5, 4, 5, 4, 5])
    codeflash_output = sorter([1, 3, 2, 3, 1, 2, 3, 1, 2])

def test_single_duplicate():
    # Lists with duplicate elements: single duplicate
    codeflash_output = sorter([1, 2, 3, 2, 4])
    codeflash_output = sorter([5, 6, 7, 6, 8, 9])

def test_all_negative():
    # Lists with negative numbers: all negative
    codeflash_output = sorter([-1, -2, -3, -4, -5])
    codeflash_output = sorter([-10, -20, -30, -40, -50])

def test_mixed_positive_and_negative():
    # Lists with negative numbers: mixed positive and negative
    codeflash_output = sorter([3, -1, 4, -1, 5, -9, 2, -6, 5, -3, 5])
    codeflash_output = sorter([-10, 5, -2, 3, -7, 6, -4, 1, -9, 8])

def test_all_positive_floats():
    # Lists with floating point numbers: all positive floats
    codeflash_output = sorter([1.1, 2.2, 3.3, 4.4, 5.5])
    codeflash_output = sorter([10.5, 20.1, 30.9, 40.3, 50.7])

def test_mixed_integers_and_floats():
    # Lists with floating point numbers: mixed integers and floats
    codeflash_output = sorter([1, 2.2, 3, 4.4, 5])
    codeflash_output = sorter([5.5, 6, 7.7, 8, 9.9])

def test_negative_floats():
    # Lists with floating point numbers: negative floats
    codeflash_output = sorter([-1.1, -2.2, -3.3, -4.4, -5.5])
    codeflash_output = sorter([-10.5, -20.1, -30.9, -40.3, -50.7])

def test_large_sorted_list():
    # Large scale test cases: large sorted list
    codeflash_output = sorter(list(range(1000)))
    codeflash_output = sorter(list(range(1000)))

def test_large_reverse_sorted_list():
    # Large scale test cases: large reverse sorted list
    codeflash_output = sorter(list(range(1000, 0, -1)))
    codeflash_output = sorter(list(range(10000, 9000, -1)))

def test_large_random_list():
    # Large scale test cases: large random list
    random_list_1000 = random.sample(range(1000), 1000)
    codeflash_output = sorter(random_list_1000)
    
    random_list_10000 = random.sample(range(1000), 1000)
    codeflash_output = sorter(random_list_10000)
# 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-m7wolvwc and push.