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⚡️ Speed up function sorter by 19% #217

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@codeflash-ai codeflash-ai bot commented Mar 3, 2025

📄 19% (0.19x) speedup for sorter in src/bubble_sort.py

⏱️ Runtime : 1.01 second 853 milliseconds (best of 9 runs)

📝 Explanation and details

You can optimize this sorting algorithm by replacing it with a more efficient sorting algorithm, such as Timsort, which is the default sorting algorithm used by Python's built-in sorted() function and list.sort() method. Timsort has a time complexity of O(n log n) which is significantly faster than the O(n^2) complexity of the original bubble sort.

Here's the optimized code using Python's built-in sorting.

This code does the exact same thing but much faster for larger datasets.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 2 Passed
🌀 Generated Regression Tests 52 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
⚙️ Existing Unit Tests Details
- benchmarks/test_benchmark_sort.py
- test_plugin_py__replay_test_0.py
- test_plugin_py__replay_test_1.py
- test_sort.py
🌀 Generated Regression Tests Details
import pytest  # used for our unit tests
from src.bubble_sort import sorter

# unit tests

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])
    codeflash_output = sorter(['a'])

def test_already_sorted_list():
    # Test with an already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter(['a', 'b', 'c', 'd'])

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

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

def test_list_with_negative_numbers():
    # Test with a list containing negative numbers
    codeflash_output = sorter([-1, -3, -2, 0, 2, 1])
    codeflash_output = sorter([-5, -1, -3, -2, -4])

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

def test_list_with_floating_point_numbers():
    # Test with a list containing floating point numbers
    codeflash_output = sorter([1.1, 2.2, 0.5, 3.3, 2.1])
    codeflash_output = sorter([-1.1, -0.5, 0.0, 1.5, -2.2])

def test_list_with_mixed_data_types():
    # Test with a list containing mixed data types that are comparable
    codeflash_output = sorter([1, 2.2, 0.5, 3, 2.1])

def test_large_list():
    # Test with a large list to assess performance and scalability
    large_list = list(range(1000, 0, -1))
    sorted_large_list = list(range(1, 1001))
    codeflash_output = sorter(large_list)

def test_list_with_strings():
    # Test with a list of strings
    codeflash_output = sorter(['banana', 'apple', 'cherry', 'date'])
    codeflash_output = sorter(['zebra', 'yak', 'x-ray', 'walrus'])

def test_list_with_special_characters():
    # Test with a list containing special characters
    codeflash_output = sorter(['!', '@', '#', ', '%'])
    codeflash_output = sorter(['a', '!', 'b', '@', 'c'])

def test_list_with_case_sensitivity():
    # Test with a list containing mixed case sensitivity
    codeflash_output = sorter(['a', 'A', 'b', 'B'])
    codeflash_output = sorter(['apple', 'Apple', 'banana', 'Banana'])

def test_list_with_non_comparable_elements():
    sorter([1, 'a', 2, 'b'])
    sorter([None, 1, 'a'])
# 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.bubble_sort import sorter

# unit tests

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

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

# Test for already sorted list
def test_already_sorted_list():
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter(['a', 'b', 'c', 'd'])

# Test for reverse sorted list
def test_reverse_sorted_list():
    codeflash_output = sorter([5, 4, 3, 2, 1])
    codeflash_output = sorter(['d', 'c', 'b', 'a'])

# Test for list with duplicates
def test_list_with_duplicates():
    codeflash_output = sorter([3, 1, 2, 3, 1])
    codeflash_output = sorter(['b', 'a', 'c', 'b', 'a'])

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

# Test for mixed data types (should raise an error)
def test_mixed_data_types():
    sorter([1, 'a', 3, 'b'])
    sorter([1, 2.5, '3', 4])

# Test for list with floating point numbers
def test_list_with_floating_point_numbers():
    codeflash_output = sorter([3.1, 2.2, 5.5, 1.0])
    codeflash_output = sorter([1.1, 1.01, 1.001, 1.0001])

# Test for large list
def test_large_list():
    codeflash_output = sorter(list(range(1000, 0, -1)))
    codeflash_output = sorter(list(range(10000, 9000, -1)))

# Test for list with all identical elements
def test_list_with_all_identical_elements():
    codeflash_output = sorter([1, 1, 1, 1, 1])
    codeflash_output = sorter(['a', 'a', 'a', 'a'])

# Test for list with strings of different lengths
def test_list_with_strings_of_different_lengths():
    codeflash_output = sorter(['apple', 'banana', 'cherry', 'date'])
    codeflash_output = sorter(['a', 'ab', 'abc', 'abcd'])

# Test for list with special characters
def test_list_with_special_characters():
    codeflash_output = sorter(['!', '@', '#', ', '%'])
    codeflash_output = sorter(['a', '!', 'b', '@'])

# Test for list with mixed case strings
def test_list_with_mixed_case_strings():
    codeflash_output = sorter(['apple', 'Banana', 'cherry', 'Date'])
    codeflash_output = sorter(['a', 'A', 'b', 'B'])

# Test for list with non-comparable elements (should raise an error)
def test_list_with_non_comparable_elements():
    sorter([1, 'a', 3.0, None])
    sorter([{}, [], (), 'string'])
# 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-m7tkqu6s and push.

Codeflash

You can optimize this sorting algorithm by replacing it with a more efficient sorting algorithm, such as Timsort, which is the default sorting algorithm used by Python's built-in `sorted()` function and `list.sort()` method. Timsort has a time complexity of O(n log n) which is significantly faster than the O(n^2) complexity of the original bubble sort.

Here's the optimized code using Python's built-in sorting.



This code does the exact same thing but much faster for larger datasets.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by CodeFlash AI label Mar 3, 2025
@codeflash-ai codeflash-ai bot requested a review from alvin-r March 3, 2025 21:30
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