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📄 90033% (209x) speedup for sorter in cli/code_to_optimize/bubble_sort.py
⏱️ Runtime : 9.03 seconds→29.9 milliseconds (best of 32 runs)
📝 Explanation and details
Test increase the speed of this function by switching to a more efficient sorting algorithm like Timsort, which is the default sorting algorithm used in Python. Here's the optimized version.
This utilizes Python's built-in sort method, which is highly efficient with a time complexity of O(n log n).
importpytest# used for our unit testsfromcode_to_optimize.bubble_sortimportsorter# unit testsdeftest_already_sorted_list():
# Test with a list that is already sortedcodeflash_output=sorter([1, 2, 3, 4, 5])
codeflash_output=sorter([10, 20, 30])
deftest_reverse_sorted_list():
# Test with a list that is sorted in reverse ordercodeflash_output=sorter([5, 4, 3, 2, 1])
codeflash_output=sorter([30, 20, 10])
deftest_unsorted_list():
# Test with a list that is unsortedcodeflash_output=sorter([3, 1, 4, 5, 2])
codeflash_output=sorter([10, 5, 20, 15])
deftest_single_element_list():
# Test with a list containing a single elementcodeflash_output=sorter([1])
codeflash_output=sorter([42])
deftest_empty_list():
# Test with an empty listcodeflash_output=sorter([])
deftest_list_with_duplicates():
# Test with a list containing duplicate elementscodeflash_output=sorter([2, 3, 2, 1, 3])
codeflash_output=sorter([5, 5, 5, 5])
deftest_list_with_negative_numbers():
# Test with a list containing negative numberscodeflash_output=sorter([-1, -3, -2, 0, 2])
codeflash_output=sorter([-5, -10, 0, 5, 10])
deftest_list_with_mixed_numbers():
# Test with a list containing both positive and negative numberscodeflash_output=sorter([-10, 5, -20, 15, 0])
codeflash_output=sorter([3, -1, 4, -5, 2])
deftest_list_with_floats():
# Test with a list containing floating point numberscodeflash_output=sorter([2.5, 3.1, 1.8, 2.9])
codeflash_output=sorter([1.1, 1.01, 1.001])
deftest_list_with_strings():
# Test with a list containing stringscodeflash_output=sorter(["apple", "banana", "cherry"])
codeflash_output=sorter(["dog", "cat", "bird"])
deftest_large_list():
# Test with a large list to assess performancelarge_list=list(range(1000, 0, -1))
sorted_large_list=list(range(1, 1001))
codeflash_output=sorter(large_list)
deftest_non_comparable_elements():
# Test with a list containing non-comparable elementswithpytest.raises(TypeError):
sorter([1, "two", 3])
withpytest.raises(TypeError):
sorter([None, 1, 2])
deftest_stability():
# Test with a list to check stability (order of equal elements)codeflash_output=sorter([1, 2, 2, 3, 3, 1])
codeflash_output=sorter([5, 3, 3, 5, 1, 1])
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.importpytest# used for our unit testsfromcode_to_optimize.bubble_sortimportsorter# unit tests# Test basic functionality with sorted listdeftest_sorted_list():
codeflash_output=sorter([1, 2, 3, 4, 5])
codeflash_output=sorter(['a', 'b', 'c'])
# Test basic functionality with reverse sorted listdeftest_reverse_sorted_list():
codeflash_output=sorter([5, 4, 3, 2, 1])
codeflash_output=sorter(['z', 'y', 'x'])
# Test basic functionality with unsorted listdeftest_unsorted_list():
codeflash_output=sorter([3, 1, 4, 2, 5])
codeflash_output=sorter(['b', 'a', 'd', 'c'])
# Test edge case with empty listdeftest_empty_list():
codeflash_output=sorter([])
# Test edge case with single element listdeftest_single_element_list():
codeflash_output=sorter([1])
codeflash_output=sorter(['a'])
# Test edge case with repeated elementsdeftest_repeated_elements():
codeflash_output=sorter([2, 3, 2, 1, 1])
codeflash_output=sorter(['a', 'b', 'a', 'c', 'b'])
# Test edge case with negative numbersdeftest_negative_numbers():
codeflash_output=sorter([-1, -3, -2, 0, 2])
# Test edge case with mixed positive and negative numbersdeftest_mixed_numbers():
codeflash_output=sorter([3, -1, 2, -3, 0])
# Test special case with all identical elementsdeftest_identical_elements():
codeflash_output=sorter([5, 5, 5, 5])
# Test special case with large numbersdeftest_large_numbers():
codeflash_output=sorter([1000000, 500000, 1000001])
# Test performance with large listdeftest_large_list():
large_list=list(range(1000, 0, -1))
sorted_list=list(range(1, 1001))
codeflash_output=sorter(large_list)
# Test robustness with non-comparable elementsdeftest_non_comparable_elements():
withpytest.raises(TypeError):
sorter([1, 'a', 3])
# Test edge case with floatsdeftest_floats():
codeflash_output=sorter([3.1, 2.2, 5.5, 4.4])
# Test edge case with mixed integers and floatsdeftest_mixed_integers_floats():
codeflash_output=sorter([1, 2.2, 3, 0.5])
# 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-m7pht0lm and push.
Test increase the speed of this function by switching to a more efficient sorting algorithm like Timsort, which is the default sorting algorithm used in Python. Here's the optimized version.
This utilizes Python's built-in `sort` method, which is highly efficient with a time complexity of O(n log n).
⚡️ codeflashOptimization PR opened by CodeFlash AI
0 participants
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📄 90033% (209x) speedup for
sorter
incli/code_to_optimize/bubble_sort.py
⏱️ Runtime :
9.03 seconds
→29.9 milliseconds
(best of32
runs)📝 Explanation and details
Test increase the speed of this function by switching to a more efficient sorting algorithm like Timsort, which is the default sorting algorithm used in Python. Here's the optimized version.
This utilizes Python's built-in
sort
method, which is highly efficient with a time complexity of O(n log n).✅ Correctness verification report:
⚙️ Existing Unit Tests Details
🌀 Generated Regression Tests Details
To edit these changes
git checkout codeflash/optimize-sorter-m7pht0lm
and push.