feat(ci) Run codeflash in on PRs modifying the Python CDK

[girarda]

What

Adds a github action running Codeflash on PRs modifying the Python CDK.

Codeflash will inspect the new code and provide suggestions to improve the performance.

The github action is not required to complete before merging. There is no requirement for updating the code as per Codeflash's suggestions.

For reference:

• Here is an example inlined suggestion
• Here is an example comment describing the improvement, the rationale, and how codeflash tested the change to avoid introducing regressions.

The goal is to try the tool and see if it can provide value by suggesting performance improvement as we go.

Code review guide

The main thing I want to make sure is the GHA has the right security filters.

User Impact

There should be no user impact.

Can this PR be safely reverted and rolled back?

• YES 💚

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1 Skipped Deployment

Name	Status	Preview	Comments	Updated (UTC)
airbyte-docs	⬜️ Ignored (Inspect)	Visit Preview		Aug 19, 2024 9:57pm

[codeflash-ai]

Suggested change

	for i in range(len(arr)):
	# This is a diff
	for j in range(len(arr) - 1):
	if arr[j] > arr[j + 1]:
	temp = arr[j]
	arr[j] = arr[j + 1]
	arr[j + 1] = temp
	return arr
	arr.sort()

[codeflash-ai]

⚡️ Codeflash found optimizations for this PR

📄 sorter() in airbyte-cdk/python/airbyte_cdk/bubble_sort.py

📈 Performance improved by 922,942% (9,229.42x faster)

⏱️ Runtime went down from 9.79 seconds to 1.06 millisecond

Explanation and details

Certainly! The original program is using Bubble Sort which is not very efficient. We can easily improve the runtime by using Python's built-in sort function, which implements Timsort, a much faster and more efficient sorting algorithm.

Here's a much faster version of the sorter function.

This updated function leverages the built-in sort method, which is highly optimized. It should provide a significant speedup compared to the original bubble sort implementation.

Correctness verification

The new optimized code was tested for correctness. The results are listed below.

✅ 3 Passed − ⚙️ Existing Unit Tests

(click to show existing tests)

- test_bubble_sort.py

✅ 20 Passed − 🌀 Generated Regression Tests

(click to show generated tests)

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

# unit tests

def test_sorted_list():
    # Test with a list that is already sorted
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter([-3, -2, -1, 0, 1, 2, 3])
    # Outputs were verified to be equal to the original implementation

def test_unsorted_list():
    # Test with a list that is not sorted
    codeflash_output = sorter([5, 3, 1, 4, 2])
    codeflash_output = sorter([10, -2, 3, 5, 0])
    # Outputs were verified to be equal to the original implementation

def test_empty_list():
    # Test with an empty list
    codeflash_output = sorter([])
    # Outputs were verified to be equal to the original implementation

def test_single_element_list():
    # Test with a single element list
    codeflash_output = sorter([42])
    # Outputs were verified to be equal to the original implementation

def test_two_elements_list():
    # Test with a two elements list
    codeflash_output = sorter([2, 1])
    codeflash_output = sorter([1, 2])
    # Outputs were verified to be equal to the original implementation

def test_list_with_duplicates():
    # Test with a list that contains duplicate elements
    codeflash_output = sorter([3, 1, 2, 3, 1, 2])
    codeflash_output = sorter([5, 5, 5, 5, 5])
    # Outputs were verified to be equal to the original implementation

def test_list_with_negative_numbers():
    # Test with a list that contains negative numbers
    codeflash_output = sorter([-1, -3, -2, 0, 2, 1])
    codeflash_output = sorter([-5, -10, -3, -1, -4])
    # Outputs were verified to be equal to the original implementation

def test_list_with_floats_and_integers():
    # Test with a list that contains both floats and integers
    codeflash_output = sorter([1.1, 2, 3.3, 1, 2.2])
    codeflash_output = sorter([5.5, 3.3, 4.4, 2.2, 1.1])
    # Outputs were verified to be equal to the original implementation

def test_large_list():
    # Test with a large list
    large_list = list(range(1000, 0, -1))
    codeflash_output = sorter(large_list)
    # Outputs were verified to be equal to the original implementation

def test_random_large_list():
    # Test with a large list of random elements
    import random
    random_list = random.sample(range(100000), 10000)
    codeflash_output = sorter(random_list)
    # Outputs were verified to be equal to the original implementation

def test_max_integers():
    # Test with a list containing very large integer values
    codeflash_output = sorter([2**31 - 1, 2**31 - 2, 2**31 - 3])
    # Outputs were verified to be equal to the original implementation

def test_min_integers():
    # Test with a list containing very small integer values
    codeflash_output = sorter([-2**31, -2**31 + 1, -2**31 + 2])
    # Outputs were verified to be equal to the original implementation

def test_all_elements_same():
    # Test with a list where all elements are the same
    codeflash_output = sorter([1, 1, 1, 1, 1])
    # Outputs were verified to be equal to the original implementation

def test_alternating_high_low():
    # Test with a list with an alternating high-low pattern
    codeflash_output = sorter([1, 100, 2, 99, 3, 98])
    # Outputs were verified to be equal to the original implementation

🔘 (none found) − ⏪ Replay Tests

[codeflash-ai]

Suggested change

	for i in range(len(arr)):
	# This is a diff
	for j in range(len(arr) - 1):
	if arr[j] > arr[j + 1]:
	temp = arr[j]
	arr[j] = arr[j + 1]
	arr[j + 1] = temp
	return arr
	arr.sort()

[codeflash-ai]

⚡️ Codeflash found optimizations for this PR

📄 sorter() in airbyte-cdk/python/airbyte_cdk/bubble_sort.py

📈 Performance improved by 16,727,728% (167,277.28x faster)

⏱️ Runtime went down from 11.8 seconds to 70.4 microseconds

Explanation and details

Certainly! The original code implements a Bubble Sort algorithm, which is quite inefficient for sorting large lists due to its O(n^2) time complexity. We can significantly improve the runtime by using a more efficient sorting algorithm such as Timsort, which is the algorithm used by Python's built-in sort() method. Here's the optimized version using the built-in sorting method.

This should provide a significant speedup, especially for larger arrays, as the built-in sort() method has an average time complexity of O(n log n).

Correctness verification

The new optimized code was tested for correctness. The results are listed below.

✅ 3 Passed − ⚙️ Existing Unit Tests

(click to show existing tests)

- test_bubble_sort.py

✅ 38 Passed − 🌀 Generated Regression Tests

(click to show generated tests)

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

# unit tests

def test_sorted_list():
    # Basic functionality: already sorted list
    codeflash_output = sorter([1, 2, 3, 4, 5])
    codeflash_output = sorter([-3, -2, -1, 0, 1, 2, 3])
    # Outputs were verified to be equal to the original implementation

def test_unsorted_list():
    # Basic functionality: unsorted list
    codeflash_output = sorter([5, 3, 2, 4, 1])
    codeflash_output = sorter([3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5])
    # Outputs were verified to be equal to the original implementation

def test_empty_list():
    # Edge case: empty list
    codeflash_output = sorter([])
    # Outputs were verified to be equal to the original implementation

def test_single_element_list():
    # Edge case: single element list
    codeflash_output = sorter([42])
    # Outputs were verified to be equal to the original implementation

def test_two_elements_list():
    # Edge case: two elements list
    codeflash_output = sorter([2, 1])
    codeflash_output = sorter([1, 2])
    # Outputs were verified to be equal to the original implementation

def test_list_with_duplicates():
    # Lists with duplicates
    codeflash_output = sorter([1, 1, 1, 1, 1])
    codeflash_output = sorter([4, 2, 2, 3, 1, 4, 3])
    codeflash_output = sorter([5, 5, 5, 3, 3, 2, 2, 1, 1])
    # Outputs were verified to be equal to the original implementation

def test_list_with_negative_numbers():
    # Lists with negative numbers
    codeflash_output = sorter([-1, -3, -2, 0, 2, 1])
    codeflash_output = sorter([3, -1, 4, -1, 5, -9, 2, 6, -5, 3, 5])
    # Outputs were verified to be equal to the original implementation

def test_list_with_floats():
    # Lists with floats
    codeflash_output = sorter([1.1, 2.2, 0.5, 3.3, 2.1])
    codeflash_output = sorter([3.14, 2.71, -1.0, 0.0, 1.41])
    # Outputs were verified to be equal to the original implementation

def test_large_list():
    # Large lists
    codeflash_output = sorter(list(range(1000, 0, -1)))
    codeflash_output = sorter(list(range(10000, -1, -1)))
    # Outputs were verified to be equal to the original implementation

def test_list_with_mixed_types():
    # Lists with mixed types should raise an error
    with pytest.raises(TypeError):
        sorter([1, 'a', 3, 'b'])
    with pytest.raises(TypeError):
        sorter([None, 1, 2])
    # Outputs were verified to be equal to the original implementation

def test_list_with_none_values():
    # Lists with None values should raise an error
    with pytest.raises(TypeError):
        sorter([3, None, 2, 1])
    with pytest.raises(TypeError):
        sorter([None, None, None])
    # Outputs were verified to be equal to the original implementation

def test_list_with_extreme_values():
    # Lists with extreme values
    codeflash_output = sorter([1, 2, 3, 999999999999, 4, 5])
    codeflash_output = sorter([999999999999, -999999999999, 0])
    codeflash_output = sorter([1, -999999999999, 2, -3, 4])
    codeflash_output = sorter([-999999999999, 999999999999, -1, 1])
    # Outputs were verified to be equal to the original implementation


def test_list_with_infinity_values():
    # Lists with infinity values
    codeflash_output = sorter([1.0, float('inf'), 2.0, float('-inf')])
    codeflash_output = sorter([float('-inf'), 0.0, float('inf')])
    # Outputs were verified to be equal to the original implementation

def test_list_with_custom_objects():
    # Lists with custom objects should raise an error
    with pytest.raises(TypeError):
        sorter([object(), 1, 2])
    with pytest.raises(TypeError):
        sorter([3, object(), 1])
    with pytest.raises(TypeError):
        sorter([1, 'a', object(), 3])
    with pytest.raises(TypeError):
        sorter([object(), 'b', 2, 1])
    # Outputs were verified to be equal to the original implementation

def test_list_with_repeated_patterns():
    # Lists with repeated patterns
    codeflash_output = sorter([1, 2, 1, 2, 1, 2])
    codeflash_output = sorter([3, 3, 2, 2, 1, 1, 0, 0])
    # Outputs were verified to be equal to the original implementation


def test_list_with_special_characters():
    # Lists with special characters
    codeflash_output = sorter(['a', '!', 'b', '#'])
    codeflash_output = sorter(['@', 'A', 'a', '1', '2', '!'])
    # Outputs were verified to be equal to the original implementation


def test_list_with_tuples():
    # Lists with tuples
    codeflash_output = sorter([(1, 2), (0, 1), (3, 4)])
    codeflash_output = sorter([(2, 3), (1, 2), (0, 1)])
    # Outputs were verified to be equal to the original implementation

🔘 (none found) − ⏪ Replay Tests