Enhancement/issue 8427 #8811
Enhancement/issue 8427 #8811
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for more information, see https://pre-commit.ci
web_programming/sliding_window.py
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Empty file, should be deleted
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Thanks, I have modified and filled it in
| >>> print(next(sw_gen)) | ||
| [1, 2, 3] | ||
| >>> print(next(sw_gen)) | ||
| [2, 3, 4] |
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Could you add a test to check whether the generator stops at the correct index when it reaches the end of the list?
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This algorithm doesn't fit in web_programming. I think it'd fit better under other instead
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Thank you for the clarification, I have moved the files to other folder
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Unfortunately we already have an implementation of max subarray sum in maths/kadanes.py, other/maximum_subarray.py, maths/largest_subarray_sum.py, other/maximum_subsequence.py, and dynamic_programming/max_sum_contiguous_subsequence.py. Furthermore, dynamic_programming/max_sub_array.py and divide_and_conquer/max_subarray_sum.py both implement this algorithm has a subroutine.
... I have no idea why there are so many near-duplicate implementations of the same algorithm, but this really shouldn't be the case. I'll open an issue to address this.
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Also, some of these commits don't pertain to the algorithm contribution itself (Create/Delete TestShiva, Add black version/delete black file, etc.), so this PR could use a rebase to get those commits deleted/squashed before it's merged |
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In the commit body, the box is checked next to
yet there are three algorithm files in this pull request. How is the first file better than Python/maths/largest_subarray_sum.py Line 4 in fa12b9a Is it more concise or faster? If so, do we have a benchmark to prove that? |
| Example: | ||
| >>> arr = [-2, -3, 4, -1, -2, 5, -3] | ||
| >>> max_sub_array_sum(arr, len(arr)) | ||
| 6 |
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Add a blank line to the tests pass.
| 6 | |
| 6 | |
As discussed in CONTRIBUTING.md please test your code by running on your local machine:
% python3 -m doctest -v dynamic_programming/max_sub_array_sum.py
| window = elements[i : i + window_size] | ||
| windows.append(window) |
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| window = elements[i : i + window_size] | |
| windows.append(window) | |
| windows.append(elements[i : i + window_size]) |
| >>> print(next(sw_gen)) | ||
| [1, 2, 3] | ||
| >>> print(next(sw_gen)) |
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| >>> print(next(sw_gen)) | |
| [1, 2, 3] | |
| >>> print(next(sw_gen)) | |
| >>> next(sw_gen) | |
| [1, 2, 3] | |
| >>> next(sw_gen) |
Describe your change:
Impelementation of 2 algorithms from the ones mentioned in the issue #8427 , namely the sliding window algorithm and Kadane's algorithm.
Checklist:
Fixes: #{$ISSUE_NO}.