* DRAFT: GitHub Actions: Test on Python 3.12
Repeats #8777
* #8777
Some of our dependencies will not be ready yet.
* Python 3.12: Disable qiskit and tensorflow algorithms
* updating DIRECTORY.md
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* Add type hints to k_nearest_neighbours.py
* Refactor k_nearest_neighbours.py into class
* Add documentation to k_nearest_neighbours.py
* Use heap-based priority queue for k_nearest_neighbours.py
* Delete knn_sklearn.py
* updating DIRECTORY.md
* Use optional args in k_nearest_neighbours.py for demo purposes
* Fix wrong function arg in k_nearest_neighbours.py
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* Move and reimplement convert_number_to_words.py
- Move convert_number_to_words.py from web_programming/ to conversions/
- Reimplement the algorithm from scratch because the logic was very
opaque and too heavily nested
- Add support for the Western numbering system (both short and long)
because the original implementation only supported the Indian
numbering system
- Add extensive doctests and error handling
* updating DIRECTORY.md
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* updating DIRECTORY.md
* fix(get-top-billionaires): Handle timestamp before epoch
* updating DIRECTORY.md
* revert(pyproject): Re-implement ignore lru_cache
* fix(age): Update age to current year
* fix(doctest): Make years since dynamic
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* Fix ruff errors
Renamed neural_network/input_data.py to neural_network/input_data.py_tf
because it should be left out of the directory for the following
reasons:
1. Its sole purpose is to be used by neural_network/gan.py_tf, which is
itself left out of the directory because of issues with TensorFlow.
2. It was taken directly from TensorFlow's codebase and is actually
already deprecated. If/when neural_network/gan.py_tf is eventually
re-added back to the directory, its implementation should be changed
to not use neural_network/input_data.py anyway.
* updating DIRECTORY.md
* Change input_data.py_tf file extension
Change input_data.py_tf file extension because algorithms-keeper bot is being picky about it
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* Input for user choose his Collatz sequence
Now the user can tell the algorithm what number he wants to run on the Collatz Sequence.
* updating DIRECTORY.md
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* Added file basic_orbital_capture
* updating DIRECTORY.md
* added second source
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fixed spelling errors
* accepted changes
* updating DIRECTORY.md
* corrected spelling error
* Added file basic_orbital_capture
* added second source
* fixed spelling errors
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* applied changes
* reviewed and checked file
* added doctest
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* removed redundant constnant
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* added scipy imports
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* added doctests to capture_radii and scipy const
* fixed conflicts
* finalizing file. Added tests
* Update physics/basic_orbital_capture.py
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* Reimplement polynomial_regression.py
Rename machine_learning/polymonial_regression.py to
machine_learning/polynomial_regression.py
Reimplement machine_learning/polynomial_regression.py using numpy
because the old original implementation was just a how-to on doing
polynomial regression using sklearn
Add detailed function documentation, doctests, and algorithm
explanation
* updating DIRECTORY.md
* Fix matrix formatting in docstrings
* Try to fix failing doctest
* Debugging failing doctest
* Fix failing doctest attempt 2
* Remove unnecessary return value descriptions in docstrings
* Readd placeholder doctest for main function
* Fix typo in algorithm description
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* updating DIRECTORY.md
* Clarify wording in PR template
* Clarify CONTRIBUTING.md wording about adding issue numbers
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Add suggested change from review to CONTRIBUTING.md
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* Incorporate review edit to CONTRIBUTING.md
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* Added minimum waiting time problem solution using greedy algorithm
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* ruff --fix
* Add type hints
* Added two more doc test
* Removed unnecessary comments
* updated type hints
* Updated the code as per the code review
* Added recursive algo to calculate product sum from an array
* Added recursive algo to calculate product sum from an array
* Update doc string
* Added doctest for product_sum function
* Updated the code and added more doctests
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* Added more test coverage for product_sum method
* Update product_sum.py
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* updating DIRECTORY.md
* feat: Count negative numbers in sorted matrix
* updating DIRECTORY.md
* chore: Fix pre-commit
* refactor: Combine functions into iteration
* style: Reformat reference
* feat: Add timings of each implementation
* chore: Fix problems with algorithms-keeper bot
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* test: Remove doctest from benchmark function
* Update matrix/count_negative_numbers_in_sorted_matrix.py
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* Update matrix/count_negative_numbers_in_sorted_matrix.py
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* Update matrix/count_negative_numbers_in_sorted_matrix.py
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* Update matrix/count_negative_numbers_in_sorted_matrix.py
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* Update matrix/count_negative_numbers_in_sorted_matrix.py
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* Update matrix/count_negative_numbers_in_sorted_matrix.py
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* refactor: Use sum instead of large iteration
* refactor: Use len not sum
* Update count_negative_numbers_in_sorted_matrix.py
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