Drop machine_learning/xgboost_classifier.py and
machine_learning/xgboost_regressor.py. Both were thin "how-to-use"
wrappers around sklearn's XGBClassifier/XGBRegressor rather than
from-scratch implementations, and the classifier's only doctest was
already disabled (# THIS TEST IS BROKEN!!), so it was never exercised
in CI.
xgboost is one of the heaviest compiled dependencies in the tree (large
wheel, needs OpenMP/libgomp at runtime, no free-threaded wheel yet), and
gradient boosting is already implemented from scratch in
machine_learning/gradient_boosting_classifier.py and
gradient_boosting_regressor.py, so no algorithm coverage is lost.
Removes the xgboost dependency from pyproject.toml, its (and its
xgboost-only transitive dep nvidia-nccl-cu13) entries from uv.lock, and
the two DIRECTORY.md links.
Refs #15081
* Skill: New pull request for TheAlgorithms/Python
@priya-sundaram-dev, please review and suggest any changes. We want to make sure that the keeper does not close new PRs as invalid.
* updating DIRECTORY.md
* Update pull request instructions in SKILL.md
Clarified instructions for creating a new pull request and emphasized the importance of branch naming.
* Clarify Markdown checkbox requirement for PRs
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
* Skill: fix uv.lock wording; add DIRECTORY.md/README.md auto-gen note (#15216)
- Clarify that uv.lock is regenerated by the uv-lock pre-commit hook when a
legitimate dependency is added; only hand-edits/reverts break the keeper.
- Add a checklist item: DIRECTORY.md and README.md are bot-generated, don't
hand-edit them.
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* Add a table of contents to DIRECTORY.md
Generate a linked table of contents of the top-level sections at the top
of DIRECTORY.md so readers can jump straight to a category, as suggested
in #13239 / #13111. The list is built in scripts/build_directory_md.py
(with a new md_anchor helper + doctests) so DIRECTORY.md stays fully
auto-generated.
* Address review: numbered ToC + link section headings to their directories
- Table of Contents is now a numbered list, so the final number shows the
total count of algorithm folders at a glance.
- Each top-level section heading links to its algorithm directory (e.g.
## [Sorts](sorts)), so clicking a section title jumps straight to the folder.
* feat: add Kelly Criterion and Sharpe Ratio to financial algorithms
* fix: replace ambiguous unicode sigma and shorten long docstring line
* fix: resolve pre-existing ruff errors in hashing, jump_search, and lda
* Apply batched suggestions from code review
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* updating DIRECTORY.md
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* Add missing type hints to hill_climbing.py
This commit adds the missing type annotations to searches/hill_climbing.py.
- Added type annotation for function_to_optimize using Callable [[int, int], int]
- Added return type hints to get_neighbors, __hash__, __eq__, and __str__
- Added missing type hint for search_prob in hill_climbing()
- Improved type clarity while preserving existing logic
- Used modern Python type hints (PEP 585)
This improves readability and typing consistency across the repository.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix unnecessary empty iterable in deque initialization (RUF037)
* Update type hint for objective function to allow float return values
* Update score() return type to support int | float
Mypy reported an incompatible return type because function_to_optimize may return float values.
Updated score() return type from int to int | float for full compatibility.
* Initialize deque with empty list for None values
* updating DIRECTORY.md
---------
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2026-09-05 23:50:24 +02:00
Michael HauseggerTheRealHauiChristian Clausspre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>pre-commit-ci[bot] <pre-commit-ci[bot]@users.noreply.github.com>
* Added some Unit Tests to increase test code coverage
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* updating DIRECTORY.md
---------
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* CPU Scheduling Algorithms with user input
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* updating DIRECTORY.md
---------
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- Added PCA implementation with dataset standardization.
- Used Singular Value Decomposition (SVD) for computing principal components.
- Fixed import sorting to comply with PEP 8 (Ruff I001).
- Ensured type hints and docstrings for better readability.
- Added doctests to validate correctness.
- Passed all Ruff checks and automated tests.
* Add word ladder algorithm in backtracking
* Improve comments and implement ruff checks
* updating DIRECTORY.md
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Change BFS to Backtracking
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* Incorporate PR Changes
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Add type hints for backtrack function
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Implemented KD-Tree Data Structure
* Implemented KD-Tree Data Structure. updated DIRECTORY.md.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Create __init__.py
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Replaced legacy `np.random.rand` call with `np.random.Generator` in kd_tree/example_usage.py
* Replaced legacy `np.random.rand` call with `np.random.Generator` in kd_tree/hypercube_points.py
* added typehints and docstrings
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* docstring for search()
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* Added tests. Updated docstrings/typehints
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* updated tests and used | for type annotations
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* E501 for build_kdtree.py, hypercube_points.py, nearest_neighbour_search.py
* I001 for example_usage.py and test_kdtree.py
* I001 for example_usage.py and test_kdtree.py
* Update data_structures/kd_tree/build_kdtree.py
Co-authored-by: Christian Clauss <cclauss@me.com>
* Update data_structures/kd_tree/example/hypercube_points.py
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* Update data_structures/kd_tree/example/hypercube_points.py
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* Added new test cases requested in Review. Refactored the test_build_kdtree() to include various checks.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Considered ruff errors
* Considered ruff errors
* Apply suggestions from code review
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Update kd_node.py
* imported annotations from __future__
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Implementation of the suffix tree data structure
* Adding data to DIRECTORY.md
* Minor file renaming
* minor correction
* renaming in DIRECTORY.md
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Considering ruff part-1
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* Considering ruff part-2
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* Considering ruff part-3
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* Considering ruff part-4
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Considering ruff part-5
* Implemented Suffix Tree Data Structure.
Added some comments to my files in #11532, #11554.
* updating DIRECTORY.md
* Implemented Suffix Tree Data Structure.
Added some comments to my files in #11532, #11554.
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* Implemented KD-Tree Data Structure
* Implemented KD-Tree Data Structure. updated DIRECTORY.md.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Create __init__.py
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Replaced legacy `np.random.rand` call with `np.random.Generator` in kd_tree/example_usage.py
* Replaced legacy `np.random.rand` call with `np.random.Generator` in kd_tree/hypercube_points.py
* added typehints and docstrings
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* docstring for search()
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Added tests. Updated docstrings/typehints
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* updated tests and used | for type annotations
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* E501 for build_kdtree.py, hypercube_points.py, nearest_neighbour_search.py
* I001 for example_usage.py and test_kdtree.py
* I001 for example_usage.py and test_kdtree.py
* Update data_structures/kd_tree/build_kdtree.py
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* Update data_structures/kd_tree/example/hypercube_points.py
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* Update data_structures/kd_tree/example/hypercube_points.py
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* Added new test cases requested in Review. Refactored the test_build_kdtree() to include various checks.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Considered ruff errors
* Considered ruff errors
* Apply suggestions from code review
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* Update kd_node.py
* imported annotations from __future__
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* updating DIRECTORY.md
* Remove separate directory for gaussian_elimination_pivoting.py
Delete the directory linear_algebra/src/gaussian_elimination_pivoting/
and move its algorithm file, gaussian_elimination_pivoting.py, into the
parent src/ directory. The gaussian_elimination_pivoting/ directory only
exists because gaussian_elimination_pivoting.py reads an example numpy
array from matrix.txt, but this input file and IO operation is entirely
unnecessary because gaussian_elimination_pivoting.py already has the
exact same array hard-coded into a variable.
* updating DIRECTORY.md
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* Remove duplicate implementation of median of two arrays algorithm
Remove maths/median_of_two_arrays.py because the repo has two
implementations of this algorithm, with
data_structures/arrays/median_two_array.py being the other. Even though
maths/median_of_two_arrays.py is the older implementation, the newer
implementation is better documented, has better error handling, and is
already located in a more appropriate directory.
* updating DIRECTORY.md
---------
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priya-sundaram-dev