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Add main workflow action (#20)
* Add main workflow action * lock scikit-learn version to 0.23.2 * exchange codeship badge with githubs
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.github/workflows/main.yml
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.github/workflows/main.yml
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name: CI
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on:
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push:
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branches: [master]
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pull_request:
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branches: [master]
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workflow_dispatch:
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jobs:
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build:
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runs-on: ${{ matrix.os }}
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strategy:
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matrix:
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os: [macos-latest, ubuntu-latest]
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python: [3.8]
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python ${{ matrix.python }}
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python }}
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- name: Install dependencies
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run: |
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pip install -q --upgrade pip
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pip install -q -r requirements.txt
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pip install -q --upgrade codecov coverage black flake8 codacy-coverage
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- name: Lint
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run: |
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black --check --diff stree
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flake8 --count stree
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- name: Tests
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run: |
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coverage run -m unittest -v stree.tests
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coverage xml
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- name: Upload coverage to Codecov
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uses: codecov/codecov-action@v1
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with:
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token: ${{ secrets.CODECOV_TOKEN }}
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files: ./coverage.xml
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- name: Run codacy-coverage-reporter
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if: runner.os == 'Linux'
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uses: codacy/codacy-coverage-reporter-action@master
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with:
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project-token: ${{ secrets.CODACY_PROJECT_TOKEN }}
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coverage-reports: coverage.xml
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16
README.md
16
README.md
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[](https://app.codeship.com/projects/399170)
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[](https://codecov.io/gh/doctorado-ml/stree)
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[](https://www.codacy.com/gh/Doctorado-ML/STree?utm_source=github.com&utm_medium=referral&utm_content=Doctorado-ML/STree&utm_campaign=Badge_Grade)
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[](https://www.codacy.com/gh/Doctorado-ML/STree?utm_source=github.com&utm_medium=referral&utm_content=Doctorado-ML/STree&utm_campaign=Badge_Grade)
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# Stree
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@@ -18,17 +18,17 @@ pip install git+https://github.com/doctorado-ml/stree
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### Jupyter notebooks
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* [](https://mybinder.org/v2/gh/Doctorado-ML/STree/master?urlpath=lab/tree/notebooks/benchmark.ipynb) Benchmark
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- [](https://mybinder.org/v2/gh/Doctorado-ML/STree/master?urlpath=lab/tree/notebooks/benchmark.ipynb) Benchmark
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* [](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/notebooks/benchmark.ipynb) Benchmark
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- [](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/notebooks/benchmark.ipynb) Benchmark
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* [](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/notebooks/features.ipynb) Test features
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- [](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/notebooks/features.ipynb) Test features
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* [](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/notebooks/adaboost.ipynb) Adaboost
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- [](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/notebooks/adaboost.ipynb) Adaboost
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* [](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/notebooks/gridsearch.ipynb) Gridsearch
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- [](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/notebooks/gridsearch.ipynb) Gridsearch
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* [](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/notebooks/test_graphs.ipynb) Test Graphics
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- [](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/notebooks/test_graphs.ipynb) Test Graphics
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### Command line
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numpy
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scikit-learn
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scikit-learn==0.23.2
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pandas
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ipympl
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2
setup.py
2
setup.py
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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"Intended Audience :: Science/Research",
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],
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install_requires=["scikit-learn>=0.23.0", "numpy", "ipympl"],
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install_requires=["scikit-learn==0.23.2", "numpy", "ipympl"],
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test_suite="stree.tests",
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zip_safe=False,
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)
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