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Release v0.1.3
 --------- Signed-off-by: Adam Li <adam2392@gmail.com>
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‎.github/workflows/build_wheels.yml‎

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- "**.py"
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- "**.pxd"
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- "**.pyx"
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- "**"
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push:
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branches: [main]
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workflow_dispatch:
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- uses: actions/upload-artifact@v3
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with:
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path: ./wheelhouse/*.whl
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path: ./wheelhouse/
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name: ${{ matrix.python[0] }}-${{ matrix.os[1] }}
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# TODO: let's figure out how to build these wheels?
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# build_wheels_macos:
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# name: Build wheels on macos-11
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# runs-on: macos-11
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# steps:
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# - uses: actions/checkout@v3
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# - uses: actions/setup-python@v4.6.1
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# with:
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# python-version: 3.9
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# - name: macosx_arm64 - setup builddir
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# run: |
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# python -m pip wheel --config-settings builddir=build .
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# - name: Build wheels
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# uses: pypa/cibuildwheel@v2.13.1
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# env:
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# CIBW_ARCHS_MACOS: arm64
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# - uses: actions/upload-artifact@v3
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# with:
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# path: ./wheelhouse/*.whl
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build-wheels-m1:
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name: Build wheels on Arm M1 with Python ${{ matrix.python[0] }}
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runs-on: macos-latest
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strategy:
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# Ensure that a wheel builder finishes even if another fails
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fail-fast: false
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matrix:
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python: [["cp39", "3.9"], ["cp310", "3.10"], ["cp311", "3.11"]]
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# python[0] is used to specify the python versions made by cibuildwheel
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steps:
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- name: Checkout code
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uses: actions/checkout@v3
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- name: Set up Python
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uses: actions/setup-python@v4.6.1
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with:
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python-version: 3.9 # Replace with the desired Python version
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- name: Install cibuildwheel dependencies
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run: |
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python -m pip install cibuildwheel
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python -m pip install -r build_requirements.txt
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python -m pip install spin
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python spin setup-submodule
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- name: Build wheels
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uses: pypa/cibuildwheel@v2.13.1
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env:
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CIBW_BUILD: ${{ matrix.python[0] }}-macosx_arm64
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CIBW_ARCHS_MACOS: arm64
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- uses: actions/upload-artifact@v3
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with:
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path: ./wheelhouse
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name: ${{ matrix.python[0] }}-arm
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# Build the source distribution under Linux
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build_sdist:
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name: Source distribution
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runs-on: ubuntu-latest
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steps:
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- name: Checkout scikit-tree
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uses: actions/checkout@v3
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- name: Setup Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.9' # update once build dependencies are available
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- name: Build source distribution
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run: |
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python -m pip install -r build_requirements.txt
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python -m pip install spin
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python spin setup-submodule
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python spin sdist
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# run: bash build_tools/github/build_source.sh
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# env:
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# SKLEARN_BUILD_PARALLEL: 3
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# - name: Test source distribution
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# run: bash build_tools/github/test_source.sh
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# env:
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# SKLEARN_SKIP_NETWORK_TESTS: 1
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- name: Store artifacts
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uses: actions/upload-artifact@v3
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with:
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path: dist/*.tar.gz
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- uses: actions/upload-artifact@v3
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with:
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path: dist
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name: ${{ matrix.python[0] }}-${{ matrix.os[1] }}

‎.github/workflows/main.yml‎

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fail-fast: false
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matrix:
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os: [ubuntu-22.04, macos-latest]
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python-version: [3.8, 3.9, "3.10"]
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python-version: [3.9, "3.10", "3.11"]
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poetry-version: [1.3.0]
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runs-on: ${{ matrix.os }}
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defaults:
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- name: pip-packages
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run: |
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pip install -r build_requirements.txt
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pip install -r test_requirements.txt
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pip install spin
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pip install numpy==1.22.4
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- name: openblas-libs
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# shell: bash

‎.github/workflows/style.yml‎

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steps:
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- name: Checkout repository
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uses: actions/checkout@v3
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- name: Setup Python 3.9
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- name: Setup Python 3.10
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uses: actions/setup-python@v4.6.1
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with:
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python-version: "3.9"
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python-version: "3.10"
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architecture: "x64"
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- name: Install packages for Ubuntu

‎.gitmodules‎

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[submodule "sktree/_lib/sklearn"]
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path = sktree/_lib/sklearn_fork
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url = https://github.com/neurodata/scikit-learn
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branch = submodulev2
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branch = v1.3

‎.spin/cmds.py‎

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# run build as normal
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ctx.invoke(meson.build, meson_args=meson_args, jobs=jobs, clean=clean, verbose=verbose)
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@click.command()
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def sdist():
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"""📦 Build a source distribution in `dist/`"""
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util.run(["python", "-m", "build", ".", "--sdist"])

‎DEVELOPING.md‎

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The general design of scikit-tree follows that of the tree-models inside scikit-learn, where tree-based models are inherently Cythonized, or written with C++. Then the actual forest (e.g. RandomForest, or ExtraForest) is just a Python API wrapper that creates an ensemble of the trees.
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In order to develop new tree models, generally Cython and C++ code will need to be written in order to optimize the tree building process, otherwise fitting a single forest model would take very long.
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# Making a Release
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Scikit-tree is in-line with scikit-learn and thus relies on each new version released there. Moreover, scikit-tree relies on compiled code, so releases are a bit more complex than the typical Python package.
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1. Download wheels from GH Actions and put all wheels into a ``dist/`` folder
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https://github.com/neurodata/scikit-tree/actions/workflows/build_wheels.yml will have all the wheels for common OSes built for each Python version.
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2. Upload wheels to test PyPi
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twine upload --repository-url https://test.pypi.org/legacy/ dist/*
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Verify that installations work as expected on your machine.
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3. Upload wheels
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twine upload dist/*
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4. Update version number on ``meson.build`` and ``_version.py`` to the relevant version.

‎build_requirements.txt‎

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doit
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pydevtool
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spin
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build

‎examples/overlapping_gaussians.png‎

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‎meson.build‎

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# Note that the git commit hash cannot be added dynamically here
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# That only happens when importing from a git repository.
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# See `sktree/__init__.py`
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version: '0.0.0.dev0',
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version: '0.1.3',
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license: 'BSD-3',
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meson_version: '>= 0.64.0',
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default_options: [
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error('MESON_BUILD_FAILED: Cython3 not found. Please install it.')
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endif
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run_command('git', 'submodule', 'update', '--init', check: true)
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# r = run_command('git', 'submodule', 'update', '--init', check: false)
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r = run_command('mv', 'sktree/_lib/sklearn_fork/sklearn', 'sktree/_lib/sklearn', check: false)
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# Setup Python:
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# https://mesonbuild.com/Python-module.html
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# print some debugging output
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message(py3.full_path())
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message(py3.get_install_dir())
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if py3.language_version().version_compare('<3.8')
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error('At least Python 3.8 is required.')
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if py3.language_version().version_compare('<3.9')
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error('At least Python 3.9 is required.')
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endif
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py3_dep = py3.dependency()
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‎pyproject.toml‎

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[project]
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name = "sktree"
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#
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# 0.0.0 is standard placeholder for poetry-dynamic-versioning
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# any changes to this should not be checked in
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#
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version = "0.1.3"
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description = "Modern decision trees in Python"
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maintainers = [
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{name="Neurodata", email="adam.li@columbia.edu"}
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]
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documentation = "https://scikit-tree.neurodata.io"
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repository = "https://github.com/neurodata/scikit-tree"
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readme = "README.md"
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requires-python = ">=3.9"
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classifiers = [
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'Development Status :: 4 - Beta',
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"Intended Audience :: Science/Research",
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"Intended Audience :: Developers",
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"License :: OSI Approved :: BSD License",
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"Programming Language :: C",
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"Programming Language :: Python",
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"Programming Language :: Python :: 3",
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'Programming Language :: Python :: 3.9',
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'Programming Language :: Python :: 3.10',
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'Programming Language :: Python :: 3.11',
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"Topic :: Scientific/Engineering",
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"Operating System :: Microsoft :: Windows",
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"Operating System :: POSIX :: Linux",
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"Operating System :: POSIX",
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"Operating System :: Unix",
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"Operating System :: MacOS",
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]
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keywords = ['tree', 'oblique trees', 'manifold-learning', 'scikit-learn']
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include = [
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{ path = "meson.build", format = "sdist" },
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]
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[tool.poetry]
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name = "sktree"
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#
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readme = "README.md"
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classifiers = [
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'Development Status :: 4 - Beta',
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'License :: OSI Approved :: BSD-3 License',
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'Programming Language :: Python :: 3.8',
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'Programming Language :: Python :: 3.9',
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'Programming Language :: Python :: 3.10',
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'Programming Language :: Python :: 3.11',
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# "spin.cmds.meson.build",
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".spin/cmds.py:build",
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".spin/cmds.py:setup_submodule",
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".spin/cmds.py:sdist",
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"spin.cmds.meson.test",
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]
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Environments = [

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