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MNT Use cibuildwheel to build the wheels with [cd build] (#17921)
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‎.github/workflows/wheels.yml‎

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# Workflow to build and test wheels
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name: Wheel builder
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on:
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schedule:
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# Nightly build at 3:42 A.M.
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- cron: "42 3 */1 * *"
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push:
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branches:
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# Release branches
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- "[0-9]+.[0-9]+.X"
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pull_request:
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branches:
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- master
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- "[0-9]+.[0-9]+.X"
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env:
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SCIKIT_LEARN_VERSION: 0.24.dev0
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jobs:
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# Check whether to build the wheels and the source tarball
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check_build_trigger:
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name: Check build trigger
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runs-on: ubuntu-latest
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outputs:
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build: ${{ steps.check_build_trigger.outputs.build }}
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steps:
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- name: Checkout scikit-learn
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uses: actions/checkout@v1
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- id: check_build_trigger
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name: Check build trigger
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run: bash build_tools/github/check_build_trigger.sh
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# Build the wheels for Linux, Windows and macOS for Python 3.6 and newer
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build_wheels:
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name: Build wheels on ${{ matrix.os }} for Python ${{ matrix.python }}
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runs-on: ${{ matrix.os }}
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needs: check_build_trigger
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if: needs.check_build_trigger.outputs.build
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strategy:
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# Ensure that a wheel builder finishes even if another fails
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fail-fast: false
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matrix:
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os: [windows-latest, ubuntu-latest, macos-latest]
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python: [36, 37, 38, 39]
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steps:
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- name: Checkout scikit-learn
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uses: actions/checkout@v1
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- name: Setup Python
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uses: actions/setup-python@v2
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- name: Build and test wheels
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env:
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# Set the directory where the wheel is unpacked
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CIBW_ENVIRONMENT: "WHEEL_DIRNAME=scikit_learn-$SCIKIT_LEARN_VERSION"
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CIBW_BUILD: cp${{ matrix.python }}-*
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CIBW_TEST_REQUIRES: pytest pandas threadpoolctl
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# Test that there are no links to system libraries
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CIBW_TEST_COMMAND: pytest --pyargs sklearn &&
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python -m threadpoolctl -i sklearn
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# By default, the Windows wheels are not repaired.
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# In this case, we need to vendor the vcomp140.dll
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CIBW_REPAIR_WHEEL_COMMAND_WINDOWS: wheel unpack {wheel} &&
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python build_tools/github/vendor_vcomp140.py %WHEEL_DIRNAME% &&
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wheel pack %WHEEL_DIRNAME% -d {dest_dir} &&
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rmdir /s /q %WHEEL_DIRNAME%
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run: bash build_tools/github/build_wheels.sh
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- name: Store artifacts
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uses: actions/upload-artifact@v2
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with:
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path: wheelhouse/*.whl
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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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needs: check_build_trigger
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if: needs.check_build_trigger.outputs.build
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steps:
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- name: Checkout scikit-learn
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uses: actions/checkout@v1
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- name: Setup Python
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uses: actions/setup-python@v2
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- name: Build and test source distribution
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run: bash build_tools/github/build_source.sh
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- name: Store artifacts
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uses: actions/upload-artifact@v2
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with:
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path: dist/*.tar.gz
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# Upload the wheels and the source distribution
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upload_anaconda:
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name: Upload to Anaconda
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runs-on: ubuntu-latest
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needs: [build_wheels, build_sdist]
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# The artifacts are not be uploaded on PRs
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if: github.event_name != 'pull_request'
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steps:
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- name: Download artifacts
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uses: actions/download-artifact@v2
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with:
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path: dist
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- name: Setup Python
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uses: actions/setup-python@v2
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- name: Upload artifacts
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env:
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# Secret variables need to be mapped to environment variables explicitly
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SCIKIT_LEARN_NIGHTLY_UPLOAD_TOKEN: ${{ secrets.SCIKIT_LEARN_NIGHTLY_UPLOAD_TOKEN }}
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SCIKIT_LEARN_STAGING_UPLOAD_TOKEN: ${{ secrets.SCIKIT_LEARN_STAGING_UPLOAD_TOKEN }}
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# Force a replacement if the remote file already exists
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run: bash build_tools/github/upload_anaconda.sh

‎build_tools/github/build_source.sh‎

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#!/bin/bash
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set -e
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set -x
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python -m pip install numpy scipy cython
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python -m pip install twine
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python -m pip install pytest pandas
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python setup.py sdist
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python -m pip install dist/*.tar.gz
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python setup.py build_ext -i
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pytest --pyargs sklearn
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# Check whether the source distribution will render correctly
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twine check dist/*.tar.gz

‎build_tools/github/build_wheels.sh‎

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#!/bin/bash
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set -e
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set -x
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# OpenMP is not present on macOS by default
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if [ "$RUNNER_OS" == "macOS" ]; then
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brew install libomp
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export CC=/usr/bin/clang
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export CXX=/usr/bin/clang++
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export CPPFLAGS="$CPPFLAGS -Xpreprocessor -fopenmp"
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export CFLAGS="$CFLAGS -I/usr/local/opt/libomp/include"
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export CXXFLAGS="$CXXFLAGS -I/usr/local/opt/libomp/include"
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export LDFLAGS="$LDFLAGS -Wl,-rpath,/usr/local/opt/libomp/lib -L/usr/local/opt/libomp/lib -lomp"
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fi
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# The version of the built dependencies are specified
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# in the pyproject.toml file, while the tests are run
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# against the most recent version of the dependencies
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python -m pip install cibuildwheel
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python -m cibuildwheel --output-dir wheelhouse

‎build_tools/github/check_build_trigger.sh‎

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#!/bin/bash
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set -e
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set -x
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COMMIT_MSG=$(git log --no-merges -1 --oneline)
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# The commit marker "[cd build]" will trigger the build when required
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if [[ "$GITHUB_EVENT_NAME" == push ||
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"$GITHUB_EVENT_NAME" == schedule ||
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"$COMMIT_MSG" =~ \[cd\ build\] ]]; then
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echo "::set-output name=build::true"
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fi

‎build_tools/github/upload_anaconda.sh‎

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#!/bin/bash
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set -e
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set -x
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if [ "$GITHUB_EVENT_NAME" == "schedule" ]; then
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ANACONDA_ORG="scipy-wheels-nightly"
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ANACONDA_TOKEN="$SCIKIT_LEARN_NIGHTLY_UPLOAD_TOKEN"
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else
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ANACONDA_ORG="scikit-learn-wheels-staging"
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ANACONDA_TOKEN="$SCIKIT_LEARN_STAGING_UPLOAD_TOKEN"
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fi
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conda install -q -y anaconda-client
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# Force a replacement if the remote file already exists
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anaconda -t $ANACONDA_TOKEN upload --force -u $ANACONDA_ORG dist/*
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echo "Index: https://pypi.anaconda.org/$ANACONDA_ORG/simple"

‎build_tools/github/vendor_vcomp140.py‎

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"""Embed vcomp140.dll after generating the scikit-learn Windows wheel."""
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import os
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import os.path as op
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import shutil
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import sys
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import textwrap
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TARGET_FOLDER = op.join("sklearn", ".libs")
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DISTRIBUTOR_INIT = op.join("sklearn", "_distributor_init.py")
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VCOMP140_SRC_PATH = "C:\\Windows\System32\\vcomp140.dll" # noqa
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def make_distributor_init(distributor_init, dll_filename):
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"""Create a _distributor_init.py file for the vcomp140.dll.
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This file is imported first when importing the
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sklearn package so as to pre-load the vendored
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vcomp140.dll.
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"""
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with open(distributor_init, "wt") as f:
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f.write(textwrap.dedent("""
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'''Helper to preload vcomp140.dll to prevent "not found" errors.
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Once the vcomp140.dll is preloaded, the namespace is made
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available to any subsequent vcomp140.dll. This is created
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as part of the scripts that build the wheel.
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'''
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import os
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import os.path as op
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from ctypes import WinDLL
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if os.name == "nt":
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# Load the vcomp140.dll in sklearn/.libs by convention
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dll_path = op.join(op.dirname(__file__), ".libs", "{0}")
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WinDLL(op.abspath(dll_path))
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""".format(dll_filename)))
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def main(wheel_dirname):
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"""Embed the vcomp140.dll in the wheel."""
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if not op.exists(VCOMP140_SRC_PATH):
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raise ValueError(f"Could not find {VCOMP140_SRC_PATH}.")
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if not op.isdir(wheel_dirname):
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raise RuntimeError(f"Could not find {wheel_dirname} file.")
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dll_filename = op.basename(VCOMP140_SRC_PATH)
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target_folder = op.join(wheel_dirname, TARGET_FOLDER)
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distributor_init = op.join(wheel_dirname, DISTRIBUTOR_INIT)
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# Create the "sklearn/.libs" subfolder
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if not op.exists(target_folder):
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os.mkdir(target_folder)
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print(f"Copying {VCOMP140_SRC_PATH} to {target_folder}.")
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shutil.copy2(VCOMP140_SRC_PATH, target_folder)
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# Generate the _distributor_init file in the source tree
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print("Generating the '_distributor_init.py' file.")
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make_distributor_init(distributor_init, dll_filename)
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if __name__ == "__main__":
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_, wheel_file = sys.argv
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main(wheel_file)

‎doc/developers/contributing.rst‎

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Commit Message Marker Action Taken by CI
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---------------------- -------------------
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[ci skip] CI is skipped completely
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[cd build] CD is run (wheels and source distribution are built)
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[lint skip] Azure pipeline skips linting
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[scipy-dev] Add a Travis build with our dependencies (numpy, scipy, etc ...) development builds
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[icc-build] Add a Travis build with the Intel C compiler (ICC)

‎sklearn/cross_decomposition/tests/test_pls.py‎

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pls.predict(X.copy(), copy=False))
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@pytest.mark.xfail
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@pytest.mark.parametrize('Est', (CCA, PLSCanonical, PLSRegression, PLSSVD))
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def test_scale_and_stability(Est):
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# scale=True is equivalent to scale=False on centered/scaled data

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