MNT/CI drop python 3.5 (#683)

Author: glemaitre

.travis.yml

@@ -28,17 +28,13 @@ env:
 
 matrix:
   include:
-    # This environment tests the using anaconda
-    # Ubuntu 14.04 environment
-    - env: DISTRIB="ubuntu" TEST_DOC="true" TEST_NUMPYDOC="false"
-    # Latest release
-    - env: DISTRIB="conda" PYTHON_VERSION="3.7"
+    - env: PYTHON_VERSION="3.7"
            NUMPY_VERSION="*" SCIPY_VERSION="*" SKLEARN_VERSION="master"
            OPTIONAL_DEPS="keras" TEST_DOC="true" TEST_NUMPYDOC="false"
-    - env: DISTRIB="conda" PYTHON_VERSION="3.7"
+    - env: PYTHON_VERSION="3.7"
            NUMPY_VERSION="*" SCIPY_VERSION="*" SKLEARN_VERSION="master"
            OPTIONAL_DEPS="tensorflow" TEST_DOC="true" TEST_NUMPYDOC="false"
-    - env: DISTRIB="conda" PYTHON_VERSION="3.7"
+    - env: PYTHON_VERSION="3.7"
            NUMPY_VERSION="*" SCIPY_VERSION="*" SKLEARN_VERSION="master"
            OPTIONAL_DEPS="false" TEST_DOC="false" TEST_NUMPYDOC="true"
 

README.rst

@@ -52,8 +52,8 @@ Dependencies
 imbalanced-learn is tested to work under Python 3.6+.
 The dependency requirements are based on the last scikit-learn release:
 
-* scipy(>=0.17)
-* numpy(>=1.11)
+* scipy(>=0.19.1)
+* numpy(>=1.13.3)
 * scikit-learn(>=0.22)
 * joblib(>=0.11)
 * keras 2 (optional)

azure-pipelines.yml

@@ -3,7 +3,7 @@ jobs:
 - job: linting
   displayName: Linting
   pool:
-    vmImage: ubuntu-16.04
+    vmImage: ubuntu-18.04
   steps:
     - bash: echo "##vso[task.prependpath]$CONDA/bin"
       displayName: Add conda to PATH
@@ -19,15 +19,15 @@ jobs:
 - template: build_tools/azure/posix.yml
   parameters:
     name: Linux
-    vmImage: ubuntu-16.04
+    vmImage: ubuntu-18.04
     dependsOn: [linting]
     matrix:
       # Linux environment to test that scikit-learn can be built against
-      # versions of numpy, scipy with ATLAS that comes with Ubuntu Xenial 16.04
-      # i.e. numpy 1.11 and scipy 0.17
-      py35_ubuntu_atlas:
+      # versions of numpy, scipy with ATLAS that comes with Ubuntu Bionic 18.04
+      # i.e. numpy 1.13.3 and scipy 0.19
+      py36_ubuntu_atlas:
         DISTRIB: 'ubuntu'
-        PYTHON_VERSION: '3.5'
+        PYTHON_VERSION: '3.6'
         JOBLIB_VERSION: '*'
       # Linux environment to test the latest available dependencies and MKL.
       pylatest_pip_openblas_pandas:
@@ -60,12 +60,12 @@ jobs:
 - template: build_tools/azure/posix-32.yml
   parameters:
     name: Linux32
-    vmImage: ubuntu-16.04
+    vmImage: ubuntu-18.04
     dependsOn: [linting]
     matrix:
-      py35_ubuntu_atlas_32bit:
+      py36_ubuntu_atlas_32bit:
         DISTRIB: 'ubuntu-32'
-        PYTHON_VERSION: '3.5'
+        PYTHON_VERSION: '3.6'
         JOBLIB_VERSION: '*'
         TEST_DOCSTRINGS: 'true'
 
@@ -100,6 +100,6 @@ jobs:
         PYTEST_VERSION: '*'
         COVERAGE: 'true'
         CHECK_WARNINGS: 'true'
-      py35_pip_openblas_32bit:
-        PYTHON_VERSION: '3.5'
+      py36_pip_openblas_32bit:
+        PYTHON_VERSION: '3.6'
         PYTHON_ARCH: '32'

build_tools/azure/install.sh

@@ -1,6 +1,7 @@
 #!/bin/bash
 
 set -e
+set -x
 
 UNAMESTR=`uname`
 
@@ -70,14 +71,14 @@ if [[ "$DISTRIB" == "conda" ]]; then
 elif [[ "$DISTRIB" == "ubuntu" ]]; then
     sudo add-apt-repository --remove ppa:ubuntu-toolchain-r/test
     sudo apt-get update
-    sudo apt-get install python3-scipy libatlas3-base libatlas-base-dev libatlas-dev python3-virtualenv git
+    sudo apt-get install python3-scipy libatlas3-base libatlas-base-dev python3-virtualenv git
     python3 -m virtualenv --system-site-packages --python=python3 $VIRTUALENV
     source $VIRTUALENV/bin/activate
     python -m pip install pytest==$PYTEST_VERSION pytest-cov joblib cython
     python -m pip install git+https://github.com/scikit-learn/scikit-learn.git
 elif [[ "$DISTRIB" == "ubuntu-32" ]]; then
     apt-get update
-    apt-get install -y python3-dev python3-scipy libatlas3-base libatlas-base-dev libatlas-dev python3-virtualenv git
+    apt-get install -y python3-dev python3-scipy libatlas3-base libatlas-base-dev python3-virtualenv git
     python3 -m virtualenv --system-site-packages --python=python3 $VIRTUALENV
     source $VIRTUALENV/bin/activate
     python -m pip install pytest==$PYTEST_VERSION pytest-cov joblib cython

build_tools/azure/posix-32.yml

@@ -40,7 +40,7 @@ jobs:
         -e OMP_NUM_THREADS=$OMP_NUM_THREADS
         -e OPENBLAS_NUM_THREADS=$OPENBLAS_NUM_THREADS
         -e SKLEARN_SKIP_NETWORK_TESTS=$SKLEARN_SKIP_NETWORK_TESTS
-        i386/ubuntu:16.04
+        i386/ubuntu:18.04
         sleep 1000000
       displayName: 'Start container'
     - script: >

build_tools/travis/install.sh

@@ -17,57 +17,43 @@ export CXX=/usr/lib/ccache/g++
 # ~60M is used by .ccache when compiling from scratch at the time of writing
 ccache --max-size 100M --show-stats
 
-if [[ "$DISTRIB" == "conda" ]]; then
-    # Deactivate the travis-provided virtual environment and setup a
-    # conda-based environment instead
-    deactivate
+# Deactivate the travis-provided virtual environment and setup a
+# conda-based environment instead
+deactivate
 
-    # Install miniconda
-    wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh \
-        -O miniconda.sh
-    MINICONDA_PATH=/home/travis/miniconda
-    chmod +x miniconda.sh && ./miniconda.sh -b -p $MINICONDA_PATH
-    export PATH=$MINICONDA_PATH/bin:$PATH
+# Install miniconda
+wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh \
+    -O miniconda.sh
+MINICONDA_PATH=/home/travis/miniconda
+chmod +x miniconda.sh && ./miniconda.sh -b -p $MINICONDA_PATH
+export PATH=$MINICONDA_PATH/bin:$PATH
 
-    # Configure the conda environment and put it in the path using the
-    # provided versions
-    conda create -n testenv --yes python=$PYTHON_VERSION pip
-    source activate testenv
-    conda install --yes numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION
+# Configure the conda environment and put it in the path using the
+# provided versions
+conda create -n testenv --yes python=$PYTHON_VERSION pip
+source activate testenv
 
-    if [[ "$OPTIONAL_DEPS" == "keras" ]]; then
-        conda install --yes pandas keras tensorflow=1
-        KERAS_BACKEND=tensorflow
-        python -c "import keras.backend"
-        sed -i -e 's/"backend":[[:space:]]*"[^"]*/"backend":\ "'$KERAS_BACKEND'/g' ~/.keras/keras.json;
-    elif [[ "$OPTIONAL_DEPS" == "tensorflow" ]]; then
-        conda install --yes pandas tensorflow
-    fi
+pip install --upgrade pip setuptools
+echo "Installing numpy and scipy master wheels"
+dev_url=https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackcdn.com
+pip install --pre --upgrade --timeout=60 -f $dev_url numpy scipy pandas cython
+echo "Installing joblib master"
+pip install https://github.com/joblib/joblib/archive/master.zip
 
-    if [[ "$SKLEARN_VERSION" == "master" ]]; then
-        pip install --pre -f https://sklearn-nightly.scdn8.secure.raxcdn.com scikit-learn
-    else
-        conda install --yes scikit-learn=$SKLEARN_VERSION
-    fi
-
-    conda install --yes pytest pytest-cov
-    pip install codecov
-    pip install -U git+https://github.com/numpy/numpydoc.git
-
-elif [[ "$DISTRIB" == "ubuntu" ]]; then
-    # At the time of writing numpy 1.9.1 is included in the travis
-    # virtualenv but we want to use the numpy installed through apt-get
-    # install.
-    deactivate
-    # Create a new virtualenv using system site packages for python, numpy
-    virtualenv --system-site-packages --python=python3 testvenv
-    source testvenv/bin/activate
+if [[ "$OPTIONAL_DEPS" == "keras" ]]; then
+    conda install --yes keras tensorflow=1
+    KERAS_BACKEND=tensorflow
+    python -c "import keras.backend"
+    sed -i -e 's/"backend":[[:space:]]*"[^"]*/"backend":\ "'$KERAS_BACKEND'/g' ~/.keras/keras.json;
+elif [[ "$OPTIONAL_DEPS" == "tensorflow" ]]; then
+    conda install --yes tensorflow
+fi
 
-    pip install --pre -f https://sklearn-nightly.scdn8.secure.raxcdn.com scikit-learn
-    pip3 install pandas
-    pip3 install pytest pytest-cov codecov sphinx numpydoc
+pip install --pre --extra-index https://pypi.anaconda.org/scipy-wheels-nightly/simple scikit-learn
 
-fi
+conda install --yes pytest pytest-cov
+pip install codecov
+pip install -U git+https://github.com/numpy/numpydoc.git
 
 python --version
 python -c "import numpy; print('numpy %s' % numpy.__version__)"

doc/install.rst

@@ -7,16 +7,17 @@ Prerequisites
 
 The imbalanced-learn package requires the following dependencies:
 
-* numpy (>=1.11)
-* scipy (>=0.17)
+* python (>=3.6)
+* numpy (>=1.13.3)
+* scipy (>=0.19.1)
 * scikit-learn (>=0.22)
 * keras 2 (optional)
 * tensorflow (optional)
 
 Install
 =======
 
-imbalanced-learn is currently available on the PyPi's reporitories and you can
+imbalanced-learn is currently available on the PyPi's repositories and you can
 install it via `pip`::
 
   pip install -U imbalanced-learn

setup.py

@@ -36,8 +36,8 @@
                'Programming Language :: Python :: 3.7',
                'Programming Language :: Python :: 3.8']
 INSTALL_REQUIRES = [
-    'numpy>=1.11',
-    'scipy>=0.17',
+    'numpy>=1.13.3',
+    'scipy>=0.19.1',
     'scikit-learn>=0.22',
     'joblib>=0.11'
 ]