使用特定的Miniconda Python和NumPy版本进行CircleCI测试

使用特定的Miniconda Python和NumPy版本进行CircleCI测试,python,circleci,circleci-2.0,Python,Circleci,Circleci 2.0,我正在从事一个使用CircleCI持续集成平台的项目。我使用Python作为主语言,Miniconda作为平台。我想在CircleCI上使用Miniconda测试多个Python和NumPy版本 我尝试使用不同的Python映像,但在安装最新的Miniconda版本时,它只使用Python3.7。你能告诉我如何使用多个版本吗 下面是config.yml: version: 2.0 workflows: version: 2 test: jobs: - py3.6-np

我正在从事一个使用CircleCI持续集成平台的项目。我使用Python作为主语言,Miniconda作为平台。我想在CircleCI上使用Miniconda测试多个Python和NumPy版本

我尝试使用不同的Python映像,但在安装最新的Miniconda版本时,它只使用Python3.7。你能告诉我如何使用多个版本吗

下面是
config.yml

version: 2.0
workflows:
  version: 2
  test:
    jobs:
      - py3.6-np1.15
      - py3.5-np1.15
      - py3.6-np1.14
      - py3.5-np1.14
      - py3.7-np1.15
      - py3.5-np1.16
      - py3.6-np1.16
      - py3.7-np1.16

jobs:
  py3.6-np1.15: &test-template
    docker:
      - image: circleci/python:3.6.8
    environment:
      NUMPY_VERSION: 1.15.2
      CYTHON_VERSION: 0.29.2
    working_directory: ~/repo

    steps:
      - checkout
      - run:
          name: Install System Dependencies
          command: sudo apt-get update && sudo apt-get install -y libmpich12 libmpich-dev build-essential

      # Download and cache dependencies
      - restore_cache:
          keys:
            - v1-dependencies-{{ .Environment.CIRCLE_JOB }}-{{ checksum "setup.py" }}

      - run:
          name: install anaconda
          command: |
            wget https://repo.continuum.io/miniconda/Miniconda3-4.7.10-Linux-x86_64.sh -O ~/miniconda.sh
            chmod +x ~/miniconda.sh && ~/miniconda.sh -b
            export PATH=$HOME/miniconda3/bin:$PATH
            conda update --quiet --yes conda

      - run:
          name: Install numpy, cython, mdtraj
          command: |
            export PATH=$HOME/miniconda3/bin:$PATH
            conda install --quiet --yes numpy==$NUMPY_VERSION cython==$CYTHON_VERSION
            conda install --quiet --yes -c conda-forge mdtraj

      # - run:
      #     name: Upgrade pip
      #     command: |
      #       python3 -m venv venv
      #       . venv/bin/activate
      #       pip install pip==18.0

      # - run:
      #     name: Install numpy and cython
      #     command: |
      #       python3 -m venv venv
      #       . venv/bin/activate
      #       pip install --progress-bar off numpy==$NUMPY_VERSION cython==$CYTHON_VERSION

      - run:
          name: Install and build 
          command: |
            export PATH=$HOME/miniconda3/bin:$PATH
            pip install --progress-bar off .[dev]
            python setup.py build_ext --inplace
            python setup.py install



  py3.5-np1.15:
    <<: *test-template
    docker:
      - image: circleci/python:3.5.7
    environment:
      NUMPY_VERSION: 1.14.2
      CYTHON_VERSION: 0.29.2

  py3.6-np1.14:
    <<: *test-template
    environment:
      NUMPY_VERSION: 1.14.2
      CYTHON_VERSION: 0.29.2

  py3.5-np1.14:
    <<: *test-template
    docker:
      - image: circleci/python:3.5.7
    environment:
      NUMPY_VERSION: 1.14.2
      CYTHON_VERSION: 0.29.2

  py3.7-np1.15:
    <<: *test-template
    docker:
      - image: circleci/python:3.7.3

  py3.5-np1.16:
    <<: *test-template
    docker:
      - image: circleci/python:3.5.7
    environment:
      NUMPY_VERSION: 1.16.5
      CYTHON_VERSION: 0.29.2

  py3.6-np1.16:
    <<: *test-template
    environment:
      NUMPY_VERSION: 1.16.5
      CYTHON_VERSION: 0.29.2

  py3.7-np1.16:
    <<: *test-template
    docker:
      - image: circleci/python:3.7.3
    environment:
      NUMPY_VERSION: 1.16.5
      CYTHON_VERSION: 0.29.2

版本:2.0
工作流程:
版本:2
测试:
工作:
-py3.6-np1.15
-py3.5-np1.15
-py3.6-np1.14
-py3.5-np1.14
-py3.7-np1.15
-py3.5-np1.16
-py3.6-np1.16
-py3.7-np1.16
工作:
py3.6-np1.15:&测试模板
码头工人:
-图:circleci/python:3.6.8
环境:
NUMPY_版本:1.15.2
CYTHON_版本:0.29.2
工作目录:~/repo
步骤:
-结帐
-运行:
名称:安装系统依赖项
命令:sudo apt get update&&sudo apt get install-y libmpich12 libmpich dev build-sential
#下载和缓存依赖项
-还原U缓存:
钥匙:
-v1依赖项-{{.Environment.CIRCLE_JOB}}-{{{checksum“setup.py”}
-运行:
名称:安装anaconda
命令:|
wgethttps://repo.continuum.io/miniconda/Miniconda3-4.7.10-Linux-x86_64.sh -O~/miniconda.sh
chmod+x~/miniconda.sh&~/miniconda.sh-b
导出路径=$HOME/miniconda3/bin:$PATH
康达更新-安静-是康达
-运行:
名称:安装numpy、cython、mdtraj
命令:|
导出路径=$HOME/miniconda3/bin:$PATH
conda安装--安静--是numpy==$numpy\u版本cython==$cython\u版本
conda安装--安静--是-c conda forge mdtraj
#-运行:
#名称:升级pip
#命令:|
#蟒蛇3-m静脉
#       . venv/bin/激活
#pip安装pip==18.0
#-运行:
#名称:安装numpy和cython
#命令:|
#蟒蛇3-m静脉
#       . venv/bin/激活
#pip安装--进程条关闭numpy==$numpy\u版本cython==$cython\u版本
-运行:
名称:安装和生成
命令:|
导出路径=$HOME/miniconda3/bin:$PATH
pip安装--关闭进度条。[dev]
python setup.py build_ext--inplace
python setup.py安装
py3.5-np1.15:

下面是一个关于如何将CircleCI与Miniconda以及特定Python和NumPy版本一起使用的最简单配置示例,从空的
ubuntu:bionic
图像开始

version: 2
jobs:
  build:
    docker:
      - image: ubuntu:bionic
    environment:
      PYTHON_VERSION: 3.5.5
      NUMPY_VERSION: 1.14.2
    steps:
      - checkout
      - run:
          name: Setup Miniconda
          command: |
            apt update
            apt install -y wget
            cd $HOME
            wget "https://repo.anaconda.com/miniconda/Miniconda3-4.7.10-Linux-x86_64.sh" -O miniconda.sh
            printf '%s' "8a324adcc9eaf1c09e22a992bb6234d91a94146840ee6b11c114ecadafc68121  miniconda.sh" | sha256sum -c
            bash miniconda.sh -b -p $HOME/miniconda
      - run:
          name: Setup environment and run tests
          command: |
            export PATH="$HOME/miniconda/bin:$PATH"
            conda update -y conda
            conda create -n myenv python=$PYTHON_VERSION -c conda-forge
            source activate myenv
            conda install -y numpy=$NUMPY_VERSION
            python --version
            python -c "import numpy; print(numpy.__version__)"
我认为在从internet下载Miniconda安装脚本
Miniconda3-4.7.10-Linux-x86_64.sh
后验证校验和是一种很好的做法

您可以更改环境变量
PYTHON\u VERSION
NUMPY\u VERSION
以获得其他版本

除了“真正的”测试之外,目前我们只是要验证我们所需的Python和NumPy版本是否与
Python--version
Python-c“import NumPy;print(NumPy.\uuu version\uuuu)”一起使用
。对于上面的示例,在日志末尾,您应该找到:

Python 3.5.5
1.14.2

根据您选择的版本,可能会出现以下错误:

  • 如果收到
    PackagesNotFoundError
    ,则需要确保所选频道具有您要查找的软件包版本。(如上例中选择了conda forge
。)
  • 如果出现
    unsatifiableerror
    ,则表明您选择了不兼容的软件包版本

  • 以下是多个版本的配置示例:

    version: 2
    
    workflows:
      version: 2
      test:
        jobs:
          - python_3.5
          - python_3.6
          - python_3.7
    
    template: &template
      docker:
        - image: ubuntu:bionic
      steps:
        - checkout
        - run:
            name: Setup Miniconda
            command: |
              apt update
              apt install -y wget
              cd $HOME
              wget "https://repo.anaconda.com/miniconda/Miniconda3-4.7.10-Linux-x86_64.sh" -O miniconda.sh
              printf '%s' "8a324adcc9eaf1c09e22a992bb6234d91a94146840ee6b11c114ecadafc68121  miniconda.sh" | sha256sum -c
              bash miniconda.sh -b -p $HOME/miniconda
        - run:
            name: Setup environment and run tests
            command: |
              export PATH="$HOME/miniconda/bin:$PATH"
              conda update -y conda
              conda create -n myenv python=$PYTHON_VERSION
              source activate myenv
              conda install -y pip numpy=$NUMPY_VERSION
              python --version
              pip --version
              python -c "import numpy; print(numpy.__version__)"
    
    jobs:
      python_3.5:
        <<: *template
        environment:
          PYTHON_VERSION: 3.5
          NUMPY_VERSION: 1.14.2
      python_3.6:
        <<: *template
        environment:
          PYTHON_VERSION: 3.6
          NUMPY_VERSION: 1.15.2
      python_3.7:
        <<: *template
        environment:
          PYTHON_VERSION: 3.7
          NUMPY_VERSION: 1.16.5
    
    版本:2
    工作流程:
    版本:2
    测试:
    工作:
    -python_3.5
    -python_3.6
    -python_3.7
    模板:&模板
    码头工人:
    -图片:ubuntu:bionic
    步骤:
    -结帐
    -运行:
    名称:安装程序Miniconda
    命令:|
    apt更新
    apt安装-y wget
    cd$HOME
    wget“https://repo.anaconda.com/miniconda/Miniconda3-4.7.10-Linux-x86_64.sh“-O miniconda.sh
    打印文件“%s”8A324ADCC9EAF1C09E22A992BB6234D91A94146840EE6B1C114ECADAFC68121 miniconda.sh“| sha256sum-c
    bash miniconda.sh-b-p$HOME/miniconda
    -运行:
    名称:安装环境并运行测试
    命令:|
    导出路径=“$HOME/miniconda/bin:$PATH”
    康达更新-y康达
    conda create-n myenv python=$python\u版本
    源代码激活myenv
    conda安装-y pip numpy=$numpy\u版本
    python——版本
    pip——版本
    python-c“导入numpy;打印(numpy.\uuuu版本)”
    工作:
    python_3.5:
    
    尝试了,这就是收集包元数据(current_repodata.json)的结果:…正在工作。。。已完成解决环境:…正在工作。。。初始冻结解算失败。用灵活的解决方法重试。正在收集包元数据(repodata.json):…正在工作。。。已完成解决环境:…正在工作。。。初始冻结解算失败。用灵活的解决方法重试。PackagesNotFoundError:以下软件包无法从当前频道获得:-//repo.continuum.io/miniconda/miniconda3-4.7.10-linux-x86_64.shI遇到了一个奇怪的问题。前两个测试没有运行,因为它安装了3.7版本。即使删除了
    shell:/bin/bash
    也可以检查这个和这个,这没关系。结果仍然如此。我也看不到echo$PYTHON\u版本的输出。怎么可能在两份工作中都是空的,而在第三份工作中又是空的呢?最后一部分是有效的。请不要忘记将最后一段添加到当前帖子中,我将标记为答案并添加非常感谢。最后一个问题是如何让缓存操作(保存缓存和恢复缓存)发挥作用?因为没有它们运行测试太长了。他
    version: 2.0
    
    workflows:
      version: 2
      test:
        jobs:
          - py3.6-np1.15
          - py3.5-np1.15
          - py3.6-np1.14
          - py3.5-np1.14
          - py3.7-np1.15
          - py3.6-np1.16
          - py3.7-np1.16
    
    test-template: &test-template
      docker:
        - image: ubuntu:bionic
      steps:
        - checkout
        - run:
            name: Install System Dependencies
            command: apt-get update && apt-get install -y libmpich12 libmpich-dev build-essential
    
        # Download and cache dependencies
        - restore_cache:
            keys:
              - v1-dependencies-{{ .Environment.CIRCLE_JOB }}-{{ checksum "setup.py" }}
    
        - run:
            name: install anaconda
            command: |
              apt update
              apt install -y wget
              cd $HOME
              wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh
              chmod +x ~/miniconda.sh && bash ~/miniconda.sh -b -p $HOME/miniconda
              export PATH=$HOME/miniconda/bin:$PATH
    
        - run:
            name: Install numpy, cython, mdtraj
            command: |
              export PATH="$HOME/miniconda/bin:$PATH"
              conda update  --yes conda
              echo $PYTHON_VERSION
              conda create -n myenv python=$PYTHON_VERSION -c conda-forge
              source activate myenv
              conda install --yes pip
              conda install --yes -c conda-forge numpy=$NUMPY_VERSION cython=$CYTHON_VERSION
              conda install --yes -c conda-forge nose mdtraj  
              python --version
              python -c "import numpy; print(numpy.__version__)"
    
        - run:
            name: Install and build package
            command: |
              export PATH=$HOME/miniconda/bin:$PATH
              source activate myenv
              pip install --progress-bar off .[dev]
              python setup.py build_ext --inplace
              python setup.py install
    
        - save_cache:
            paths:
              - ~/miniconda
            key: v1-dependencies-{{ checksum "setup.py" }}
    
        - run:
            name: Run non-MPI tests
            command: |
              export PATH=$HOME/miniconda/bin:$PATH
              source activate myenv
              nosetests -a '!mpi' package
    
        - run:
            name: Run MPI tests
            command: |
              export PATH=$HOME/miniconda/bin:$PATH
              source activate myenv
              OMP_NUM_THREADS=1 mpiexec -n 2 nosetests -a mpi package
    
        - store_artifacts:
            path: test-reports
            destination: test-reports
    
    jobs:
      py3.6-np1.15:
        <<: *test-template
        environment:
          NUMPY_VERSION: 1.14.2
          CYTHON_VERSION: 0.26.1
          PYTHON_VERSION: 3.6
    
      py3.5-np1.15:
        <<: *test-template
        environment:
          NUMPY_VERSION: 1.14.2
          CYTHON_VERSION: 0.26.1
          PYTHON_VERSION: 3.5
    
      py3.6-np1.14:
        <<: *test-template
        environment:
          NUMPY_VERSION: 1.14.2
          CYTHON_VERSION: 0.26.1
          PYTHON_VERSION: 3.6
    
      py3.5-np1.14:
        <<: *test-template
        environment:
          NUMPY_VERSION: 1.14.2
          CYTHON_VERSION: 0.26.1
          PYTHON_VERSION: 3.5
    
      py3.7-np1.15:
        <<: *test-template
        environment:
          NUMPY_VERSION: 1.15.2
          CYTHON_VERSION: 0.26.1
          PYTHON_VERSION: 3.7.1
    
      py3.6-np1.16:
        <<: *test-template
        environment:
          NUMPY_VERSION: 1.16.5
          CYTHON_VERSION: 0.26.1
          PYTHON_VERSION: 3.6
    
      py3.7-np1.16:
        <<: *test-template
        environment:
          NUMPY_VERSION: 1.16.5
          CYTHON_VERSION: 0.29.2
          PYTHON_VERSION: 3.7.1