This action sets up a base conda environment by one of:

• locating the conda installation bundled with the available runners and available in $CONDA
• installing a specific (or latest) version of
  • Miniconda3
  • Miniforge (or Mambaforge)
  • any constructor-based installer by or URL or filesystem path

A conda-build-version or mamba-version may be provided to install into base.

The base condabin/ folder is added to $PATH and shell integration is initialized across all platforms.

By default, this action will then create, and activate, an environment by one of:

• creating a mostly-empty test environment, containing only the latest python-version and its dependencies
• creating an test environment described in a given environment-file:
  • an environment.yml-like file (which can be patched with python-version)
    • the patched environment will be cleaned up unless clean-patched-environment-file: false is given
  • a lockfile

This action correctly handles activation of environments and offers the possibility of automatically activating the test environment on all shells.

Please see the IMPORTANT notes on additional information on environment activation.

Each of the examples below is discussed in a dedicated section below.

Documentation	Workflow Status
Basic usage
Other shells
Other options
Channels
Custom installer
Mamba
Lockfiles
Miniforge
Caching packages
Caching environments

These are quality control and test workflows, and are not described in depth.

QA Workflow	Linting	Catch Invalid Enviroments	Handle Empty Channels
Workflow Status

This action will by default activate an environment called test, not activate the base environment. This encourages the practice of not using the base environment to install packages used for the workflow and leave the base environment untouched, with only conda (and/or mamba) in it.

For a full list of available inputs and outputs for this action see action.yml.

You can change the default test environment to have a different name or path by setting the activate-environment input option.

- uses: conda-incubator/setup-miniconda@v2
  with:
    activate-environment: whatever

This will be create a named env in $CONDA/envs/whatever, where $CONDA is the path to the infrequently-updated, but very fast to start, "bundled" Miniconda installation.

• If activate-environment contains either POSIX or Windows slashes, it will be interpreted as a path, or prefix in conda terminology. Use this to avoid "path too long"-style errors, especially on Windows.
• Self-hosted runners can emulate the "bundled" Miniconda approach by pre-installing a constructor-based installer and ensuring $CONDA is set prior to starting setup-miniconda

If your specific workflow still needs to activate and use base you will need to do both of:

• set activate-environment to an empty string
• set auto-activate-base to true

- uses: conda-incubator/setup-miniconda@v2
  with:
    auto-activate-base: true
    activate-environment: ""

This example shows how to set a basic python workflow with conda using the crossplatform available shells: bash and pwsh. On this example an environment named test will be created with the specific python-version installed for each opearating system, resulting on 6 build workers.

jobs:
  example-1:
    name: Ex1 (${{ matrix.python-version }}, ${{ matrix.os }})
    runs-on: ${{ matrix.os }}
    strategy:
      fail-fast: false
      matrix:
        os: ["ubuntu-latest", "macos-latest", "windows-latest"]
        python-version: ["3.7", "2.7"]
    steps:
      - uses: conda-incubator/setup-miniconda@v2
        with:
          auto-update-conda: true
          python-version: ${{ matrix.python-version }}
      - name: Conda info
        shell: bash -el {0}
        run: conda info
      - name: Conda list
        shell: pwsh
        run: conda list

This example shows how to use all other available shells for specific operating systems. On this example we select to download the latest anaconda version available and create and activate by default an environment named foo.

jobs:
  example-2-linux:
    name: Ex2 Linux
    runs-on: "ubuntu-latest"
    steps:
      - uses: conda-incubator/setup-miniconda@v2
        with:
          miniconda-version: "latest"
          activate-environment: foo
      - name: Bash
        shell: bash -el {0}
        run: |
          conda info
          conda list
      - name: PowerShell Core
        shell: pwsh
        run: |
          conda info
          conda list

  example-2-mac:
    name: Ex2 Mac
    runs-on: "macos-latest"
    steps:
      - uses: conda-incubator/setup-miniconda@v2
        with:
          miniconda-version: "latest"
          activate-environment: foo
      - name: Sh
        shell: sh -l {0}
        run: |
          conda info
          conda list
      - name: Bash
        shell: bash -el {0}
        run: |
          conda info
          conda list
      - name: PowerShell Core
        shell: pwsh
        run: |
          conda info
          conda list

  example-2-win:
    name: Ex2 Windows
    runs-on: "windows-latest"
    steps:
      - uses: conda-incubator/setup-miniconda@v2
        with:
          miniconda-version: "latest"
          activate-environment: foo
      - name: Bash
        shell: bash -el {0}
        run: |
          conda info
          conda list
      - name: PowerShell
        shell: powershell
        run: |
          conda info
          conda list
      - name: PowerShell Core
        shell: pwsh
        run: |
          conda info
          conda list
      - name: Cmd.exe
        shell: cmd /C CALL {0}
        run: >-
          conda info && conda list

This example shows how to use environment.yml for easier creation of test/build environments and .condarc files for fine grained configuration management. On this example we use a custom configuration file, install an environment from a yaml file and disable autoactivating the base environment before activating the anaconda-client-env.

jobs:
  example-3:
    name: Ex3 Linux
    runs-on: "ubuntu-latest"
    defaults:
      run:
        shell: bash -el {0}
    steps:
      - uses: actions/checkout@v2
      - uses: conda-incubator/setup-miniconda@v2
        with:
          activate-environment: anaconda-client-env
          environment-file: etc/example-environment.yml
          python-version: 3.5
          condarc-file: etc/example-condarc.yml
          auto-activate-base: false
      - run: |
          conda info
          conda list

This example shows how to use channels option and other extra options. The priority will be set by the order of the channels. In this example it will result in:

• conda-forge
• spyder-ide
• defaults

jobs:
  example-4:
    name: Ex4 Linux
    runs-on: "ubuntu-latest"
    defaults:
      run:
        shell: bash -el {0}
    steps:
      - uses: actions/checkout@v2
      - uses: conda-incubator/setup-miniconda@v2
        with:
          activate-environment: foo
          python-version: 3.6
          channels: conda-forge,spyder-ide
          allow-softlinks: true
          channel-priority: flexible
          show-channel-urls: true
          use-only-tar-bz2: true
      - run: |
          conda info
          conda list
          conda config --show-sources
          conda config --show

Any installer created with constructor which includes conda can be used in place of Miniconda. For example, conda-forge maintains additional builds of miniforge for platforms not yet supported by Miniconda. For more, see Example 10.

Notes:

• Installer downloads are cached based on their full URL: adding some non-functional salt to the URL will prevent this behavior, e.g. #${{ github.run_number }}

jobs:
  example-5:
    name: Ex5 Miniforge for PyPy
    runs-on: "ubuntu-latest"
    defaults:
      run:
        shell: bash -el {0}
    steps:
      - uses: actions/checkout@v2
      - uses: conda-incubator/setup-miniconda@v2
        with:
          installer-url: https://github.com/conda-forge/miniforge/releases/download/4.8.3-2/Miniforge-pypy3-4.8.3-2-Linux-x86_64.sh
          allow-softlinks: true
          show-channel-urls: true
          use-only-tar-bz2: true
      - run: |
          conda info
          conda list
          conda config --show-sources
          conda config --show

Experimental! Use mamba to handle conda installs in a faster way. mamba-version accepts a version string x.y (including "*"). It requires you specify conda-forge as part of the channels, ideally with the highest priority.

Notes:

• If a custom installer provides mamba, it can be prioritized wherever possible (including installing mamba-version) with use-mamba: true.

jobs:
  example-6:
    name: Ex6 Mamba
    runs-on: "ubuntu-latest"
    steps:
      - uses: actions/checkout@v2
      - uses: conda-incubator/setup-miniconda@v2
        with:
          python-version: 3.6
          mamba-version: "*"
          channels: conda-forge,defaults
          channel-priority: true
          activate-environment: anaconda-client-env
          environment-file: etc/example-environment.yml
      - shell: bash -el {0}
        run: |
          conda info
          conda list
          conda config --show-sources
          conda config --show
          printenv | sort
      - shell: bash -el {0}
        run: mamba install jupyterlab

conda list --explicit and conda-lock support generating explicit environment specifications, which skip the environment solution step altogether, as they contain the ordered list of exact URLs needed to reproduce the environment.

This means explicitly-defined environments...

• are much faster to install, as several expensive steps are skipped:
  • channels are not queried for their repo data
  • no solver is run
• are not cross-platform, as the URLs almost always contain platform/architecture information
• can become broken if any file becomes unavailable

This approach can be useful as part of a larger system e.g. a separate workflow that runs conda-lock for all the platforms needed in a separate job.

jobs:
  example-7:
    name: Ex7 Explicit
    runs-on: "ubuntu-latest"
    defaults:
      run:
        shell: bash -el {0}
    steps:
      - uses: actions/checkout@v2
      - uses: conda-incubator/setup-miniconda@v2
        with:
          auto-update-conda: false
          activate-environment: explicit-env
          environment-file: etc/example-explicit.conda.lock
      - run: |
          conda info
          conda list
          conda config --show-sources
          conda config --show
          printenv | sort

Miniforge provides a number of alternatives to Miniconda, built from the ground up with conda-forge packages and with only conda-forge in its default channels.

If only miniforge-version is provided, Miniforge3 will be used.

jobs:
  example-10-miniforge:
    name: Ex10 (${{ matrix.os }}, Miniforge)
    runs-on: ${{ matrix.os }}-latest
    strategy:
      matrix:
        os: ["ubuntu", "macos", "windows"]
    steps:
      - uses: actions/checkout@v2
      - uses: conda-incubator/setup-miniconda@v2
        with:
          environment-file: etc/example-environment.yml
          miniforge-version: latest

In addition to Miniforge3 with conda and CPython, for each of its many supported platforms and architectures, additional variants including Mambaforge (which comes pre-installed mamba in addition to conda on all platforms) and Miniforge-pypy3/Mamabaforge-pypy3 (which replace CPython with pypy3 on Linux/MacOS) are available.

jobs:
  example-10-mambaforge:
    name: Ex10 (${{ matrix.os }}, Mambaforge)
    runs-on: ${{ matrix.os }}-latest
    strategy:
      fail-fast: false
      matrix:
        os: ["ubuntu", "macos", "windows"]
        include:
          - os: ubuntu
            environment-file: etc/example-environment-no-name.yml
            miniforge-variant: Mambaforge
            miniforge-version: 4.9.2-4
          - os: macos
            environment-file: etc/example-empty-channels-environment.yml
            miniforge-variant: Mambaforge-pypy3
          - os: windows
            environment-file: etc/example-explicit.Windows.conda.lock
            condarc-file: etc/example-condarc.yml
            miniforge-variant: Mambaforge
    steps:
      - uses: actions/checkout@v2
      - uses: conda-incubator/setup-miniconda@v2
        with:
          condarc-file: ${{ matrix.condarc-file }}
          environment-file: ${{ matrix.environment-file }}
          miniforge-variant: ${{ matrix.miniforge-variant }}
          miniforge-version: ${{ matrix.miniforge-version }}
          use-mamba: true

In addition to the default 64-bit builds of Miniconda, 32-bit versions are available for Windows. Note that although some x86 builds are available for Linux and MacOS, these are too old (<4.6) to be supported by this action.

jobs:
  example-11:
    name:
      Ex11 (os=${{ matrix.os }} architecture=${{ matrix.architecture }}
      miniconda-version=${{ matrix.miniconda-version }})
    runs-on: ${{ matrix.os }}
    strategy:
      fail-fast: false
      matrix:
        os: ["windows-latest"]
        architecture: ["x86"]
        miniconda-version: ["latest"]
    steps:
      - uses: actions/checkout@v2
      - uses: ./
        with:
          architecture: ${{ matrix.architecture }}
          miniconda-version: $${{ matrix.miniconda-version }}
          auto-update-conda: true
          python-version: "3.8"

If you want to enable package caching for conda you can use the cache action using ~/conda_pkgs_dir as path for conda packages.

The cache will use a explicit key for restoring and saving the cache.

This can be based in the contents of files like:

• setup.py
• requirements.txt
• environment.yml

jobs:
  caching-example:
    name: Caching
    runs-on: "ubuntu-latest"
    steps:
      - uses: actions/checkout@v2
      - name: Cache conda
        uses: actions/cache@v2
        env:
          # Increase this value to reset cache if etc/example-environment.yml has not changed
          CACHE_NUMBER: 0
        with:
          path: ~/conda_pkgs_dir
          key:
            ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-${{
            hashFiles('etc/example-environment.yml') }}
      - uses: conda-incubator/setup-miniconda@v2
        with:
          activate-environment: anaconda-client-env
          channel-priority: strict
          environment-file: etc/example-environment.yml
          use-only-tar-bz2: true # IMPORTANT: This needs to be set for caching to work properly!

If you are using pip to resolve any dependencies in your conda environment then you may want to cache those dependencies separately, as they are not included in the conda package cache.

The first installation step should setup a Miniconda variant without specifying a environment file.

- name: Setup Mambaforge
  uses: conda-incubator/setup-miniconda@v2
  with:
    miniforge-variant: Mambaforge
    miniforge-version: latest
    activate-environment: anaconda-client-env
    use-mamba: true

It's a good idea to refresh the cache every 24 hours to avoid inconsistencies of package versions between the CI pipeline and local installations. Here we ensure that this happens by adding the current date to the cache key. You can remove the "Get Date" step below if you use a resolved environment file product of conda env export or conda list --explicit.

- name: Get Date
  id: get-date
  run: echo "today=$(/bin/date -u '+%Y%m%d')" >> $GITHUB_OUTPUT
  shell: bash

- name: Cache Conda env
  uses: actions/cache@v2
  with:
    path: ${{ env.CONDA }}/envs
    key:
      conda-${{ runner.os }}--${{ runner.arch }}--${{
      steps.get-date.outputs.today }}-${{
      hashFiles('etc/example-environment-caching.yml') }}-${{ env.CACHE_NUMBER
      }}
  env:
    # Increase this value to reset cache if etc/example-environment.yml has not changed
    CACHE_NUMBER: 0
  id: cache

Keep in mind that hashing etc/example-environment-caching.yml is not the same as hashing a resolved environment file. conda (and mamba) resolves the dependencies declared in the YAML file according to the packages available on the channels at installation time. Since packages are updated all the time, you will not see these changes reflected in the cache until the key gets updated by date.

This means that the same environment file can make your tests pass locally but fail on CI, or the other way around. In that case, reset the cache manually to see if that leads to consistent results, or use a resolved environment file.

Finally, update the environment based on the environment file if the cache does not exist.

- name: Update environment
  run:
    mamba env update -n anaconda-client-env -f
    etc/example-environment-caching.yml
  if: steps.cache.outputs.cache-hit != 'true'

Assuming you are using the bash shell, now adding to shell: bash -el {0} to every single step can be avoided if your workflow uses the same shell for all the steps.

By adding a defaults section and specifying the bash -el {0}, all steps in the job will default to that value.

For other shells, make sure to use the right shell parameter as the default value. Check the section below for some examples.

More information the Github help page.

jobs:
  default-shell:
    name: Default shell
    runs-on: "ubuntu-latest"
    defaults:
      run:
        shell: bash -el {0}
    steps:
      - uses: actions/checkout@v2
      - uses: conda-incubator/setup-miniconda@v2
        with:
          activate-environment: anaconda-client-env
          environment-file: etc/example-environment-caching.yml
      - run: conda info
      - run: conda list
      - run: conda config --show

• Bash shells do not use ~/.profile or ~/.bashrc so these shells need to be explicitely declared as shell: bash -el {0} on steps that need to be properly activated (or use a default shell). This is because bash shells are executed with bash --noprofile --norc -eo pipefail {0} thus ignoring updated on bash profile files made by conda init bash. See Github Actions Documentation and thread.
• Sh shells do not use ~/.profile or ~/.bashrc so these shells need to be explicitely declared as shell: sh -l {0} on steps that need to be properly activated (or use a default shell). This is because sh shells are executed with sh -e {0} thus ignoring updated on bash profile files made by conda init bash. See Github Actions Documentation.
• Cmd shells do not run Autorun commands so these shells need to be explicitely declared as shell: cmd /C call {0} on steps that need to be properly activated (or use a default shell). This is because cmd shells are executed with %ComSpec% /D /E:ON /V:OFF /S /C "CALL "{0}"" and the /D flag disabled execution of Command Processor/Autorun Windows registry keys, which is what conda init cmd.exe sets. See Github Actions Documentation.
• For caching to work properly, you will need to set the use-only-tar-bz2 option to true.
• Some options (e.g. use-only-tar-bz2) are not available on the default conda installed on Windows VMs, be sure to use auto-update-conda or provide a version of conda compatible with the option.
• If you plan to use a environment.yaml file to set up the environment, the action will read the channelslisted in the key (if found). If you provide the channels input in the action they must not conflict with what was defined in environment.yaml, otherwise the conda solver might find conflicts and result in very long install times.
• Conda activation does not correctly work on sh. Please use bash.

See the CHANGELOG for project history, or CONTRIBUTING to get started adding features you need.

Thanks to all the contributors that make this awesome project possible!

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The scripts and documentation in this project are released under the MIT License