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 specific
versions of conda
or mamba
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 latestpython-version
and its dependencies - creating a
test
environment described in a givenenvironment-file
including:- an
environment.yml
-like file (which can be patched withpython-version
). Note: the patched environment will be cleaned up unlessclean-patched-environment-file: false
is given - a lockfile
- an
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.
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
and not
activate the base
environment. This encourages the recommended practice of not
installing workflow packages into the base
environment and leaving it with
only conda
(and/or mamba
).
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@v3
with:
activate-environment: whatever
This will 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, orprefix
inconda
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
$CONDA
is set prior to startingsetup-miniconda
If your specific workflow still needs to activate and use base
you will need
to do both of:
- set
activate-environment
to an empty string - set
auto-activate-base
totrue
- uses: conda-incubator/setup-miniconda@v3
with:
auto-activate-base: true
activate-environment: ""
This example shows how to set a basic python workflow with conda using the
cross-platform available shells: bash
and pwsh
. In this example an
environment named test
will be created with the specific python-version
installed for each operating system, resulting in 6 build workers.
jobs:
example-1:
name: Ex1 (${{ 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", "3.11"]
steps:
- uses: conda-incubator/setup-miniconda@v3
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. In this example we download the latest anaconda version then create and
activate a default environment named foo
.
jobs:
example-2-linux:
name: Ex2 Linux
runs-on: "ubuntu-latest"
steps:
- uses: conda-incubator/setup-miniconda@v3
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@v3
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@v3
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. In 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@v4
- uses: conda-incubator/setup-miniconda@v3
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 the channels
option and other extra options. The
priority will be set by the order of the channels. The following example will
result in these priorities (from highest to lowest):
- 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@v4
- uses: conda-incubator/setup-miniconda@v3
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 the
constructor tool (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 details, see
Example 10.
Note:
- 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@v4
- uses: conda-incubator/setup-miniconda@v3
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 enable much faster conda installs. 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 installingmamba-version
) withuse-mamba: true
.
jobs:
example-6:
name: Ex6 Mamba
runs-on: "ubuntu-latest"
steps:
- uses: actions/checkout@v4
- uses: conda-incubator/setup-miniconda@v3
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 which:
- 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@v4
- uses: conda-incubator/setup-miniconda@v3
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 channel(s).
If only miniforge-version
is provided then Miniforge3
will be used.
jobs:
example-10-miniforge:
name: Ex10 (${{ matrix.os }}, Miniforge)
runs-on: ${{ matrix.os }}-latest
strategy:
matrix:
os: ["ubuntu", "macos", "windows"]
steps:
- uses: actions/checkout@v4
- uses: conda-incubator/setup-miniconda@v3
with:
environment-file: etc/example-environment.yml
miniforge-version: latest
In addition to Miniforge3
with conda
and CPython
, for each of its many
supported platforms and architectures, additional variants including
Mambaforge
(which comes pre-installed mamba
in addition to conda
on all
platforms) and Miniforge-pypy3
/Mamabaforge-pypy3
(which replace CPython
with pypy3
on Linux/MacOS) are available.
jobs:
example-10-mambaforge:
name: Ex10 (${{ 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: windows
environment-file: etc/example-explicit.Windows.conda.lock
condarc-file: etc/example-condarc.yml
miniforge-variant: Mambaforge
steps:
- uses: actions/checkout@v4
- uses: conda-incubator/setup-miniconda@v3
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@v4
- uses: conda-incubator/setup-miniconda@v3
with:
architecture: ${{ matrix.architecture }}
miniconda-version: $${{ matrix.miniconda-version }}
auto-update-conda: true
python-version: "3.8"
Set the conda solver plugin to use. Only applies to the conda
client, not
mamba
. Starting with Miniconda 23.5.2 and Miniforge 23.3.1, you can choose
between classic
and libmamba
. Best when combined with
auto-update-conda: true
.
jobs:
example-12:
name: Ex12 (os=${{ matrix.os }} solver=${{ matrix.solver }})
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
solver: ["classic", "libmamba"]
os: ["ubuntu-latest", "windows-latest"]
steps:
- uses: actions/checkout@v4
- uses: conda-incubator/setup-miniconda@v3
id: setup-miniconda
continue-on-error: true
with:
auto-update-conda: true
conda-solver: ${{ matrix.solver }}
python-version: "3.9"
jobs:
example-13:
name: Ex13 (os=${{ matrix.os }})
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: ["macos-14"]
steps:
- uses: actions/checkout@v4
- uses: ./
id: setup-miniconda
continue-on-error: true
with:
miniconda-version: latest
- name: Check arm64
shell: bash -el {0}
run: |
conda install -y python
python -c "import platform; assert platform.machine() == 'arm64', platform.machine()"
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 an 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@v4
- name: Cache conda
uses: actions/cache@v3
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 }}-${{
hashFiles('etc/example-environment.yml') }}
- uses: conda-incubator/setup-miniconda@v3
with:
activate-environment: anaconda-client-env
channel-priority: strict
environment-file: etc/example-environment.yml
use-only-tar-bz2: true # IMPORTANT: This needs to be set for caching to work properly!
If you are using pip to resolve any dependencies in your conda environment then you may want to cache those dependencies separately, as they are not included in the conda package cache.
The first installation step should setup a Miniconda variant without specifying a environment file.
- name: Setup Mambaforge
uses: conda-incubator/setup-miniconda@v3
with:
miniforge-variant: Mambaforge
miniforge-version: latest
activate-environment: anaconda-client-env
use-mamba: true
It's a good idea to refresh the cache every 24 hours to avoid inconsistencies of
package versions between the CI pipeline and local installations. Here we ensure
that this happens by adding the current date to the cache key. You can remove
the "Get Date" step below if you use a resolved environment file product of
conda env export
or conda list --explicit
.
- name: Get Date
id: get-date
run: echo "today=$(/bin/date -u '+%Y%m%d')" >> $GITHUB_OUTPUT
shell: bash
- name: Cache Conda env
uses: actions/cache@v3
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'
If you use the same shell for every step in your workflow you don't have to add
a shell directive to every step (e.g., shell: bash -el {0}
when using bash).
You can add a defaults
section and specify the desired directive (e.g.,
bash -el {0}
or equivalent). All steps in the job will then default to using
that value.
For other shells, make sure to use the correct shell
parameter as the default
value. Check the section below for some examples.
For more information see the Github Actions help page.
jobs:
default-shell:
name: Default shell
runs-on: "ubuntu-latest"
defaults:
run:
shell: bash -el {0}
steps:
- uses: actions/checkout@v4
- uses: conda-incubator/setup-miniconda@v3
with:
activate-environment: anaconda-client-env
environment-file: etc/example-environment-caching.yml
- run: conda info
- run: conda list
- run: conda config --show
- Conda activation does not correctly work on
sh
. Please usebash
. - Bash shells do not use
~/.profile
or~/.bashrc
so these shells need to be explicitly declared asshell: bash -el {0}
on steps that need to be properly activated (or use a default shell). This is because bash shells are executed withbash --noprofile --norc -eo pipefail {0}
thus ignoring updated on bash profile files made byconda init bash
. See Github Actions Documentation and this community thread. - Sh shells do not use
~/.profile
or~/.bashrc
so these shells need to be explicitly declared asshell: sh -l {0}
on steps that need to be properly activated (or use a default shell). This is because sh shells are executed withsh -e {0}
thus ignoring updates on bash profile files made byconda init bash
. See Github Actions Documentation. - Cmd shells do not run
Autorun
commands so these shells need to be explicitly declared asshell: 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 disables execution ofCommand Processor/Autorun
Windows registry keys, which is whatconda init cmd.exe
sets. See Github Actions Documentation. - For caching to work properly, you will need to set the
use-only-tar-bz2
option totrue
. - Some options (e.g.
use-only-tar-bz2
) are not available on the default conda installed on Windows VMs, be sure to useauto-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 thechannels
listed in the key (if found). If you provide thechannels
input in the action they must not conflict with what was defined inenvironment.yaml
, otherwise the conda solver might find conflicts which cause very long install times or install failures.
Security and reproducibility is important especially when workflows deal with secrets. No matter how much individual Github action repositories are secured, git branches and tags are always mutable. It is thus good practice to:
- pin the action to a specific sha1 with tag as comment, instead of e.g. using
v2 or v2.2.1 (which are mutable tags):
uses: conda-incubator/setup-miniconda@9f54435e0e72c53962ee863144e47a4b094bfd35 # v2.3.0
see example - keep the non-human-readable pinning updated to not run behind recent updates and fixes via automation like renovate or dependabot
- use conda-lock files, see conda-lock
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