Spack environments

New in version 23.02.0-edge.

Spack is a package manager for supercomputers, Linux, and macOS. It makes installing scientific software easy. Spack is not tied to a particular language; you can build a software stack in Python or R, link to libraries written in C, C++, or Fortran, and easily swap compilers or target specific CPU microarchitectures.

Nextflow has built-in support for Spack that allows the configuration of workflow dependencies using Spack recipes and environment files.

This allows Nextflow applications to build packages from source on the compute infrastructure in use, whilst taking advantage of the configuration flexibility provided by Nextflow. At shared compute facilities where Spack has been configured by the administrators, this may result in optimized builds without user intervention. With appropriate options, this also permits end users to customize binary optimizations by themselves.


This feature requires the Spack package manager to be installed on your system.

How it works

Nextflow automatically creates and activates the Spack environment(s) given the dependencies specified by each process.

Dependencies are specified by using the spack directive, providing either the names of the required Spack packages, the path of a Spack environment yaml file or the path of an existing Spack environment directory.


Spack always installs the software packages in its own directories, regardless of the Nextflow specifications. The Spack environment created by Nextflow only contains symbolic links pointing to the appropriate package locations, and therefore it is relatively small in size.

You can specify the directory where the Spack environment is stored using the spack.cacheDir configuration property (see the configuration page for details). When using a computing cluster, make sure to use a shared file system path accessible from all compute nodes.


The Spack environment feature is not supported by executors that use remote object storage as the work directory, e.g. AWS Batch.

Enabling Spack environment

The use of Spack recipes specified using the spack directive needs to be enabled explicitly by setting the option shown below in the pipeline configuration file (i.e. nextflow.config):

spack.enabled = true

Alternatively, it can be specified by setting the variable NXF_SPACK_ENABLED=true in your environment or by using the -with-spack command line option.

Use Spack package names

Spack package names can specified using the spack directive. Multiple package names can be specified by separating them with a blank space. For example:

process foo {
  spack 'bwa samtools py-multiqc'

  your_command --here

Using the above definition, a Spack environment that includes BWA, Samtools, and MultiQC tools is created and activated when the process is executed.

The usual Spack package syntax and naming conventions can be used. The version of a package can be specified after the package name like so: bwa@0.7.15.

Spack is able to infer the local CPU microarchitecture and optimize the build accordingly. If you really need to customize this option, you can use the arch directive.

Read the Spack documentation for more details about package specifications.

Use Spack environment files

Spack environments can also be defined using one or more Spack environment files. A Spack environment file is a YAML file that lists the required packages and channels. For example:

  - star@2.5.4a
  - bwa@0.7.15

    unify: true

Here, the concretizer option is a sensible default for Spack environments.


When creating a Spack environment, Nextflow always enables the corresponding Spack view. This is required by Nextflow to locate executables at pipeline runtime.

As mentioned above, Spack is able to guess the target CPU microarchitecture and optimize the build accordingly. If you really need to customize this option, we advise to use the arch directive rather than the available options for the Spack environment file.

Read the Spack documentation for more details about how to create environment files.

The path of an environment file can be specified using the spack directive:

process foo {
  spack '/some/path/my-env.yaml'

  your_command --here


The environment file name must have a .yaml extension or else it won’t be properly recognized.

Use existing Spack environments

If you already have a local Spack environment, you can use it in your workflow specifying the installation directory of such environment by using the spack directive:

process foo {
  spack '/path/to/an/existing/env/directory'

  your_command --here

Best practices

Building Spack packages for Nextflow pipelines

Spack builds most software package from their source codes, and it does this for a request package and for all its required dependencies. As a result, Spack builds can last for long, even several hours. This can represent an inconvenience, in that it can significantly lengthen the duration of Nextflow processes. Here we briefly discuss two strategies to mitigate this aspect, and render the usage of Spack more effective.

  1. Use a Spack yaml file, and pre-build the environment outside of Nextflow, prior to running the pipeline. Building packages outside of the Nextflow pipeline will work since Spack always installs packages in its own directories, and only creates symbolic links in the environment. This sequence of commands will do the trick in most cases:

    spack env create myenv /path/to/spack.yaml
    spack env activate myenv
    spack env view enable
    spack concretize -f
    spack install -y
    spack env deactivate
  2. Use the Nextflow stub functionality prior to running the pipeline for production. Nextflow will run the stub pipeline, skipping process executions but still setting up the required software packages. This option is useful if it is not possible to write a Spack yaml file for the environment. The stub functionality is described in the Stub section of the Processes page.

Configuration file

When the spack directive is used in any process definition within the pipeline script, Spack is required for the pipeline execution.

Specifying the Spack environments in a separate configuration profile is therefore recommended to allow the execution via a command line option and to enhance the pipeline portability. For example:

profiles {
  spack {
    process.spack = 'samtools'

  docker {
    process.container = 'biocontainers/samtools'
    docker.enabled = true

The above configuration snippet allows the execution either with Spack or Docker by specifying -profile spack or -profile docker when running the pipeline script.

Advanced settings

Spack advanced configuration settings are described in the Spack section on the Nextflow configuration page.