+ Statement of need
+ The integration of bioinformatic analyses into comprehensive
+ pipelines (aka workflows) has revolutionised the field by improving
+ the robustness and reproducibility of analyses. One of the most
+ popular workflow frameworks is Snakemake
+ (Mölder
+ et al., 2021). Snakemake is a user-friendly and adaptable
+ make-style workflow framework with a powerful specification language
+ built atop of the Python programming language. Despite its success,
+ Snakemake workflows are often developed for specific research analysis
+ rather than as general-purpose reusable tools. That is, Snakemake
+ workflows are typically built for the reproducibility of a single
+ analysis but not necessarily built for flexibility.
+ To improve their utility, Snakemake workflows developers often
+ encapsulate workflows within CLI tools by producing wrapper code to
+ abstract the workflow execution, sometimes called
+ workflows-as-applications or workflows packages
+ (Roach
+ et al., 2022). These wrappers serve as intermediaries between
+ the end-user (via the CLI) and the workflow execution, enabling
+ developers to tailor the Snakemake experience to specific use cases.
+ For example, the pangolin CLI tool wraps a Snakemake workflow for
+ SARS-CoV-2 lineage assignment
+ (O’Toole
+ et al., 2022). Initiatives like Snaketool have simplified the
+ development of Snakemake-based CLIs by offering a template for
+ developers
+ (Roach
+ et al., 2022). Nonetheless, the onus remains on the developer
+ to create and maintain the CLI wrappers for their workflow.
+ Here we present Snk, a Snakemake workflow management system that
+ allows users to install Snakemake workflows as dynamically generated
+ CLIs. Thus users can create a CLI for their (or others’) Snakemake
+ workflows with minimal to no code changes required. The Snk-generated
+ CLIs follow best practices and include several features out of the box
+ that improve user experience. The CLIs can be configured at install
+ time or via a snk.yaml configuration file. Snk
+ is readily available for installation via PyPI and Conda, using the
+ commands pip install snk and
+ conda install snk, respectively.
+ Snk has two distinct major functions; managing the installation of
+ workflows, and dynamical generating CLIs from Snakemake configuration
+ files. To install a workflow as a CLI, users can specify the file
+ path, URL, or GitHub name (username/repo) of a workflow. Snk copies
+ (clones) workflows into a managed directory structure, creates a CLI
+ entry point, and optionally creates an isolated virtual environment
+ for each workflow. Workflows can be installed from specific commits,
+ tags, or branches, ensuring reproducibility. The advent of Snk allows
+ users to utilise the Snakemake workflow catalog
+ (https://snakemake.github.io/snakemake-workflow-catalog)
+ as a searchable package index of Snk-installable Snakemake tools. The
+ snk install command is flexible and can be used to install diverse
+ workflows using installation options. For example, the
+ dna-seq-gatk-variant-calling
+ workflow (release tag v2.1.1) can be installed as a CLI
+ named variant-calling with Snakemake v8.10.8
+ and Pandas and NumPy dependencies using the following command:
+ snk install \
+ snakemake-workflows/dna-seq-gatk-variant-calling \
+ --name variant-calling \
+ --snakemake 8.10.8 \
+ -d pandas==1.5.3 \
+ -d numpy==1.26.4 \
+ -t v2.1.1
+ The workflow will then be accessible via the
+ variant-calling CLI in the terminal (Figure 1).
+ Additionally, the snk command can be used to
+ list and uninstall workflows installed with Snk. The complete
+ documentation for managing workflows can be found at
+ https://snk.wytamma.com/managing_workflows.
+
+ The variant-calling CLI generated
+ by Snk.
+ ![]()
+
+ The core functionality of Snk is the dynamic creation of CLIs.
+ Internally snk uses the Snk-CLI sister package
+ to generate the CLI. By default key values pairs of the Snakemake
+ configfile are mapped to CLI option. For example,
+ samples: samples.tsv in the configfile will
+ generate a --samples option in the CLI with the
+ default value samples.tsv (Figure 2). The CLI
+ generated by snk is highly customisable and can be configured via a
+ snk.yaml file placed in the workflow directory. The snk.yaml file can
+ configure many aspects of CLI including subcommands, ASCII art, help
+ messages, resource files, default values, and much more. Complete
+ documentation for the Snk config file can be found at
+ https://snk.wytamma.com/snk_config_file.
+
+ The run command of the
+ variant-calling CLI dynamically generated
+ from the Snakemake configfile. Several standard options are provided
+ in the Options section, e.g., --dry
+ (equivalent to Snakemakes --dry-run),
+ --dag to create a DAG plot of the workflow,
+ and --cores witch defaults to all. The
+ Workflow Configuration section contains the options dynamically
+ generated from the configfile. Snk-CLI automatically infers the
+ defaults and types of the options and creates flags for boolean
+ options.
+ ![]()
+
+ Developers can also directly use the Snk-CLI package to generate
+ CLIs for their Snakemake workflows. By using the
+ CLI class from Snk-CLI, developers can build a
+ fully featured workflow package without having to write a Snakemake
+ wrapper. We provide a guide for using Snk-CLI to build self-contained
+ workflow packages at
+ https://snk.wytamma.com/workflow_packages.
+ The Snk-CLI package is available via PyPI and can be installed using
+ the command pip install snk-cli.
+ Snk is a powerful tool that simplifies the use of Snakemake
+ workflows by dynamically generating CLIs. Snk is open-source software
+ released under the MIT license. Snk documentation, source code, and
+ issue tracker are available at
+ https://github.com/Wytamma/snk.
+ We welcome contributions and feedback from the community to improve
+ Snk and make it a valuable tool for the Snakemake community and
+ reproducible research at large.
+
+