wf2wf Documentation

Welcome to wf2wf – the universal workflow-format converter.

Docs in progress

This documentation site is still growing. If something is missing, please open an issue or contribute a pull request!

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Overview 🌐

wf2wf converts workflows between any supported engines via a loss-preserving Intermediate Representation (IR). Supported today:

• Snakemake • CWL • Nextflow • WDL • Galaxy • HTCondor DAGMan (+ BioCompute Objects)

Key features:

• 🔄 Universal conversion – always A → IR → B for maximum fidelity.

• 🧠 Intelligent inference – automatically fills in missing resource specifications and configurations.

• 💬 Interactive prompting – guided assistance for complex conversions and missing information.

• 🧬 Loss mapping – records unexpressed fields in side-cars so nothing vanishes.

• 🐳 Environment automation – Conda → OCI → Apptainer with SBOM generation.

• ⚖ Regulatory support – Emits BioCompute Objects and provenance metadata.

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Quick install

pip install wf2wf            # or: conda install -c conda-forge wf2wf

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Quick CLI tour 🚀

# Convert Snakemake → DAGMan and build container images
wf2wf convert -i Snakefile -o pipeline.dag --auto-env build --interactive

# Convert CWL → Nextflow, aborting on information loss
wf2wf convert -i analysis.cwl -o main.nf --out-format nextflow --fail-on-loss

# Enhanced conversion with interactive resource specification
wf2wf convert -i Snakefile -o pipeline.dag --interactive --infer-resources

# Convert CWL → Nextflow with resource validation and loss detection
wf2wf convert -i analysis.cwl -o main.nf --out-format nextflow --fail-on-loss --validate-resources

# Comprehensive conversion with all enhanced features
wf2wf convert -i workflow.smk -o workflow.dag \
    --interactive \
    --infer-resources \
    --validate-resources \
    --resource-profile cluster \
    --target-env distributed \
    --report-md

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Enhanced Features 🆕

Intelligent Resource Inference

Automatically detect and specify resource requirements based on command analysis:

wf2wf convert -i workflow.smk -o workflow.dag --infer-resources
# Analyzes: "bwa mem" → 8GB memory, 4 CPU
# Analyzes: "samtools sort" → 4GB memory, 2 CPU

Interactive Conversion Mode

Get guided assistance for complex conversions:

wf2wf convert -i workflow.smk -o workflow.dag --interactive
# Prompts for: missing resources, containers, error handling, file transfers

Resource Processing

Validate and optimize resource specifications:

wf2wf convert -i workflow.smk -o workflow.dag --validate-resources --resource-profile cluster

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Sections

• User Guide – step-by-step tutorials and best practices.

• Shared Infrastructure – comprehensive guide to intelligent inference and interactive features.

• CLI Reference – exhaustive help for every command.

• Developer Guide – IR schema, environment pipeline, contributor tips.

• Changelog – project history and release notes.