Snakemake Argparse Bridge

A Python package that allows existing argparse-based scripts to work seamlessly in both command-line and Snakemake environments with minimal code changes.

Why does this exist?

You just wrote a Python script for your Snakemake rule that uses argparse so you can test and run it on the command line. But then when you integrate it into your workflow, you realize you need to:

1. Rewrite the script to work with Snakemake's script: directive
2. Maintain two versions - one for CLI testing, one for Snakemake
3. Manually map Snakemake variables (wildcards, input, output) to script arguments

This bridge eliminates that friction. Just add one decorator and your script works seamlessly in both environments.

Installation

pip install snakemake-argparse-bridge

Quick Start

1. Decorate your existing script

# scripts/process_sample.py
import argparse
from snakemake_argparse_bridge import snakemake_compatible

@snakemake_compatible(mapping={
    'sample': 'wildcards.sample',
    'input_file': 'input[0]',
    'output_file': 'output[0]',
    'threads': 'threads'
})
def main():
    parser = argparse.ArgumentParser()
    parser.add_argument('--sample', required=True)
    parser.add_argument('--input-file', required=True)
    parser.add_argument('--output-file', required=True)
    parser.add_argument('--threads', type=int, default=1)
    
    # This works in both CLI and Snakemake contexts!
    args = parser.parse_args()
    
    # Your processing logic here
    print(f"Processing {args.sample} with {args.threads} threads")

if __name__ == '__main__':
    main()

2. Use in Snakemake

# Snakefile
rule process_sample:
    input: "data/{sample}.txt"
    output: "results/{sample}_processed.txt"
    threads: 4
    script: "scripts/process_sample.py"

3. Still works from command line

python scripts/process_sample.py --sample test --input-file data.txt --output-file results.txt --threads 2

How it works

The @snakemake_compatible decorator temporarily patches argparse.ArgumentParser.parse_args() to:

• In Snakemake context: Extract values from snakemake.wildcards, snakemake.input, snakemake.params, etc.
• In CLI context: Use normal argparse behavior

Mapping Options

Explicit Mapping

@snakemake_compatible(mapping={
    'sample': 'wildcards.sample',           # Wildcard
    'input_file': 'input[0]',               # First input file
    'output_file': 'output[0]',             # First output file  
    'method': 'params.method',              # Parameter
    'threads': 'threads',                   # Thread count
    'memory': 'resources.mem_mb',           # Memory resource
    'log_file': 'log[0]',                   # Log file
})

Available Snakemake Attributes

• input, input[0], input[1], etc. - Input files
• output, output[0], output[1], etc. - Output files
• wildcards.{name} - Wildcard values
• params.{name} - Rule parameters
• log, log[0], etc. - Log files
• threads - Number of threads
• resources.{name} - Resource specifications
• config.{name} - Configuration values

Testing

# Run tests
pytest tests/

# Test with actual Snakemake (requires snakemake installation)
pytest tests/test_snakemake_integration.py

Requirements

• Python 3.7+
• No additional dependencies for basic usage
• Snakemake (for Snakemake integration, obviously)

License

MIT License