snakemk-util 3.0.0

utility functions for snakemake

Snakemake Utility functions for easier working with snakemake

When debugging a script that uses snakemake to define its inputs, it is often difficult to manually set some example inputs for testing. This utility allows to directly obtain a Snakemake object from the pipeline by specifying the desired rule and wildcards.

Loading snakemake object without actually running snakemake

For obtaining a Snakemake object in python, simply paste the following preamble in your script and adjust snakefile_path, rule_name and default_wildcards.

try:
    snakemake
except NameError:
    import os
    from snakemk_util import load_rule_args, pretty_print_snakemake
    
    snakefile_path = os.getcwd() + "/Snakefile"
    snakemake = load_rule_args(
        snakefile = snakefile_path,
        rule_name = 'create_prediction_target',
        default_wildcards={
            'ds_dir': 'all_data'
        }
    )
    print(pretty_print_snakemake(snakemake))

Output:

Snakemake({
  "threads": 64,
  "resources": {
    "_cores": 64,
    "_nodes": 1,
    "tmpdir": "<function DefaultResources.__init__.<locals>.fallback.<locals>.callable at 0x154022f799d0>",
    "ntasks": 1,
    "mem_mb": 250000
  },
  "input": {
    "0": "some_input.csv"
    "config": "some_config.yaml",
  },
  "params": {
    "nb_script": "create_prediction_target.py"
  },
  "output": {
    [...]
  },
  "wildcards": {
    "ds_dir": "all_data"
  },
  "log": [],
  "config": {
    [...]
  },
  "rule": "create_prediction_target"
})

• The preamble has no effect during snakemake runs, so it can be kept in the script permanently.
• pretty_print_snakemake knows about the NamedList that snakemake uses and prints all non-named parameters by their index

Here the corresponding snippet for R:

if (! exists("snakemake")) {
    snakefile = "Snakefile"
    rule = "create_prediction_target"
    python = "/opt/anaconda/envs/snakemake/bin/python"
    wildcards = c(
        # "comparison=all",
    )

    cmd=c(
        "-m snakemk_util.main",
        "--rule", rule,
        "--snakefile", normalizePath(snakefile),
        "--root_dir", dirname(normalizePath(snakefile)),
        "--gen-preamble", "RScript",
        "--create_dirs",
        if (length(wildcards) > 0) c("--wildcards", wildcards) else NULL
    )
    eval(parse(text=system2(python, cmd, stdout=TRUE, stderr="")))
}

Inspecting the rule parameters on the command line

snakemk_util also provides a command-line interface which allows to display the snakemake objects for some rule and wildcard as well as generating script preambles for different languages:

# snakemk_util --help
usage: snakemk_util [-h] --rule RULE_NAME [--gen-preamble FLAVOR] [--snakefile SNAKEFILE] [--root_dir ROOT_DIR] [--wildcards [KEY=VALUE ...]] [--create_dirs]

Utility to sow Snakemake rule contents and creating script preambles without actually running Snakemake.

optional arguments:
  -h, --help            show this help message and exit
  --rule RULE_NAME      Name of the rule that should be formatted
  --gen-preamble FLAVOR
                        Script language for which the preamble should be generated Examples: 'BashScript', 'JuliaScript', 'PythonScript', 'RMarkdown', 'RScript', 'RustScript', 'PythonJupyterNotebook', 'RJupyterNotebook'
  --snakefile SNAKEFILE
                        path to the Snakefile
  --root_dir ROOT_DIR   Root directory from where you would run the `snakemake` command. By default, this is the current working directory.
  --wildcards [KEY=VALUE ...]
                        Wildcards used to format the rule output, given as space-separated 'key=value' tokens. Example: --wildcards wildcard0=x wildcard1=y
  --create_dirs         Create the output directories for the rule

Installation

pip install snakemk_util