cli.rst

Command line interface

This part of the documentation describes the snakemake executable. Snakemake is primarily a command-line tool, so the snakemake executable is the primary way to execute, debug, and visualize workflows.

Useful Command Line Arguments

If called without parameters, i.e.

$ snakemake

Snakemake tries to execute the workflow specified in a file called Snakefile in the same directory (instead, the Snakefile can be given via the parameter -s).

By issuing

$ snakemake -n

a dry-run can be performed. This is useful to test if the workflow is defined properly and to estimate the amount of needed computation. Further, the reason for each rule execution can be printed via

$ snakemake -n -r

Importantly, Snakemake can automatically determine which parts of the workflow can be run in parallel. By specifying the number of available cores, i.e.

$ snakemake --cores 4

one can tell Snakemake to use up to 4 cores and solve a binary knapsack problem to optimize the scheduling of jobs. If the number is omitted (i.e., only --cores is given), the number of used cores is determined as the number of available CPU cores in the machine.

Dealing with very large workflows

If your workflow has a lot of jobs, Snakemake might need some time to infer the dependencies (the job DAG) and which jobs are actually required to run. The major bottleneck involved is the filesystem, which has to be queried for existence and modification dates of files. To overcome this issue, Snakemake allows to run large workflows in batches. This way, fewer files have to be evaluated at once, and therefore the job DAG can be inferred faster. By running

$ snakemake --cores 4 --batch myrule=1/3

you instruct to only compute the first of three batches of the inputs of the rule myrule. To generate the second batch, run

$ snakemake --cores 4 --batch myrule=2/3

Finally, when running

$ snakemake --cores 4 --batch myrule=3/3

Snakemake will process beyond the rule myrule, because all of its input files have been generated, and complete the workflow. Obviously, a good choice of the rule to perform the batching is a rule that has a lot of input files and upstream jobs, for example a central aggregation step within your workflow. We advice all workflow developers to inform potential users of the best suited batching rule.

Profiles

Adapting Snakemake to a particular environment can entail many flags and options. Therefore, since Snakemake 4.1, it is possible to specify a configuration profile to be used to obtain default options:

$ snakemake --profile myprofile

Here, a folder myprofile is searched in per-user and global configuration directories (on Linux, this will be $HOME/.config/snakemake and /etc/xdg/snakemake, you can find the answer for your system via snakemake --help). Alternatively, an absolute or relative path to the folder can be given. The profile folder is expected to contain a file config.yaml that defines default values for the Snakemake command line arguments. For example, the file

cluster: qsub
jobs: 100

would setup Snakemake to always submit to the cluster via the qsub command, and never use more than 100 parallel jobs in total. Under https://github.com/snakemake-profiles/doc, you can find publicly available profiles. Feel free to contribute your own.

The profile folder can additionally contain auxilliary files, e.g., jobscripts, or any kind of wrappers. See https://github.com/snakemake-profiles/doc for examples.

All Options

.. argparse::
   :module: snakemake
   :func: get_argument_parser
   :prog: snakemake

   All command line options can be printed by calling ``snakemake -h``.

Bash Completion

Snakemake supports bash completion for filenames, rulenames and arguments. To enable it globally, just append

`snakemake --bash-completion`

including the accents to your .bashrc. This only works if the snakemake command is in your path.