Running WDL with Toil¶
Toil has beta support for running WDL workflows, using the toil-wdl-runner
command. This command comes with the [wdl] extra; see Installing Toil with Extra Features for how
to install it if you do not have it.
You can run WDL workflows with toil-wdl-runner. Currently,
toil-wdl-runner works by using MiniWDL to parse and interpret the WDL
workflow, and has support for workflows in WDL 1.0 or later (which are required
to declare a version, and which use inputs and outputs sections).
Tip
The last release of Toil that supported unversioned, draft-2 WDL workflows was 5.12.0.
Toil is, for compatible workflows, a drop-in replacement for the Cromwell WDL runner. Instead of running a workflow with Cromwell:
java -jar Cromwell.jar run myWorkflow.wdl --inputs myWorkflow_inputs.json
You can run the workflow with toil-wdl-runner:
toil-wdl-runner myWorkflow.wdl --inputs myWorkflow_inputs.json
This will default to executing on the current machine, with a job store in an automatically determined temporary location, but you can add a few Toil options to use other Toil-supported batch systems, such as Kubernetes:
toil-wdl-runner --jobStore aws:us-west-2:wdl-job-store --batchSystem kubernetes myWorkflow.wdl --inputs myWorkflow_inputs.json
For Toil, the --inputs is optional, and inputs can be passed as a positional
argument:
toil-wdl-runner myWorkflow.wdl myWorkflow_inputs.json
You can also run workflows from URLs. For example, to run the MiniWDL self test workflow, you can do:
toil-wdl-runner https://raw.githubusercontent.com/DataBiosphere/toil/36b54c45e8554ded5093bcdd03edb2f6b0d93887/src/toil/test/wdl/miniwdl_self_test/self_test.wdl https://raw.githubusercontent.com/DataBiosphere/toil/36b54c45e8554ded5093bcdd03edb2f6b0d93887/src/toil/test/wdl/miniwdl_self_test/inputs.json
Toil WDL Runner Options¶
--jobStore: Specifies where to keep the Toil state information while
running the workflow. Must be accessible from all machines.
-o or --outputDirectory: Specifies the output folder or URI prefix to
save workflow output files in. Defaults to a new directory in the current
directory.
-m or --outputFile: Specifies a JSON file name or URI to save workflow
output values at. Defaults to standard output.
-i or --input: Alternative to the positional argument for the
input JSON file, for compatibility with other WDL runners.
--outputDialect: Specifies an output format dialect. Can be
cromwell to just return the workflow’s output values as JSON or miniwdl
to nest that under an outputs key and includes a dir key.
--container: Specifies the container engine to use to run tasks. By default
this is auto, which tries Singularity if it is installed and Docker if it
isn’t. Can also be set to docker or singularity explicitly.
Any number of other Toil options may also be specified. For defined Toil options, see Commandline Options.
Managing Workflow Logs¶
At the default settings, if a WDL task succeeds, the standard output and
standard error will be printed in the toil-wdl-runner output, unless they
are captured by the workflow (with the stdout() and stderr() WDL
built-in functions). If a WDL task fails, they will be printed whether they
were meant to be captured or not. Complete logs from Toil for failed jobs will
also be printed.
If you would like to save the logs organized by WDL task, you can use the
--writeLogs or --writeLogsGzip options to specify a directory where the
log files should be saved. Log files will be named after the same dotted,
hierarchical workflow and task names used to set values from the input JSON,
except that scatters will add an additional numerical component. In addition
to the logs for WDL tasks, Toil job logs for failed jobs will also appear here
when running at the default log level.
For example, if you run:
toil-wdl-runner --writeLogs logs https://raw.githubusercontent.com/DataBiosphere/toil/36b54c45e8554ded5093bcdd03edb2f6b0d93887/src/toil/test/wdl/miniwdl_self_test/self_test.wdl https://raw.githubusercontent.com/DataBiosphere/toil/36b54c45e8554ded5093bcdd03edb2f6b0d93887/src/toil/test/wdl/miniwdl_self_test/inputs.json
You will end up with a logs/ directory containing:
hello_caller.0.hello.stderr_000.log
hello_caller.1.hello.stderr_000.log
hello_caller.2.hello.stderr_000.log
The final number is a sequential counter: if a step has to be retried, or if you run the workflow multiple times without clearing out the logs directory, it will increment.
