Workflow Description Language local runner & developer toolkit for Python 3.6+
pip3 install miniwdl
conda install miniwdl after adding conda-forge
Source install: see the Dockerfile for dependencies to run setup.py
See the Releases for change logs. The Project board shows the current prioritization of issues.
Feedback and contributions to miniwdl are welcome, via issues and pull requests on this repository. See CONTRIBUTING.md for guidelines and instructions to set up your development environment.
miniwdl check /path/to/workflow.wdl loads the WDL document and shows a brief outline with any lint warnings. Add --path /path/to/tasks/ with a directory to search for imported documents (one or more times). Example with HumanCellAtlas/skylab:
$ git clone https://github.com/HumanCellAtlas/skylab.git
$ miniwdl check --path skylab/library/tasks/ \
skylab/pipelines/smartseq2_single_sample/SmartSeq2SingleSample.wdl
SmartSeq2SingleSample.wdl
workflow SmartSeq2SingleCell
(Ln 14, Col 8) UnusedDeclaration, nothing references File gtf_file
call HISAT2.HISAT2PairedEnd
call Picard.CollectMultipleMetrics
call Picard.CollectRnaMetrics
call Picard.CollectDuplicationMetrics
call HISAT2.HISAT2RSEM as HISAT2Transcriptome
call RSEM.RSEMExpression
call GroupQCs.GroupQCOutputs
call ZarrUtils.SmartSeq2ZarrConversion
GroupQCs : GroupMetricsOutputs.wdl
task GroupQCOutputs
(Ln 10, Col 10) StringCoercion, String mem = :Int:
(Ln 11, Col 10) StringCoercion, String cpu = :Int:
(Ln 12, Col 10) StringCoercion, String disk_space = :Int:
HISAT2 : HISAT2.wdl
task HISAT2PairedEnd
task HISAT2RSEM
task HISAT2InspectIndex (not called)
task HISAT2SingleEnd (not called)
Picard : Picard.wdl
task CollectDuplicationMetrics
task CollectMultipleMetrics
task CollectRnaMetrics
RSEM : RSEM.wdl
task RSEMExpression
ZarrUtils : ZarrUtils.wdl
task SmartSeq2ZarrConversion
(Ln 36, Col 6) CommandShellCheck, SC2006 Use $(..) instead of legacy `..`.
(Ln 39, Col 9) CommandShellCheck, SC2006 Use $(..) instead of legacy `..`.
(Ln 39, Col 15) CommandShellCheck, SC2086 Double quote to prevent globbing and word splitting.
(Ln 40, Col 10) CommandShellCheck, SC2086 Double quote to prevent globbing and word splitting.
(Ln 40, Col 21) CommandShellCheck, SC2086 Double quote to prevent globbing and word splitting.
Individual lint warnings can be suppressed by a WDL comment containing the string !WarningName on the same line or the following line.
In addition to its suite of WDL warnings, miniwdl check uses ShellCheck, if available, to detect possible issues in each task command script. You may need to install ShellCheck separately, as it's not included with miniwdl. Individual ShellCheck warnings can be suppressed with that tool's own directives.
miniwdl can run a parallelized workflow on the local host, provided that Docker is installed and the invoking user has permission to control it. (miniwdl uses the built-in Docker Swarm mode, which it'll enable locally if it isn't already.)
- Start with
miniwdl run_self_testfor a quick viability check.
By analyzing the WDL file, the runner can receive workflow inputs via the command line, as illustrated:
$ cat << 'EOF' > hello.wdl
version 1.0
task hello {
input {
Array[String]+ who
Int x = 0
}
command <<<
awk '{print "Hello", $0}' "~{write_lines(who)}"
>>>
output {
Array[String]+ messages = read_lines(stdout())
Int meaning_of_life = x+1
}
}
EOF
$ miniwdl run hello.wdl
missing required inputs for hello: who
required inputs:
Array[String]+ who
optional inputs:
Int x
outputs:
Array[String]+ messages
Int meaning_of_life
$ miniwdl run hello.wdl who=Alyssa "who=Ben Bitdiddle" x=41
{
"outputs": {
"hello.messages": [
"Hello Alyssa",
"Hello Ben Bitdiddle"
],
"hello.meaning_of_life": 42
},
"dir": "/home/user/20190718_213847_hello"
}
Relative or absolute paths, and web URIs to download, are accepted for File inputs. The runner can also provide shell tab-completion for the workflow's available inputs. To use this, enable argcomplete global completion by invoking activate-global-python-argcomplete and starting a new shell session. Then, start a command line miniwdl run hello.wdl and try double-tab.
Lastly, inputs can be supplied through a Cromwell-style JSON file; see miniwdl run --help for this and other options.
The WDL package provides programmatic access to the WDL parser and AST. The following example prints all declarations in a workflow, descending into scatter and if stanzas as needed.
$ python3 -c "
import WDL
doc = WDL.load('skylab/pipelines/optimus/Optimus.wdl',
path=['skylab/library/tasks/'])
def show(body):
for elt in body:
if isinstance(elt, WDL.Decl):
print(str(elt.type) + ' ' + elt.name)
elif isinstance(elt, WDL.Scatter) or isinstance(elt, WDL.Conditional):
show(elt.body)
show(doc.workflow.body)
"
String version
Array[File] r1_fastq
Array[File] r2_fastq
Array[File] i1_fastq
String sample_id
File tar_star_reference
File annotations_gtf
File ref_genome_fasta
File whitelist
String fastq_suffix
Array[Int] indices
Array[File] non_optional_i1_fastq
File barcoded_bam
Online Python developer documentation for the WDL package:
The documentation includes several Python Codelabs to get started.
Read the Docs currently builds from the mlin/miniwdl fork of this repository. Locally, make doc triggers Sphinx to generate the docs under docs/_build/html/. Or, after building the docker image, copy them out with docker run --rm -v ~/Desktop:/io miniwdl cp -r /miniwdl/docs/_build/html /io/miniwdl_docs.
Please disclose security issues responsibly by contacting [email protected].