This is the reference implementation of the Common Workflow Language. It is intended to feature complete and provide comprehensive validation of CWL files as well as provide other tools related to working with CWL.
This is written and tested for Python 2.7 and 3.x {x = 4, 5, 6}
The reference implementation consists of two packages. The cwltool package is the primary Python module containing the reference implementation in the cwltool module and console executable by the same name.
The cwlref-runner package is optional and provides an additional entry point under the alias cwl-runner, which is the implementation-agnostic name for the default CWL interpreter installed on a host.
It is highly recommended to setup virtual environment before installing cwltool:
virtualenv -p python2 venv # Create a virtual environment, can use `python3` as well source venv/bin/activate # Activate environment before installing `cwltool`
Installing the official package from PyPi (will install "cwltool" package as well)
pip install cwlref-runner
If installing alongside another CWL implementation then
Or you can install from source:
git clone https://github.com/common-workflow-language/cwltool.git # clone cwltool repo cd cwltool # Switch to source directory pip install . # Install `cwltool` from source cwltool --version # Check if the installation works correctly
Remember, if co-installing multiple CWL implementations then you need to maintain which implementation cwl-runner points to via a symbolic file system link or another facility.
(/tests):To run the basis tests after installing cwltool execute the following:
pip install pytest mock py.test --ignore cwltool/schemas/ --pyarg cwltool
To run various tests in all supported Python environments we use tox. To run the test suite in all supported Python environments first downloading the complete code repository (see the git clone instructions above) and then run the following in the terminal: pip install tox; tox
List of all environment can be seen using: tox --listenvs and running a specfic test env using: tox -e <env name> and additionally run a specific test using this format: tox -e py36-unit -- tests/test_examples.py::TestParamMatching
The GitHub repository for the CWL specifications contains a script that tests a CWL implementation against a wide array of valid CWL files using the cwltest program
Instructions for running these tests can be found in the Common Workflow Language Specification repository at https://github.com/common-workflow-language/common-workflow-language/blob/master/CONFORMANCE_TESTS.md
Simple command:
cwl-runner [tool-or-workflow-description] [input-job-settings]
Or if you have multiple CWL implementations installed and you want to override the default cwl-runner use:
cwltool [tool-or-workflow-description] [input-job-settings]
boot2docker is running docker inside a virtual machine and it only mounts Users on it. The default behavior of CWL is to create temporary directories under e.g. /Var which is not accessible to Docker containers.
To run CWL successfully with boot2docker you need to set the --tmpdir-prefix and --tmp-outdir-prefix to somewhere under /Users:
$ cwl-runner --tmp-outdir-prefix=/Users/username/project --tmpdir-prefix=/Users/username/project wc-tool.cwl wc-job.jsonUsing user-space replacements for Docker
Some shared computing environments don't support Docker software containers for technical or policy reasons. As a work around, the CWL reference runner supports using a alternative docker implementations on Linux with the --user-space-docker-cmd option.
One such "user space" friendly docker replacement is udocker https://github.com/indigo-dc/udocker and another is dx-docker https://wiki.dnanexus.com/Developer-Tutorials/Using-Docker-Images
udocker installation: https://github.com/indigo-dc/udocker/blob/master/doc/installation_manual.md#22-install-from-indigo-datacloud-repositories
dx-docker installation: start with the DNAnexus toolkit (see https://wiki.dnanexus.com/Downloads for instructions).
Run cwltool just as you normally would, but with the new option, e.g. from the conformance tests:
cwltool --user-space-docker-cmd=udocker https://raw.githubusercontent.com/common-workflow-language/common-workflow-language/master/v1.0/v1.0/test-cwl-out2.cwl https://github.com/common-workflow-language/common-workflow-language/blob/master/v1.0/v1.0/empty.json
or
cwltool --user-space-docker-cmd=dx-docker https://raw.githubusercontent.com/common-workflow-language/common-workflow-language/master/v1.0/v1.0/test-cwl-out2.cwl https://github.com/common-workflow-language/common-workflow-language/blob/master/v1.0/v1.0/empty.json
cwltool can use Singularity as a Docker container runtime, an experimental feature. Singularity will run software containers specified in DockerRequirement and therefore works with Docker images only, native Singularity images are not supported. To use Singularity as the Docker container runtime, provide --singularity command line option to cwltool.
cwltool --singularity https://raw.githubusercontent.com/common-workflow-language/common-workflow-language/master/v1.0/v1.0/v1.0/cat3-tool-mediumcut.cwl https://github.com/common-workflow-language/common-workflow-language/blob/master/v1.0/v1.0/cat-job.jsonTool or workflow loading from remote or local locations
cwltool can run tool and workflow descriptions on both local and remote systems via its support for HTTP[S] URLs.
Input job files and Workflow steps (via the run directive) can reference CWL documents using absolute or relative local filesytem paths. If a relative path is referenced and that document isn't found in the current directory then the following locations will be searched: http://www.commonwl.org/v1.0/CommandLineTool.html#Discovering_CWL_documents_on_a_local_filesystem
Use with GA4GH Tool Registry APICwltool can launch tools directly from GA4GH Tool Registry API endpoints.
By default, cwltool searches https://dockstore.org/ . Use --add-tool-registry to add other registries to the search path.
For example
cwltool --non-strict quay.io/collaboratory/dockstore-tool-bamstats:master test.json
and (defaults to latest when a version is not specified)
cwltool --non-strict quay.io/collaboratory/dockstore-tool-bamstats test.json
For this example, grab the test.json (and input file) from https://github.com/CancerCollaboratory/dockstore-tool-bamstats
Add
to your script.
The easiest way to use cwltool to run a tool or workflow from Python is to use a Factory
import cwltool.factory
fac = cwltool.factory.Factory()
echo = f.make("echo.cwl")
result = echo(inp="foo")
# result["out"] == "foo" Leveraging SoftwareRequirements (Beta)
CWL tools may be decorated with SoftwareRequirement hints that cwltool may in turn use to resolve to packages in various package managers or dependency management systems such as Environment Modules.
Utilizing SoftwareRequirement hints using cwltool requires an optional dependency, for this reason be sure to use specify the deps modifier when installing cwltool. For instance:
$ pip install 'cwltool[deps]'
Installing cwltool in this fashion enables several new command line options. The most general of these options is --beta-dependency-resolvers-configuration. This option allows one to specify a dependency resolvers configuration file. This file may be specified as either XML or YAML and very simply describes various plugins to enable to "resolve" SoftwareRequirement dependencies.
To discuss some of these plugins and how to configure them, first consider the following hint definition for an example CWL tool.
SoftwareRequirement:
packages:
- package: seqtk
version:
- r93
Now imagine deploying cwltool on a cluster with Software Modules installed and that a seqtk module is available at version r93. This means cluster users likely won't have the binary seqtk on their PATH by default, but after sourcing this module with the command modulecmd sh load seqtk/r93 seqtk is available on the PATH. A simple dependency resolvers configuration file, called dependency-resolvers-conf.yml for instance, that would enable cwltool to source the correct module environment before executing the above tool would simply be:
The outer list indicates that one plugin is being enabled, the plugin parameters are defined as a dictionary for this one list item. There is only one required parameter for the plugin above, this is type and defines the plugin type. This parameter is required for all plugins. The available plugins and the parameters available for each are documented (incompletely) here. Unfortunately, this documentation is in the context of Galaxy tool requirement s instead of CWL SoftwareRequirement s, but the concepts map fairly directly.
cwltool is distributed with an example of such seqtk tool and sample corresponding job. It could executed from the cwltool root using a dependency resolvers configuration file such as the above one using the command:
cwltool --beta-dependency-resolvers-configuration /path/to/dependency-resolvers-conf.yml \
tests/seqtk_seq.cwl \
tests/seqtk_seq_job.json
This example demonstrates both that cwltool can leverage existing software installations and also handle workflows with dependencies on different versions of the same software and libraries. However the above example does require an existing module setup so it is impossible to test this example "out of the box" with cwltool. For a more isolated test that demonstrates all the same concepts - the resolver plugin type galaxy_packages can be used.
"Galaxy packages" are a lighter weight alternative to Environment Modules that are really just defined by a way to lay out directories into packages and versions to find little scripts that are sourced to modify the environment. They have been used for years in Galaxy community to adapt Galaxy tools to cluster environments but require neither knowledge of Galaxy nor any special tools to setup. These should work just fine for CWL tools.
The cwltool source code repository's test directory is setup with a very simple directory that defines a set of "Galaxy packages" (but really just defines one package named random-lines). The directory layout is simply:
tests/test_deps_env/
random-lines/
1.0/
env.sh
If the galaxy_packages plugin is enabled and pointed at the tests/test_deps_env directory in cwltool's root and a SoftwareRequirement such as the following is encountered.
hints:
SoftwareRequirement:
packages:
- package: 'random-lines'
version:
- '1.0'
Then cwltool will simply find that env.sh file and source it before executing the corresponding tool. That env.sh script is only responsible for modifying the job's PATH to add the required binaries.
This is a full example that works since resolving "Galaxy packages" has no external requirements. Try it out by executing the following command from cwltool's root directory:
cwltool --beta-dependency-resolvers-configuration tests/test_deps_env_resolvers_conf.yml \
tests/random_lines.cwl \
tests/random_lines_job.json
The resolvers configuration file in the above example was simply:
- type: galaxy_packages base_path: ./tests/test_deps_env
It is possible that the SoftwareRequirement s in a given CWL tool will not match the module names for a given cluster. Such requirements can be re-mapped to specific deployed packages and/or versions using another file specified using the resolver plugin parameter mapping_files. We will demonstrate this using galaxy_packages but the concepts apply equally well to Environment Modules or Conda packages (described below) for instance.
So consider the resolvers configuration file (tests/test_deps_env_resolvers_conf_rewrite.yml):
- type: galaxy_packages base_path: ./tests/test_deps_env mapping_files: ./tests/test_deps_mapping.yml
And the corresponding mapping configuraiton file (tests/test_deps_mapping.yml):
- from:
name: randomLines
version: 1.0.0-rc1
to:
name: random-lines
version: '1.0'
This is saying if cwltool encounters a requirement of randomLines at version 1.0.0-rc1 in a tool, to rewrite to our specific plugin as random-lines at version 1.0. cwltool has such a test tool called random_lines_mapping.cwl that contains such a source SoftwareRequirement. To try out this example with mapping, execute the following command from the cwltool root directory:
cwltool --beta-dependency-resolvers-configuration tests/test_deps_env_resolvers_conf_rewrite.yml \
tests/random_lines_mapping.cwl \
tests/random_lines_job.json
The previous examples demonstrated leveraging existing infrastructure to provide requirements for CWL tools. If instead a real package manager is used cwltool has the oppertunity to install requirements as needed. While initial support for Homebrew/Linuxbrew plugins is available, the most developed such plugin is for the Conda package manager. Conda has the nice properties of allowing multiple versions of a package to be installed simultaneously, not requiring evalated permissions to install Conda itself or packages using Conda, and being cross platform. For these reasons, cwltool may run as a normal user, install its own Conda environment and manage multiple versions of Conda packages on both Linux and Mac OS X.
The Conda plugin can be endlessly configured, but a sensible set of defaults that has proven a powerful stack for dependency management within the Galaxy tool development ecosystem can be enabled by simply passing cwltool the --beta-conda-dependencies flag.
With this we can use the seqtk example above without Docker and without any externally managed services - cwltool should install everything it needs and create an environment for the tool. Try it out with the follwing command:
cwltool --beta-conda-dependencies tests/seqtk_seq.cwl tests/seqtk_seq_job.json
The CWL specification allows URIs to be attached to SoftwareRequirement s that allow disambiguation of package names. If the mapping files described above allow deployers to adapt tools to their infrastructure, this mechanism allows tools to adapt their requirements to multiple package managers. To demonstrate this within the context of the seqtk, we can simply break the package name we use and then specify a specific Conda package as follows:
hints:
SoftwareRequirement:
packages:
- package: seqtk_seq
version:
- '1.2'
specs:
- https://anaconda.org/bioconda/seqtk
- https://packages.debian.org/sid/seqtk
The example can be executed using the command:
cwltool --beta-conda-dependencies tests/seqtk_seq_wrong_name.cwl tests/seqtk_seq_job.json
The plugin framework for managing resolution of these software requirements as maintained as part of galaxy-lib - a small, portable subset of the Galaxy project. More information on configuration and implementation can be found at the following links:
Sometimes a workflow needs additional requirements to run in a particular environment or with a particular dataset. To avoid the need to modify the underlying workflow, cwltool supports requirement "overrides".
The format of the "overrides" object is a mapping of item identifier (workflow, workflow step, or command line tool) to the process requirements that should be applied.
cwltool:overrides:
echo.cwl:
requirements:
EnvVarRequirement:
envDef:
MESSAGE: override_value
Overrides can be specified either on the command line, or as part of the job input document. Workflow steps are identified using the name of the workflow file followed by the step name as a document fragment identifier "#id". Override identifiers are relative to the toplevel workflow document.
cwltool --overrides overrides.yml my-tool.cwl my-job.yml
input_parameter1: value1
input_parameter2: value2
cwltool:overrides:
workflow.cwl#step1:
requirements:
EnvVarRequirement:
envDef:
MESSAGE: override_value
cwltool my-tool.cwl my-job-with-overrides.yml
Technical outline of how cwltool works internally, for maintainers.
load_tool() to load document.
make_tool()` callback. This yields a CommandLineTool, Workflow, or ExpressionTool. For workflows, this recursively constructs each workflow step.make_tool()job() method of the Process object to get back runnable jobs.
job() is a generator method (uses the Python iterator protocol)job() method is invoked in an iteration, it returns one of: a runnable item (an object with a run() method), None (indicating there is currently no work ready to run) or end of iteration (indicating the process is complete.)run(). This runs the tool and gets output.job() may be iterated over multiple times. It will yield all the work that is currently ready to run and then yield None.Workflow objects create a corresponding WorkflowJob and WorkflowJobStep objects to hold the workflow state for the duration of the job invocation.
job() method of the workflow job step.CommandLineTool job() objects yield a single runnable object.
job() method calls makeJobRunner() to create a CommandLineJob objectrun() method of CommandLineJob executes the command line tool or Docker container, waits for it to complete, collects output, and makes the output callback.The following functions can be provided to main(), to load_tool(), or to the executor to override or augment the listed behaviors.
executor(tool, job_order_object, **kwargs) (Process, Dict[Text, Any], **Any) -> Tuple[Dict[Text, Any], Text]
A toplevel workflow execution loop, should synchronously execute a process object and return an output object.
makeTool(toolpath_object, **kwargs) (Dict[Text, Any], **Any) -> Process
Construct a Process object from a document.
selectResources(request) (Dict[Text, int]) -> Dict[Text, int]
Take a resource request and turn it into a concrete resource assignment.
() () -> Text
Return version string.
make_fs_access(basedir) (Text) -> StdFsAccess
Return a file system access object.
fetcher_constructor(cache, session) (Dict[unicode, unicode], requests.sessions.Session) -> Fetcher
Construct a Fetcher object with the supplied cache and HTTP session.
resolver(document_loader, document) (Loader, Union[Text, dict[Text, Any]]) -> Text
Resolve a relative document identifier to an absolute one which can be fetched.
logger_handler logging.Handler
Handler object for logging.
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