Common workflow language reference implementation
Project description
==================================================================
Common workflow language tool description reference implementation
==================================================================
CWL Conformance test: |Build Status|
Travis: |Unix Build Status|
.. |Unix Build Status| image:: https://img.shields.io/travis/common-workflow-language/cwltool/master.svg?label=unix%20build
:target: https://travis-ci.org/common-workflow-language/cwltool
This is the reference implementation of the Common Workflow Language. It is
intended to be 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.
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.
Install
-------
Installing the official package from PyPi (will install "cwltool" package as
well)::
pip install cwlref-runner
If installing alongside another CWL implementation then::
pip install cwltool
To install from source::
git clone https://github.com/common-workflow-language/cwltool.git
cd cwltool && python setup.py install
cd cwlref-runner && python setup.py install # co-installing? skip this
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 <https://wiki.debian.org/DebianAlternatives>`_.
Running tests locally
---------------------
- Running basic tests ``(/tests)``:
.. code:: bash
python setup.py test
- Running the entire suite of CWL conformance tests:
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 <https://github.com/common-workflow-language/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
Run on the command line
-----------------------
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]
Use with boot2docker
--------------------
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.json
.. |Build Status| image:: https://ci.commonwl.org/buildStatus/icon?job=cwltool-conformance
:target: https://ci.commonwl.org/job/cwltool-conformance/
Tool 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 API
--------------------------------
Cwltool 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
.. _`GA4GH Tool Registry API`: https://github.com/ga4gh/tool-registry-schemas
Import as a module
------------------
Add::
import cwltool
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 decoarated 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
<http://modules.sourceforge.net/>`__.
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.
.. code:: yaml
SoftwareRequirement:
packages:
- package: seqtk
version:
- r93
Now imagine deploying cwltool on a cluster with Software Modules installed
and that a ``seqtk`` module is avaialble at version ``r93``. This means cluster
users likely won't have the ``seqtk`` the binary 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:
.. code:: yaml
- type: module
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
<https://docs.galaxyproject.org/en/latest/admin/dependency_resolvers.html>`__.
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.
.. code:: yaml
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:
.. code:: yaml
- 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`):
.. code:: yaml
- 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`):
.. code:: yaml
- 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 <https://conda.io/docs/#>`__ 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:
.. code:: yaml
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 <https://github.com/galaxyproject/galaxy-lib>`__ - a small, portable subset of the Galaxy
project. More information on configuration and implementation can be found
at the following links:
- `Dependency Resolvers in Galaxy <https://docs.galaxyproject.org/en/latest/admin/dependency_resolvers.html>`__
- `Conda for [Galaxy] Tool Dependencies <https://docs.galaxyproject.org/en/latest/admin/conda_faq.html>`__
- `Mapping Files - Implementation <https://github.com/galaxyproject/galaxy/commit/495802d229967771df5b64a2f79b88a0eaf00edb>`__
- `Specifications - Implementation <https://github.com/galaxyproject/galaxy/commit/81d71d2e740ee07754785306e4448f8425f890bc>`__
- `Initial cwltool Integration Pull Request <https://github.com/common-workflow-language/cwltool/pull/214>`__
Cwltool control flow
--------------------
Technical outline of how cwltool works internally, for maintainers.
#. Use CWL `load_tool()` to load document.
#. Fetches the document from file or URL
#. Applies preprocessing (syntax/identifier expansion and normalization)
#. Validates the document based on cwlVersion
#. If necessary, updates the document to latest spec
#. Constructs a Process object using `make_tool()` callback. This yields a
CommandLineTool, Workflow, or ExpressionTool. For workflows, this
recursively constructs each workflow step.
#. To construct custom types for CommandLineTool, Workflow, or
ExpressionTool, provide a custom `make_tool()`
#. Iterate on the `job()` method of the Process object to get back runnable jobs.
#. `job()` is a generator method (uses the Python iterator protocol)
#. Each time the `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.)
#. Invoke the runnable item by calling `run()`. This runs the tool and gets output.
#. Output of a process is reported by an output callback.
#. `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.
#. The WorkflowJob iterates over each WorkflowJobStep and determines if the
inputs the step are ready.
#. When a step is ready, it constructs an input object for that step and
iterates on the `job()` method of the workflow job step.
#. Each runnable item is yielded back up to top level run loop
#. When a step job completes and receives an output callback, the
job outputs are assigned to the output of the workflow step.
#. When all steps are complete, the intermediate files are moved to a final
workflow output, intermediate directories are deleted, and the output
callback for the workflow is called.
#. "CommandLineTool" job() objects yield a single runnable object.
#. The CommandLineTool `job()` method calls `makeJobRunner()` to create a
`CommandLineJob` object
#. The job method configures the CommandLineJob object by setting public
attributes
#. The job method iterates over file and directories inputs to the
CommandLineTool and creates a "path map".
#. Files are mapped from their "resolved" location to a "target" path where
they will appear at tool invocation (for example, a location inside a
Docker container.) The target paths are used on the command line.
#. Files are staged to targets paths using either Docker volume binds (when
using containers) or symlinks (if not). This staging step enables files
to be logically rearranged or renamed independent of their source layout.
#. The run() method of CommandLineJob executes the command line tool or
Docker container, waits for it to complete, collects output, and makes
the output callback.
Extension points
----------------
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.
versionfunc()
() -> 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.
Common workflow language tool description reference implementation
==================================================================
CWL Conformance test: |Build Status|
Travis: |Unix Build Status|
.. |Unix Build Status| image:: https://img.shields.io/travis/common-workflow-language/cwltool/master.svg?label=unix%20build
:target: https://travis-ci.org/common-workflow-language/cwltool
This is the reference implementation of the Common Workflow Language. It is
intended to be 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.
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.
Install
-------
Installing the official package from PyPi (will install "cwltool" package as
well)::
pip install cwlref-runner
If installing alongside another CWL implementation then::
pip install cwltool
To install from source::
git clone https://github.com/common-workflow-language/cwltool.git
cd cwltool && python setup.py install
cd cwlref-runner && python setup.py install # co-installing? skip this
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 <https://wiki.debian.org/DebianAlternatives>`_.
Running tests locally
---------------------
- Running basic tests ``(/tests)``:
.. code:: bash
python setup.py test
- Running the entire suite of CWL conformance tests:
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 <https://github.com/common-workflow-language/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
Run on the command line
-----------------------
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]
Use with boot2docker
--------------------
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.json
.. |Build Status| image:: https://ci.commonwl.org/buildStatus/icon?job=cwltool-conformance
:target: https://ci.commonwl.org/job/cwltool-conformance/
Tool 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 API
--------------------------------
Cwltool 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
.. _`GA4GH Tool Registry API`: https://github.com/ga4gh/tool-registry-schemas
Import as a module
------------------
Add::
import cwltool
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 decoarated 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
<http://modules.sourceforge.net/>`__.
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.
.. code:: yaml
SoftwareRequirement:
packages:
- package: seqtk
version:
- r93
Now imagine deploying cwltool on a cluster with Software Modules installed
and that a ``seqtk`` module is avaialble at version ``r93``. This means cluster
users likely won't have the ``seqtk`` the binary 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:
.. code:: yaml
- type: module
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
<https://docs.galaxyproject.org/en/latest/admin/dependency_resolvers.html>`__.
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.
.. code:: yaml
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:
.. code:: yaml
- 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`):
.. code:: yaml
- 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`):
.. code:: yaml
- 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 <https://conda.io/docs/#>`__ 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:
.. code:: yaml
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 <https://github.com/galaxyproject/galaxy-lib>`__ - a small, portable subset of the Galaxy
project. More information on configuration and implementation can be found
at the following links:
- `Dependency Resolvers in Galaxy <https://docs.galaxyproject.org/en/latest/admin/dependency_resolvers.html>`__
- `Conda for [Galaxy] Tool Dependencies <https://docs.galaxyproject.org/en/latest/admin/conda_faq.html>`__
- `Mapping Files - Implementation <https://github.com/galaxyproject/galaxy/commit/495802d229967771df5b64a2f79b88a0eaf00edb>`__
- `Specifications - Implementation <https://github.com/galaxyproject/galaxy/commit/81d71d2e740ee07754785306e4448f8425f890bc>`__
- `Initial cwltool Integration Pull Request <https://github.com/common-workflow-language/cwltool/pull/214>`__
Cwltool control flow
--------------------
Technical outline of how cwltool works internally, for maintainers.
#. Use CWL `load_tool()` to load document.
#. Fetches the document from file or URL
#. Applies preprocessing (syntax/identifier expansion and normalization)
#. Validates the document based on cwlVersion
#. If necessary, updates the document to latest spec
#. Constructs a Process object using `make_tool()` callback. This yields a
CommandLineTool, Workflow, or ExpressionTool. For workflows, this
recursively constructs each workflow step.
#. To construct custom types for CommandLineTool, Workflow, or
ExpressionTool, provide a custom `make_tool()`
#. Iterate on the `job()` method of the Process object to get back runnable jobs.
#. `job()` is a generator method (uses the Python iterator protocol)
#. Each time the `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.)
#. Invoke the runnable item by calling `run()`. This runs the tool and gets output.
#. Output of a process is reported by an output callback.
#. `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.
#. The WorkflowJob iterates over each WorkflowJobStep and determines if the
inputs the step are ready.
#. When a step is ready, it constructs an input object for that step and
iterates on the `job()` method of the workflow job step.
#. Each runnable item is yielded back up to top level run loop
#. When a step job completes and receives an output callback, the
job outputs are assigned to the output of the workflow step.
#. When all steps are complete, the intermediate files are moved to a final
workflow output, intermediate directories are deleted, and the output
callback for the workflow is called.
#. "CommandLineTool" job() objects yield a single runnable object.
#. The CommandLineTool `job()` method calls `makeJobRunner()` to create a
`CommandLineJob` object
#. The job method configures the CommandLineJob object by setting public
attributes
#. The job method iterates over file and directories inputs to the
CommandLineTool and creates a "path map".
#. Files are mapped from their "resolved" location to a "target" path where
they will appear at tool invocation (for example, a location inside a
Docker container.) The target paths are used on the command line.
#. Files are staged to targets paths using either Docker volume binds (when
using containers) or symlinks (if not). This staging step enables files
to be logically rearranged or renamed independent of their source layout.
#. The run() method of CommandLineJob executes the command line tool or
Docker container, waits for it to complete, collects output, and makes
the output callback.
Extension points
----------------
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.
versionfunc()
() -> 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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