"""
Contains possible interactions with the Galaxy Workflows
"""
from bioblend.galaxy.client import Client
import json
import os
[docs]class WorkflowClient(Client):
def __init__(self, galaxy_instance):
self.module = 'workflows'
super(WorkflowClient, self).__init__(galaxy_instance)
[docs] def get_workflows(self, workflow_id=None, name=None, deleted=False, published=False):
"""
Get all workflows or filter the specific one(s) via the provided ``name``
or ``workflow_id``. Provide only one argument, ``name`` or ``workflow_id``,
but not both.
:type workflow_id: str
:param workflow_id: Encoded workflow ID (incompatible with ``name``)
:type name: str
:param name: Filter by name of workflow (incompatible with
``workflow_id``). If multiple names match the given name, all the
workflows matching the argument will be returned.
:type deleted: bool
:param deleted: this parameter is deprecated and ignored, it will be
removed in BioBlend 0.6
:type published: bool
:param published: if ``True``, return also published workflows
:rtype: list
:return: A list of workflow dicts.
For example::
[{u'id': u'92c56938c2f9b315',
u'name': u'Simple',
u'url': u'/api/workflows/92c56938c2f9b315'}]
"""
if workflow_id is not None and name is not None:
raise ValueError('Provide only one argument between name or workflow_id, but not both')
kwargs = {}
if published:
kwargs['params'] = {'show_published': 'True'}
workflows = Client._get(self, **kwargs)
if workflow_id is not None:
workflow = next((_ for _ in workflows if _['id'] == workflow_id), None)
workflows = [workflow] if workflow is not None else []
elif name is not None:
workflows = [_ for _ in workflows if _['name'] == name]
return workflows
[docs] def show_workflow(self, workflow_id):
"""
Display information needed to run a workflow
:type workflow_id: str
:param workflow_id: Encoded workflow ID
:rtype: list
:return: A description of the workflow and its inputs as a JSON object.
For example::
{u'id': u'92c56938c2f9b315',
u'inputs': {u'23': {u'label': u'Input Dataset', u'value': u''}},
u'name': u'Simple',
u'url': u'/api/workflows/92c56938c2f9b315'}
"""
return Client._get(self, id=workflow_id)
[docs] def import_workflow_json(self, workflow_json):
"""
Imports a new workflow given a json representation of a previously exported
workflow.
:type workflow_json: str
:param workflow_json: JSON string representing the workflow to be imported
"""
payload = {}
payload['workflow'] = workflow_json
url = self.gi._make_url(self)
url = '/'.join([url, "upload"])
return Client._post(self, url=url, payload=payload)
[docs] def import_workflow_from_local_path(self, file_local_path):
"""
Imports a new workflow given the path to a file containing a previously
exported workflow.
:type file_local_path: str
:param file_local_path: File to upload to the server for new workflow
"""
with open(file_local_path, 'r') as fp:
workflow_json = json.load(fp)
return self.import_workflow_json(workflow_json)
[docs] def import_shared_workflow(self, workflow_id):
"""
Imports a new workflow from the shared published workflows
:type workflow_id: str
:param workflow_id: Encoded workflow ID
:rtype: dict
:return: A description of the workflow.
For example::
{u'id': u'ee0e2b4b696d9092',
u'model_class': u'StoredWorkflow',
u'name': u'Super workflow that solves everything!',
u'published': False,
u'tags': [],
u'url': u'/api/workflows/ee0e2b4b696d9092'}
"""
payload = {}
payload['workflow_id'] = workflow_id
url = self.gi._make_url(self)
url = '/'.join([url, 'import'])
return Client._post(self, url=url, payload=payload)
[docs] def export_workflow_json(self, workflow_id):
"""
Exports a workflow
:type workflow_id: str
:param workflow_id: Encoded workflow ID
:rtype: dict
:return: Dict representing the workflow requested
"""
url = self.gi._make_url(self)
url = '/'.join([url, "download"])
url = '/'.join([url, workflow_id])
return Client._get(self, url=url)
[docs] def export_workflow_to_local_path(self, workflow_id, file_local_path, use_default_filename=True):
"""
Exports a workflow in json format to a given local path.
:type workflow_id: str
:param workflow_id: Encoded workflow ID
:type file_local_path: str
:param file_local_path: Local path to which the exported file will be saved.
(Should not contain filename if use_default_name=True)
:type use_default_filename: bool
:param use_default_filename: If the use_default_name parameter is True, the exported
file will be saved as file_local_path/Galaxy-Workflow-%s.ga, where %s
is the workflow name. If use_default_name is False, file_local_path
is assumed to contain the full file path including filename.
"""
workflow_json = self.export_workflow_json(workflow_id)
if use_default_filename:
filename = 'Galaxy-Workflow-%s.ga' % workflow_json['name']
file_local_path = os.path.join(file_local_path, filename)
with open(file_local_path, 'w') as fp:
json.dump(workflow_json, fp)
[docs] def run_workflow(self, workflow_id, dataset_map=None, params=None,
history_id=None, history_name=None,
import_inputs_to_history=False, replacement_params=None):
"""
Run the workflow identified by ``workflow_id``
:type workflow_id: str
:param workflow_id: Encoded workflow ID
:type dataset_map: str or dict
:param dataset_map: A mapping of workflow inputs to datasets. The datasets
source can be a LibraryDatasetDatasetAssociation (``ldda``),
LibraryDataset (``ld``), or HistoryDatasetAssociation (``hda``).
The map must be in the following format:
``{'<input>': {'id': <encoded dataset ID>, 'src': '[ldda, ld, hda]'}}``
(e.g. ``{'23': {'id': '29beef4fadeed09f', 'src': 'ld'}}``)
:type params: str or dict
:param params: A mapping of tool parameters that are non-datasets parameters. The map must be in the
following format:
``{'blastn': {'param': 'evalue', 'value': '1e-06'}}``
:type history_id: str
:param history_id: The encoded history ID where to store the workflow
output. Alternatively, ``history_name`` may be specified to create a
new history.
:type history_name: str
:param history_name: Create a new history with the given name to store
the workflow output. If both ``history_id`` and ``history_name`` are
provided, ``history_name`` is ignored. If neither is specified, a new
'Unnamed history' is created.
:type import_inputs_to_history: bool
:param import_inputs_to_history: If ``True``, used workflow inputs will be imported
into the history. If ``False``, only workflow outputs
will be visible in the given history.
:type replacement_params: dict
:param replacement_params: pattern-based replacements for post-job actions (see below)
:rtype: dict
:return: A dict containing the history ID where the outputs are placed as well as
output dataset IDs.
For example::
{u'history': u'64177123325c9cfd',
u'outputs': [u'aa4d3084af404259']}
The ``replacement_params`` dict should map parameter names in
post-job actions (PJAs) to their runtime values. For
instance, if the final step has a PJA like the following::
{u'RenameDatasetActionout_file1': {
u'action_arguments': {u'newname': u'${output}'},
u'action_type': u'RenameDatasetAction',
u'output_name': u'out_file1'}}
then the following renames the output dataset to 'foo'::
replacement_params = {'output': 'foo'}
see also `this thread
<http://lists.bx.psu.edu/pipermail/galaxy-dev/2011-September/006875.html>`_
"""
payload = {}
payload['workflow_id'] = workflow_id
if dataset_map:
payload['ds_map'] = dataset_map
if params:
payload['parameters'] = params
if replacement_params:
payload['replacement_params'] = replacement_params
if history_id:
payload['history'] = 'hist_id={0}'.format(history_id)
elif history_name:
payload['history'] = history_name
if import_inputs_to_history is False:
payload['no_add_to_history'] = True
return Client._post(self, payload)
[docs] def delete_workflow(self, workflow_id):
"""
Delete a workflow identified by `workflow_id`.
:type workflow_id: str
:param workflow_id: Encoded workflow ID
.. warning::
Deleting a workflow is irreversible - all workflow data
will be permanently deleted.
"""
payload = {}
return Client._delete(self, payload, id=workflow_id)