def generate_workflow_image(trans, workflow_name, repository_metadata_id=None, repository_id=None):
"""
Return an svg image representation of a workflow dictionary created when the workflow was exported. This method is called
from both Galaxy and the tool shed. When called from the tool shed, repository_metadata_id will have a value and repository_id
will be None. When called from Galaxy, repository_metadata_id will be None and repository_id will have a value.
"""
workflow_name = encoding_util.tool_shed_decode(workflow_name)
if trans.webapp.name == 'tool_shed':
# We're in the tool shed.
repository_metadata = metadata_util.get_repository_metadata_by_id(trans.app, repository_metadata_id)
repository_id = trans.security.encode_id(repository_metadata.repository_id)
changeset_revision = repository_metadata.changeset_revision
metadata = repository_metadata.metadata
else:
# We're in Galaxy.
repository = repository_util.get_tool_shed_repository_by_id(trans.app, repository_id)
changeset_revision = repository.changeset_revision
metadata = repository.metadata
# metadata[ 'workflows' ] is a list of tuples where each contained tuple is
# [ <relative path to the .ga file in the repository>, <exported workflow dict> ]
for workflow_tup in metadata['workflows']:
workflow_dict = workflow_tup[1]
if workflow_dict['name'] == workflow_name:
break
if 'tools' in metadata:
tools_metadata = metadata['tools']
else:
tools_metadata = []
workflow, missing_tool_tups = get_workflow_from_dict(trans=trans,
workflow_dict=workflow_dict,
tools_metadata=tools_metadata,
repository_id=repository_id,
changeset_revision=changeset_revision)
workflow_canvas = WorkflowCanvas()
canvas = workflow_canvas.canvas
# Store px width for boxes of each step.
for step in workflow.steps:
step.upgrade_messages = {}
module = module_factory.from_workflow_step(trans, repository_id, changeset_revision, tools_metadata, step)
tool_errors = module.type == 'tool' and not module.tool
module_data_inputs = get_workflow_data_inputs(step, module)
module_data_outputs = get_workflow_data_outputs(step, module, workflow.steps)
module_name = get_workflow_module_name(module, missing_tool_tups)
workflow_canvas.populate_data_for_step(
step,
module_name,
module_data_inputs,
module_data_outputs,
tool_errors=tool_errors
)
workflow_canvas.add_steps(highlight_errors=True)
workflow_canvas.finish()
trans.response.set_content_type("image/svg+xml")
return canvas.tostring()
def generate_workflow_image( trans, workflow_name, repository_metadata_id=None, repository_id=None ):
"""
Return an svg image representation of a workflow dictionary created when the workflow was exported. This method is called
from both Galaxy and the tool shed. When called from the tool shed, repository_metadata_id will have a value and repository_id
will be None. When called from Galaxy, repository_metadata_id will be None and repository_id will have a value.
"""
workflow_name = encoding_util.tool_shed_decode( workflow_name )
if trans.webapp.name == 'tool_shed':
# We're in the tool shed.
repository_metadata = metadata_util.get_repository_metadata_by_id( trans.app, repository_metadata_id )
repository_id = trans.security.encode_id( repository_metadata.repository_id )
changeset_revision = repository_metadata.changeset_revision
metadata = repository_metadata.metadata
else:
# We're in Galaxy.
repository = suc.get_tool_shed_repository_by_id( trans.app, repository_id )
changeset_revision = repository.changeset_revision
metadata = repository.metadata
# metadata[ 'workflows' ] is a list of tuples where each contained tuple is
# [ <relative path to the .ga file in the repository>, <exported workflow dict> ]
for workflow_tup in metadata[ 'workflows' ]:
workflow_dict = workflow_tup[1]
if workflow_dict[ 'name' ] == workflow_name:
break
if 'tools' in metadata:
tools_metadata = metadata[ 'tools' ]
else:
tools_metadata = []
workflow, missing_tool_tups = get_workflow_from_dict( trans=trans,
workflow_dict=workflow_dict,
tools_metadata=tools_metadata,
repository_id=repository_id,
changeset_revision=changeset_revision )
workflow_canvas = WorkflowCanvas()
canvas = workflow_canvas.canvas
# Store px width for boxes of each step.
for step in workflow.steps:
step.upgrade_messages = {}
module = module_factory.from_workflow_step( trans, repository_id, changeset_revision, tools_metadata, step )
tool_errors = module.type == 'tool' and not module.tool
module_data_inputs = get_workflow_data_inputs( step, module )
module_data_outputs = get_workflow_data_outputs( step, module, workflow.steps )
module_name = get_workflow_module_name( module, missing_tool_tups )
workflow_canvas.populate_data_for_step(
step,
module_name,
module_data_inputs,
module_data_outputs,
tool_errors=tool_errors
)
workflow_canvas.add_steps( highlight_errors=True )
workflow_canvas.finish( )
trans.response.set_content_type( "image/svg+xml" )
return canvas.tostring()
def _workflow_to_svg_canvas(self, trans, stored):
workflow = stored.latest_workflow
workflow_canvas = WorkflowCanvas()
for step in workflow.steps:
# Load from database representation
module = module_factory.from_workflow_step(trans, step)
module_name = module.get_name()
module_data_inputs = module.get_data_inputs()
module_data_outputs = module.get_data_outputs()
workflow_canvas.populate_data_for_step(
step,
module_name,
module_data_inputs,
module_data_outputs,
)
workflow_canvas.add_steps()
return workflow_canvas.finish()
def _workflow_to_svg_canvas(self, trans, stored):
workflow = stored.latest_workflow
workflow_canvas = WorkflowCanvas()
for step in workflow.steps:
# Load from database representation
module = module_factory.from_workflow_step(trans, step)
module_name = module.get_name()
module_data_inputs = module.get_data_inputs()
module_data_outputs = module.get_data_outputs()
workflow_canvas.populate_data_for_step(
step,
module_name,
module_data_inputs,
module_data_outputs,
)
workflow_canvas.add_steps()
return workflow_canvas.finish()
