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140 lines
4.6 KiB
Python
140 lines
4.6 KiB
Python
from functools import partial
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import yaml
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from galaxy import model
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from galaxy.model import mapping
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from galaxy.security.idencoding import IdEncodingHelper
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from galaxy.util import bunch
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class MockTrans(object):
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def __init__(self):
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self.app = TestApp()
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self.sa_session = self.app.model.context
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self._user = None
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def save_workflow(self, workflow):
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stored_workflow = model.StoredWorkflow()
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stored_workflow.latest_workflow = workflow
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workflow.stored_workflow = stored_workflow
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stored_workflow.user = self.user
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self.sa_session.add(stored_workflow)
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self.sa_session.flush()
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return stored_workflow
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@property
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def user(self):
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if self._user is None:
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self._user = model.User(
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email="testworkflows@bx.psu.edu",
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password="password"
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)
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return self._user
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class TestApp(object):
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def __init__(self):
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self.config = bunch.Bunch(
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tool_secret="awesome_secret",
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)
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self.model = mapping.init(
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"/tmp",
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"sqlite:///:memory:",
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create_tables=True
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)
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self.toolbox = TestToolbox()
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self.datatypes_registry = TestDatatypesRegistry()
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self.security = IdEncodingHelper(id_secret="testing")
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class TestDatatypesRegistry(object):
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def __init__(self):
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pass
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def get_datatype_by_extension(self, ext):
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return ext
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class TestToolbox(object):
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def __init__(self):
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self.tools = {}
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def get_tool(self, tool_id, tool_version=None, exact=False, tool_uuid=None):
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# Real tool box returns None of missing tool also
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return self.tools.get(tool_id, None)
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def get_tool_id(self, tool_id):
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tool = self.get_tool(tool_id)
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return tool and tool.id
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def yaml_to_model(has_dict, id_offset=100):
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if isinstance(has_dict, str):
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has_dict = yaml.safe_load(has_dict)
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workflow = model.Workflow()
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workflow.steps = []
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for i, step in enumerate(has_dict.get("steps", [])):
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workflow_step = model.WorkflowStep()
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if "order_index" not in step:
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step["order_index"] = i
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if "id" not in step:
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# Fixed Offset ids just to test against assuption order_index != id
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step["id"] = id_offset
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id_offset += 1
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step_type = step.get("type", None)
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assert step_type is not None
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if step_type == "subworkflow":
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subworkflow_dict = step["subworkflow"]
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del step["subworkflow"]
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subworkflow = yaml_to_model(subworkflow_dict, id_offset=id_offset)
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step["subworkflow"] = subworkflow
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id_offset += len(subworkflow.steps)
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for key, value in step.items():
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if key == "input_connections":
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raise NotImplementedError()
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if key == "inputs":
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inputs = []
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for input_name, input_def in value.items():
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step_input = model.WorkflowStepInput(workflow_step)
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step_input.name = input_name
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connections = []
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for conn_dict in input_def.get("connections", []):
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conn = model.WorkflowStepConnection()
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for conn_key, conn_value in conn_dict.items():
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if conn_key == "@output_step":
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target_step = workflow.steps[conn_value]
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conn_value = target_step
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conn_key = "output_step"
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if conn_key == "@input_subworkflow_step":
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conn_value = step["subworkflow"].step_by_index(conn_value)
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conn_key = "input_subworkflow_step"
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setattr(conn, conn_key, conn_value)
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connections.append(conn)
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step_input.connections = connections
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inputs.append(step_input)
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value = inputs
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if key == "workflow_outputs":
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value = [partial(_dict_to_workflow_output, workflow_step)(_) for _ in value]
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if key == 'collection_type':
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key = 'tool_inputs'
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value = {'collection_type': value}
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setattr(workflow_step, key, value)
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workflow.steps.append(workflow_step)
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return workflow
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def _dict_to_workflow_output(workflow_step, as_dict):
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output = model.WorkflowOutput(workflow_step)
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for key, value in as_dict.items():
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setattr(output, key, value)
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return output
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