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156 lines
5.3 KiB
Python
156 lines
5.3 KiB
Python
import unittest
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import galaxy.model.mapping
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from galaxy import model
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from galaxy.workflow import extract
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UNDEFINED_JOB = object()
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class TestWorkflowExtractSummary( unittest.TestCase ):
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def setUp( self ):
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self.history = MockHistory()
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self.trans = MockTrans( self.history )
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def test_empty_history( self ):
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job_dict, warnings = extract.summarize( trans=self.trans )
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assert not warnings
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assert not job_dict
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def test_summarize_returns_name_and_dataset_list( self ):
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# Create two jobs and three datasets, test they are groupped
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# by job correctly with correct output names.
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hda1 = MockHda()
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self.history.active_datasets.append( hda1 )
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hda2 = MockHda( job=hda1.job, output_name="out2" )
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self.history.active_datasets.append( hda2 )
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hda3 = MockHda( output_name="out3" )
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self.history.active_datasets.append( hda3 )
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job_dict, warnings = extract.summarize( trans=self.trans )
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assert len( job_dict ) == 2
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assert not warnings
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self.assertEquals( job_dict[ hda1.job ], [ ( 'out1', hda1 ), ( 'out2', hda2 ) ] )
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self.assertEquals( job_dict[ hda3.job ], [ ( 'out3', hda3 ) ] )
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def test_finds_original_job_if_copied( self ):
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hda = MockHda()
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derived_hda_1 = MockHda()
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derived_hda_1.copied_from_history_dataset_association = hda
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derived_hda_2 = MockHda()
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derived_hda_2.copied_from_history_dataset_association = derived_hda_1
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self.history.active_datasets.append( derived_hda_2 )
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job_dict, warnings = extract.summarize( trans=self.trans )
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assert not warnings
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assert len( job_dict ) == 1
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self.assertEquals( job_dict[ hda.job ], [ ('out1', derived_hda_2 ) ] )
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def test_fake_job_hda( self ):
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""" Fakes job if creating_job_associations is empty.
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"""
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hda = MockHda( job=UNDEFINED_JOB )
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self.history.active_datasets.append( hda )
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job_dict, warnings = extract.summarize( trans=self.trans )
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assert not warnings
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assert len( job_dict ) == 1
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fake_job = job_dict.keys()[ 0 ]
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assert fake_job.id.startswith( "fake_" )
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datasets = job_dict.values()[ 0 ]
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assert datasets == [ ( None, hda ) ]
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def test_fake_job_hdca( self ):
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hdca = MockHdca( )
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self.history.active_datasets.append( hdca )
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job_dict, warnings = extract.summarize( trans=self.trans )
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assert not warnings
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assert len( job_dict ) == 1
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fake_job = job_dict.keys()[ 0 ]
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assert fake_job.id.startswith( "fake_" )
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assert fake_job.is_fake
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content_instances = job_dict.values()[ 0 ]
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assert content_instances == [ ( None, hdca ) ]
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def test_implicit_map_job_hdca( self ):
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creating_job = model.Job()
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hdca = MockHdca( implicit_output_name="out1", job=creating_job )
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self.history.active_datasets.append( hdca )
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job_dict, warnings = extract.summarize( trans=self.trans )
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assert not warnings
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assert len( job_dict ) == 1
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job = job_dict.keys()[ 0 ]
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assert job is creating_job
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def test_warns_and_skips_datasets_if_not_finished( self ):
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hda = MockHda( state='queued' )
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self.history.active_datasets.append( hda )
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job_dict, warnings = extract.summarize( trans=self.trans )
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assert warnings
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assert len( job_dict ) == 0
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class MockHistory( object ):
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def __init__( self ):
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self.active_datasets = []
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@property
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def active_contents( self ):
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return self.active_datasets
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class MockTrans( object ):
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def __init__( self, history ):
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self.history = history
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def get_history( self ):
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return self.history
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class MockHda( object ):
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def __init__( self, state='ok', output_name='out1', job=None ):
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self.id = 123
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self.state = state
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self.copied_from_history_dataset_association = None
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self.history_content_type = "dataset"
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if job is not UNDEFINED_JOB:
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if not job:
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job = model.Job()
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self.job = job
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assoc = model.JobToOutputDatasetAssociation( output_name, self )
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assoc.job = job
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self.creating_job_associations = [ assoc ]
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else:
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self.creating_job_associations = []
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class MockHdca( object ):
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def __init__( self, implicit_output_name=None, job=None, hid=1 ):
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self.id = 124
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self.copied_from_history_dataset_collection_association = None
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self.history_content_type = "dataset_collection"
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self.implicit_output_name = implicit_output_name
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self.hid = 1
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self.collection = model.DatasetCollection()
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self.creating_job_associations = []
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element = model.DatasetCollectionElement(
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collection=self.collection,
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element=model.HistoryDatasetAssociation(),
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element_index=0,
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element_identifier="moocow",
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)
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element.dataset_instance.dataset = model.Dataset()
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element.dataset_instance.dataset.state = "ok"
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creating = model.JobToOutputDatasetAssociation(
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implicit_output_name,
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element.dataset_instance,
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)
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creating.job = job
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element.dataset_instance.creating_job_associations = [
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creating,
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]
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self.collection.elements = [element]
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