def testRun(self):
registry = self.makeRegistry()
# Check insertion and retrieval with two different collections
for collection in ["one", "two"]:
run = registry.makeRun(collection)
self.assertIsInstance(run, Run)
self.assertEqual(run.collection, collection)
# Test retrieval by collection
runCpy1 = registry.getRun(collection=run.collection)
self.assertEqual(runCpy1, run)
# Test retrieval by (run/execution) id
runCpy2 = registry.getRun(id=run.id)
self.assertEqual(runCpy2, run)
# Non-existing collection should return None
self.assertIsNone(registry.getRun(collection="bogus"))
# Non-existing id should return None
self.assertIsNone(registry.getRun(id=100))
# Inserting with a preexisting collection should fail
with self.assertRaises(ConflictingDefinitionError):
registry.makeRun("one")
# Insert a new Run and check that ensureRun silently ignores it
collection = "dummy"
run = registry.makeRun(collection)
registry.ensureRun(run)
# Calling ensureRun with a different Run with the same id should fail
run2 = Run(collection="hello")
run2._id = run.id
with self.assertRaises(ConflictingDefinitionError):
registry.ensureRun(run2)
run2._id = None
# Now it should work
registry.ensureRun(run2)
self.assertEqual(run2, registry.getRun(id=run2.id))
def makeDatasetRef(self,
datasetTypeName,
dimensions,
storageClass,
dataId,
id=None,
run=None):
"""Make a DatasetType and wrap it in a DatasetRef for a test"""
datasetType = DatasetType(datasetTypeName, dimensions, storageClass)
if id is None:
self.id += 1
id = self.id
if run is None:
run = Run(id=1, collection="dummy")
return DatasetRef(datasetType, dataId, id=id, run=run)
def __init__(self, config=None, *, butler, **kwds):
super().__init__(config, **kwds)
self.butler = butler
self.datasetType = self.getDatasetType()
self.dimensions = butler.registry.dimensions.extract(["Instrument", "Detector", "PhysicalFilter",
"Visit", "Exposure"])
# Dictionary of {Dimension: set(DataId)} indicating Dimension entries
# we know are in the Registry.
self.dimensionEntriesDone = {k: set() for k in self.dimensions}
# Cache of Instrument instances retrieved from Registry; needed to look
# up formatters.
self.instrumentCache = {}
# (Possibly) create a Run object for the "stash": where we put datasets
# that lose conflicts. Note that this doesn't actually add this Run
# to the Registry; we only do that on first use.
self.stashRun = Run(self.config.stash) if self.config.stash is not None else None
def _makeQuanta(self, config):
"""Create set of Quanta
"""
universe = DimensionUniverse()
run = Run(collection=1, environment=None, pipeline=None)
connections = config.connections.ConnectionsClass(config=config)
dstype0 = connections.input.makeDatasetType(universe)
dstype1 = connections.output.makeDatasetType(universe)
quanta = []
for visit in range(100):
quantum = Quantum(run=run)
quantum.addPredictedInput(
self._makeDSRefVisit(dstype0, visit, universe))
quantum.addOutput(self._makeDSRefVisit(dstype1, visit, universe))
quanta.append(quantum)
return quanta
def _makeQuanta(self, config):
"""Create set of Quanta
"""
universe = DimensionUniverse.fromConfig()
run = Run(collection=1, environment=None, pipeline=None)
descriptor = pipeBase.DatasetTypeDescriptor.fromConfig(config.input)
dstype0 = descriptor.makeDatasetType(universe)
descriptor = pipeBase.DatasetTypeDescriptor.fromConfig(config.output)
dstype1 = descriptor.makeDatasetType(universe)
quanta = []
for visit in range(100):
quantum = Quantum(run=run, task=None)
quantum.addPredictedInput(self._makeDSRefVisit(dstype0, visit))
quantum.addOutput(self._makeDSRefVisit(dstype1, visit))
quanta.append(quantum)
return quanta