def processAlgorithm(self, parameters, context, feedback):
"""
Here is where the processing itself takes place.
"""
layerHandler = LayerHandler()
inputLyr = self.parameterAsVectorLayer(parameters, self.INPUT, context)
if inputLyr is None:
raise QgsProcessingException(
self.invalidSourceError(parameters, self.INPUT))
onlySelected = self.parameterAsBool(parameters, self.SELECTED, context)
attributeBlackList = self.parameterAsFields(parameters,
self.ATTRIBUTE_BLACK_LIST,
context)
ignoreVirtual = self.parameterAsBool(parameters,
self.IGNORE_VIRTUAL_FIELDS,
context)
ignorePK = self.parameterAsBool(parameters, self.IGNORE_PK_FIELDS,
context)
# Compute the number of steps to display within the progress bar and
# get features from source
multiStepFeedback = QgsProcessingMultiStepFeedback(2, feedback)
multiStepFeedback.setCurrentStep(0)
duplicatedGeomDict = layerHandler.getDuplicatedFeaturesDict(
inputLyr,
onlySelected=onlySelected,
attributeBlackList=attributeBlackList,
excludePrimaryKeys=ignorePK,
ignoreVirtualFields=ignoreVirtual,
feedback=multiStepFeedback)
multiStepFeedback.setCurrentStep(1)
self.deleteDuplicatedFeaturesFlags(inputLyr, duplicatedGeomDict,
multiStepFeedback)
return {self.OUTPUT: inputLyr}
def processAlgorithm(self, parameters, context, feedback):
"""
Here is where the processing itself takes place.
"""
inputLyr = self.parameterAsVectorLayer(parameters, self.INPUT, context)
if inputLyr is None:
raise QgsProcessingException(
self.invalidSourceError(parameters, self.INPUT))
onlySelected = self.parameterAsBool(parameters, self.SELECTED, context)
self.prepareFlagSink(parameters, inputLyr, inputLyr.wkbType(), context)
# Compute the number of steps to display within the progress bar and
# get features from source
layerHandler = LayerHandler()
multiStepFeedback = QgsProcessingMultiStepFeedback(2, feedback)
multiStepFeedback.setCurrentStep(0)
geomDict = layerHandler.getDuplicatedFeaturesDict(
inputLyr, onlySelected=onlySelected, feedback=multiStepFeedback)
multiStepFeedback.setCurrentStep(1)
self.raiseDuplicatedFeaturesFlags(
inputLyr, geomDict, multiStepFeedback)
return {self.FLAGS: self.flag_id}
