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Since it's safe to evaluate parameters in background threads now, it's usually going to be ok to evaluate everything in the processAlgorithm step. This keeps the algorithm code as simple as possible, and will make porting faster. Note that the prepare/postProcess virtual methods still exist and can be used when an algorithm MUST do setup/cleanup work in the main thread.
74 lines
2.7 KiB
Python
74 lines
2.7 KiB
Python
# -*- coding: utf-8 -*-
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"""
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***************************************************************************
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SaveSelectedFeatures.py
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---------------------
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Date : August 2012
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Copyright : (C) 2012 by Victor Olaya
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Email : volayaf at gmail dot com
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***************************************************************************
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* *
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* This program is free software; you can redistribute it and/or modify *
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* it under the terms of the GNU General Public License as published by *
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* the Free Software Foundation; either version 2 of the License, or *
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* (at your option) any later version. *
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* *
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***************************************************************************
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"""
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__author__ = 'Victor Olaya'
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__date__ = 'August 2012'
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__copyright__ = '(C) 2012, Victor Olaya'
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# This will get replaced with a git SHA1 when you do a git archive
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__revision__ = '$Format:%H$'
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from qgis.core import (QgsFeatureSink,
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QgsProcessingParameterVectorLayer,
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QgsProcessingParameterFeatureSink,
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QgsProcessingOutputVectorLayer)
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from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
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class SaveSelectedFeatures(QgisAlgorithm):
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OUTPUT = 'OUTPUT'
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INPUT = 'INPUT'
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def group(self):
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return self.tr('Vector general tools')
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def __init__(self):
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super().__init__()
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self.addParameter(QgsProcessingParameterVectorLayer(self.INPUT, self.tr('Input layer')))
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self.addParameter(QgsProcessingParameterFeatureSink(self.OUTPUT, self.tr('Selection')))
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self.addOutput(QgsProcessingOutputVectorLayer(self.OUTPUT, self.tr("Selection")))
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def name(self):
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return 'saveselectedfeatures'
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def displayName(self):
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return self.tr('Save selected features')
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def processAlgorithm(self, parameters, context, feedback):
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vectorLayer = self.parameterAsVectorLayer(parameters, self.INPUT, context)
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(sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context,
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vectorLayer.fields(), vectorLayer.wkbType(), vectorLayer.sourceCrs())
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features = vectorLayer.getSelectedFeatures()
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count = int(vectorLayer.selectedFeatureCount())
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total = 100.0 / count if count else 1
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for current, feat in enumerate(features):
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if feedback.isCanceled():
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break
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sink.addFeature(feat, QgsFeatureSink.FastInsert)
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feedback.setProgress(int(current * total))
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return {self.OUTPUT: dest_id}
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