def testVariantStats(self): """ test with non-datetime values """ s = QgsDateTimeStatisticalSummary() self.assertEqual(s.statistics(), QgsDateTimeStatisticalSummary.All) s.calculate( [ QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), "asdasd", QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), 34, QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1)), QDateTime(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54)), QDateTime(), QDateTime(QDate(2011, 1, 5), QTime(11, 10, 54)), ] ) self.assertEqual(s.count(), 7) self.assertEqual( set(s.distinctValues()), set( [ QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1)), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54)), QDateTime(QDate(2011, 1, 5), QTime(11, 10, 54)), QDateTime(), ] ), ) self.assertEqual(s.countMissing(), 2) self.assertEqual(s.min(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54))) self.assertEqual(s.max(), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1))) self.assertEqual(s.range(), QgsInterval(693871147))
def testIndividualStats(self): # tests calculation of statistics one at a time, to make sure statistic calculations are not # dependent on each other tests = [{'stat': QgsDateTimeStatisticalSummary.Count, 'expected': 9}, {'stat': QgsDateTimeStatisticalSummary.CountDistinct, 'expected': 6}, {'stat': QgsDateTimeStatisticalSummary.CountMissing, 'expected': 2}, {'stat': QgsDateTimeStatisticalSummary.Min, 'expected': QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54))}, {'stat': QgsDateTimeStatisticalSummary.Max, 'expected': QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1))}, {'stat': QgsDateTimeStatisticalSummary.Range, 'expected': QgsInterval(693871147)}, ] s = QgsDateTimeStatisticalSummary() for t in tests: # test constructor s2 = QgsDateTimeStatisticalSummary(t['stat']) self.assertEqual(s2.statistics(), t['stat']) s.setStatistics(t['stat']) self.assertEqual(s.statistics(), t['stat']) s.calculate([QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2011, 1, 5), QTime(15, 3, 1)), QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1)), QDateTime(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54)), QDateTime(), QDateTime(QDate(2011, 1, 5), QTime(11, 10, 54))]) self.assertEqual(s.statistic(t['stat']), t['expected']) # display name self.assertTrue(len(QgsDateTimeStatisticalSummary.displayName(t['stat'])) > 0)
def testDates(self): """ test with date values """ s = QgsDateTimeStatisticalSummary() self.assertEqual(s.statistics(), QgsDateTimeStatisticalSummary.All) s.calculate( [ QDate(2015, 3, 4), QDate(2015, 3, 4), QDate(2019, 12, 28), QDate(), QDate(1998, 1, 2), QDate(), QDate(2011, 1, 5), ] ) self.assertEqual(s.count(), 7) self.assertEqual( set(s.distinctValues()), set( [ QDateTime(QDate(2015, 3, 4), QTime()), QDateTime(QDate(2019, 12, 28), QTime()), QDateTime(QDate(1998, 1, 2), QTime()), QDateTime(), QDateTime(QDate(2011, 1, 5), QTime()), ] ), ) self.assertEqual(s.countMissing(), 2) self.assertEqual(s.min(), QDateTime(QDate(1998, 1, 2), QTime())) self.assertEqual(s.max(), QDateTime(QDate(2019, 12, 28), QTime())) self.assertEqual(s.range(), QgsInterval(693792000))
def calcDateTimeStats(self, values, sink, feedback): stat = QgsDateTimeStatisticalSummary() total = 50.0 / len(values) if values else 0 current = 0 for cat, v in values.items(): if feedback.isCanceled(): break feedback.setProgress(int(current * total) + 50) stat.calculate(v) f = QgsFeature() f.setAttributes(list(cat) + [stat.count(), stat.countDistinct(), stat.countMissing(), stat.count() - stat.countMissing(), stat.statistic(QgsDateTimeStatisticalSummary.Min), stat.statistic(QgsDateTimeStatisticalSummary.Max) ]) sink.addFeature(f, QgsFeatureSink.FastInsert) current += 1
def calcDateTimeStats(self, features, feedback, field, count): total = 100.0 / count if count else 1 stat = QgsDateTimeStatisticalSummary() for current, ft in enumerate(features): if feedback.isCanceled(): break stat.addValue(ft[field.name()]) feedback.setProgress(int(current * total)) stat.finalize() results = {self.COUNT: stat.count(), self.UNIQUE: stat.countDistinct(), self.EMPTY: stat.countMissing(), self.FILLED: stat.count() - stat.countMissing(), self.MIN: stat.statistic(QgsDateTimeStatisticalSummary.Min), self.MAX: stat.statistic(QgsDateTimeStatisticalSummary.Max)} data = [] data.append(self.tr('Count: {}').format(count)) data.append(self.tr('Unique values: {}').format(stat.countDistinct())) data.append(self.tr('NULL (missing) values: {}').format(stat.countMissing())) data.append( self.tr('Minimum value: {}').format(field.displayString(stat.statistic(QgsDateTimeStatisticalSummary.Min)))) data.append( self.tr('Maximum value: {}').format(field.displayString(stat.statistic(QgsDateTimeStatisticalSummary.Max)))) return data, results
def calcDateTimeStats(self, features, progress, field): count = len(features) total = 100.0 / float(count) stat = QgsDateTimeStatisticalSummary() for current, ft in enumerate(features): stat.addValue(ft[field.name()]) progress.setPercentage(int(current * total)) stat.finalize() self.setOutputValue(self.COUNT, stat.count()) self.setOutputValue(self.UNIQUE, stat.countDistinct()) self.setOutputValue(self.EMPTY, stat.countMissing()) self.setOutputValue(self.FILLED, stat.count() - stat.countMissing()) self.setOutputValue(self.MIN, stat.statistic(QgsDateTimeStatisticalSummary.Min)) self.setOutputValue(self.MAX, stat.statistic(QgsDateTimeStatisticalSummary.Max)) data = [] data.append(self.tr('Count: {}').format(count)) data.append(self.tr('Unique values: {}').format(stat.countDistinct())) data.append(self.tr('NULL (missing) values: {}').format(stat.countMissing())) data.append(self.tr('Minimum value: {}').format(field.displayString(stat.statistic(QgsDateTimeStatisticalSummary.Min)))) data.append(self.tr('Maximum value: {}').format(field.displayString(stat.statistic(QgsDateTimeStatisticalSummary.Max)))) return data
def testStats(self): s = QgsDateTimeStatisticalSummary() self.assertEqual(s.statistics(), QgsDateTimeStatisticalSummary.All) s.calculate([QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2011, 1, 5), QTime(15, 3, 1)), QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1)), QDateTime(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54)), QDateTime(), QDateTime(QDate(2011, 1, 5), QTime(11, 10, 54))]) self.assertEqual(s.count(), 9) self.assertEqual(s.countDistinct(), 6) self.assertEqual(set(s.distinctValues()), set([QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2011, 1, 5), QTime(15, 3, 1)), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1)), QDateTime(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54)), QDateTime(QDate(2011, 1, 5), QTime(11, 10, 54))])) self.assertEqual(s.countMissing(), 2) self.assertEqual(s.min(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54))) self.assertEqual(s.max(), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1))) self.assertEqual(s.range(), QgsInterval(693871147))
def testStats(self): # we test twice, once with values added as a list and once using values # added one-at-a-time dates = [QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2011, 1, 5), QTime(15, 3, 1)), QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1)), QDateTime(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54)), QDateTime(), QDateTime(QDate(2011, 1, 5), QTime(11, 10, 54))] s = QgsDateTimeStatisticalSummary() self.assertEqual(s.statistics(), QgsDateTimeStatisticalSummary.All) s.calculate(dates) s2 = QgsDateTimeStatisticalSummary() for d in dates: s2.addValue(d) s2.finalize() self.assertEqual(s.count(), 9) self.assertEqual(s2.count(), 9) self.assertEqual(s.countDistinct(), 6) self.assertEqual(s2.countDistinct(), 6) self.assertEqual(set(s.distinctValues()), set([QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2011, 1, 5), QTime(15, 3, 1)), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1)), QDateTime(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54)), QDateTime(QDate(2011, 1, 5), QTime(11, 10, 54))])) self.assertEqual(s2.distinctValues(), s.distinctValues()) self.assertEqual(s.countMissing(), 2) self.assertEqual(s2.countMissing(), 2) self.assertEqual(s.min(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54))) self.assertEqual(s2.min(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54))) self.assertEqual(s.max(), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1))) self.assertEqual(s2.max(), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1))) self.assertEqual(s.range(), QgsInterval(693871147)) self.assertEqual(s2.range(), QgsInterval(693871147))
def testMissing(self): s = QgsDateTimeStatisticalSummary() s.calculate([NULL, 'not a date']) self.assertEqual(s.countMissing(), 2)
def testTimes(self): """ test with time values """ s = QgsDateTimeStatisticalSummary() self.assertEqual(s.statistics(), QgsDateTimeStatisticalSummary.All) s.calculate([QTime(11, 3, 4), QTime(15, 3, 4), QTime(19, 12, 28), QTime(), QTime(8, 1, 2), QTime(), QTime(19, 12, 28)]) self.assertEqual(s.count(), 7) self.assertEqual(s.countDistinct(), 5) self.assertEqual(s.countMissing(), 2) self.assertEqual(s.min().time(), QTime(8, 1, 2)) self.assertEqual(s.max().time(), QTime(19, 12, 28)) self.assertEqual(s.statistic(QgsDateTimeStatisticalSummary.Min), QTime(8, 1, 2)) self.assertEqual(s.statistic(QgsDateTimeStatisticalSummary.Max), QTime(19, 12, 28)) self.assertEqual(s.range(), QgsInterval(40286))
def testDates(self): """ test with date values """ s = QgsDateTimeStatisticalSummary() self.assertEqual(s.statistics(), QgsDateTimeStatisticalSummary.All) s.calculate([QDate(2015, 3, 4), QDate(2015, 3, 4), QDate(2019, 12, 28), QDate(), QDate(1998, 1, 2), QDate(), QDate(2011, 1, 5)]) self.assertEqual(s.count(), 7) self.assertEqual(set(s.distinctValues()), set([ QDateTime(QDate(2015, 3, 4), QTime()), QDateTime(QDate(2019, 12, 28), QTime()), QDateTime(QDate(1998, 1, 2), QTime()), QDateTime(), QDateTime(QDate(2011, 1, 5), QTime())])) self.assertEqual(s.countMissing(), 2) self.assertEqual(s.min(), QDateTime(QDate(1998, 1, 2), QTime())) self.assertEqual(s.max(), QDateTime(QDate(2019, 12, 28), QTime())) self.assertEqual(s.range(), QgsInterval(693792000))
def testVariantStats(self): """ test with non-datetime values """ s = QgsDateTimeStatisticalSummary() self.assertEqual(s.statistics(), QgsDateTimeStatisticalSummary.All) s.calculate([QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), 'asdasd', QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), 34, QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1)), QDateTime(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54)), QDateTime(), QDateTime(QDate(2011, 1, 5), QTime(11, 10, 54))]) self.assertEqual(s.count(), 9) self.assertEqual(set(s.distinctValues()), set([QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1)), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54)), QDateTime(QDate(2011, 1, 5), QTime(11, 10, 54)), QDateTime()])) self.assertEqual(s.countMissing(), 4) self.assertEqual(s.min(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54))) self.assertEqual(s.max(), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1))) self.assertEqual(s.range(), QgsInterval(693871147))
def calcDateTimeStats(self, features, feedback, field, count): total = 100.0 / count if count else 1 stat = QgsDateTimeStatisticalSummary() for current, ft in enumerate(features): if feedback.isCanceled(): break stat.addValue(ft[field.name()]) feedback.setProgress(int(current * total)) stat.finalize() results = { self.COUNT: stat.count(), self.UNIQUE: stat.countDistinct(), self.EMPTY: stat.countMissing(), self.FILLED: stat.count() - stat.countMissing(), self.MIN: stat.statistic(QgsDateTimeStatisticalSummary.Min), self.MAX: stat.statistic(QgsDateTimeStatisticalSummary.Max) } data = [] data.append(self.tr('Count: {}').format(count)) data.append(self.tr('Unique values: {}').format(stat.countDistinct())) data.append( self.tr('NULL (missing) values: {}').format(stat.countMissing())) data.append( self.tr('Minimum value: {}').format( field.displayString( stat.statistic(QgsDateTimeStatisticalSummary.Min)))) data.append( self.tr('Maximum value: {}').format( field.displayString( stat.statistic(QgsDateTimeStatisticalSummary.Max)))) return data, results
def calcDateTimeStats(self, features, feedback, field, count): total = 100.0 / float(count) stat = QgsDateTimeStatisticalSummary() for current, ft in enumerate(features): stat.addValue(ft[field.name()]) feedback.setProgress(int(current * total)) stat.finalize() self.setOutputValue(self.COUNT, stat.count()) self.setOutputValue(self.UNIQUE, stat.countDistinct()) self.setOutputValue(self.EMPTY, stat.countMissing()) self.setOutputValue(self.FILLED, stat.count() - stat.countMissing()) self.setOutputValue(self.MIN, stat.statistic(QgsDateTimeStatisticalSummary.Min)) self.setOutputValue(self.MAX, stat.statistic(QgsDateTimeStatisticalSummary.Max)) data = [] data.append(self.tr('Count: {}').format(count)) data.append(self.tr('Unique values: {}').format(stat.countDistinct())) data.append( self.tr('NULL (missing) values: {}').format(stat.countMissing())) data.append( self.tr('Minimum value: {}').format( field.displayString( stat.statistic(QgsDateTimeStatisticalSummary.Min)))) data.append( self.tr('Maximum value: {}').format( field.displayString( stat.statistic(QgsDateTimeStatisticalSummary.Max)))) return data
def testIndividualStats(self): # tests calculation of statistics one at a time, to make sure statistic calculations are not # dependent on each other tests = [{'stat': QgsDateTimeStatisticalSummary.Count, 'expected': 9}, {'stat': QgsDateTimeStatisticalSummary.CountDistinct, 'expected': 6}, {'stat': QgsDateTimeStatisticalSummary.CountMissing, 'expected': 2}, {'stat': QgsDateTimeStatisticalSummary.Min, 'expected': QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54))}, {'stat': QgsDateTimeStatisticalSummary.Max, 'expected': QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1))}, {'stat': QgsDateTimeStatisticalSummary.Range, 'expected': QgsInterval(693871147)}, ] # we test twice, once with values added as a list and once using values # added one-at-a-time s = QgsDateTimeStatisticalSummary() s3 = QgsDateTimeStatisticalSummary() for t in tests: # test constructor s2 = QgsDateTimeStatisticalSummary(t['stat']) self.assertEqual(s2.statistics(), t['stat']) s.setStatistics(t['stat']) self.assertEqual(s.statistics(), t['stat']) s3.setStatistics(t['stat']) dates = [QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2011, 1, 5), QTime(15, 3, 1)), QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2015, 3, 4), QTime(11, 10, 54)), QDateTime(QDate(2019, 12, 28), QTime(23, 10, 1)), QDateTime(), QDateTime(QDate(1998, 1, 2), QTime(1, 10, 54)), QDateTime(), QDateTime(QDate(2011, 1, 5), QTime(11, 10, 54))] s.calculate(dates) s3.reset() for d in dates: s3.addValue(d) s3.finalize() self.assertEqual(s.statistic(t['stat']), t['expected']) self.assertEqual(s3.statistic(t['stat']), t['expected']) # display name self.assertTrue(len(QgsDateTimeStatisticalSummary.displayName(t['stat'])) > 0)
def processAlgorithm(self, parameters, context, feedback): source = self.parameterAsSource(parameters, self.INPUT, context) join_source = self.parameterAsSource(parameters, self.JOIN, context) join_fields = self.parameterAsFields(parameters, self.JOIN_FIELDS, context) discard_nomatch = self.parameterAsBool(parameters, self.DISCARD_NONMATCHING, context) summaries = [ self.statistics[i][0] for i in sorted( self.parameterAsEnums(parameters, self.SUMMARIES, context)) ] if not summaries: # none selected, so use all summaries = [s[0] for s in self.statistics] source_fields = source.fields() fields_to_join = QgsFields() join_field_indexes = [] if not join_fields: # no fields selected, use all join_fields = [ join_source.fields().at(i).name() for i in range(len(join_source.fields())) ] def addFieldKeepType(original, stat): """ Adds a field to the output, keeping the same data type as the original """ field = QgsField(original) field.setName(field.name() + '_' + stat) fields_to_join.append(field) def addField(original, stat, type): """ Adds a field to the output, with a specified type """ field = QgsField(original) field.setName(field.name() + '_' + stat) field.setType(type) if type == QVariant.Double: field.setLength(20) field.setPrecision(6) fields_to_join.append(field) numeric_fields = (('count', QVariant.Int, 'count'), ('unique', QVariant.Int, 'variety'), ('min', QVariant.Double, 'min'), ('max', QVariant.Double, 'max'), ('range', QVariant.Double, 'range'), ('sum', QVariant.Double, 'sum'), ('mean', QVariant.Double, 'mean'), ('median', QVariant.Double, 'median'), ('stddev', QVariant.Double, 'stDev'), ('minority', QVariant.Double, 'minority'), ('majority', QVariant.Double, 'majority'), ('q1', QVariant.Double, 'firstQuartile'), ('q3', QVariant.Double, 'thirdQuartile'), ('iqr', QVariant.Double, 'interQuartileRange')) datetime_fields = (('count', QVariant.Int, 'count'), ('unique', QVariant.Int, 'countDistinct'), ('empty', QVariant.Int, 'countMissing'), ('filled', QVariant.Int), ('min', None), ('max', None)) string_fields = (('count', QVariant.Int, 'count'), ('unique', QVariant.Int, 'countDistinct'), ('empty', QVariant.Int, 'countMissing'), ('filled', QVariant.Int), ('min', None, 'min'), ('max', None, 'max'), ('min_length', QVariant.Int, 'minLength'), ('max_length', QVariant.Int, 'maxLength'), ('mean_length', QVariant.Double, 'meanLength')) field_types = [] for f in join_fields: idx = join_source.fields().lookupField(f) if idx >= 0: join_field_indexes.append(idx) join_field = join_source.fields().at(idx) if join_field.isNumeric(): field_types.append('numeric') field_list = numeric_fields elif join_field.type() in (QVariant.Date, QVariant.Time, QVariant.DateTime): field_types.append('datetime') field_list = datetime_fields else: field_types.append('string') field_list = string_fields for f in field_list: if f[0] in summaries: if f[1] is not None: addField(join_field, f[0], f[1]) else: addFieldKeepType(join_field, f[0]) out_fields = QgsProcessingUtils.combineFields(source_fields, fields_to_join) (sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context, out_fields, source.wkbType(), source.sourceCrs()) # do the join predicates = [ self.predicates[i][0] for i in self.parameterAsEnums(parameters, self.PREDICATE, context) ] features = source.getFeatures() total = 100.0 / source.featureCount() if source.featureCount() else 0 # bounding box transform bbox_transform = QgsCoordinateTransform(source.sourceCrs(), join_source.sourceCrs()) for current, f in enumerate(features): if feedback.isCanceled(): break if not f.hasGeometry(): if not discard_nomatch: sink.addFeature(f, QgsFeatureSink.FastInsert) continue bbox = bbox_transform.transformBoundingBox( f.geometry().boundingBox()) engine = None values = [] request = QgsFeatureRequest().setFilterRect( bbox).setSubsetOfAttributes( join_field_indexes).setDestinationCrs(source.sourceCrs()) for test_feat in join_source.getFeatures(request): if feedback.isCanceled(): break join_attributes = [] for a in join_field_indexes: join_attributes.append(test_feat.attributes()[a]) if engine is None: engine = QgsGeometry.createGeometryEngine( f.geometry().constGet()) engine.prepareGeometry() for predicate in predicates: if getattr(engine, predicate)(test_feat.geometry().constGet()): values.append(join_attributes) break feedback.setProgress(int(current * total)) if len(values) == 0: if discard_nomatch: continue else: sink.addFeature(f, QgsFeatureSink.FastInsert) else: attrs = f.attributes() for i in range(len(join_field_indexes)): attribute_values = [v[i] for v in values] field_type = field_types[i] if field_type == 'numeric': stat = QgsStatisticalSummary() for v in attribute_values: stat.addVariant(v) stat.finalize() for s in numeric_fields: if s[0] in summaries: attrs.append(getattr(stat, s[2])()) elif field_type == 'datetime': stat = QgsDateTimeStatisticalSummary() stat.calculate(attribute_values) for s in datetime_fields: if s[0] in summaries: if s[0] == 'filled': attrs.append(stat.count() - stat.countMissing()) elif s[0] == 'min': attrs.append( stat.statistic( QgsDateTimeStatisticalSummary.Min)) elif s[0] == 'max': attrs.append( stat.statistic( QgsDateTimeStatisticalSummary.Max)) else: attrs.append(getattr(stat, s[2])()) else: stat = QgsStringStatisticalSummary() for v in attribute_values: if v == NULL: stat.addString('') else: stat.addString(str(v)) stat.finalize() for s in string_fields: if s[0] in summaries: if s[0] == 'filled': attrs.append(stat.count() - stat.countMissing()) else: attrs.append(getattr(stat, s[2])()) f.setAttributes(attrs) sink.addFeature(f, QgsFeatureSink.FastInsert) return {self.OUTPUT: dest_id}