def getVectorWriter(self, fields, geomType, crs, context):
"""Returns a suitable writer to which features can be added as
a result of the algorithm. Use this to transparently handle
output values instead of creating your own method.
Executing this method might modify the object, adding additional
information to it, so the writer can be later accessed and
processed within QGIS. It should be called just once, since a
new call might result in previous data being replaced, thus
rendering a previously obtained writer useless.
@param fields a list of QgsField
@param geomType a suitable geometry type, as it would be passed
to a QgsVectorFileWriter constructor
@param crs the crs of the layer to create
@return writer instance of the vector writer class
:param context:
"""
if self.encoding is None:
settings = QgsSettings()
self.encoding = settings.value('/Processing/encoding', 'System', str)
w, w_dest = QgsProcessingUtils.createFeatureSink(self.value, context, fields, geomType, crs, {'fileEncoding': self.encoding})
self.value = w_dest
return w
def executeIterating(alg, parameters, paramToIter, context, feedback):
# Generate all single-feature layers
parameter_definition = alg.parameterDefinition(paramToIter)
if not parameter_definition:
return False
iter_source = QgsProcessingParameters.parameterAsSource(
parameter_definition, parameters, context)
sink_list = []
if iter_source.featureCount() == 0:
return False
total = 100.0 / iter_source.featureCount()
for current, feat in enumerate(iter_source.getFeatures()):
if feedback.isCanceled():
return False
sink, sink_id = QgsProcessingUtils.createFeatureSink(
'memory:', context, iter_source.fields(), iter_source.wkbType(),
iter_source.sourceCrs())
sink_list.append(sink_id)
sink.addFeature(feat, QgsFeatureSink.FastInsert)
del sink
feedback.setProgress(int(current * total))
# store output values to use them later as basenames for all outputs
outputs = {}
for out in alg.destinationParameterDefinitions():
outputs[out.name()] = parameters[out.name()]
# now run all the algorithms
for i, f in enumerate(sink_list):
if feedback.isCanceled():
return False
parameters[paramToIter] = f
for out in alg.destinationParameterDefinitions():
o = outputs[out.name()]
parameters[
out.name()] = QgsProcessingUtils.generateIteratingDestination(
o, i, context)
feedback.setProgressText(
QCoreApplication.translate('AlgorithmExecutor',
'Executing iteration {0}/{1}…').format(
i, len(sink_list)))
feedback.setProgress(i * 100 / len(sink_list))
ret, results = execute(alg, parameters, context, feedback)
if not ret:
return False
handleAlgorithmResults(alg, context, feedback, False)
return True
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
fieldName = self.parameterAsString(parameters, self.FIELD, context)
directory = self.parameterAsString(parameters, self.OUTPUT, context)
output_format = context.preferredVectorFormat()
if not output_format in QgsVectorFileWriter.supportedFormatExtensions():
# fallback to gpkg if preferred format is not available
output_format = 'gpkg'
mkdir(directory)
fieldIndex = source.fields().lookupField(fieldName)
uniqueValues = source.uniqueValues(fieldIndex)
baseName = os.path.join(directory, '{0}'.format(fieldName))
fields = source.fields()
crs = source.sourceCrs()
geomType = source.wkbType()
total = 100.0 / len(uniqueValues) if uniqueValues else 1
output_layers = []
for current, i in enumerate(uniqueValues):
if feedback.isCanceled():
break
fName = '{0}_{1}.{2}'.format(baseName, str(i).strip(), output_format)
feedback.pushInfo(self.tr('Creating layer: {}').format(fName))
sink, dest = QgsProcessingUtils.createFeatureSink(fName, context, fields, geomType, crs)
filter = '{} = {}'.format(QgsExpression.quotedColumnRef(fieldName), QgsExpression.quotedValue(i))
req = QgsFeatureRequest().setFilterExpression(filter)
count = 0
for f in source.getFeatures(req):
if feedback.isCanceled():
break
sink.addFeature(f, QgsFeatureSink.FastInsert)
count += 1
feedback.pushInfo(self.tr('Added {} features to layer').format(count))
output_layers.append(fName)
del sink
feedback.setProgress(int(current * total))
return {self.OUTPUT: directory, self.OUTPUT_LAYERS: output_layers}
def executeIterating(alg, parameters, paramToIter, context, feedback):
# Generate all single-feature layers
parameter_definition = alg.parameterDefinition(paramToIter)
if not parameter_definition:
return False
iter_source = QgsProcessingParameters.parameterAsSource(parameter_definition, parameters, context)
sink_list = []
if iter_source.featureCount() == 0:
return False
total = 100.0 / iter_source.featureCount()
for current, feat in enumerate(iter_source.getFeatures()):
if feedback.isCanceled():
return False
sink, sink_id = QgsProcessingUtils.createFeatureSink('memory:', context, iter_source.fields(), iter_source.wkbType(), iter_source.sourceCrs())
sink_list.append(sink_id)
sink.addFeature(feat, QgsFeatureSink.FastInsert)
del sink
feedback.setProgress(int(current * total))
# store output values to use them later as basenames for all outputs
outputs = {}
for out in alg.destinationParameterDefinitions():
if out.name() in parameters:
outputs[out.name()] = parameters[out.name()]
# now run all the algorithms
for i, f in enumerate(sink_list):
if feedback.isCanceled():
return False
parameters[paramToIter] = f
for out in alg.destinationParameterDefinitions():
if out.name() not in outputs:
continue
o = outputs[out.name()]
parameters[out.name()] = QgsProcessingUtils.generateIteratingDestination(o, i, context)
feedback.setProgressText(QCoreApplication.translate('AlgorithmExecutor', 'Executing iteration {0}/{1}…').format(i + 1, len(sink_list)))
feedback.setProgress(i * 100 / len(sink_list))
ret, results = execute(alg, parameters, context, feedback)
if not ret:
return False
handleAlgorithmResults(alg, context, feedback, False)
return True
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(self.invalidSourceError(parameters, self.INPUT))
fieldName = self.parameterAsString(parameters, self.FIELD, context)
directory = self.parameterAsString(parameters, self.OUTPUT, context)
mkdir(directory)
fieldIndex = source.fields().lookupField(fieldName)
uniqueValues = source.uniqueValues(fieldIndex)
baseName = os.path.join(directory, '{0}'.format(fieldName))
fields = source.fields()
crs = source.sourceCrs()
geomType = source.wkbType()
total = 100.0 / len(uniqueValues) if uniqueValues else 1
output_layers = []
for current, i in enumerate(uniqueValues):
if feedback.isCanceled():
break
fName = '{0}_{1}.gpkg'.format(baseName, str(i).strip())
feedback.pushInfo(self.tr('Creating layer: {}').format(fName))
sink, dest = QgsProcessingUtils.createFeatureSink(fName, context, fields, geomType, crs)
filter = '{} = {}'.format(QgsExpression.quotedColumnRef(fieldName), QgsExpression.quotedValue(i))
req = QgsFeatureRequest().setFilterExpression(filter)
count = 0
for f in source.getFeatures(req):
if feedback.isCanceled():
break
sink.addFeature(f, QgsFeatureSink.FastInsert)
count += 1
feedback.pushInfo(self.tr('Added {} features to layer').format(count))
output_layers.append(fName)
del sink
feedback.setProgress(int(current * total))
return {self.OUTPUT: directory, self.OUTPUT_LAYERS: output_layers}
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsSource(parameters, self.INPUT, context)
fieldName = self.parameterAsString(parameters, self.FIELD, context)
directory = self.parameterAsString(parameters, self.OUTPUT, context)
mkdir(directory)
fieldIndex = source.fields().lookupField(fieldName)
uniqueValues = source.uniqueValues(fieldIndex)
baseName = os.path.join(directory, '{0}'.format(fieldName))
fields = source.fields()
crs = source.sourceCrs()
geomType = source.wkbType()
total = 100.0 / len(uniqueValues) if uniqueValues else 1
output_layers = []
for current, i in enumerate(uniqueValues):
if feedback.isCanceled():
break
fName = u'{0}_{1}.shp'.format(baseName, str(i).strip())
feedback.pushInfo(self.tr('Creating layer: {}').format(fName))
sink, dest = QgsProcessingUtils.createFeatureSink(
fName, context, fields, geomType, crs)
filter = '{} = {}'.format(QgsExpression.quotedColumnRef(fieldName),
QgsExpression.quotedValue(i))
req = QgsFeatureRequest().setFilterExpression(filter)
count = 0
for f in source.getFeatures(req):
if feedback.isCanceled():
break
sink.addFeature(f, QgsFeatureSink.FastInsert)
count += 1
feedback.pushInfo(
self.tr('Added {} features to layer').format(count))
output_layers.append(fName)
del sink
feedback.setProgress(int(current * total))
return {self.OUTPUT: directory, self.OUTPUT_LAYERS: output_layers}
def processAlgorithm(self, parameters, context, feedback):
expr_context = self.createExpressionContext(parameters, context)
self.group_by_expr.prepare(expr_context)
# Group features in memory layers
source = self.source
count = self.source.featureCount()
if count:
progress_step = 50.0 / count
current = 0
groups = {}
keys = [] # We need deterministic order for the tests
feature = QgsFeature()
for feature in self.source.getFeatures():
expr_context.setFeature(feature)
group_by_value = self.evaluateExpression(self.group_by_expr,
expr_context)
# Get an hashable key for the dict
key = group_by_value
if isinstance(key, list):
key = tuple(key)
group = groups.get(key, None)
if group is None:
sink, id = QgsProcessingUtils.createFeatureSink(
'memory:', context, source.fields(), source.wkbType(),
source.sourceCrs())
layer = QgsProcessingUtils.mapLayerFromString(id, context)
group = {'sink': sink, 'layer': layer, 'feature': feature}
groups[key] = group
keys.append(key)
group['sink'].addFeature(feature, QgsFeatureSink.FastInsert)
current += 1
feedback.setProgress(int(current * progress_step))
if feedback.isCanceled():
return
(sink, dest_id) = self.parameterAsSink(
parameters, self.OUTPUT, context, self.fields,
QgsWkbTypes.multiType(source.wkbType()), source.sourceCrs())
# Calculate aggregates on memory layers
if len(keys):
progress_step = 50.0 / len(keys)
for current, key in enumerate(keys):
group = groups[key]
expr_context = self.createExpressionContext(parameters, context)
expr_context.appendScope(
QgsExpressionContextUtils.layerScope(group['layer']))
expr_context.setFeature(group['feature'])
geometry = self.evaluateExpression(self.geometry_expr,
expr_context)
if geometry is not None and not geometry.isEmpty():
geometry = QgsGeometry.unaryUnion(
geometry.asGeometryCollection())
if geometry.isEmpty():
raise QgsProcessingException(
'Impossible to combine geometries for {} = {}'.format(
self.group_by, group_by_value))
attrs = []
for fields_expr in self.fields_expr:
attrs.append(self.evaluateExpression(fields_expr,
expr_context))
# Write output feature
outFeat = QgsFeature()
if geometry is not None:
outFeat.setGeometry(geometry)
outFeat.setAttributes(attrs)
sink.addFeature(outFeat, QgsFeatureSink.FastInsert)
feedback.setProgress(50 + int(current * progress_step))
if feedback.isCanceled():
return
return {self.OUTPUT: dest_id}
def processAlgorithm(self, parameters, context, feedback):
expr_context = self.createExpressionContext(parameters, context, self.source)
self.group_by_expr.prepare(expr_context)
# Group features in memory layers
source = self.source
count = self.source.featureCount()
if count:
progress_step = 50.0 / count
current = 0
groups = {}
keys = [] # We need deterministic order for the tests
feature = QgsFeature()
for feature in self.source.getFeatures():
expr_context.setFeature(feature)
group_by_value = self.evaluateExpression(self.group_by_expr, expr_context)
# Get an hashable key for the dict
key = group_by_value
if isinstance(key, list):
key = tuple(key)
group = groups.get(key, None)
if group is None:
sink, id = QgsProcessingUtils.createFeatureSink(
'memory:',
context,
source.fields(),
source.wkbType(),
source.sourceCrs())
layer = QgsProcessingUtils.mapLayerFromString(id, context)
group = {
'sink': sink,
'layer': layer,
'feature': feature
}
groups[key] = group
keys.append(key)
group['sink'].addFeature(feature, QgsFeatureSink.FastInsert)
current += 1
feedback.setProgress(int(current * progress_step))
if feedback.isCanceled():
return
(sink, dest_id) = self.parameterAsSink(parameters,
self.OUTPUT,
context,
self.fields,
QgsWkbTypes.multiType(source.wkbType()),
source.sourceCrs())
if sink is None:
raise QgsProcessingException(self.invalidSinkError(parameters, self.OUTPUT))
# Calculate aggregates on memory layers
if len(keys):
progress_step = 50.0 / len(keys)
for current, key in enumerate(keys):
group = groups[key]
expr_context = self.createExpressionContext(parameters, context)
expr_context.appendScope(QgsExpressionContextUtils.layerScope(group['layer']))
expr_context.setFeature(group['feature'])
geometry = self.evaluateExpression(self.geometry_expr, expr_context)
if geometry is not None and not geometry.isEmpty():
geometry = QgsGeometry.unaryUnion(geometry.asGeometryCollection())
if geometry.isEmpty():
raise QgsProcessingException(
'Impossible to combine geometries for {} = {}'
.format(self.group_by, group_by_value))
attrs = []
for fields_expr in self.fields_expr:
attrs.append(self.evaluateExpression(fields_expr, expr_context))
# Write output feature
outFeat = QgsFeature()
if geometry is not None:
outFeat.setGeometry(geometry)
outFeat.setAttributes(attrs)
sink.addFeature(outFeat, QgsFeatureSink.FastInsert)
feedback.setProgress(50 + int(current * progress_step))
if feedback.isCanceled():
return
return {self.OUTPUT: dest_id}
##Centroids=name
##Geometry=group
##INPUT_LAYER=vector
##OUTPUT_LAYER=output vector
from qgis.core import QgsWkbTypes, QgsProcessingUtils
layer = QgsProcessingUtils.mapLayerFromString(INPUT_LAYER, context)
fields = layer.fields()
writer, writer_dest = QgsProcessingUtils.createFeatureSink(
OUTPUT_LAYER, context, fields, QgsWkbTypes.Point, layer.crs(),
{'fileEncoding': 'utf-8'})
features = QgsProcessingUtils.getFeatures(layer, context)
count = QgsProcessingUtils.featureCount(layer, context)
if count == 0:
raise GeoAlgorithmExecutionException('Input layer contains no features.')
total = 100.0 / count
for count, f in enumerate(features):
outputFeature = f
if f.hasGeometry():
outputGeometry = f.geometry().centroid()
outputFeature.setGeometry(outputGeometry)
writer.addFeature(outputFeature)
feedback.setProgress(int(count * total))
##Centroids=name
##Geometry=group
##INPUT_LAYER=vector
##OUTPUT_LAYER=output vector
from qgis.core import QgsWkbTypes, QgsProcessingUtils
layer = QgsProcessingUtils.mapLayerFromString(INPUT_LAYER, context)
fields = layer.fields()
writer, writer_dest = QgsProcessingUtils.createFeatureSink(
OUTPUT_LAYER, 'utf-8', fields, QgsWkbTypes.Point, layer.crs(), context)
features = QgsProcessingUtils.getFeatures(layer, context)
count = QgsProcessingUtils.featureCount(layer, context)
if count == 0:
raise GeoAlgorithmExecutionException('Input layer contains no features.')
total = 100.0 / count
for count, f in enumerate(features):
outputFeature = f
if f.hasGeometry():
outputGeometry = f.geometry().centroid()
outputFeature.setGeometry(outputGeometry)
writer.addFeature(outputFeature)
feedback.setProgress(int(count * total))
##Vector table tools=group
##input=vector
##class_field=field input
##value_field=field input
##N_unique_values=output vector
from qgis.PyQt.QtCore import QVariant
from qgis.core import QgsFeature, QgsField, QgsProcessingUtils
layer = QgsProcessingUtils.mapLayerFromString(input, context)
fields = layer.fields()
fields.append(QgsField('UNIQ_COUNT', QVariant.Int))
writer, writer_dest = QgsProcessingUtils.createFeatureSink(
N_unique_values, context, fields, layer.wkbType(), layer.crs())
class_field_index = layer.fields().lookupField(class_field)
value_field_index = layer.fields().lookupField(value_field)
outFeat = QgsFeature()
classes = {}
feats = QgsProcessingUtils.getFeatures(layer, context)
nFeat = QgsProcessingUtils.featureCount(layer, context)
for n, inFeat in enumerate(feats):
feedback.setProgress(int(100 * n / nFeat))
attrs = inFeat.attributes()
clazz = attrs[class_field_index]
value = attrs[value_field_index]
if clazz not in classes:
classes[clazz] = []
if value not in classes[clazz]:
classes[clazz].append(value)
##Centroids=name
##Geometry=group
##INPUT_LAYER=vector
##OUTPUT_LAYER=output vector
from qgis.core import QgsWkbTypes, QgsProcessingUtils
layer = QgsProcessingUtils.mapLayerFromString(INPUT_LAYER, context)
fields = layer.fields()
writer, writer_dest = QgsProcessingUtils.createFeatureSink(OUTPUT_LAYER, context, fields, QgsWkbTypes.Point, layer.crs(), {'fileEncoding': 'utf-8'})
features = QgsProcessingUtils.getFeatures(layer, context)
count = QgsProcessingUtils.featureCount(layer, context)
if count == 0:
raise GeoAlgorithmExecutionException('Input layer contains no features.')
total = 100.0 / count
for count, f in enumerate(features):
outputFeature = f
if f.hasGeometry():
outputGeometry = f.geometry().centroid()
outputFeature.setGeometry(outputGeometry)
writer.addFeature(outputFeature)
feedback.setProgress(int(count * total))
##Vector table tools=group
##input=vector
##class_field=field input
##value_field=field input
##N_unique_values=output vector
from qgis.PyQt.QtCore import QVariant
from qgis.core import QgsFeature, QgsField, QgsProcessingUtils
layer = QgsProcessingUtils.mapLayerFromString(input, context)
fields = layer.fields()
fields.append(QgsField('UNIQ_COUNT', QVariant.Int))
writer, writer_dest = QgsProcessingUtils.createFeatureSink(N_unique_values, context, fields, layer.wkbType(), layer.crs())
class_field_index = layer.fields().lookupField(class_field)
value_field_index = layer.fields().lookupField(value_field)
outFeat = QgsFeature()
classes = {}
feats = QgsProcessingUtils.getFeatures(layer, context)
nFeat = QgsProcessingUtils.featureCount(layer, context)
for n, inFeat in enumerate(feats):
feedback.setProgress(int(100 * n / nFeat))
attrs = inFeat.attributes()
clazz = attrs[class_field_index]
value = attrs[value_field_index]
if clazz not in classes:
classes[clazz] = []
if value not in classes[clazz]:
classes[clazz].append(value)
