Merge pull request #4873 from nyalldawson/processing_feature_alg

Add QgsProcessingFeatureBasedAlgorithm subclass

Author: nyalldawson

python/core/processing/qgsprocessingalgorithm.sip

@@ -30,6 +30,8 @@ class QgsProcessingAlgorithm
 %ConvertToSubClassCode
     if ( dynamic_cast< QgsProcessingModelAlgorithm * >( sipCpp ) != NULL )
       sipType = sipType_QgsProcessingModelAlgorithm;
+    else if ( dynamic_cast< QgsProcessingFeatureBasedAlgorithm * >( sipCpp ) != NULL )
+      sipType = sipType_QgsProcessingFeatureBasedAlgorithm;
     else
       sipType = sipType_QgsProcessingAlgorithm;
 %End
@@ -717,6 +719,136 @@ QFlags<QgsProcessingAlgorithm::Flag> operator|(QgsProcessingAlgorithm::Flag f1,
 
 
 
+class QgsProcessingFeatureBasedAlgorithm : QgsProcessingAlgorithm
+{
+%Docstring
+ An abstract QgsProcessingAlgorithm base class for processing algorithms which operate "feature-by-feature".
+
+ Feature based algorithms are algorithms which operate on individual features in isolation. These
+ are algorithms where one feature is output for each input feature, and the output feature result
+ for each input feature is not dependent on any other features present in the source.
+
+ For instance, algorithms like "centroids" and "buffers" are feature based algorithms since the centroid
+ or buffer of a feature is calculated for each feature in isolation. An algorithm like "dissolve"
+ is NOT suitable for a feature based algorithm as the dissolved output depends on multiple input features
+ and these features cannot be processed in isolation.
+
+ Using QgsProcessingFeatureBasedAlgorithm as the base class for feature based algorithms allows
+ shortcutting much of the common algorithm code for handling iterating over sources and pushing
+ features to output sinks. It also allows the algorithm execution to be optimised in future
+ (for instance allowing automatic multi-thread processing of the algorithm, or use of the
+ algorithm in "chains", avoiding the need for temporary outputs in multi-step models).
+
+.. versionadded:: 3.0
+%End
+
+%TypeHeaderCode
+#include "qgsprocessingalgorithm.h"
+%End
+  public:
+
+    QgsProcessingFeatureBasedAlgorithm();
+%Docstring
+ Constructor for QgsProcessingFeatureBasedAlgorithm.
+%End
+
+  protected:
+
+    virtual void initAlgorithm( const QVariantMap &configuration = QVariantMap() );
+
+
+    virtual QString outputName() const = 0;
+%Docstring
+ Returns the translated, user visible name for any layers created by this algorithm.
+ This name will be used as the default name when loading the resultant layer into a
+ QGIS project.
+ :rtype: str
+%End
+
+    virtual QgsProcessing::LayerType outputLayerType() const;
+%Docstring
+ Returns the layer type for layers generated by this algorithm, if
+ this is possible to determine in advance.
+ :rtype: QgsProcessing.LayerType
+%End
+
+    virtual QgsWkbTypes::Type outputWkbType( QgsWkbTypes::Type inputWkbType ) const;
+%Docstring
+ Maps the input WKB geometry type (``inputWkbType``) to the corresponding
+ output WKB type generated by the algorithm. The default behavior is that the algorithm maintains
+ the same WKB type.
+ This is called once by the base class when creating the output sink for the algorithm (i.e. it is
+ not called once per feature processed).
+ :rtype: QgsWkbTypes.Type
+%End
+
+    virtual QgsFields outputFields( const QgsFields &inputFields ) const;
+%Docstring
+ Maps the input source fields (``inputFields``) to corresponding
+ output fields generated by the algorithm. The default behavior is that the algorithm maintains
+ the same fields as are input.
+ Algorithms which add, remove or modify existing fields should override this method and
+ implement logic here to indicate which fields are output by the algorithm.
+
+ This is called once by the base class when creating the output sink for the algorithm (i.e. it is
+ not called once per feature processed).
+ :rtype: QgsFields
+%End
+
+    virtual QgsCoordinateReferenceSystem outputCrs( const QgsCoordinateReferenceSystem &inputCrs ) const;
+%Docstring
+ Maps the input source coordinate reference system (``inputCrs``) to a corresponding
+ output CRS generated by the algorithm. The default behavior is that the algorithm maintains
+ the same CRS as the input source.
+
+ This is called once by the base class when creating the output sink for the algorithm (i.e. it is
+ not called once per feature processed).
+ :rtype: QgsCoordinateReferenceSystem
+%End
+
+    virtual void initParameters( const QVariantMap &configuration = QVariantMap() );
+%Docstring
+ Initializes any extra parameters added by the algorithm subclass. There is no need
+ to declare the input source or output sink, as these are automatically created by
+ QgsProcessingFeatureBasedAlgorithm.
+%End
+
+    QgsCoordinateReferenceSystem sourceCrs() const;
+%Docstring
+ Returns the source's coordinate reference system. This will only return a valid CRS when
+ called from a subclasses' processFeature() implementation.
+ :rtype: QgsCoordinateReferenceSystem
+%End
+
+    virtual QgsFeature processFeature( const QgsFeature &feature, QgsProcessingFeedback *feedback ) = 0;
+%Docstring
+ Processes an individual input ``feature`` from the source. Algorithms should implement their
+ logic in this method for performing the algorithm's operation (e.g. replacing the feature's
+ geometry with the centroid of the original feature geometry for a 'centroid' type
+ algorithm).
+
+ Implementations should return the modified feature. Returning an invalid feature (e.g.
+ a default constructed QgsFeature) will indicate that this feature should be 'skipped',
+ and will not be added to the algorithm's output. Subclasses can use this approach to
+ filter the incoming features as desired.
+
+ The provided ``feedback`` object can be used to push messages to the log and for giving feedback
+ to users. Note that handling of progress reports and algorithm cancelation is handled by
+ the base class and subclasses do not need to reimplement this logic.
+
+ Algorithms can throw a QgsProcessingException if a fatal error occurred which should
+ prevent the algorithm execution from continuing. This can be annoying for users though as it
+ can break valid model execution - so use with extreme caution, and consider using
+ ``feedback`` to instead report non-fatal processing failures for features instead.
+ :rtype: QgsFeature
+%End
+
+    virtual QVariantMap processAlgorithm( const QVariantMap &parameters,
+                                          QgsProcessingContext &context, QgsProcessingFeedback *feedback );
+
+};
+
+
 
 /************************************************************************
  * This file has been generated automatically from                      *

python/plugins/processing/algs/help/qgis.yaml

@@ -160,6 +160,9 @@ qgis:distancetonearesthub: >
 qgis:dropgeometries: >
   This algorithm removes any geometries from an input layer and returns a layer containing only the feature attributes.
 
+qgis:dropmzvalues: >
+  This algorithm can remove any measure (M) or Z values from input geometries.
+
 qgis:eliminateselectedpolygons: >
   This algorithm combines selected polygons of the input layer with certain adjacent polygons by erasing their common boundary. The adjacent polygon can be either the one with the largest or smallest area or the one sharing the largest common boundary with the polygon to be eliminated. The selected features will always be eliminated whether the option "Use only selected features" is set or not.
   Eliminate is normally used to get rid of sliver polygons, i.e. tiny polygons that are a result of polygon intersection processes where boundaries of the inputs are similar but not identical.
@@ -503,13 +506,22 @@ qgis:selectbyexpression: >
 qgis:selectbylocation: >
   This algorithm creates a selection in a vector layer. The criteria for selecting features is based on the spatial relationship between each feature and the features in an additional layer.
 
+qgis:setmvalue: >
+  This algorithm sets the M value for geometries in a layer.
+
+  If M values already exist in the layer, they will be overwritten with the new value. If no M values exist, the geometry will be upgraded to include M values and the specified value used as the initial M value for all geometries.
 
 qgis:setstyleforrasterlayer: >
   This algorithm sets the style of a raster layer. The style must be defined in a QML file.
 
 qgis:setstyleforvectorlayer: >
   This algorithm sets the style of a vector layer. The style must be defined in a QML file.
 
+qgis:setzvalue: >
+  This algorithm sets the Z value for geometries in a layer.
+
+  If Z values already exist in the layer, they will be overwritten with the new value. If no Z values exist, the geometry will be upgraded to include Z values and the specified value used as the initial Z value for all geometries.
+
 qgis:simplifygeometries: >
   This algorithm simplifies the geometries in a line or polygon layer. It creates a new layer with the same features as the ones in the input layer, but with geometries containing a lower number of vertices.
 

python/plugins/processing/algs/qgis/AddTableField.py

@@ -27,19 +27,14 @@
 
 from qgis.PyQt.QtCore import QVariant
 from qgis.core import (QgsField,
-                       QgsFeatureSink,
-                       QgsProcessingParameterFeatureSource,
                        QgsProcessingParameterString,
                        QgsProcessingParameterNumber,
-                       QgsProcessingParameterEnum,
-                       QgsProcessingParameterFeatureSink)
-from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
+                       QgsProcessingParameterEnum)
+from processing.algs.qgis.QgisAlgorithm import QgisFeatureBasedAlgorithm
 
 
-class AddTableField(QgisAlgorithm):
+class AddTableField(QgisFeatureBasedAlgorithm):
 
-    OUTPUT_LAYER = 'OUTPUT_LAYER'
-    INPUT_LAYER = 'INPUT_LAYER'
     FIELD_NAME = 'FIELD_NAME'
     FIELD_TYPE = 'FIELD_TYPE'
     FIELD_LENGTH = 'FIELD_LENGTH'
@@ -55,10 +50,9 @@ def __init__(self):
         self.type_names = [self.tr('Integer'),
                            self.tr('Float'),
                            self.tr('String')]
+        self.field = None
 
-    def initAlgorithm(self, config=None):
-        self.addParameter(QgsProcessingParameterFeatureSource(self.INPUT_LAYER,
-                                                              self.tr('Input layer')))
+    def initParameters(self, config=None):
         self.addParameter(QgsProcessingParameterString(self.FIELD_NAME,
                                                        self.tr('Field name')))
         self.addParameter(QgsProcessingParameterEnum(self.FIELD_TYPE,
@@ -68,41 +62,32 @@ def initAlgorithm(self, config=None):
                                                        10, False, 1, 255))
         self.addParameter(QgsProcessingParameterNumber(self.FIELD_PRECISION,
                                                        self.tr('Field precision'), QgsProcessingParameterNumber.Integer, 0, False, 0, 10))
-        self.addParameter(QgsProcessingParameterFeatureSink(self.OUTPUT_LAYER, self.tr('Added')))
 
     def name(self):
         return 'addfieldtoattributestable'
 
     def displayName(self):
         return self.tr('Add field to attributes table')
 
-    def processAlgorithm(self, parameters, context, feedback):
-        source = self.parameterAsSource(parameters, self.INPUT_LAYER, context)
+    def outputName(self):
+        return self.tr('Added')
 
-        fieldType = self.parameterAsEnum(parameters, self.FIELD_TYPE, context)
-        fieldName = self.parameterAsString(parameters, self.FIELD_NAME, context)
-        fieldLength = self.parameterAsInt(parameters, self.FIELD_LENGTH, context)
-        fieldPrecision = self.parameterAsInt(parameters, self.FIELD_PRECISION, context)
+    def prepareAlgorithm(self, parameters, context, feedback):
+        field_type = self.parameterAsEnum(parameters, self.FIELD_TYPE, context)
+        field_name = self.parameterAsString(parameters, self.FIELD_NAME, context)
+        field_length = self.parameterAsInt(parameters, self.FIELD_LENGTH, context)
+        field_precision = self.parameterAsInt(parameters, self.FIELD_PRECISION, context)
 
-        fields = source.fields()
-        fields.append(QgsField(fieldName, self.TYPES[fieldType], '',
-                               fieldLength, fieldPrecision))
-        (sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT_LAYER, context,
-                                               fields, source.wkbType(), source.sourceCrs())
+        self.field = QgsField(field_name, self.TYPES[field_type], '',
+                              field_length, field_precision)
+        return True
 
-        features = source.getFeatures()
-        total = 100.0 / source.featureCount() if source.featureCount() else 0
+    def outputFields(self, inputFields):
+        inputFields.append(self.field)
+        return inputFields
 
-        for current, input_feature in enumerate(features):
-            if feedback.isCanceled():
-                break
-
-            output_feature = input_feature
-            attributes = input_feature.attributes()
-            attributes.append(None)
-            output_feature.setAttributes(attributes)
-
-            sink.addFeature(output_feature, QgsFeatureSink.FastInsert)
-            feedback.setProgress(int(current * total))
-
-        return {self.OUTPUT_LAYER: dest_id}
+    def processFeature(self, feature, feedback):
+        attributes = feature.attributes()
+        attributes.append(None)
+        feature.setAttributes(attributes)
+        return feature

python/plugins/processing/algs/qgis/AutoincrementalField.py

@@ -26,26 +26,15 @@
 __revision__ = '$Format:%H$'
 
 from qgis.PyQt.QtCore import QVariant
-from qgis.core import (QgsField,
-                       QgsFeatureSink,
-                       QgsProcessingParameterFeatureSource,
-                       QgsProcessingParameterFeatureSink)
-from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
+from qgis.core import (QgsField)
+from processing.algs.qgis.QgisAlgorithm import QgisFeatureBasedAlgorithm
 
 
-class AutoincrementalField(QgisAlgorithm):
-
-    INPUT = 'INPUT'
-    OUTPUT = 'OUTPUT'
+class AutoincrementalField(QgisFeatureBasedAlgorithm):
 
     def __init__(self):
         super().__init__()
-
-    def initAlgorithm(self, config=None):
-        self.addParameter(QgsProcessingParameterFeatureSource(self.INPUT,
-                                                              self.tr('Input layer')))
-
-        self.addParameter(QgsProcessingParameterFeatureSink(self.OUTPUT, self.tr('Incremented')))
+        self.current = 0
 
     def group(self):
         return self.tr('Vector table tools')
@@ -56,26 +45,16 @@ def name(self):
     def displayName(self):
         return self.tr('Add autoincremental field')
 
-    def processAlgorithm(self, parameters, context, feedback):
-        source = self.parameterAsSource(parameters, self.INPUT, context)
-        fields = source.fields()
-        fields.append(QgsField('AUTO', QVariant.Int))
-
-        (sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context,
-                                               fields, source.wkbType(), source.sourceCrs())
-
-        features = source.getFeatures()
-        total = 100.0 / source.featureCount() if source.featureCount() else 0
-        for current, input_feature in enumerate(features):
-            if feedback.isCanceled():
-                break
-
-            output_feature = input_feature
-            attributes = input_feature.attributes()
-            attributes.append(current)
-            output_feature.setAttributes(attributes)
+    def outputName(self):
+        return self.tr('Incremented')
 
-            sink.addFeature(output_feature, QgsFeatureSink.FastInsert)
-            feedback.setProgress(int(current * total))
+    def outputFields(self, inputFields):
+        inputFields.append(QgsField('AUTO', QVariant.Int))
+        return inputFields
 
-        return {self.OUTPUT: dest_id}
+    def processFeature(self, feature, feedback):
+        attributes = feature.attributes()
+        attributes.append(self.current)
+        self.current += 1
+        feature.setAttributes(attributes)
+        return feature