backporting #6678 to release-3_0

Author: ghtmtt

python/plugins/processing/script/ScriptTemplate.py

@@ -0,0 +1,145 @@
+# -*- coding: utf-8 -*-
+
+from PyQt5.QtCore import QCoreApplication
+from qgis.core import (QgsProcessing,
+                       QgsFeatureSink,
+                       QgsProcessingAlgorithm,
+                       QgsProcessingParameterFeatureSource,
+                       QgsProcessingParameterFeatureSink)
+
+
+class ExampleProcessingAlgorithm(QgsProcessingAlgorithm):
+    """
+    This is an example algorithm that takes a vector layer and
+    creates a new identical one.
+
+    It is meant to be used as an example of how to create your own
+    algorithms and explain methods and variables used to do it. An
+    algorithm like this will be available in all elements, and there
+    is not need for additional work.
+
+    All Processing algorithms should extend the QgsProcessingAlgorithm
+    class.
+    """
+
+    # Constants used to refer to parameters and outputs. They will be
+    # used when calling the algorithm from another algorithm, or when
+    # calling from the QGIS console.
+
+    INPUT = 'INPUT'
+    OUTPUT = 'OUTPUT'
+
+    def tr(self, string):
+        """
+        Returns a translatable string with the self.tr() function.
+        """
+        return QCoreApplication.translate('Processing', string)
+
+    def createInstance(self):
+        return ExampleProcessingAlgorithm()
+
+    def name(self):
+        """
+        Returns the algorithm name, used for identifying the algorithm. This
+        string should be fixed for the algorithm, and must not be localised.
+        The name should be unique within each provider. Names should contain
+        lowercase alphanumeric characters only and no spaces or other
+        formatting characters.
+        """
+        return 'duplicatevectorlayer'
+
+    def displayName(self):
+        """
+        Returns the translated algorithm name, which should be used for any
+        user-visible display of the algorithm name.
+        """
+        return self.tr('Duplicate a vector layer')
+
+    def group(self):
+        """
+        Returns the name of the group this algorithm belongs to. This string
+        should be localised.
+        """
+        return self.tr('Example scripts')
+
+    def groupId(self):
+        """
+        Returns the unique ID of the group this algorithm belongs to. This
+        string should be fixed for the algorithm, and must not be localised.
+        The group id should be unique within each provider. Group id should
+        contain lowercase alphanumeric characters only and no spaces or other
+        formatting characters.
+        """
+        return 'examplescripts'
+
+    def initAlgorithm(self, config=None):
+        """
+        Here we define the inputs and output of the algorithm, along
+        with some other properties.
+        """
+
+        # We add the input vector features source. It can have any kind of
+        # geometry.
+        self.addParameter(
+            QgsProcessingParameterFeatureSource(
+                self.INPUT,
+                self.tr('Input layer'),
+                [QgsProcessing.TypeVectorAnyGeometry]
+            )
+        )
+
+        # We add a feature sink in which to store our processed features (this
+        # usually takes the form of a newly created vector layer when the
+        # algorithm is run in QGIS).
+        self.addParameter(
+            QgsProcessingParameterFeatureSink(
+                self.OUTPUT,
+                self.tr('Output layer')
+            )
+        )
+
+    def processAlgorithm(self, parameters, context, feedback):
+        """
+        Here is where the processing itself takes place.
+        """
+
+        # Retrieve the feature source and sink. The 'dest_id' variable is used
+        # to uniquely identify the feature sink, and must be included in the
+        # dictionary returned by the processAlgorithm function.
+        source = self.parameterAsSource(
+            parameters,
+            self.INPUT,
+            context
+        )
+        (sink, dest_id) = self.parameterAsSink(
+            parameters,
+            self.OUTPUT,
+            context,
+            source.fields(),
+            source.wkbType(),
+            source.sourceCrs()
+        )
+
+        # Compute the number of steps to display within the progress bar and
+        # get features from source
+        total = 100.0 / source.featureCount() if source.featureCount() else 0
+        features = source.getFeatures()
+
+        for current, feature in enumerate(features):
+            # Stop the algorithm if cancel button has been clicked
+            if feedback.isCanceled():
+                break
+
+            # Add a feature in the sink
+            sink.addFeature(feature, QgsFeatureSink.FastInsert)
+
+            # Update the progress bar
+            feedback.setProgress(int(current * total))
+
+        # Return the results of the algorithm. In this case our only result is
+        # the feature sink which contains the processed features, but some
+        # algorithms may return multiple feature sinks, calculated numeric
+        # statistics, etc. These should all be included in the returned
+        # dictionary, with keys matching the feature corresponding parameter
+        # or output names.
+        return {self.OUTPUT: dest_id}