Writing new Processing algorithms as Python scripts ==================================================== .. only:: html .. contents:: :local: In QGIS 3.4, the only way to write Processing algorithms using Python is to extend the :class:`QgsProcessingAlgorithm ` class. Within QGIS, you can use :guilabel:`Create new script` in the :guilabel:`Scripts` menu at the top of the :guilabel:`Processing Toolbox` to open the :guilabel:`Processing Script Editor` where you can write your code. To simplify the task, you can start with a script template by using :guilabel:`Create new script from template` from the same menu. This opens a template that extends :class:`QgsProcessingAlgorithm `. If you save the script in the :file:`scripts` folder (the default location) with a :file:`.py` extension, the algorithm will become available in the :guilabel:`Processing Toolbox`. Extending QgsProcessingAlgorithm -------------------------------- The following code #. takes a vector layer as input #. counts the number of features #. does a buffer operation #. creates a raster layer from the result of the buffer operation #. returns the buffer layer, raster layer and number of features .. testcode:: from qgis.PyQt.QtCore import QCoreApplication from qgis.core import (QgsProcessing, QgsProcessingAlgorithm, QgsProcessingException, QgsProcessingOutputNumber, QgsProcessingParameterDistance, QgsProcessingParameterFeatureSource, QgsProcessingParameterVectorDestination, QgsProcessingParameterRasterDestination) import processing class ExampleProcessingAlgorithm(QgsProcessingAlgorithm): """ This is an example algorithm that takes a vector layer, creates some new layers and returns some results. """ def tr(self, string): """ Returns a translatable string with the self.tr() function. """ return QCoreApplication.translate('Processing', string) def createInstance(self): # Must return a new copy of your algorithm. return ExampleProcessingAlgorithm() def name(self): """ Returns the unique algorithm name. """ return 'bufferrasterextend' def displayName(self): """ Returns the translated algorithm name. """ return self.tr('Buffer and export to raster (extend)') def group(self): """ Returns the name of the group this algorithm belongs to. """ return self.tr('Example scripts') def groupId(self): """ Returns the unique ID of the group this algorithm belongs to. """ return 'examplescripts' def shortHelpString(self): """ Returns a localised short help string for the algorithm. """ return self.tr('Example algorithm short description') def initAlgorithm(self, config=None): """ Here we define the inputs and outputs of the algorithm. """ # 'INPUT' is the recommended name for the main input # parameter. self.addParameter( QgsProcessingParameterFeatureSource( 'INPUT', self.tr('Input vector layer'), types=[QgsProcessing.TypeVectorAnyGeometry] ) ) self.addParameter( QgsProcessingParameterVectorDestination( 'BUFFER_OUTPUT', self.tr('Buffer output'), ) ) # 'OUTPUT' is the recommended name for the main output # parameter. self.addParameter( QgsProcessingParameterRasterDestination( 'OUTPUT', self.tr('Raster output') ) ) self.addParameter( QgsProcessingParameterDistance( 'BUFFERDIST', self.tr('BUFFERDIST'), defaultValue = 1.0, # Make distance units match the INPUT layer units: parentParameterName='INPUT' ) ) self.addParameter( QgsProcessingParameterDistance( 'CELLSIZE', self.tr('CELLSIZE'), defaultValue = 10.0, parentParameterName='INPUT' ) ) self.addOutput( QgsProcessingOutputNumber( 'NUMBEROFFEATURES', self.tr('Number of features processed') ) ) def processAlgorithm(self, parameters, context, feedback): """ Here is where the processing itself takes place. """ # First, we get the count of features from the INPUT layer. # This layer is defined as a QgsProcessingParameterFeatureSource # parameter, so it is retrieved by calling # self.parameterAsSource. input_featuresource = self.parameterAsSource(parameters, 'INPUT', context) numfeatures = input_featuresource.featureCount() # Retrieve the buffer distance and raster cell size numeric # values. Since these are numeric values, they are retrieved # using self.parameterAsDouble. bufferdist = self.parameterAsDouble(parameters, 'BUFFERDIST', context) rastercellsize = self.parameterAsDouble(parameters, 'CELLSIZE', context) if feedback.isCanceled(): return {} buffer_result = processing.run( 'native:buffer', { # Here we pass on the original parameter values of INPUT # and BUFFER_OUTPUT to the buffer algorithm. 'INPUT': parameters['INPUT'], 'OUTPUT': parameters['BUFFER_OUTPUT'], 'DISTANCE': bufferdist, 'SEGMENTS': 10, 'DISSOLVE': True, 'END_CAP_STYLE': 0, 'JOIN_STYLE': 0, 'MITER_LIMIT': 10 }, # Because the buffer algorithm is being run as a step in # another larger algorithm, the is_child_algorithm option # should be set to True is_child_algorithm=True, # # It's important to pass on the context and feedback objects to # child algorithms, so that they can properly give feedback to # users and handle cancelation requests. context=context, feedback=feedback) # Check for cancelation if feedback.isCanceled(): return {} # Run the separate rasterization algorithm using the buffer result # as an input. rasterized_result = processing.run( 'qgis:rasterize', { # Here we pass the 'OUTPUT' value from the buffer's result # dictionary off to the rasterize child algorithm. 'LAYER': buffer_result['OUTPUT'], 'EXTENT': buffer_result['OUTPUT'], 'MAP_UNITS_PER_PIXEL': rastercellsize, # Use the original parameter value. 'OUTPUT': parameters['OUTPUT'] }, is_child_algorithm=True, context=context, feedback=feedback) if feedback.isCanceled(): return {} # Return the results return {'OUTPUT': rasterized_result['OUTPUT'], 'BUFFER_OUTPUT': buffer_result['OUTPUT'], 'NUMBEROFFEATURES': numfeatures} Processing algorithm standard functions: * createInstance (mandatory) Must return a new copy of your algorithm. If you change the name of the class, make sure you also update the value returned here to match! * name (mandatory) Returns the unique algorithm name, used for identifying the algorithm. * displayName (mandatory) Returns the translated algorithm name. * group Returns the name of the group this algorithm belongs to. * groupId Returns the unique ID of the group this algorithm belongs to. * shortHelpString Returns a localised short help string for the algorithm. * initAlgorithm (mandatory) Here we define the inputs and outputs of the algorithm. ``INPUT`` and ``OUTPUT`` are recommended names for the main input and main output parameters, respectively. If a parameter depends on another parameter, ``parentParameterName`` is used to specify this relationship (could be the field / band of a layer or the distance units of a layer). * processAlgorithm (mandatory) This is where the processing takes place. Parameters are retrieved using special purpose functions, for instance ``parameterAsSource`` and ``parameterAsDouble``. ``processing.run`` can be used to run other processing algorithms from a processing algorithm. The first parameter is the name of the algorithm, the second is a dictionary of the parameters to the algorithm. ``is_child_algorithm`` is normally set to ``True`` when running an algorithm from within another algorithm. ``context`` and ``feedback`` inform the algorithm about the environment to run in and the channel for communicating with the user (catching cancel request, reporting progress, providing textual feedback). When using the (parent) algorithm's parameters as parameters to "child" algorithms, the original parameter values should be used (e.g. ``parameters['OUTPUT']``). It is good practice to check the feedback object for cancelation as much as is sensibly possible! Doing so allows for responsive cancelation, instead of forcing users to wait for unwanted processing to occur. The algorithm should return values for all the output parameters it has defined as a dictionary. In this case, that's the buffer and rasterized output layers, and the count of features processed. The dictionary keys must match the original parameter/output names. .. _processing_algs_input_output: Input and output types for Processing Algorithms ------------------------------------------------------- Here is the list of input and output types that are supported in Processing with their corresponding alg decorator constants (:file:`algfactory.py` contains the complete list of alg constants). Sorted on class name. .. list-table:: Input types :widths: 55 21 :header-rows: 1 * - Class - Description * - :class:`QgsProcessingParameterBand ` - A band of a raster layer * - :class:`QgsProcessingParameterBoolean ` - A boolean value * - :class:`QgsProcessingParameterCrs ` - A Coordinate Reference System * - :class:`QgsProcessingParameterDistance ` - A double numeric parameter for distance values * - :class:`QgsProcessingParameterEnum ` - An enumeration, allowing for selection from a set of predefined values * - :class:`QgsProcessingParameterExpression ` - An expression * - :class:`QgsProcessingParameterExtent ` - A spatial extent defined by xmin, xmax, ymin, ymax * - :class:`QgsProcessingParameterFeatureSink ` - A feature sink * - :class:`QgsProcessingParameterFeatureSource ` - A feature source * - :class:`QgsProcessingParameterField ` - A field in the attribute table of a vector layer * - :class:`QgsProcessingParameterFile ` - A filename of an existing file * - :class:`QgsProcessingParameterFileDestination ` - A filename for a newly created output file * - :class:`QgsProcessingParameterFolderDestination ` - A folder * - :class:`QgsProcessingParameterMapLayer ` - A map layer * - :class:`QgsProcessingParameterMatrix ` - A matrix * - :class:`QgsProcessingParameterMultipleLayers ` - A set of layers * - :class:`QgsProcessingParameterNumber ` - A numerical value * - :class:`QgsProcessingParameterPoint ` - A point * - :class:`QgsProcessingParameterRange ` - A number range * - :class:`QgsProcessingParameterRasterLayer ` - A raster layer * - :class:`QgsProcessingParameterRasterDestination ` - A raster layer * - :class:`QgsProcessingParameterString ` - A text string * - :class:`QgsProcessingParameterVectorLayer ` - A vector layer * - :class:`QgsProcessingParameterVectorDestination ` - A vector layer | .. list-table:: Output types :widths: 50 25 :header-rows: 1 * - Class - Description * - :class:`QgsProcessingOutputFile ` - A filename of an existing file * - :class:`QgsProcessingOutputFolder ` - A folder * - :class:`QgsProcessingOutputHtml ` - HTML * - :class:`QgsProcessingOutputLayerDefinition ` - A layer definition * - :class:`QgsProcessingOutputMapLayer ` - A map layer * - :class:`QgsProcessingOutputMultipleLayers ` - A set of layers * - :class:`QgsProcessingOutputNumber ` - A numerical value * - :class:`QgsProcessingOutputRasterLayer ` - A raster layer * - :class:`QgsProcessingOutputString ` - A text string * - :class:`QgsProcessingOutputVectorLayer ` - A vector layer Handing algorithm output ------------------------ When you declare an output representing a layer (raster or vector), the algorithm will try to add it to QGIS once it is finished. * Raster layer output: QgsProcessingParameterRasterDestination. * Vector layer output: QgsProcessingParameterVectorDestination. So even if the ``processing.run()`` method does not add the layers it creates into the user's current project, the two output layers (buffer and raster buffer) will be loaded, since they are saved to the destinations entered by the user (or to temporary destinations if the user does not specify a destination). If a layer is created as output of an algorithm, it should be declared as such. Otherwise, you will not be able to properly use the algorithm in the modeler, since what is declared will not match what the algorithm really creates. You can return strings, numbers and more by specifying them in the result dictionary (as demonstrated for "NUMBEROFFEATURES"), but they should always be explicitly defined as outputs from your algorithm. We encourage algorithms to output as many useful values as possible, since these can be valuable for use in later algorithms when your algorithm is used as part of a model. Communicating with the user --------------------------- If your algorithm takes a long time to process, it is a good idea to inform the user about the progress. You can use ``feedback`` (:class:`QgsProcessingFeedback `) for this. The progress text and progressbar can be updated using two methods: :meth:`setProgressText(text) ` and :meth:`setProgress(percent) `. You can provide more information to the user using :meth:`pushCommandInfo(text) `, :meth:`pushDebugInfo(text) `, :meth:`pushInfo(text) ` and :meth:`reportError(text) `. If your script has a problem, the correct way of handling it is to raise a :class:`QgsProcessingException `. You can pass a message as an argument to the constructor of the exception. Processing will take care of handling it and communicating with the user, depending on where the algorithm is being executed from (toolbox, modeler, Python console, ...) Documenting your scripts ------------------------ You can document your scripts by overloading the :meth:`helpString() ` and :meth:`helpUrl() ` methods of :class:`QgsProcessingAlgorithm `. Flags ----- You can override the :meth:`flags ` method of :class:`QgsProcessingAlgorithm ` to tell QGIS more about your algorithm. You can for instance tell QGIS that the script shall be hidden from the modeler, that it can be canceled, that it is not thread safe, and more. .. tip:: By default, Processing runs algorithms in a separate thread in order to keep QGIS responsive while the processing task runs. If your algorithm is regularly crashing, you are probably using API calls which are not safe to do in a background thread. Try returning the QgsProcessingAlgorithm.FlagNoThreading flag from your algorithm's flags() method to force Processing to run your algorithm in the main thread instead. Best practices for writing script algorithms -------------------------------------------- Here's a quick summary of ideas to consider when creating your script algorithms and, especially, if you want to share them with other QGIS users. Following these simple rules will ensure consistency across the different Processing elements such as the toolbox, the modeler or the batch processing interface. * Do not load resulting layers. Let Processing handle your results and load your layers if needed. * Always declare the outputs your algorithm creates. * Do not show message boxes or use any GUI element from the script. If you want to communicate with the user, use the methods of the feedback object (:class:`QgsProcessingFeedback `) or throw a :class:`QgsProcessingException `. There are already many processing algorithms available in QGIS. You can find code on :source:`python/plugins/processing/algs/qgis`.