Le portail francophone de la géomatique

from qgis.core import QgsProcessing
from qgis.core import QgsProcessingAlgorithm
from qgis.core import QgsProcessingMultiStepFeedback
from qgis.core import QgsProcessingParameterVectorLayer
from qgis.core import QgsProcessingParameterFeatureSource
from qgis.core import QgsProcessingParameterFeatureSink
import processing


class Modele_iteration(QgsProcessingAlgorithm):

    def initAlgorithm(self, config=None):
        self.addParameter(QgsProcessingParameterVectorLayer('total', 'Sortie "total" ', types=[QgsProcessing.TypeVectorPolygon], defaultValue='I:/user/DONNEES/temp/test_iteration_pyqgis/total.shp'))
        self.addParameter(QgsProcessingParameterFeatureSource('nonbati', 'Sortie "non bâti" ', types=[QgsProcessing.TypeVectorPolygon], defaultValue='I:/user/DONNEES/temp/test_iteration_pyqgis/nonbati.shp'))
        self.addParameter(QgsProcessingParameterFeatureSink('Sortie', 'sortie', type=QgsProcessing.TypeVectorAnyGeometry, createByDefault=True, defaultValue='I:/user/DONNEES/temp/test_iteration_pyqgis/test.shp'))

    def processAlgorithm(self, parameters, context, model_feedback):
        # Use a multi-step feedback, so that individual child algorithm progress reports are adjusted for the
        # overall progress through the model
        feedback = QgsProcessingMultiStepFeedback(1, model_feedback)
        results = {}
        outputs = {}
        
        features = parameters['nonbati'].getFeatures()
        
        for feature in features :
            
            # Tampon
            alg_params = {
                'DISSOLVE': False,
                'DISTANCE': 0.5,
                'END_CAP_STYLE': 0,
                'INPUT': f,
                'JOIN_STYLE': 0,
                'MITER_LIMIT': 2,
                'SEGMENTS': 5,
                'OUTPUT': parameters['Sortie']
            }
            outputs['Tampon'] = processing.run('native:buffer', alg_params, context=context, feedback=feedback, is_child_algorithm=True)
            results['Sortie'] = outputs['Tampon']['OUTPUT']
            return results

    def name(self):
        return 'modele_iteration'

    def displayName(self):
        return 'modele_iteration'

    def group(self):
        return 'modele'

    def groupId(self):
        return 'modele'

    def createInstance(self):
        return Modele_iteration()