Subgroup: Processing

Class: QgsProcessingModelAlgorithm¶

class qgis.core.QgsProcessingModelAlgorithm(name: str = '', group: str = '', groupId: str = '')¶

Bases: qgis._core.QgsProcessingAlgorithm

Constructor for QgsProcessingModelAlgorithm.

Model based algorithm with processing.

New in version 3.0: Methods

`activateChildAlgorithm`	Attempts to activate the child algorithm with matching `id`.
`addChildAlgorithm`	Adds a new child `algorithm` to the model.
`addModelParameter`	Adds a new parameter to the model, with the specified `definition` and graphical `component`.
`addOutput`
`addParameter`
`asPythonCode`	Attempts to convert the model to executable Python code.
`asPythonCommand`
`availableSourcesForChild`	Returns a list of possible sources which can be used for the parameters for a child algorithm in the model.
`canExecute`
`childAlgorithm`	Returns the child algorithm with matching `id`.
`childAlgorithms`	Returns the map of child algorithms contained in the model.
`childAlgorithmsDependOnParameter`	Returns true if any child algorithms depend on the model parameter with the specified `name`.
`createExpressionContextScopeForChildAlgorithm`	Creates a new expression context scope for a child algorithm within the model.
`createInstance`
`deactivateChildAlgorithm`	Deactivates the child algorithm with matching `id`.
`dependentChildAlgorithms`	Returns a list of the child algorithm IDs depending on the child algorithm with the specified `childId`.
`dependsOnChildAlgorithms`	Returns a list of the child algorithm IDs on which the child algorithm with the specified `childId` depends upon.
`displayName`
`flags`
`fromFile`	Reads the model from a file, at the specified `path`.
`group`
`groupId`
`helpContent`	Returns the model’s help contents (a free-form map of values describing the algorithm’s use and metadata).
`helpUrl`
`icon`
`initAlgorithm`
`name`
`otherParametersDependOnParameter`	Returns true if any other model parameters depend on the parameter with the specified `name` (e.
`parameterAsBool`
`parameterAsCompatibleSourceLayerPath`
`parameterAsCrs`
`parameterAsDouble`
`parameterAsEnum`
`parameterAsEnums`
`parameterAsExpression`
`parameterAsExtent`
`parameterAsExtentCrs`
`parameterAsExtentGeometry`
`parameterAsFields`
`parameterAsFile`
`parameterAsFileOutput`
`parameterAsInt`
`parameterAsLayer`
`parameterAsLayerList`
`parameterAsMatrix`
`parameterAsOutputLayer`
`parameterAsPoint`
`parameterAsPointCrs`
`parameterAsRange`
`parameterAsRasterLayer`
`parameterAsSink`
`parameterAsSource`
`parameterAsString`
`parameterAsVectorLayer`
`parameterComponent`	Returns the parameter component with matching `name`.
`parameterComponents`	Returns the map of parameter components used by the model.
`postProcessAlgorithm`
`prepareAlgorithm`
`processAlgorithm`
`removeChildAlgorithm`	Attempts to remove the child algorithm with matching `id`.
`removeModelParameter`	Removes an existing model parameter by `name`.
`removeParameter`
`setChildAlgorithm`	Sets the child `algorithm` within the model.
`setChildAlgorithms`	Sets the map of child algorithms contained in the model.
`setGroup`	Sets the model `group`.
`setHelpContent`	Sets the model’s help `contents` (a free-form map of values describing the algorithm’s use and metadata).
`setName`	Sets the model `name`.
`setParameterComponent`	Sets a parameter `component` for the model.
`setParameterComponents`	Sets the map of parameter components used by the model.
`setSourceFilePath`	Sets the source file `path` for the model, if available.
`shortHelpString`
`sourceFilePath`	Returns the source file path for the model, if available.
`svgIconPath`
`toFile`	Writes the model to a file, at the specified `path`.
`updateDestinationParameters`	Updates the model’s parameter definitions to include all relevant destination parameters as required by child algorithm ModelOutputs.
`updateModelParameter`	Replaces the definition of an existing parameter (by parameter name) with a new `definition`.
`variablesForChildAlgorithm`	Returns a map of variable name to variable definition for expression context variables which are available for use by child algorithm during model execution.

Signals

Attributes

class VariableDefinition(value: Any = None, source: QgsProcessingModelChildParameterSource = QgsProcessingModelChildParameterSource.fromStaticValue(QVariant()), description: str = '')¶

Bases: sip.wrapper

Constructor for a new VariableDefinition with the specified value and original parameter source, and description.

QgsProcessingModelAlgorithm.VariableDefinition(QgsProcessingModelAlgorithm.VariableDefinition)

Definition of a expression context variable available during model execution.

New in version 3.0.

description¶

source¶

value¶

activateChildAlgorithm(self, id: str) → bool¶: Attempts to activate the child algorithm with matching id. If any child algorithms on which the child depends are not active, then the child will not be activated and false will be returned.

See also

deactivateChildAlgorithm()

addChildAlgorithm(self, algorithm: QgsProcessingModelChildAlgorithm) → str¶: Adds a new child algorithm to the model. If a child algorithm already exists in the model with the same child ID then algorithm will be assigned a new autogenerated unique ID. The assigned child ID will be returned.

See also

childAlgorithms()

See also

childAlgorithm()

See also

setChildAlgorithm()

See also

setChildAlgorithms()

addModelParameter(self, definition: QgsProcessingParameterDefinition, component: QgsProcessingModelParameter)¶: Adds a new parameter to the model, with the specified definition and graphical component. Ownership of definition is transferred to the model.

See also

updateModelParameter()

See also

removeModelParameter()

addOutput()¶

addParameter()¶

asPythonCode(self) → str¶: Attempts to convert the model to executable Python code.

asPythonCommand(self, parameters: Dict[str, Any], context: QgsProcessingContext) → str¶

availableSourcesForChild(self, childId: str, parameterTypes: Iterable[str] = [], outputTypes: Iterable[str] = [], dataTypes: Iterable[int] = []) → object¶: Returns a list of possible sources which can be used for the parameters for a child algorithm in the model. Returned sources are those which match either one of the specified parameterTypes (see QgsProcessingParameterDefinition.type() ) or on of the specified outputTypes (see QgsProcessingOutputDefinition.type() ). If specified, an optional list of dataTypes can be used to filter the returned sources to those with compatible data types for the parameter/outputs.

canExecute(self) → Tuple[bool, str]¶

childAlgorithm(self, id: str) → QgsProcessingModelChildAlgorithm¶: Returns the child algorithm with matching id. If no child algorithm exists with this ID a new algorithm will be added to the model and returned.

See also

addChildAlgorithm()

See also

childAlgorithms()

childAlgorithms(self) → object¶: Returns the map of child algorithms contained in the model. The keys are the child algorithm ids (see QgsProcessingModelAlgorithm.ChildAlgorithm.childId()).

See also

childAlgorithm()

See also

setChildAlgorithms()

See also

addChildAlgorithm()

childAlgorithmsDependOnParameter(self, name: str) → bool¶: Returns true if any child algorithms depend on the model parameter with the specified name.

See also

otherParametersDependOnParameter()

createExpressionContextScopeForChildAlgorithm(self, childId: str, context: QgsProcessingContext, modelParameters: Dict[str, Any] = QVariantMap(), results: Dict[str, Any] = QVariantMap()) → QgsExpressionContextScope¶: Creates a new expression context scope for a child algorithm within the model.

See also

variablesForChildAlgorithm()

createInstance(self) → QgsProcessingAlgorithm¶

deactivateChildAlgorithm(self, id: str)¶: Deactivates the child algorithm with matching id. All other child algorithms which depend on the child algorithm will also be deactivated.

See also

removeChildAlgorithm()

See also

activateChildAlgorithm()

dependentChildAlgorithms(self, childId: str) → Set[str]¶: Returns a list of the child algorithm IDs depending on the child algorithm with the specified childId.

See also

dependsOnChildAlgorithms()

dependsOnChildAlgorithms(self, childId: str) → Set[str]¶: Returns a list of the child algorithm IDs on which the child algorithm with the specified childId depends upon.

See also

dependentChildAlgorithms()

displayName(self) → str¶

flags(self) → QgsProcessingAlgorithm.Flags¶

fromFile(self, path: str) → bool¶: Reads the model from a file, at the specified path.

See also

toFile()

group(self) → str¶

groupId(self) → str¶

helpContent(self) → Dict[str, Any]¶: Returns the model’s help contents (a free-form map of values describing the algorithm’s use and metadata).

See also

setHelpContent()

helpUrl(self) → str¶

icon(self) → QIcon¶

initAlgorithm(self, configuration: Dict[str, Any] = QVariantMap())¶

name(self) → str¶

otherParametersDependOnParameter(self, name: str) → bool¶: Returns true if any other model parameters depend on the parameter with the specified name (e.g. field parameters where name is the parent layer parameter).

See also

childAlgorithmsDependOnParameter()

parameterAsBool()¶

parameterAsCompatibleSourceLayerPath()¶

parameterAsCrs()¶

parameterAsDouble()¶

parameterAsEnum()¶

parameterAsEnums()¶

parameterAsExpression()¶

parameterAsExtent()¶

parameterAsExtentCrs()¶

parameterAsExtentGeometry()¶

parameterAsFields()¶

parameterAsFile()¶

parameterAsFileOutput()¶

parameterAsInt()¶

parameterAsLayer()¶

parameterAsLayerList()¶

parameterAsMatrix()¶

parameterAsOutputLayer()¶

parameterAsPoint()¶

parameterAsPointCrs()¶

parameterAsRange()¶

parameterAsRasterLayer()¶

parameterAsSink()¶

parameterAsSource()¶

parameterAsString()¶

parameterAsVectorLayer()¶

parameterComponent(self, name: str) → QgsProcessingModelParameter¶: Returns the parameter component with matching name. If no parameter component exists with this name a new component will be added to the model and returned.

See also

parameterComponents()

See also

setParameterComponents()

See also

setParameterComponent()

parameterComponents(self) → object¶: Returns the map of parameter components used by the model. The keys should match the algorithm’s parameter names (see parameterDefinitions() ).

See also

setParameterComponent()

See also

parameterComponent()

postProcessAlgorithm()¶

prepareAlgorithm()¶

processAlgorithm(self, parameters: Dict[str, Any], context: QgsProcessingContext, feedback: QgsProcessingFeedback) → Dict[str, Any]¶

removeChildAlgorithm(self, id: str) → bool¶: Attempts to remove the child algorithm with matching id. Returns true if the algorithm could be removed, or false if the algorithm could not be removed (e.g. due to other child algorithms depending on it).

See also

deactivateChildAlgorithm()

removeModelParameter(self, name: str)¶: Removes an existing model parameter by name. The definition of the matching parameter is deleted.

See also

addModelParameter()

See also

updateModelParameter()

removeParameter()¶

setChildAlgorithm(self, algorithm: QgsProcessingModelChildAlgorithm)¶: Sets the child algorithm within the model. If a child algorithm already exists in the model with the same child ID then that algorithm will be replaced.

See also

addChildAlgorithm()

See also

setChildAlgorithms()

setChildAlgorithms(self, childAlgorithms: Dict[str, QgsProcessingModelChildAlgorithm])¶: Sets the map of child algorithms contained in the model. The keys are the child algorithm ids (see QgsProcessingModelAlgorithm.ChildAlgorithm.childId()). All existing child algorithms will be replaced.

See also

childAlgorithms()

See also

childAlgorithm()

See also

setChildAlgorithm()

See also

addChildAlgorithm()

setGroup(self, group: str)¶: Sets the model group.

See also

group()

setHelpContent(self, contents: Dict[str, Any])¶: Sets the model’s help contents (a free-form map of values describing the algorithm’s use and metadata).

See also

helpContent()

setName(self, name: str)¶: Sets the model name.

See also

name()

setParameterComponent(self, component: QgsProcessingModelParameter)¶: Sets a parameter component for the model. If a parameter component already exists in the model with the same parameter name then that component will be replaced.

See also

parameterComponents()

See also

setParameterComponents()

See also

parameterComponent()

setParameterComponents(self, parameterComponents: Dict[str, QgsProcessingModelParameter])¶: Sets the map of parameter components used by the model. The keys should match the algorithm’s parameter names (see parameterDefinitions() ). All existing parameter components will be replaced.

See also

parameterComponents()

See also

setParameterComponent()

See also

parameterComponent()

setSourceFilePath(self, path: str)¶: Sets the source file path for the model, if available.

See also

sourceFilePath()

shortHelpString(self) → str¶

sourceFilePath(self) → str¶: Returns the source file path for the model, if available.

See also

setSourceFilePath()

svgIconPath(self) → str¶

toFile(self, path: str) → bool¶: Writes the model to a file, at the specified path.

See also

fromFile()

updateDestinationParameters(self)¶: Updates the model’s parameter definitions to include all relevant destination parameters as required by child algorithm ModelOutputs. Must be called whenever child algorithm ModelOutputs are altered.

updateModelParameter(self, definition: QgsProcessingParameterDefinition)¶: Replaces the definition of an existing parameter (by parameter name) with a new definition. Ownership of definition is transferred to the model, and any existing parameter is deleted.

See also

addModelParameter()

See also

removeModelParameter()

variablesForChildAlgorithm(self, childId: str, context: QgsProcessingContext, modelParameters: Dict[str, Any] = QVariantMap(), results: Dict[str, Any] = QVariantMap()) → object¶

Returns a map of variable name to variable definition for expression context variables which are available for use by child algorithm during model execution.

The child algorithm childId and processing context are manadatory. If modelParameters and results are not specified, then only the variable names and sources will be returned, but all variable values will be null. This can be used to determine in advance which variables will be available for a specific child algorithm, e.g. for use in expression builder widgets.

In order to calculate the actual variable value, the input model modelParameters and already executed child algorithm results must be passed.