23.5. The model designer

The model designer allows you to create complex models using a simple and easy-to-use interface. When working with a GIS, most analysis operations are not isolated, rather part of a chain of operations. Using the model designer, that chain of operations can be wrapped into a single process, making it convenient to execute later with a different set of inputs. No matter how many steps and different algorithms it involves, a model is executed as a single algorithm, saving time and effort.

The model designer can be opened from the Processing menu (Processing ► Model Designer).

23.5.1. The model designer interface 

../../../_images/modeler_canvas.png

Fig. 23.18 Model designer

In its main part, the modeler has a working canvas where the structure of the model and the workflow it represents can be constructed.

At the top of the dialog, different menus and the Navigation toolbar give access to a variety of tools.

23.5.1.1. Model menu 

Label	Shortcut	Navigation Toolbar	Description
success Validate Model	Checks whether the algorithms and inputs used in the model exist. Convenient before releasing a model.
play Run Model...	`F5`	checkbox	Executes the model
runSelected Run Selected Steps...	`Shift+F5`	Runs only the selected steps in a model, allowing to run a subset of the model
Reorder Model Inputs...	Sets the order in which inputs are presented to the user in the algorithm dialog.
Reorder Output Layers...	Sets a specific order which the outputs from the model must use when loading the results into a project.
fileOpen Open Model...	`Ctrl+O`	checkbox	Opens a `.model3` file for edit or execution
fileSave Save Model	`Ctrl+S`	checkbox	Saves the model to disk as a `.model3` file
fileSaveAs Save Model as...	`Ctrl+Shift+S`	checkbox	Saves the model to disk as a new `.model3` file
fileSave Save Model in project	checkbox	Embeds the model file in the project file, making it available when sharing the project file.
helpContents Edit Model Help...	checkbox	An interface to document the model, the algorithms, the parameters and outputs, as well as the author and versioning
Export ►
saveMapAsImage ► Export as Image...	checkbox	Saves the model’s graphical design to an image file format (for illustration purpose)
saveAsPDF ► Export as PDF...	Saves the model’s graphical design to a `PDF` file format (for illustration purpose)
saveAsSVG ► Export as SVG...	Saves the model’s graphical design to an `SVG` file format (for illustration purpose)
fileSave ► Export as Script Algorithm...	checkbox	Generates a python script file including the model’s instructions

23.5.1.2. Edit menu 

Label	Shortcut	Navigation Toolbar	Description
selectAll Select All	`Ctrl+A`	Selects all the model components in the designer
Snap selected components to Grid	snaps and aligns the elements into a grid
redo Redo	`Ctrl+Y`	checkbox	Rollback the latest canceled action. See also the Undo/Redo panel.
undo Undo	`Ctrl+Z`	checkbox	Cancel the previous change. See also the Undo/Redo panel.
editCut Cut	`Ctrl+X`	Cuts a selection of components from the model.
editCopy Copy	`Ctrl+C`	Copies a selection of components from the model.
editPaste Paste	`Ctrl+V`	Pastes a cut or copied selection of components from a model to another or within the same model. The selected components keep their original properties and comments.
deleteSelected Delete selected components	`Del`	Removes a component from the model.
Add Group Box	Adds a box at the background of related components in order to visually group them. Particularly useful in big models to keep the workflow clean.

23.5.1.3. View menu 

Label	Shortcut	Navigation Toolbar	Description
Zoom To ►	Zooms to the selected group box extent
zoomIn Zoom In	`Ctrl++`	checkbox
zoomOut Zoom Out	`Ctrl+-`	checkbox
zoomActual Zoom to 100%	`Ctrl+1`	checkbox
zoomFullExtent Zoom Full	`Ctrl+0`	checkbox	Displays all the components in the designer current canvas
checkbox Show Comments	Displays comments associated to every algorithm or input in the model designer
unchecked Enable Snapping
unchecked Toggle Panel Visibility	`Ctrl+Tab`	Switches ON or OFF the panels in the designer

23.5.1.4. Panels 

The left part of the window is a section with five panels that can be used to add new elements to the model:

Model Properties: specify the name (required) of the model and the group in which it will be displayed in the Processing Toolbox
Inputs: all the input parameters that could shape your model
Algorithms: the available Processing algorithms
Variables: Models can contain dedicated variables that are unique and only available to them. These variables can be accessed by any expression used within the model. They are useful to control algorithms within a model and control multiple aspects of the model by changing a single variable. The variables can be viewed and modified in the Variables panel.
Undo History: this panel will register everything that happens in the modeler, making it easy to cancel things you did wrong.

23.5.1.5. About available algorithms 

Some algorithms that can be executed from the toolbox do not appear in the list of available algorithms when you are designing a model. To be included in a model, an algorithm must have the correct semantic. If an algorithm does not have such a well-defined semantic (for instance, if the number of output layers cannot be known in advance), then it is not possible to use it within a model, and it will not appear in the list of algorithms that you can find in the modeler dialog. On the other hand some algorithms are specific to the modeler. Those algorithms are located within the group ‘Modeler Tools’.

23.5.2. Creating a model 

Creating a model involves two basic steps:

Definition of necessary inputs. These inputs will be added to the parameters window, so the user can set their values when executing the model. The model itself is an algorithm, so the parameters window is generated automatically as for all algorithms available in the Processing framework.
Definition of the workflow. Using the input data of the model, the workflow is defined by adding algorithms and selecting how they use the defined inputs or the outputs generated by other algorithms in the model.

23.5.2.1. Definition of inputs 

The first step is to define the inputs for the model. They are found in the Inputs panel on the left side of the modeler window. Hovering with the mouse over the inputs will show a tooltip with additional information. For a full list of available parameters in modeler and their correspondance for scripting, please read Input and output types for Processing Algorithms.

When double-clicking on an element, a dialog is shown that lets you define its characteristics. Depending on the parameter, the dialog will contain at least one element (the description, which is what the user will see when executing the model). For example, when adding a numerical value, as can be seen in the next figure, in addition to the description of the parameter, you have to set a default value and the range of valid values.

../../../_images/models_parameters.png

Fig. 23.19 Model Parameters Definition

You can define your input as mandatory for your model by checking the checkbox Mandatory option and by checking the unchecked Advanced checkbox you can set the input to be within the Advanced section. This is particularly useful when the model has many parameters and some of them are not trivial, but you still want to choose them.

For each added input, a new element is added to the modeler canvas.

../../../_images/models_parameters2.png

Fig. 23.20 Model Parameters

You can also add inputs by dragging the input type from the list and dropping it at the position where you want it in the modeler canvas. If you want to change a parameter of an existing input, just double click on it, and the same dialog will pop up.

When using a model within another model, the inputs and outputs necessary will be displayed in the canvas.

23.5.2.2. Definition of the workflow 

In the following example we will add two inputs and two algorithms. The aim of the model is to copy the elevation values from a DEM raster layer to a line layer using the Drape algorithm, and then calculate the total ascent of the line layer using the Climb Along Line algorithm.

In the Inputs tab, choose the two inputs as Vector Layer for the line and Raster Layer for the DEM. We are now ready to add the algorithms to the workflow.

Algorithms can be found in the Algorithms panel, grouped much in the same way as they are in the Processing toolbox.

../../../_images/models_parameters3.png

Fig. 23.21 Model Inputs

To add an algorithm to a model, double-click on its name or drag and drop it, just like for inputs. As for the inputs you can change the description of the algorithm and add a comment. When adding an algorithm, an execution dialog will appear, with a content similar to the one found in the execution panel that is shown when executing the algorithm from the toolbox. The following picture shows both the Drape (set Z value from raster) and the Climb along line algorithm dialogs.

../../../_images/models_parameters4.png

Fig. 23.22 Model Algorithm parameters

As you can see, there are however some differences. Each parameter has a drop-down menu next to it allowing to control how it will be served during the workflow:

fieldInteger ^Value: allows you to assign a static value to the parameter. Depending on the parameter type, the widget will let you enter a number (5.0), a string (mytext), select layer(s) loaded in the QGIS project or from a folder, pick items from a list, ...
expression ^{Pre-calculated Value}: opens the Expression Builder dialog and lets you define an expression to fill the parameter. Model inputs together with some other layer statistics are available as variables and are listed at the top of the Search dialog of the Expression Builder. The expression is evaluated once before the child algorithm is executed and used during the execution of that algorithm.
processingModel ^{Model Input}: allows to use an input added to the model as a parameter. Once clicked, this option will list all the suitable inputs for the parameter.
processingAlgorithm ^{Algorithm Output}: allows to use the output of another algorithm as an input of the current algorithm. As of model inputs, this option will list all the suitable inputs for the parameter.
The output parameter also has the above options in its drop-down menu:
- add static outputs for child algorithms, e.g. always saving a child algorithm’s output to a predefined geopackage or postgres layer
- use an expression based output values for child algorithms, e.g. generating an automatic file name based on today’s date and saving outputs to that file
- use a model input, e.g. the File/Folder model input to specify an output file or folder
- use another algorithm output, e.g. the output of the Create directory algorithm (from Modeler tools)
- an addditional modelOutput ^{Model Output} option makes the output of the algorithm available in the model. If a layer generated by the algorithm is only to be used as input to another algorithm, don’t edit that text box.
In the following picture you can see the two input parameters defined as Model Input and the temporary output layer:

../../../_images/models_parameters5.png

Fig. 23.23 Algorithm Input and Output parameters

You will also find an additional parameter named Dependencies that is not available when calling the algorithm from the toolbox. This parameter allows you to define the order in which algorithms are executed, by explicitly defining one algorithm as a parent of the current one. This will force the parent algorithm to be executed before the current one.

When you use the output of a previous algorithm as the input of your algorithm, that implicitly sets the previous algorithm as parent of the current one (and places the corresponding arrow in the modeler canvas). However, in some cases an algorithm might depend on another one even if it does not use any output object from it (for instance, an algorithm that executes a SQL sentence on a PostGIS database and another one that imports a layer into that same database). In that case, just select the previous algorithm in the Dependencies parameter and they will be executed in the correct order.

Once all the parameters have been assigned valid values, click on OK and the algorithm will be added to the canvas. It will be linked to the elements in the canvas (algorithms or inputs) that provide objects that are used as inputs for the algorithm.

Elements can be dragged to a different position on the canvas using the select ^{Select/Move Item} tool. This is useful to make the structure of the model clearer and more intuitive. You can also resize the elements, grasping their border. This is particularly useful if the description of the input or algorithm is long. With View ► Enable snapping option checked, items resizing or displacement can be bound to a virtual grid, for a more visually structured algorithm design.

Links between elements are updated automatically and you can see a + button at the top and at the bottom of each algorithm. Clicking the button will list all the inputs and outputs of the algorithm so you can have a quick overview.

../../../_images/models_model.png

Fig. 23.24 A complete model

With the Edit ► Add Group Box tool, you can add a draggable box to the canvas. This feature is very useful in big models to group related elements in the modeler canvas and to keep the workflow clean. For example we might group together all the inputs of the example:

../../../_images/model_group_box.png

Fig. 23.25 Model Group Box

You can change the name and the color of the boxes. Group boxes are very useful when used together with View ► Zoom To ► tool, allowing you to zoom to a specific part of the model. You can also zoom in and out by using the mouse wheel.

You might want to change the order of the inputs and how they are listed in the main model dialog. At the bottom of the Input panel you will find the Reorder Model Inputs... button and by clicking on it a new dialog pops up allowing you to change the order of the inputs:

../../../_images/model_reorder_inputs.png

Fig. 23.26 Reorder Model Inputs

There is also the possibility to set a specific order which the outputs from the model must use when loading the results into a project. This gives the model creator a means of ensuring that layers are logically ordered on the canvas when running a model, such as placing a vector layer output over a raster layer output, or a point layer over a polygon layer. The model creator can also set an optional "Group name" for the outputs for automatically grouping outputs within the layer tree using a new group name or by adding them to an existing group. In the Model menu you will find the Reorder Output Layers... entry and by clicking on it a new dialog pops up allowing you to change the order of the output layers:

../../../_images/model_reorder_output_layers.png

Fig. 23.27 Reorder Output Layers

Comments can also be added to inputs or algorithms present in the modeler. This can be done by going in the Comment tab of the item or with a right-click. In the same tab a color can be set manual for individual model comments. Comments are visible only in the modeler canvas and not in the final algorithm dialog; they can be hidden by deactivating View ► Show Comments.

Your model can be run in various ways:

You can run the whole model by clicking on start ^{Run Model...} from the toolbar, right-clicking on the model in the Browser panel or Model ► start Run Model...: when using the editor to execute a model, any non-default values will be saved in the inputs. This means that executing the model at a later time from the editor will have the dialog prefilled with those values on any subsequent run.
You can select elements of the model and run only that subset of the model: press the runSelected Run Selected Steps... option from the Models ► menu or from the contextual menu of a selected algorithm. The initial state will be taken from any previous executions of the model through the editor, so results from previous steps in the model are available for the selected steps. This makes it possible to fix parts of a large model, without having to constantly run the entire model to test. Especially useful when earlier steps in the model are time consuming.
You can run a subset of the model, starting from a specific algorithm: right-click the algorithm and select start Run from Here.... Likewise, values are taken from previous executions.
In order to use the algorithm from the Processing Toolbox, it has to be saved and the modeler dialog closed, to allow the toolbox to refresh its contents.

23.5.2.3. Documenting your model 

You need to document your model, and this can be done from the modeler itself. Click on the editHelpContent ^{Edit model help} button, and a dialog like the one shown next will appear.

../../../_images/help_edition.png

Fig. 23.28 Editing Help

On the right-hand side, you will see a simple HTML page, created using the description of the input parameters and outputs of the algorithm, along with some additional items like a general description of the model or its author. Also, there is an Example section where you can input your own custom examples to help explain the usage of the model. The first time you open the help editor, all these descriptions are empty, but you can edit them using the elements on the left-hand side of the dialog. Select an element on the upper part and then write its description in the text box below.

Model help is saved as part of the model itself.

23.5.3. Saving and loading models 

23.5.3.1. Saving models 

Use the fileSave ^{Save model} button to save the current model and the fileOpen ^{Open Model} button to open a previously saved model. Models are saved with the .model3 extension. If the model has already been saved from the modeler window, you will not be prompted for a filename. Since there is already a file associated with the model, that file will be used for subsequent saves.

Before saving a model, you have to enter a name and a group for it in the text boxes in the upper part of the window.

Models saved in the models folder (the default folder when you are prompted for a filename to save the model) will appear in the toolbox in the corresponding branch. When the toolbox is invoked, it searches the models folder for files with the .model3 extension and loads the models they contain. Since a model is itself an algorithm, it can be added to the toolbox just like any other algorithm.

Models can also be saved within the project file using the addToProject ^{Save model in project} button. Models saved using this method won’t be written as .model3 files on the disk but will be embedded in the project file.

Project models are available in the qgsProjectFile Project models menu of the toolbox and in the Project ► Models menu item.

The models folder can be set from the Processing configuration dialog, under the Modeler group.

Models loaded from the models folder appear not only in the toolbox, but also in the algorithms tree in the Algorithms tab of the modeler window. That means that you can incorporate a model as a part of a bigger model, just like other algorithms.

Models will show up in the Browser panel and can be run from there.

23.5.3.2. Exporting a model as a Python script 

As we will see in a later chapter, Processing algorithms can be called from the QGIS Python console, and new Processing algorithms can be created using Python. A quick way to create such a Python script is to create a model and then export it as a Python file.

To do so, click on the saveAsPython ^{Export as Script Algorithm...} in the modeler canvas or right click on the name of the model in the Processing Toolbox and choose saveAsPython ^{Export Model as Python Algorithm...}.

23.5.3.3. Exporting a model as an image, PDF or SVG 

A model can also be exported as an image, SVG or PDF (for illustration purposes) by clicking saveMapAsImage ^{Export as image}, saveAsPDF ^{Export as PDF} or saveAsSVG ^{Export as SVG}.

23.5.4. Editing a model 

You can edit the model you are currently creating, redefining the workflow and the relationships between the algorithms and inputs that define the model.

You can also edit existing model from the Browser panel choosing Edit Model... option.

If you right-click on an algorithm in the canvas, you will see a context menu like the one shown next:

../../../_images/modeler_right_click.png

Fig. 23.29 Modeler Right Click

Options for running part of the model have been exposed earlier.
Selecting the Remove option will cause the selected algorithm to be removed. An algorithm can be removed only if there are no other algorithms depending on it. That is, if no output from the algorithm is used as input in a different one.
Selecting the Edit... option will show the parameter dialog so you can change the inputs and parameter values. Not all input elements available in the model will appear as available inputs. Layers or values generated at a more advanced step in the workflow defined by the model will not be available if they cause circular dependencies.

Select the new values and click on the OK button as usual. The connections between the model elements will change in the modeler canvas accordingly.
The Add comment... allows you to add a comment to the algorithm to better describe the behavior.

Note

Right-clicking an input parameter will also allow you to Remove, Edit... and Add comment...

A model can be run partially by deactivating some of its algorithms. To do it, select the Deactivate option in the context menu that appears when right-clicking on an algorithm element. The selected algorithm, and all the ones in the model that depend on it will be displayed in grey and will not be executed as part of the model.

../../../_images/deactivated.png

Fig. 23.30 Model with a deactivated algorithm

When right-clicking on an algorithm that is not active, you will see an Activate menu option that you can use to reactivate it.
When editing a model through the designer (and after having run that model), right-clicking any child step in the model allows to select showSelectedLayers View Output Layers. This will add the output layers from that step as new layers in the current QGIS project.

This action is available for all child algorithms in the model, even if the model is not configured to use the outputs from those children as model outputs. This is designed as a helpful debugging action. If a model fails (or gives unexpected results), you can then trace through the model and view the outputs for suspected problematic steps. It avoids the need to add temporary outputs to a model and re-run to test.

Additionally, this action is always available after running the model, even if the model itself failed (e.g., because of a misconfigured step later in the model).
The View Log action helps you see the log for each child algorithm after you’ve closed down the algorithm dialog.