26.7. Using processing algorithms from the console
The console allows advanced users to increase their productivity and perform complex operations that cannot be performed using any of the other GUI elements of the processing framework. Models involving several algorithms can be defined using the command-line interface, and additional operations such as loops and conditional sentences can be added to create more flexible and powerful workflows.
There is not a processing console in QGIS, but all processing commands are available instead from the QGIS built-in Python console. That means that you can incorporate those commands into your console work and connect processing algorithms to all the other features (including methods from the QGIS API) available from there.
The code that you can execute from the Python console, even if it does not call any specific processing method, can be converted into a new algorithm that you can later call from the toolbox, the graphical modeler or any other component, just like you do with any other algorithm. In fact, some algorithms that you can find in the toolbox are simple scripts.
In this section, we will see how to use processing algorithms from the QGIS Python console, and also how to write algorithms using Python.
26.7.1. Calling algorithms from the Python console
The first thing you have to do is to import the processing functions with the following line:
>>> from qgis import processing
Now, there is basically just one (interesting) thing you can do with
that from the console: execute an algorithm. That is done using the
run() method, which
takes the name of the algorithm to execute
as its first parameter, and then a variable number of additional
parameters depending on the requirements of the algorithm. So the
first thing you need to know is the name of the algorithm to
execute. That is not the name you see in the toolbox, but rather a
unique command–line name. To find the right name for your algorithm,
you can use the processingRegistry.
Type the following line in your console:
>>> for alg in QgsApplication.processingRegistry().algorithms():
print(alg.id(), "->", alg.displayName())
You will see something like this (with some extra dashes added to improve readability).
3d:tessellate --------------> Tessellate
gdal:aspect ----------------> Aspect
gdal:assignprojection ------> Assign projection
gdal:buffervectors ---------> Buffer vectors
gdal:buildvirtualraster ----> Build Virtual Raster
gdal:cliprasterbyextent ----> Clip raster by extent
gdal:cliprasterbymasklayer -> Clip raster by mask layer
gdal:clipvectorbyextent ----> Clip vector by extent
gdal:clipvectorbypolygon ---> Clip vector by mask layer
gdal:colorrelief -----------> Color relief
gdal:contour ---------------> Contour
gdal:convertformat ---------> Convert format
gdal:dissolve --------------> Dissolve
...
That’s a list of all the available algorithm IDs, sorted by provider name and algorithm name, along with their corresponding names.
Once you know the command-line name of the algorithm, the next thing
to do is to determine the right syntax to execute it. That means
knowing which parameters are needed when calling the run() method.
There is a method to describe an algorithm in detail, which can be
used to get a list of the parameters that an algorithm requires and
the outputs that it will generate. To get this information, you can
use the algorithmHelp(id_of_the_algorithm) method. Use the ID of
the algorithm, not the full descriptive name.
Calling the method with native:buffer as parameter
(qgis:buffer is an alias for native:buffer and will also
work), you get the following description:
>>> processing.algorithmHelp("native:buffer")
Buffer (native:buffer)
This algorithm computes a buffer area for all the features in an
input layer, using a fixed or dynamic distance.
The segments parameter controls the number of line segments to
use to approximate a quarter circle when creating rounded
offsets.
The end cap style parameter controls how line endings are handled
in the buffer.
The join style parameter specifies whether round, miter or
beveled joins should be used when offsetting corners in a line.
The miter limit parameter is only applicable for miter join
styles, and controls the maximum distance from the offset curve
to use when creating a mitered join.
----------------
Input parameters
----------------
INPUT: Input layer
Parameter type: QgsProcessingParameterFeatureSource
Accepted data types:
- str: layer ID
- str: layer name
- str: layer source
- QgsProcessingFeatureSourceDefinition
- QgsProperty
- QgsVectorLayer
DISTANCE: Distance
Parameter type: QgsProcessingParameterDistance
Accepted data types:
- int
- float
- QgsProperty
SEGMENTS: Segments
Parameter type: QgsProcessingParameterNumber
Accepted data types:
- int
- float
- QgsProperty
END_CAP_STYLE: End cap style
Parameter type: QgsProcessingParameterEnum
Available values:
- 0: Round
- 1: Flat
- 2: Square
Accepted data types:
- int
- str: as string representation of int, e.g. '1'
- QgsProperty
JOIN_STYLE: Join style
Parameter type: QgsProcessingParameterEnum
Available values:
- 0: Round
- 1: Miter
- 2: Bevel
Accepted data types:
- int
- str: as string representation of int, e.g. '1'
- QgsProperty
MITER_LIMIT: Miter limit
Parameter type: QgsProcessingParameterNumber
Accepted data types:
- int
- float
- QgsProperty
DISSOLVE: Dissolve result
Parameter type: QgsProcessingParameterBoolean
Accepted data types:
- bool
- int
- str
- QgsProperty
OUTPUT: Buffered
Parameter type: QgsProcessingParameterFeatureSink
Accepted data types:
- str: destination vector file, e.g. 'd:/test.shp'
- str: 'memory:' to store result in temporary memory layer
- str: using vector provider ID prefix and destination URI,
e.g. 'postgres:...' to store result in PostGIS table
- QgsProcessingOutputLayerDefinition
- QgsProperty
----------------
Outputs
----------------
OUTPUT: <QgsProcessingOutputVectorLayer>
Buffered
Now you have everything you need to run any algorithm. As we have
already mentioned, algorithms can be run using: run().
Its syntax is as follows:
>>> processing.run(name_of_the_algorithm, parameters)
Where parameters is a dictionary of parameters that depend on the
algorithm you want to run, and is exactly the list that the
algorithmHelp() method gives you.
1 >>> processing.run("native:buffer", {'INPUT': '/data/lines.shp',
2 'DISTANCE': 100.0,
3 'SEGMENTS': 10,
4 'DISSOLVE': True,
5 'END_CAP_STYLE': 0,
6 'JOIN_STYLE': 0,
7 'MITER_LIMIT': 10,
8 'OUTPUT': '/data/buffers.shp'})
If a parameter is optional and you do not want to use it, then don’t include it in the dictionary.
If a parameter is not specified, the default value will be used.
Depending on the type of parameter, values are introduced differently. The next list gives a quick review of how to introduce values for each type of input parameter:
Raster Layer, Vector Layer or Table. Simply use a string with the name that identifies the data object to use (the name it has in the QGIS Table of Contents) or a filename (if the corresponding layer is not opened, it will be opened but not added to the map canvas). If you have an instance of a QGIS object representing the layer, you can also pass it as parameter.
Enumeration. If an algorithm has an enumeration parameter, the value of that parameter should be entered using an integer value. To know the available options, you can use the
algorithmHelp()command, as above. For instance, thenative:bufferalgorithm has an enumeration called JOIN_STYLE:JOIN_STYLE: Join style Parameter type: QgsProcessingParameterEnum Available values: - 0: Round - 1: Miter - 2: Bevel Accepted data types: - int - str: as string representation of int, e.g. '1' - QgsProperty
In this case, the parameter has three options. Notice that ordering is zero-based.
Boolean. Use
TrueorFalse.Multiple input. The value is a string with input descriptors separated by semicolons (
;). As in the case of single layers or tables, each input descriptor can be the data object name, or its file path.Table Field from XXX. Use a string with the name of the field to use. This parameter is case-sensitive.
Fixed Table. Type the list of all table values separated by commas (
,) and enclosed between quotes ("). Values start on the upper row and go from left to right. You can also use a 2-D array of values representing the table.CRS. Enter the EPSG code number of the desired CRS.
Extent. You must use a string with
xmin,xmax,yminandymaxvalues separated by commas (,).
Boolean, file, string and numerical parameters do not need any additional explanations.
Input parameters such as strings, booleans, or numerical values have default values. The default value is used if the corresponding parameter entry is missing.
For output data objects, type the file path to be used to save it, just as it is done from the toolbox. If the output object is not specified, the result is saved to a temporary file (or skipped if it is an optional output). The extension of the file determines the file format. If you enter a file extension not supported by the algorithm, the default file format for that output type will be used, and its corresponding extension appended to the given file path.
Unlike when an algorithm is executed from the toolbox, outputs are not
added to the map canvas if you execute that same algorithm from the
Python console using run(),
but runAndLoadResults() will do that.
The run() method returns
a dictionary with one or more output names (the
ones shown in the algorithm description) as keys and the file paths of
those outputs as values:
1 >>> myresult = processing.run("native:buffer", {'INPUT': '/data/lines.shp',
2 'DISTANCE': 100.0,
3 'SEGMENTS': 10,
4 'DISSOLVE': True,
5 'END_CAP_STYLE': 0,
6 'JOIN_STYLE': 0,
7 'MITER_LIMIT': 10,
8 'OUTPUT': '/data/buffers.shp'})
9 >>> myresult['OUTPUT']
10 /data/buffers.shp
You can load feature output by passing the corresponding file paths to
the load() method.
Or you could use runAndLoadResults() instead of
run() to load
them immediately.
If you want to open an algorithm dialog from the console you can use the
createAlgorithmDialog method. The only mandatory parameter is the algorithm
name, but you can also define the dictionary of parameters so that the dialog
will be filled automatically:
1 >>> my_dialog = processing.createAlgorithmDialog("native:buffer", {
2 'INPUT': '/data/lines.shp',
3 'DISTANCE': 100.0,
4 'SEGMENTS': 10,
5 'DISSOLVE': True,
6 'END_CAP_STYLE': 0,
7 'JOIN_STYLE': 0,
8 'MITER_LIMIT': 10,
9 'OUTPUT': '/data/buffers.shp'})
10 >>> my_dialog.show()
The execAlgorithmDialog method opens the dialog immediately:
1 >>> processing.execAlgorithmDialog("native:buffer", {
2 'INPUT': '/data/lines.shp',
3 'DISTANCE': 100.0,
4 'SEGMENTS': 10,
5 'DISSOLVE': True,
6 'END_CAP_STYLE': 0,
7 'JOIN_STYLE': 0,
8 'MITER_LIMIT': 10,
9 'OUTPUT': '/data/buffers.shp'})
26.7.2. Creating scripts and running them from the toolbox
You can create your own algorithms by writing Python code.
Processing scripts extend
QgsProcessingAlgorithm, so you
need to add some extra lines of code to implement mandatory functions.
You can find Create new script (clean sheet) and
Create New Script from Template (template that includes
code for mandatory functions of
QgsProcessingAlgorithm) under
the Scripts dropdown menu on the top of the Processing toolbox.
The Processing Script Editor will open, and that’s where you should type
your code.
Saving the script from there in the scripts folder (the default folder
when you open the save file dialog) with a .py extension should
create the corresponding algorithm.
The name of the algorithm (the one you will see in the toolbox) is defined within the code.
Let’s have a look at the following code, which defines a Processing algorithm that performs a buffer operation with a user defined buffer distance on a vector layer that is specified by the user, after first smoothing the layer.
1from qgis.core import (QgsProcessingAlgorithm,
2 QgsProcessingParameterNumber,
3 QgsProcessingParameterFeatureSource,
4 QgsProcessingParameterFeatureSink)
5
6from qgis import processing
7
8class algTest(QgsProcessingAlgorithm):
9 INPUT_BUFFERDIST = 'BUFFERDIST'
10 OUTPUT_BUFFER = 'OUTPUT_BUFFER'
11 INPUT_VECTOR = 'INPUT_VECTOR'
12
13 def __init__(self):
14 super().__init__()
15
16 def name(self):
17 return "algTest"
18
19 def displayName(self):
20 return "algTest script"
21
22 def createInstance(self):
23 return type(self)()
24
25 def initAlgorithm(self, config=None):
26 self.addParameter(QgsProcessingParameterFeatureSource(
27 self.INPUT_VECTOR, "Input vector"))
28 self.addParameter(QgsProcessingParameterNumber(
29 self.INPUT_BUFFERDIST, "Buffer distance",
30 QgsProcessingParameterNumber.Double,
31 100.0))
32 self.addParameter(QgsProcessingParameterFeatureSink(
33 self.OUTPUT_BUFFER, "Output buffer"))
34
35 def processAlgorithm(self, parameters, context, feedback):
36 #DO SOMETHING
37 algresult = processing.run("native:smoothgeometry",
38 {'INPUT': parameters[self.INPUT_VECTOR],
39 'ITERATIONS':2,
40 'OFFSET':0.25,
41 'MAX_ANGLE':180,
42 'OUTPUT': 'memory:'},
43 context=context, feedback=feedback, is_child_algorithm=True)
44 smoothed = algresult['OUTPUT']
45 algresult = processing.run('native:buffer',
46 {'INPUT': smoothed,
47 'DISTANCE': parameters[self.INPUT_BUFFERDIST],
48 'SEGMENTS': 5,
49 'END_CAP_STYLE': 0,
50 'JOIN_STYLE': 0,
51 'MITER_LIMIT': 10,
52 'DISSOLVE': True,
53 'OUTPUT': parameters[self.OUTPUT_BUFFER]},
54 context=context, feedback=feedback, is_child_algorithm=True)
55 buffered = algresult['OUTPUT']
56 return {self.OUTPUT_BUFFER: buffered}
After doing the necessary imports, the following
QgsProcessingAlgorithm
functions are specified:
name(): The id of the algorithm (lowercase).displayName(): A human readable name for the algorithm.createInstance(): Create a new instance of the algorithm class.initAlgorithm(): Configure the parameterDefinitions and outputDefinitions.Here you describe the parameters and output of the algorithm. In this case, a feature source for the input, a feature sink for the result and a number for the buffer distance.
processAlgorithm(): Do the work.Here we first run the
smoothgeometryalgorithm to smooth the geometry, and then we run thebufferalgorithm on the smoothed output. To be able to run algorithms from within another algorithm we have to set theis_child_algorithmargument toTrue. You can see how input and output parameters are used as parameters to thesmoothgeometryandbufferalgorithms.
There are a number of different parameter types available for input and output. Below is an alphabetically sorted list:
The first parameter to the constructors is the name of the parameter, and the second is the description of the parameter (for the user interface). The rest of the constructor parameters are parameter type specific.
The input can be turned into QGIS classes using the parameterAs functions
of QgsProcessingAlgorithm.
For instance to get the number provided for the buffer distance as a double:
self.parameterAsDouble(parameters, self.INPUT_BUFFERDIST, context)).
The processAlgorithm function should return a dictionary
containing values for every output defined by the algorithm. This
allows access to these outputs from other algorithms, including other
algorithms contained within the same model.
Well behaved algorithms should define and return as many outputs as makes sense. Non-feature outputs, such as numbers and strings, are very useful when running your algorithm as part of a larger model, as these values can be used as input parameters for subsequent algorithms within the model. Consider adding numeric outputs for things like the number of features processed, the number of invalid features encountered, the number of features output, etc. The more outputs you return, the more useful your algorithm becomes!
26.7.2.1. Feedback
The feedback object passed to
processAlgorithm()
should be used for user feedback / interaction.
You can use the setProgress()
function of the feedback object to update
the progress bar (0 to 100) to inform the user about the progress of the
algorithm. This is very useful if your algorithm takes a long time to complete.
The feedback object provides an
isCanceled() method that
should be monitored to enable cancelation of the algorithm by the user.
The pushInfo() method of
feedback can be used to send information
to the user, and reportError()
is handy for pushing non-fatal errors to users.
Algorithms should avoid using other forms of providing feedback to
users, such as print statements or logging to
QgsMessageLog, and
should always use the feedback object instead. This allows verbose
logging for the algorithm, and is also thread-safe (which is
important, given that algorithms are typically run in a background
thread).
26.7.2.2. Handling errors
If your algorithm encounters an error which prevents it from
executing, such as invalid input values or some other condition from
which it cannot or should not recover, then you should raise a
QgsProcessingException.
E.g.:
if feature['value'] < 20:
raise QgsProcessingException('Invalid input value {}, must be >= 20'.format(feature['value']))
Try to avoid raising
QgsProcessingException for
non-fatal errors
(e.g. when a feature has a null geometry), and instead just report
these errors via feedback.reportError() and skip the feature. This
helps make your algorithm „model-friendly”, as it avoids halting the
execution of an entire algorithm when a non-fatal error is
encountered.
26.7.2.3. Documenting your scripts
As in the case of models, you can create additional documentation for your scripts, to explain what they do and how to use them.
QgsProcessingAlgorithm
provides the helpString(),
shortHelpString() and
helpUrl() functions for that purpose.
Specify / override these to provide more help to the user.
shortDescription()
is used in the tooltip when hovering over the algorithm in the toolbox.
26.7.3. Pre- and post-execution script hooks
Scripts can also be used as pre- and post-execution hooks that are run before and after an algorithm is run, respectively. This can be used to automate tasks that should be performed whenever an algorithm is executed.
The syntax is identical to the syntax explained above, but an additional global
variable named alg is available, representing the algorithm that has just
been (or is about to be) executed.
In the General group of the processing options dialog, you will find two entries named Pre-execution script and Post-execution script where the filenames of the scripts to be run in each case can be entered.