Runs an algorithm using 'qgis_process'. See the QGIS docs for a detailed description of the algorithms provided 'out of the box' on QGIS.
Usage
qgis_run_algorithm(
algorithm,
...,
PROJECT_PATH = NULL,
ELLIPSOID = NULL,
.raw_json_input = NULL,
.quiet = TRUE
)
Arguments
- algorithm
A qualified algorithm name (e.g.,
"native:buffer"
) or a path to a QGIS model file.- ...
Named key-value pairs as arguments for the algorithm. Features of
rlang::list2()
are supported. These arguments are converted to strings usingas_qgis_argument()
.- PROJECT_PATH, ELLIPSOID
Global values for QGIS project file and ellipsoid name for distance calculations.
- .raw_json_input
The raw JSON to use as input in place of
...
. See Details section.- .quiet
Use
FALSE
to get extra output from 'qgis_process'. This can be useful in debugging.
Details
qgis_run_algorithm()
accepts various R objects as algorithm arguments.
An overview is given by vignette("qgis_arguments")
.
Examples include an R matrix or data frame for the
argument type 'matrix', R colors for the argument type 'color',
sf or terra (SpatVector) objects for the argument type 'vector' and
raster/terra/stars objects for the argument type 'raster', but there are many
more.
qgis_run_algorithm()
preprocesses the provided objects into the format that
QGIS expects for a given argument.
Providing R objects that cannot be converted to the applicable argument type will lead to an error.
Algorithm arguments can be passed as arguments of qgis_run_algorithm()
, but
they can also be combined as a JSON string and fed into the .raw_json_input
argument.
A JSON string can be obtained from the QGIS GUI, either from the
processing tool dialog or from the processing history dialog, by selecting
'Copy as JSON' in the 'Advanced' dropdown menu.
So a user can first try out a geoprocessing step in the QGIS GUI, and
once the chosen algorithm arguments are satisfactory, copy the JSON string
to reproduce the operation in R.
A screenshot is available at the package homepage.
Running QGIS models and Python scripts
QGIS models and Python scripts can be added to the Processing Toolbox in the
QGIS GUI, by pointing at their corresponding file.
This will put the model or script below the provider 'Models' or
'Scripts', respectively.
Next, it is necessary to run qgis_configure()
in R in order to make the
model or script available to qgisprocess (even reloading the package won't
detect it, since these providers have dynamic content, not tied to a
plugin or to a QGIS version).
You can check the outcome with qgis_providers()
and
qgis_search_algorithms()
.
Now, just as with other algorithms, you can provide the model:<name>
or
script:<name>
identifier to the algorithm
argument of
qgis_run_algorithm()
.
As the output argument name of a QGIS model can have an R-unfriendly
syntax, you may need to take the JSON parameter string from the QGIS
processing dialog and feed the JSON string to the .raw_json_input
argument
of qgis_run_algorithm()
instead of providing separate arguments.
Although the 'qgis_process' backend also supports replacing the 'algorithm' parameter by the file path of a model file or a Python script, it is not planned to implement this in qgisprocess, as it would bypass argument preprocessing in R (including checks).
See also
Other functions to run one geoprocessing algorithm:
qgis_run_algorithm_p()
Examples
qgis_run_algorithm(
"native:buffer",
INPUT = system.file("longlake/longlake_depth.gpkg", package = "qgisprocess"),
DISTANCE = 10
)
#> Argument `SEGMENTS` is unspecified (using QGIS default value).
#> Using `END_CAP_STYLE = "Round"`
#> Using `JOIN_STYLE = "Round"`
#> Argument `MITER_LIMIT` is unspecified (using QGIS default value).
#> Argument `DISSOLVE` is unspecified (using QGIS default value).
#> Argument `SEPARATE_DISJOINT` is unspecified (using QGIS default value).
#> Using `OUTPUT = qgis_tmp_vector()`
#> <Result of `qgis_run_algorithm("native:buffer", ...)`>
#> List of 1
#> $ OUTPUT: 'qgis_outputVector' chr "/tmp/Rtmp7nb1k0/file2b044d88ac6c/file2b04661b6f45.gpkg"