add an explicit log level getter/setter to QgsProcessingContext which
algorithms can use to determine an appropriate level of feedback
to push to users.
Initially the verbose log only triggers the full verbose output
of model executions (which is also used when running models through
the model designer), but the intention is that more algorithms
will fine tune their output based on the logging level.
qgis_process also gains a new --verbose switch to enable verbose
log output.
When designing a model, users typically will need to run the model
many times as they tweak its structure.
This change causes the parameters used when running the model from
the designer to be remembered and saved into the model, so that
each time you run the model from the designer you don't have to
re-set all the input parameter values to the desired test ones.
Makes iterative model design SO much easier!
Sponsored by Alta Ehf
Only minimal shells of objects are left in Python now, the bare minimum
required because they call objects which depend on Python compatibility
for deprecated API calls...
to handle creation of parameter definition widgets
Previously, these configuration widgets were all hardcoded into the Python modeler
dialog. This prevented 3rd party, plugin provided, parameters from ever being full
first class citizens in QGIS, as there was no way to allow their use as inputs to
user created models to be customised.
Now, the registry is responsible for creating the configuration widget, allowing
for 3rd party parameter types to provide their own customised configuration
widgets.
Refs #26493
And add a Processing setting to allow these to be shown. When shown, they
are highlighted in red with a tooltip explaining that the algorithm
has known issues
This adds a new "Model Variables" dock panel to the model editor, allowing
users to create and set custom expression variables for use in the model.
These variables are available anywhere expressions are (correctly) evaluated
within the model, so can be used as input parameter values for child
algorithms, within data-defined dynamic parameters, etc.
The use case here is for models which use a constant value throughout
multiple steps within the model (e.g. @target_resolution: a target
raster resolution, @max_simplification: a simplification value for
input features coming from different sources, etc), allowing users
one single place to define and edit these constant values (instead
of hunting down and setting them in multiple places throughout the model).
These variables are stored within the model itself, and are not exposed
outside of the model designer dialog.
Brings back QGIS 2.18's ability to directly convert a Processing model
to an equivalent Processing Python script algorithm, correctly
updated and working in the 3.x API.
Available from the model dialog, and from the right-click context
menu on an existing model.
Sponsored by Solspec
