Fixes:
- enum parameters set to "allow multiple" only allow a single
value selection when used in modeler
- optional enum parameters cannot be set to no value when
used outside of modeler
Fixes#20406
Replace with just f[idx]. Calling QgsFeature.attributes()
allocates a list of all attributes, which is inefficient
when only a single attribute value is needed.
Include descriptive text with the specified parameter value
in error, and always check that sources were loaded to avoid
raw Python exceptions when they are not
Improvements:
- transparently handle different source/join CRS
- added option to create output feature for EVERY joined
feature (i.e. 1 to many type join)
- added option to select joined fields to take
- optimised performance of algorithm
The previous option to create a summary of joined features has been
removed, and will be moved to a separate 'Join by location (summary)'
algorithm.
Rationale:
- the correct use for this option is unclear, and users are
mistakenly using it as a 'tolerance' option
- it's very likely to generate invalid geometries as a result
of the snapping, causing unreliable results
Given these substantial issues, it's safer to remove this
option and require that users who need the snap to grid
precision change explicitly do this via an extra model
step before running the algorithm.
initAlgorithm() method
This allows 2 benefits:
- algorithms can be subclassed and have subclasses add additional
parameters/outputs to the algorithm. With the previous approach
of declaring parameters/outputs in the constructor, it's not
possible to call virtual methods to add additional parameters/
outputs (since you can't call virtual methods from a constructor).
- initAlgorithm takes a variant map argument, allowing the algorithm
to dynamically adjust its declared parameters and outputs according
to this configuration map. This potentially allows model algorithms which
can be configured to have variable numbers of parameters and
outputs at run time. E.g. a "router" algorithm which directs
features to one of any number of output sinks depending on some
user configured criteria.
Algorithms and other processing code should use this method
(instead of dataobjects.getLayerFromString) to
retrieve layers from a string, as it considers the processing
context and allows resolving strings to temporarily stored layers.
This permits processing models to function correctly when
intermediate results are stored as memory layers. Subsequent
model algorithms can then access these temporary layers as inputs.
All temporary layers will be removed when the context object
is destroyed after the model algorithm is run.
Also
- simplify and add tests
- remove large memory leak (persistant store of all non-project layers)
- remove broken support for direct loading postgres/virtual layers
by string (Python version was very broken and would never match
a postgres/virtual layer)
