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)
This adds a new input type for expression inputs. Expression
inputs can be linked to a parent layer so that the builder
shows the correct fields and layer variables.
It's designed for two use cases:
1. to be used when an algorithm specifically requires an expression,
eg Select by Expression and Extract by Expression.
2. to be potentially used as a replacement input instead of string
or number literals in algorithms. Eg - if the simplify algorithm
tolerance parameter was replaced with an expression paremeter, then
this expression would be evaluated for every feature before
simplifying that feature. It would allow parameters to be calculated
per feature, as opposed to the current approach of calculating
a parameter once before running the algorithm. It would also
mean algorithms like "variable distance buffer" would no longer
be needed, as a single "buffer" algorithm could then be used
for either a fixed distance, field based, or expression based
distance.
