Instead, parameters evaluate to QgsFeatureSource, which are
used for retrieving features, feature count, crs, wkb type,
etc.
This abstracts away the actual feature source, so that
algorithms may potentially operate from non-layer
feature sources.
It also helps remove the need for specialised QgsProcessingUtils
methods like getFeatures, featureCount, and createSpatialIndex.
Instead the standard API methods using QgsFeatureSources can
be used instead.
Rationale:
- there was a lot of large objects passed by value, so potentially
there's a speed bump from this
- even for implicitly shared classes like QString/QList there's still
a (small) cost for copying the objects when there's no reason to
- it's the right thing to do!
This is much faster way of initializing a spatial index. From python it is as simple as
>>> index = QgsSpatialIndex( layer.getFeatures() )
From a simple test with 50K points in a memory layer:
- bulk loading ~ 100 ms
- inserting features ~ 600 ms
The index tree should be in theory also better constructed and may result in faster lookups.
- update methods of existing classes
- add comment to methods missing in the sip bindings
- split up collective sip files into single files and use
same directory structure in python/ as in src/
- add a lot of missing classes (some might not make sense because of
missing python methods in those classes)
- remove some non-existing methods from the header files
- add scripts/sipdiff
- replace some usages of std::vector and std::set with QVector/QSet
