This is a continuation of:
- #8db3dead87e385f2798356d
- #5c97d22b16320874dbe1
This commit only affects users that have multiple GRASS installations on
their Macs. Using the most recent GRASS version is what we do on Linux too.
Fixes a condition to enable Postgis provider insert optimization
(by skipping the PK column if its default is a sequence)
The check must ensure that each row value is also not the SQL
default of nextval('seq'::regclass), otherwise the condition will
not be met
After @Nyalldawson suggestion [1], we've implemented a Processing plugin
that exposes a GRASS Addon [2]. In order to do this we had to subclass
`Grass7AlgorithmProvider` and override `createAlgsList()`.
`createAlgsList()` had to be overriden in order to change the
"description folder" location.
Nyall wrote:
> And if you do it right (and only import existing
> processing grass code, minimising the copy/paste of this code), then
> your provider will automatically inherit any future fixes and
> features added to the main grass provider.
With this commit we convert the `descriptionFolder` to a class attribute
and in this way, subclasses of `Grass7AlgorithmProvider` will no longer
have to override `createAlgsList()` and will be able to continue inheriting
future enhancements.
References:
1. https://lists.osgeo.org/pipermail/qgis-developer/2019-February/056155.html
2. 948820b1c0/estimap_recreation_provider.py (L40-59)
This potentially avoids a second expensive feature request after
building a spatial index and later needing to re-request features
which match spatial index search.
It's non-default, as it requires the index to store all feature
geometries, so it's more memory expensive.
for return values where available
...instead of the older, server-specific properties
This affects:
- layer_property(...,'title')
- layer_property(...,'abstract')
- layer_property(...,'keywords')
- layer_property(...,'attribution')
configuration widget in modeler
Allows filters to be built (in the GUI) using context related variables
and functions such as input parameter values, model variables, etc
