Datacage: Added <dc:filter> element. This allows cleaner way to narrow the datasets. Example: <dc:context> <dc:statement> SELECT DISTINCT name AS hws_name, official AS hws_official, kind_id AS hws_kind FROM hws_lines WHERE river_id = ${river_id} </dc:statement> <dc:if test="dc:has-result()"> <lines> <dc:macro name="hws-lines"> <dc:elements> <hws factory="hwsfactory" name="{$hws_name}"/> </dc:elements> </dc:macro> <dc:filter expr="$hws_official=1"> <dc:if test="dc:has-result()"> <official> <dc:filter expr="$hws_kind=1"> <dc:if test="dc:has-result()"> <Durchlass><dc:call-macro name="hws-lines"></Durchlass> </dc:if> </dc:filter> <dc:filter expr="$hws_kind=2"> <dc:if test="dc:has-result()"> <Damm><dc:call-macro name="hws-lines"></Damm> </dc:if> </dc:filter> <dc:filter expr="$hws_kind=3"> <dc:if test="dc:has-result()"> <Graben><dc:call-macro name="hws-lines"></Graben> </dc:if> </dc:filter> </official> </dc:if> </dc:filter> </lines> </dc:if> </dc:context>

#!/bin/sh

# Required
RIVER_PATH="/path/to/rivers/river"
RIVER_ID=1
TARGET_SRS=31466
HOST=localhost
USER=the_user
PASS=the_pass

# Optional
VERBOSE=1
SKIP_AXIS=0
SKIP_KMS=0
SKIP_CROSSSECTIONS=0
SKIP_LINES=0
SKIP_FIXPOINTS=0
SKIP_BUILDINGS=0
SKIP_FLOODPLAINS=0
SKIP_HYDR_BOUNDARIES=0
SKIP_HWS=0
SKIP_GAUGE_LOCATION=0
SKIP_UESG=0

exec python shpimporter.py \
    --directory $RIVER_PATH \
    --river_id $RIVER_ID \
    --target_srs $TARGET_SRS \
    --host $HOST \
    --user $USER \
    --password $PASS \
    --verbose $VERBOSE \
    --skip_axis $SKIP_AXIS \
    --skip_kms $SKIP_KMS \
    --skip_crosssections $SKIP_CROSSSECTIONS \
    --skip_lines $SKIP_LINES \
    --skip_fixpoints $SKIP_FIXPOINTS \
    --skip_buildings $SKIP_BUILDINGS \
    --skip_floodplains $SKIP_FLOODPLAINS \
    --skip_hydr_boundaries $SKIP_HYDR_BOUNDARIES \
    --skip_hws $SKIP_HWS \
    --skip_gauge_locations $SKIP_GAUGE_LOCATION \
    --skip_uesgs $SKIP_UESG