gursAddressesConflationProfile.py

# addressed update 
# based on https://github.com/cascafico/MilanoHousenumbers/blob/master/profile.py
# aggiunge tag source=pippo
#add_source = False
source = 'GURS'

# do not add unique reference IDs to OSM?

# aggiunge tag ref:<dataset_id>=<id del Comune di Milano (IDMASTER)>
# True -> relying only on geometric matching every time
no_dataset_id = True
#dataset_id = 'gurs:hs_mid'

#A boolean value, False by default. If True, objects with ref:whatever tag are downloaded only for the import region, not for the whole world.
bounded_update = True

# Overpass query to use when searching OSM for data
#overpass_timeout = 120 default
overpass_timeout = 300
#query = [('amenity', 'fuel'),('waterway', 'fuel')] both conditions
#query = [('amenity', 'fuel')],[('waterway', 'fuel')]  or condition
#query = [('amenity', 'fuel'),('disused:amenity','fuel')]  namespace disused and abandoned are implicit
#query = [('amenity', 'fuel'),('ref:mise','.*')] 
#query = [('addr:postcode', '33050')] 
#query = [('addr:housenumber','.*')] 
#query = [('addr:housenumber','~.*')]  e se lettera e interno non hanno stesso case?
#query = [('addr:street','~.*')]  

# query = [('addr:housenumber','~.*')]
query = [('addr:housenumber',)]
#query = [('addr:housenumber')],[('addr:street')] #or condition
# query = [('addr:housenumber')]
#query = [('addr:housenumber'),[('addr:street'),('addr:place')]] #or condition

# parameter --osm will use indipendently generated queries, ie:
# http://overpass-turbo.eu/s/BZq
# http://overpass-turbo.eu/s/BZM (amenity=fuel and fuel:cng or fuel:lpg not "yes" 
# use wget -O manual-query.osm <http_addr obtained exporting compact query>

# attenzione, coord errate possono rendere enorme il bbox
# use openrefine for lat lon ranges
# vantaggio: fa richieste multiple ad overpass
#bbox = True

# italia
#bbox = [35.28,6.62,47.1,18.79]

# tags to replace on matched OSM objects
#master_tags = ('addr:housenumber', 'addr:street')
master_tags = ('addr:housenumber', 'addr:street', 'addr:postcode', 'addr:village', 'addr:city' )

# delete_unmatched = True cancellerebbe anche i POI con indirizzo
delete_unmatched = False
#tag_unmatched = { 'fixme':'this addr is missing from source dataset: please check in range >10meters' }
#tag_unmatched = { 'fixme':'this addr is missing in GURS: please check in range >10meters' }


# max distance to search for a match in meters
max_distance = 20

# Dataset points that are closer than this distance (in meters) will be considered duplicates of each other.
# Eg: 5 hišnih številk na popolnoma istem mestu (razdalja 0), 30 na razdalji 1 m ... pod 10 m jih je 40939.
duplicate_distance = 0

# https://wiki.openstreetmap.org/wiki/OSM_Conflator#Transforming_tags
transform = {
#    'postal_code': '>addr:postcode',
#    'phone': format_phone,

    #bilingual
#    'addr:street:hu': '-',
#    'addr:street:it': '-',
#    'addr:street:sl': '-',
#    'addr:place:hu': '-',
#    'addr:place:it': '-',
#    'addr:place:sl': '-',

    #meta
#    'source:addr': '-',
#    'source:addr:date': '-',
#    'ref:gurs:hs_mid': '-',

    #'ref_id': '-' // no effect, that is internal for osm_ conflator
}