Getting started

Start with initalizing an instance of pnvdb:

>>> import pnvdb
>>> nvdb = pnvdb.Nvdb(client='Your-App-Name', contact='Your-contact-information')

Now we can test our connection to NVDB:

>>> print(nvdb.status())
{'datagrunnlag': {'sist_oppdatert': '2017-11-05 11:59:37'}, 'datakatalog': {'id': 782, 'dato': '2017-09-29', 'versjon': '2.10'}}

To work with a spesific nvdb object, we can initialize it like this:

>>> objekt = nvdb.objekt(objekt_type=67, nvdb_id=86543444)

This will get us access to a number of attributes assosiated with this object. Let’s print one out:

>>> print(objekt.metadata)
{'type': {'id': 67, 'navn': 'Tunnelløp'}, 'versjon': 14, 'startdato': '2014-09-19', 'sist_modifisert': '2017-10-24 15:40:48'}

We can search using area and property filters. This will return a generator object that can be itterated over.

>>> criteria = {'fylke':'2','egenskap':'1820>=20'} # 1820 = "Takst liten bil"
>>> objekttype = 45 # Bomstasjon
>>> tollstations = nvdb.hent(objekttype, criteria)
>>> for tollstation in tollstations:
        if tollstation.egenskap(1078): # Check for existance
                print(tollstation.egenskap(1078)['verdi'])
Hovinmoen - Dal
Dal - Boksrud
Minnesund - Hedmark grense

Add data to datafangst:

>>> datafangst = pnvdb.Datafangst(username, password, contractId)
>>> a_point = (10.39241731, 63.43053048) # Geometry

initialize the feature

>>> skiltpunkt = datafangst.feature(96, point, "Skilt")

Add attribute data to the feature

>>> skiltpunkt.attribute(1876,4605)
>>> skiltpunkt.attribute(1877,1)
>>> skiltpunkt.attribute(1671,2435)
>>> skiltpunkt.attribute(1887,1)

Add a comment

>>> skiltpunkt.comment("Fra Pnvdb")

Initialize a feature collection to hold the feautures

>>> datafangst_collection = datafangst.feature_collection()

Add the feature we build

>>> datafangst_collection.add_feature(skiltpunkt)

Push the feature to datafangst

>>> datafangst_collection.push()

Query the status of the transaction with datafangst

>>> print(datafangst_collection.status())