from datacatalogtordf import Catalog, Dataset
# Create catalog object
catalog = Catalog()
catalog.identifier = "http://example.com/catalogs/1"
catalog.title = {"en": "A dataset catalog"}
catalog.publisher = "https://example.com/publishers/1"
# Create a dataset:
dataset = Dataset()
dataset.identifier = "http://example.com/datasets/1"
dataset.title = {"nb": "inntektsAPI", "en": "incomeAPI"}
#
# Add concept to catalog:
catalog.datasets.append(dataset)
# get rdf representation in turtle (default)
rdf = catalog.to_rdf()
print(rdf.decode())
def _add_mandatory_catalog_props(catalog: Catalog) -> None:
catalog.title = {"nb": "NAV åpne APIer"}
catalog.identifier = os.environ["COLLECTION_IDENTIFIER"]
catalog.publisher = URI(os.environ["PUBLISHER"])
def main(req: func.HttpRequest, msg: func.Out[str]) -> func.HttpResponse:
logging.info('Python HTTP trigger function processed a request.')
search = req.params.get('search')
if not search:
try:
req_body = req.get_json()
except ValueError:
pass
else:
search = req_body.get('search')
assetType = req.params.get('assetType')
if not assetType:
try:
req_body = req.get_json()
except ValueError:
pass
else:
search = req_body.get('assetType')
entityType = req.params.get('entityType')
if not entityType:
try:
req_body = req.get_json()
except ValueError:
pass
else:
search = req_body.get('entityType')
if search:
logging.info(search)
logging.info(assetType)
logging.info(entityType)
# search purview
value = entitySearch(search)
if int(json.loads(value)['@search.count']) > 0:
logging.info(json.loads(value)['@search.count'])
else:
logging.info("Nothing was returned from the search")
return func.HttpResponse(
"This HTTP triggered function executed successfully, but no search criteria was returned from the Purview catalog. Pass a search in the query string or in the request body for a response.",
status_code=200
)
#parse the response
objToexport = []
score = 0
#loop through all of the results and filter on the assetType and entityType
jsonObj = json.loads(value)
for obj in jsonObj['value'] :
if (obj['assetType'][0] == assetType) and (obj['entityType'] == entityType):
#if there are multiple objects returned, select the one with the highest score
if (obj['@search.score'] > score):
objToexport = obj
score = obj['@search.score']
# return function if not match has been found in the data returned from Purview
if(len(objToexport) == 0):
logging.info("No match was found in the Purview catalog for the search, assetType and entityType combination entityType: {0} {1} {2} ".format(search, assetType, entityType))
return func.HttpResponse(
f"No match was found in the Purview catalog for search : {search} assetType: {assetType} entityType: {entityType} ",
status_code=200
)
publisher = os.environ.get('publisher')
logging.info(objToexport['assetType'])
logging.info(objToexport['entityType'])
logging.info(objToexport['@search.score'])
logging.info(objToexport['qualifiedName'])
logging.info(objToexport['name'])
logging.info(publisher)
logging.info(score)
# Create catalog object
catalog = Catalog()
catalog.identifier = objToexport['qualifiedName']
catalog.title = {"en": objToexport['name']}
catalog.publisher = publisher
# Create a dataset:
dataset = Dataset()
dataset.identifier = objToexport['qualifiedName']
dataset.title = {"nb": objToexport['name'], "en": objToexport['name']}
#
# Add dataset to catalog:
catalog.datasets.append(dataset)
# get rdf representation in turtle (default)
rdf = catalog.to_rdf()
logging.info(rdf.decode())
# write the rdf to Azure storage
msg.set(rdf.decode())
# return the function
return func.HttpResponse(f"The HTTP triggered function for {search} executed successfully. The assetType provided was: {assetType} and the entityType was: {entityType }")
else:
return func.HttpResponse(
"This HTTP triggered function executed successfully, but no search criteria was supplied. Pass a search in the query string or in the request body for a response.",
status_code=200
)