def _main(project=None,
bq_project=None,
bq_dataset=None,
bq_table=None,
read_time=None,
verbose=False):
'Module entry point used by cli and cloud function wrappers.'
_configure_logging(verbose)
if not read_time:
read_time = datetime.datetime.now()
client = asset_v1.AssetServiceClient()
parent = 'projects/%s' % project
content_type = asset_v1.ContentType.RESOURCE
output_config = asset_v1.OutputConfig()
output_config.bigquery_destination.dataset = 'projects/%s/datasets/%s' % (
bq_project, bq_dataset)
output_config.bigquery_destination.table = '%s_%s' % (
bq_table, read_time.strftime('%Y%m%d'))
output_config.bigquery_destination.force = True
try:
response = client.export_assets(
request={
'parent': parent,
'read_time': read_time,
'content_type': content_type,
'output_config': output_config
})
except (GoogleAPIError, googleapiclient.errors.HttpError) as e:
logging.debug('API Error: %s', e, exc_info=True)
raise RuntimeError(
'Error fetching Asset Inventory entries (project: %s)' % parent, e)
def export_assets(project_id, dump_file_path):
# [START asset_quickstart_export_assets]
from google.cloud import asset_v1
# TODO project_id = 'Your Google Cloud Project ID'
# TODO dump_file_path = 'Your asset dump file path'
client = asset_v1.AssetServiceClient()
parent = "projects/{}".format(project_id)
output_config = asset_v1.OutputConfig()
output_config.gcs_destination.uri = dump_file_path
response = client.export_assets(request={
"parent": parent,
"output_config": output_config
})
print(response.result())
def hello_pubsub(event, context):
from google.cloud import asset_v1
parent_id = os.environ['PARENT']
dump_file_path = os.environ['GCS_FILE_PATH']
now = time.time()
client = asset_v1.AssetServiceClient()
output_config = asset_v1.OutputConfig()
output_config.gcs_destination.uri = dump_file_path+str(now)
content_type = asset_v1.ContentType.RESOURCE
response = client.export_assets(
request={
"parent": parent_id,
"content_type": content_type,
"output_config": output_config
}
)
def sample_export_assets():
# Create a client
client = asset_v1.AssetServiceClient()
# Initialize request argument(s)
output_config = asset_v1.OutputConfig()
output_config.gcs_destination.uri = "uri_value"
request = asset_v1.ExportAssetsRequest(
parent="parent_value",
output_config=output_config,
)
# Make the request
operation = client.export_assets(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
def export_assets_bigquery(project_id, dataset, table, content_type):
# [START asset_quickstart_export_assets_bigquery]
from google.cloud import asset_v1
# TODO project_id = 'Your Google Cloud Project ID'
# TODO dataset = 'Your BigQuery dataset path'
# TODO table = 'Your BigQuery table name'
# TODO content_type ="Content type to export"
client = asset_v1.AssetServiceClient()
parent = "projects/{}".format(project_id)
output_config = asset_v1.OutputConfig()
output_config.bigquery_destination.dataset = dataset
output_config.bigquery_destination.table = table
output_config.bigquery_destination.force = True
response = client.export_assets(
request={
"parent": parent,
"content_type": content_type,
"output_config": output_config
})
print(response.result())
