def setUp(self):
with mock.patch(
"airflow.contrib.hooks."
"gcp_api_base_hook.CloudBaseHook.__init__",
new=mock_base_gcp_hook_no_default_project_id,
):
self.hook = CloudNaturalLanguageHook(gcp_conn_id="test")
def execute(self, context):
hook = CloudNaturalLanguageHook(gcp_conn_id=self.gcp_conn_id)
self.log.info("Start analyzing entities")
response = hook.analyze_entities(document=self.document,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata)
self.log.info("Finished analyzing entities")
return MessageToDict(response)
def execute(self, context):
hook = CloudNaturalLanguageHook(gcp_conn_id=self.gcp_conn_id)
self.log.info("Start text classify")
response = hook.classify_text(document=self.document,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata)
self.log.info("Finished text classify")
return MessageToDict(response)
def execute(self, context):
hook = CloudNaturalLanguageHook(
gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain,
)
self.log.info("Start sentiment analyze")
response = hook.analyze_sentiment(
document=self.document, retry=self.retry, timeout=self.timeout, metadata=self.metadata
)
self.log.info("Finished sentiment analyze")
return MessageToDict(response)
def execute(self, context):
hook = CloudNaturalLanguageHook(gcp_conn_id=self.gcp_conn_id)
self.log.info("Start entity sentiment analyze")
response = hook.analyze_entity_sentiment(
document=self.document,
encoding_type=self.encoding_type,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
self.log.info("Finished entity sentiment analyze")
return MessageToDict(response)
def setUp(self):
with mock.patch(
"airflow.providers.google.cloud.hooks.base.CloudBaseHook.__init__",
new=mock_base_gcp_hook_no_default_project_id,
):
self.hook = CloudNaturalLanguageHook(gcp_conn_id="test")
