# [START howto_operator_gcp_natural_language_analyze_sentiment]
analyze_sentiment = \
CloudNaturalLanguageAnalyzeSentimentOperator(document=document, task_id="analyze_sentiment")
# [END howto_operator_gcp_natural_language_analyze_sentiment]
# [START howto_operator_gcp_natural_language_analyze_sentiment_result]
analyze_sentiment_result = BashOperator(
bash_command="echo \"{{ task_instance.xcom_pull('analyze_sentiment') }}\"",
task_id="analyze_sentiment_result",
)
# [END howto_operator_gcp_natural_language_analyze_sentiment_result]
# [START howto_operator_gcp_natural_language_analyze_classify_text]
analyze_classify_text = CloudNaturalLanguageClassifyTextOperator(
document=document, task_id="analyze_classify_text"
)
# [END howto_operator_gcp_natural_language_analyze_classify_text]
# [START howto_operator_gcp_natural_language_analyze_classify_text_result]
analyze_classify_text_result = BashOperator(
bash_command="echo \"{{ task_instance.xcom_pull('analyze_classify_text') }}\"",
task_id="analyze_classify_text_result",
)
# [END howto_operator_gcp_natural_language_analyze_classify_text_result]
analyze_entities >> analyze_entities_result
analyze_entity_sentiment >> analyze_entity_sentiment_result
analyze_sentiment >> analyze_sentiment_result
analyze_classify_text >> analyze_classify_text_result
def test_minimal_green_path(self, hook_mock):
hook_mock.return_value.classify_text.return_value = CLASSIFY_TEXT_RRESPONSE
op = CloudNaturalLanguageClassifyTextOperator(task_id="task-id", document=DOCUMENT)
resp = op.execute({})
self.assertEqual(resp, {})