tests.system.google.cloud.natural_language.example_natural_language¶

Example Airflow DAG for Google Cloud Natural Language service

Attributes¶

`ENV_ID`
`DAG_ID`
`TEXT`
`document`
`GCS_CONTENT_URI`
`document_gcs`
`analyze_entities`
`test_run`

Module Contents¶

tests.system.google.cloud.natural_language.example_natural_language.ENV_ID[source]¶

tests.system.google.cloud.natural_language.example_natural_language.DAG_ID = 'gcp_natural_language'[source]¶

tests.system.google.cloud.natural_language.example_natural_language.TEXT = Multiline-String[source]¶

Show Value

"""Airflow is a platform to programmatically author, schedule and monitor workflows.

Use Airflow to author workflows as Directed Acyclic Graphs (DAGs) of tasks. The Airflow scheduler executes
 your tasks on an array of workers while following the specified dependencies. Rich command line utilities
 make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize
 pipelines running in production, monitor progress, and troubleshoot issues when needed.
"""

tests.system.google.cloud.natural_language.example_natural_language.document[source]¶

tests.system.google.cloud.natural_language.example_natural_language.GCS_CONTENT_URI = 'gs://INVALID BUCKET NAME/sentiment-me.txt'[source]¶

tests.system.google.cloud.natural_language.example_natural_language.document_gcs[source]¶

tests.system.google.cloud.natural_language.example_natural_language.analyze_entities[source]¶

tests.system.google.cloud.natural_language.example_natural_language.test_run[source]¶