airflow-dags/reference/providers/google/cloud/example_dags/example_functions.py

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"""
Example Airflow DAG that displays interactions with Google Cloud Functions.
It creates a function and then deletes it.

This DAG relies on the following OS environment variables
https://airflow.apache.org/concepts.html#variables

* GCP_PROJECT_ID - Google Cloud Project to use for the Cloud Function.
* GCP_LOCATION - Google Cloud Functions region where the function should be
  created.
* GCF_ENTRYPOINT - Name of the executable function in the source code.
* and one of the below:

    * GCF_SOURCE_ARCHIVE_URL - Path to the zipped source in Google Cloud Storage

    * GCF_SOURCE_UPLOAD_URL - Generated upload URL for the zipped source and GCF_ZIP_PATH - Local path to
      the zipped source archive

    * GCF_SOURCE_REPOSITORY - The URL pointing to the hosted repository where the function
      is defined in a supported Cloud Source Repository URL format
      https://cloud.google.com/functions/docs/reference/rest/v1/projects.locations.functions#SourceRepository

"""

import os

from airflow import models
from airflow.providers.google.cloud.operators.functions import (
    CloudFunctionDeleteFunctionOperator,
    CloudFunctionDeployFunctionOperator,
    CloudFunctionInvokeFunctionOperator,
)
from airflow.utils import dates

GCP_PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "example-project")
GCP_LOCATION = os.environ.get("GCP_LOCATION", "europe-west1")
GCF_SHORT_FUNCTION_NAME = os.environ.get("GCF_SHORT_FUNCTION_NAME", "hello").replace(
    "-", "_"
)  # make sure there are no dashes in function name (!)
FUNCTION_NAME = "projects/{}/locations/{}/functions/{}".format(
    GCP_PROJECT_ID, GCP_LOCATION, GCF_SHORT_FUNCTION_NAME
)
GCF_SOURCE_ARCHIVE_URL = os.environ.get("GCF_SOURCE_ARCHIVE_URL", "")
GCF_SOURCE_UPLOAD_URL = os.environ.get("GCF_SOURCE_UPLOAD_URL", "")
GCF_SOURCE_REPOSITORY = os.environ.get(
    "GCF_SOURCE_REPOSITORY",
    "https://source.developers.google.com/"
    "projects/{}/repos/hello-world/moveable-aliases/master".format(GCP_PROJECT_ID),
)
GCF_ZIP_PATH = os.environ.get("GCF_ZIP_PATH", "")
GCF_ENTRYPOINT = os.environ.get("GCF_ENTRYPOINT", "helloWorld")
GCF_RUNTIME = "nodejs6"
GCP_VALIDATE_BODY = os.environ.get("GCP_VALIDATE_BODY", "True") == "True"

# [START howto_operator_gcf_deploy_body]
body = {
    "name": FUNCTION_NAME,
    "entryPoint": GCF_ENTRYPOINT,
    "runtime": GCF_RUNTIME,
    "httpsTrigger": {},
}
# [END howto_operator_gcf_deploy_body]

# [START howto_operator_gcf_default_args]
default_args = {"owner": "airflow"}
# [END howto_operator_gcf_default_args]

# [START howto_operator_gcf_deploy_variants]
if GCF_SOURCE_ARCHIVE_URL:
    body["sourceArchiveUrl"] = GCF_SOURCE_ARCHIVE_URL
elif GCF_SOURCE_REPOSITORY:
    body["sourceRepository"] = {"url": GCF_SOURCE_REPOSITORY}
elif GCF_ZIP_PATH:
    body["sourceUploadUrl"] = ""
    default_args["zip_path"] = GCF_ZIP_PATH
elif GCF_SOURCE_UPLOAD_URL:
    body["sourceUploadUrl"] = GCF_SOURCE_UPLOAD_URL
else:
    raise Exception("Please provide one of the source_code parameters")
# [END howto_operator_gcf_deploy_variants]


with models.DAG(
    "example_gcp_function",
    schedule_interval=None,  # Override to match your needs
    start_date=dates.days_ago(1),
    tags=["example"],
) as dag:
    # [START howto_operator_gcf_deploy]
    deploy_task = CloudFunctionDeployFunctionOperator(
        task_id="gcf_deploy_task",
        project_id=GCP_PROJECT_ID,
        location=GCP_LOCATION,
        body=body,
        validate_body=GCP_VALIDATE_BODY,
    )
    # [END howto_operator_gcf_deploy]
    # [START howto_operator_gcf_deploy_no_project_id]
    deploy2_task = CloudFunctionDeployFunctionOperator(
        task_id="gcf_deploy2_task",
        location=GCP_LOCATION,
        body=body,
        validate_body=GCP_VALIDATE_BODY,
    )
    # [END howto_operator_gcf_deploy_no_project_id]
    # [START howto_operator_gcf_invoke_function]
    invoke_task = CloudFunctionInvokeFunctionOperator(
        task_id="invoke_task",
        project_id=GCP_PROJECT_ID,
        location=GCP_LOCATION,
        input_data={},
        function_id=GCF_SHORT_FUNCTION_NAME,
    )
    # [END howto_operator_gcf_invoke_function]
    # [START howto_operator_gcf_delete]
    delete_task = CloudFunctionDeleteFunctionOperator(
        task_id="gcf_delete_task", name=FUNCTION_NAME
    )
    # [END howto_operator_gcf_delete]
    deploy_task >> deploy2_task >> invoke_task >> delete_task