search_ads

Example Airflow DAG that shows how to use SearchAds.

Data Processing


Providers:

Run this DAG

1. Install Astronomer CLISkip if you already have the CLI

2. Initate the project:

3. Copy and paste the code below into a file in the

dags
directory.

4. Add the following to your requirements.txt file:

5. Run the DAG:

#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""
Example Airflow DAG that shows how to use SearchAds.
"""
import os
from airflow import models
from airflow.providers.google.marketing_platform.operators.search_ads import (
GoogleSearchAdsDownloadReportOperator,
GoogleSearchAdsInsertReportOperator,
)
from airflow.providers.google.marketing_platform.sensors.search_ads import GoogleSearchAdsReportSensor
from airflow.utils import dates
# [START howto_search_ads_env_variables]
AGENCY_ID = os.environ.get("GMP_AGENCY_ID")
ADVERTISER_ID = os.environ.get("GMP_ADVERTISER_ID")
GCS_BUCKET = os.environ.get("GMP_GCS_BUCKET", "test-cm-bucket")
REPORT = {
"reportScope": {"agencyId": AGENCY_ID, "advertiserId": ADVERTISER_ID},
"reportType": "account",
"columns": [{"columnName": "agency"}, {"columnName": "lastModifiedTimestamp"}],
"includeRemovedEntities": False,
"statisticsCurrency": "usd",
"maxRowsPerFile": 1000000,
"downloadFormat": "csv",
}
# [END howto_search_ads_env_variables]
with models.DAG(
"example_search_ads",
schedule_interval=None, # Override to match your needs,
start_date=dates.days_ago(1),
) as dag:
# [START howto_search_ads_generate_report_operator]
generate_report = GoogleSearchAdsInsertReportOperator(report=REPORT, task_id="generate_report")
# [END howto_search_ads_generate_report_operator]
# [START howto_search_ads_get_report_id]
report_id = "{{ task_instance.xcom_pull('generate_report', key='report_id') }}"
# [END howto_search_ads_get_report_id]
# [START howto_search_ads_get_report_operator]
wait_for_report = GoogleSearchAdsReportSensor(report_id=report_id, task_id="wait_for_report")
# [END howto_search_ads_get_report_operator]
# [START howto_search_ads_getfile_report_operator]
download_report = GoogleSearchAdsDownloadReportOperator(
report_id=report_id, bucket_name=GCS_BUCKET, task_id="download_report"
)
# [END howto_search_ads_getfile_report_operator]
generate_report >> wait_for_report >> download_report