ads

Example Airflow DAG that shows how to use GoogleAdsToGcsOperator.

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 GoogleAdsToGcsOperator.
"""
import os
from airflow import models
from airflow.providers.google.ads.operators.ads import GoogleAdsListAccountsOperator
from airflow.providers.google.ads.transfers.ads_to_gcs import GoogleAdsToGcsOperator
from airflow.utils import dates
# [START howto_google_ads_env_variables]
CLIENT_IDS = ["1111111111", "2222222222"]
BUCKET = os.environ.get("GOOGLE_ADS_BUCKET", "gs://INVALID BUCKET NAME")
GCS_OBJ_PATH = "folder_name/google-ads-api-results.csv"
GCS_ACCOUNTS_CSV = "folder_name/accounts.csv"
QUERY = """
SELECT
segments.date,
customer.id,
campaign.id,
ad_group.id,
ad_group_ad.ad.id,
metrics.impressions,
metrics.clicks,
metrics.conversions,
metrics.all_conversions,
metrics.cost_micros
FROM
ad_group_ad
WHERE
segments.date >= '2020-02-01'
AND segments.date <= '2020-02-29'
"""
FIELDS_TO_EXTRACT = [
"segments.date.value",
"customer.id.value",
"campaign.id.value",
"ad_group.id.value",
"ad_group_ad.ad.id.value",
"metrics.impressions.value",
"metrics.clicks.value",
"metrics.conversions.value",
"metrics.all_conversions.value",
"metrics.cost_micros.value",
]
# [END howto_google_ads_env_variables]
with models.DAG(
"example_google_ads",
schedule_interval=None, # Override to match your needs
start_date=dates.days_ago(1),
) as dag:
# [START howto_google_ads_to_gcs_operator]
run_operator = GoogleAdsToGcsOperator(
client_ids=CLIENT_IDS,
query=QUERY,
attributes=FIELDS_TO_EXTRACT,
obj=GCS_OBJ_PATH,
bucket=BUCKET,
task_id="run_operator",
)
# [END howto_google_ads_to_gcs_operator]
# [START howto_ads_list_accounts_operator]
list_accounts = GoogleAdsListAccountsOperator(
task_id="list_accounts", bucket=BUCKET, object_name=GCS_ACCOUNTS_CSV
)
# [END howto_ads_list_accounts_operator]