Using a secret key in Amazon Secrets Manager for an Apache Airflow Snowflake connection - Amazon Managed Workflows for Apache Airflow
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Using a secret key in Amazon Secrets Manager for an Apache Airflow Snowflake connection

The following sample calls Amazon Secrets Manager to get a secret key for an Apache Airflow Snowflake connection on Amazon Managed Workflows for Apache Airflow. It assumes you've completed the steps in Configuring an Apache Airflow connection using a Amazon Secrets Manager secret.


  • You can use the code example on this page with Apache Airflow v2 and above in Python 3.10.


To use the sample code on this page, you'll need the following:



To use the sample code on this page, add the following dependencies to your requirements.txt. To learn more, see Installing Python dependencies.


Code sample

The following steps describe how to create the DAG code that calls Secrets Manager to get the secret.

  1. In your command prompt, navigate to the directory where your DAG code is stored. For example:

    cd dags
  2. Copy the contents of the following code sample and save locally as

    """ Copyright, Inc. or its affiliates. All Rights Reserved. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from airflow import DAG from airflow.providers.snowflake.operators.snowflake import SnowflakeOperator from airflow.utils.dates import days_ago snowflake_query = [ """use warehouse "MY_WAREHOUSE";""", """select * from "SNOWFLAKE_SAMPLE_DATA"."WEATHER"."WEATHER_14_TOTAL" limit 100;""", ] with DAG(dag_id='snowflake_test', schedule_interval=None, catchup=False, start_date=days_ago(1)) as dag: snowflake_select = SnowflakeOperator( task_id="snowflake_select", sql=snowflake_query, snowflake_conn_id="snowflake_conn", )

What's next?

  • Learn how to upload the DAG code in this example to the dags folder in your Amazon S3 bucket in Adding or updating DAGs.