![]() ![]() Also, none of the existing Slack operators can return the response of a Slack API call, which you might want to log for monitoring purposes. The following example shows how you can use the hooks ( S3Hook and SlackHook) to retrieve values from files in an Amazon S3 bucket, run a check on them, post the result of the check on Slack, and then log the response of the Slack API.įor this use case, you'll use hooks directly in your Python functions because none of the existing Amazon S3 operators can read data from multiple files within an Amazon S3 bucket. If you regularly need to connect to an API and a hook is not available, write your own hook and share it with the community.When an operator with built-in hooks exists for your specific use case, you should use the operator instead of manually setting up a hook. ![]() If you write a custom operator to interact with an external system, it should use a hook.Hooks should always be used over manual API interaction to connect to external systems.The following are some general guidelines for using hooks in Airflow: However, there are some cases when you should use hooks directly in a Python function in your DAG. Since hooks are the building blocks of operators, their use in Airflow is often abstracted away from the DAG author. download_file: Downloads a file from the Amazon S3 location to the local file system.load_file: Loads a local file to Amazon S3.list_keys: Lists keys in a bucket according to specified parameters.list_prefixes: Lists prefixes in a bucket according to specified parameters.check_for_bucket: Checks if a bucket with a specific name exists.The following are some of the methods that are included with S3Hook: The S3Hook contains over 20 methods to interact with Amazon S3 buckets. For example, the S3Hook relies on the boto3 library to manage its Amazon S3 connection. These methods might rely on different Python libraries for these interactions. On top of making the connection to an external system, individual hooks can contain additional methods to perform various actions within the external system. For more information about setting up connections, see Manage your connections in Apache Airflow.Īll hooks inherit from the BaseHook class, which contains the logic to set up an external connection with a connection ID. To use a hook, you typically only need a connection ID to connect with an external system. Hooks standardize how Astronomer interacts with external systems and using them makes your DAG code cleaner, easier to read, and less prone to errors. Hooks wrap around APIs and provide methods to interact with different external systems. To get the most out of this guide, you should have an understanding of: If a hook isn't available for your use case, you can write your own and share it with the community. Over 200 hooks are available in the Astronomer Registry. You'll also implement two different hooks in a DAG. ![]() In this guide, you'll learn about using hooks in Airflow and when you should use them directly in DAG code. Hooks are built into many operators, but they can also be used directly in DAG code. A hook is an abstraction of a specific API that allows Airflow to interact with an external system. ![]()
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