how to Airflow : Streamline your data processes by implementing a custom hook.

The airflow.hooks.base module provides the foundational building blocks for creating these hooks. In this article, we delve deep into the concept of hooks in Airflow, capped with a detailed, real-world example to cement your understanding.

Understanding Airflow Hooks

Hooks are a pivotal part of the Airflow ecosystem, allowing for easy interaction with external data sources and services. They act as the glue between Airflow and the external system, abstracting the complexities involved in the connection and interaction process.

The BaseHook class

The BaseHook class is the superclass for all hooks, encapsulating the logic for creating and managing connections to external services. It provides methods for retrieving connection metadata from the Airflow backend and utility functions for establishing connections.

Implementing a custom hook

To demonstrate the power and flexibility of Airflow hooks, let’s create a custom hook to interact with a fictional external REST API service that provides real-time stock market data.

Define the custom hook

from airflow.hooks.base_hook import BaseHook
import requests

class StockMarketHook(BaseHook):

    def __init__(self, conn_id):
        super().__init__(source=None)
        self.conn_id = conn_id
        self.connection = self.get_connection(conn_id)
        self.extras = self.connection.extra_dejson

    def get_stock_data(self, symbol):
        endpoint = f"{self.connection.host}/api/stocks/{symbol}"
        api_key = self.extras.get('api_key')
        response = requests.get(endpoint, headers={"Authorization": f"Bearer {api_key}"})
        response.raise_for_status()
        return response.json()

In the above example, the StockMarketHook class inherits from BaseHook. It utilizes the get_connection method to retrieve the connection information stored in Airflow’s backend. The get_stock_data method makes a GET request to the external API and returns the JSON response.

Store connection information

Before using the hook, store the connection information in Airflow:

• Go to Admin -> Connections in the Airflow UI.
• Add a new connection with conn_id as stock_market_api.
• Include the host URL and API key in the Extras field as JSON: {"api_key": "YOUR_API_KEY"}.

Use the Hook in a DAG

from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from datetime import datetime
from custom_hooks.stock_market_hook import StockMarketHook

default_args = {
    'start_date': datetime(2023, 1, 1),
}

def pull_stock_data(ti, symbol):
    hook = StockMarketHook(conn_id="stock_market_api")
    stock_data = hook.get_stock_data(symbol)
    ti.xcom_push(key='stock_data', value=stock_data)

with DAG('stock_market_dag', default_args=default_args, schedule_interval='@daily') as dag:
    pull_data = PythonOperator(
        task_id='pull_stock_data',
        python_callable=pull_stock_data,
        op_kwargs={'symbol': 'AAPL'},
    )

pull_data

In the DAG definition, the PythonOperator uses the custom hook to pull data for the Apple Inc. stock (AAPL) and pushes it to XComs for other tasks to use.

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