apache-airflow-providers-salesforce

import os from datetime import datetime from airflow.models.dag import DAG from airflow.providers.salesforce.hooks.salesforce import SalesforceHook from airflow.providers.salesforce.operators.salesforce import SalesforceToTableOperator with DAG( dag_id='salesforce_example_dag', start_date=datetime(2023, 1, 1), schedule_interval=None, catchup=False, tags=['salesforce', 'example'], ) as dag: # Example of using SalesforceToTableOperator to extract data extract_contacts = SalesforceToTableOperator( task_id='extract_salesforce_contacts', salesforce_conn_id='salesforce_default', # Ensure this connection is configured in Airflow UI sobjects=['Contact'], table_name='airflow_contacts', selected_fields=['Id', 'FirstName', 'LastName', 'Email'], where_clause="MailingState = 'CA'", # Optional: You might push to a database table or another destination # E.g., postgres_conn_id='postgres_default' # For this example, we'll just demonstrate extraction. ) # Example of using SalesforceHook directly (e.g., in a PythonOperator) def get_salesforce_data(**kwargs): hook = SalesforceHook(salesforce_conn_id='salesforce_default') sf_client = hook.get_conn() # Query the Salesforce API directly records = sf_client.query("SELECT Id, Name FROM Account LIMIT 5") print(f"Fetched {len(records['records'])} Account records.") return records['records'] # You'd typically use a PythonOperator to wrap the hook usage # from airflow.operators.python import PythonOperator # fetch_data_task = PythonOperator( # task_id='fetch_data_with_hook', # python_callable=get_salesforce_data, # ) # extract_contacts >> fetch_data_task