![]() # You need to set `expose_config = True` in Airflow configuration in order to retrieve configuration.Ĭonf_api_instance = config_api.ConfigApi(api_client)Īpi_response = conf_api_instance.get_config()Įxcept airflow_client.client. Note, this is disabled by default with most installation. Print( "Exception when calling DAGRunAPI->post_dag_run: %s\n" % e) hex,Īpi_response = dag_run_api_instance.post_dag_run(DAG_ID, dag_run) # Create a DAGRun object (no dag_id should be specified because it is read-only property of DAGRun) # dag_run id is generated randomly to allow multiple executions of the scriptĭag_run_id= 'some_test_run_' uuid.uuid4(). Print( 'Getting Tasks successful')ĭag_run_api_instance = dag_run_api.DAGRunApi(api_client) Print( "Exception when calling DagAPI->get_tasks: %s\n" % e) Print( 'Getting DAG list successful')Īpi_response = dag_api_instance.get_tasks(DAG_ID)Įxcept airflow_ as e: Print( "Exception when calling DagAPI->get_dags: %s\n" % e) # Make sure in the section, the `load_examples` config is set to True in your airflow.cfg # or AIRFLOW_CORE_LOAD_EXAMPLES environment variable set to TrueĭAG_ID = "example_bash_operator" # Enter a context with an instance of the API client with airflow_(configuration) as api_client:ĭag_api_instance = dag_api.DAGApi(api_client)Īpi_response = dag_api_instance.get_dags()Įxcept airflow_ as e: In the `` section of your `airflow.cfg` set: # auth_backend = .session.basic_auth # Make sure that your user/name are configured properly - using the user/password that has admin # privileges in Airflow # Configure HTTP basic authorization: BasicĬonfiguration = airflow_( # In case of the basic authentication below, make sure that Airflow is # configured also with the basic_auth as backend additionally to regular session backend needed # by the UI. # Examples for each auth method are provided below, use the example that # satisfies your auth use case. # The client must use the authentication and authorization parameters # in accordance with the API server security policy. Pass from airflow_ import config_api, dag_api, dag_run_apiįrom airflow_run import DAGRun It allows you to automate the extraction of data from various sources, including APIs, and save it to your. Please install rich to get colored output: `pip install rich`") Airflow is a popular platform for creating, scheduling, and monitoring workflows. ![]() # If you have rich installed, you will have nice colored output of the API responses from rich import print except ImportError: Please follow the installation procedure and then run the following Then import the package: import airflow_client.client If youre working with Airflow chances are that some of your DAGs may require access to data obtained through an API. (or sudo python setup.py install to install the package for all users) You can install directly using pip: pip install apache-airflow-client Python >= 3.7 Installation
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