airflow-provider-tm1 0.4.0

A package to simplify connecting to the TM1 REST API from Apache Airflow

airflow-provider-tm1

A package by Knowledgeseed and Cubewise that provides a hook to simplify the connection to the IBM Cognos TM1 / Planning Analytics REST API.

https://github.com/airflow-provider-tm1/airflow-provider-tm1

This repository builds on https://github.com/MariusWirtz/airflow-tm1 and https://github.com/scrambldchannel/airflow-tm1 which offer only Airflow 1.x compatibility, and upgrades the provider to ensure Airflow 2.x compatibility. Some parts and have been reused from https://github.com/scrambldchannel/airflow-provider-tm1 as well.

Requirements

• Python 3.7+
• Airflow 2.3+
• TM1py 2.0+

Development

python -m venv .env
source .env/bin/activate
python -m pip install -r requirements.txt
python -m build

To execute the automated test suite locally, you can leverage (https://github.com/nektos/act):

act -j build  -W .github/workflows/build-test.yml -s DUSERNAME=knowledgeseed -s DPASSWORD=<obtain access token to private DockerHub registry from KS>

Installation

Install with pip pip install airflow-provider-tm1

Usage

Create a connection in Airflow:

• TM1 11 on-premise: BaseURL (or Address+Port+SSL), User, Password
• TM1 11 on IBM cloud: BaseURL, Namespace, User. Password, Extras/async_requests_mode, Extras/verify
• TM1 12 PAaaS: BaseURL, User, Password, Extras/async_requests_mode, Extras/verify
• TM1 12 on-premise & Cloud Pak For Data: BaseURL (or Address + Extras/instance + Extras/database), Extras/application_client_id, Extras/application_client_secret, User
• TM1 12 on-premise with access token: BaseURL (or Address + Extras/instance + Extras/database), User, Extras/access_token, Extras/async_requests_mode, Extras/verify

Any other parameter accepted by the TM1py RestService constructor can also be added as key/value pairs in the Extras field.

For the exact parameterization of TM1Service and further examples, please check https://github.com/cubewise-code/tm1py

In your DAG file:

from airflow_provider_tm1.operators.tm1_run_ti import TM1RunTIOperator

...

t1 = TM1RunTIOperator (
        task_id='t1',
        tm1_conn_id='tm1_conn',
        process_name='airflow_test_params_success_dag',
        tm1_params={'testParam1': 'testParamValue'},
        timeout=20,
        cancel_at_timeout=True
    )

This will attempt to connect to the TM1 server using the details provided and initialise an instance of the TM1Service class than be accessed at airflow_provider_tm1.hooks.tm1.TM1Hook

See TM1py for more details.

It's important to mention that TM1Py will execute TI process in asynchronous mode. The operator submits the request, receives the async_id from TM1 and starts polling the result using async_id until the response is retrieved or times out. Timeout is defined in seconds, default value is 300 seconds. It's also important that Airflow-side timeout does not involve automatically the cancellation of the TI process. If cancel_at_timeout is set True, Airflow will make an attempt to cancel the long-running TI process.

For further examples, please see tests_integration/dags folder.

Manual integration testing

Use tests_integration/docker-compose.yaml as a baseline, which spins up an Airflow including the TM1 provider and a base TM1 database to test against. Please note that tm1-docker image is properietary IBM product wrapped in Docker by Knowledgeseed and therefore it is only available internally for Knowledgeseed developers.

To obtain a licensed IBM TM1 database for testing or production purpose, please see https://www.ibm.com/topics/tm1 for further details.

License

See LICENSE