Metadata-Version: 2.1
Name: bigeye-airflow1
Version: 0.0.21
Summary: Airflow operators to be used with Bigeye.  Supporting Airflow version 1.10.10.
Home-page: https://github.com/torodata/toro-airflow
Author: Bigeye
Author-email: support@bigeye.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# bigeye-airflow
Airflow operators to interact with Bigeye API.

## The Test Environment
[Astronomer](astronomer.io) provides a local runtime for Airflow DAGs.  This runtime
is build from the Dockerfile in the astro folder.  A startup bash script has been 
added, ***astro_dev***, to facilitate the needed code copy into the astro environment.

Test environment is currently compatible with Python 3.6 and Airflow 1.10.7.

```shell
bash astro_dev start <-v 1>
bash astro_dev stop <-v 1>
bash astro_dev restart <-v 1>
```  
### Credentials Setup
* Go to the Admin menu and choose Connections:
    ![Admin Menu - Connections](docs/images/astronomer_connections_1.png "Admin Menu - Connections")  

* Fill out the form for an HTTP connection using the appropriate Host, User and Pass. The current test Dags use 
'bigeye_connection' as a connection_id for basic auth to the Bigeye API.
    ![Admin Menu - Connections](docs/images/astronomer_connections_2.png "Admin Menu - Connections") 

### Testing Metric Creation:  
Testing in a DAG runtime can be achieved by altering the test dag: 
[test_create_metrics_dag.py](https://github.com/bigeyedata/bigeye-airflow/blob/main/astro/dags/test_create_metrics_dag.py)


