Metadata-Version: 2.1
Name: dag-schedule-graph
Version: 0.2.2
Summary: Airflow plugin for visualising DAG schedules within 24 hour window of a day.
Home-page: https://github.com/arunvelsriram/dag-schedule-graph
Author: Arunvel Sriram
Author-email: arunvelsriram@gmail.com
License: MIT
Download-URL: https://github.com/arunvelsriram/dag-schedule-graph/archive/v0.2.2.tar.gz
Description: # DAG Schedule Graph
        
        Airflow plugin for visualising DAG schedules within 24 hour window of a day.
        
        ![Airflow dag-schedule-graph plugin screenshot](./images/screenshot-1.png)
        
        Each bubble indicates the number of DAGs that will run at that instant. Bubble radius is relative to the DAG count.
        
        ## Install
        
        ```shell
        pip install dag-schedule-graph
        ```
        
        ## Trying it out using Docker
        
        ```shell
        # Start the services
        docker-compose up
        
        # Access the webserver
        open http://localhost:8082/dag-schedule-graph/
        
        # Cleanup containers, networks and volumes
        docker-compose down -v
        ```
        
        ## Development
        
        ```shell
        # Create virtual environment using conda  
        conda create -n dag-schedule-graph python=3.7.9
        
        # Activate the environment
        conda activate dag-schedule-graph
        
        # Load environemnt variables
        source .env
        
        # Create Postgres database and user
        createuser airflow_rbac
        createdb -O airflow_rbac airflow_rbac
        
        # Install plugin and all dependencies
        pip install -e '.[dev]'
        
        # Running tests
        pytest tests
        
        # Initialize Airflow
        airflow initdb
        
        # Create Airflow user 
        airflow create_user -u admin -e admin@gmail.com -p admin -f admin -l admin -r Admin
        
        # Build static assets
        npm run build
        
        # Start Airflow Webserver
        airflow webserver
        
        # Access webserver
        open http://localhost:8080/dag-schedule-graph/
        ```
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
Provides-Extra: dev
