https://github.com/arunvelsriram/dag-schedule-graph
Airflow plugin for visualising DAG schedules within 24 hour window of a day.
https://github.com/arunvelsriram/dag-schedule-graph
airflow airflow-dags airflow-plugin graph python
Last synced: 7 months ago
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Airflow plugin for visualising DAG schedules within 24 hour window of a day.
- Host: GitHub
- URL: https://github.com/arunvelsriram/dag-schedule-graph
- Owner: arunvelsriram
- License: mit
- Created: 2020-12-06T14:01:10.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2020-12-12T10:52:22.000Z (almost 5 years ago)
- Last Synced: 2024-09-30T09:19:03.430Z (about 1 year ago)
- Topics: airflow, airflow-dags, airflow-plugin, graph, python
- Language: Python
- Homepage: https://github.com/arunvelsriram/dag-schedule-graph
- Size: 1.02 MB
- Stars: 1
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# DAG Schedule Graph
Airflow plugin for visualising DAG schedules within 24 hour window of a day.

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/
```