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
pip install dag-schedule-graph
Trying it out using Docker
# 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
# 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/
Metadata
Release files for dag-schedule-graph 0.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dag-schedule-graph-0.2.2.tar.gz | 110.7 kB | Details |
Release files / dag-schedule-graph-0.2.2.tar.gz
| Download URL | dag-schedule-graph-0.2.2.tar.gz |
|---|---|
| Size | 110.7 kB |
| Tags | Source |
|
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twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/50.3.2.post20201201 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.7.9
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