Awesome
Standard Energy Efficiency Data (SEED) Platform™
The SEED Platform is a web-based application that helps organizations easily manage data on the energy performance of large groups of buildings. Users can combine data from multiple sources, clean and validate it, and share the information with others. The software application provides an easy, flexible, and cost-effective method to improve the quality and availability of data to help demonstrate the economic and environmental benefits of energy efficiency, to implement programs, and to target investment activity.
The SEED application is written in Python/Django, with AngularJS, Bootstrap, and other javascript libraries used for the front-end. The back-end database is required to be PostgreSQL.
The SEED web application provides both a browser-based interface for users to
upload and manage their building data, as well as a full set of APIs that app
developers can use to access these same data management functions. From a
running server, the Swagger API documentation can be found at /api/swagger
or from the front end by clicking the API documentation link in the sidebar.
Installation
- Production on Amazon Web Service: See Installation Notes
- Development on Mac OSX: Installation Notes
- Development using Docker: Installation Notes
Starting SEED Platform
In production the following two commands will run the web server (uWSGI) and the background task manager (Celery) with:
bin/start_uwsgi.sh
bin/start_celery.sh
In development mode, you can start the web server (uWSGI) and the background task manager (Celery) with:
./manage.py runserver
celery -A seed worker -l INFO -c 4 --max-tasks-per-child 1000 -EBS django_celery_beat.schedulers:DatabaseScheduler
Developer Resources
- Source code documentation is on the SEED website and there are links to [older versions][code-documentations-links] as needed.
- Several notes regarding Django and AngularJS integration: See Developer Resources
Testing
- Running tests: See Testing Notes
Copyright
See the information in the LICENSE.md file.