Build of the Pfeffernusse (RESTful Spice) microservice.
901
This project uses the NAIF supplied spice data and exposes it as a RESTful service. This is a prototype proof of concept with no documentation. As an alpha product, Pfeffernusse is not ready for production. The functionality of pfeffernusse is also currently conflated some with the SpiceRack project. In coming releases we will separate these microservices with spicerack supporting management of kernels, distributed synchronization, and a light RESTful API to report kernel availability. This project will then be able to focus on exploitation of the kernels and generation of higher order data packages, e.g., a Community Sensor Model compliant Image Support Data (ISD) blob.
The module depends on:
spiceypy
flask
sqlalchemy
numpy
Optionally, to run the example ipython notebooks.
python setup.py develop# To get the pfeffernusse module installedpython run.py
then in a browser navigate to localhost:5000. The app is running in debug mode by default (can be changed at the end of run.py).
This is how we intend Pfeffernusse to be deployed. Simply running the following will get Pfeffernusse up and running as a Docker container.
docker run -p <hostport>:5000 -v <host_spice_root>:/spice/data usgsastro/pfeffernusse
The app assumes that spice data is stored in /data/spice. This is done intentionally as we intend the application to be run as a containerized microservice. If you will to change the root directory:
/bin/create_spice_db.py change the ROOT to the desired root.mk.db and rerun /bin/create_spice_db.py to update the PATH info that is being stored in the database.Content type
Image
Digest
Size
337.9 MB
Last updated
about 8 years ago
docker pull jlaura/restful-spice