TOSCA Parser 0.5.1 & Types v. 1.0.1
The TOSCA Parser is an OpenStack project and licensed under Apache 2. It is developed to parse TOSCA Simple Profile in YAML. It reads the TOSCA templates and creates an in-memory graph of TOSCA nodes and their relationship.
- more information on its Architecture can be found in the README
The INDIGO TOSCA Types repository shows a YAML description of new types added in the INDIGO project to extend TOSCA Simple Profile in YAML Version 1.0 to add high level entities. In the examples directory there are a set of TOSCA documents using these types that will be supported by the INDIGO components.
- The TOSCA Parser now supports profile definition extensions that can be accessed via a custom tosca_definitions_version. Extensions can be added by creating a module in the "toscaparser/extensions" directory. See the "nfv" module for an example.
- Release Notes
This is the first release of TOSCA Parser and Types - entirely developed through the INDIGO-DC project
Highlight of the first release in INDIGO:
- Contributed several bug fixes to the OpenStack's tosca-parser project.
- INDIGO-DataCloud partners (UPV) rank #2 in the top commiters for the tosca-parser in OpenStack Liberty
- Included new non-normative types for the TOSCA Simple Profile in YAML Version 1.0 specification, supporting both INDIGO-DataCloud applications (e.g. Kepler, Galaxy, Disvis, Powerfit, etc.) and capabilities (e.g. virtual elastic clusters).
- CentOS7 & Ubuntu 14:04, OpenStack
List of RfCs
- TOSCA types: - list of solved issues can be found in GitHub Issues List
TOSCA-parser: - list of solved issues can be found in GitHub Issues List
Comprehensive list of bug fixes is available here
After setting the INDIGO-DC repositories as explained in the Generic Installation & Configuration Guide:
On CentOS 7
$ yum clean all
$ yum install tosca-parser
On Ubuntu 14.04 - after setting the INDIGO-DC repositories as explained in the Generic Installation & Configuration Guide:
$ apt-get update
$ apt-get install python-tosca-parser
List of Artifacts
- Please use the INDIGO - DataCloud CatchAll GGUS Support Unit