Tripper

Triplestore wrapper for Python providing a simple and consistent interface to a range of triplestore backends.

Basic concepts

Tripper provides a simple and consistent interface to a range of triplestore backends. It strives for simplicity and is modelled after rdflib (with a few simplifications).

In Tripper:

• All IRIs are represented by Python strings. Example: "https://w3id.org/emmo#Metre"

• Blank nodes are strings starting with "_:". Example: "_:bnode1"

• Literals are constructed with tripper.Literal. Example: tripper.Literal(3.14, datatype=XSD.float)

To make it easy to work with IRIs, provide Tripper a set of pre-defined namespaces, like XSD.float. New namespaces can be defined with the tripper.Namespace class.

A triplestore wrapper is created with the tripper.Triplestore class.

Advanced features

The submodules mappings and convert provide additional functionality beyond interfacing triplestore backends:

• tripper.mappings: traverse mappings stored in the triplestore and find possible mapping routes.
• tripper.convert: convert between RDF and other data representations.

Documentation

• Getting started: See the tutorial
• Discovery of custom backends
• Reference manual

Available backends

The following backends are currently available, either in Tripper or other packages.

Installation

Tripper has by itself no dependencies outside the standard library, but the triplestore backends may have specific dependencies.

The package can be installed from PyPI using pip:

pip install tripper

In addition you would need to install the requirements for one or more of the backends listed in the table above. For mappings you would also need to install Pint. For example:

pip install rdflib pint

License and copyright

All files in this repository are licensed under the MIT license. If not stated otherwise in the top of the files, they have copyright © 2022 SINTEF.

Acknowledgements

We gratefully acknowledge the following projects for supporting the development of Tripper:

• OntoTrans (2020-2024) that receives funding from the European Union's Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 862136.
• OpenModel (2021-2025) that receives funding from the European Union's Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 953167.
• SFI PhysMet (2020-2028) funded by Forskningsrådet and Norwegian industry partners.
• DOME 4.0 (2021-2025) that receives funding from the European Union's Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 953163.
• VIPCOAT (2021-2025) that receives funding from the European Union's Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 952903.
• MEDIATE (2022-2025) that receives funding from the RCN, Norway; FNR, Luxenburg; SMWK Germany via the M-era.net programme, project 9557,
• MatCHMaker (2022-2026) that receives funding from the European Union's Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 101091687.