pySHACL

A Python validator for SHACL.

This is a pure Python module which allows for the validation of RDF graphs against Shapes Constraint Language (SHACL) graphs. This module uses the rdflib Python library for working with RDF and is dependent on the OWL-RL Python module for OWL2 RL Profile-based expansion of data graphs.

This module is developed to adhere to the SHACL Recommendation:

Holger Knublauch; Dimitris Kontokostas. Shapes Constraint Language (SHACL). 20 July 2017. W3C Recommendation. URL: https://www.w3.org/TR/shacl/ ED: https://w3c.github.io/data-shapes/shacl/

Installation

Install with PIP (Using the Python3 pip installer pip3)

$ pip3 install pyshacl

Or in a python virtualenv (these example commandline instructions are for a Linux/Unix based OS)

$ python3 -m virtualenv --python=python3 --no-site-packages shaclvenv
$ source ./shaclvenv/bin/activate
$ pip3 install pyshacl

To exit the virtual enviornment:

$ deactivate

Command Line Use

For command line use:
(these example commandline instructions are for a Linux/Unix based OS)

pyshacl -s /path/to/shapesGraph.ttl -m -i rdfs -f human /path/to/dataGraph.ttl

Where

-s is an (optional) path to the shapes graph to use
-i is the pre-inferencing option
-f is the ValidationReport output format (human = human-readable validation report)
-m enable the meta-shacl feature

System exit codes are:
0 = DataGraph is Conformant
1 = DataGraph is Non-Conformant
2 = The validator encountered a RuntimeError (check stderr output for details)
3 = Not-Implemented; The validator encountered a SHACL feature that is not yet implemented.

Full CLI Usage options:

pyshacl [-h] [-s [SHACL]] [-i {none,rdfs,owlrl,both}] [-m] [-a] [-d]
               [-f {human,turtle,xml,json-ld,nt}] [-o [OUTPUT]]
               DataGraph

positional arguments:
  DataGraph             The file containing the Target Data Graph.

optional arguments:
  -h, --help            show this help message and exit
  -s [SHACL], --shacl [SHACL]
                        [Optional] The file containing the SHACL Shapes Graph.
  -i {none,rdfs,owlrl,both}, --inference {none,rdfs,owlrl,both}
                        [Optional] Choose a type of inferencing to run against
                        the Data Graph before validating.
  -m, --metashacl       [Optional] Validate the SHACL Shapes graph against the
                        shacl-shacl Shapes Graph before before validating the
                        Data Graph.
  -a, --abort           [Optional] Abort on first error.
  -d, --debug           [Optional] Output additional runtime messages.
  -f {human,turtle,xml,json-ld,nt}, --format {human,turtle,xml,json-ld,nt}
                        [Optional] Choose an output format. Default is
                        "human".
  -o [OUTPUT], --output [OUTPUT]
                        [Optional] Send output to a file (defaults to stdout).

Python Module Use

For basic use of this module, you can just call the validate function of the pyshacl module like this:

from pyshacl import validate
r = validate(target_graph, shacl_graph, inference='rdfs', abort_on_error=False, meta_shacl=False, debug=False)
conforms, results_graph, results_text = r

where:

target_graph is an rdflib Graph object, the graph to be validated
shacl_graph is an rdflib Graph object, the graph containing the SHACL shapes to validate with, or None if the SHACL shapes are included in the target_graph.
inference is a Python string value to indicate whether or not to perform OWL inferencing expansion of the target_graph before validation. Options are 'rdfs', 'owlrl', 'both', or 'none'. The default is 'none'.
abort_on_error (optional) a Python bool value to indicate whether or not the program should abort after encountering a validation error or to continue. Default is to continue.
meta_shacl (optional) a Python bool value to indicate whether or not the program should enable the Meta-SHACL feature. Default is False.
debug (optional) a Python bool value to indicate whether or not the program should emit debugging output text. Default is False.

on return:

a three-component tuple containing:
- conforms a bool, indicating whether or not the target_graph conforms to the shacl_graph
- results_graph an rdflib Graph object built according to the SHACL specification's Validation Report semantics
- results_text python string representing a verbose textual representation of the Validation Report

PySHACL is a Python3 library. For best compatibility use Python v3.5 or greater. This library does not work on Python 2.7.x or below.

Features

A features matrix is kept in the FEATURES file.

Changelog

A comprehensive changelog is kept in the CHANGELOG file.

Benchmarks

This project includes a script to measure the difference in performance of validating the same source graph that has been inferenced using each of the four different inferencing options. Run it on your computer to see how fast the validator operates for you.

License

This repository is licensed under Apache License, Version 2.0. See the LICENSE deed for details.

Contributors

See the CONTRIBUTORS file.

Contacts

Project Lead:
Nicholas Car
Senior Experimental Scientist
CSIRO Land & Water, Environmental Informatics Group
Brisbane, Qld, Australia
nicholas.car@csiro.au
http://orcid.org/0000-0002-8742-7730

Lead Developer:
Ashley Sommer
Software Engineer
CSIRO Land & Water, Environmental Informatics Group
Brisbane, Qld, Australia
Ashley.Sommer@csiro.au

Release files for pyshacl 0.9.4.post1

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