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 .venv
$ source ./.venv/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 -a -j -f human /path/to/dataGraph.ttl
Where
-s
is an (optional) path to the shapes graph to use-e
is an (optional) path to an extra ontology graph to import-i
is the pre-inferencing option-f
is the ValidationReport output format (human
= human-readable validation report)-m
enable the meta-shacl feature-a
enable SHACL Advanced Features-j
enable SHACL-JS Features (ifpyhsacl[js]
is installed)
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:
usage: pyshacl [-h] [-s [SHACL]] [-e [ONT]] [-i {none,rdfs,owlrl,both}] [-m]
[--imports] [--abort] [-a] [-j] [-d] [-f {human,turtle,xml,json-ld,nt,n3}]
[-df {auto,turtle,xml,json-ld,nt,n3}]
[-sf {auto,turtle,xml,json-ld,nt,n3}]
[-ef {auto,turtle,xml,json-ld,nt,n3}] [-V] [-o [OUTPUT]]
DataGraph
Run the pySHACL validator from the command line.
positional arguments:
DataGraph The file containing the Target Data Graph.
optional arguments:
-h, --help show this help message and exit
-s [SHACL], --shacl [SHACL]
A file containing the SHACL Shapes Graph.
-e [ONT], --ont-graph [ONT]
A file path or URL to a docucument containing extra
ontological information to mix into the data graph.
-i {none,rdfs,owlrl,both}, --inference {none,rdfs,owlrl,both}
Choose a type of inferencing to run against the Data
Graph before validating.
-m, --metashacl Validate the SHACL Shapes graph against the shacl-
shacl Shapes Graph before before validating the Data
Graph.
--imports Allow import of sub-graphs defined in statements with
owl:imports.
-a, --advanced Enable support for SHACL Advanced Features.
-j, --js Enable support for SHACL-JS Features.
--abort Abort on first error.
-d, --debug Output additional runtime messages, including violations that didn\'t
lead to non-conformance.
-f {human,turtle,xml,json-ld,nt,n3}, --format {human,turtle,xml,json-ld,nt,n3}
Choose an output format. Default is "human".
-df {auto,turtle,xml,json-ld,nt,n3}, --data-file-format {auto,turtle,xml,json-ld,nt,n3}
Explicitly state the RDF File format of the input
DataGraph file. Default="auto".
-sf {auto,turtle,xml,json-ld,nt,n3}, --shacl-file-format {auto,turtle,xml,json-ld,nt,n3}
Explicitly state the RDF File format of the input
SHACL file. Default="auto".
-ef {auto,turtle,xml,json-ld,nt,n3}, --ont-file-format {auto,turtle,xml,json-ld,nt,n3}
Explicitly state the RDF File format of the extra
ontology file. Default="auto".
-V, --version Print the PySHACL version and exit.
-o [OUTPUT], --output [OUTPUT]
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(data_graph, shacl_graph=sg, ont_graph=og, inference='rdfs', abort_on_error=False, meta_shacl=False, advanced=False, js=False, debug=False)
conforms, results_graph, results_text = r
Where:
data_graph
is an rdflibGraph
object or file path of the graph to be validatedshacl_graph
is an rdflibGraph
object or file path or Web URL of the graph containing the SHACL shapes to validate with, or None if the SHACL shapes are included in the data_graph.ont_graph
is an rdflibGraph
object or file path or Web URL a graph containing extra ontological information, or None if not required.inference
is a Python string value to indicate whether or not to perform OWL inferencing expansion of thedata_graph
before validation. Options are 'rdfs', 'owlrl', 'both', or 'none'. The default is 'none'.abort_on_error
(optional) a Pythonbool
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 Pythonbool
value to indicate whether or not the program should enable the Meta-SHACL feature. Default is False.advanced
: (optional) a Pythonbool
value to enable SHACL Advanced Featuresjs
: (optional) a Pythonbool
value to enable SHACL-JS Features (ifpyshacl[js]
is installed)debug
(optional) a Pythonbool
value to indicate whether or not the program should emit debugging output text, including violations that didn't lead to non-conformance overall. So when debug is True don't judge conformance by absense of violation messages. Default is False.
Some other optional keyword variables available available on the validate
function:
data_graph_format
: Override the format detection for the given data graph source file.shacl_graph_format
: Override the format detection for the given shacl graph source file.ont_graph_format
: Override the format detection for the given extra ontology graph source file.do_owl_imports
: Enable the feature to allow the import of subgraphs usingowl:imports
for the shapes graph and the ontology graph. Note, you explicitly cannot use this on the target data graph.serialize_report_graph
: Convert the report results_graph into a serialised representation (for example, 'turtle')check_dash_result
: Check the validation result against the given expected DASH test suite result.check_sht_result
: Check the validation result against the given expected SHT test suite result.
Return value:
- a three-component
tuple
containing:conforms
: abool
, indicating whether or not thedata_graph
conforms to theshacl_graph
results_graph
: aGraph
object built according to the SHACL specification's Validation Report structureresults_text
: python string representing a verbose textual representation of the Validation Report
Python Module Call
You can get an equivalent of the Command Line Tool using the Python3 executable by doing:
python3 -m pyshacl
Errors
Under certain circumstances pySHACL can produce a Validation Failure
. This is a formal error defined by the SHACL specification and is required to be produced as a result of specific conditions within the SHACL graph.
If the validator produces a Validation Failure
, the results_graph
variable returned by the validate()
function will be an instance of ValidationFailure
.
See the message
attribute on that instance to get more information about the validation failure.
Other errors the validator can generate:
ShapeLoadError
: This error is thrown when a SHACL Shape in the SHACL graph is in an invalid state and cannot be loaded into the validation engine.ConstraintLoadError
: This error is thrown when a SHACL Constraint Component is in an invalid state and cannot be loaded into the validation engine.ReportableRuntimeError
: An error occurred for a different reason, and the reason should be communicated back to the user of the validator.RuntimeError
: The validator encountered a situation that caused it to throw an error, but the reason does concern the user.
Unlike ValidationFailure
, these errors are not passed back as a result by the validate()
function, but thrown as exceptions by the validation engine and must be
caught in a try ... except
block.
In the case of ShapeLoadError
and ConstraintLoadError
, see the str()
string representation of the exception instance for the error message along with a link to the relevant section in the SHACL spec document.
Windows CLI
Pyinstaller can be
used to create an
executable for Windows that has the same characteristics as the Linux/Mac
CLI program.
The necessary .spec
file is already included in pyshacl/pyshacl-cli.spec
.
The pyshacl-cli.spec
PyInstaller spec file creates a .exe
for the
pySHACL Command Line utility. See above for the pySHACL command line util usage instructions.
See the PyInstaller installation guide for info on how to install PyInstaller for Windows.
Once you have pyinstaller, use pyinstaller to generate the pyshacl.exe
CLI file like so:
$ cd src/pyshacl
$ pyinstaller pyshacl-cli.spec
This will output pyshacl.exe
in the dist
directory in src/pyshacl
.
You can now run the pySHACL Command Line utility via pyshacl.exe
.
See above for the pySHACL command line util usage instructions.
Compatibility
PySHACL is a Python3 library. For best compatibility use Python v3.6 or greater. Python3 v3.5 or below is not supported and this library does not work on Python v2.7.x or below.
PySHACL is now a PEP518 & PEP517 project, it uses pyproject.toml
and poetry
to manage dependencies, build and install.
For best compatibility when installing from PyPI with pip
, upgrade to pip v18.1.0 or above.
- If you're on Ubuntu 16.04 or 18.04, you will need to run
sudo pip3 install --upgrade pip
to get the newer version.
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 [email protected] http://orcid.org/0000-0002-8742-7730
Lead Developer: Ashley Sommer Informatics Software Engineer CSIRO Land & Water, Environmental Informatics Group Brisbane, Qld, Australia [email protected] https://orcid.org/0000-0003-0590-0131