Skip to main content

A Spec By Example framework for RDF and SPARQL, Inspired by Cucumber.

Project description

== Mustrd

// tag::body[]

image::https://github.com/Semantic-partners/mustrd/raw/python-coverage-comment-action-data/badge.svg[Coverage badge,link="https://github.com/Semantic-partners/mustrd/tree/python-coverage-comment-action-data"]

=== Why?

How do you know your SPARQL, whether it's in a pipeline, or a query, is doing what you intend?

As much as we love RDF and SPARQL and Semantic Tech in general, we found a small gap in tooling which would give us that certainty.

We missed the powerful testing frameworks that have evolved in imperative languages that help ensure you've written code that does what you think it should.

We wanted to be able to:

* setup data scenarios and ensure queries worked as expected
* setup edge cases for queries and ensure they still work
* isolate small sparql enrichment / transformation steps and to know we're only INSERTing what we intend

Enter MustRD.

=== What?

MustRD is a Spec-By-Example ontology, with a reference python implementation, inspired by the likes of Cucumber.

It's designed to be triplestore/SPARQL engine agnostic (aren't open standards *wonderful*!).

=== What it is NOT
MustRD is nothing to do with SHACL, or an alternative to it. In fact, we use SHACL for some of our features.

SHACL provides validation around data.

MustRD provides validation around data transformations.

=== How?
You define your specs in ttl, or trig files.
We use the SBE approach of *Given*, *When*, *Then* to define starting dataset, an action, and a set of expectations. We build up a set of data.
Then, depending on whether your SPARQL is a CONSTRUCT, SELECT or a INSERT/DELETE, we run it, and compare results against a set of expectations (*Then*) that are defined in the same way as a *Given* .
Alternatively, you could define your *Then*

* as an explicit ASK, or
* select; or
* in a higher-order expectation language like you will be used to in various platforms, a set of expectations.


=== When?

Soon. It's a work in progress, and we're building the things *we* need for the projects we work on at multiple clients, with multiple vendor stacks.
We already think it's useful, but it might not meet *your* needs, out of the box.

We invite you to try it, see where it doesn't fit, and raise an issue, or even better, a PR! If you need something custom, please check out our consultancy rates, and we might be able to prioritise a new feature for you.

== Support
We're a specialist consultancy in Semantic Tech, we're putting this out in case it's useful, but if you need more support, kindly contact our business team on info@semanticpartners.com

// tag::body[]
include::src/README.adoc[tags=body]

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mustrd-0.1.3.tar.gz (30.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mustrd-0.1.3-py3-none-any.whl (42.4 kB view details)

Uploaded Python 3

File details

Details for the file mustrd-0.1.3.tar.gz.

File metadata

  • Download URL: mustrd-0.1.3.tar.gz
  • Upload date:
  • Size: 30.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.1 CPython/3.11.7 Windows/10

File hashes

Hashes for mustrd-0.1.3.tar.gz
Algorithm Hash digest
SHA256 be8773abb875459b51968346a92bd01bccc9f382d440e133c109ffcbec38e002
MD5 b29fe87ae0f4a93e084572fffa05c55c
BLAKE2b-256 2d7eda3b7666c2612bf9c09c26937664e9ea443e7ac69ed941c9ccea3339d5f8

See more details on using hashes here.

File details

Details for the file mustrd-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: mustrd-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 42.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.1 CPython/3.11.7 Windows/10

File hashes

Hashes for mustrd-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 b3fe6dd555667085b60a3c0d60f2ce4305ede2d81a071b0c649b1649f195fbae
MD5 fe137a7a26c0cac74870acdc21a3f0bf
BLAKE2b-256 242c8cb21a199682f14b28914c17cdcaef11730f37099bbc8b3c885e104a99c5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page