Skip to main content

Python implementation of the Eyeling Notation3 reasoner

Project description

pyling

PyPI version Python versions License

pyling is a Python port of the Eyeling Notation3 reasoner. Install it from PyPI as pyling-n3, import it as pyling, and use it to run N3 rules over RDF data from Python code, notebooks, or the command line.

It is useful when you want a small Python dependency for:

  • deriving facts with Notation3 rules
  • mixing N3 reasoning with RDFLib graphs
  • reading Turtle, TriG, N-Triples, and N-Quads through RDFLib
  • checking RDF 1.2 surface syntax in Python tooling
  • replaying RDF Message Logs as whole logs or as message streams

The Eyeling repositories remain the main implementation; pyling gives Python projects a native package interface to the same style of N3 reasoning.

Install in your project

Install the published package from PyPI:

python -m pip install pyling-n3

With project-oriented package managers:

uv add pyling-n3
poetry add pyling-n3
pdm add pyling-n3

The distribution package is named pyling-n3; the Python import package and CLI command remain pyling.

from pyling import reason

program = """
@prefix : <http://example.org/> .

:Socrates a :Man .
{ ?x a :Man } => { ?x a :Mortal } .
"""

print(reason(program))
pyling rules-and-facts.n3

For an unreleased development snapshot, install directly from GitHub:

python -m pip install "pyling-n3 @ git+https://github.com/eyereasoner/pyling.git"
uv add "pyling-n3 @ git+https://github.com/eyereasoner/pyling.git"

Requirements

  • Python 3.10 or newer
  • rdflib, installed automatically with pyling-n3
  • pytest, needed only for the test suite

Install from a checkout

cd pyling
python -m venv .venv
. .venv/bin/activate        # Windows: .venv\Scripts\activate
python -m pip install --upgrade pip
python -m pip install -e ".[test]"

Verify the install:

pyling --help
python -m pytest -q

Command-line usage

Run a simple N3 rule program from standard input:

cat > example.n3 <<'EOF'
@prefix : <http://example.org/> .

:Socrates a :Man .
{ ?x a :Man } => { ?x a :Mortal } .
EOF

pyling example.n3

Expected derived output:

@prefix : <http://example.org/> .

:Socrates a :Mortal .

Include explicit input facts in the rendered closure:

pyling --include-input-facts example.n3

Read multiple sources, such as facts plus rules:

pyling facts.n3 rules.n3

Enable RDF/Turtle/TriG/RDF Message compatibility mode:

pyling --rdf data.trig rules.n3

Force a line format:

pyling --rdf --input-format nt data.nt

pyling --rdf --input-format nquads data.nq

Python API

from pyling import reason, reason_stream, run_async

program = """
@prefix : <http://example.org/> .
:a :p :b .
{ ?s :p ?o } => { ?s :q ?o } .
"""

print(reason(program))

result = reason_stream(program, include_input_facts_in_closure=True)
print(result.closure_n3)
print(result.derived)

Multi-source input mirrors Eyeling’s source-list style:

from pyling import reason

out = reason({
    "sources": [
        "@prefix : <http://example.org/> .\n:Socrates a :Man .\n",
        "@prefix : <http://example.org/> .\n{ ?x a :Man } => { ?x a :Mortal } .\n",
    ]
})

The main exported term classes are Iri, Literal, Var, Blank, ListTerm, GraphTerm, Triple, Rule, and PrefixEnv.

Notebook examples

Publishable notebooks live in docs/notebooks/:

Run them locally with:

python -m pip install -e ".[docs]"
jupyter lab docs/notebooks

GitHub Actions executes the notebooks and converts them to HTML in the Notebook docs workflow. Pull requests upload the generated notebook-site artifact; pushes to main also publish the same site/ output through GitHub Pages when Pages is enabled for GitHub Actions.

RDF and RDF 1.2 compatibility

RDF mode is selected with --rdf on the CLI or {"rdf": True} in the API. It routes ordinary RDF syntax through rdflib instead of the N3 rule parser:

from pyling import reason

rdf = """
PREFIX : <http://example.org/>
:a :p :b .
"""

print(reason(rdf, rdf=True, include_input_facts_in_closure=True))

RDFLib graphs can also be passed directly:

from rdflib import Graph, Namespace
from pyling import reason_graph

ex = Namespace("http://example.org/")
g = Graph()
g.bind("", ex)
g.add((ex.a, ex.p, ex.b))

closure = reason_graph(g, include_input_facts_in_closure=True)
print(closure.serialize(format="turtle"))

Supported compatibility inputs include:

  • Turtle / .ttl
  • TriG / .trig
  • N-Triples / .nt
  • N-Quads / .nq
  • uppercase PREFIX, BASE, and RDF 1.2 VERSION surface forms
  • simple RDF 1.2 annotation syntax, preserving the asserted triple
  • RDF Message Logs using VERSION "1.2-messages" and MESSAGE

The RDF 1.2 layer includes strict surface checks for common negative conformance cases such as surrogate numeric escapes, invalid RDF 1.2 language tags in line syntaxes, relative IRIREFs in N-Triples/N-Quads, and annotation syntax in line syntaxes.

Run the bundled offline RDF 1.2 smoke suite:

python tools/run_rdf12_w3c.py

Run the W3C RDF 1.2 syntax compliance manifests (requires Node.js and network access on the first run):

npm ci
npm run spec

The W3C runner caches downloaded manifests and fixtures in .rdf-test-suite-cache/. All RDF 1.2 syntax cases in the configured N-Triples, N-Quads, Turtle, and TriG manifests are enabled.

Performance comparisons

See the performance report for measured comparisons with Eyeling, FuXi, and owlrl, including which runs completed, whether their outputs were comparable, the benchmark method, and reproduction commands.

npm run perf -- --list
npm run perf -- --case=socrates --reasoner=pyling,eyeling,fuxi
EYELING_PATH=../eyeling npm run perf:eyeling-examples

RDF Message Logs

Whole-log replay:

cat > messages.trig <<'EOF'
VERSION "1.2-messages"
PREFIX : <http://example.org/>

:a :value 21 .

MESSAGE

# Empty heartbeat message.

MESSAGE

:b :value 22 .
EOF

pyling --rdf --include-input-facts messages.trig

Streaming replay, one message envelope at a time:

pyling --rdf --stream-messages rules.n3 messages.trig

Python streaming API:

from pyling import reason_message_stream

for result in reason_message_stream({"sources": [rules_n3, messages_trig]}):
    print(result.closure_n3)

The QUDT notebook shows this API applying automatic unit-normalization rules independently to each message.

The replay vocabulary uses:

@prefix eymsg: <https://eyereasoner.github.io/eyeling/vocab/message#> .

It materializes stream/envelope metadata, eymsg:orderedEnvelopes, eymsg:messageCount, eymsg:payloadKind, and payload formula links through log:nameOf. Rules can inspect each payload graph with log:includes.

Built-ins

The package includes the built-in registry API:

from pyling import register_builtin, unregister_builtin, list_builtin_iris

Built-in coverage includes common predicates in these namespaces:

  • math: numeric comparison and arithmetic, plus common trig functions
  • string: contains/matches/replace/format/length/comparison helpers
  • list: first/rest/member/append/reverse/sort and related helpers
  • log: includes/notIncludes/content/semantics/semanticsOrError/conjunction, plus skolem/URI and equality helpers
  • dt: datatype inspection, validation, value comparison, canonicalization
  • crypto: md5/sha/sha256/sha512
  • time: year/month/day/hour/minute/second/timeZone/localTime

log:content retrieves an HTTP(S) resource as a string. log:semantics retrieves and parses an N3 document as a formula, resolving relative IRIs against the final URL after redirects. Requests send N3/RDF Accept headers and a versioned User-Agent, use a 30-second timeout, and reject responses larger than 32 MiB. log:semanticsOrError binds an error string when retrieval or parsing fails.

HTTP dereferencing can access any network location reachable by the process. Applications handling untrusted N3 should restrict access with Python urllib audit hooks or a custom installed opener, following RDFLib's security guidance.

Registering a custom built-in:

from pyling import Literal, XSD_NS, register_builtin


def hello(ctx):
    return [ctx.unify_term(ctx.goal.o, Literal("world", XSD_NS + "string"), ctx.subst)]

register_builtin("http://example.org/custom#hello", hello)

Stores

The synchronous API uses in-memory reasoning. run_async(..., {"store": ...}) can persist explicit and inferred triples through the included JSON-backed persistent store.

import asyncio
from pyling import run_async

async def main():
    result = await run_async(program, {"store": {"name": "demo", "path": ".eyeling-store", "clear": True}})
    await result.store.close()

asyncio.run(main())

Tests

Run the package tests:

python -m pytest -q

Run the offline RDF 1.2 compatibility smoke suite:

python tools/run_rdf12_w3c.py

Run the W3C RDF 1.2 compliance tests:

npm ci
npm run spec

Run the external phochste/notation3tests suite when you have network access or an existing checkout:

# Existing checkout
python tools/run_notation3tests.py /path/to/notation3tests

# Or let the runner clone and install the public suite at https://codeberg.org/phochste/notation3tests
python tools/run_notation3tests.py --clone

The runner defaults to NETWORKING=1 so the networking fixtures for log:content, log:semantics, and log:semanticsOrError are included. Set NETWORKING=0 explicitly for an offline conformance run.

You can also have pytest run the external suite by setting:

NOTATION3TESTS_DIR=/path/to/notation3tests python -m pytest -q

Notes

  • rdflib is used only for RDF/Turtle/TriG/N-Triples/N-Quads parsing. N3 rules and formulas are parsed by the local parser.
  • RDF Message Logs are split and replayed before reasoning so message boundaries, empty heartbeat messages, and per-message blank-node scope are preserved.
  • Packaging and publishing it on Pypi happens via a github action: create a new tag and release. Make sure the pyproject.toml is correct.

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

pyling_n3-0.1.3.tar.gz (80.9 kB view details)

Uploaded Source

Built Distribution

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

pyling_n3-0.1.3-py3-none-any.whl (67.4 kB view details)

Uploaded Python 3

File details

Details for the file pyling_n3-0.1.3.tar.gz.

File metadata

  • Download URL: pyling_n3-0.1.3.tar.gz
  • Upload date:
  • Size: 80.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.14

File hashes

Hashes for pyling_n3-0.1.3.tar.gz
Algorithm Hash digest
SHA256 eda7d216a9281da7ffaf48e698cc680fe066ad4c71e979430f3e6adabdff3118
MD5 57541de2588a135335875c1ed21bcaa3
BLAKE2b-256 5fed19d52fe5b960dde405baecfc058fc336ef2b8cd0b924fdb32d7bd5779e06

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyling_n3-0.1.3.tar.gz:

Publisher: package.yml on eyereasoner/pyling

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file pyling_n3-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: pyling_n3-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 67.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.14

File hashes

Hashes for pyling_n3-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 cb668d1c139ced7607dc3f21a98ef52f47af8ff1bbf851283feecd8b63053f3e
MD5 3c2a3c2d0e394dc9882363954a45829f
BLAKE2b-256 d71958d638a64a9dc04a80f2aef0a752925259aac17a90a027558920ca84d8a2

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyling_n3-0.1.3-py3-none-any.whl:

Publisher: package.yml on eyereasoner/pyling

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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