PyOntoenv

Installation

pip install pyontoenv

Usage

from ontoenv import OntoEnv
from rdflib import Graph

# creates a new environment in the current directory, or loads
# an existing one. To use a different directory, pass the 'path'
# argument: OntoEnv(path="/path/to/env")
# OntoEnv() will discover ontologies in the current directory and
# its subdirectories
env = OntoEnv()

# add an ontology from a file path.
# env.add returns the name of the ontology, which is its URI
# e.g. "https://brickschema.org/schema/1.4-rc1/Brick"
brick_name = env.add("../brick/Brick.ttl")
print(f"Added ontology {brick_name}")

# When you add from a URL whose declared ontology name differs (for example a
# versioned IRI served at a versionless URL), pyontoenv records that alias. You
# can later refer to the ontology by either the canonical name or the original
# URL when resolving imports or querying.

# get the graph of the ontology we just added
# env.get_graph returns an rdflib.Graph
brick_graph = env.get_graph(brick_name)
print(f"Brick graph has {len(brick_graph)} triples")

# get the full closure of the ontology, including all of its imports
# returns a tuple (rdflib.Graph, list[str])
brick_closure_graph, _ = env.get_closure(brick_name)
print(f"Brick closure has {len(brick_closure_graph)} triples")

# you can also add ontologies from a URL
rec_name = env.add("https://w3id.org/rec/rec.ttl")
rec_graph = env.get_graph(rec_name)
print(f"REC graph has {len(rec_graph)} triples")

# if you have an rdflib.Graph with an owl:Ontology declaration,
# you can transitively import its dependencies into the graph
g = Graph()
# this graph just has one triple: the ontology declaration for Brick
g.parse(data="""
@prefix owl: <http://www.w3.org/2002/07/owl#> .
<https://brickschema.org/schema/1.4-rc1/Brick> a owl:Ontology .
""")
# this will load all of the owl:imports of the Brick ontology into 'g'
env.import_dependencies(g)
print(f"Graph with imported dependencies has {len(g)} triples")

Module Command (python -m)

You can initialize an environment without writing any Python by using the module command:

python -m ontoenv.init [options]

This provides a simple, Python-only frontend that mirrors the OntoEnv(...) constructor. It is useful when you don’t want to call into the API directly or use the Rust CLI.

Examples:

• Create (or overwrite) an env at a path:
  • python -m ontoenv.init --path ./myproj --recreate
• Initialize a temporary (in-memory) env for quick tasks:
  • python -m ontoenv.init --temporary --root .
• Open an existing env in read-only mode:
  • python -m ontoenv.init --path ./myproj --read-only
• Discover ontologies under a search directory when initializing:
  • python -m ontoenv.init --path ./myproj --recreate --search-dir ./brick

Arguments (mirror OntoEnv kwargs):

• --path PATH: Root directory where .ontoenv lives or will be created
• --recreate: Create or overwrite an env at --path
• --read-only: Open the env in read-only mode
• --search-dir DIR: Directory to search for ontologies (repeatable)
• --require-ontology-names: Require explicit ontology names
• --strict: Enable strict mode (treat resolution failures as errors)
• --offline: Disable network access for resolution
• --resolution-policy NAME: Resolution policy to use (default: default)
• --root DIR: Discovery start directory when not recreating (default: .)
• --include PATTERN: Include pattern for discovery (repeatable)
• --exclude PATTERN: Exclude pattern for discovery (repeatable)
• --temporary: Use an in-memory environment (no files created)
• --no-search: Disable local directory search

Behavior:

• Prints the environment store path on success when persisted (non-temporary).
• Exits with code 0 on success; on error prints a message and exits non‑zero.