pyoxigraph
Python bindings of Oxigraph, a SPARQL database and RDF toolkit
Decision gist · record as of 2026-08-14
Yes, with conditions. Pyoxigraph is actively maintained, permissively licensed, and offers a performant SPARQL implementation for Python with no runtime dependencies. However, it is classified as Alpha, so production use should account for potential API changes. Install if you need embedded RDF/SPARQL capabilities; avoid if you require a stable, production-hardened triple store.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.8 or later; compiled wheels are provided for common platforms, but installation on unsupported architectures may require building from source.
- Medium install friction due to compiled wheels; however, prebuilt binaries are available for Python 3.8–3.14 across Linux (x86_64, aarch64), Windows (x86_64, ARM64), and PyPy.
- Repository is actively maintained with recent commits.
License · maintenance · safety
MIT OR Apache-2.0 (permissive) — Dual-licensed under MIT or Apache-2.0 (permissive); you may choose either license. Both permit commercial use, modification, and distribution with minimal restrictions.
last release 2026-06-18 (57 days) · last repo commit 2026-08-13 · 1,817 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 260,019 downloads/mo, #8,400 on PyPI
Alternatives
Verify before relying
pip install pyoxigraph
import pyoxigraph
store = pyoxigraph.Store()
store.add_triple(pyoxigraph.Triple(
pyoxigraph.NamedNode("http://example.org/subject"),
pyoxigraph.NamedNode("http://example.org/predicate"),
pyoxigraph.Literal("object")
))- Performance characteristics and scalability limits for disk-based stores with large datasets
- Comparison of query performance against other SPARQL implementations
- Stability guarantees given 'Alpha' development status classification
What it is and what it does
Pyoxigraph is a Python binding to Oxigraph, a Rust-based RDF and SPARQL toolkit. It offers two store implementations—one held entirely in memory, the other persisted to disk—both capable of executing SPARQL 1.1 queries. The library also includes parsers and serializers for six RDF formats, making it suitable for applications that need to store, query, and transform semantic web data.
The package is written in Rust using PyO3 and built with Maturin, delivering performance-oriented graph operations from Python. It supports Python 3.8 through 3.14 and is distributed via PyPI and conda-forge. The project is actively maintained, with documentation available and community support channels (GitHub discussions, Gitter chat) available for questions.
Use it for
- Build a semantic search engine that queries RDF triples using SPARQL to find relationships between entities
- Parse and validate RDF data in multiple formats (Turtle, JSON-LD, N-Triples) before loading into a knowledge graph
- Store and query linked data locally without external database infrastructure, using the in-memory store for prototyping
- Migrate RDF datasets between formats by reading one format and writing to another using pyoxigraph's conversion utilities
- Implement a knowledge base application that persists triples to disk and executes complex SPARQL queries over time
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, with conditions.
Pyoxigraph is actively maintained, permissively licensed, and offers a performant SPARQL implementation for Python with no runtime dependencies. However, it is classified as Alpha, so production use should account for potential API changes. Install if you need embedded RDF/SPARQL capabilities; avoid if you require a stable, production-hardened triple store.
Install
pyoxigraph on PyPI
Before you install
Medium install friction due to compiled wheels; however, prebuilt binaries are available for Python 3.8–3.14 across Linux (x86_64, aarch64), Windows (x86_64, ARM64), and PyPy. Repository is actively maintained with recent commits.
Requires Python 3.8 or later; compiled wheels are provided for common platforms, but installation on unsupported architectures may require building from source.
License in practice
Dual-licensed under MIT or Apache-2.0 (permissive); you may choose either license. Both permit commercial use, modification, and distribution with minimal restrictions.
Quickstart
pip install pyoxigraph
import pyoxigraph
store = pyoxigraph.Store()
store.add_triple(pyoxigraph.Triple(
pyoxigraph.NamedNode("http://example.org/subject"),
pyoxigraph.NamedNode("http://example.org/predicate"),
pyoxigraph.Literal("object")
))Verify before relying
- Performance characteristics and scalability limits for disk-based stores with large datasets
- Comparison of query performance against other SPARQL implementations
- Stability guarantees given 'Alpha' development status classification
Package facts
| License | MIT OR Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 57 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 260,019 / month, #8,400 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyProgramming Language :: RustTopic :: Database :: Database Engines/ServersTopic :: Software Development :: Libraries :: Python Modules |
Evidence: pyoxigraph-0.5.9-cp310-cp310-manylinux_2_28_aarch64.whl; pyoxigraph-0.5.9-cp310-cp310-manylinux_2_28_x86_64.whl; pyoxigraph-0.5.9-cp310-cp310-win_amd64.whl; pyoxigraph-0.5.9-cp311-cp311-manylinux_2_28_aarch64.whl; pyoxigraph-0.5.9-cp311-cp311-manylinux_2_28_x86_64.whl; pyoxigraph-0.5.9-cp311-cp311-win_amd64.whl; pyoxigraph-0.5.9-cp312-cp312-manylinux_2_28_aarch64.whl; pyoxigraph-0.5.9-cp312-cp312-manylinux_2_28_x86_64.whl; pyoxigraph-0.5.9-cp312-cp312-win_amd64.whl; pyoxigraph-0.5.9-cp312-cp312-win_arm64.whl; pyoxigraph-0.5.9-cp313-cp313-manylinux_2_28_aarch64.whl; pyoxigraph-0.5.9-cp313-cp313-manylinux_2_28_x86_64.whl; pyoxigraph-0.5.9-cp313-cp313t-win_amd64.whl; pyoxigraph-0.5.9-cp313-cp313-win_amd64.whl; pyoxigraph-0.5.9-cp313-cp313-win_arm64.whl; pyoxigraph-0.5.9-cp314-cp314-manylinux_2_28_aarch64.whl; pyoxigraph-0.5.9-cp314-cp314-manylinux_2_28_x86_64.whl; pyoxigraph-0.5.9-cp314-cp314t-manylinux_2_28_aarch64.whl; pyoxigraph-0.5.9-cp314-cp314t-manylinux_2_28_x86_64.whl; pyoxigraph-0.5.9-cp314-cp314t-win_amd64.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “sparql database python”
- pyoxigraphPyoxigraph is a Python library that provides in-memory and disk-based…
- pystardogPython client library for querying and managing Stardog knowledge…
- sparqlslurperTranslates rdflib Graph.triples() calls into SPARQL queries and…
Give your agent the search over MCP, or paste the wish link into any chat.
More Python Modules packages
Converts domain names between Unicode and ASCII-compatible encoding (Punycode) according to IDNA 2008 and Unicode Technical Standard 46, with security validation and broader script coverage than the standard library.
Install it if you work with internationalized domain names, need to validate domains, or use HTTP clients that depend on it transitively.
Setuptools is a Python build backend and package management tool that handles building, distributing, and installing Python packages, including support for C/C++ extension modules.
PyYAML parses and emits YAML 1.1 data format, enabling serialization and deserialization of configuration files and Python objects to and from human-readable YAML text.
Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.
Provides reusable metadata objects for use with PEP-593 `typing.Annotated` to express common constraints like bounds, collection sizes, and predicates on types.
Install it if you use or build libraries that need to express type constraints in a standardized, inspectable way—or if you want to annotate your own types with…
Provides runtime tools to inspect and introspect Python type annotations, enabling programmatic examination of type hints at execution time.
See also rdflib · pymantic · pyshacl · pystardog · sparqlslurper · owlrl · SPARQLWrapper · PyShEx · rdflib-jsonld · graspologic-native