---
id: bioregistry
version: "0.14.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# bioregistry — Integrated registry of biological databases and nomenclatures

License: permissive · Maintenance: active · Downloads: 173.1K/mo

## What it is and what it does

Bioregistry is a community-maintained meta-registry that aggregates metadata about life science databases, ontologies, and persistent identifier systems. It provides Python functions to normalize biological prefixes (handling case variations and synonyms), parse CURIEs into normalized prefix-identifier pairs, and convert between CURIEs and IRIs using a comprehensive registry of provider URL patterns.

The package is designed for developers working with biological data who need to standardize identifier formats across heterogeneous sources. It handles common prefix variations found in OBO Foundry ontologies, MIRIAM, and other life science standards, and can parse IRIs from OLS, identifiers.org, and other well-known providers back into canonical CURIEs. The underlying registry is automatically updated daily and includes weekly health checks to verify that provider URLs remain functional.

Use it for:

- Normalize biological identifiers from different sources (e.g., 'CHEBI' → 'chebi', 'taxonomy' → 'ncbitaxon')
- Parse a CURIE string into its canonical prefix and local identifier components
- Convert between CURIE and IRI representations for biological resources
- Resolve ambiguous or misspelled biological database prefixes to their canonical forms
- Integrate identifier handling into bioinformatics pipelines that work with multiple ontologies

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Bioregistry provides a unified Python interface to query, normalize, and parse identifiers and CURIEs across life science databases, ontologies, and other biological resources.

Yes. Bioregistry is actively maintained, has no known vulnerabilities, supports current Python versions (3.11+), and solves a real problem in bioinformatics: standardizing identifiers across fragmented biological databases. Low install friction and permissive licensing make it a straightforward addition to life science projects.

## Install

pip install bioregistry
uv add bioregistry
poetry add bioregistry

## Installing bioregistry

Before you install: Low friction installation with 11 runtime dependencies, all standard Python packages. Actively maintained with daily automated updates and weekly health checks; last release 4 days ago.

License in practice: MIT license (permissive) allows free use, modification, and distribution. Manually curated data are available under CC0 1.0 Universal; aggregated data redistributed under their original licenses.

Quickstart:

pip install bioregistry

from bioregistry import normalize_prefix, parse_curie, normalize_curie

# Normalize a prefix variant
assert "chebi" == normalize_prefix("CHEBI")

# Parse a CURIE
assert ("chebi", "1234") == parse_curie("chebi:1234")

# Normalize a full CURIE
assert "chebi:1234" == normalize_curie("CHEBI:1234")

Verify before relying:

- Whether the package supports querying remote Bioregistry endpoints or only works with local/bundled data
- Performance characteristics when working with the full registry of prefixes and identifiers

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 173.1K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

biological identifier normalization, CURIE parsing life science, database prefix registry, ontology identifier resolution, persistent identifier lookup, biomedical database registry, IRI to CURIE conversion, bioinformatics, identifier-normalization, ontology

[View on SkillFed](https://skillfed.io/packages/bioregistry) · [View on PyPI](https://pypi.org/project/bioregistry/)