$npx skillfedfor your agent

bioregistry

Integrated registry of biological databases and nomenclatures

Worth itPyPI DatabaseReleased Aug 2026173.1K downloads / moMITPure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — bioregistry-0.14.0-py3-none-any.whl
v0.14.0 · released 2026-08-10 · Python >=3.11 · 11 runtime deps: requests, tqdm, pystow, click, more-click, pydantic, curies, sssom-pydantic

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.AI-flagged interpretation of the facts on this page — verify before relying

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 · maintenance · safety

MIT (permissive) — 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.

last release 2026-08-10 (4 days) · last repo commit 2026-08-10 · 146 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 173,068 downloads/mo, #10,317 on PyPI

Verify before relying

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")
  • 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
Same gist for agents: .md · .json

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 on this page. Verify before relying on it.

Worth it

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

bioregistry on PyPI

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

LicenseMIT permissive
Python supportSupports the current Python release >=3.11
Install frictionLow. Pure-Python wheel
Runtime dependencies
11 packages
requeststqdmpystowclickmore-clickpydanticcuriessssom-pydanticurllib3python-multipartidna
MaintenanceActively maintained 4 days since the last release
Last repo commit
First released
Downloads173,068 / month, #10,317 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 4 - BetaEnvironment :: ConsoleFramework :: PytestFramework :: SphinxFramework :: toxIntended Audience :: DevelopersOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14

Evidence: bioregistry-0.14.0-py3-none-any.whl

Tags

Capabilities
biological identifier normalizationCURIE parsing life sciencedatabase prefix registryontology identifier resolutionpersistent identifier lookupbiomedical database registryIRI to CURIE conversion
Topics
bioinformaticsidentifier-normalizationontology
PyPI keywords
snekpackcookiecutterdatabasesbiological databasesbiomedical databasespersistent identifiers

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 › “biological identifier normalization”

  • bioregistryBioregistry provides a unified Python interface to query, normalize,…
  • deepbiopDeepBioP is a deep learning preprocessing library for biological…
  • rigourRigour provides data cleaning and validation functions for…

Give your agent the search over MCP, or paste the wish link into any chat.

More Database packages

psycopg2-binary Worth it
PyPI · Software Development · released Apr 2026

psycopg2-binary is a PostgreSQL database adapter for Python that implements the DB API 2.0 specification, enabling Python applications to connect to and query PostgreSQL databases with thread-safe concurrent operations.

copyleftcompiled wheel · 3.9+
271.6Mdownloads / mo
redis Worth it
PyPI · Database · released Jul 2026

Python client library for connecting to and executing commands against Redis key-value stores, supporting both synchronous and asynchronous operations.

Install it if your application needs to interact with Redis; the only prerequisite is a running Redis server instance.

MITpure Python · 3.10+
268.3Mdownloads / mo
ydb Worth it
PyPI · Database · released Jul 2026

YDB Python SDK is the official client library for connecting to and querying YDB databases from Python applications.

Install it if you need to connect Python applications to YDB databases.

permissive licensepure Python · 3.10+
210.0Mdownloads / mo
snowflake-connector-python Worth it
PyPI · Software Development · released Aug 2026

Connects Python applications to Snowflake data warehouses using the DB API 2.0 specification, enabling SQL queries, data transfers, and warehouse operations.

Apache-2.0compiled wheel · 3.10+
193.6Mdownloads / mo
sqlparse Worth it
PyPI · Software Development · released Aug 2026

sqlparse tokenizes SQL text into a tree of statements, clauses, and expressions, and provides functions to split scripts, format queries, and inspect parsed tokens without validating dialect or syntax.

Install it if you need to manipulate, format, or analyze SQL text programmatically.

BSD-3-Clausepure Python · 3.10+
148.9Mdownloads / mo
dbt-adapters With conditions
PyPI · Database · released Jul 2026

Provides base adapter protocols and shared functionality that database adapters use to integrate with dbt-core, handling connections, dialect translation, relation caching, and core interface management.

Apache-2.0pure Python · 3.10.0+
121.3Mdownloads / mo

See also bionty · bioversions · curies · isa-rwval · prefixcommons · fastobo · pronto · whoisit · prefixmaps · rfc3987