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📛 A Python package for using ontologies, terminologies, and biomedical nomenclatures


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Build Status Current version on PyPI Stable Supported Python Versions MIT License Zenodo Black Code Style Powered by the Bioregistry

Tools for biological identifiers, names, synonyms, xrefs, hierarchies, relations, and properties through the perspective of OBO.

Example Usage

Note! PyOBO is no-nonsense. This means that there's no repetitive prefixes in identifiers. It also means all identifiers are strings, no exceptions.

Note! The first time you run these, they have to download and cache all resources. We're not in the business of redistributing data, so all scripts should be completely reproducible. There's some AWS tools for hosting/downloading pre-compiled versions in if you don't have time for that.

Note! PyOBO can perform grounding in a limited number of cases, but it is not a general solution for named entity recognition (NER) or grounding. It's suggested to check Gilda for a no-nonsense solution.

Mapping Identifiers and CURIEs

Get mapping of ChEBI identifiers to names:

import pyobo

chebi_id_to_name = pyobo.get_id_name_mapping('chebi')

name = chebi_id_to_name['132964']
assert name == 'fluazifop-P-butyl'

Or, you don't have time for two lines:

import pyobo

name = pyobo.get_name('chebi', '132964')
assert name == 'fluazifop-P-butyl'

Get reverse mapping of ChEBI names to identifiers:

import pyobo

chebi_name_to_id = pyobo.get_name_id_mapping('chebi')

identifier = chebi_name_to_id['fluazifop-P-butyl']
assert identifier == '132964'

Maybe you live in CURIE world and just want to normalize something like CHEBI:132964:

import pyobo

name = pyobo.get_name_by_curie('CHEBI:132964')
assert name == 'fluazifop-P-butyl'

Sometimes you accidentally got an old CURIE. It can be mapped to the more recent one using alternative identifiers listed in the underlying OBO with:

import pyobo

# Look up DNA-binding transcription factor activity (go:0003700)
# based on an old id
primary_curie = pyobo.get_primary_curie('go:0001071')
assert primary_curie == 'go:0003700'

# If it's already the primary, it just gets returned
assert 'go:0003700' == pyobo.get_priority_curie('go:0003700')

Mapping Species

Some resources have species information for their term. Get a mapping of WikiPathway identifiers to species (as NCBI taxonomy identifiers):

import pyobo

wikipathways_id_to_species = pyobo.get_id_species_mapping('wikipathways')

# Apoptosis (Homo sapiens)
taxonomy_id = wikipathways_id_to_species['WP254']
assert taxonomy_id == '9606'

Or, you don't have time for two lines:

import pyobo

# Apoptosis (Homo sapiens)
taxonomy_id = pyobo.get_species('wikipathways', 'WP254')
assert taxonomy_id == '9606'


Maybe you've got names/synonyms you want to try and map back to ChEBI synonyms. Given the brand name Fusilade II of CHEBI:132964, it should be able to look it up and its preferred label.

import pyobo

prefix, identifier, name = pyobo.ground('chebi', 'Fusilade II')
assert prefix == 'chebi'
assert identifier == '132964'
assert name == 'fluazifop-P-butyl'

# When failure happens...
prefix, identifier, name = pyobo.ground('chebi', 'Definitely not a real name')
assert prefix is None
assert identifier is None
assert name is None

If you're not really sure which namespace a name might belong to, you can try a few in a row (prioritize by ones that cover the appropriate entity type to avoid false positives in case of conflicts):

import pyobo

# looking for phenotypes/pathways
prefix, identifier, name = pyobo.ground(['efo', 'go'], 'ERAD')
assert prefix == 'go'
assert identifier == '0030433'
assert name == 'ubiquitin-dependent ERAD pathway'


Get xrefs from ChEBI to PubChem:

import pyobo

chebi_id_to_pubchem_compound_id = pyobo.get_filtered_xrefs('chebi', 'pubchem.compound')

pubchem_compound_id = chebi_id_to_pubchem_compound_id['132964']
assert pubchem_compound_id == '3033674'

If you don't have time for two lines:

import pyobo

pubchem_compound_id = pyobo.get_xref('chebi', '132964', 'pubchem.compound')
assert pubchem_compound_id == '3033674'

Get xrefs from Entrez to HGNC, but they're only available through HGNC so you need to flip them:

import pyobo

hgnc_id_to_ncbigene_id = pyobo.get_filtered_xrefs('hgnc', 'ncbigene')
ncbigene_id_to_hgnc_id = {
    ncbigene_id: hgnc_id
    for hgnc_id, ncbigene_id in hgnc_id_to_ncbigene_id.items()
mapt_hgnc = ncbigene_id_to_hgnc_id['4137']
assert mapt_hgnc == '6893'

Since this is a common pattern, there's a keyword argument flip that does this for you:

import pyobo

ncbigene_id_to_hgnc_id = pyobo.get_filtered_xrefs('hgnc', 'ncbigene', flip=True)
mapt_hgnc_id = ncbigene_id_to_hgnc_id['4137']
assert mapt_hgnc_id == '6893'

If you don't have time for two lines (I admit this one is a bit confusing) and need to flip it:

import pyobo

hgnc_id = pyobo.get_xref('hgnc', '4137', 'ncbigene', flip=True)
assert hgnc_id == '6893'

Remap a CURIE based on pre-defined priority list and Inspector Javert's Xref Database:

import pyobo

# Map to the best source possible
mapt_ncbigene = pyobo.get_priority_curie('hgnc:6893')
assert mapt_ncbigene == 'ncbigene:4137'

# Sometimes you know you're the best. Own it.
assert 'ncbigene:4137' == pyobo.get_priority_curie('ncbigene:4137')

Find all CURIEs mapped to a given one using Inspector Javert's Xref Database:

import pyobo

# Get a set of all CURIEs mapped to MAPT
mapt_curies = pyobo.get_equivalent('hgnc:6893')
assert 'ncbigene:4137' in mapt_curies
assert 'ensembl:ENSG00000186868' in mapt_curies

If you don't want to wait to build the database locally for the pyobo.get_priority_curie and pyobo.get_equivalent, you can use the following code to download a release from Zenodo:

import pyobo.resource_utils



Get properties, like SMILES. The semantics of these are defined on an OBO-OBO basis.

import pyobo

# I don't make the rules. I wouldn't have chosen this as the key for this property. It could be any string
chebi_smiles_property = ''
chebi_id_to_smiles = pyobo.get_filtered_properties_mapping('chebi', chebi_smiles_property)

smiles = chebi_id_to_smiles['132964']
assert smiles == 'C1(=CC=C(N=C1)OC2=CC=C(C=C2)O[C@@H](C(OCCCC)=O)C)C(F)(F)F'

If you don't have time for two lines:

import pyobo

smiles = pyobo.get_property('chebi', '132964', '')
assert smiles == 'C1(=CC=C(N=C1)OC2=CC=C(C=C2)O[C@@H](C(OCCCC)=O)C)C(F)(F)F'


Check if an entity is in the hierarchy:

import networkx as nx
import pyobo

# check that go:0008219 ! cell death is an ancestor of go:0006915 ! apoptotic process
assert 'go:0008219' in pyobo.get_ancestors('go', '0006915')

# check that go:0070246 ! natural killer cell apoptotic process is a
# descendant of go:0006915 ! apoptotic process
apopototic_process_descendants = pyobo.get_descendants('go', '0006915')
assert 'go:0070246' in apopototic_process_descendants

Get the subhierarchy below a given node:

# get the descendant graph of go:0006915 ! apoptotic process
apopototic_process_subhierarchy = pyobo.get_subhierarchy('go', '0006915')

# check that go:0070246 ! natural killer cell apoptotic process is a
# descendant of go:0006915 ! apoptotic process through the subhierarchy
assert 'go:0070246' in apopototic_process_subhierarchy

Get a hierarchy with properties pre-loaded in the node data dictionaries:

import pyobo

prop = ''
chebi_hierarchy = pyobo.get_hierarchy('chebi', properties=[prop])

assert 'chebi:132964' in chebi_hierarchy
assert prop in chebi_hierarchy.nodes['chebi:132964']
assert chebi_hierarchy.nodes['chebi:132964'][prop] == 'C1(=CC=C(N=C1)OC2=CC=C(C=C2)O[C@@H](C(OCCCC)=O)C)C(F)(F)F'


Get all orthologies (ro:HOM0000017) between HGNC and MGI (note: this is one way)

>>> import pyobo
>>> human_mapt_hgnc_id = '6893'
>>> mouse_mapt_mgi_id = '97180'
>>> hgnc_mgi_orthology_mapping = pyobo.get_relation_mapping('hgnc', 'ro:HOM0000017', 'mgi')
>>> assert mouse_mapt_mgi_id == hgnc_mgi_orthology_mapping[human_mapt_hgnc_id]

If you want to do it in one line, use:

>>> import pyobo
>>> human_mapt_hgnc_id = '6893'
>>> mouse_mapt_mgi_id = '97180'
>>> assert mouse_mapt_mgi_id == pyobo.get_relation('hgnc', 'ro:HOM0000017', 'mgi', human_mapt_hgnc_id)

Writings Tests that Use PyOBO

If you're writing your own code that relies on PyOBO, and unit testing it (as you should) in a continuous integration setting, you've probably realized that loading all of the resources on each build is not so fast. In those scenarios, you can use some of the pre-build patches like in the following:

import unittest
import pyobo
from pyobo.mocks import get_mock_id_name_mapping

mock_id_name_mapping = get_mock_id_name_mapping({
    'chebi': {
        '132964': 'fluazifop-P-butyl',

class MyTestCase(unittest.TestCase):
    def my_test(self):
        with mock_id_name_mapping:
            # use functions directly, or use your functions that wrap them
            pyobo.get_name('chebi', '1234')


PyOBO can be installed from PyPI with:

$ pip install pyobo

It can be installed in development mode from GitHub with:

$ git clone
$ cd pyobo
$ pip install -e .

Curation of the Bioregistry

In order to normalize references and identify resources, PyOBO uses the Bioregistry. It used to be a part of PyOBO, but has since been externalized for more general reuse.

At src/pyobo/registries/metaregistry.json is the curated "metaregistry". This is a source of information that contains all sorts of fixes for missing/wrong information in MIRIAM, OLS, and OBO Foundry; entries that don't appear in any of them; additional synonym information for each namespace/prefix; rules for normalizing xrefs and CURIEs, etc.

Other entries in the metaregistry:

  • The "remappings"->"full" entry is a dictionary from strings that might follow xref: in a given OBO file that need to be completely replaced, due to incorrect formatting
  • The "remappings"->"prefix" entry contains a dictionary of prefixes for xrefs that need to be remapped. Several rules, for example, remove superfluous spaces that occur inside CURIEs or and others address instances of the GOGO issue.
  • The "blacklists" entry contains rules for throwing out malformed xrefs based on full string, just prefix, or just suffix.


The OBO Foundry seems to be pretty unstable with respect to the URLs to OBO resources. If you get an error like:

pyobo.getters.MissingOboBuild: OBO Foundry is missing a build for: mondo

Then you should check the corresponding page on the OBO Foundry (in this case, and make update to the url entry for that namespace in the Bioregistry.