I maintain an R client for the GBIF API, at rgbif. Been working on it for a few years, and recently been thinking that there should be a nice low level client for Python as well. I didn’t see one searching Github, etc. so I started working on one recently: pygbif

It’s up on pypi.

There’s not much in pygbif yet - I wanted to get something up to start getting some users to more quickly make the library useful to people.

There’s three modules, with a few methods each:

  • species
    • name_backbone()
    • name_suggest()
  • registry
    • nodes()
    • dataset_metrics()
    • datasets()
  • occurrences
    • search()
    • get()
    • get_verbatim()
    • get_fragment()
    • count()
    • count_basisofrecord()
    • count_year()
    • count_datasets()
    • count_countries()
    • count_publishingcountries()
    • count_schema()

Here’s a quick intro (in a Jupyter notebook):

Install

pip install pygbif

Registry/datasets

from pygbif import registry
registry.dataset_metrics(uuid='3f8a1297-3259-4700-91fc-acc4170b27ce')

{u'colCoveragePct': 79,
 u'colMatchingCount': 24335,
 u'countByConstituent': {},
 u'countByIssue': {u'BACKBONE_MATCH_FUZZY': 573,
  u'BACKBONE_MATCH_NONE': 1306,
  u'VERNACULAR_NAME_INVALID': 7777},
 u'countByKingdom': {u'ANIMALIA': 30,
  u'FUNGI': 3,
  u'INCERTAE_SEDIS': 26,
  u'PLANTAE': 10997,
  u'PROTOZOA': 1},
 ...
}

Taxonomic names

from pygbif import species
species.name_suggest(q='Puma concolor', limit = 1)

{'data': [{u'canonicalName': u'Puma concolor',
   u'class': u'Mammalia',
   u'classKey': 359,
   u'family': u'Felidae',
   u'familyKey': 9703,
   u'genus': u'Puma',
   u'genusKey': 2435098,
   u'key': 2435099,
   u'kingdom': u'Animalia',
   u'kingdomKey': 1,
   u'nubKey': 2435099,
   u'order': u'Carnivora',
   u'orderKey': 732,
   u'parent': u'Puma',
   u'parentKey': 2435098,
   u'phylum': u'Chordata',
   u'phylumKey': 44,
   u'rank': u'SPECIES',
   u'species': u'Puma concolor',
   u'speciesKey': 2435099}],
 'hierarchy': [{u'1': u'Animalia',
   u'2435098': u'Puma',
   u'359': u'Mammalia',
   u'44': u'Chordata',
   u'732': u'Carnivora',
   u'9703': u'Felidae'}]}

Occurrence data

Search

from pygbif import occurrences
res = occurrences.search(taxonKey = 3329049, limit = 10)
[ x['phylum'] for x in res['results'] ]

[u'Basidiomycota',
 u'Basidiomycota',
 u'Basidiomycota',
 u'Basidiomycota',
 u'Basidiomycota',
 u'Basidiomycota',
 u'Basidiomycota',
 u'Basidiomycota',
 u'Basidiomycota',
 u'Basidiomycota']

Fetch specific occurrences

occurrences.get(key = 252408386)

{u'basisOfRecord': u'OBSERVATION',
 u'catalogNumber': u'70875196',
 u'collectionCode': u'7472',
 u'continent': u'EUROPE',
 u'country': u'United Kingdom',
 u'countryCode': u'GB',
 u'datasetKey': u'26a49731-9457-45b2-9105-1b96063deb26',
 u'day': 30,
...
}

Occurrence counts API

occurrences.count(isGeoreferenced = True)

500283031

feedback

Would love any feedback…