Example: Storing an ontology

This tutorial will show you how to store an ontology, via its JSON representation.

[11]:

import pandas as pd
import pystow

[12]:

path=pystow.ensure("tmp", "eccode.json", url="https://w3id.org/biopragmatics/resources/eccode/eccode.json")

[13]:

import json

graphdoc = json.load(open(path))
graph = graphdoc["graphs"][0]

[14]:

len(graph["nodes"]), len(graph["edges"])

[14]:

(7177, 506022)

[15]:

!rm -f /tmp/eccode.db

[16]:

from linkml_store import Client

client = Client()
db = client.attach_database("duckdb:////tmp/eccode.db", "eccode")

[17]:

nodes_collection = db.create_collection("Node", "nodes")

[18]:

nodes_collection.insert(graph["nodes"])

[19]:

from linkml_store.index.implementations.llm_index import LLMIndex

index = LLMIndex(name="test")

[20]:

nodes_collection.attach_index(index)

[21]:

qr = nodes_collection.search("sugar transporters")

[22]:

results = [{"sim": r[0], "id": r[1]["id"], "name": r[1]["lbl"]} for r in qr.ranked_rows]

[23]:

import pandas as pd
df = pd.DataFrame(results)

[24]:

df

[24]:

	sim	id	name
0	0.797146	http://purl.obolibrary.org/obo/eccode_7.5.2.2	ABC-type oligosaccharide transporter
1	0.792401	http://purl.obolibrary.org/obo/eccode_7.5.2.1	ABC-type maltose transporter
2	0.791971	http://purl.obolibrary.org/obo/eccode_7.3.2.3	ABC-type sulfate transporter
3	0.791232	http://purl.obolibrary.org/obo/eccode_7.5.2.11	ABC-type D-galactose transporter
4	0.789132	http://purl.obolibrary.org/obo/eccode_7.6.2.12	ABC-type capsular-polysaccharide transporter
...	...	...	...
7172	0.673991	http://purl.obolibrary.org/obo/eccode_3.4.22.57	caspase-4
7173	0.673331	http://purl.obolibrary.org/obo/eccode_3.4.22.63	caspase-10
7174	0.670908	http://purl.obolibrary.org/obo/eccode_1.14.99	Miscellaneous
7175	0.668042	http://purl.obolibrary.org/obo/eccode_3.4.24.4	3.4.24.30, 3.4.24.31, 3.4.24.32, 3.4.24.39 and...
7176	0.663048	http://www.geneontology.org/formats/oboInOwl#h...	has_obo_format_version

7177 rows × 3 columns

[24]: