{"library":"pgvecto-rs","title":"pgvecto-rs Python Binding","description":"Python binding for pgvecto.rs, a vector similarity search extension for PostgreSQL. Current version 0.2.2, requires Python 3.8-3.12. Provides client and ORM integrations for vector operations in PostgreSQL.","language":"python","status":"active","last_verified":"Mon Apr 27","install":{"commands":["pip install pgvecto-rs"],"cli":null},"imports":["from pgvecto_rs import client","from pgvecto_rs.sqlalchemy import SQLModelVector","from pgvecto_rs.sqlalchemy import Vector"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"from pgvecto_rs import client\n\nconn = client.connect(\n    host='localhost',\n    port=5432,\n    user='postgres',\n    password=os.environ.get('PGPASSWORD', ''),\n    database='vectordb'\n)\nconn.execute(\"CREATE EXTENSION IF NOT EXISTS vectors\")\nconn.execute(\"CREATE TABLE IF NOT EXISTS items (id bigserial PRIMARY KEY, embedding vector(3))\")\nconn.execute(\"INSERT INTO items (embedding) VALUES ('[1,2,3]'::vector)\")\nresults = conn.execute(\"SELECT * FROM items ORDER BY embedding <-> '[3,2,1]'::vector LIMIT 5\")\nfor row in results:\n    print(row)","lang":"python","description":"Connect to PostgreSQL, enable pgvecto.rs extension, create a vector table, insert and query vectors.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}