{"categories":[{"label":"Database","url":"https://skillfed.io/packages/category/database/3"}],"enrichment":{"capability":"Provides Python bindings for PGVecto.rs, a PostgreSQL vector database extension, with support for multiple vector types and integration with SQLAlchemy, Psycopg3, and Django.","skillfed_tags":["vector-database","orm-integration","embeddings"],"use_cases":["Store and query embeddings from machine learning models in PostgreSQL using ORM without writing raw SQL.","Perform approximate nearest-neighbor searches on vector embeddings with HNSW or IVF indexing for semantic search or recommendation systems.","Bulk-load large sets of vectors into PostgreSQL via Psycopg3's COPY interface for efficient data ingestion.","Define vector fields in Django models and run similarity queries through the ORM without custom database functions.","Support multiple vector representations (full-precision, sparse, half-precision, binary) in a single PostgreSQL database for different use cases."],"what_it_does":"pgvecto-rs is a Python client library for PGVecto.rs, a PostgreSQL extension that adds native vector data types and approximate nearest-neighbor search capabilities. It bridges Python applications to PostgreSQL by providing type mappings and helper functions for four vector types: standard vectors, sparse vectors, half-precision vectors, and binary vectors. The library integrates with three major Python database frameworks\u2014SQLAlchemy, Psycopg3, and Django\u2014allowing developers to store, index, and query embeddings through their ORM or query interface.\n\nThe package handles vector insertion, approximate indexing via HNSW and IVF algorithms, and distance-based queries. It requires a running PGVecto.rs PostgreSQL instance and supports Python 3.8 through 3.12. Because the package is dormant with no recent updates, users should verify compatibility with their target PostgreSQL and PGVecto.rs versions before adopting it in production.","worth_installing":"Yes, if you are already committed to PGVecto.rs and need Python ORM integration. The library has low install friction, but its dormant maintenance status (675 days since last release) means no updates for security, compatibility, or bugs. Install only if you can tolerate stalled upstream development and verify compatibility with your PostgreSQL and PGVecto.rs versions independently."},"id":"pgvecto-rs","links":{"html":"https://skillfed.io/packages/pgvecto-rs","md":"https://skillfed.io/packages/pgvecto-rs.md","pypi":"https://pypi.org/project/pgvecto-rs/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2024-10-08","license_spdx":null,"license_treatment":"permissive","name":"pgvecto-rs","python_support":"capped_below_current","summary":"Python binding for pgvecto.rs"},"popularity":{"monthly_downloads":231563,"position":9084,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.2.2"}