{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/10"}],"enrichment":{"capability":"Provides utility functions for vector search operations in MongoDB using PyMongo, simplifying the integration of vector-based queries with MongoDB collections.","skillfed_tags":["vector-search","mongodb","embeddings"],"use_cases":["Building semantic search features that query MongoDB collections by vector similarity rather than keyword matching.","Simplifying vector embedding workflows in RAG systems that store and retrieve document embeddings from MongoDB.","Reducing boilerplate code when implementing recommendation engines that rely on vector distance calculations.","Integrating vector search into data pipelines that already use PyMongo for MongoDB operations.","Prototyping or developing applications that combine traditional MongoDB queries with vector-based similarity search."],"what_it_does":"This package is a utility library that wraps common vector search operations for MongoDB, designed to reduce boilerplate when working with vector embeddings and similarity queries through PyMongo. It sits between your application and PyMongo, providing helper functions and abstractions for vector search workflows.\n\nThe library targets developers building applications that rely on MongoDB's vector search capabilities\u2014such as semantic search, recommendation systems, or retrieval-augmented generation (RAG) pipelines. It depends only on pymongo and supports current Python versions (3.10 through 3.14), making it straightforward to integrate into existing PyMongo-based projects with minimal additional dependencies.","worth_installing":"Yes, if you are already using PyMongo and need vector search functionality in MongoDB. The package has low install friction, permissive licensing, active maintenance, and no known vulnerabilities. However, adoption is still limited (top 15000 tier), so verify that its API surface and feature set match your specific vector search requirements before committing to production use."},"id":"pymongo-search-utils","links":{"html":"https://skillfed.io/packages/pymongo-search-utils","md":"https://skillfed.io/packages/pymongo-search-utils.md","pypi":"https://pypi.org/project/pymongo-search-utils/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-02-03","license_spdx":null,"license_treatment":"permissive","name":"pymongo-search-utils","python_support":"supports_current","summary":"Utility library for working with vector search in MongoDB using PyMongo"},"popularity":{"monthly_downloads":617930,"position":5736,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.3.0"}