{"categories":[{"label":"Database","url":"https://skillfed.io/packages/category/database/3"}],"enrichment":{"capability":"A Python client for pushing ML feature data from offline sources to Orion Feature Store and retrieving feature metadata via protobuf serialization and Kafka integration.","skillfed_tags":["feature-store","kafka-integration","spark-pipeline"],"use_cases":["Push batch-computed features from Spark DataFrames to Orion Feature Store via Kafka for model serving.","Retrieve feature metadata and schema information from Orion to validate offline feature computation pipelines.","Serialize ML feature vectors into protobuf format for efficient Kafka transport.","Integrate offline feature engineering on Delta/Hive tables with a centralized feature store backend.","Automate feature ingestion workflows that read from cloud storage and publish to Orion."],"what_it_does":"Orion Python Client is a lightweight wrapper for pushing ML model features from offline data sources (Hive/Delta tables, cloud-stored Parquet/Delta folders) into Orion Feature Store. It handles feature metadata retrieval, protobuf serialization of feature values, and Kafka message production to enable asynchronous feature ingestion pipelines.\n\nThe package is designed for teams running feature engineering workflows on Spark who need to serialize and stream features to a centralized feature store. It supports scalar types (FP32, FP64, Int32, Int64, UInt32, UInt64, String, Bool) and vector types, with Kafka acting as the transport layer. You initialize a client with metadata source credentials, call methods to fetch feature schemas and generate protobuf-encoded DataFrames, then push those to Kafka topics for downstream consumption.","worth_installing":"Yes, if you are already running Spark-based feature engineering and have Orion Feature Store deployed as your backend. The low install friction and permissive license make it a straightforward addition. However, the aging maintenance status (343 days since last release) means you should verify that it remains compatible with your Spark, Kafka, and Orion versions before committing to production use."},"id":"orion-py-client","links":{"html":"https://skillfed.io/packages/orion-py-client","md":"https://skillfed.io/packages/orion-py-client.md","pypi":"https://pypi.org/project/orion-py-client/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-09-05","license_spdx":null,"license_treatment":"permissive","name":"orion-py-client","python_support":"supports_current","summary":"Python Client for Orion Feature Store to push/produce Model Features and get features' metadata"},"popularity":{"monthly_downloads":225969,"position":9209,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.1.14"}