Juturna is a data pipeline library written in Python (meetecho.github.io)

Juturna is a new Python data-pipeline library aimed at fast prototyping of multimedia and real-time data applications and for exploring and testing AI models in a modular, flexible way. It provides a quickstart with example pipelines so developers can create and wire up nodes and tasks in minutes, a set of built-in nodes for common data-handling tasks, and a community-driven Juturna Hub where users can share and reuse nodes and full pipelines. Official technical documentation covers the library’s APIs and component behavior for developers who need deeper integration. For the AI/ML community, Juturna offers a lightweight, composable way to build end-to-end data flows — from ingestion and preprocessing to model evaluation against live or simulated streams — without heavy infrastructure. Its node/task abstraction and packaged nodes lower the friction of assembling multimedia (audio/video) and real-time pipelines, accelerating iteration cycles when testing models on streaming data or building demo apps. The Hub and documented APIs also encourage reuse and extensibility, making it a practical tool for prototyping, reproducible experiments, and bridging research code to interactive or production-adjacent workflows.