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Pyper is a Python-native orchestration and scheduling framework designed for modern data workflows, machine learning pipelines, and any task that benefits from a lightweight DAG-based execution engine. Unlike heavier platforms like Airflow, Pyper aims to remain lean, modular, and developer-friendly, embracing Pythonic conventions and minimizing boilerplate. It focuses on local development ergonomics and seamless transition to production environments, making it ideal for small teams and individuals needing a programmable and flexible orchestration solution without the overhead of enterprise systems.
Features
- Lightweight DAG-based workflow orchestration
- Fully written and operated in native Python
- Simple syntax for defining dependencies and execution order
- CLI interface for running and managing workflows
- Local-first development with easy testing and debugging
- Environment-aware execution for production readiness
- Extensible with custom operators and hooks
- Ideal for ML, ETL, and data transformation tasks
Project Samples
Categories
Stream ProcessingLicense
MIT LicenseFollow Pyper
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