prefect — Workflow orchestration framework for building resilient data pipelines in Python

Overview

Prefect is a Python-based workflow orchestration framework designed to simplify the process of building and managing data pipelines. It enables developers to elevate scripts into production workflows with minimal code, offering features such as scheduling, caching, retries, and event-based automations. Prefect stands out for its ability to handle complex branching logic, dependencies, and automatic retries, making it a robust choice for dynamic data pipeline management.

Key Features

Resilience and Recovery: Automatically recovers from unexpected changes and failures in data pipelines.
Scheduling and Caching: Offers built-in scheduling and caching capabilities to optimize workflow execution.
Event-based Automations: Supports event-driven triggers for more dynamic and responsive data processing.
Monitoring and Tracking: Workflow activity is tracked and can be monitored through a self-hosted Prefect server or Prefect Cloud dashboard.

Use Cases

Data Automation: Automating repetitive data tasks and processes within organizations.
Data Pipeline Management: Managing and orchestrating complex data pipelines in a production environment.
Dynamic Workflows: Creating workflows that react to external events and data changes in real-time.

Advantages

Simplicity: Elevates scripts to production workflows with minimal additional code.
Extensibility: Easily integrates with other tools and systems, allowing for customization and extension.
Reliability: Built to be resilient and self-healing, ensuring continuous workflow operation.

Limitations / Considerations

Learning Curve: There might be a learning curve for new users unfamiliar with workflow orchestration concepts.
Python Dependency: Requires Python 3.9+, which may not be suitable for all environments or legacy systems.

Apache Airflow: A platform to programmatically author, schedule, and monitor workflows, differing in its more complex UI/UX and broader range of supported languages.
Luigi: A Python module that helps build complex pipelines of batch jobs, differing in its simpler design and lack of a built-in monitoring dashboard.
Dagster: A data orchestrator for machine learning, analytics, and ETL, differing in its focus on data applications and less emphasis on general workflow orchestration.

Basic Information

GitHub: https://github.com/PrefectHQ/prefect
Stars: 20,275
License: Unknown
Last Commit: 2025-09-07

Requirements:

Python Version: Python 3.9+
Installation Command: pip install -U prefect or uv add prefect

📊 Project Information

Project Name: prefect
GitHub URL: https://github.com/PrefectHQ/prefect
Programming Language: Python
⭐ Stars: 20,275
🍴 Forks: 1,935
📅 Created: 2018-06-29
🔄 Last Updated: 2025-09-07

🏷️ Project Topics

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📚 Documentation

Prefect Cloud

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