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GitHub · PrefectHQ/prefect↑ +66 today

Manage data processes with Python

Prefect is a workflow orchestration framework used to create Python-based data pipelines. Designed to develop resilient data processes, this tool enables management and monitoring of complex data workflows.

Updates

  • November 7, 2026: Stars 24,102 → 24,127, latest release 3.9.2 (November 6, 2026).
  • October 31, 2026: Stars 24,051 → 24,102, latest release 3.9.1 (October 30, 2026).
  • October 21, 2026: Stars 23,982 → 24,051, latest release 3.9.0 (October 21, 2026).
  • October 7, 2026: Stars 23,931 → 23,982, latest release 3.8.8 (October 6, 2026).

What you get

  • Moving data pipelines to production level
  • Error handling and automatic retry
  • Visually monitor workflows

Installation

Installation via pip
pip install -U prefect
Installation with UV
uv add prefect

Running it

Starting the server
prefect server start

If you don't write code

Paste this into your AI agent (Claude Code · Codex · Antigravity)

I want to automate my data workflows using Python. Help me create a simple data pipeline using the flow and task decorators from the Prefect library. Explain with sample codes how I can integrate error management, scheduling and monitoring features, and how I can turn a Python file into a production-level workflow.

Repository: https://github.com/PrefectHQ/prefect. Follow the official instructions in the README of this repository for setup and execution.

Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.

Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.

Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.

Related dictionary terms

Who it is forFor data teams that want to automate data processes and reliably manage complex data pipelines.
LicenseApache-2.0

Links

TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-07-13: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.