---
id: prefect
version: "3.8.3"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# prefect — Workflow orchestration and management.

License: permissive · Maintenance: active · Downloads: 12.4M/mo

## What it is and what it does

Prefect is a workflow orchestration framework that lets you define data pipelines as Python functions decorated with @flow and @task. It handles the operational complexity of production workflows—scheduling, retries, error handling, caching, and dependency management—so you can focus on the business logic. Workflows can be run locally, deployed to production environments, or triggered by events.

The framework includes a self-hosted server and UI for monitoring, or you can use Prefect Cloud for managed orchestration. It integrates with common data tools and supports complex branching, conditional execution, and dynamic task generation. At its core, Prefect transforms a simple Python script into a resilient, observable, and maintainable data pipeline with minimal code changes.

Use it for:

- Schedule recurring ETL jobs to run on a cron schedule and monitor their execution from a web dashboard.
- Build data pipelines that automatically retry failed tasks and skip cached results to reduce compute costs.
- Trigger workflows in response to external events or API calls rather than on a fixed schedule.
- Deploy multi-step data processing pipelines across distributed workers with centralized orchestration and logging.
- Add observability and error tracking to existing Python scripts without rewriting the core logic.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Prefect is a Python workflow orchestration framework that turns scripts into production-ready data pipelines with scheduling, retries, caching, and event-driven automation.

Yes. Prefect is actively maintained, has no known vulnerabilities, installs with low friction, and is widely used (top 5000 PyPI packages). It solves a real problem—turning ad-hoc scripts into production workflows—with a clean API and strong community support. The 57 dependencies are a trade-off for a complete orchestration platform, but justified if you need scheduling, retries, and monitoring. Start with it if you're building data pipelines or automating recurring tasks.

## Install

pip install prefect
uv add prefect
poetry add prefect

## Installing prefect

Before you install: Low friction installation as a pure Python wheel. Active maintenance with a release within the last day and 23623 repository stars. Requires Python 3.10 or later. Brings in 57 runtime dependencies including FastAPI, httpx, and database drivers, which is substantial but typical for a full orchestration platform.

License in practice: Licensed under Apache-2.0 (permissive). You can use, modify, and distribute Prefect freely in commercial and private projects with minimal restrictions.

Quickstart:

pip install prefect

from prefect import flow, task
import httpx

@task
def fetch_data(url: str):
    return httpx.get(url).json()

@flow
def my_pipeline():
    data = fetch_data("https://api.example.com/data")
    return data

if __name__ == "__main__":
    my_pipeline()

Requires Python 3.10 or later. To monitor workflow runs, you must start a Prefect server (prefect server start) or connect to Prefect Cloud.

Verify before relying:

- Whether the 57 runtime dependencies can be selectively installed or if lighter distributions exist for minimal deployments.
- Performance characteristics and scalability limits for high-volume task execution.
- Integration breadth with external systems beyond what the description mentions.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 12.4M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

workflow orchestration python, data pipeline automation, task scheduling and retries, dag execution framework, production workflow management, event-driven task execution, distributed data pipeline, orchestration, etl, scheduling

[View on SkillFed](https://skillfed.io/packages/prefect) · [View on PyPI](https://pypi.org/project/prefect/)