Installation
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Quickstart
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Build workflows
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Deploy workflows
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Prefect Cloud
Prefect
Prefect is a workflow orchestration framework for building data pipelines in Python.
It's the simplest way to elevate a script into a production workflow.
With Prefect, you can build resilient, dynamic data pipelines that react to the world around them and recover from unexpected changes.
With just a few lines of code, data teams can confidently automate any data process with features such as scheduling, caching, retries, and event-based automations.
Workflow activity is tracked and can be monitored with a self-hosted Prefect server instance or managed Prefect Cloud dashboard.
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Prefect flows can handle retries, dependencies, and even complex branching logic
Check our docs or see the example below to learn more!
Getting started
Prefect requires Python 3.10+. To install the latest version of Prefect, run one of the following commands:
pip install -U prefect
uv add prefect
Then create and run a Python file that uses Prefect flow and task decorators to orchestrate and observe your workflow - in this case, a simple script that fetches the number of GitHub stars from a repository:
from prefect import flow, task
import httpx
@task(log_prints=True)
def get_stars(repo: str):
url = f"https://api.github.com/repos/{repo}"
count = httpx.get(url).json()["stargazers_count"]
print(f"{repo} has {count} stars!")
@flow(name="GitHub Stars")
def github_stars(repos: list[str]):
for repo in repos:
get_stars(repo)
# run the flow!
if __name__ == "__main__":
github_stars(["PrefectHQ/prefect"])
Fire up a Prefect server and open the UI at http://localhost:4200 to see what happened:
prefect server start
To run your workflow on a schedule, turn it into a deployment and schedule it to run every minute by changing the last line of your script to the following:
if __name__ == "__main__":
github_stars.serve(
name="first-deployment",
cron="* * * * *",
parameters={"repos": ["PrefectHQ/prefect"]}
)
You now have a process running locally that is looking for scheduled deployments!
Additionally you can run your workflow manually from the UI or CLI. You can even run deployments in response to events.
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Where to go next - check out our documentation to learn more about:
Prefect Cloud
Prefect Cloud provides workflow orchestration for the modern data enterprise. By automating over 200 million data tasks monthly, Prefect empowers diverse organizations — from Fortune 50 leaders such as Progressive Insurance to innovative disruptors such as Cash App — to increase engineering productivity, reduce pipeline errors, and cut data workflow compute costs.
Read more about Prefect Cloud here or sign up to try it for yourself.
prefect-client
If your use case is geared towards communicating with Prefect Cloud or a remote Prefect server, check out our
prefect-client. It is a lighter-weight option for accessing client-side functionality in the Prefect SDK and is ideal for use in ephemeral execution environments.
Connect & Contribute
Join a thriving community of over 25,000 practitioners who solve data challenges with Prefect. Prefect's community is built on collaboration, technical innovation, and continuous improvement.
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Your contributions, questions, and ideas make Prefect better every day. Whether you're reporting bugs, suggesting features, or improving documentation, your input is invaluable to the Prefect community.
Prefect 是一个 Python 工作流编排框架，可以把普通脚本变成稳定、可用于生产环境的数据管道，支持定时调度、失败重试、结果缓存以及基于事件的自动化。