<p align="center"><img src="https://github.com/PrefectHQ/prefect/assets/3407835/c654cbc6-63e8-4ada-a92a-efd2f8f24b85" width=1000></p>
<p align="center">
<a href="https://pypi.python.org/pypi/prefect/" alt="PyPI version">
<img alt="PyPI" src="https://img.shields.io/pypi/v/prefect?color=0052FF&labelColor=090422"></a>
<a href="https://github.com/prefecthq/prefect/" alt="Stars">
<img src="https://img.shields.io/github/stars/prefecthq/prefect?color=0052FF&labelColor=090422" /></a>
<a href="https://pepy.tech/badge/prefect/" alt="Downloads">
<img src="https://img.shields.io/pypi/dm/prefect?color=0052FF&labelColor=090422" /></a>
<a href="https://github.com/prefecthq/prefect/pulse" alt="Activity">
<img src="https://img.shields.io/github/commit-activity/m/prefecthq/prefect?color=0052FF&labelColor=090422" /></a>
<br>
<a href="https://prefect.io/slack" alt="Slack">
<img src="https://img.shields.io/badge/slack-join_community-red.svg?color=0052FF&labelColor=090422&logo=slack" /></a>
<a href="https://www.youtube.com/c/PrefectIO/" alt="YouTube">
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</p>
# Prefect
Prefect is a workflow orchestration framework for building data pipelines in Python.
It's the simplest way to elevate a script into a resilient 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](https://docs.prefect.io/latest/manage/self-host/?utm_source=oss&utm_medium=oss&utm_campaign=oss_gh_repo&utm_term=none&utm_content=none) instance or managed [Prefect Cloud](https://www.prefect.io/cloud-vs-oss?utm_source=oss&utm_medium=oss&utm_campaign=oss_gh_repo&utm_term=none&utm_content=none) dashboard.
## Getting started
Prefect requires Python 3.9 or later. To [install the latest or upgrade to the latest version of Prefect](https://docs.prefect.io/get-started/install), run the following command:
```bash
pip install -U 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:
```python
from prefect import flow, task
from typing import List
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 the Prefect UI to see what happened:
```bash
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:
```python
if __name__ == "__main__":
github_stars.serve(
name="first-deployment",
cron="* * * * *",
parameters={"repos": ["PrefectHQ/prefect"]}
)
```
You now have a server 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](https://docs.prefect.io/latest/automate/?utm_source=oss&utm_medium=oss&utm_campaign=oss_gh_repo&utm_term=none&utm_content=none).
## 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](https://www.prefect.io/cloud-vs-oss?utm_source=oss&utm_medium=oss&utm_campaign=oss_gh_repo&utm_term=none&utm_content=none) or sign up to [try it for yourself](https://app.prefect.cloud?utm_source=oss&utm_medium=oss&utm_campaign=oss_gh_repo&utm_term=none&utm_content=none).
## prefect-client
If your use case is geared towards communicating with Prefect Cloud or a remote Prefect server, check out our
[prefect-client](https://pypi.org/project/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.
## Next steps
- Check out the [Docs](https://docs.prefect.io/).
- Join the [Prefect Slack community](https://prefect.io/slack).
- Learn how to [contribute to Prefect](https://docs.prefect.io/contribute/).
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To [install the latest or upgrade to the latest version of Prefect](https://docs.prefect.io/get-started/install), run the following command:\n\n```bash\npip install -U prefect\n```\n\nThen 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:\n\n```python\nfrom prefect import flow, task\nfrom typing import List\nimport httpx\n\n\n@task(log_prints=True)\ndef get_stars(repo: str):\n url = f\"https://api.github.com/repos/{repo}\"\n count = httpx.get(url).json()[\"stargazers_count\"]\n print(f\"{repo} has {count} stars!\")\n\n\n@flow(name=\"GitHub Stars\")\ndef github_stars(repos: List[str]):\n for repo in repos:\n get_stars(repo)\n\n\n# run the flow!\nif __name__==\"__main__\":\n github_stars([\"PrefectHQ/Prefect\"])\n```\n\nFire up the Prefect UI to see what happened:\n\n```bash\nprefect server start\n```\n\nTo 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:\n\n```python\nif __name__ == \"__main__\":\n github_stars.serve(\n name=\"first-deployment\",\n cron=\"* * * * *\",\n parameters={\"repos\": [\"PrefectHQ/prefect\"]}\n )\n```\n\nYou now have a server running locally that is looking for scheduled deployments!\nAdditionally you can run your workflow manually from the UI or CLI. 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