Resilient by design, from script to scale
flow.py
1from prefect import flow, task
2
3
4@task(log_prints=True)
5def say_hello(name: str):
6 print(f"Hello {name}!")
7
8
9@flow
10def hello_universe(names: list[str]):
11 for name in names:
12 say_hello(name)
13
14
15if __name__ == "__main__":
16 # create your first deployment to automate your flow
17 hello_universe.serve(name="your-first-deployment")Complete visibility
Orchestrate your code with scheduling, automatic retries, and prioritized instant alerting, giving you full observability into your workflows.
Write It Your way
You bring raw Python functions, Prefect handles the rest. No more boilerplate code.
Don't dread failures
With custom retry behavior, caching, and extensive automations, go from red to green in minutes instead of days.
Lightweight
Start a local test server with a single command,
and test your work without pain.
Convenient & Secure
Configure your execution environment, all the way down to the individual @flow.
With work pools and work queues, you have granular control over your infrastructure.
Total Visibility
Look inside your pipelines with events from any third party tool.
Braun Reyes
Saving us days on DAG design vs. Airflow
NateYesterday
Okay, Prefect is officially awesome. I just launched the server locally and realized i didn’t see the whole picture from the docs. Thanks for building such an amazing product.
Andreas
Underrated @PrefectIO use-case of the day: ... observability and retries! Prefect is not only a "scheduler". By adding a flow/task decorator, you can add observability to your python scripts.
Ben Doremus
Our critical bug rate has dropped by 65% since we’ve implemented Prefect
Madison Schott
Our previous architecture took 24 hours to run the models. With Prefect, it's 3.
sshawnkimm
Hello, Currently scoping out using Prefect for our orchestration. Thanks for the great project. :)
Lee Mendelowitz
Prefect Core provides a really nice, clean set of easy to use features for constructing data pipelines (Tasks, Flows, States, Results) and it’s easy to model the dependencies between tasks.
bargava
• Airflow has a steeper learning curve. Team struggled.
• @PrefectIO is more Pythonic and team picked it up quite easily
• Cloud version has a generous free-tier. Lesser friction to get started.
Andreas
Invest heavily in Automation early on. If you do things twice, automate it, or at least document it. @PrefectIO is free and easy to set up, it`ll be the reliable backbone of your business automations
Chas DeVeas
We used to spend 20% of our time (and up to 80% at times) on errors. With Prefect, we're approaching 5%, a 75% reduction.