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Build bulletproof workflows

Ship resilient code faster, and turn your workflows into powerful applications

hello_world.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")
Orchestrate

Ship trustworthy pipelines faster

With Prefect orchestration, build scalable workflows in pure python without changing how you work:

  • Scheduling
  • Retries
  • Parameterization
  • Dependency management
  • Caching
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flow.py
1import httpx
2from prefect import flow, task
3
4
5@task
6def get_url(url: str, params: dict = None):
7    response = httpx.get(url, params=params)
8    response.raise_for_status()
9    return response.json()
10
11
12@flow(retries=3, retry_delay_seconds=5, log_prints=True)
13def get_repo_info(repo_name: str = "PrefectHQ/prefect"):
14    url = f"https://api.github.com/repos/{repo_name}"
15    repo_stats = get_url(url)
16    print(f"{repo_name} repository statistics 🤓:")
17    print(f"Stars 🌠 : {repo_stats['stargazers_count']}")
18    print(f"Forks 🍴 : {repo_stats['forks_count']}")
19
20    
21if __name__ == "__main__":
22    get_repo_info.serve(name="my-first-deployment")
Testimonial
“Prefect has become the backbone of our data stack.”
David Anderson
David Anderson
Chief Product Officer, Tandym
Testimonial
“Prefect’s observability helps us to trust that our data is accurate.”
Matt Delacour
Matt Delacour
Data Lead, Coinlist
Testimonial
“Issues that took weeks of developer time can now be resolved in minutes.”
Chandler Soto
Chandler Soto
Data Engineer, Crumbl
Always know the status

Visualize, monitor, and triage

From the individual flow to your entire system health, always know where your failures are:

  • Visualize the execution graph of thousands of workflow tasks
  • Inspect individual workflows, or track holistic health
  • Notify your stakeholders and get ahead of questions
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Deploy easily

Dev to production, simplified

Spin up a local orchestration server with a single command. No code changes means your workflow runs as expected, locally or in production.

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$ prefect server start
 ___ ___ ___ ___ ___ ___ _____ 
| _ \ _ \ __| __| __/ __|_   _| 
|  _/   / _|| _|| _| (__  | |  
|_| |_|_\___|_| |___\___| |_|  

Configure Prefect to communicate with the server with:

    prefect config set PREFECT_API_URL=http://127.0.0.1:4200/api

View the API reference documentation at http://127.0.0.1:4200/docs

Check out the dashboard at http://127.0.0.1:4200

Learn About Prefect

Dynamic workflows

Just write python

Add a single decorator to your functions to gain scheduling, monitoring, and resiliency without unnecessary abstractions.

alt
loop.py
1import prefect
2from prefect import flow
3
4@flow
5def simple_looping_flow():
6    for i in range(5):
7        print(f"Current iteration: {i}")
8
9if __name__ == "__main__":
10    simple_looping_flow.serve(name="simple_looping_flow_deployment")

Infrastructure agnostic

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.

Dynamic workflows

Granular access controls

Stay compliant and manage provisions & permissions the way you want to

  • SSO & SCIM
  • Team management
  • Custom roles and RBAC
  • Object-level access control
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Get Started