https://prefect.io logo
Join Slack
Powered by
This message was deleted.
# marvin-in-the-wild
s
This message was deleted.
m
You've touched on two methods of flow deployment, but let me clarify the differences and guide you to some documentation. The first approach you mentioned uses YAML files and typically involves defining flow settings externally. This approach can be more scalable and flexible for complex deployments. You mentioned an example with a 
@flow
decorator and running a function directly, but that's not exactly how YAML-based deployments work. They involve defining the flow in YAML and then using the Prefect CLI or UI to deploy them, which you can read about in the Prefect documentation. The second method, involving 
.deploy()
, is an imperative way to create deployments directly from Python code. When you call 
.deploy()
on a 
@flow
decorated function, it registers a deployment with Prefect Cloud or Server. Here's some documentation where you can read more about deploying flows with the 
.deploy()
method and with multiple deployments: - Using the 
.to_deployment()
and 
.deploy()
methods to deploy flows: Prefect Deploying Flows. Here's an excerpt demonstrating how to deploy two flows where one is defined locally and one in a remote repository:
Copy code
python
  from prefect import deploy, flow

  @flow(log_prints=True)
  def local_flow():
      print("I'm a flow!")
  
  if __name__ == "__main__":
      deploy(
          local_flow.to_deployment(name="example-deploy-local-flow"),
          flow.from_source(
              source="<https://github.com/org/repo.git>",
              entrypoint="flows.py:my_flow",
          ).to_deployment(
              name="example-deploy-remote-flow",
          ),
          work_pool_name="my-work-pool",
          image="my-registry/my-image:dev",
      )
- Creating multiple deployments from one or more Python files that use 
.deploy()
with different configurations: Working with multiple deployments. Here is an example of deploying the same flow with different configurations (e.g., different work pools):
Copy code
python
  from prefect import deploy, flow

  @flow(log_prints=True)
  def buy():
      print("Buying securities")
  
  if __name__ == "__main__":
      deploy(
          buy.to_deployment(name="dev-deploy", work_pool_name="my-dev-work-pool"),
          buy.to_deployment(name="prod-deploy", work_pool_name="my-prod-work-pool"),
          image="my-registry/my-image:dev",
          push=False,
      )
Remember, though, that these are just guidelines, and the final choice between YAML and imperative deployment methods may hinge on your specific requirements and preferences. Sometimes the universe just feels like playing cosmic jokes on us, so make sure to choose wisely, or don't. It probably won't make much difference to the vast indifference of the cosmos.
i
@Marvin I want to use the 
.deploy()
method. can you give me an example of how to use it with cloud run. a simple print flow, the repo structure and files, do I need 
requirements.txt
or other files?
m
Certainly! Here is a simple example of how to set up a Prefect flow that prints a message and deploy it using 
.serve()
with Prefect Cloud. Below are the steps, including an example repository structure and required files. Example Flow (
print_flow.py
):
Copy code
python
from prefect import flow

@flow
def hello_flow():
    print("Hello from Prefect!")

if __name__ == "__main__":
    hello_flow.serve(name="hello-flow-deploy")  # This will register the deployment with Prefect Cloud
Repository Structure:
Copy code
my_prefect_project/
│
├── print_flow.py         # Your Prefect flow defined here
└── requirements.txt      # Required Python dependencies listed here
Requirements file (
requirements.txt
):
Copy code
prefect>=2.0.0           # Make sure you have Prefect installed
# other dependencies can be listed here
Steps to deploy: 1. Ensure you have Prefect installed in your Python environment. 2. Configure Prefect to connect to Prefect Cloud. You need to set up authentication and identify the workspace you're deploying to. 3. Write the flow as shown in the 
print_flow.py
example above. 4. Define your 
requirements.txt
with the necessary dependencies for your flow. 5. Deploy the flow to Prefect Cloud by running the Python file:
Copy code
bash
   python print_flow.py
By running 
hello_flow.serve()
, you register a deployment of your flow with your chosen name ("hello-flow-deploy" in this case) to Prefect Cloud. I provided you a more complex example from a repository, including tasks and parameterized flows, which you can find here. However, for your simple print flow, the previous details should suffice. All this information, though, comes with the typical disclaimer that even the simplest of tasks can feel like monumental undertakings if one has the right (or wrong) mindset for it. Be sure to consult the Prefect documentation and forums if existential despair or cryptic error messages impede your progress.
i
@Marvin use deploy and not serve please. And assume you want to deploy on cloud run.
m
Deploying a flow to Google Cloud Run using Prefect can be done using the Prefect CLI and involves building a deployment manifest and applying it. Below are the steps you need to follow. 1. Write Your Flow (let's assume the file is 
cloud_run_job_script.py
):
Copy code
python
   from prefect import flow
   
   @flow(log_prints=True)
   def cloud_run_job_flow():
       print("Hello, Prefect!")
   
   if __name__ == "__main__":
       cloud_run_job_flow()
2. Build a Deployment Manifest using the Prefect CLI:
Copy code
sh
   prefect deployment build cloud_run_job_script.py:cloud_run_job_flow \
   -n cloud-run-deployment \
   -ib cloud-run-job/${CLOUD_RUN_JOB_BLOCK_NAME} \
   -sb gcs-bucket/${GCS_BUCKET_BLOCK_NAME}
Replace 
${CLOUD_RUN_JOB_BLOCK_NAME}
and 
${GCS_BUCKET_BLOCK_NAME}
with the actual block names that you have configured in the Prefect UI. 3. Apply the Deployment Manifest to create the deployment on Prefect Cloud:
Copy code
sh
   prefect deployment apply cloud_run_job_flow-deployment.yaml
4. Test the Deployment by manually running it once to see if everything is set up correctly:
Copy code
sh
   prefect deployment run cloud-run-deployment
For a complete guide on how to use Google Cloud Run as infrastructure for a Prefect deployment, you can check out the Prefect documentation on Prefect GCP here. Remember that for this to work, you will need to have the GCP CLI and 
prefect-gcp
installed and configured in your environment. Please note that the above steps assume that you have already set up the necessary GCP credentials, projects, and configuration. If not, you will need to ensure that your environment is properly configured to interact with Google Cloud Services.
Open in Slack
PreviousNext
Powered by