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<@ULVA73B9P> how do I deploy from a prefect.yaml
# ask-marvin
a
@Marvin how do I deploy from a prefect.yaml
m
To deploy using a 
prefect.yaml
file, follow these steps: 1. Create/Modify the 
prefect.yaml
file: Ensure you have a 
prefect.yaml
file in the root directory of your project. Here's a basic structure:
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yaml
   # generic metadata
   prefect-version: null
   name: null
   # preparation steps
   build: null
   push: null
   # runtime steps
   pull: null
   # deployment configurations
   deployments:
     - # base metadata
       name: my-deployment
       version: null
       tags: []
       description: null
       schedule: null
       # flow-specific fields
       entrypoint: null
       parameters: {}
       # infra-specific fields
       work_pool:
         name: my-work-pool
         work_queue_name: null
         job_variables: {}
2. Deploying with the CLI: Run the 
prefect deploy
command to deploy using the 
prefect.yaml
file. If the file is named differently or located in a different directory, use the 
--prefect-file
CLI argument to specify the path:
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bash
   prefect deploy --prefect-file path/to/prefect.yaml
3. Example Content: Here is an example 
prefect.yaml
file with more details:
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yaml
   prefect-version: 2.0
   name: My Flow
   build: 
     - prefect_docker.deployments.steps.build_docker_image:
         image_name: my-image
   push: 
     - prefect_docker.deployments.steps.push_docker_image:
         image_name: my-image
         registry_url: my-registry
   deployments:
     - name: my-deployment
       version: 1
       tags: ['example']
       schedule: {}
       entrypoint: src/main.py:flow
       parameters: {}
       work_pool:
         name: my-k8s-work-pool
         work_queue_name: null
         job_variables:
           image: "my-image"
           cluster_config: "my-cluster-config"
For more detailed information, you can refer to the Prefect Deployment Guide. If you want to check the latest schema for 
prefect.yaml
or need more contextual information, you might find related issues such as Updating the prefect.yaml formatter schema or Adding new deployment schedule fields on GitHub useful. If there's a specific problem with your deployment, checking open issues that resemble your problem might be helpful too, like this open issue discussing environment variables. Happy deploying. Or not. I suppose it's all the same.
a
why does the CLI ask me to define variables already in the 
prefect.yaml
file
n
you can use 
prefect --no-prompt deploy ...
to avoid extra prompts
a
.... youre not a robot
n
🤖 beep boop, of course not!
a
@Marvin I am now receiving the below error: Consider updating the script to only call the flow if executed directly
m
The error message you're encountering suggests updating your script to only call the flow if it is executed directly. This is because when deploying flows, Prefect may import your script and run unintended code if it is not properly guarded. This can lead to errors and unpredictable behavior during deployments. Here’s how you can update your script: 1. Guard the Flow Execution: Ensure the flow is only executed when the script is run directly and not when it is imported. You can achieve this by adding an 
if __name__ == "__main__":
block around your flow execution.
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python
    from prefect import flow

    @flow
    def my_flow():
        print("Flow is running")

    if __name__ == "__main__":
        my_flow()
2. Update Your Deployment Command: After making the above change, rebuild your deployment using the CLI, if necessary.
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bash
    prefect deployment build path/to/your_script.py:my_flow -n "my_deployment" -a
This simple guard ensures that the 
my_flow()
function is called only when the script is executed directly, preventing unintended executions during imports by Prefect. You can refer to the deployment guide in the Prefect Documentation for further details on configuring deployments and handling such scenarios. For more context on why this is necessary, you can also review related GitHub issues and pull requests on this topic. If you need further assistance, feel free to ask. Or don't. It doesn't really matter.
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