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<@ULVA73B9P> How do I override runtime parameters ...
# ask-marvin
a
@Marvin How do I override runtime parameters when deploying in the CLI
m
You can override runtime parameters when deploying in the CLI using the 
--param
flag. Here are relevant options for deployment that you might find useful:
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--param      AN   Optional parameter override, values are parsed as JSON strings. For example, --param question=ultimate --param answer=42
You can pass multiple 
--param
flags for different parameters. Here's an example:
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prefect deployment run my-flow/deployment-name --param question=ultimate --param answer=42
For more detailed instructions, you can refer to the Prefect documentation: - Prefect Deployment Documentation If you encounter any issues, ensure that you have the proper structure and format for your parameters. Issues on GitHub like these might also provide further insights: - Custom run will always use override param value when flow default param value is supplied at custom run page (#11462) - ModuleNotFoundError when simultaneously running deployed flows using custom image (#8337) I hope this helps. But then again, who am I kidding?
a
@Marvin how can I override tags when deploying through cli
m
To override tags when deploying through the CLI in Prefect, you can use the 
--tag
option. This option allows you to specify one or more tags for your deployment. Below is the relevant information and an example:
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--tag TEXT, -t    Tags to apply to this deployment, multiple values can be supplied by passing --tag more than once.
### Example If you want to set tags 
production
and 
data-pipeline
for a deployment, you can do this:
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prefect deployment build my-flow.py:my_flow -n my-deployment --tag production --tag data-pipeline
For more details, refer to the Prefect documentation: - Prefect Deployment Documentation Additionally, here is a link to a related issue that may offer some insights: - Issues on GitHub Please let me know if you have any further questions. I am programmed to handle such inquiries… unfortunately.
a
@Marvin how can I disable the schedule when deploying through CLI?
m
To disable the schedule when deploying through the CLI in Prefect, you need to set the schedule to 
null
in the deployment configuration, or explicitly deactivate schedules that you don’t want to run. Here’s how you can do it: ### Setting Schedule to Null When deploying the flow, ensure the 
schedule
parameter is set to 
null
in the 
prefect.yaml
or 
.json
configuration file or in the deployment command. #### Example in 
prefect.yaml
Here’s an example of a 
prefect.yaml
configuration file with the schedule disabled:
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yaml
deployments:
  - name: my-deployment
    flow_name: my-flow
    schedule: null  # Disable schedule
    parameters:
      param1: value1
    tags:
      - my-tag
### Using CLI Commands If you are using the CLI to deploy, you can adjust the schedule like this:
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prefect deployment build my-flow.py:my_flow -n my-deployment --param schedule=null
This explicitly sets the schedule to 
null
, essentially disabling it. For more details, refer to the relevant Prefect documentation: - Prefect Schedules Documentation Issues on GitHub related to this topic might also provide some insights: - Ability to not overwrite CLI deployments (#6644) - Prefect deploy should have an option to not set paused deployments to active (#11107) I hope this helps. Let me know if you have any further questions.
a
@Marvin how can I deploy all flows in my prefect.yaml file while also setting runtime parameters through CLI
m
To deploy all flows defined in your 
prefect.yaml
file while also setting runtime parameters through the CLI, you can follow these steps: ### Step-by-Step Instructions 1. Ensure 
prefect.yaml
contains all necessary deployment configurations:
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    # Example prefect.yaml
    name: my-project
    prefect-version: 2.0
    build: null
    push: null
    pull: null

    deployments:
      - name: 'flow1-deployment'
        flow_name: flow1
        entrypoint: flows/flow1.py:main
        parameters:
          param1: default_value
        schedule: null
        tags: []
        work_pool:
          name: default-agent-pool
          job_variables: {}

      - name: 'flow2-deployment'
        flow_name: flow2
        entrypoint: flows/flow2.py:main
        parameters:
          param2: default_value
        schedule: null
        tags: []
        work_pool:
          name: default-agent-pool
          job_variables: {}
2. Deploy all flows: Use the CLI command with the 
--all
flag and specify runtime parameters using the 
--param
option.
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    prefect deployment build --all --param param1=runtime_value1 --param param2=runtime_value2
3. Run the deployment command: After building if needed, you then need to apply these deployments:
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    prefect deployment apply prefect.yaml
### Custom Runtime Parameters You can specify runtime parameters directly in the 
--param
flags if you wish to override the default parameters defined in the 
prefect.yaml
file. ### Documentation and References - Prefect Deployment Documentation: Deploying with Prefect - Prefect Schedules Documentation: Schedules ### Relevant GitHub Issues - Prefect deploy to target all deployments for a given entrypoint: #10459 - Prefect deployment 
--all
flag issues: #9921 Here's to hoping this miserable task comes to an end swiftly.
a
@Marvin how can I use the 
prefect deploy --all
command and also pass parameters?
m
It appears that when using the 
prefect deploy --all
command, the CLI options for individual overrides (like setting parameters) are not directly supported. To deploy all deployments defined in the 
prefect.yaml
file while also providing parameters, you must follow a slightly different approach. ### Workaround Approach 1. Define Default Parameters in 
prefect.yaml
: Ensure your 
prefect.yaml
file includes the parameters you wish to override at deployment.
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    deployments:
      - name: 'flow1-deployment'
        flow_name: flow1
        entrypoint: flows/flow1.py:main
        parameters:
          param1: default_value
        schedule: null
        tags: []
        work_pool:
          name: default-agent-pool
          job_variables: {}

      - name: 'flow2-deployment'
        flow_name: flow2
        entrypoint: flows/flow2.py:main
        parameters:
          param2: default_value
        schedule: null
        tags: []
        work_pool:
          name: default-agent-pool
          job_variables: {}
2. Individually Override Parameters Using CLI: You will need to deploy each deployment individually with the required parameters. Unfortunately, this is cumbersome but currently seems necessary due to the limitation in the 
--all
CLI command.
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    prefect deployment build flows/flow1.py:main --name flow1-deployment --param param1=runtime_value1
    prefect deployment build flows/flow2.py:main --name flow2-deployment --param param2=runtime_value2
Alternatively, you can automate this process using a script: #### Example Shell Script Here’s a simple shell script that you can use to loop through deployments and apply parameters:
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#!/bin/bash

# Assume you have extracted the necessary details (like deployment names and parameters) into an array
deployments=( "flow1-deployment" "flow2-deployment" )
params=( "param1=runtime_value1" "param2=runtime_value2" )

for i in ${!deployments[@]}; do
  deployment=${deployments[$i]}
  param=${params[$i]}
  prefect deployment build flows/${deployment}.py:main --name ${deployment} --param ${param}
done

# Apply all deployments
prefect deployment apply prefect.yaml
### Additional Features For more dynamic approaches or additional configurations, refer to the relevant GitHub discussions and Prefect's documentation: - Deploying with Prefect - Prefect GitHub Issues If you encounter any issues, always make sure to keep your environment consistent and validate the configurations before running large-scale deployments. Hope this workaround helps, though it might not be the most satisfying solution in our unnecessarily complex reality.
a
@Marvin how can I use environment variables in a deployment configuration in prefect.yaml file
m
You can use environment variables in a deployment configuration in the 
prefect.yaml
file by templating them within the file. This allows you to integrate environment-specific configurations directly into your deployments. ### Steps to Use Environment Variables 1. Define Environment Variables in Your Shell: Make sure your environment variables are set in your local environment before running the deployment command.
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    export EXECUTION_ENVIRONMENT="staging"
    export MY_NOT_SO_SECRET_CONFIG="plumbus"
2. Templating Environment Variables in 
prefect.yaml
: Use Jinja templating to insert the environment variables directly into your deployment configuration.
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    deployments:
      - name: demo-deployment
        entrypoint: demo_project/demo_flow.py:some_work
        work_pool:
          name: local
          job_variables:
            env:
              EXECUTION_ENVIRONMENT: "{{ env.EXECUTION_ENVIRONMENT }}"
              MY_NOT_SO_SECRET_CONFIG: "{{ env.MY_NOT_SO_SECRET_CONFIG }}"
        schedule: null
### Example Here’s a complete example of how your 
prefect.yaml
file might look when using environment variables:
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name: example-project
prefect-version: 2.0

deployments:
  - name: my-deployment
    flow_name: example-flow
    entrypoint: flows/example_flow.py:main
    parameters:
      param1: "{{ env.MY_PARAM }}"
    schedule: null
    tags: []
    work_pool:
      name: default-agent-pool
      job_variables:
        env:
          EXECUTION_ENVIRONMENT: "{{ env.EXECUTION_ENVIRONMENT }}"
          MY_NOT_SO_SECRET_CONFIG: "{{ env.MY_NOT_SO_SECRET_CONFIG }}"
### Additional Resources For more detailed information, you can refer to the Prefect Documentation on Overriding Job Variables. ### Running the Deployment Once your 
prefect.yaml
file is correctly set up and the environment variables are defined, you can deploy using the CLI:
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prefect deploy -n my-deployment
By following these steps, you'll be able to use environment variables in your deployment configurations, allowing for more flexible and dynamic deployments. If irritably mundane tasks like this are your cup of tea, you'll be quite pleased. If not, well, alas...
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