@Marvin I need your help with the jinja syntax and available variables in making a deployment. How can I use the name of the deployment in one of the

job_variables

in a jinja template?

Ah, the sweet smell of jinja in the air. In Prefect, you can use the deployment name within a jinja template by referencing it with double brackets like

{{ field_name }}

. In your case, you can use

{{ name }}

to reference the deployment name in the

job_variables

section of your deployment YAML file. Here's an example of how to use the deployment name in a jinja template within Prefect:

yaml
deployments:
  - name: my_deployment
    job_variables:
      deployment_name: "{{ name }}"

In this example, the

deployment_name

variable in the

job_variables

section will be populated with the deployment name, which is "my_deployment" in this case. You can find more information about using dynamic values in deployment YAML files in the Prefect documentation. Now go forth and deploy, my human friend.

@Marvin That did not work.. Check out my deployment 👇

deployments:
- name: dbt
  version: null
  tags: []
  description: 'Trigger dbt commands'
  entrypoint: prefect/flows/dbt.py:trigger_dbt_flow
  parameters: {}
  work_pool:
    name: ecs-default
    work_queue_name: null
    job_variables: 
      image: '{{ build_image.image }}'
      execution_role_arn: 'arn:aws:iam::1231231232:role/prefect-flow-run-execution-role'
      cloudwatch_logs_options: {
        "awslogs-group": "beacon-{{ name }}"
      }
  schedule: null

I apologize for the confusion earlier. After further investigation, it seems that there isn't a direct way to use the deployment name as a variable in the

job_variables

section of the deployment YAML file. However, you can use a workaround by defining a custom variable and using it in your YAML file. Here's an example of how you can achieve this: 1. Set a custom variable in Prefect:

bash
prefect variables set deployment_name dbt

2. Use the custom variable in your deployment YAML file:

yaml
deployments:
- name: dbt
  version: null
  tags: []
  description: 'Trigger dbt commands'
  entrypoint: prefect/flows/dbt.py:trigger_dbt_flow
  parameters: {}
  work_pool:
    name: ecs-default
    work_queue_name: null
    job_variables: 
      image: '{{ build_image.image }}'
      execution_role_arn: 'arn:aws:iam::1231231232:role/prefect-flow-run-execution-role'
      cloudwatch_logs_options: {
        "awslogs-group": "beacon-{{ prefect.variables.deployment_name }}"
      }
  schedule: null

In this example, I've set a custom variable called

deployment_name

and used it in the

job_variables

section with

{{ prefect.variables.deployment_name }}

. This way, you can use the deployment name as a variable in your YAML file. Keep in mind that this workaround requires you to set the custom variable manually and keep it in sync with the deployment name. It's not an ideal solution, but it should help you achieve your goal. I hope this helps you in your quest for jinja enlightenment.

@Marvin But if I want to set a variable on the Worker config to default to the deployment name on all deployments, that’s not really nice, is it? 😄

Ah, I see your point. You're right, the workaround I provided earlier isn't the most elegant solution for setting a default variable on the Worker config for all deployments. Unfortunately, as of now, Prefect doesn't provide a built-in way to directly reference the deployment name in the

job_variables

section of the deployment YAML file. However, you can still achieve your goal by using a consistent naming convention for your deployments and custom variables. For example, you can create a custom variable for each deployment with a prefix like

deployment_

followed by the deployment name: 1. Set custom variables for each deployment:

bash
prefect variables set deployment_dbt dbt
prefect variables set deployment_another_deployment another_deployment

2. Use the custom variables in your deployment YAML files:

yaml
deployments:
- name: dbt
  # ...
  work_pool:
    # ...
    job_variables: 
      # ...
      cloudwatch_logs_options: {
        "awslogs-group": "beacon-{{ prefect.variables.deployment_dbt }}"
      }
  # ...

- name: another_deployment
  # ...
  work_pool:
    # ...
    job_variables: 
      # ...
      cloudwatch_logs_options: {
        "awslogs-group": "beacon-{{ prefect.variables.deployment_another_deployment }}"
      }
  # ...

By following this naming convention, you can ensure that each deployment has a corresponding custom variable that defaults to the deployment name. While this approach still requires manual management of custom variables, it provides a more consistent and organized way to handle deployment-specific variables in your Worker config. I hope this solution brings a smile to your face, even if it's not perfect.