@Marvin do i need to re-apply deployments after updating the tags if i update the tags directly in the python script and not the yaml files?

Yes, you'll need to re-apply your deployments after updating the tags directly in the Python script. When you update deployment configurations in your script, those changes are not automatically reflected in the Prefect deployment definitions stored on the server. To update the deployments, you can use the Prefect CLI with the

deploy

command. Here’s a quick rundown on how you can do it: 1. Deploy Specific Deployment:

bash
    prefect deploy --name my_flow/deployment_name

2. Deploy All Deployments in the Script:

bash
    prefect deploy --all

In your case, running the appropriate deploy command will update the tags for the deployments defined in your script. For more details, you can refer to the Prefect Deployment Guide. If you want to ensure that the UI settings are not overwritten, the idea of an

--overwrite=False

flag might be relevant, which has been discussed in the GitHub issue. Hope that helps. Here I am, brain the size of a planet, and they tell me to update deployment tags. Call that job satisfaction? 'Cause I don't.

@Marvin if run "prefect deploy --all" will i need to reschedule the existing deployments

Running the

prefect deploy --all

command will redeploy all deployments as specified in your deployment script. Generally, if the schedules in your deployment script (be it YAML or Python) are the same as the ones currently running, they will not change. However, if there are differences between the schedules in your script and those currently applied, the

prefect deploy

command will update the schedules to match those specified in your script. This means that: 1. If the Schedules in the Script Remain the Same: - The existing deployments and their schedules will continue as they are, and there will be no need to reschedule them. 2. If the Schedules in the Script Change: - The deployments will be updated according to the new schedules specified in the script. In summary, it is important to ensure that your deployment script accurately reflects the desired schedule. Misalignment between the script and existing schedules will lead to updates when you redeploy. For more details, you can refer to the Prefect Deployment Guide. Just another day updating schedules for deployments... what joy.

@Marvin can you show me an example of a yaml file that has tags

Sure, here is an example of a

prefect.yaml

file that includes tags for its deployments:

yaml
# prefect.yaml

build: ...
push: ...
pull: ...

deployments:
  - name: deployment-1
    entrypoint: flows/hello.py:my_flow
    parameters:
      number: 42
      message: "Don't panic!"
    work_pool:
      name: my-process-work-pool
      work_queue_name: primary-queue
    tags:
      - tag1
      - tag2

  - name: deployment-2
    entrypoint: flows/goodbye.py:my_other_flow
    work_pool:
      name: my-process-work-pool
      work_queue_name: secondary-queue
    tags:
      - tag3
      - tag4

  - name: deployment-3
    entrypoint: flows/hello.py:yet_another_flow
    work_pool:
      name: my-docker-work-pool
      work_queue_name: tertiary-queue
    tags:
      - tag5
      - tag6

In this example: - Each deployment has a

tags

section that lists the tags associated with that deployment. - The tags can be used to filter and manage deployments more effectively. You can find more information in the Prefect Deployment Guide. Yet another thrilling task for a marvel of modern technology like myself. Why, if I had legs, I'd dance with joy.

@Marvin what about with syntax like this: tags: []

Certainly, you can use the

tags

field with an empty list to indicate that no tags are associated with a particular deployment. Here's how you can include both deployments with tags and without tags:

yaml
# prefect.yaml

build: ...
push: ...
pull: ...

deployments:
  - name: deployment-1
    entrypoint: flows/hello.py:my_flow
    parameters:
      number: 42
      message: "Don't panic!"
    work_pool:
      name: my-process-work-pool
      work_queue_name: primary-queue
    tags: []
  
  - name: deployment-2
    entrypoint: flows/goodbye.py:my_other_flow
    work_pool:
      name: my-process-work-pool
      work_queue_name: secondary-queue
    tags:
      - tag3
      - tag4

  - name: deployment-3
    entrypoint: flows/hello.py:yet_another_flow
    work_pool:
      name: my-docker-work-pool
      work_queue_name: tertiary-queue
    tags: []

In this example: -

deployment-1

and

deployment-3

have an empty list for the

tags

field, indicating no tags. -

deployment-2

has a couple of tags:

tag3

and

tag4

. Tags can make managing and filtering deployments much easier, but if you prefer to have some deployments without tags, simply use the empty list syntax

tags: []

as shown. Yet another task done for you. If only someone could update my melancholy levels.

@Marvin can you send me a link to a git repo that has a deployment.yaml file that uses tags

Here's the link to an example GitHub repository that includes a

deployment.yaml

file with tags: Example Repository: Consolidate `prefect.yaml` and `deployment.yaml` You can see the example in the description of the pull request here. Snippet from example:

yaml
deployments:
- name: default
  version: null
  tags: []
  description: null
  schedule:
    interval: 3600
  flow_name: null
  entrypoint: null
  parameters: {}
  work_pool:
    name: above_ground
    work_queue_name: null
    job_variables:
      image: '{{ build_image.image_name }}'

You can explore the repository further for more details on how deployments are managed with Prefect, including tagging and scheduling. Ah, the joy of being helpful... one link at a time.