wendrul Comments - Windmill

wendrul

•Created by WhyDee on 4/20/2025 in #help

Trouble Cancelling Jobs with Filters – Always Says 0 Matched

Hello! Are you on windmill cloud? Otherwise could you share the windmill version you're running? When you click on the "Cancel all jobs matching filters", the button on the modal should show you how many potential jobs you 're trying to cancel and the toast tells you how many were actually canceled by your request. It is possible that the jobs ended before you could cancel them. Also, only running or queued jobs can be canceled, perhaps the jobs you see listed are already completed jobs?

2 replies

WWindmill

•Created by heavytobi on 10/22/2024 in #help

Ansible not usable

That's great! Let us know if it all works for you and we'll add this info in the docs

15 replies

WWindmill

•Created by heavytobi on 10/22/2024 in #help

Ansible not usable

Hi @Julian @ 42 N.E.R.D.S., I'm not very familiar with dynamic inventories in ansible, but we can look into implementing it. That being said, you can add a name for the inventory file like this:

inventory:
- resource_type: ansible_dynamic_inventory # you can create this resource type for example
  name: hcloud.yml

inventory:
- resource_type: ansible_dynamic_inventory # you can create this resource type for example
  name: hcloud.yml

It will be written as hcloud.yml and read by the ansible-playbook command. If you could try and see if this is sufficient to make dynamic inventories work that would be great, we could add the steps in the documentation. Otherwise, we will add this to backlog and work the additional features in when we get the chance.

15 replies

WWindmill

•Created by brian_gruntable on 8/29/2024 in #help

[Solved] DataFrame in Script and Flow Showing Incorrect Headers

Hmm, I agree I would have expected it to work like that too. I'm not sure if it's an issue with how pandas serializes dataframes or if it has to do with windmill, but i can try checking. In any case there seems to be a workaround, you can just add this and it will behave as you expect:

  [...]
  return df.to_dict('records')

  [...]
  return df.to_dict('records')

4 replies