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Vikunja

Get data from Vikunja's API

Overview

This node integrates with the Vikunja API to manage projects and their components. Specifically, the "Delete a Kanban Bucket" operation under the "Project" resource allows users to delete a specific bucket (a Kanban column or container) within a project view. This is useful for workflows that automate project management tasks such as cleaning up completed or obsolete buckets in a Kanban board.

Practical examples include:

  • Automatically removing empty or inactive Kanban buckets from a project view.
  • Integrating with other tools to maintain project boards by deleting buckets based on external triggers or conditions.

Properties

Name Meaning
Project Title or ID The target project where the bucket exists. You can select a project from a searchable list or specify its ID directly.
Project View ID The specific project view (e.g., a Kanban board) within the project where the bucket resides. Select from a list or provide an ID.
Bucket ID The numeric identifier of the bucket to delete within the selected project view.

Output

The node outputs JSON data representing the result of the delete operation. Typically, this will be a confirmation of successful deletion or an error message if the bucket could not be deleted. There is no indication that binary data is output by this operation.

Dependencies

  • Requires an API key credential for authenticating with the Vikunja API.
  • Needs the base URL of the Vikunja instance configured in the credentials.
  • The node uses internal helper methods to search and map projects and project views for user convenience.

Troubleshooting

  • Common issues:

    • Providing an invalid or non-existent Project ID, Project View ID, or Bucket ID will cause the operation to fail.
    • Insufficient permissions or incorrect API credentials may lead to authorization errors.
    • Network connectivity problems with the Vikunja server can cause request failures.
  • Error messages and resolutions:

    • "Not Found" or similar errors usually mean the specified bucket or project does not exist; verify IDs.
    • "Unauthorized" errors indicate invalid or missing API credentials; check and update authentication details.
    • "Bad Request" might occur if required parameters are missing or malformed; ensure all required fields are correctly filled.

Links and References

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