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Dataflow

Manage Python Environment

The Python Environment Approval process allows Admins to review and control which custom environments are published for use across your workspace. This ensures security, compatibility, and standardisation for all workflows.

What is Environment Approval?

When users create a custom Python environment in Studio, they can:

  • Save it as a draft for personal use and further editing
  • Submit it for publishing, making it available to all users after Admin approval

The Admin review process ensures only tested, secure, and compatible environments are published in the workspace.

Approving or Rejecting an Environment

1 Viewing Pending Environments

  1. Navigate to Admin → Python Environments from the sidebar.
  2. You will see a list of environments needs approval:

2 Reviewing Environment Details

Click on the environment name to view:

  • Environment Name and Base Environment
  • Creator (user who built it)
  • Installed Libraries and Versions (e.g. pandas==1.3.5, scikit-learn==1.1.3)
  • Description (optional notes from the creator)

You can also compare libraries and versions with existing published environments to ensure consistency, security compliance, or avoid duplication.

3 Approving an Environment

  • Click Approve if the environment meets your workspace standards.
  • The status will change to Published and it becomes available for all users in Studio for selection during server launch and in runtimes.

4 Rejecting an Environment

  • Click Reject if the environment does not meet requirements or needs modification.
  • The status will revert to Draft, and the user can update and resubmit the environment for approval.

Approval Workflow Summary

  1. User creates and builds environment → Saves as draft
  2. User submits environment for publishing
  3. Admin reviews environment details and libraries
  4. Admin approves ➔ Environment status changes to Published
  5. Admin rejects ➔ Environment status reverts to Draft, user can edit and resubmit

Best Practices

  • Approve only environments with validated, secure, and workspace-compliant libraries.
  • Reject and provide feedback for environments with outdated or conflicting library versions.
  • Periodically review published environments to deprecate unused ones and maintain a clean, standardised environment list.

Summary

Through the Python Environment Approval process, Admins ensure:

  • Only verified environments are published and used across the platform
  • Workspace compatibility, security, and cost-efficiency are maintained
  • Users can build custom environments confidently while adhering to governance policies