backend-use-case

To structure backend use cases in Python, apply a defined decorator stack order for error handling and transactions, use a repository container for data access, and enforce org_id scoping. This pattern separates business logic from data persistence and ensures controlled transaction management.

The correct decorator stack order layers transaction management and error handling decorators systematically around backend use cases. Applying these decorators in the specified sequence ensures domain exceptions are caught and database transactions are managed predictably during execution.

Enforce org_id scoping in backend repositories by routing data access through a repository container. This mechanism automatically filters queries and restricts operations to the correct organizational boundary, preventing cross-tenant data leaks during use case execution.

Set up tests for backend use cases by initializing mock repositories and mock database sessions using the provided test setup pattern. This approach isolates business logic during testing by substituting actual repository container dependencies with controlled mock objects.

Yes, you need Python to execute this backend development pattern. The structured approach for creating use cases, managing the repository container, and handling the decorator stack requires a Python execution environment to function.