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Settings_stories
US Application Settings Management : Define settings for the application.
classDiagram
direction LR
class Settings {
<<abstract>>
}
Settings --|> pdts.BaseSettings : inherits
class MainSettings {
+job: jobs.JobKind
}
MainSettings --|> Settings : inherits
class jobs.JobKind {
<<external>>
}
class pdt.Field {
<<external>>
+Field(..., discriminator="KIND")
}
class pdts.BaseSettings {
<<external>>
}
MainSettings --> jobs.JobKind : "uses"
MainSettings --> pdt.Field : "uses"
Title:
As an application administrator, I want to configure application settings, so that I can adjust how the application behaves according to different execution contexts.
Description:
The Settings class encapsulates high-level preferences for the application, allowing configurable parameters that influence job execution.
Acceptance Criteria:
- The settings class can be instantiated with various configurations needed for the application.
- Default values are handled correctly, and the settings can be overridden.
Title:
As a data scientist, I want to specify the job to run within the main settings, so that I can ensure the correct job is executed based on the application's context.
Description:
The MainSettings class holds the configuration for the job to be executed, ensuring that it is readily accessible when the application runs.
Acceptance Criteria:
- The job is specified within the
MainSettingsand reflects the expected type. - The job configuration can be validated against the expected structure before execution.
Title:
As a developer, I want to validate the application settings structure, so that I can ensure all required parameters are present and correct before the application runs.
Description:
The settings classes use Pydantic to automatically validate the structure of the settings against predefined schemas.
Acceptance Criteria:
- Validation occurs at instantiation, ensuring required parameters are not missing.
- Clear error messages are raised for any discrepancies in the settings structure.
Title:
As a developer, I want to keep settings separate from their providers (e.g., command-line interface), so that I can maintain a clean and organized codebase.
Description:
By defining settings as a distinct class, the application can cleanly interface with different configuration sources (e.g., CLI, files) while keeping the settings validation and application separate.
Acceptance Criteria:
- The settings are decoupled from the underlying logic of the application so that changes in one do not directly impact the other.
- The architecture allows for easy swapping of settings providers without extensive code changes.
-
Implementation Requirements:
- The
SettingsandMainSettingsclasses must properly inherit from Pydantic's base settings. - Required parameters in the settings must be defined with appropriate types.
- The
-
Error Handling:
- Informative error messages should be provided if settings validation fails.
- The application should handle missing or invalid settings gracefully, preventing runtime errors.
-
Testing:
- Unit tests validate settings initialization, validation, and any provided default values.
- Tests should ensure various scenarios where settings are provided through different sources are handled correctly.
-
Documentation:
- Each class and method should include detailed docstrings explaining their purpose and usage.
- Users should have access to examples that demonstrate the integration of settings into the application.
- The
SettingsandMainSettingsclasses are fully implemented with all respective functionalities. - All user stories are verified through testing and meet acceptance criteria.
- Comprehensive documentation accompanies the code.
src/regression_model_template/settings.py
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