Requirement
- class Requirement
Bases:
CommonBaseModelDefines a single requirement for engineering or scientific projects, encapsulating attributes for specification, tracking, and validation.
- name
A unique identifier for the requirement.
- Type:
str
- description
A detailed description of what the requirement entails.
- Type:
str
- category
The classification of the requirement (e.g., performance, safety).
- Type:
Optional[str]
- priority
The priority level of the requirement (e.g., high, medium, low).
- Type:
str
- verification_method
The method to be used for verifying the requirement (e.g., test, analysis, inspection).
- Type:
str
- status
The current status of the requirement (e.g., open, closed, in progress).
- Type:
str
- source
The origin or source of the requirement (e.g., customer, internal, regulation).
- Type:
Optional[str]
- target_component
The component or system to which the requirement applies.
- Type:
Optional[str]
- acceptance_criteria
The criteria that must be met for the requirement to be considered satisfied.
- Type:
str
- risk
A description of the potential risks associated with the requirement.
- Type:
Optional[str]
- verification_evidence
Documentation or evidence proving the requirement has been verified.
- Type:
Optional[str]
- metadata
Additional metadata providing context or details about the requirement.
- Type:
Optional[Metadata]
- Raises:
ValueError – If essential string attributes are empty, ensuring all requirements are descriptive and actionable.
Attributes Summary
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
Methods Summary
validate_non_empty(value)Validates that critical string fields are not empty or just whitespace, ensuring requirements are clear and actionable.
Attributes Documentation
- model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'allow', 'protected_namespaces': (), 'validate_assignment': True}
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
Methods Documentation
- classmethod validate_non_empty(value)
Validates that critical string fields are not empty or just whitespace, ensuring requirements are clear and actionable.
- Parameters:
value (str) – The value of the field being validated.
- Returns:
The validated string value.
- Raises:
ValueError – If the input value is empty or consists only of whitespace.
- Return type:
str
Methods:
validate_non_empty(value)Validates that critical string fields are not empty or just whitespace, ensuring requirements are clear and actionable.
Attributes:
__setattr__ handlers.
- classmethod validate_non_empty(value)
Validates that critical string fields are not empty or just whitespace, ensuring requirements are clear and actionable.
- Parameters:
value (str) – The value of the field being validated.
- Returns:
The validated string value.
- Raises:
ValueError – If the input value is empty or consists only of whitespace.
- Return type:
str
- __pydantic_setattr_handlers__: ClassVar[Dict[str, Callable[[BaseModel, str, Any], None]]] = {}
__setattr__ handlers. Memoizing the handlers leads to a dramatic performance improvement in __setattr__