0
# Policy Management
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Policy-based configuration and governance system with JSON-defined rules, configurable targets, and extensible rule evaluation framework. The policy management system supports complex business logic and compliance requirements with flexible alert configurations and comprehensive policy lifecycle management.
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## Capabilities
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### Abstract Policy Manager
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Core policy management framework providing JSON-based configuration loading, policy validation, and rule configuration with extensible architecture for custom policy implementations.
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```python { .api }
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class AbstractPolicyManager(ABC):
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    """
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    Abstract class containing logic for reading and parsing policies and rules from JSON configuration.
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    Class Attributes:
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    - __logger - LogManager instance for AbstractPolicyManager
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    - __policyLocation = "POLICY_LOCATION" - Environment variable name for policy location
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    Properties:
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    - policies: Dict[str, Policy] - Returns policies dictionary
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    """
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    def __init__(self) -> None:
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        """Initialize policy manager and load configurations"""
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        ...
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    def getPoliciesLocation(self) -> str:
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        """Get policies location from config or environment"""
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        ...
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    def loadPolicyConfigurations(self, policiesLocation: str) -> None:
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        """Load policy configurations from JSON files"""
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        ...
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    def loadJsonFilesInDirectory(self, policyConfigurationsLocation: str) -> None:
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        """Load all JSON files in directory"""
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        ...
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    def loadJsonFile(self, filePath: str, fileName: str) -> None:
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        """Load individual JSON file"""
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        ...
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    def validateAndAddPolicies(self, policies: List[PolicyInput]) -> None:
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        """Validate and add list of policies"""
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        ...
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    def validateAndAddPolicy(self, policyInput: PolicyInput) -> None:
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        """Validate and add single policy"""
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        ...
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    def validateAndConfigureRule(self, ruleInput: PolicyRuleInput, targets: List[Target]) -> ConfiguredRule:
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        """Validate and configure policy rule"""
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        ...
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    def getPolicy(self, policyIdentifier: str) -> Policy:
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        """Get policy by identifier"""
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        ...
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    def getDeserializationClass(self) -> any:
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        """Get class for JSON deserialization (can be overridden)"""
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        ...
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    def createPolicy(self, policyIdentifier: str) -> Policy:
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        """Create policy instance (can be overridden)"""
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        ...
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    def setAdditionalConfigurations(self, policy: Policy, input: PolicyInput) -> None:
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        """Set additional configurations (can be overridden)"""
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        ...
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```
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### Default Policy Manager
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Singleton implementation of the policy management framework providing centralized policy access and configuration management across application components.
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```python { .api }
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class DefaultPolicyManager(AbstractPolicyManager):
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    """
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    Default singleton policy manager implementation.
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    Class Attributes:
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    - __instance = None - Singleton instance
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    """
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    def __init__(self) -> None:
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        """Initialize singleton instance"""
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        ...
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    @staticmethod
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    def getInstance() -> DefaultPolicyManager:
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        """Get singleton instance"""
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        ...
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```
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### Policy Configuration
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Configuration management for policy system settings including policy location and default values with property-based configuration support.
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```python { .api }
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class PolicyConfiguration:
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    """
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    Used to configure policy location and defaults.
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    """
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    def __init__(self) -> None:
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        """Initialize with policy-configuration.properties"""
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        ...
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    def policiesLocation(self) -> str:
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        """Returns policies location from configuration"""
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        ...
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```
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### Policy Data Models
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Comprehensive data models for policy definition including alert options, targets, rules, and extensible configuration support with deprecated field handling for backward compatibility.
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```python { .api }
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class AlertOptions(Enum):
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    """
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    Enum to determine when alerts will be sent for policies.
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    Values:
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    - ALWAYS = "ALWAYS"
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    - ON_DETECTION = "ON_DETECTION"  
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    - NEVER = "NEVER"
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    """
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    ALWAYS = "ALWAYS"
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    ON_DETECTION = "ON_DETECTION"
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    NEVER = "NEVER"
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class Target(BaseModel):
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    """
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    Contains target information for the policy.
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    Attributes:
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    - retrieve_url: Optional[str] = None - Target retrieval URL
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    - type: Optional[str] = None - Target type
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    """
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    retrieve_url: Optional[str] = None
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    type: Optional[str] = None
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class ConfiguredTarget(Target):
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    """
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    Contains target information with configurations needed by the rule.
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    Attributes:
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    - target_configurations: Dict[str, Any] - Target configurations dictionary
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    - Inherits: retrieve_url and type from Target
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    """
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    target_configurations: Dict[str, Any]
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class ConfiguredRule(BaseModel):
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    """
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    Represents a rule read by the policy manager with class and configuration information.
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    Class Attributes:
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    - __logger - LogManager instance for ConfiguredRule
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    - __deprecated_set_methods - Dictionary for deprecated method mapping
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    Attributes:
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    - className: str - Rule class name
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    - configurations: Optional[Dict[str, Any]] = None - Rule configurations
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    - configuredTargets: Optional[List[ConfiguredTarget]] = [] - List of configured targets
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    Properties:
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    - targetConfigurations: ConfiguredTarget - Deprecated property (use configuredTargets)
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    """
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    className: str
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    configurations: Optional[Dict[str, Any]] = None
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    configuredTargets: Optional[List[ConfiguredTarget]] = []
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    def set_deprecated_targetConfigurations(self, new_value: ConfiguredTarget):
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        """Deprecated setter method"""
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        ...
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    def __setattr__(self, key, val):
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        """Custom attribute setter for deprecated attributes"""
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        ...
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class Policy(BaseModel):
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    """
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    Maps a rule or set of rules with identifier for policy execution.
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    Class Attributes:
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    - __logger - LogManager instance for Policy
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    - __deprecated_set_methods - Dictionary for deprecated method mapping
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    Attributes:
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    - alertOptions: AlertOptions = AlertOptions.ON_DETECTION - Alert options (default: ON_DETECTION)
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    - identifier: str - Policy identifier
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    - description: Optional[str] = None - Policy description
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    - targets: Optional[List[Target]] = [] - List of targets
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    - rules: List[ConfiguredRule] = [] - List of configured rules
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    Properties:
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    - target: Target - Deprecated property (use targets)
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    """
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    alertOptions: AlertOptions = AlertOptions.ON_DETECTION
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    identifier: str
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    description: Optional[str] = None
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    targets: Optional[List[Target]] = []
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    rules: List[ConfiguredRule] = []
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    def set_deprecated_target(self, new_value: Target):
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        """Deprecated setter method"""
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        ...
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    def __setattr__(self, key, val):
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        """Custom attribute setter for deprecated attributes"""
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        ...
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```
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### Policy Input Models
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JSON deserialization models for loading policy configurations from files with support for both current and deprecated field structures for backward compatibility.
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```python { .api }
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class PolicyRuleInput(BaseModel):
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    """
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    Represents policy rule data read from JSON file.
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    Attributes:
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    - className: str - Class name for the rule (required)
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    - configurations: Optional[Dict[str, Any]] = None - Rule configuration
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    - targetConfigurations: Optional[Dict[str, Any]] = None - Target configurations
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    """
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    className: str
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    configurations: Optional[Dict[str, Any]] = None
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    targetConfigurations: Optional[Dict[str, Any]] = None
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class PolicyInput(BaseModel):
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    """
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    Represents policy information read from JSON file.
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    Class Attributes:
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    - __logger - LogManager instance for PolicyInput
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    Attributes:
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    - identifier: str - Policy identifier (required)
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    - description: Optional[str] = None - Policy description
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    - targets: Optional[List[Target]] = None - List of targets
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    - shouldSendAlert: Optional[AlertOptions] = None - Alert configuration
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    - rules: List[PolicyRuleInput] = [] - List of policy rules
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    - target: Optional[Target] = None - Deprecated single target
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    """
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    identifier: str
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    description: Optional[str] = None
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    targets: Optional[List[Target]] = None
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    shouldSendAlert: Optional[AlertOptions] = None
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    rules: List[PolicyRuleInput] = []
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    target: Optional[Target] = None
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    def getAnyTargets(self) -> List[Target]:
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        """Returns targets list, checking both new and deprecated attributes"""
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        ...
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```
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### Policy Invocation Results
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Result tracking for policy execution with comprehensive metadata including policy identification, description, and execution timestamps for audit and monitoring purposes.
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```python { .api }
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class PolicyInvocationResult(BaseModel):
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    """
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    Represents the results of a policy invocation.
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    Attributes:
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    - policyName: str - Name of the policy
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    - policyDescription: Optional[str] = None - Policy description
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    - timestamp: str - Invocation timestamp
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    """
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    policyName: str
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    policyDescription: Optional[str] = None
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    timestamp: str
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```
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## Usage Examples
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### Basic Policy Management Setup
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```python
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from policy_manager import DefaultPolicyManager
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from policy_manager.policy.policy import Policy, AlertOptions
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import json
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import os
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# Initialize policy manager (singleton)
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policy_manager = DefaultPolicyManager.getInstance()
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# Get available policies
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available_policies = policy_manager.policies
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print(f"Loaded {len(available_policies)} policies:")
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for policy_id, policy in available_policies.items():
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    print(f"  - {policy_id}: {policy.description}")
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# Get specific policy
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try:
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    security_policy = policy_manager.getPolicy("data_security_policy")
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    print(f"Security policy loaded: {security_policy.identifier}")
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    print(f"Rules count: {len(security_policy.rules)}")
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    print(f"Alert setting: {security_policy.alertOptions}")
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except Exception as e:
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    print(f"Policy not found: {e}")
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```
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### JSON Policy Configuration
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```python
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from policy_manager import DefaultPolicyManager
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from policy_manager.policy.policy import Policy, ConfiguredRule, Target, AlertOptions
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from policy_manager.policy.json.policy_input import PolicyInput, PolicyRuleInput
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import json
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import tempfile
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import os
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def create_sample_policy_configuration():
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    """Create sample JSON policy configuration"""
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    # Define policy configuration
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    policy_config = {
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        "identifier": "data_quality_policy",
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        "description": "Ensures data quality standards across all datasets",
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        "shouldSendAlert": "ON_DETECTION",
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        "targets": [
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            {
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                "retrieve_url": "s3://data-lake/raw-data/",
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                "type": "data_source"
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            },
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            {
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                "retrieve_url": "s3://data-lake/processed-data/",
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                "type": "processed_data"
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            }
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        ],
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        "rules": [
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            {
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                "className": "com.example.rules.CompletenessRule",
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                "configurations": {
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                    "minimum_completeness": 0.95,
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                    "required_fields": ["id", "timestamp", "value"]
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                },
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                "targetConfigurations": {
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                    "batch_size": 10000,
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                    "sampling_rate": 0.1
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                }
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            },
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            {
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                "className": "com.example.rules.AccuracyRule", 
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                "configurations": {
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                    "accuracy_threshold": 0.98,
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                    "validation_method": "statistical"
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                }
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            }
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        ]
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    }
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    # Create temporary policy file
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    with tempfile.NamedTemporaryFile(mode='w', suffix='.json', delete=False) as f:
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        json.dump(policy_config, f, indent=2)
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        return f.name
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def load_custom_policies():
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    """Load custom policies from JSON configuration"""
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    # Create sample configuration
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    policy_file = create_sample_policy_configuration()
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    try:
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        # Get policy manager
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        manager = DefaultPolicyManager.getInstance()
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        # Load the custom policy file
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        manager.loadJsonFile(os.path.dirname(policy_file), os.path.basename(policy_file))
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        # Retrieve the loaded policy
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        policy = manager.getPolicy("data_quality_policy")
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        print(f"Loaded policy: {policy.identifier}")
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        print(f"Description: {policy.description}")
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        print(f"Alert options: {policy.alertOptions}")
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        print(f"Number of targets: {len(policy.targets)}")
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        print(f"Number of rules: {len(policy.rules)}")
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        # Print rule details
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        for i, rule in enumerate(policy.rules):
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            print(f"\nRule {i+1}:")
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            print(f"  Class: {rule.className}")
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            print(f"  Configurations: {rule.configurations}")
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            if rule.configuredTargets:
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                print(f"  Target configurations: {len(rule.configuredTargets)}")
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        return policy
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    finally:
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        # Clean up temporary file
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        if os.path.exists(policy_file):
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            os.unlink(policy_file)
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# Usage example
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custom_policy = load_custom_policies()
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```
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### Policy Execution Framework
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```python
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from policy_manager import DefaultPolicyManager
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from policy_manager.policy.policy import Policy, ConfiguredRule
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from policy_manager.policy.result.policy_invocation_result import PolicyInvocationResult
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from datetime import datetime
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from typing import Dict, List, Any
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import logging
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class PolicyExecutionEngine:
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    """Engine for executing policies and tracking results"""
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    def __init__(self):
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        self.policy_manager = DefaultPolicyManager.getInstance()
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        self.execution_results = []
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        self.logger = logging.getLogger(__name__)
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    def execute_policy(self, policy_identifier: str, target_data: Any, context: Dict[str, Any] = None) -> PolicyInvocationResult:
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        """Execute a specific policy against target data"""
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        try:
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            # Get policy configuration
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            policy = self.policy_manager.getPolicy(policy_identifier)
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            # Create invocation result
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            result = PolicyInvocationResult(
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                policyName=policy.identifier,
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                policyDescription=policy.description,
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                timestamp=datetime.now().isoformat()
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            )
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435
            print(f"Executing policy: {policy.identifier}")
436
            
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            # Execute each rule in the policy
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            rule_results = []
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            for rule in policy.rules:
440
                rule_result = self._execute_rule(rule, target_data, policy.targets, context)
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                rule_results.append(rule_result)
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                print(f"  Rule {rule.className}: {'PASSED' if rule_result['passed'] else 'FAILED'}")
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                if not rule_result['passed']:
445
                    print(f"    Reason: {rule_result.get('reason', 'Unknown')}")
446
            
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            # Determine overall policy result
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            policy_passed = all(result['passed'] for result in rule_results)
449
            
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            # Handle alerting based on policy configuration
451
            if not policy_passed and policy.alertOptions != AlertOptions.NEVER:
452
                self._send_alert(policy, rule_results, context)
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            elif policy.alertOptions == AlertOptions.ALWAYS:
454
                self._send_alert(policy, rule_results, context)
455
            
456
            # Store result
457
            result.rule_results = rule_results  # Add rule results to invocation result
458
            result.overall_status = "PASSED" if policy_passed else "FAILED"
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            self.execution_results.append(result)
460
            
461
            return result
462
            
463
        except Exception as e:
464
            self.logger.error(f"Policy execution failed: {e}")
465
            raise
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467
    def _execute_rule(self, rule: ConfiguredRule, target_data: Any, targets: List, context: Dict[str, Any]) -> Dict[str, Any]:
468
        """Execute individual rule (this would integrate with actual rule implementations)"""
469
        
470
        # This is a simplified rule execution simulation
471
        # In practice, this would dynamically load and execute the rule class
472
        
473
        rule_result = {
474
            'rule_class': rule.className,
475
            'passed': True,
476
            'details': {},
477
            'execution_time': datetime.now().isoformat()
478
        }
479
        
480
        # Simulate rule-specific logic based on class name
481
        if "CompletenessRule" in rule.className:
482
            rule_result.update(self._execute_completeness_rule(rule, target_data))
483
        elif "AccuracyRule" in rule.className:
484
            rule_result.update(self._execute_accuracy_rule(rule, target_data))
485
        elif "DataFreshnessRule" in rule.className:
486
            rule_result.update(self._execute_freshness_rule(rule, target_data))
487
        else:
488
            # Generic rule execution
489
            rule_result['details']['message'] = f"Executed {rule.className} successfully"
490
        
491
        return rule_result
492
    
493
    def _execute_completeness_rule(self, rule: ConfiguredRule, data: Any) -> Dict[str, Any]:
494
        """Simulate completeness rule execution"""
495
        config = rule.configurations or {}
496
        min_completeness = config.get('minimum_completeness', 0.95)
497
        
498
        # Simulate completeness check (in practice, this would analyze actual data)
499
        simulated_completeness = 0.97  # Assume 97% completeness
500
        
501
        passed = simulated_completeness >= min_completeness
502
        return {
503
            'passed': passed,
504
            'details': {
505
                'completeness_score': simulated_completeness,
506
                'threshold': min_completeness,
507
                'message': f"Data completeness: {simulated_completeness:.2%}"
508
            },
509
            'reason': None if passed else f"Completeness {simulated_completeness:.2%} below threshold {min_completeness:.2%}"
510
        }
511
    
512
    def _execute_accuracy_rule(self, rule: ConfiguredRule, data: Any) -> Dict[str, Any]:
513
        """Simulate accuracy rule execution"""
514
        config = rule.configurations or {}
515
        accuracy_threshold = config.get('accuracy_threshold', 0.98)
516
        
517
        # Simulate accuracy check
518
        simulated_accuracy = 0.96  # Assume 96% accuracy
519
        
520
        passed = simulated_accuracy >= accuracy_threshold
521
        return {
522
            'passed': passed,
523
            'details': {
524
                'accuracy_score': simulated_accuracy,
525
                'threshold': accuracy_threshold,
526
                'validation_method': config.get('validation_method', 'unknown')
527
            },
528
            'reason': None if passed else f"Accuracy {simulated_accuracy:.2%} below threshold {accuracy_threshold:.2%}"
529
        }
530
    
531
    def _execute_freshness_rule(self, rule: ConfiguredRule, data: Any) -> Dict[str, Any]:
532
        """Simulate data freshness rule execution"""
533
        config = rule.configurations or {}
534
        max_age_hours = config.get('max_age_hours', 24)
535
        
536
        # Simulate freshness check
537
        simulated_age_hours = 30  # Assume data is 30 hours old
538
        
539
        passed = simulated_age_hours <= max_age_hours
540
        return {
541
            'passed': passed,
542
            'details': {
543
                'data_age_hours': simulated_age_hours,
544
                'max_allowed_hours': max_age_hours
545
            },
546
            'reason': None if passed else f"Data age {simulated_age_hours}h exceeds limit {max_age_hours}h"
547
        }
548
    
549
    def _send_alert(self, policy: Policy, rule_results: List[Dict], context: Dict[str, Any]):
550
        """Send policy violation alert"""
551
        failed_rules = [r for r in rule_results if not r['passed']]
552
        
553
        alert_message = f"Policy Violation: {policy.identifier}\n"
554
        alert_message += f"Description: {policy.description}\n"
555
        alert_message += f"Failed Rules: {len(failed_rules)}/{len(rule_results)}\n\n"
556
        
557
        for failed_rule in failed_rules:
558
            alert_message += f"- {failed_rule['rule_class']}: {failed_rule['reason']}\n"
559
        
560
        print(f"🚨 POLICY ALERT 🚨")
561
        print(alert_message)
562
        
563
        # In practice, this would integrate with alerting systems
564
        # (email, Slack, PagerDuty, etc.)
565
    
566
    def get_execution_summary(self) -> Dict[str, Any]:
567
        """Get summary of all policy executions"""
568
        total_executions = len(self.execution_results)
569
        passed_executions = sum(1 for result in self.execution_results if getattr(result, 'overall_status', 'FAILED') == 'PASSED')
570
        
571
        return {
572
            'total_executions': total_executions,
573
            'passed_executions': passed_executions,
574
            'failed_executions': total_executions - passed_executions,
575
            'success_rate': (passed_executions / total_executions * 100) if total_executions > 0 else 0
576
        }
577

578
# Usage example
579
execution_engine = PolicyExecutionEngine()
580

581
# Execute policies against sample data
582
sample_data = {
583
    'dataset_id': 'customer_transactions_2024',
584
    'record_count': 1500000,
585
    'last_updated': '2024-09-05T10:30:00Z'
586
}
587

588
# Execute different policies
589
try:
590
    # Data quality policy
591
    quality_result = execution_engine.execute_policy(
592
        policy_identifier='data_quality_policy',
593
        target_data=sample_data,
594
        context={'environment': 'production', 'pipeline_id': 'etl_001'}
595
    )
596
    
597
    print(f"Quality policy result: {getattr(quality_result, 'overall_status', 'Unknown')}")
598
    
599
    # Get execution summary
600
    summary = execution_engine.get_execution_summary()
601
    print(f"\nExecution Summary:")
602
    print(f"  Total executions: {summary['total_executions']}")
603
    print(f"  Success rate: {summary['success_rate']:.1f}%")
604
    
605
except Exception as e:
606
    print(f"Policy execution failed: {e}")
607
```
608

609
### Dynamic Policy Configuration Management
610

611
```python
612
from policy_manager import DefaultPolicyManager
613
from policy_manager.policy.policy import Policy, ConfiguredRule, Target, AlertOptions
614
from policy_manager.configuration.policy_configuration import PolicyConfiguration
615
import json
616
import os
617
from typing import Dict, List
618
from datetime import datetime
619

620
class DynamicPolicyManager:
621
    """Advanced policy management with dynamic configuration updates"""
622
    
623
    def __init__(self):
624
        self.base_manager = DefaultPolicyManager.getInstance()
625
        self.config = PolicyConfiguration()
626
        self.policy_cache = {}
627
        self.change_listeners = []
628
    
629
    def register_change_listener(self, callback):
630
        """Register callback for policy configuration changes"""
631
        self.change_listeners.append(callback)
632
    
633
    def notify_change_listeners(self, policy_id: str, change_type: str):
634
        """Notify registered listeners of policy changes"""
635
        for callback in self.change_listeners:
636
            try:
637
                callback(policy_id, change_type)
638
            except Exception as e:
639
                print(f"Error notifying change listener: {e}")
640
    
641
    def create_policy_runtime(self, policy_config: Dict) -> Policy:
642
        """Create policy dynamically from configuration dictionary"""
643
        
644
        # Create targets
645
        targets = []
646
        if 'targets' in policy_config:
647
            for target_config in policy_config['targets']:
648
                target = Target(
649
                    retrieve_url=target_config.get('retrieve_url'),
650
                    type=target_config.get('type')
651
                )
652
                targets.append(target)
653
        
654
        # Create rules
655
        rules = []
656
        if 'rules' in policy_config:
657
            for rule_config in policy_config['rules']:
658
                rule = ConfiguredRule(
659
                    className=rule_config['className'],
660
                    configurations=rule_config.get('configurations'),
661
                    configuredTargets=[]  # Would be populated based on targetConfigurations
662
                )
663
                rules.append(rule)
664
        
665
        # Create policy
666
        policy = Policy(
667
            identifier=policy_config['identifier'],
668
            description=policy_config.get('description'),
669
            alertOptions=AlertOptions(policy_config.get('shouldSendAlert', 'ON_DETECTION')),
670
            targets=targets,
671
            rules=rules
672
        )
673
        
674
        return policy
675
    
676
    def update_policy_configuration(self, policy_id: str, updates: Dict):
677
        """Update existing policy configuration"""
678
        try:
679
            # Get existing policy
680
            existing_policy = self.base_manager.getPolicy(policy_id)
681
            
682
            # Create updated configuration
683
            updated_config = {
684
                'identifier': existing_policy.identifier,
685
                'description': existing_policy.description,
686
                'shouldSendAlert': existing_policy.alertOptions.value,
687
                'targets': [
688
                    {'retrieve_url': t.retrieve_url, 'type': t.type} 
689
                    for t in existing_policy.targets
690
                ] if existing_policy.targets else [],
691
                'rules': [
692
                    {
693
                        'className': r.className,
694
                        'configurations': r.configurations,
695
                        'targetConfigurations': {}  # Simplified
696
                    }
697
                    for r in existing_policy.rules
698
                ]
699
            }
700
            
701
            # Apply updates
702
            updated_config.update(updates)
703
            
704
            # Create new policy
705
            new_policy = self.create_policy_runtime(updated_config)
706
            
707
            # Update in manager (simplified - would need proper integration)
708
            self.policy_cache[policy_id] = new_policy
709
            
710
            # Notify listeners
711
            self.notify_change_listeners(policy_id, 'UPDATED')
712
            
713
            print(f"Policy {policy_id} updated successfully")
714
            return new_policy
715
            
716
        except Exception as e:
717
            print(f"Failed to update policy {policy_id}: {e}")
718
            raise
719
    
720
    def create_conditional_policy(self, base_policy_id: str, conditions: Dict) -> str:
721
        """Create conditional policy based on existing policy"""
722
        
723
        base_policy = self.base_manager.getPolicy(base_policy_id)
724
        
725
        # Generate conditional policy ID
726
        condition_hash = hash(json.dumps(conditions, sort_keys=True))
727
        conditional_id = f"{base_policy_id}_conditional_{abs(condition_hash)}"
728
        
729
        # Create conditional rules
730
        conditional_rules = []
731
        for rule in base_policy.rules:
732
            # Add conditions to rule configuration
733
            enhanced_config = rule.configurations.copy() if rule.configurations else {}
734
            enhanced_config['conditions'] = conditions
735
            
736
            conditional_rule = ConfiguredRule(
737
                className=rule.className,
738
                configurations=enhanced_config,
739
                configuredTargets=rule.configuredTargets
740
            )
741
            conditional_rules.append(conditional_rule)
742
        
743
        # Create conditional policy
744
        conditional_policy = Policy(
745
            identifier=conditional_id,
746
            description=f"Conditional variant of {base_policy.description}",
747
            alertOptions=base_policy.alertOptions,
748
            targets=base_policy.targets,
749
            rules=conditional_rules
750
        )
751
        
752
        # Store in cache
753
        self.policy_cache[conditional_id] = conditional_policy
754
        
755
        # Notify listeners
756
        self.notify_change_listeners(conditional_id, 'CREATED')
757
        
758
        return conditional_id
759
    
760
    def get_policy_with_fallback(self, policy_id: str) -> Policy:
761
        """Get policy with cache fallback"""
762
        
763
        # Try cache first
764
        if policy_id in self.policy_cache:
765
            return self.policy_cache[policy_id]
766
        
767
        # Fallback to base manager
768
        try:
769
            return self.base_manager.getPolicy(policy_id)
770
        except Exception:
771
            # Create default policy if not found
772
            return self._create_default_policy(policy_id)
773
    
774
    def _create_default_policy(self, policy_id: str) -> Policy:
775
        """Create default policy for unknown identifiers"""
776
        
777
        default_policy = Policy(
778
            identifier=policy_id,
779
            description=f"Default policy for {policy_id}",
780
            alertOptions=AlertOptions.NEVER,
781
            targets=[],
782
            rules=[]
783
        )
784
        
785
        self.policy_cache[policy_id] = default_policy
786
        return default_policy
787
    
788
    def export_policies_to_json(self, policy_ids: List[str] = None) -> str:
789
        """Export policies to JSON configuration"""
790
        
791
        policies_to_export = policy_ids or list(self.base_manager.policies.keys())
792
        
793
        export_data = []
794
        for policy_id in policies_to_export:
795
            try:
796
                policy = self.get_policy_with_fallback(policy_id)
797
                
798
                policy_data = {
799
                    'identifier': policy.identifier,
800
                    'description': policy.description,
801
                    'shouldSendAlert': policy.alertOptions.value,
802
                    'targets': [
803
                        {
804
                            'retrieve_url': target.retrieve_url,
805
                            'type': target.type
806
                        }
807
                        for target in (policy.targets or [])
808
                    ],
809
                    'rules': [
810
                        {
811
                            'className': rule.className,
812
                            'configurations': rule.configurations or {},
813
                            'targetConfigurations': {}  # Simplified
814
                        }
815
                        for rule in policy.rules
816
                    ]
817
                }
818
                
819
                export_data.append(policy_data)
820
                
821
            except Exception as e:
822
                print(f"Error exporting policy {policy_id}: {e}")
823
        
824
        return json.dumps(export_data, indent=2)
825

826
# Usage example
827
def policy_management_demo():
828
    """Demonstrate dynamic policy management capabilities"""
829
    
830
    dynamic_manager = DynamicPolicyManager()
831
    
832
    # Register change listener
833
    def policy_change_handler(policy_id: str, change_type: str):
834
        print(f"📋 Policy Change: {policy_id} - {change_type}")
835
    
836
    dynamic_manager.register_change_listener(policy_change_handler)
837
    
838
    # Create new policy at runtime
839
    new_policy_config = {
840
        'identifier': 'dynamic_security_policy',
841
        'description': 'Runtime created security policy',
842
        'shouldSendAlert': 'ALWAYS',
843
        'targets': [
844
            {'retrieve_url': 'https://api.security.com/scan', 'type': 'security_endpoint'}
845
        ],
846
        'rules': [
847
            {
848
                'className': 'com.example.rules.ThreatDetectionRule',
849
                'configurations': {
850
                    'sensitivity': 'high',
851
                    'scan_types': ['malware', 'intrusion', 'anomaly']
852
                }
853
            }
854
        ]
855
    }
856
    
857
    new_policy = dynamic_manager.create_policy_runtime(new_policy_config)
858
    print(f"Created policy: {new_policy.identifier}")
859
    
860
    # Update existing policy
861
    updates = {
862
        'description': 'Updated security policy with enhanced monitoring',
863
        'rules': [
864
            {
865
                'className': 'com.example.rules.EnhancedThreatDetectionRule',
866
                'configurations': {
867
                    'sensitivity': 'maximum',
868
                    'scan_types': ['malware', 'intrusion', 'anomaly', 'behavioral'],
869
                    'real_time_monitoring': True
870
                }
871
            }
872
        ]
873
    }
874
    
875
    try:
876
        updated_policy = dynamic_manager.update_policy_configuration('dynamic_security_policy', updates)
877
        print(f"Updated policy: {updated_policy.identifier}")
878
    except Exception as e:
879
        print(f"Update failed: {e}")
880
    
881
    # Create conditional policy
882
    conditions = {
883
        'environment': 'production',
884
        'data_classification': 'sensitive',
885
        'time_window': '09:00-17:00'
886
    }
887
    
888
    conditional_id = dynamic_manager.create_conditional_policy('dynamic_security_policy', conditions)
889
    print(f"Created conditional policy: {conditional_id}")
890
    
891
    # Export policies
892
    exported_config = dynamic_manager.export_policies_to_json(['dynamic_security_policy', conditional_id])
893
    print("Exported policy configuration:")
894
    print(exported_config[:200] + "..." if len(exported_config) > 200 else exported_config)
895

896
# Run the demonstration
897
policy_management_demo()
898
```
899

900
## Best Practices
901

902
### Policy Design
903
- Use clear, descriptive policy identifiers and descriptions
904
- Design policies to be composable and reusable
905
- Implement proper validation for policy configurations
906
- Use appropriate alert options based on business requirements
907

908
### Configuration Management
909
- Store policy configurations in version control
910
- Use environment-specific policy configurations
911
- Implement policy configuration validation
912
- Regular policy configuration backups
913

914
### Rule Development
915
- Create modular, testable rule implementations
916
- Use dependency injection for rule dependencies
917
- Implement comprehensive error handling in rules
918
- Document rule configuration parameters clearly
919

920
### Performance and Scalability
921
- Cache frequently accessed policies
922
- Implement efficient policy loading strategies
923
- Monitor policy execution performance
924
- Use asynchronous execution for complex rule evaluations
925

926
### Governance and Compliance
927
- Implement policy change approval workflows
928
- Maintain audit trails for policy executions
929
- Regular policy effectiveness reviews
930
- Compliance reporting and documentation