SIENTIAPDE-1182
Remove Docker configuration files and refactor project structure - Deleted docker-compose.yml and Dockerfile as part of the project restructuring. - Updated README.md to reflect changes in project setup and configuration. - Introduced a new __init__.py file in the laborious package to provide an overview of the system. - Enhanced documentation across various modules, including metrics, activities, and workflows, to improve clarity and usability. - Added comprehensive docstrings and comments to key classes and methods for better maintainability.
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vitor-aignosi
@@ -15,6 +15,24 @@ OPC_WRITTING_ERROR_CONFIDENCE = 12
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class OPC(BaseActivity):
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"""
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OPC server integration activities for real-time data export.
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This class provides comprehensive OPC UA client functionality for connecting
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to multiple OPC servers and writing prediction data in real-time. It implements
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secure communication with certificate-based authentication and automatic
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reconnection capabilities.
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The class supports multiple OPC servers with individual configurations and
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provides robust error handling and monitoring for production environments.
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Attributes:
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opc_servers (dict): Configuration for multiple OPC servers
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opc_repository (dict): Active OPC repository connections
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logger (Logger): Logging and observability instance
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notification_handler (NotificationHandler): Notification management instance
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"""
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def __init__(self, opc_servers: dict[str, dict[str, Any]],
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logger: Logger, notification_handler: NotificationHandler):
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@@ -29,7 +47,29 @@ class OPC(BaseActivity):
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self.opc_servers = opc_servers
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async def init_opc(self):
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"""
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Initialize OPC server connections and establish communication channels.
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This method iterates through all configured OPC servers and attempts to
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establish secure connections using certificate-based authentication.
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Each server connection is managed independently, and connection failures
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are reported through the notification system.
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The method performs the following operations:
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1. Creates OpcRepository instances for each configured server
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2. Establishes secure connections with certificate validation
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3. Reports connection success/failure through notifications
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4. Logs connection status for operational visibility
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Raises:
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Exception: If OPC repository initialization fails or connection
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establishment encounters critical errors
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Note:
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Connection failures are logged and reported but do not prevent
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the initialization of other OPC servers. Each server is handled
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independently to ensure maximum availability.
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"""
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self.logger.info("Initializing OPC servers...")
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for id, server in self.opc_servers.items():
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self.opc_repository[id] = OpcRepository(
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@@ -67,7 +107,12 @@ class OPC(BaseActivity):
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async def write_data(self, server_id: str, tag: str, data: Any,
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data_type: str, tag_type: str, metadata: dict[str, Any]) -> bool:
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"""
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Write data to OPC server.
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Write data to a specific OPC server tag with comprehensive error handling.
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This method provides a secure and reliable way to write data to OPC servers
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with automatic error handling, notification integration, and detailed logging.
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It validates server availability before attempting write operations and
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provides comprehensive error reporting for operational monitoring.
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Args:
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- server_id (str): The id of the OPC server.
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@@ -108,6 +153,26 @@ class OPC(BaseActivity):
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raise e
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def validate_server(self, server_id: str, metadata: dict[str, Any]) -> bool:
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"""
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Validate that an OPC server is available and configured for write operations.
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This method checks if the specified OPC server exists in the active
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repository and is available for data writing operations. It provides
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immediate feedback for server availability and logs validation failures
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for operational monitoring.
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Args:
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server_id (str): Unique identifier for the OPC server to validate
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metadata (dict[str, Any]): Context metadata for logging and notifications
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Returns:
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bool: True if server is available, False otherwise
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Note:
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Server validation failures are automatically reported through the
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notification system with detailed information about available servers.
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This helps operators quickly identify configuration issues.
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"""
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if self.opc_repository.get(server_id) is None:
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message = f"OPC server {server_id} not found to perform write operation."
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self.send_notification(
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@@ -124,6 +189,32 @@ class OPC(BaseActivity):
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async def manage_output_tags(
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self, server_id: str, config: dict[str, Any], data: DataFrame,
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metadata: dict[str, Any], success: bool) -> tuple[bool, int]:
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"""
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Manage the writing of prediction and confidence data to OPC server tags.
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This method orchestrates the writing of multiple data types to OPC servers
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based on configuration. It handles both prediction data and confidence
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values independently, allowing for flexible tag configuration and
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comprehensive error handling.
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The method supports two main tag types:
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1. Prediction tags: Write actual prediction values to configured OPC tags
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2. Confidence tags: Write confidence scores to separate OPC tags
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Args:
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server_id (str): Unique identifier for the target OPC server
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config (dict[str, Any]): OPC tag configuration containing:
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- prediction_tags (dict, optional): Prediction tag configurations
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- confidence_tags (dict, optional): Confidence tag configurations
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data (DataFrame): DataFrame containing prediction and confidence data
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metadata (dict[str, Any]): Context metadata for logging and notifications
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success (bool): Current success status to maintain across operations
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Returns:
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tuple[bool, int]: (overall_success, total_tags_written)
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- overall_success: True if all configured tags were written successfully
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- total_tags_written: Count of successfully written tags
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"""
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count = 0
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if 'prediction_tags' in config:
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@@ -204,17 +295,29 @@ class OPC(BaseActivity):
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def process_confidence(self, data: DataFrame, success: bool, metadata: dict[str, Any]) -> dict[Any, Any]:
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"""
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Processes the confidence of OPC server write operations and updates the DataFrame accordingly.
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Process prediction confidence based on OPC write operation success.
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If the write operation was not successful, sets the 'prediction_confidence' column in the DataFrame
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to a predefined error confidence value and logs a debug message. Otherwise, logs a success message.
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This method updates the prediction confidence values in the DataFrame
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based on the success status of OPC server write operations. If any
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write operations failed, it sets the confidence to a predefined error
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value to indicate data quality issues.
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The method implements a confidence degradation strategy:
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- Success: Maintains original confidence values
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- Failure: Sets confidence to error value for operational awareness
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Args:
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data (DataFrame): The DataFrame containing the data to be processed.
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success (bool): Indicates whether the data was successfully written to the OPC servers.
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data (DataFrame): DataFrame containing prediction and confidence data
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success (bool): Overall success status of OPC write operations
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metadata (dict[str, Any]): Context metadata for logging and notifications
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Returns:
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dict[Any, Any]: The processed data as a dictionary.
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dict[Any, Any]: Processed data as a dictionary with updated confidence values
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Note:
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The error confidence value (OPC_WRITTING_ERROR_CONFIDENCE = 12) is
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used to indicate that data was not successfully exported to OPC servers.
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This allows downstream systems to handle data quality appropriately.
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"""
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if not success:
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@@ -230,5 +333,24 @@ class OPC(BaseActivity):
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return data.to_dict()
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async def shutdown(self):
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"""
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Gracefully shutdown all OPC server connections and cleanup resources.
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This method ensures proper cleanup of all active OPC server connections
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by calling the disconnect method on each repository instance. It's
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designed to be called during application shutdown to prevent resource
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leaks and ensure clean termination.
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The method performs the following cleanup operations:
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1. Iterates through all active OPC repository connections
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2. Calls disconnect() on each repository instance
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3. Allows for graceful connection termination
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4. Prevents resource leaks and connection hanging
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Note:
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This method should be called during application shutdown to ensure
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proper cleanup. It handles all active connections regardless of
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their current state and provides a clean shutdown experience.
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"""
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for opc in self.opc_repository.values():
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await opc.disconnect()
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