995ba7900a
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.
357 lines
16 KiB
Python
357 lines
16 KiB
Python
from temporalio import activity, workflow
|
|
|
|
|
|
with workflow.unsafe.imports_passed_through():
|
|
from sientia_do.notifications.handlers import CoreNotificationHandler as NotificationHandler
|
|
from sientia_do.notifications.models import NotificationLevel
|
|
from sientia_do.temporal.activities.base import BaseActivity
|
|
from sientia_do.observability.logger import Logger
|
|
from laborious.utils.repository.opc_repository import OpcRepository
|
|
from typing import Any
|
|
import traceback
|
|
from pandas import DataFrame
|
|
|
|
OPC_WRITTING_ERROR_CONFIDENCE = 12
|
|
|
|
|
|
class OPC(BaseActivity):
|
|
"""
|
|
OPC server integration activities for real-time data export.
|
|
|
|
This class provides comprehensive OPC UA client functionality for connecting
|
|
to multiple OPC servers and writing prediction data in real-time. It implements
|
|
secure communication with certificate-based authentication and automatic
|
|
reconnection capabilities.
|
|
|
|
The class supports multiple OPC servers with individual configurations and
|
|
provides robust error handling and monitoring for production environments.
|
|
|
|
Attributes:
|
|
opc_servers (dict): Configuration for multiple OPC servers
|
|
opc_repository (dict): Active OPC repository connections
|
|
logger (Logger): Logging and observability instance
|
|
notification_handler (NotificationHandler): Notification management instance
|
|
"""
|
|
|
|
def __init__(self, opc_servers: dict[str, dict[str, Any]],
|
|
logger: Logger, notification_handler: NotificationHandler):
|
|
|
|
self.logger = logger
|
|
self.notification_handler = notification_handler
|
|
self.opc_servers = opc_servers
|
|
|
|
BaseActivity.__init__(
|
|
self, logger, notification_handler, set_error_counter=True)
|
|
|
|
self.opc_repository: dict[str, OpcRepository] = {}
|
|
self.opc_servers = opc_servers
|
|
|
|
async def init_opc(self):
|
|
"""
|
|
Initialize OPC server connections and establish communication channels.
|
|
|
|
This method iterates through all configured OPC servers and attempts to
|
|
establish secure connections using certificate-based authentication.
|
|
Each server connection is managed independently, and connection failures
|
|
are reported through the notification system.
|
|
|
|
The method performs the following operations:
|
|
1. Creates OpcRepository instances for each configured server
|
|
2. Establishes secure connections with certificate validation
|
|
3. Reports connection success/failure through notifications
|
|
4. Logs connection status for operational visibility
|
|
|
|
Raises:
|
|
Exception: If OPC repository initialization fails or connection
|
|
establishment encounters critical errors
|
|
|
|
Note:
|
|
Connection failures are logged and reported but do not prevent
|
|
the initialization of other OPC servers. Each server is handled
|
|
independently to ensure maximum availability.
|
|
"""
|
|
self.logger.info("Initializing OPC servers...")
|
|
for id, server in self.opc_servers.items():
|
|
self.opc_repository[id] = OpcRepository(
|
|
id=server['id'],
|
|
url=server['url'],
|
|
logger=self.logger,
|
|
server_uri=server['server_uri'],
|
|
cert_path=server['cert_path'],
|
|
private_key_path=server['private_key_path'],
|
|
server_cert_path=server['server_cert_path'],
|
|
notification_handler=self.notification_handler,
|
|
reconnection_interval=server['reconnection_interval'],
|
|
pod_id=self.pod_id
|
|
)
|
|
is_connected, error_data = await self.opc_repository[id].connect()
|
|
if not is_connected:
|
|
self.send_notification(
|
|
metadata={
|
|
'model_id': '-',
|
|
'model_name': '-',
|
|
'workflow_name': '-',
|
|
'schedule_name': 'INITIALIZATION'
|
|
},
|
|
notification_id=error_data['notification_id'],
|
|
message=error_data['message'],
|
|
block=error_data['block'],
|
|
level=error_data.get('level', NotificationLevel.ERROR),
|
|
attachment_content=error_data.get(
|
|
'attachment_content', None)
|
|
)
|
|
else:
|
|
self.logger.info(
|
|
f"OPC server {id} connected successfully.")
|
|
|
|
async def write_data(self, server_id: str, tag: str, data: Any,
|
|
data_type: str, tag_type: str, metadata: dict[str, Any]) -> bool:
|
|
"""
|
|
Write data to a specific OPC server tag with comprehensive error handling.
|
|
|
|
This method provides a secure and reliable way to write data to OPC servers
|
|
with automatic error handling, notification integration, and detailed logging.
|
|
It validates server availability before attempting write operations and
|
|
provides comprehensive error reporting for operational monitoring.
|
|
|
|
Args:
|
|
- server_id (str): The id of the OPC server.
|
|
- tag (str): The tag to write to.
|
|
- data (Any): The data to write.
|
|
- data_type (str): The data type.
|
|
- tag_type (str): The tag type.
|
|
|
|
Returns:
|
|
- bool: True if the data was written successfully, False otherwise.
|
|
"""
|
|
|
|
try:
|
|
is_success, error_data = await self.opc_repository[server_id].write_data(
|
|
tag, data, data_type, self.logger, metadata)
|
|
if not is_success:
|
|
self.send_notification(
|
|
metadata=metadata,
|
|
notification_id=error_data['notification_id'],
|
|
message=error_data['message'],
|
|
block=error_data['block'],
|
|
level=error_data.get('level', NotificationLevel.ERROR),
|
|
attachment_content=error_data.get(
|
|
'attachment_content', None)
|
|
)
|
|
return False
|
|
return True
|
|
except Exception as e:
|
|
trace = traceback.format_exc()
|
|
self.send_notification(
|
|
metadata=metadata,
|
|
notification_id=f"WRITE_OPC_{tag_type.upper()}_ERROR",
|
|
message=f"Error writing data to OPC server: {e}",
|
|
block="write_opc_data",
|
|
level=NotificationLevel.ERROR,
|
|
attachment_content=trace
|
|
)
|
|
raise e
|
|
|
|
def validate_server(self, server_id: str, metadata: dict[str, Any]) -> bool:
|
|
"""
|
|
Validate that an OPC server is available and configured for write operations.
|
|
|
|
This method checks if the specified OPC server exists in the active
|
|
repository and is available for data writing operations. It provides
|
|
immediate feedback for server availability and logs validation failures
|
|
for operational monitoring.
|
|
|
|
Args:
|
|
server_id (str): Unique identifier for the OPC server to validate
|
|
metadata (dict[str, Any]): Context metadata for logging and notifications
|
|
|
|
Returns:
|
|
bool: True if server is available, False otherwise
|
|
|
|
Note:
|
|
Server validation failures are automatically reported through the
|
|
notification system with detailed information about available servers.
|
|
This helps operators quickly identify configuration issues.
|
|
"""
|
|
if self.opc_repository.get(server_id) is None:
|
|
message = f"OPC server {server_id} not found to perform write operation."
|
|
self.send_notification(
|
|
metadata=metadata,
|
|
notification_id="OPC_SERVER_NOT_FOUND",
|
|
message=message,
|
|
block="write_opc_data",
|
|
level=NotificationLevel.ERROR,
|
|
attachment_content=f"OPC servers: {list(self.opc_repository.keys())}"
|
|
)
|
|
return False
|
|
return True
|
|
|
|
async def manage_output_tags(
|
|
self, server_id: str, config: dict[str, Any], data: DataFrame,
|
|
metadata: dict[str, Any], success: bool) -> tuple[bool, int]:
|
|
"""
|
|
Manage the writing of prediction and confidence data to OPC server tags.
|
|
|
|
This method orchestrates the writing of multiple data types to OPC servers
|
|
based on configuration. It handles both prediction data and confidence
|
|
values independently, allowing for flexible tag configuration and
|
|
comprehensive error handling.
|
|
|
|
The method supports two main tag types:
|
|
1. Prediction tags: Write actual prediction values to configured OPC tags
|
|
2. Confidence tags: Write confidence scores to separate OPC tags
|
|
|
|
Args:
|
|
server_id (str): Unique identifier for the target OPC server
|
|
config (dict[str, Any]): OPC tag configuration containing:
|
|
- prediction_tags (dict, optional): Prediction tag configurations
|
|
- confidence_tags (dict, optional): Confidence tag configurations
|
|
data (DataFrame): DataFrame containing prediction and confidence data
|
|
metadata (dict[str, Any]): Context metadata for logging and notifications
|
|
success (bool): Current success status to maintain across operations
|
|
|
|
Returns:
|
|
tuple[bool, int]: (overall_success, total_tags_written)
|
|
- overall_success: True if all configured tags were written successfully
|
|
- total_tags_written: Count of successfully written tags
|
|
"""
|
|
|
|
count = 0
|
|
if 'prediction_tags' in config:
|
|
for tag, tag_config in config['prediction_tags'].items():
|
|
local_success = await self.write_data(
|
|
server_id=server_id,
|
|
tag=tag,
|
|
data=data.head(1)['prediction'].values[0],
|
|
data_type=tag_config['data_type'],
|
|
tag_type='prediction',
|
|
metadata=metadata
|
|
)
|
|
if local_success:
|
|
self.info(
|
|
f"Prediction data written to OPC server {server_id} for tag {tag}.", metadata)
|
|
count += 1
|
|
success = success and local_success
|
|
|
|
if 'confidence_tags' in config:
|
|
for tag, tag_config in config['confidence_tags'].items():
|
|
local_success = await self.write_data(
|
|
server_id=server_id,
|
|
tag=tag,
|
|
data=data.head(1)['prediction_confidence'].values[0],
|
|
data_type=tag_config['data_type'],
|
|
tag_type='confidence',
|
|
metadata=metadata
|
|
)
|
|
if local_success:
|
|
self.info(
|
|
f"Confidence data written to OPC server {server_id} for tag {tag}.", metadata)
|
|
count += 1
|
|
success = success and local_success
|
|
|
|
return success, count
|
|
|
|
@activity.defn(name='write_opc_data')
|
|
async def write_opc_data(self, input_data: dict[str, Any]) -> dict[Any, Any]:
|
|
"""
|
|
Write prediction and confidence data to OPC servers. The two writing
|
|
operations are optional and independent of each other.
|
|
|
|
Args:
|
|
- input_data(dict[str, Any]): The input data. Contains the following keys:
|
|
- data(dict[str, Any]): The dataframe that contains the data to write
|
|
to the OPC servers.
|
|
- opc_output_config(dict[str, Any]): The OPC writing configuration.
|
|
The keys are the OPC server names and the values contain:
|
|
- prediction_tags(dict[str, Any]): The tags to write to the OPC servers.
|
|
- confidence_tags(dict[str, Any]): The tags to write to the OPC servers.
|
|
|
|
Returns:
|
|
- dict[Any, Any]: The data that was written to the OPC servers.
|
|
|
|
"""
|
|
metadata = input_data['metadata']
|
|
self.info("Writing data to OPC servers...", metadata)
|
|
data = DataFrame(input_data['data'])
|
|
opc_output_config = input_data['opc_output_config']
|
|
self.info(f"Data to write: {data.size} rows", metadata)
|
|
|
|
success = True
|
|
|
|
for server_id, config in opc_output_config.items():
|
|
|
|
if not self.validate_server(server_id, metadata):
|
|
success = False
|
|
continue
|
|
|
|
local_success, local_count = await self.manage_output_tags(
|
|
server_id, config, data, metadata, success)
|
|
success = success and local_success
|
|
|
|
self.info(
|
|
f"Process completed for OPC server {server_id}: {local_count} of {len(config['prediction_tags'])} prediction tags and {len(config['confidence_tags'])} confidence tags", metadata)
|
|
|
|
return self.process_confidence(data, success, metadata)
|
|
|
|
def process_confidence(self, data: DataFrame, success: bool, metadata: dict[str, Any]) -> dict[Any, Any]:
|
|
"""
|
|
Process prediction confidence based on OPC write operation success.
|
|
|
|
This method updates the prediction confidence values in the DataFrame
|
|
based on the success status of OPC server write operations. If any
|
|
write operations failed, it sets the confidence to a predefined error
|
|
value to indicate data quality issues.
|
|
|
|
The method implements a confidence degradation strategy:
|
|
- Success: Maintains original confidence values
|
|
- Failure: Sets confidence to error value for operational awareness
|
|
|
|
Args:
|
|
data (DataFrame): DataFrame containing prediction and confidence data
|
|
success (bool): Overall success status of OPC write operations
|
|
metadata (dict[str, Any]): Context metadata for logging and notifications
|
|
|
|
Returns:
|
|
dict[Any, Any]: Processed data as a dictionary with updated confidence values
|
|
|
|
Note:
|
|
The error confidence value (OPC_WRITTING_ERROR_CONFIDENCE = 12) is
|
|
used to indicate that data was not successfully exported to OPC servers.
|
|
This allows downstream systems to handle data quality appropriately.
|
|
"""
|
|
|
|
if not success:
|
|
data['prediction_confidence'] = OPC_WRITTING_ERROR_CONFIDENCE
|
|
self.debug(
|
|
f"Some data could not be written to OPC servers, setting confidence to {OPC_WRITTING_ERROR_CONFIDENCE}.",
|
|
metadata
|
|
)
|
|
|
|
else:
|
|
self.debug("Data written to OPC servers successfully.", metadata)
|
|
|
|
return data.to_dict()
|
|
|
|
async def shutdown(self):
|
|
"""
|
|
Gracefully shutdown all OPC server connections and cleanup resources.
|
|
|
|
This method ensures proper cleanup of all active OPC server connections
|
|
by calling the disconnect method on each repository instance. It's
|
|
designed to be called during application shutdown to prevent resource
|
|
leaks and ensure clean termination.
|
|
|
|
The method performs the following cleanup operations:
|
|
1. Iterates through all active OPC repository connections
|
|
2. Calls disconnect() on each repository instance
|
|
3. Allows for graceful connection termination
|
|
4. Prevents resource leaks and connection hanging
|
|
|
|
Note:
|
|
This method should be called during application shutdown to ensure
|
|
proper cleanup. It handles all active connections regardless of
|
|
their current state and provides a clean shutdown experience.
|
|
"""
|
|
for opc in self.opc_repository.values():
|
|
await opc.disconnect()
|