SIENTIAPDE-1445
Enhance Activities and API Integration - Updated Activities class to include API operations for external data ingestion. - Added API configuration builder to connectors_config.py for environment variable management. - Integrated API configuration into worker setup. - Expanded unit tests to cover new API functionality and configuration handling. - Updated requirements.txt to include pycurl and prometheus-client for enhanced metrics support.
This commit is contained in:
@@ -5,3 +5,4 @@ redis
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pymongo
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git+ssh://git@github.com/Aignosi/sientia-dataops-library.git@1.6.1
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prometheus-client
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pycurl
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@@ -9,12 +9,13 @@ with workflow.unsafe.imports_passed_through():
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from sientia_do.observability.logger import Logger
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from sientia_do.temporal.activities.postgres import Postgres
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from scouter.activities.api import API
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from scouter.activities.gates import Gates
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from scouter.activities.mongodb import MongoDB
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from scouter.activities.redis import Redis
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class Activities(Postgres, Redis, Gates, MongoDB):
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class Activities(Postgres, Redis, Gates, MongoDB, API):
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"""
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Unified activities class that combines multiple data processing services.
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@@ -24,6 +25,7 @@ class Activities(Postgres, Redis, Gates, MongoDB):
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- Redis operations for caching and temporary storage
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- Data quality gates and filtering
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- MongoDB operations for data retrieval
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- PI Web API operations for external data ingestion
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- Notification handling and logging
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The class implements the multiple inheritance pattern to provide a unified
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@@ -35,6 +37,7 @@ class Activities(Postgres, Redis, Gates, MongoDB):
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postgres_config: dict[str, Any],
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redis_config: dict[str, Any],
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mongodb_config: dict[str, Any],
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api_config: dict[str, Any],
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logger: Logger,
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notification_handler: NotificationHandler,
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):
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@@ -48,6 +51,8 @@ class Activities(Postgres, Redis, Gates, MongoDB):
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Required fields: host, port, username, password
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mongodb_config (dict[str, Any]): MongoDB connection configuration.
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Required fields: connection_string, database_name
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api_config (dict[str, Any]): PI Web API configuration.
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Required fields: base_url, auth_type, auth_token
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logger (Logger): Logger instance for application logging
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notification_handler (NotificationHandler): Handler for system notifications
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"""
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@@ -100,6 +105,17 @@ class Activities(Postgres, Redis, Gates, MongoDB):
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metrics_controller=metrics_controller,
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)
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# Initialize API
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API.__init__(
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self,
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base_url=api_config['base_url'],
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auth_type=api_config['auth_type'],
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auth_token=api_config['auth_token'],
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logger=logger,
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notification_handler=notification_handler,
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metrics_controller=metrics_controller,
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)
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self.pod_id = getenv('HOSTNAME', 'localhost')
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def shutdown(self):
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@@ -113,3 +129,4 @@ class Activities(Postgres, Redis, Gates, MongoDB):
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MongoDB.close(self)
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Redis.close(self)
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Gates.close(self)
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API.close(self)
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133
scouter/activities/api.py
Normal file
133
scouter/activities/api.py
Normal file
@@ -0,0 +1,133 @@
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from temporalio import activity, workflow
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with workflow.unsafe.imports_passed_through():
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import traceback
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from typing import Any
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from sientia_do.notifications.handlers import NotificationHandler
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from sientia_do.notifications.models import NotificationLevel
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from sientia_do.observability.logger import Logger
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from sientia_do.observability.metrics_controller import MetricsController
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from sientia_do.observability.sientia_monitoring import SientiaMonitoring
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from scouter.utils.clients.pi_web_api_client import PIWebAPIClient
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class API(SientiaMonitoring):
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"""
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PI Web API operations for data retrieval.
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This class provides Temporal activities for interacting with the PI Web API
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to retrieve tag values and historical data. It implements:
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- Tag value retrieval from PI Web API endpoints
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- Data quality filtering and validation
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- Error handling with notifications
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- Metrics collection for monitoring
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The class wraps the PIWebAPIClient to provide Temporal-aware activity methods
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that can be used in workflow orchestration.
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"""
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def __init__(
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self,
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base_url: str,
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auth_type: str,
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auth_token: str,
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logger: Logger,
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notification_handler: NotificationHandler,
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metrics_controller: MetricsController,
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) -> None:
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"""
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Initialize API activity with PI Web API client.
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Args:
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base_url (str): Base URL of the PI Web API server
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auth_type (str): Authentication type ('basic' or 'bearer')
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auth_token (str): Authentication token
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logger (Logger): Logger instance for operation logging
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notification_handler (NotificationHandler): Handler for system notifications
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metrics_controller (MetricsController): Controller for metrics collection
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"""
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SientiaMonitoring.__init__(self, logger, notification_handler, metrics_controller)
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self.pi_web_api_client = PIWebAPIClient(
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base_url=base_url,
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auth_config={
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'type': auth_type,
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'token': auth_token,
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},
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logger=logger,
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notification_handler=notification_handler,
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metrics_controller=metrics_controller,
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)
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def close(self) -> None:
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"""
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Close the PI Web API client and shutdown monitoring services.
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"""
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self.pi_web_api_client.close()
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SientiaMonitoring.shutdown(self)
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@activity.defn(name='get_tag_values')
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async def get_tag_values(self, input_data: dict[str, Any]) -> list[dict]:
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"""
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Retrieve tag values from PI Web API for specified WebIds.
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This activity fetches historical or real-time data from the PI Web API
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for a set of configured tags. It returns the data as a list of dictionaries
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suitable for further processing in the workflow.
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Args:
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input_data (dict[str, Any]): Activity input parameters.
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Required fields:
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- metadata (dict[str, Any]): Workflow execution metadata
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- endpoint (str): PI Web API endpoint path
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- web_ids (dict[str, str | None]): Tag names mapped to WebIds
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- period (dict[str, str]): Time period with 'start_time' field
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- api_timeout (int): Request timeout in seconds
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- max_count (int, optional): Maximum data points per tag. Defaults to 1
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Returns:
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list[dict]: List of data records, each containing:
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- timestamp: Data point timestamp
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- name: Tag name
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- value: Numeric value
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- tag: WebId
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Raises:
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PIMSRequestError: If API request fails
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Exception: If data retrieval or processing fails
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"""
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metadata = input_data['metadata']
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endpoint = input_data['endpoint']
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web_ids = input_data['web_ids']
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period = input_data['period']
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max_count = input_data.get('max_count', 1)
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api_timeout = input_data['api_timeout']
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self.info(f'Getting tag values from {endpoint}', metadata=metadata)
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self.debug(f'Web IDs: {web_ids}', metadata=metadata)
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try:
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latest_values = await self.pi_web_api_client.get_latest_values_df(
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endpoint=endpoint,
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web_ids=web_ids,
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start_time=period,
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max_count=max_count,
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metadata=metadata,
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timeout=api_timeout,
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)
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except Exception as e:
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await self.send_notification_async(
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metadata=metadata,
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notification_id='PI_WEB_API_REQUEST_ERROR',
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message=f'Error getting tag values from PI Web API: {e}',
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block='get_tag_values',
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level=NotificationLevel.ERROR,
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attachment_content=traceback.format_exc(),
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)
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raise e
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self.debug(f'Latest values: {latest_values}', metadata=metadata)
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self.info(f'Gathered {len(latest_values)} tag values', metadata=metadata)
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return latest_values.to_dict(orient='records')
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@@ -1,4 +1,5 @@
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from prometheus_client import Counter, Gauge
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from prometheus_client import Counter, Gauge, Histogram
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from sientia_do.observability.metrics import CORE_LABELS as SIENTIA_CORE_LABELS
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# Application health and status metrics
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APP_UP = Gauge(
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@@ -23,3 +24,23 @@ TAG_CHANGES_MONITOR = Gauge(
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'Current value change of each tag',
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[*CORE_LABELS, 'tag_name'],
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)
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# Generic REST client metrics
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GENERIC_REST_CLIENT_LAG = Histogram(
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'scouter_generic_rest_client_lag',
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'Lag time for a request to a generic REST client',
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SIENTIA_CORE_LABELS,
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)
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GENERIC_REST_READ_COUNT = Counter(
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'scouter_generic_rest_client_read_count',
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'Number of reads from a generic REST client',
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SIENTIA_CORE_LABELS,
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)
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GENERIC_REST_READ_ERROR_COUNT = Counter(
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'scouter_generic_rest_client_read_error_count',
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'Number of read errors from a generic REST client',
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SIENTIA_CORE_LABELS,
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)
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335
scouter/utils/clients/pi_web_api_client.py
Normal file
335
scouter/utils/clients/pi_web_api_client.py
Normal file
@@ -0,0 +1,335 @@
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import io
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import json
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import time
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import warnings
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from typing import Any
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from urllib.parse import urlencode
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import pandas as pd
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import pycurl
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from sientia_do.notifications.handlers import NotificationHandler
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from sientia_do.observability.logger import Logger
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from sientia_do.observability.metrics_controller import MetricsController
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from sientia_do.observability.sientia_monitoring import SientiaMonitoring
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from scouter import metrics
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warnings.simplefilter('ignore') # Ignore warnings such as 'verify=False'
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class PIMSRequestError(Exception):
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"""Generic error for failed requests to PI Web API using pycurl."""
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pass
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class PIWebAPIClient(SientiaMonitoring):
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"""
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Client for interacting with the PI Web API.
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This class provides a robust interface for querying historical and real-time
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data from OSIsoft PI systems through the PI Web API. It implements:
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- Asynchronous HTTP requests using pycurl
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- Authentication support (Basic and Bearer)
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- Automatic data normalization and timestamp handling
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- Comprehensive error handling and monitoring
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- Metrics collection for observability
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The client is designed for high-performance data retrieval with proper
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connection management and error recovery mechanisms.
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"""
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def __init__(
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self,
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base_url: str,
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auth_config: dict[str, Any],
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logger: Logger,
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notification_handler: NotificationHandler,
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metrics_controller: MetricsController,
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headers_config: dict[str, Any] | None = None,
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) -> None:
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"""
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Initialize the PI Web API client with connection parameters.
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Args:
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base_url (str): Base URL of the PI Web API server
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auth_config (dict[str, Any]): Authentication configuration.
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Required fields:
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- type (str): Authentication type ('basic' or 'bearer')
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- token (str): Authentication token
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logger (Logger): Logger instance for operation logging
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notification_handler (NotificationHandler): Handler for system notifications
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metrics_controller (MetricsController): Controller for metrics collection
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headers_config (dict[str, Any], optional): HTTP headers configuration.
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Default headers include content-type, accept, and x-requested-with
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max_concurrency (int, optional): Maximum number of concurrent requests. Defaults to 8
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"""
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if headers_config is None:
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headers_config = {
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'Content-Type': 'application/json',
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'Accept': 'application/json',
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'x-requested-with': 'XMLHttpRequest',
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}
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SientiaMonitoring.__init__(self, logger, notification_handler, metrics_controller)
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self.base_url = base_url.rstrip('/')
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# auth_config spec:
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# 'type': 'basic' or 'bearer',
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# 'token': 'token',
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self.auth_config = auth_config
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self.auth_config['type'] = self.auth_config['type'].lower()
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self.headers: dict[str, str] = headers_config
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self.authenticate()
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def close(self) -> None:
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"""
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Close the client and shutdown monitoring services.
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"""
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SientiaMonitoring.shutdown(self)
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def _to_clean_timestamp(self, series: pd.Series) -> pd.Series:
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"""
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Convert a Series of timestamps to datetime, UTC, and round to the nearest second.
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Args:
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series (pd.Series): Series containing timestamp values
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Returns:
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pd.Series: Cleaned timestamp series in UTC, floored to seconds
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"""
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series = pd.to_datetime(series, utc=True, errors='coerce')
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return series.dt.floor('s')
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def _extract_numeric(self, value: Any) -> float | None:
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"""
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Normalize a value (potentially nested) to float.
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This method handles PI Web API response values that may be nested
|
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in dictionaries or other structures, extracting the numeric value.
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|
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Args:
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value (Any): Value to extract and normalize
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Returns:
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float | None: Numeric value as float, or None if conversion fails
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"""
|
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if isinstance(value, dict):
|
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value = value.get('Value', value)
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return pd.to_numeric(value, errors='coerce')
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def authenticate(self):
|
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"""
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Configure authentication headers based on auth_config.
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This method sets up the Authorization header using either Basic or Bearer
|
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authentication based on the configured authentication type.
|
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Raises:
|
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ValueError: If authentication type is not 'basic' or 'bearer'
|
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"""
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self.logger.info(f'Authenticating with {self.auth_config["type"]} authentication')
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|
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if self.auth_config['type'] == 'basic':
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self.headers['Authorization'] = f'Basic {self.auth_config["token"]}'
|
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elif self.auth_config['type'] == 'bearer':
|
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self.headers['Authorization'] = f'Bearer {self.auth_config["token"]}'
|
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else:
|
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raise ValueError(f'Invalid authentication type: {self.auth_config["type"]}')
|
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|
||||
async def _curl_get_json(
|
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self,
|
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url: str,
|
||||
params: list[tuple[str, str]] | None = None,
|
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timeout: int = 30,
|
||||
verify: bool = True,
|
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metadata: dict[str, Any] | None = None,
|
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) -> dict[str, Any]:
|
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"""
|
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Perform a GET request using pycurl and return the decoded JSON response.
|
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|
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This method executes an asynchronous HTTP GET request with proper error handling,
|
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metrics collection, and timeout management. It automatically tracks request
|
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latency and emits monitoring metrics.
|
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|
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Args:
|
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url (str): Target URL for the GET request
|
||||
params (list[tuple[str, str]], optional): Query parameters as list of tuples.
|
||||
Each tuple contains (parameter_name, parameter_value)
|
||||
timeout (int, optional): Request timeout in seconds. Defaults to 30
|
||||
verify (bool, optional): Verify SSL certificates. Defaults to True
|
||||
metadata (dict[str, Any], optional): Workflow execution metadata for tracking
|
||||
|
||||
Returns:
|
||||
dict[str, Any]: Parsed JSON response body
|
||||
|
||||
Raises:
|
||||
PIMSRequestError: If HTTP error, connection error, or JSON parsing error occurs
|
||||
"""
|
||||
if metadata is None:
|
||||
metadata = {}
|
||||
|
||||
buffer = io.BytesIO()
|
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c = pycurl.Curl()
|
||||
|
||||
core_labels = self.get_core_labels(metadata=metadata, operation_type='get_json')
|
||||
|
||||
try:
|
||||
if params:
|
||||
query_string = urlencode(params, doseq=True)
|
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full_url = f'{url}?{query_string}'
|
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else:
|
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full_url = url
|
||||
|
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c.setopt(pycurl.URL, full_url.encode('utf-8'))
|
||||
c.setopt(pycurl.WRITEDATA, buffer)
|
||||
|
||||
# Configure HTTP headers
|
||||
header_list = [f'{k}: {v}' for k, v in self.headers.items()]
|
||||
if header_list:
|
||||
c.setopt(pycurl.HTTPHEADER, header_list)
|
||||
|
||||
# Set request timeout
|
||||
c.setopt(pycurl.TIMEOUT, timeout)
|
||||
|
||||
# Configure SSL verification
|
||||
if not verify:
|
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c.setopt(pycurl.SSL_VERIFYPEER, 0)
|
||||
c.setopt(pycurl.SSL_VERIFYHOST, 0)
|
||||
|
||||
start_time = time.time()
|
||||
try:
|
||||
c.perform()
|
||||
except Exception as e:
|
||||
await self.emit_metric(
|
||||
metric_object=metrics.GENERIC_REST_READ_ERROR_COUNT,
|
||||
tags=core_labels,
|
||||
)
|
||||
raise e
|
||||
await self.observe_lag(
|
||||
start_time=start_time,
|
||||
metric_object=metrics.GENERIC_REST_CLIENT_LAG,
|
||||
tags=core_labels,
|
||||
)
|
||||
await self.emit_metric(
|
||||
metric_object=metrics.GENERIC_REST_READ_COUNT,
|
||||
tags=core_labels,
|
||||
)
|
||||
|
||||
status_code = c.getinfo(pycurl.RESPONSE_CODE)
|
||||
body = buffer.getvalue().decode('utf-8', errors='replace')
|
||||
|
||||
if status_code >= 400:
|
||||
await self.emit_metric(
|
||||
metric_object=metrics.GENERIC_REST_READ_ERROR_COUNT,
|
||||
tags=core_labels,
|
||||
)
|
||||
raise PIMSRequestError(f"HTTP {status_code} calling '{full_url}': {body[:200]}")
|
||||
|
||||
try:
|
||||
return json.loads(body)
|
||||
except json.JSONDecodeError as e:
|
||||
raise PIMSRequestError(
|
||||
f"Error decoding JSON response from '{full_url}': {e}; body: {body[:200]}"
|
||||
) from e
|
||||
|
||||
except pycurl.error as e:
|
||||
raise PIMSRequestError(f"Connection error calling '{url}': {e}") from e
|
||||
finally:
|
||||
c.close()
|
||||
|
||||
async def get_latest_values_df(
|
||||
self,
|
||||
web_ids: dict[str, dict[str, str]],
|
||||
endpoint: str,
|
||||
timeout: int = 30,
|
||||
start_time: str = '*-1d',
|
||||
end_time: str = '*',
|
||||
max_count: int | None = 1,
|
||||
metadata: dict[str, Any] | None = None,
|
||||
) -> pd.DataFrame:
|
||||
"""
|
||||
Retrieve historical values for multiple WebIds using PI Web API streamsets.
|
||||
|
||||
This method queries the PI Web API's /streamsets/recorded endpoint to fetch
|
||||
historical data for multiple tags simultaneously. It returns a normalized
|
||||
DataFrame with timestamps, tag names, values, and WebIds.
|
||||
|
||||
Args:
|
||||
web_ids (dict[str, str | None]): Dictionary mapping tag names to their WebIds.
|
||||
None values are filtered out before querying
|
||||
endpoint (str): PI Web API endpoint path (e.g., '/streamsets/recorded')
|
||||
timeout (int, optional): Request timeout in seconds. Defaults to 30
|
||||
start_time (str, optional): Start time in PI Web API format (e.g., "*-50d").
|
||||
Defaults to "*-1d" (1 day ago)
|
||||
end_time (str, optional): End time in PI Web API format (e.g., "*").
|
||||
Defaults to "*" (current time)
|
||||
max_count (int, optional): Maximum number of data points per series.
|
||||
Defaults to 1. If None, maxCount parameter is not sent
|
||||
metadata (dict[str, Any], optional): Workflow execution metadata for tracking
|
||||
|
||||
Returns:
|
||||
pd.DataFrame: DataFrame with columns:
|
||||
- timestamp: Cleaned timestamp (UTC, floored to seconds)
|
||||
- name: Tag name
|
||||
- value: Numeric value (normalized)
|
||||
- tag: WebId of the tag
|
||||
Returns empty DataFrame if no data is found
|
||||
|
||||
Raises:
|
||||
PIMSRequestError: If API request fails or returns invalid data
|
||||
"""
|
||||
if metadata is None:
|
||||
metadata = {}
|
||||
|
||||
url = f'{self.base_url}{endpoint}'
|
||||
|
||||
# Build query parameters with WebIds (filtering out None values)
|
||||
params: list[tuple[str, str]] = [('webid', web_id['webid']) for web_id in web_ids.values()]
|
||||
params.extend(
|
||||
[
|
||||
('startTime', start_time),
|
||||
('endtime', end_time),
|
||||
('selectedFields', 'Items.Name;Items.Items.Timestamp;Items.Items.Value'),
|
||||
]
|
||||
)
|
||||
|
||||
params.append(('maxCount', str(max_count)))
|
||||
|
||||
data = await self._curl_get_json(
|
||||
url=url,
|
||||
params=params,
|
||||
timeout=timeout,
|
||||
verify=False,
|
||||
metadata=metadata,
|
||||
)
|
||||
|
||||
raw_data = data.get('Items', [])
|
||||
|
||||
records = []
|
||||
for entry in raw_data:
|
||||
tag_name = entry.get('Name')
|
||||
series_items = entry.get('Items', [])
|
||||
for it in series_items:
|
||||
if isinstance(it, dict) and 'Timestamp' in it and 'Value' in it:
|
||||
ts = it.get('Timestamp')
|
||||
val = it.get('Value')
|
||||
web_id = web_ids.get(tag_name)
|
||||
if ts is not None:
|
||||
records.append(
|
||||
{
|
||||
'timestamp': ts,
|
||||
'name': tag_name,
|
||||
'value': self._extract_numeric(val),
|
||||
'tag': web_id,
|
||||
}
|
||||
)
|
||||
|
||||
if not records:
|
||||
return pd.DataFrame()
|
||||
|
||||
df = pd.DataFrame.from_records(records)
|
||||
df['timestamp'] = self._to_clean_timestamp(df['timestamp'])
|
||||
|
||||
return df
|
||||
@@ -83,6 +83,23 @@ def build_mongodb_config() -> dict[str, Any]:
|
||||
}
|
||||
|
||||
|
||||
def build_api_config() -> dict[str, Any]:
|
||||
"""
|
||||
Build API connection configuration from environment variables.
|
||||
|
||||
Returns:
|
||||
dict[str, Any]: API configuration dictionary with keys:
|
||||
- base_url: API base URL (default: https://pi.example.com)
|
||||
- auth_type: API authentication type (default: basic)
|
||||
- auth_token: API authentication token (default: None)
|
||||
"""
|
||||
return {
|
||||
'base_url': getenv('API_BASE_URL', 'https://pi.example.com'),
|
||||
'auth_type': getenv('API_AUTH_TYPE', 'basic'),
|
||||
'auth_token': getenv('API_AUTH_TOKEN', None),
|
||||
}
|
||||
|
||||
|
||||
def build_druid_config() -> dict[str, Any]:
|
||||
"""
|
||||
Build Apache Druid connection configuration from environment variables.
|
||||
|
||||
@@ -15,6 +15,7 @@ with workflow.unsafe.imports_passed_through():
|
||||
from scouter import metrics
|
||||
from scouter.activities.activities import Activities
|
||||
from scouter.utils.connectors_config import (
|
||||
build_api_config,
|
||||
build_mongodb_config,
|
||||
build_postgres_config,
|
||||
build_redis_config,
|
||||
@@ -103,6 +104,7 @@ async def main():
|
||||
postgres_config=build_postgres_config(),
|
||||
redis_config=build_redis_config(),
|
||||
mongodb_config=build_mongodb_config(),
|
||||
api_config=build_api_config(),
|
||||
)
|
||||
|
||||
logger.custom_info(f'Starting SDK Metrics Server on port {SDK_METRICS_PORT}...', metadata)
|
||||
|
||||
101
scouter/workflow/pi_web_api_scouter.py
Normal file
101
scouter/workflow/pi_web_api_scouter.py
Normal file
@@ -0,0 +1,101 @@
|
||||
from temporalio import workflow
|
||||
|
||||
with workflow.unsafe.imports_passed_through():
|
||||
from datetime import timedelta
|
||||
from typing import Any
|
||||
|
||||
from sientia_do.temporal.policies import retry_policy
|
||||
|
||||
from scouter.activities.activities import Activities
|
||||
|
||||
|
||||
@workflow.defn(name='pi_web_api_scouter')
|
||||
class PIWebAPIScouter:
|
||||
"""
|
||||
PI Web API Scouter workflow that orchestrates data ingestion from PI systems.
|
||||
|
||||
This workflow serves as the entry point for PI Web API data processing pipelines.
|
||||
Unlike the standard Scouter that loads from MongoDB, this workflow directly queries
|
||||
PI Web API endpoints to retrieve tag values and processes them for downstream use.
|
||||
|
||||
The workflow implements a direct API ingestion pattern with:
|
||||
- Real-time data retrieval from PI Web API
|
||||
- Configurable time periods and data point limits
|
||||
- Error handling and retry policies
|
||||
- Child workflow orchestration for data processing
|
||||
- Integration with CoreScouter for standardized processing
|
||||
"""
|
||||
|
||||
@workflow.run
|
||||
async def run(self, input_data: dict[str, Any]) -> None:
|
||||
"""
|
||||
Execute the PI Web API Scouter workflow.
|
||||
|
||||
This method orchestrates the complete data ingestion process from PI Web API:
|
||||
1. Retrieves tag values from PI Web API using configured WebIds
|
||||
2. Validates and normalizes the retrieved data
|
||||
3. Delegates data processing to the CoreScouter workflow
|
||||
|
||||
Args:
|
||||
input_data (dict[str, Any]): Configuration and parameters for the workflow execution.
|
||||
Required fields:
|
||||
- model_name (str): Name of the data model being processed
|
||||
- model_id (str): Unique identifier for the data model
|
||||
- schedule_name (str): Unique identifier for the data collection schedule
|
||||
- endpoint (str): PI Web API endpoint path (e.g., '/streamsets/recorded')
|
||||
- web_ids (dict[str, str | None]): Mapping of tag names to WebIds
|
||||
- period (dict[str, str]): Time period configuration with 'start_time'
|
||||
- api_timeout (int): Request timeout in seconds for PI Web API calls
|
||||
- max_count (int, optional): Maximum data points per tag. Defaults to 1
|
||||
- trigger_laborious (bool): Flag to enable intensive data processing
|
||||
- filters (dict[str, str]): Data quality filters configuration
|
||||
- schema (str): Target database schema for data export
|
||||
- table_name (str): Target table name for data export
|
||||
- retention_time (int): Data retention period in Redis (seconds)
|
||||
- model_tags (dict[str, Any]): Tag-specific configuration including:
|
||||
- data_range: [min, max] values for data validation
|
||||
- aggr_function: Aggregation method (avg, mdn, max, min, lts)
|
||||
- frequency: Data collection frequency in milliseconds
|
||||
- topics: List of Kafka topics for data routing
|
||||
|
||||
Returns:
|
||||
None: This workflow doesn't return data, it orchestrates data processing
|
||||
|
||||
Raises:
|
||||
WorkflowExecutionError: If workflow execution fails
|
||||
ActivityExecutionError: If any activity fails after retry attempts
|
||||
PIMSRequestError: If PI Web API request fails
|
||||
"""
|
||||
|
||||
input_data['workflow_name'] = 'scouter'
|
||||
|
||||
metadata = {
|
||||
'metadata': {
|
||||
'model_id': input_data['model_id'],
|
||||
'model_name': input_data['model_name'],
|
||||
'schedule_name': input_data['schedule_name'],
|
||||
'workflow_name': input_data['workflow_name'],
|
||||
}
|
||||
}
|
||||
|
||||
data = await workflow.execute_local_activity_method(
|
||||
Activities.get_tag_values,
|
||||
{
|
||||
**metadata,
|
||||
'endpoint': input_data['endpoint'],
|
||||
'web_ids': input_data['model_tags'],
|
||||
'period': input_data['period'],
|
||||
'api_timeout': input_data['api_timeout'],
|
||||
'max_count': input_data.get('max_count', 1),
|
||||
},
|
||||
start_to_close_timeout=timedelta(seconds=60),
|
||||
retry_policy=retry_policy,
|
||||
)
|
||||
|
||||
if not data:
|
||||
return
|
||||
|
||||
input_data['data'] = data
|
||||
input_data['metadata'] = metadata
|
||||
|
||||
await workflow.execute_child_workflow('subworkflow.core_scouter', input_data)
|
||||
@@ -3,6 +3,7 @@ from unittest.mock import ANY, MagicMock, patch
|
||||
from sientia_do.temporal.activities.postgres import Postgres
|
||||
|
||||
from scouter.activities.activities import Activities
|
||||
from scouter.activities.api import API
|
||||
from scouter.activities.gates import Gates
|
||||
from scouter.activities.mongodb import MongoDB
|
||||
from scouter.activities.redis import Redis
|
||||
@@ -12,9 +13,15 @@ from scouter.activities.redis import Redis
|
||||
@patch('scouter.activities.activities.Postgres.__init__')
|
||||
@patch('scouter.activities.activities.Redis.__init__')
|
||||
@patch('scouter.activities.activities.Gates.__init__')
|
||||
@patch('scouter.activities.activities.API.__init__')
|
||||
@patch('scouter.activities.activities.MetricsController')
|
||||
def test___init__(
|
||||
mock_metrics_controller, mock_gates_init, mock_redis_init, mock_postgres_init, mock_mongodb_init
|
||||
mock_metrics_controller,
|
||||
mock_api_init,
|
||||
mock_gates_init,
|
||||
mock_redis_init,
|
||||
mock_postgres_init,
|
||||
mock_mongodb_init,
|
||||
):
|
||||
postgres_config = {
|
||||
'host': 'localhost',
|
||||
@@ -33,6 +40,12 @@ def test___init__(
|
||||
'database_name': 'test_database',
|
||||
}
|
||||
|
||||
api_config = {
|
||||
'base_url': 'https://api.example.com',
|
||||
'auth_type': 'bearer',
|
||||
'auth_token': 'test_token',
|
||||
}
|
||||
|
||||
logger = MagicMock()
|
||||
notification_handler = MagicMock()
|
||||
|
||||
@@ -40,6 +53,7 @@ def test___init__(
|
||||
postgres_config=postgres_config,
|
||||
redis_config=redis_config,
|
||||
mongodb_config=mongodb_config,
|
||||
api_config=api_config,
|
||||
logger=logger,
|
||||
notification_handler=notification_handler,
|
||||
)
|
||||
@@ -49,6 +63,7 @@ def test___init__(
|
||||
assert isinstance(activities, Redis)
|
||||
assert isinstance(activities, MongoDB)
|
||||
assert isinstance(activities, Gates)
|
||||
assert isinstance(activities, API)
|
||||
|
||||
mock_postgres_init.assert_called_once_with(
|
||||
ANY,
|
||||
@@ -91,20 +106,34 @@ def test___init__(
|
||||
metrics_controller=mock_metrics_controller.return_value,
|
||||
)
|
||||
|
||||
mock_api_init.assert_called_once_with(
|
||||
ANY,
|
||||
base_url=api_config['base_url'],
|
||||
auth_type=api_config['auth_type'],
|
||||
auth_token=api_config['auth_token'],
|
||||
logger=logger,
|
||||
notification_handler=notification_handler,
|
||||
metrics_controller=mock_metrics_controller.return_value,
|
||||
)
|
||||
|
||||
|
||||
@patch('scouter.activities.activities.Postgres.__init__')
|
||||
@patch('scouter.activities.activities.Redis.__init__')
|
||||
@patch('scouter.activities.activities.Gates.__init__')
|
||||
@patch('scouter.activities.activities.MongoDB.__init__')
|
||||
@patch('scouter.activities.activities.API.__init__')
|
||||
@patch('scouter.activities.activities.Postgres.close')
|
||||
@patch('scouter.activities.activities.MongoDB.close')
|
||||
@patch('scouter.activities.activities.Redis.close')
|
||||
@patch('scouter.activities.activities.Gates.close')
|
||||
@patch('scouter.activities.activities.API.close')
|
||||
def test_shutdown(
|
||||
mock_api_close,
|
||||
mock_gates_close,
|
||||
mock_redis_close,
|
||||
mock_mongodb_close,
|
||||
mock_postgres_close,
|
||||
_mock_api_init,
|
||||
_mock_mongodb_init,
|
||||
_mock_gates_init,
|
||||
_mock_redis_init,
|
||||
@@ -127,6 +156,12 @@ def test_shutdown(
|
||||
'database_name': 'test_database',
|
||||
}
|
||||
|
||||
api_config = {
|
||||
'base_url': 'https://api.example.com',
|
||||
'auth_type': 'bearer',
|
||||
'auth_token': 'test_token',
|
||||
}
|
||||
|
||||
logger = MagicMock()
|
||||
notification_handler = MagicMock()
|
||||
|
||||
@@ -134,6 +169,7 @@ def test_shutdown(
|
||||
postgres_config=postgres_config,
|
||||
redis_config=redis_config,
|
||||
mongodb_config=mongodb_config,
|
||||
api_config=api_config,
|
||||
logger=logger,
|
||||
notification_handler=notification_handler,
|
||||
)
|
||||
@@ -144,3 +180,4 @@ def test_shutdown(
|
||||
mock_mongodb_close.assert_called()
|
||||
mock_redis_close.assert_called()
|
||||
mock_gates_close.assert_called()
|
||||
mock_api_close.assert_called()
|
||||
|
||||
322
tests/activities/test_api.py
Normal file
322
tests/activities/test_api.py
Normal file
@@ -0,0 +1,322 @@
|
||||
from unittest.mock import ANY, AsyncMock, MagicMock, patch
|
||||
|
||||
import pandas as pd
|
||||
import pytest
|
||||
from sientia_do.notifications.models import NotificationLevel
|
||||
|
||||
from scouter.activities.api import API
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
@patch('scouter.activities.api.PIWebAPIClient')
|
||||
def api_activity(mock_pi_web_api_client):
|
||||
"""Fixture to create an API activity instance with mocked dependencies."""
|
||||
logger = MagicMock()
|
||||
notification_handler = MagicMock()
|
||||
metrics_controller = MagicMock()
|
||||
|
||||
activity = API(
|
||||
base_url='https://pi.example.com',
|
||||
auth_type='basic',
|
||||
auth_token='test_token',
|
||||
logger=logger,
|
||||
notification_handler=notification_handler,
|
||||
metrics_controller=metrics_controller,
|
||||
)
|
||||
|
||||
activity.logger = logger
|
||||
activity.notification_handler = notification_handler
|
||||
activity.metrics_controller = metrics_controller
|
||||
activity.pod_id = 'test_pod_id'
|
||||
|
||||
return activity
|
||||
|
||||
|
||||
metadata = {
|
||||
'metadata': {
|
||||
'model_id': 'test_model_id',
|
||||
'model_name': 'test_model',
|
||||
'schedule_name': 'test_schedule',
|
||||
'workflow_name': 'pi_web_api_scouter',
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@patch('scouter.activities.api.PIWebAPIClient')
|
||||
def test_api_initialization(mock_pi_web_api_client):
|
||||
"""Test API activity initialization."""
|
||||
logger = MagicMock()
|
||||
notification_handler = MagicMock()
|
||||
metrics_controller = MagicMock()
|
||||
|
||||
activity = API(
|
||||
base_url='https://pi.example.com',
|
||||
auth_type='basic',
|
||||
auth_token='test_token',
|
||||
logger=logger,
|
||||
notification_handler=notification_handler,
|
||||
metrics_controller=metrics_controller,
|
||||
)
|
||||
|
||||
mock_pi_web_api_client.assert_called_once_with(
|
||||
base_url='https://pi.example.com',
|
||||
auth_config={
|
||||
'type': 'basic',
|
||||
'token': 'test_token',
|
||||
},
|
||||
logger=logger,
|
||||
notification_handler=notification_handler,
|
||||
metrics_controller=metrics_controller,
|
||||
)
|
||||
|
||||
assert activity.pi_web_api_client is not None
|
||||
|
||||
|
||||
@patch('scouter.activities.api.SientiaMonitoring')
|
||||
def test_close(mock_sientia_monitoring, api_activity):
|
||||
"""Test close method."""
|
||||
api_activity.close()
|
||||
api_activity.pi_web_api_client.close.assert_called_once()
|
||||
mock_sientia_monitoring.shutdown.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_tag_values_success(api_activity):
|
||||
"""Test get_tag_values with successful data retrieval."""
|
||||
# Setup test data
|
||||
test_data = {
|
||||
**metadata,
|
||||
'endpoint': '/streamsets/recorded',
|
||||
'web_ids': {
|
||||
'tag1': {
|
||||
'webid': 'webid1',
|
||||
'aggr_function': 'avg',
|
||||
'data_range': [0, 100],
|
||||
},
|
||||
'tag2': {
|
||||
'webid': 'webid2',
|
||||
'aggr_function': 'avg',
|
||||
'data_range': [0, 100],
|
||||
},
|
||||
'tag3': {
|
||||
'webid': 'webid3',
|
||||
'aggr_function': 'avg',
|
||||
'data_range': [0, 100],
|
||||
},
|
||||
},
|
||||
'period': '*-1d',
|
||||
'max_count': 10,
|
||||
'api_timeout': 30,
|
||||
}
|
||||
|
||||
# Mock DataFrame response
|
||||
mock_df = pd.DataFrame(
|
||||
{
|
||||
'timestamp': ['2023-01-01 12:00:00', '2023-01-01 12:01:00', '2023-01-01 12:02:00'],
|
||||
'name': ['tag1', 'tag2', 'tag3'],
|
||||
'value': [10.5, 20.3, 30.7],
|
||||
'tag': ['webid1', 'webid2', 'webid3'],
|
||||
}
|
||||
)
|
||||
|
||||
api_activity.pi_web_api_client.get_latest_values_df = AsyncMock(return_value=mock_df)
|
||||
|
||||
# Execute
|
||||
result = await api_activity.get_tag_values(test_data)
|
||||
|
||||
# Verify
|
||||
api_activity.pi_web_api_client.get_latest_values_df.assert_called_once_with(
|
||||
endpoint='/streamsets/recorded',
|
||||
web_ids={
|
||||
'tag1': {'webid': 'webid1', 'aggr_function': 'avg', 'data_range': [0, 100]},
|
||||
'tag2': {'webid': 'webid2', 'aggr_function': 'avg', 'data_range': [0, 100]},
|
||||
'tag3': {'webid': 'webid3', 'aggr_function': 'avg', 'data_range': [0, 100]},
|
||||
},
|
||||
start_time='*-1d',
|
||||
max_count=10,
|
||||
metadata=metadata['metadata'],
|
||||
timeout=30,
|
||||
)
|
||||
|
||||
assert len(result) == 3
|
||||
assert result[0]['name'] == 'tag1'
|
||||
assert result[0]['value'] == 10.5
|
||||
assert result[1]['name'] == 'tag2'
|
||||
assert result[2]['name'] == 'tag3'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_tag_values_with_default_max_count(api_activity):
|
||||
"""Test get_tag_values with default max_count value."""
|
||||
# Setup test data without max_count
|
||||
test_data = {
|
||||
**metadata,
|
||||
'endpoint': '/streamsets/recorded',
|
||||
'web_ids': {
|
||||
'tag1': {
|
||||
'webid': 'webid1',
|
||||
'aggr_function': 'avg',
|
||||
'data_range': [0, 100],
|
||||
}
|
||||
},
|
||||
'period': '*-1h',
|
||||
'api_timeout': 15,
|
||||
}
|
||||
|
||||
mock_df = pd.DataFrame(
|
||||
{
|
||||
'timestamp': ['2023-01-01 12:00:00'],
|
||||
'name': ['tag1'],
|
||||
'value': [42.0],
|
||||
'tag': ['webid1'],
|
||||
}
|
||||
)
|
||||
|
||||
api_activity.pi_web_api_client.get_latest_values_df = AsyncMock(return_value=mock_df)
|
||||
|
||||
# Execute
|
||||
result = await api_activity.get_tag_values(test_data)
|
||||
|
||||
# Verify default max_count is 1
|
||||
api_activity.pi_web_api_client.get_latest_values_df.assert_called_once_with(
|
||||
endpoint='/streamsets/recorded',
|
||||
web_ids={'tag1': {'webid': 'webid1', 'aggr_function': 'avg', 'data_range': [0, 100]}},
|
||||
start_time='*-1h',
|
||||
max_count=1,
|
||||
metadata=metadata['metadata'],
|
||||
timeout=15,
|
||||
)
|
||||
|
||||
assert len(result) == 1
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_tag_values_with_none_webids(api_activity):
|
||||
"""Test get_tag_values with some None WebIds."""
|
||||
# Setup test data with None values
|
||||
test_data = {
|
||||
**metadata,
|
||||
'endpoint': '/streamsets/recorded',
|
||||
'web_ids': {
|
||||
'tag1': {
|
||||
'webid': 'webid1',
|
||||
'aggr_function': 'avg',
|
||||
'data_range': [0, 100],
|
||||
},
|
||||
'tag2': None,
|
||||
'tag3': {
|
||||
'webid': 'webid3',
|
||||
'aggr_function': 'max',
|
||||
'data_range': [0, 200],
|
||||
},
|
||||
},
|
||||
'period': '*-1h',
|
||||
'max_count': 5,
|
||||
'api_timeout': 20,
|
||||
}
|
||||
|
||||
mock_df = pd.DataFrame(
|
||||
{
|
||||
'timestamp': ['2023-01-01 12:00:00', '2023-01-01 12:01:00'],
|
||||
'name': ['tag1', 'tag3'],
|
||||
'value': [10.5, 30.7],
|
||||
'tag': ['webid1', 'webid3'],
|
||||
}
|
||||
)
|
||||
|
||||
api_activity.pi_web_api_client.get_latest_values_df = AsyncMock(return_value=mock_df)
|
||||
|
||||
# Execute
|
||||
result = await api_activity.get_tag_values(test_data)
|
||||
|
||||
# Verify - should only query non-None WebIds
|
||||
assert len(result) == 2
|
||||
assert all(r['name'] in ['tag1', 'tag3'] for r in result)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_tag_values_api_error(api_activity):
|
||||
"""Test get_tag_values when PI Web API client raises an error and sends notification."""
|
||||
# Setup test data
|
||||
test_data = {
|
||||
**metadata,
|
||||
'endpoint': '/streamsets/recorded',
|
||||
'web_ids': {
|
||||
'tag1': {
|
||||
'webid': 'webid1',
|
||||
'aggr_function': 'avg',
|
||||
'data_range': [0, 100],
|
||||
}
|
||||
},
|
||||
'period': '*-1d',
|
||||
'max_count': 1,
|
||||
'api_timeout': 30,
|
||||
}
|
||||
|
||||
# Mock API error
|
||||
api_activity.pi_web_api_client.get_latest_values_df = AsyncMock(
|
||||
side_effect=Exception('PI Web API connection error')
|
||||
)
|
||||
api_activity.send_notification_async = AsyncMock()
|
||||
|
||||
# Execute and verify exception is raised
|
||||
with pytest.raises(Exception) as exc_info:
|
||||
await api_activity.get_tag_values(test_data)
|
||||
|
||||
assert str(exc_info.value) == 'PI Web API connection error'
|
||||
|
||||
# Verify notification was sent
|
||||
api_activity.send_notification_async.assert_called_once_with(
|
||||
metadata=metadata['metadata'],
|
||||
notification_id='PI_WEB_API_REQUEST_ERROR',
|
||||
message='Error getting tag values from PI Web API: PI Web API connection error',
|
||||
block='get_tag_values',
|
||||
level=NotificationLevel.ERROR,
|
||||
attachment_content=ANY,
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_get_tag_values_with_nan_values(api_activity):
|
||||
"""Test get_tag_values handling NaN values in the DataFrame."""
|
||||
# Setup test data
|
||||
test_data = {
|
||||
**metadata,
|
||||
'endpoint': '/streamsets/recorded',
|
||||
'web_ids': {
|
||||
'tag1': {
|
||||
'webid': 'webid1',
|
||||
'aggr_function': 'avg',
|
||||
'data_range': [0, 100],
|
||||
},
|
||||
'tag2': {
|
||||
'webid': 'webid2',
|
||||
'aggr_function': 'avg',
|
||||
'data_range': [0, 100],
|
||||
},
|
||||
},
|
||||
'period': '*-1d',
|
||||
'max_count': 1,
|
||||
'api_timeout': 30,
|
||||
}
|
||||
|
||||
# Mock DataFrame with NaN values
|
||||
mock_df = pd.DataFrame(
|
||||
{
|
||||
'timestamp': ['2023-01-01 12:00:00', '2023-01-01 12:00:00'],
|
||||
'name': ['tag1', 'tag2'],
|
||||
'value': [10.0, float('nan')],
|
||||
'tag': ['webid1', 'webid2'],
|
||||
}
|
||||
)
|
||||
|
||||
api_activity.pi_web_api_client.get_latest_values_df = AsyncMock(return_value=mock_df)
|
||||
|
||||
# Execute
|
||||
result = await api_activity.get_tag_values(test_data)
|
||||
|
||||
# Verify
|
||||
assert len(result) == 2
|
||||
assert result[0]['value'] == 10.0
|
||||
# NaN should be preserved in the result
|
||||
assert pd.isna(result[1]['value'])
|
||||
0
tests/utils/clients/__init__.py
Normal file
0
tests/utils/clients/__init__.py
Normal file
560
tests/utils/clients/test_pi_web_api_client.py
Normal file
560
tests/utils/clients/test_pi_web_api_client.py
Normal file
@@ -0,0 +1,560 @@
|
||||
import json
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import pandas as pd
|
||||
import pycurl
|
||||
import pytest
|
||||
|
||||
from scouter.utils.clients.pi_web_api_client import PIMSRequestError, PIWebAPIClient
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_logger():
|
||||
return MagicMock()
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_notification_handler():
|
||||
return AsyncMock()
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_metrics_controller():
|
||||
return AsyncMock()
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def auth_config_basic():
|
||||
return {'type': 'basic', 'token': 'test_token_123'}
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def auth_config_bearer():
|
||||
return {'type': 'bearer', 'token': 'bearer_token_456'}
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def pi_client(mock_logger, mock_notification_handler, mock_metrics_controller, auth_config_basic):
|
||||
return PIWebAPIClient(
|
||||
base_url='https://pi.example.com',
|
||||
auth_config=auth_config_basic,
|
||||
logger=mock_logger,
|
||||
notification_handler=mock_notification_handler,
|
||||
metrics_controller=mock_metrics_controller,
|
||||
)
|
||||
|
||||
|
||||
def test_init_with_basic_auth(
|
||||
mock_logger, mock_notification_handler, mock_metrics_controller, auth_config_basic
|
||||
):
|
||||
"""Test initialization with basic authentication"""
|
||||
client = PIWebAPIClient(
|
||||
base_url='https://pi.example.com/',
|
||||
auth_config=auth_config_basic,
|
||||
logger=mock_logger,
|
||||
notification_handler=mock_notification_handler,
|
||||
metrics_controller=mock_metrics_controller,
|
||||
)
|
||||
|
||||
assert client.base_url == 'https://pi.example.com'
|
||||
assert client.auth_config['type'] == 'basic'
|
||||
assert client.headers['Authorization'] == 'Basic test_token_123'
|
||||
assert client.headers['Content-Type'] == 'application/json'
|
||||
assert client.headers['Accept'] == 'application/json'
|
||||
mock_logger.info.assert_called_with('Authenticating with basic authentication')
|
||||
|
||||
|
||||
def test_init_with_bearer_auth(
|
||||
mock_logger, mock_notification_handler, mock_metrics_controller, auth_config_bearer
|
||||
):
|
||||
"""Test initialization with bearer authentication"""
|
||||
client = PIWebAPIClient(
|
||||
base_url='https://pi.example.com',
|
||||
auth_config=auth_config_bearer,
|
||||
logger=mock_logger,
|
||||
notification_handler=mock_notification_handler,
|
||||
metrics_controller=mock_metrics_controller,
|
||||
)
|
||||
|
||||
assert client.base_url == 'https://pi.example.com'
|
||||
assert client.auth_config['type'] == 'bearer'
|
||||
assert client.headers['Authorization'] == 'Bearer bearer_token_456'
|
||||
mock_logger.info.assert_called_with('Authenticating with bearer authentication')
|
||||
|
||||
|
||||
def test_init_with_custom_headers(
|
||||
mock_logger, mock_notification_handler, mock_metrics_controller, auth_config_basic
|
||||
):
|
||||
"""Test initialization with custom headers"""
|
||||
custom_headers = {
|
||||
'Content-Type': 'application/xml',
|
||||
'Custom-Header': 'custom_value',
|
||||
}
|
||||
|
||||
client = PIWebAPIClient(
|
||||
base_url='https://pi.example.com',
|
||||
auth_config=auth_config_basic,
|
||||
logger=mock_logger,
|
||||
notification_handler=mock_notification_handler,
|
||||
metrics_controller=mock_metrics_controller,
|
||||
headers_config=custom_headers,
|
||||
)
|
||||
|
||||
assert client.headers['Content-Type'] == 'application/xml'
|
||||
assert client.headers['Custom-Header'] == 'custom_value'
|
||||
assert client.headers['Authorization'] == 'Basic test_token_123'
|
||||
|
||||
|
||||
def test_authenticate_invalid_type(mock_logger, mock_notification_handler, mock_metrics_controller):
|
||||
"""Test that invalid authentication type raises ValueError"""
|
||||
invalid_auth_config = {'type': 'invalid', 'token': 'test_token'}
|
||||
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
PIWebAPIClient(
|
||||
base_url='https://pi.example.com',
|
||||
auth_config=invalid_auth_config,
|
||||
logger=mock_logger,
|
||||
notification_handler=mock_notification_handler,
|
||||
metrics_controller=mock_metrics_controller,
|
||||
)
|
||||
|
||||
assert 'Invalid authentication type: invalid' in str(exc_info.value)
|
||||
|
||||
|
||||
@patch('scouter.utils.clients.pi_web_api_client.SientiaMonitoring.shutdown')
|
||||
def test_close(mock_shutdown, pi_client):
|
||||
"""Test close method calls shutdown"""
|
||||
pi_client.close()
|
||||
|
||||
mock_shutdown.assert_called_once()
|
||||
|
||||
|
||||
def test_to_clean_timestamp(pi_client):
|
||||
"""Test timestamp cleaning and normalization"""
|
||||
timestamps = pd.Series(
|
||||
[
|
||||
'2025-01-15T10:30:45.123456Z',
|
||||
'2025-01-15T10:30:46.789012Z',
|
||||
'2025-01-15T10:30:47.999999Z',
|
||||
]
|
||||
)
|
||||
|
||||
result = pi_client._to_clean_timestamp(timestamps)
|
||||
|
||||
assert isinstance(result, pd.Series)
|
||||
assert result.dtype == 'datetime64[ns, UTC]'
|
||||
# Verify microseconds are floored to seconds
|
||||
assert result[0] == pd.Timestamp('2025-01-15T10:30:45Z')
|
||||
assert result[1] == pd.Timestamp('2025-01-15T10:30:46Z')
|
||||
assert result[2] == pd.Timestamp('2025-01-15T10:30:47Z')
|
||||
|
||||
|
||||
def test_to_clean_timestamp_with_invalid_values(pi_client):
|
||||
"""Test timestamp cleaning with invalid values returns NaT"""
|
||||
timestamps = pd.Series(['invalid', 'not_a_date', '2025-01-15T10:30:45Z'])
|
||||
|
||||
result = pi_client._to_clean_timestamp(timestamps)
|
||||
|
||||
assert pd.isna(result[0])
|
||||
assert pd.isna(result[1])
|
||||
assert result[2] == pd.Timestamp('2025-01-15T10:30:45Z')
|
||||
|
||||
|
||||
def test_extract_numeric_with_float(pi_client):
|
||||
"""Test extracting numeric value from float"""
|
||||
result = pi_client._extract_numeric(42.5)
|
||||
|
||||
assert result == 42.5
|
||||
|
||||
|
||||
def test_extract_numeric_with_int(pi_client):
|
||||
"""Test extracting numeric value from int"""
|
||||
result = pi_client._extract_numeric(42)
|
||||
|
||||
assert result == 42.0
|
||||
|
||||
|
||||
def test_extract_numeric_with_string(pi_client):
|
||||
"""Test extracting numeric value from string"""
|
||||
result = pi_client._extract_numeric('123.45')
|
||||
|
||||
assert result == 123.45
|
||||
|
||||
|
||||
def test_extract_numeric_with_dict(pi_client):
|
||||
"""Test extracting numeric value from dictionary"""
|
||||
result = pi_client._extract_numeric({'Value': 99.9})
|
||||
|
||||
assert result == 99.9
|
||||
|
||||
|
||||
def test_extract_numeric_with_invalid_value(pi_client):
|
||||
"""Test extracting numeric value from invalid value returns None/NaN"""
|
||||
result = pi_client._extract_numeric('invalid_number')
|
||||
|
||||
assert pd.isna(result)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch('scouter.utils.clients.pi_web_api_client.pycurl.Curl')
|
||||
async def test_curl_get_json_success(mock_curl_class, pi_client):
|
||||
"""Test successful GET request with JSON response"""
|
||||
mock_curl = MagicMock()
|
||||
mock_curl_class.return_value = mock_curl
|
||||
|
||||
response_data = {'status': 'success', 'data': [1, 2, 3]}
|
||||
response_json = json.dumps(response_data).encode('utf-8')
|
||||
|
||||
def mock_perform():
|
||||
buffer = mock_curl.setopt.call_args_list[1][0][1]
|
||||
buffer.write(response_json)
|
||||
|
||||
mock_curl.perform.side_effect = mock_perform
|
||||
mock_curl.getinfo.return_value = 200
|
||||
|
||||
result = await pi_client._curl_get_json('https://pi.example.com/api/test')
|
||||
|
||||
assert result == response_data
|
||||
mock_curl.setopt.assert_any_call(pycurl.TIMEOUT, 30)
|
||||
mock_curl.perform.assert_called_once()
|
||||
mock_curl.close.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch('scouter.utils.clients.pi_web_api_client.pycurl.Curl')
|
||||
async def test_curl_get_json_with_params(mock_curl_class, pi_client):
|
||||
"""Test GET request with query parameters"""
|
||||
mock_curl = MagicMock()
|
||||
mock_curl_class.return_value = mock_curl
|
||||
|
||||
response_data = {'result': 'ok'}
|
||||
response_json = json.dumps(response_data).encode('utf-8')
|
||||
|
||||
def mock_perform():
|
||||
buffer = mock_curl.setopt.call_args_list[1][0][1]
|
||||
buffer.write(response_json)
|
||||
|
||||
mock_curl.perform.side_effect = mock_perform
|
||||
mock_curl.getinfo.return_value = 200
|
||||
|
||||
params = [('key1', 'value1'), ('key2', 'value2')]
|
||||
result = await pi_client._curl_get_json('https://pi.example.com/api', params=params)
|
||||
|
||||
assert result == response_data
|
||||
# Verify URL includes query parameters
|
||||
set_url_call = [call for call in mock_curl.setopt.call_args_list if call[0][0] == pycurl.URL][0]
|
||||
assert b'key1=value1' in set_url_call[0][1]
|
||||
assert b'key2=value2' in set_url_call[0][1]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch('scouter.utils.clients.pi_web_api_client.pycurl.Curl')
|
||||
async def test_curl_get_json_http_error(mock_curl_class, pi_client):
|
||||
"""Test GET request with HTTP error response"""
|
||||
mock_curl = MagicMock()
|
||||
mock_curl_class.return_value = mock_curl
|
||||
|
||||
error_response = b'{"error": "Not found"}'
|
||||
|
||||
def mock_perform():
|
||||
buffer = mock_curl.setopt.call_args_list[1][0][1]
|
||||
buffer.write(error_response)
|
||||
|
||||
mock_curl.perform.side_effect = mock_perform
|
||||
mock_curl.getinfo.return_value = 404
|
||||
|
||||
with pytest.raises(PIMSRequestError) as exc_info:
|
||||
await pi_client._curl_get_json('https://pi.example.com/api/notfound')
|
||||
|
||||
assert 'HTTP 404' in str(exc_info.value)
|
||||
mock_curl.close.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch('scouter.utils.clients.pi_web_api_client.pycurl.Curl')
|
||||
async def test_curl_get_json_connection_error(mock_curl_class, pi_client):
|
||||
"""Test GET request with connection error"""
|
||||
mock_curl = MagicMock()
|
||||
mock_curl_class.return_value = mock_curl
|
||||
|
||||
mock_curl.perform.side_effect = pycurl.error('Connection failed')
|
||||
|
||||
with pytest.raises(PIMSRequestError) as exc_info:
|
||||
await pi_client._curl_get_json('https://pi.example.com/api/test')
|
||||
|
||||
assert 'Connection error' in str(exc_info.value)
|
||||
mock_curl.close.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch('scouter.utils.clients.pi_web_api_client.pycurl.Curl')
|
||||
async def test_curl_get_json_invalid_json(mock_curl_class, pi_client):
|
||||
"""Test GET request with invalid JSON response"""
|
||||
mock_curl = MagicMock()
|
||||
mock_curl_class.return_value = mock_curl
|
||||
|
||||
invalid_json = b'This is not valid JSON'
|
||||
|
||||
def mock_perform():
|
||||
buffer = mock_curl.setopt.call_args_list[1][0][1]
|
||||
buffer.write(invalid_json)
|
||||
|
||||
mock_curl.perform.side_effect = mock_perform
|
||||
mock_curl.getinfo.return_value = 200
|
||||
|
||||
with pytest.raises(PIMSRequestError) as exc_info:
|
||||
await pi_client._curl_get_json('https://pi.example.com/api/test')
|
||||
|
||||
assert 'Error decoding JSON response' in str(exc_info.value)
|
||||
mock_curl.close.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch('scouter.utils.clients.pi_web_api_client.pycurl.Curl')
|
||||
async def test_curl_get_json_with_custom_timeout(mock_curl_class, pi_client):
|
||||
"""Test GET request with custom timeout"""
|
||||
mock_curl = MagicMock()
|
||||
mock_curl_class.return_value = mock_curl
|
||||
|
||||
response_data = {'status': 'ok'}
|
||||
response_json = json.dumps(response_data).encode('utf-8')
|
||||
|
||||
def mock_perform():
|
||||
buffer = mock_curl.setopt.call_args_list[1][0][1]
|
||||
buffer.write(response_json)
|
||||
|
||||
mock_curl.perform.side_effect = mock_perform
|
||||
mock_curl.getinfo.return_value = 200
|
||||
|
||||
await pi_client._curl_get_json('https://pi.example.com/api/test', timeout=60)
|
||||
|
||||
mock_curl.setopt.assert_any_call(pycurl.TIMEOUT, 60)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch('scouter.utils.clients.pi_web_api_client.pycurl.Curl')
|
||||
async def test_curl_get_json_without_ssl_verify(mock_curl_class, pi_client):
|
||||
"""Test GET request with SSL verification disabled"""
|
||||
mock_curl = MagicMock()
|
||||
mock_curl_class.return_value = mock_curl
|
||||
|
||||
response_data = {'status': 'ok'}
|
||||
response_json = json.dumps(response_data).encode('utf-8')
|
||||
|
||||
def mock_perform():
|
||||
buffer = mock_curl.setopt.call_args_list[1][0][1]
|
||||
buffer.write(response_json)
|
||||
|
||||
mock_curl.perform.side_effect = mock_perform
|
||||
mock_curl.getinfo.return_value = 200
|
||||
|
||||
await pi_client._curl_get_json('https://pi.example.com/api/test', verify=False)
|
||||
|
||||
mock_curl.setopt.assert_any_call(pycurl.SSL_VERIFYPEER, 0)
|
||||
mock_curl.setopt.assert_any_call(pycurl.SSL_VERIFYHOST, 0)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch.object(PIWebAPIClient, '_curl_get_json', new_callable=AsyncMock)
|
||||
async def test_get_latest_values_df_success(mock_curl_get_json, pi_client):
|
||||
"""Test successful retrieval of latest values"""
|
||||
mock_curl_get_json.return_value = {
|
||||
'Items': [
|
||||
{
|
||||
'Name': 'tag1',
|
||||
'Items': [
|
||||
{'Timestamp': '2025-01-15T10:30:00Z', 'Value': 42.5},
|
||||
{'Timestamp': '2025-01-15T10:31:00Z', 'Value': 43.0},
|
||||
],
|
||||
},
|
||||
{
|
||||
'Name': 'tag2',
|
||||
'Items': [
|
||||
{'Timestamp': '2025-01-15T10:30:00Z', 'Value': 100.0},
|
||||
],
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
web_ids = {
|
||||
'tag1': {'webid': 'webid1'},
|
||||
'tag2': {'webid': 'webid2'},
|
||||
}
|
||||
|
||||
result = await pi_client.get_latest_values_df(
|
||||
web_ids=web_ids,
|
||||
endpoint='/streamsets/recorded',
|
||||
start_time='*-1d',
|
||||
end_time='*',
|
||||
max_count=10,
|
||||
)
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 3
|
||||
assert list(result.columns) == ['timestamp', 'name', 'value', 'tag']
|
||||
assert result['name'].tolist() == ['tag1', 'tag1', 'tag2']
|
||||
assert result['value'].tolist() == [42.5, 43.0, 100.0]
|
||||
|
||||
mock_curl_get_json.assert_called_once()
|
||||
call_args = mock_curl_get_json.call_args
|
||||
assert call_args[1]['url'] == 'https://pi.example.com/streamsets/recorded'
|
||||
assert call_args[1]['timeout'] == 30
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch.object(PIWebAPIClient, '_curl_get_json', new_callable=AsyncMock)
|
||||
async def test_get_latest_values_df_with_custom_params(mock_curl_get_json, pi_client):
|
||||
"""Test get_latest_values_df with custom parameters"""
|
||||
mock_curl_get_json.return_value = {
|
||||
'Items': [
|
||||
{
|
||||
'Name': 'tag1',
|
||||
'Items': [
|
||||
{'Timestamp': '2025-01-15T10:30:00Z', 'Value': 42.5},
|
||||
],
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
web_ids = {'tag1': {'webid': 'webid1'}}
|
||||
metadata = {'model_id': 'test_model'}
|
||||
|
||||
result = await pi_client.get_latest_values_df(
|
||||
web_ids=web_ids,
|
||||
endpoint='/streamsets/recorded',
|
||||
start_time='*-7d',
|
||||
end_time='*-1d',
|
||||
max_count=100,
|
||||
timeout=60,
|
||||
metadata=metadata,
|
||||
)
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 1
|
||||
|
||||
mock_curl_get_json.assert_called_once()
|
||||
call_args = mock_curl_get_json.call_args
|
||||
params = call_args[1]['params']
|
||||
|
||||
# Verify parameters
|
||||
assert ('startTime', '*-7d') in params
|
||||
assert ('endtime', '*-1d') in params
|
||||
assert ('maxCount', '100') in params
|
||||
assert call_args[1]['timeout'] == 60
|
||||
assert call_args[1]['metadata'] == metadata
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch.object(PIWebAPIClient, '_curl_get_json', new_callable=AsyncMock)
|
||||
async def test_get_latest_values_df_empty_response(mock_curl_get_json, pi_client):
|
||||
"""Test get_latest_values_df with empty response"""
|
||||
mock_curl_get_json.return_value = {'Items': []}
|
||||
|
||||
web_ids = {'tag1': {'webid': 'webid1'}}
|
||||
|
||||
result = await pi_client.get_latest_values_df(
|
||||
web_ids=web_ids,
|
||||
endpoint='/streamsets/recorded',
|
||||
)
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 0
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch.object(PIWebAPIClient, '_curl_get_json', new_callable=AsyncMock)
|
||||
async def test_get_latest_values_df_no_items_in_tag(mock_curl_get_json, pi_client):
|
||||
"""Test get_latest_values_df when tag has no items"""
|
||||
mock_curl_get_json.return_value = {
|
||||
'Items': [
|
||||
{
|
||||
'Name': 'tag1',
|
||||
'Items': [],
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
web_ids = {'tag1': {'webid': 'webid1'}}
|
||||
|
||||
result = await pi_client.get_latest_values_df(
|
||||
web_ids=web_ids,
|
||||
endpoint='/streamsets/recorded',
|
||||
)
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 0
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch.object(PIWebAPIClient, '_curl_get_json', new_callable=AsyncMock)
|
||||
async def test_get_latest_values_df_with_missing_timestamp(mock_curl_get_json, pi_client):
|
||||
"""Test get_latest_values_df filters out items with missing timestamp"""
|
||||
mock_curl_get_json.return_value = {
|
||||
'Items': [
|
||||
{
|
||||
'Name': 'tag1',
|
||||
'Items': [
|
||||
{'Timestamp': '2025-01-15T10:30:00Z', 'Value': 42.5},
|
||||
{'Value': 43.0}, # Missing Timestamp
|
||||
{'Timestamp': None, 'Value': 44.0}, # None Timestamp
|
||||
],
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
web_ids = {'tag1': {'webid': 'webid1'}}
|
||||
|
||||
result = await pi_client.get_latest_values_df(
|
||||
web_ids=web_ids,
|
||||
endpoint='/streamsets/recorded',
|
||||
)
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 1 # Only the first item should be included
|
||||
assert result['value'].tolist() == [42.5]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch.object(PIWebAPIClient, '_curl_get_json', new_callable=AsyncMock)
|
||||
async def test_get_latest_values_df_with_nested_value(mock_curl_get_json, pi_client):
|
||||
"""Test get_latest_values_df with nested value extraction"""
|
||||
mock_curl_get_json.return_value = {
|
||||
'Items': [
|
||||
{
|
||||
'Name': 'tag1',
|
||||
'Items': [
|
||||
{'Timestamp': '2025-01-15T10:30:00Z', 'Value': {'Value': 42.5}},
|
||||
],
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
web_ids = {'tag1': {'webid': 'webid1'}}
|
||||
|
||||
result = await pi_client.get_latest_values_df(
|
||||
web_ids=web_ids,
|
||||
endpoint='/streamsets/recorded',
|
||||
)
|
||||
|
||||
assert isinstance(result, pd.DataFrame)
|
||||
assert len(result) == 1
|
||||
assert result['value'].tolist() == [42.5]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch.object(PIWebAPIClient, '_curl_get_json', new_callable=AsyncMock)
|
||||
async def test_get_latest_values_df_default_max_count(mock_curl_get_json, pi_client):
|
||||
"""Test get_latest_values_df uses default max_count of 1"""
|
||||
mock_curl_get_json.return_value = {'Items': []}
|
||||
|
||||
web_ids = {'tag1': {'webid': 'webid1'}}
|
||||
|
||||
await pi_client.get_latest_values_df(
|
||||
web_ids=web_ids,
|
||||
endpoint='/streamsets/recorded',
|
||||
)
|
||||
|
||||
call_args = mock_curl_get_json.call_args
|
||||
params = call_args[1]['params']
|
||||
|
||||
assert ('maxCount', '1') in params
|
||||
@@ -4,6 +4,7 @@ from unittest.mock import patch
|
||||
import pytest
|
||||
|
||||
from scouter.utils.connectors_config import (
|
||||
build_api_config,
|
||||
build_druid_config,
|
||||
build_kafka_config,
|
||||
build_mongodb_config,
|
||||
@@ -154,6 +155,38 @@ def test_build_mongodb_config_with_env_vars():
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.usefixtures('mock_env_vars')
|
||||
def test_build_api_config_defaults():
|
||||
"""Test that build_api_config returns default values when no env vars are set"""
|
||||
config = build_api_config()
|
||||
|
||||
assert config == {
|
||||
'base_url': 'https://pi.example.com',
|
||||
'auth_type': 'basic',
|
||||
'auth_token': None,
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.usefixtures('mock_env_vars')
|
||||
def test_build_api_config_with_env_vars():
|
||||
"""Test that build_api_config uses env vars when set"""
|
||||
with patch.dict(
|
||||
os.environ,
|
||||
{
|
||||
'API_BASE_URL': 'https://api.production.com',
|
||||
'API_AUTH_TYPE': 'bearer',
|
||||
'API_AUTH_TOKEN': 'secret_token_123',
|
||||
},
|
||||
):
|
||||
config = build_api_config()
|
||||
|
||||
assert config == {
|
||||
'base_url': 'https://api.production.com',
|
||||
'auth_type': 'bearer',
|
||||
'auth_token': 'secret_token_123',
|
||||
}
|
||||
|
||||
|
||||
def test_build_druid_config_defaults():
|
||||
"""Test that build_druid_config returns default values when no env vars are set"""
|
||||
config = build_druid_config()
|
||||
|
||||
126
tests/workflow/test_pi_web_api_scouter.py
Normal file
126
tests/workflow/test_pi_web_api_scouter.py
Normal file
@@ -0,0 +1,126 @@
|
||||
from unittest.mock import ANY, AsyncMock, patch
|
||||
|
||||
from pytest import fixture, mark
|
||||
|
||||
from scouter.activities.activities import Activities
|
||||
from scouter.workflow.pi_web_api_scouter import PIWebAPIScouter
|
||||
|
||||
|
||||
@fixture
|
||||
def pi_web_api_scouter():
|
||||
return PIWebAPIScouter()
|
||||
|
||||
|
||||
@mark.asyncio
|
||||
@patch('scouter.workflow.pi_web_api_scouter.workflow', new_callable=AsyncMock)
|
||||
async def test_pi_web_api_scouter_workflow(mock_workflow, pi_web_api_scouter):
|
||||
mock_workflow.execute_local_activity_method.return_value = 'test_data'
|
||||
await pi_web_api_scouter.run(
|
||||
input_data={
|
||||
'model_name': 'test_model',
|
||||
'model_id': 'test_model_id',
|
||||
'schedule_name': 'test_schedule',
|
||||
'endpoint': '/streamsets/recorded',
|
||||
'model_tags': {'tag1': 'webid1', 'tag2': 'webid2'},
|
||||
'period': {'start_time': '2025-01-01T00:00:00Z'},
|
||||
'api_timeout': 30,
|
||||
'max_count': 10,
|
||||
'trigger_laborious': True,
|
||||
'filters': {'quality': 'good'},
|
||||
'schema': 'test_schema',
|
||||
'table_name': 'test_table',
|
||||
'retention_time': 3600,
|
||||
}
|
||||
)
|
||||
|
||||
expected_metadata = {
|
||||
'metadata': {
|
||||
'model_id': 'test_model_id',
|
||||
'model_name': 'test_model',
|
||||
'schedule_name': 'test_schedule',
|
||||
'workflow_name': 'scouter',
|
||||
}
|
||||
}
|
||||
|
||||
mock_workflow.execute_local_activity_method.assert_called_once_with(
|
||||
Activities.get_tag_values,
|
||||
{
|
||||
**expected_metadata,
|
||||
'endpoint': '/streamsets/recorded',
|
||||
'web_ids': {'tag1': 'webid1', 'tag2': 'webid2'},
|
||||
'period': {'start_time': '2025-01-01T00:00:00Z'},
|
||||
'api_timeout': 30,
|
||||
'max_count': 10,
|
||||
},
|
||||
start_to_close_timeout=ANY,
|
||||
retry_policy=ANY,
|
||||
)
|
||||
|
||||
mock_workflow.execute_child_workflow.assert_called_once_with(
|
||||
'subworkflow.core_scouter',
|
||||
{
|
||||
'model_name': 'test_model',
|
||||
'model_id': 'test_model_id',
|
||||
'schedule_name': 'test_schedule',
|
||||
'endpoint': '/streamsets/recorded',
|
||||
'model_tags': {'tag1': 'webid1', 'tag2': 'webid2'},
|
||||
'period': {'start_time': '2025-01-01T00:00:00Z'},
|
||||
'api_timeout': 30,
|
||||
'max_count': 10,
|
||||
'trigger_laborious': True,
|
||||
'filters': {'quality': 'good'},
|
||||
'schema': 'test_schema',
|
||||
'table_name': 'test_table',
|
||||
'retention_time': 3600,
|
||||
'workflow_name': 'scouter',
|
||||
'data': 'test_data',
|
||||
'metadata': expected_metadata,
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
@mark.asyncio
|
||||
@patch('scouter.workflow.pi_web_api_scouter.workflow', new_callable=AsyncMock)
|
||||
async def test_pi_web_api_scouter_workflow_empty(mock_workflow, pi_web_api_scouter):
|
||||
mock_workflow.execute_local_activity_method.return_value = []
|
||||
await pi_web_api_scouter.run(
|
||||
input_data={
|
||||
'model_name': 'test_model',
|
||||
'model_id': 'test_model_id',
|
||||
'schedule_name': 'test_schedule',
|
||||
'endpoint': '/streamsets/recorded',
|
||||
'model_tags': {'tag1': 'webid1', 'tag2': 'webid2'},
|
||||
'period': {'start_time': '2025-01-01T00:00:00Z'},
|
||||
'api_timeout': 30,
|
||||
'trigger_laborious': True,
|
||||
'filters': {'quality': 'good'},
|
||||
'schema': 'test_schema',
|
||||
'table_name': 'test_table',
|
||||
'retention_time': 3600,
|
||||
}
|
||||
)
|
||||
|
||||
expected_metadata = {
|
||||
'metadata': {
|
||||
'model_id': 'test_model_id',
|
||||
'model_name': 'test_model',
|
||||
'schedule_name': 'test_schedule',
|
||||
'workflow_name': 'scouter',
|
||||
}
|
||||
}
|
||||
|
||||
mock_workflow.execute_local_activity_method.assert_called_once_with(
|
||||
Activities.get_tag_values,
|
||||
{
|
||||
**expected_metadata,
|
||||
'endpoint': '/streamsets/recorded',
|
||||
'web_ids': {'tag1': 'webid1', 'tag2': 'webid2'},
|
||||
'period': {'start_time': '2025-01-01T00:00:00Z'},
|
||||
'api_timeout': 30,
|
||||
'max_count': 1,
|
||||
},
|
||||
start_to_close_timeout=ANY,
|
||||
retry_policy=ANY,
|
||||
)
|
||||
|
||||
mock_workflow.execute_child_workflow.assert_not_called()
|
||||
Reference in New Issue
Block a user