130 lines
5.0 KiB
Python
130 lines
5.0 KiB
Python
import json
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from logging import Logger
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from time import sleep
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from kafka import KafkaProducer
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from kafka.errors import NoBrokersAvailable
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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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import traceback
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import ingestor.metrics as metrics
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import os
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class DataManager:
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def __init__(
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self,
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kafka_servers: str,
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logger: Logger,
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notification_handler: NotificationHandler,
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) -> None:
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"""
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Initializes the DataManager instance with a Kafka producer.
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This constructor attempts to establish a connection to the specified Kafka servers
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and initializes a Kafka producer for sending messages. It retries the connection
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up to 3 times if the Kafka servers are unavailable.
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Args:
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kafka_servers (str): A comma-separated string of Kafka server addresses.
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logger (Logger): A logger instance for logging messages.
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Raises:
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NoBrokersAvailable: If the connection to Kafka servers fails after 3 attempts.
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"""
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self.pod_id = os.getenv("HOSTNAME", "localhost")
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self.kafka_producer = None
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for i in range(0, 3):
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logger.info(
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f"Trying ({i}) to initializing DataManager with Kafka servers: {kafka_servers}"
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)
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try:
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self.kafka_producer = KafkaProducer(
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bootstrap_servers=kafka_servers,
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value_serializer=lambda v: json.dumps(v).encode(
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"utf-8"
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), # Serialize JSON messages
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key_serializer=lambda k: str(k).encode("utf-8") if k else None,
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)
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# Kafka connected
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metrics.KAFKA_CONNECTION_STATUS.labels(pod_id=self.pod_id).set(1)
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break
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except NoBrokersAvailable:
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logger.error(
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f"Kafka servers {kafka_servers} are not available. Retrying..."
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)
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sleep(5)
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else:
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# Kafka not connected
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metrics.KAFKA_CONNECTION_STATUS.labels(pod_id=self.pod_id).set(0)
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logger.error(
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f"Failed to connect to Kafka servers {kafka_servers} after 3 attempts."
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)
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raise NoBrokersAvailable(
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f"Failed to connect to Kafka servers {kafka_servers} after 3 attempts."
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)
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logger.info(f"DataManager initialized with Kafka servers: {kafka_servers}")
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self.logger = logger
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self.notification_handler = notification_handler
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def shutdown(self):
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"""Closes the Kafka producer connection."""
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if self.kafka_producer:
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try:
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self.kafka_producer.flush(timeout=10)
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self.kafka_producer.close()
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# Mark as disconnected
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metrics.KAFKA_CONNECTION_STATUS.labels(pod_id=self.pod_id).set(0)
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except Exception as e:
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self.logger.error(f"Error closing Kafka producer: {e}")
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else:
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self.logger.warning("Kafka producer is already closed or not initialized.")
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def __del__(self):
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self.shutdown()
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def delivery_report(self, msg: str):
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"""Callback for delivery reports from Kafka."""
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self.logger.debug(
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f"Record successfully produced to {msg.topic} [{msg.partition}] at offset {msg.offset}"
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)
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def delivery_error(self, err: str):
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"""Callback for delivery reports from Kafka."""
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self.logger.error(f"Delivery failed for record : {err}")
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def publish(self, topic: str, data: dict) -> None:
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"""
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Publishes a message to a specified Kafka topic.
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Args:
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topic (str): The name of the Kafka topic to which the message will be published.
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data (dict): The message data to be sent to the Kafka topic.
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Returns:
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None
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Raises:
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Exception: If there is an error during message delivery, it will be handled by the `delivery_error` callback.
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"""
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try:
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self.logger.debug(f"Publishing message to topic {topic}: {data}")
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self.kafka_producer.send(topic=topic, value=data).add_callback(
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self.delivery_report
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).add_errback(self.delivery_error)
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self.kafka_producer.flush(timeout=10)
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metrics.KAFKA_MESSAGES_SENT.labels(pod_id=self.pod_id, topic=topic).inc()
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except Exception as e:
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metrics.KAFKA_MESSAGES_ERRORS.labels(pod_id=self.pod_id, topic=topic).inc()
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trace = traceback.format_exc()
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self.notification_handler.build_and_send_notification(
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notification_id=f"KAFKA_PRODUCER_ERROR_{topic}",
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message=f"Error publishing message to topic {topic}: {e}",
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block="kafka_producer",
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level=NotificationLevel.ERROR,
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attachment_content=trace,
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)
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self.logger.error(trace)
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