988ee65fbf
Implement initial structure for data ingestion with Kafka and OPC UA integration - Added DataManager for Kafka message handling - Introduced IngestorManager to manage data ingestion processes - Created OpcManager for OPC UA client interactions - Developed ResourceManager for Redis-based resource management - Established testing framework with unit tests for DataManager and OpcManager - Configured project settings for Python testing with pytest
69 lines
1.7 KiB
Python
69 lines
1.7 KiB
Python
from unittest.mock import MagicMock, patch
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from pytest import fixture
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from ingestor.managers.data_manager import DataManager
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@fixture
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@patch("ingestor.managers.data_manager.KafkaProducer")
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def data_manager(kafka):
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return DataManager(
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kafka_servers="localhost:9092",
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logger=MagicMock()
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)
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def test___del__(data_manager):
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flush_mock = MagicMock()
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close_mock = MagicMock()
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data_manager.kafka_producer.flush = flush_mock
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data_manager.kafka_producer.close = close_mock
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data_manager.__del__()
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flush_mock.assert_called_once()
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close_mock.assert_called_once()
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def test_delivery_report(data_manager):
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msg = MagicMock()
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msg.topic = "test_topic"
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msg.partition = 0
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msg.offset = 1
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data_manager.delivery_report(msg)
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data_manager.logger.info.assert_called_once_with(
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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 test_delivery_error(data_manager):
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err = "Test error"
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data_manager.delivery_error(err)
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data_manager.logger.error.assert_called_once_with(
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f"Delivery failed for record : {err}"
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)
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def test_publish(data_manager):
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topic = "test_topic"
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data = {"key": "value"}
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# Mock the send method of the Kafka producer
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send_mock = MagicMock()
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data_manager.kafka_producer.send = send_mock
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# Call the publish method
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data_manager.publish(topic, data)
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# Check if the send method was called with the correct arguments
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send_mock.assert_called_once_with(
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topic=topic, value=data
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)
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send_mock.return_value.add_callback.assert_called_once()
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data_manager.kafka_producer.flush.assert_called_once()
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