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#!/usr/bin/env python3
"""
Unit tests for the BatchProcessor class (_batch_processor.py)
This module tests the BatchProcessor class to ensure proper
message batching, topic grouping, and future management.
"""
from confluent_kafka.experimental.aio.producer._kafka_batch_executor import ProducerBatchExecutor as KafkaBatchExecutor
from confluent_kafka.experimental.aio.producer._AIOProducer import AIOProducer
from confluent_kafka.experimental.aio.producer._producer_batch_processor import (
ProducerBatchManager as ProducerBatchProcessor
)
import asyncio
import unittest
from unittest.mock import Mock, patch
import sys
import os
import concurrent.futures
import confluent_kafka
# Add src to path for imports
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
class TestProducerBatchProcessor(unittest.TestCase):
"""Test cases for ProducerBatchProcessor class"""
def setUp(self):
self.loop = asyncio.new_event_loop()
asyncio.set_event_loop(self.loop)
self.executor = concurrent.futures.ThreadPoolExecutor(max_workers=2)
self.producer_config = {
'bootstrap.servers': 'localhost:9092',
'client.id': 'test-producer',
'message.timeout.ms': 100,
'queue.buffering.max.messages': 1000,
'api.version.request': False,
}
self.confluent_kafka_producer = confluent_kafka.Producer(self.producer_config)
self.kafka_executor = KafkaBatchExecutor(self.confluent_kafka_producer, self.executor)
self.batch_processor = ProducerBatchProcessor(self.kafka_executor)
async def create_aio_producer():
return AIOProducer(self.producer_config, executor=self.executor)
self.aio_producer = self.loop.run_until_complete(create_aio_producer())
def tearDown(self):
try:
self.loop.run_until_complete(self.aio_producer.close())
except Exception:
pass
try:
self.confluent_kafka_producer.flush(timeout=1)
except Exception:
pass
try:
self.executor.shutdown(wait=True, timeout=1)
except Exception:
pass
self.loop.close()
def test_basic_functionality(self):
self.assertEqual(self.batch_processor.get_buffer_size(), 0)
self.assertTrue(self.batch_processor.is_buffer_empty())
future1 = Mock()
future2 = Mock()
msg_data1 = {'topic': 'topic1', 'value': 'test1', 'key': 'key1'}
msg_data2 = {'topic': 'topic2', 'value': 'test2', 'key': 'key2'}
self.batch_processor.add_message(msg_data1, future1)
self.batch_processor.add_message(msg_data2, future2)
self.assertEqual(self.batch_processor.get_buffer_size(), 2)
self.assertFalse(self.batch_processor.is_buffer_empty())
self.batch_processor.clear_buffer()
self.assertEqual(self.batch_processor.get_buffer_size(), 0)
self.assertTrue(self.batch_processor.is_buffer_empty())
def test_group_messages_by_topic(self):
future1 = Mock()
future2 = Mock()
future3 = Mock()
msg1 = {'topic': 'topic1', 'value': 'test1', 'user_callback': Mock()}
msg2 = {'topic': 'topic2', 'value': 'test2'}
msg3 = {'topic': 'topic1', 'value': 'test3', 'user_callback': Mock()}
self.batch_processor.add_message(msg1, future1)
self.batch_processor.add_message(msg2, future2)
self.batch_processor.add_message(msg3, future3)
topic_groups = self.batch_processor._group_messages_by_topic_and_partition()
self.assertEqual(len(topic_groups), 2)
self.assertIn(('topic1', -1), topic_groups)
topic1_group = topic_groups[('topic1', -1)]
self.assertEqual(len(topic1_group['messages']), 2)
self.assertEqual(len(topic1_group['futures']), 2)
self.assertEqual(topic1_group['futures'][0], future1)
self.assertEqual(topic1_group['futures'][1], future3)
self.assertIn(('topic2', -1), topic_groups)
topic2_group = topic_groups[('topic2', -1)]
self.assertEqual(len(topic2_group['messages']), 1)
self.assertEqual(len(topic2_group['futures']), 1)
self.assertEqual(topic2_group['futures'][0], future2)
def test_prepare_batch_messages(self):
messages = [
{'topic': 'test', 'value': 'test1', 'user_callback': Mock(), 'key': 'key1'},
{'topic': 'test', 'value': 'test2', 'partition': 1},
]
batch_messages = self.batch_processor._prepare_batch_messages(messages)
self.assertEqual(len(batch_messages), 2)
self.assertNotIn('topic', batch_messages[0])
self.assertIn('value', batch_messages[0])
self.assertIn('key', batch_messages[0])
self.assertNotIn('topic', batch_messages[1])
self.assertIn('value', batch_messages[1])
self.assertIn('partition', batch_messages[1])
def test_assign_future_callbacks(self):
batch_messages = [
{'value': 'test1'},
{'value': 'test2'},
]
futures = [Mock(), Mock()]
self.batch_processor._assign_future_callbacks(batch_messages, futures)
self.assertIn('callback', batch_messages[0])
self.assertIn('callback', batch_messages[1])
def test_handle_batch_failure(self):
"""Test handling batch failures"""
futures = [Mock(), Mock()]
futures[0].done.return_value = False
futures[1].done.return_value = True # Already done
exception = RuntimeError("Batch failed")
# Handle batch failure
self.batch_processor._handle_batch_failure(
exception, futures
)
# Verify first future got exception (not already done)
futures[0].set_exception.assert_called_once_with(exception)
# Verify second future was not modified (already done)
futures[1].set_exception.assert_not_called()
# Note: For real AIOProducer, the user callback is invoked directly by _handle_user_callback
def test_flush_empty_buffer(self):
"""Test flushing empty buffer is no-op"""
async def async_test():
await self.batch_processor.flush_buffer()
self.assertTrue(self.batch_processor.is_buffer_empty())
self.loop.run_until_complete(async_test())
def test_flush_buffer_with_messages(self):
"""Test successful buffer flush with messages"""
async def async_test():
future1 = self.loop.create_future()
future2 = self.loop.create_future()
msg1 = {'topic': 'topic1', 'value': 'test1'}
msg2 = {'topic': 'topic1', 'value': 'test2'}
self.batch_processor.add_message(msg1, future1)
self.batch_processor.add_message(msg2, future2)
success_future = self.loop.create_future()
success_future.set_result("success")
with patch.object(self.loop, 'run_in_executor', return_value=success_future):
await self.batch_processor.flush_buffer()
self.assertTrue(self.batch_processor.is_buffer_empty())
self.loop.run_until_complete(async_test())
def test_flush_buffer_selective_topic(self):
"""Test selective topic flushing"""
async def async_test():
future3 = self.loop.create_future()
future4 = self.loop.create_future()
msg3 = {'topic': 'topic1', 'value': 'test3'}
msg4 = {'topic': 'topic2', 'value': 'test4'}
self.batch_processor.add_message(msg3, future3)
self.batch_processor.add_message(msg4, future4)
success_future = self.loop.create_future()
success_future.set_result("success")
with patch.object(self.loop, 'run_in_executor', return_value=success_future):
await self.batch_processor.flush_buffer(target_topic='topic1')
self.assertEqual(self.batch_processor.get_buffer_size(), 1)
self.loop.run_until_complete(async_test())
def test_flush_buffer_exception_handling(self):
"""Test exception handling during buffer flush"""
async def async_test():
future = self.loop.create_future()
msg = {'topic': 'topic1', 'value': 'test'}
self.batch_processor.add_message(msg, future)
exception = RuntimeError("Batch execution failed")
with patch.object(self.loop, 'run_in_executor', side_effect=exception):
with self.assertRaises(RuntimeError):
await self.batch_processor.flush_buffer()
# Buffer should NOT be empty on exception - we want to retry
self.assertFalse(self.batch_processor.is_buffer_empty())
self.assertEqual(self.batch_processor.get_buffer_size(), 1)
self.loop.run_until_complete(async_test())
def test_kafka_executor_integration(self):
"""Test executing a batch operation via KafkaBatchExecutor"""
async def async_test():
batch_messages = [
{'value': 'test1', 'callback': Mock()},
{'value': 'test2', 'callback': Mock()},
]
# Mock the executor to return a completed future
future_result = self.loop.create_future()
future_result.set_result("poll_result")
with patch.object(self.loop, 'run_in_executor', return_value=future_result) as mock_run_in_executor:
result = await self.kafka_executor.execute_batch('test-topic', batch_messages)
# Verify run_in_executor was called
mock_run_in_executor.assert_called_once()
self.assertEqual(result, "poll_result")
self.loop.run_until_complete(async_test())
def _create_mixed_topic_messages(self):
"""Helper to create messages across multiple topics"""
messages_data = []
futures = []
user_callbacks = []
for i in range(4):
future = Mock()
future.done.return_value = False
user_callback = Mock()
msg_data = {
'topic': f'topic{i % 2}',
'value': f'unique_value_{i}',
'key': f'unique_key_{i}',
'user_callback': user_callback
}
self.batch_processor.add_message(msg_data, future)
messages_data.append(msg_data)
futures.append(future)
user_callbacks.append(user_callback)
return messages_data, futures, user_callbacks
def _add_alternating_topic_messages(self):
"""Helper to add messages alternating between two topics"""
futures = []
for i in range(5):
future = self.loop.create_future()
msg_data = {
'topic': f'topic{i % 2}',
'value': f'test{i}',
'key': f'key{i}'
}
self.batch_processor.add_message(msg_data, future)
futures.append(future)
return futures
def test_batch_cycle_buffer_state(self):
"""Test buffer state during batch cycle"""
self._add_alternating_topic_messages()
self.assertEqual(self.batch_processor.get_buffer_size(), 5)
self.assertFalse(self.batch_processor.is_buffer_empty())
def test_batch_cycle_topic_grouping(self):
"""Test topic grouping in batch cycle"""
self._add_alternating_topic_messages()
topic_groups = self.batch_processor._group_messages_by_topic_and_partition()
self.assertEqual(len(topic_groups), 2)
self.assertIn(('topic0', -1), topic_groups)
self.assertIn(('topic1', -1), topic_groups)
self.assertEqual(len(topic_groups[('topic0', -1)]['messages']), 3)
self.assertEqual(len(topic_groups[('topic1', -1)]['messages']), 2)
def test_batch_cycle_message_preparation(self):
"""Test message preparation in batch cycle"""
self._add_alternating_topic_messages()
topic_groups = self.batch_processor._group_messages_by_topic_and_partition()
batch_messages = self.batch_processor._prepare_batch_messages(
topic_groups[('topic0', -1)]['messages']
)
self.assertEqual(len(batch_messages), 3)
for batch_msg in batch_messages:
self.assertNotIn('topic', batch_msg)
self.assertIn('value', batch_msg)
self.assertIn('key', batch_msg)
def test_batch_message_preparation_with_mixed_sizes(self):
"""Test batch message preparation with mixed message sizes"""
# Create test messages with different sizes
messages = [
{'topic': 'test-topic', 'value': 'small message'},
{'topic': 'test-topic', 'value': 'x' * (5 * 1024 * 1024)}, # Large message
{'topic': 'test-topic', 'value': 'another small'},
]
futures = [asyncio.Future(), asyncio.Future(), asyncio.Future()]
for msg, future in zip(messages, futures):
self.batch_processor.add_message(msg, future)
topic_groups = self.batch_processor._group_messages_by_topic_and_partition()
topic_data = topic_groups[('test-topic', -1)]
batch_messages = self.batch_processor._prepare_batch_messages(topic_data['messages'])
self.assertEqual(len(batch_messages), 3)
large_msg = next((msg for msg in batch_messages if len(str(msg.get('value', ''))) > 1000), None)
self.assertIsNotNone(large_msg)
def test_future_based_usage_pattern(self):
"""Test the recommended Future-based usage pattern instead of callbacks."""
# Create test messages without user callbacks
messages = [
{'topic': 'test-topic', 'value': 'test1', 'key': 'key1'},
{'topic': 'test-topic', 'value': 'test2', 'key': 'key2'},
]
futures = [asyncio.Future(), asyncio.Future()]
# Add messages to batch processor
for msg, future in zip(messages, futures):
self.batch_processor.add_message(msg, future)
# Verify messages are in buffer
self.assertEqual(self.batch_processor.get_buffer_size(), 2)
# Simulate successful delivery by resolving futures
mock_msg1 = Mock()
mock_msg1.topic.return_value = 'test-topic'
mock_msg1.value.return_value = b'test1'
mock_msg2 = Mock()
mock_msg2.topic.return_value = 'test-topic'
mock_msg2.value.return_value = b'test2'
# Applications should await these futures to get delivery results
futures[0].set_result(mock_msg1)
futures[1].set_result(mock_msg2)
# Verify futures are resolved
self.assertTrue(futures[0].done())
self.assertTrue(futures[1].done())
self.assertEqual(futures[0].result(), mock_msg1)
self.assertEqual(futures[1].result(), mock_msg2)
def test_future_based_error_handling(self):
"""Test Future-based error handling pattern."""
# Create test message
message = {'topic': 'test-topic', 'value': 'test', 'key': 'key'}
future = asyncio.Future()
# Add message to batch processor
self.batch_processor.add_message(message, future)
# Simulate delivery error by setting exception on future
mock_error = RuntimeError("Delivery failed")
future.set_exception(mock_error)
# Verify future is resolved with exception
self.assertTrue(future.done())
with self.assertRaises(RuntimeError):
future.result()
def test_add_batches_back_to_buffer_basic(self):
"""Test adding batches back to buffer with basic message data"""
from confluent_kafka.experimental.aio.producer._message_batch import create_message_batch
# Create test futures
future1 = asyncio.Future()
future2 = asyncio.Future()
# Create test batch with basic message data
batch = create_message_batch(
topic='test-topic',
messages=[
{'value': 'test1', 'key': 'key1'},
{'value': 'test2', 'key': 'key2'}
],
futures=[future1, future2],
partition=0
)
# Ensure buffer is initially empty
self.assertTrue(self.batch_processor.is_buffer_empty())
# Add batch back to buffer
self.batch_processor._add_batches_back_to_buffer([batch])
# Verify buffer state
self.assertEqual(self.batch_processor.get_buffer_size(), 2)
self.assertFalse(self.batch_processor.is_buffer_empty())
# Verify message data was reconstructed correctly
self.assertEqual(self.batch_processor._message_buffer[0]['topic'], 'test-topic')
self.assertEqual(self.batch_processor._message_buffer[0]['value'], 'test1')
self.assertEqual(self.batch_processor._message_buffer[0]['key'], 'key1')
self.assertEqual(self.batch_processor._message_buffer[1]['topic'], 'test-topic')
self.assertEqual(self.batch_processor._message_buffer[1]['value'], 'test2')
self.assertEqual(self.batch_processor._message_buffer[1]['key'], 'key2')
# Verify futures are preserved
self.assertEqual(self.batch_processor._buffer_futures[0], future1)
self.assertEqual(self.batch_processor._buffer_futures[1], future2)
def test_add_batches_back_to_buffer_empty_batch(self):
"""Test adding empty batch back to buffer"""
from confluent_kafka.experimental.aio.producer._message_batch import create_message_batch
# Create empty batch
batch = create_message_batch(
topic='test-topic',
messages=[],
futures=[],
partition=0
)
initial_size = self.batch_processor.get_buffer_size()
# Add empty batch back
self.batch_processor._add_batches_back_to_buffer([batch])
# Buffer size should remain unchanged
self.assertEqual(self.batch_processor.get_buffer_size(), initial_size)
if __name__ == '__main__':
# Run all tests
unittest.main(verbosity=2)
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