fix pre-commit and delte pcap test file

src/alerter/alerter.py

@@ -331,9 +331,7 @@ def bootstrap_alerter_instance(self):
                                 # 2. Executing Base Logging Actions
                                 self._log_to_file_action()
                                 self._log_to_kafka_action()
-                                self._record_alerter_terminal_events(
-                                    server_message_ids
-                                )
+                                self._record_alerter_terminal_events(server_message_ids)
                         finally:
                             self.clear_data()
 

src/base/kafka/config.py

@@ -56,6 +56,5 @@
 def bootstrap_servers() -> str:
     """Return the configured brokers in confluent-kafka format."""
     return ",".join(
-        f"{broker['hostname']}:{broker['internal_port']}"
-        for broker in KAFKA_BROKERS
+        f"{broker['hostname']}:{broker['internal_port']}" for broker in KAFKA_BROKERS
     )

src/base/kafka/consumer.py

@@ -124,15 +124,19 @@ def consume_batch(
         """Fetch a bounded group of records without committing offsets."""
         batch_size = max(
             1,
-            kafka_config.KAFKA_TRANSACTION_BATCH_SIZE
-            if max_messages is None
-            else int(max_messages),
+            (
+                kafka_config.KAFKA_TRANSACTION_BATCH_SIZE
+                if max_messages is None
+                else int(max_messages)
+            ),
         )
         batch_timeout_ms = max(
             0,
-            kafka_config.KAFKA_TRANSACTION_BATCH_TIMEOUT_MS
-            if timeout_ms is None
-            else int(timeout_ms),
+            (
+                kafka_config.KAFKA_TRANSACTION_BATCH_TIMEOUT_MS
+                if timeout_ms is None
+                else int(timeout_ms)
+            ),
         )
         deadline = time.monotonic() + batch_timeout_ms / 1000
         records = []

src/base/kafka/topics.py

@@ -203,9 +203,7 @@ def _wait_for_admin_futures(futures: dict, operation: str) -> None:
             try:
                 future.result()
             except KafkaException as exception:
-                if operation == "create topic" and _is_topic_already_created(
-                    exception
-                ):
+                if operation == "create topic" and _is_topic_already_created(exception):
                     logger.info("Kafka topic '%s' already exists.", topic)
                     continue
                 if (

src/base/retry.py

@@ -47,9 +47,7 @@ def load_retry_settings(config: dict[str, Any]) -> RetrySettings:
         max_delay_seconds=max(
             initial_delay, _float_setting(merged, "max_delay_seconds")
         ),
-        backoff_multiplier=max(
-            1.0, _float_setting(merged, "backoff_multiplier")
-        ),
+        backoff_multiplier=max(1.0, _float_setting(merged, "backoff_multiplier")),
         jitter_seconds=max(0.0, _float_setting(merged, "jitter_seconds")),
         log_every_attempts=max(1, _int_setting(merged, "log_every_attempts")),
     )

src/logserver/server.py

@@ -124,7 +124,9 @@ def fetch_from_kafka(self) -> None:
                 for source_message in source_messages:
                     value = source_message.value
                     if value is None:
-                        raise ValueError("LogServer received a Kafka record without data.")
+                        raise ValueError(
+                            "LogServer received a Kafka record without data."
+                        )
                     logger.debug(f"From Kafka: '{value}'")
 
                     message_id = uuid.uuid4()

src/monitoring/monitoring_agent.py

@@ -27,12 +27,8 @@
     "hostname"
 ]
 MONITORING_CONSUMER_CONFIG = CONFIG["pipeline"]["monitoring"]["kafka_consumer"]
-MONITORING_CONSUMER_BATCH_SIZE = max(
-    1, int(MONITORING_CONSUMER_CONFIG["batch_size"])
-)
-MONITORING_CONSUMER_TIMEOUT_MS = max(
-    0, int(MONITORING_CONSUMER_CONFIG["timeout_ms"])
-)
+MONITORING_CONSUMER_BATCH_SIZE = max(1, int(MONITORING_CONSUMER_CONFIG["batch_size"]))
+MONITORING_CONSUMER_TIMEOUT_MS = max(0, int(MONITORING_CONSUMER_CONFIG["timeout_ms"]))
 
 
 def prepare_all_tables():
@@ -144,9 +140,7 @@ def run(self) -> None:
                     )
                     for source_record in source_records:
                         try:
-                            table_name = source_record.topic.removeprefix(
-                                "clickhouse_"
-                            )
+                            table_name = source_record.topic.removeprefix("clickhouse_")
                             data = self.data_schemas[table_name].loads(
                                 source_record.value
                             )
@@ -177,9 +171,7 @@ def build_monitoring_worker(worker_id: str) -> MonitoringAgent:
     return MonitoringAgent(worker_id=worker_id)
 
 
-def run_monitoring_worker_process(
-    process_index: int, threads_per_process: int
-) -> None:
+def run_monitoring_worker_process(process_index: int, threads_per_process: int) -> None:
     """Run all monitoring threads assigned to one process."""
     run_thread_worker_pool(
         worker_factory=build_monitoring_worker,

tests/logserver/test_server.py

@@ -134,9 +134,7 @@ async def test_fetch_from_kafka(
         mock_uuid.return_value = mock_uuid_instance
         mock_uuid.uuid4.return_value = UUID("bd72ccb4-0ef2-4100-aa22-e787122d6875")
         mock_consume_handler = MagicMock()
-        source_message = ConsumedKafkaMessage(
-            "key1", "value1", "test-topic", 0, 1
-        )
+        source_message = ConsumedKafkaMessage("key1", "value1", "test-topic", 0, 1)
         mock_consume_handler.consume_batch.side_effect = [
             [source_message],
             _StopFetching(),