queue

from datetime import datetime import asyncio import queue # Set up logging logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) # Create a rotating file handler file_handler = RotatingFileHandler('auth_logs.log', maxBytes=1…

es_client.indices.create(index='auth_logs', body=settings) ``` #### Step 6: Use Efficient Data Formats Use JSON for logging, which can be easily parsed and indexed by Elasticsearch. ### Full Example Here is the full example combining al…

Before diving into implementation, define what you need to log. For query performance, you might want to capture: - Query text - Execution time - User ID - Query parameters - Timestamp ### Step 2: Use Asynchronous Logging Asynchronous lo…

q = queue.Queue(-1) # No limit on queue size queue_handler = QueueHandler(q) queue_listener = QueueListener(q, logging.FileHandler('query_performance.log')) # Add the queue handler to the logger logger.addHandler(queue_handler) # Start t…

Using a dedicated thread for logging can help offload the logging task and reduce the impact on the main application. ### Example Implementation Here's an updated version of your code that incorporates these improvements: ```python impor…

log_processor_thread.start() # Define a function to log queries def log_query(query, user_id=None, query_params=None): log_entry = { "query": query, "user_id": user_id, "query_params": query_params, "tim…