asyncio.sleep

- Added exception handling to capture and report any failures during query execution. 5. **Granular Timing**: - Tracks the total execution time of all queries and prints it at the end. This approach provides a more realistic simulat…

2. **Asynchronous Processing**: Use asynchronous execution to handle multiple queries concurrently. 3. **Batch Processing**: Batch similar queries together to reduce overhead. 4. **Optimize Network Calls**: If the delay is due to network ca…

time.sleep(10) # Simulating a time-consuming task def main(): start_time = datetime.datetime.now() # Profile the critical assignment code profiler = cProfile.Profile() profiler.enable() critical_assignmen…

try: future = producer.send(topic, value=data) record_metadata = future.get(timeout=10) # Wait for the message to be sent print(f"Message sent to topic {record_metadata.topic}, partition {record_…

def fetch_data(lang): # Simulate fetching data time.sleep(1) return {"result": f"Query result for {lang}"} return jsonify(fetch_data(language)) # Example usage if __name__ == '__main__': app.run(deb…

- Use parallel processing and asynchronous I/O to handle large numbers of files efficiently. By following these steps and considerations, you can ensure that your encryption method is properly implemented to handle a large number of file…

Here's an improved version of your Flask API endpoint using `Flask` and `gunicorn` for better performance and scalability: #### 1. **Asynchronous Processing with Flask and Gunicorn** Using `gunicorn` with multiple worker processes can hel…

1. **Sleep Simulation**: The `time.sleep(0.01)` simulates a 10ms delay per query. To handle 1,500 queries per minute, you need to process each query in less than 4ms (since 60,000ms / 1,500 queries = 40ms/query). 2. **Sequential Processing…

3. **Performance Measurement**: Added timing to measure the total processing time for 1,500 queries. ### Further Optimization 1. **Batch Processing**: If the query rewriting logic can be batched, consider processing queries in batches to …