kwargs

artifact.update(**kwargs) else: raise KeyError(f"No artifact found with ID {artifact_id}") def remove_artifact(self, artifact_id): if artifact_id in self.artifacts: del self.artifacts…

start_time = time.perf_counter() result = func(*args, **kwargs) end_time = time.perf_counter() latency = end_time - start_time logging.info(f"Function {func.__name__} took {latency:.6f} seconds") …

# Check if the result is already in the cache cached_result = r.get(cache_key) if cached_result: return SearchResponse.parse_raw(cached_result) # Call the original…

To implement a multi-stage caching system, you need to ensure that the decorators are applied in the correct order and that the caching logic is properly nested. Here's a revised version of your implementation: ### Revised Implementation …

from functools import wraps def timer_decorator(func): @wraps(func) def wrapper(*args, **kwargs): start_time = time.time() result = func(*args, **kwargs) end_time = time.time() print(f"Function {func…

2. **Concurrency**: Use threading or multiprocessing to handle multiple queries concurrently. 3. **Caching**: Cache frequent queries to avoid redundant processing. 4. **Model Optimization**: If you are using a machine learning model, consid…

def profile_function(func, *args, **kwargs): pr = cProfile.Profile() pr.enable() result = func(*args, **kwargs) pr.disable() s = io.StringIO() ps = Stats(pr, stream=s).sort_stats('cumtime') ps.print_stats() p…