predict_with_monitor.py

import time

class PerformanceMonitor:
    
    def __init__(self):
        self.inference_times = []
    
    def record(self, prediction_time: float) -> None:
        self.inference_times.append(prediction_time)
    
    def mean(self) -> float:
        return sum(self.inference_times)/len(self.inference_times)
        

def model_predict(user_id: str) -> float:
    start = time.time()
    model = load_latest_model()
    features = feature_store.get_user_feature(user_id)
    prediction = model.predict([[v for k,v in features.items() if k != "target"]])
    end = time.time()
    monitor.record(end-start)
    return prediction

monitor = PerformanceMonitor()
model_predict("a27b0912-0cf8-11ed-899e-b29c4abd48f4")