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from locust import HttpUser, task, between class RegularUser(HttpUser): wait_time = between(1, 5) # Regular users wait between 1 to 5 seconds between requests @task def get_index(self): self.client.get("/api/v1/endpoi…

# Example endpoint @app.get("/api/v1/sensitive-data") def get_sensitive_data(user_role: str = Depends(restrict_access)): return {"message": "Sensitive data"} @app.get("/api/v1/sensitive-settings") def get_sensitive_settings(user_role: …

if __name__ == '__main__': app.run(debug=True) ``` ### Explanation 1. **Setup Flask and Flask-Caching**: - Import necessary modules and initialize Flask and Flask-Caching. - Configure caching to use Redis. 2. **Define the API E…

# Define the API endpoint @app.route("/api/v1/sparse-train", methods=["GET"]) @limiter.limit("450/second") def get_sparse_data(): # ... (not sure how to implement this part) return jsonify({"message": "Sparse data retrieved successf…

from flask_limiter.util import get_remote_address app = Flask(__name__) limiter = Limiter(app, key_func=get_remote_address) # Define the API endpoint @app.route("/api/v1/sparse-train", methods=["GET"]) @limiter.limit("450/second") def get…

When you initialize the `QueryProcessor` with the optimal threshold, it will use this value to process queries and expand synonyms accordingly. ### Conclusion By integrating the optimal threshold into your query processing pipeline, you c…

'track_total_hits': True # Enable total hits tracking }) print(response['hits']['total']['value']) # Output: 1 ``` #### 4. Hardware and Resource Allocation - **Ensure Sufficient Resources**: Allocate enough CPU, memory, and disk spa…