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| import json | |
| import pandas as pd | |
| from pathlib import Path | |
| import os | |
| LOG_FILE = Path("logs/api_requests.jsonl") | |
| OUT_FILE = Path("monitoring/prod_data.csv") | |
| MODE = os.getenv("PROD_MODE", "recent_half") # all | recent_half | |
| records = [] | |
| with open(LOG_FILE, "r", encoding="utf-8") as f: | |
| for line in f: | |
| record = json.loads(line) | |
| if record.get("event") == "prediction": | |
| records.append({ | |
| "probability_default": record["output"]["probability_default"] | |
| }) | |
| df = pd.DataFrame(records) | |
| if df.empty: | |
| raise ValueError("Aucune donnée de production trouvée (event=prediction dans les logs).") | |
| # Par défaut: on prend la moitié la plus récente comme 'current' pour le drift | |
| mode = MODE | |
| if mode == "recent_half" and len(df) > 1: | |
| split_index = max(1, len(df) // 2) | |
| df = df.iloc[split_index:].reset_index(drop=True) | |
| df.to_csv(OUT_FILE, index=False) | |
| print(f"✅ Données de production exportées : {OUT_FILE}") | |