From 059c436717dd48776a68deb49d736ba3cfdf2c28 Mon Sep 17 00:00:00 2001
From: Marko Djordjevic <marko.homoludens@gmail.com>
Date: Wed, 18 Feb 2026 20:58:11 +0100
Subject: [PATCH] code-review-fix task 15.3: replace datetime.utcnow() with
 datetime.now(timezone.utc) in main.py

---
 services/ml/app/main.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/services/ml/app/main.py b/services/ml/app/main.py
index 83fc328..3632072 100644
--- a/services/ml/app/main.py
+++ b/services/ml/app/main.py
@@ -14,7 +14,7 @@ import uuid
 from contextlib import asynccontextmanager
 from pathlib import Path
 from typing import Optional, Dict, Any, List
-from datetime import datetime
+from datetime import datetime, timezone
 import json
 
 import requests as http_requests
@@ -81,7 +81,7 @@ async def lifespan(app: FastAPI):
                 .where(TrainingRun.status == "running")
                 .values(
                     status="failed",
-                    completed_at=datetime.utcnow(),
+                    completed_at=datetime.now(timezone.utc),
                     metrics_summary={"error": "Service restarted while training was in progress"},
                 )
             )
@@ -1226,7 +1226,7 @@ def _run_training_background(run_id: str, model_type: str, config: PipelineConfi
                             .where(TrainingRun.run_id == run_id)
                             .values(
                                 status="failed",
-                                completed_at=datetime.utcnow(),
+                                completed_at=datetime.now(timezone.utc),
                                 metrics_summary={
                                     "error": "Training timed out after 30 minutes"
                                 },
@@ -1268,7 +1268,7 @@ def _run_training_background(run_id: str, model_type: str, config: PipelineConfi
             "model": model_instance,
             "metadata": {
                 "model_type": model_type,
-                "trained_at": datetime.utcnow().isoformat(),
+                "trained_at": datetime.now(timezone.utc).isoformat(),
                 "run_id": run_id,
                 "feature_columns": feature_cols,
                 "labels": (
@@ -1288,7 +1288,7 @@ def _run_training_background(run_id: str, model_type: str, config: PipelineConfi
                 .where(TrainingRun.run_id == run_id)
                 .values(
                     status="completed",
-                    completed_at=datetime.utcnow(),
+                    completed_at=datetime.now(timezone.utc),
                     metrics_summary=metrics,
                 )
             )
@@ -1306,7 +1306,7 @@ def _run_training_background(run_id: str, model_type: str, config: PipelineConfi
                     .where(TrainingRun.run_id == run_id)
                     .values(
                         status="failed",
-                        completed_at=datetime.utcnow(),
+                        completed_at=datetime.now(timezone.utc),
                         metrics_summary={"error": str(exc)},
                     )
                 )
@@ -1368,7 +1368,7 @@ async def training_start(request: TrainingStartRequest):
                 experiment_name=config.stages.training.mlflow.experiment_name,
                 pipeline_config_hash=config_hash,
                 status="running",
-                created_at=datetime.utcnow(),
+                created_at=datetime.now(timezone.utc),
                 metrics_summary={},
             )
             db.add(training_run)