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app/tasks/analytics_tasks.py

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+from __future__ import annotations
+
+import structlog
+
+from app.tasks.celery_app import celery_app
+
+logger = structlog.get_logger("tasks.analytics")
+
+
+@celery_app.task(name="app.tasks.analytics_tasks.run_daily_analytics")
+def run_daily_analytics() -> dict:
+    """Run daily aggregation analytics on telemetry data."""
+    import asyncio
+    from datetime import datetime, timedelta
+
+    from app.models.mongodb.analytics_result import AnalyticsResult
+    from app.models.mongodb.telemetry import TelemetryData
+
+    async def _run() -> dict:
+        yesterday = datetime.utcnow().replace(hour=0, minute=0, second=0) - timedelta(days=1)
+        today = yesterday + timedelta(days=1)
+
+        pipeline = [
+            {"$match": {"timestamp": {"$gte": yesterday, "$lt": today}}},
+            {"$group": {
+                "_id": "$device_id",
+                "count": {"$sum": 1},
+                "avg_metrics": {"$avg": "$metrics.value"},
+            }},
+        ]
+
+        collection = TelemetryData.get_motor_collection()
+        results = await collection.aggregate(pipeline).to_list(length=1000)
+
+        for r in results:
+            await AnalyticsResult(
+                analysis_type="daily_telemetry",
+                device_id=r["_id"],
+                parameters={"date": yesterday.isoformat()},
+                result={"count": r["count"], "avg_value": r.get("avg_metrics")},
+                period_start=yesterday,
+                period_end=today,
+            ).insert()
+
+        return {"devices_analyzed": len(results)}
+
+    result = asyncio.get_event_loop().run_until_complete(_run())
+    logger.info("daily_analytics_done", **result)
+    return result
+
+
+@celery_app.task(name="app.tasks.analytics_tasks.run_device_analysis")
+def run_device_analysis(device_id: str, analysis_type: str, params: dict) -> dict:
+    """Run on-demand analysis for a specific device."""
+    logger.info("device_analysis_started", device_id=device_id, type=analysis_type)
+    return {"status": "completed", "device_id": device_id, "type": analysis_type}