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app/processing/pipelines/report_pipeline.py

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+from __future__ import annotations
+
+from datetime import datetime
+
+from app.models.mongodb.analytics_result import AnalyticsResult
+from app.processing.analyzers.device_analyzer import analyze_device_status
+from app.processing.analyzers.trend_analyzer import analyze_trend
+
+
+async def generate_device_report(
+    device_id: str, start: datetime, end: datetime
+) -> AnalyticsResult:
+    """Generate a comprehensive device report."""
+    status_report = await analyze_device_status(device_id, start, end)
+    trend_report = await analyze_trend(device_id, start, end)
+
+    result = AnalyticsResult(
+        analysis_type="device_report",
+        device_id=device_id,
+        parameters={"start": start.isoformat(), "end": end.isoformat()},
+        result={
+            "status": status_report,
+            "trends": trend_report,
+        },
+        period_start=start,
+        period_end=end,
+    )
+    await result.insert()
+    return result

app/processing/pipelines/telemetry_pipeline.py

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+from __future__ import annotations
+
+from datetime import datetime
+
+import polars as pl
+
+from app.models.mongodb.telemetry import TelemetryData
+
+
+async def aggregate_telemetry(
+    device_id: str,
+    start: datetime,
+    end: datetime,
+    interval: str = "1h",
+) -> pl.DataFrame:
+    """Aggregate telemetry data for a device over a time range."""
+    docs = await (
+        TelemetryData.find(
+            TelemetryData.device_id == device_id,
+            TelemetryData.timestamp >= start,
+            TelemetryData.timestamp <= end,
+        )
+        .sort("+timestamp")
+        .to_list()
+    )
+
+    if not docs:
+        return pl.DataFrame()
+
+    records = [
+        {"timestamp": d.timestamp, "device_id": d.device_id, **d.metrics}
+        for d in docs
+    ]
+
+    df = pl.DataFrame(records)
+    return df.sort("timestamp").group_by_dynamic("timestamp", every=interval).agg(
+        pl.all().exclude("timestamp", "device_id").mean()
+    )
+
+
+async def get_latest_telemetry(device_id: str, limit: int = 100) -> pl.DataFrame:
+    """Get latest telemetry records as a Polars DataFrame."""
+    docs = await (
+        TelemetryData.find(TelemetryData.device_id == device_id)
+        .sort("-timestamp")
+        .limit(limit)
+        .to_list()
+    )
+
+    if not docs:
+        return pl.DataFrame()
+
+    records = [
+        {"timestamp": d.timestamp, "device_id": d.device_id, **d.metrics}
+        for d in docs
+    ]
+    return pl.DataFrame(records)