I build automated data systems that replace manual engineering grunt work.

' =========================================================================
' Asset: Tower_Alpha_DXB // NABERS Energy API Automated Orchestration
' Sub: ExecuteCompliancePayloadDispatch(ByVal AssetID As String, ByVal TelemetryPayload As String)
' =========================================================================

Public Sub ExecuteCompliancePayloadDispatch(ByVal AssetID As String)
    Dim http As Object, jsonBody As String, endpointURL As String
    Dim httpStatus As Long, responseText As String, retryCount As Integer
    
    endpointURL = "https://api.compliance-engine.internal/v2/ratings/commercial"
    
    ' Construct strictly typed JSON payload with sanitized meter telemetry
    jsonBody = "{" & _
               """asset_id"": """ & AssetID & """," & _
               """assessment_period"": {""start"": ""2025-01-01"", ""end"": ""2025-12-31""}," & _
               """gross_floor_area_sqm"": 48250.0," & _
               """rated_hours_per_week"": 55.0," & _
               """half_hourly_consumption_kwh"": " & GetTelemetryStreamBuffer(AssetID) & _
               "}"
               
    Set http = CreateObject("MSXML2.ServerXMLHTTP.6.0")
    
    ' Exponential backoff retry handler for 429 / 503 HTTP responses
    retryCount = 0
    Do
        http.Open "POST", endpointURL, False
        http.setRequestHeader "Content-Type", "application/json"
        http.setRequestHeader "Authorization", "Bearer " & GetSecureVaultToken()
        http.setRequestHeader "X-Audit-Origin", "DXB-Asset-Automator-v2.4"
        
        http.send jsonBody
        httpStatus = http.Status
        
        If httpStatus = 200 Or httpStatus = 201 Then
            responseText = http.responseText
            ParseAndCommitRatingRecord AssetID, responseText
            Exit Do
        ElseIf httpStatus = 429 And retryCount < 4 Then
            retryCount = retryCount + 1
            Sleep (2 ^ retryCount) * 1000 ' 2s, 4s, 8s backoff
        Else
            LogErrorToAuditLog AssetID, httpStatus, http.responseText
            Err.Raise vbObjectError + 501, "API_FAULT", "HTTP Failure: " & httpStatus
        End If
    Loop
End Sub

-- =========================================================================
-- Measure: [Baseline_Anomaly_Flag_3Sigma]
-- Model: Fact_MeterTelemetry linked 1:N to Dim_Asset, Dim_Calendar, Dim_Weather
-- =========================================================================

[Baseline_Anomaly_Flag_3Sigma] = 
VAR _CurrentHalfHourLoad = SUM(Fact_MeterTelemetry[ActivePower_kW])
VAR _AssetID = SELECTEDVALUE(Dim_Asset[AssetID])
VAR _CurrentOutdoorTemp = AVERAGE(Dim_Weather[AmbientDryBulb_C])

-- Calculate baseline load dynamically matching asset operating schedule & weather bin
VAR _HistoricalBaselineTable = 
    CALCULATETABLE(
        SUMMARIZE(
            Fact_MeterTelemetry,
            Dim_Calendar[Date],
            Fact_MeterTelemetry[HalfHourIndex],
            "@HistoricalKW", SUM(Fact_MeterTelemetry[ActivePower_kW])
        ),
        DATESINPERIOD(Dim_Calendar[Date], MAX(Dim_Calendar[Date]), -90, DAY),
        Fact_MeterTelemetry[IsOutageEvent] = FALSE,
        Dim_Weather[DegreeDayBin] = SELECTEDVALUE(Dim_Weather[DegreeDayBin])
    )

VAR _MeanLoad = AVERAGEX(_HistoricalBaselineTable, [@HistoricalKW])
VAR _StdDevLoad = STDEVX.S(_HistoricalBaselineTable, [@HistoricalKW])
VAR _ZScore = DIVIDE(_CurrentHalfHourLoad - _MeanLoad, _StdDevLoad, 0)

RETURN
    SWITCH(
        TRUE(),
        ISBLANK(_CurrentHalfHourLoad), BLANK(),
        _ZScore > 3.0, "CRITICAL_PEAK_BREACH",
        _ZScore < -3.0, "UNEXPECTED_SHUTDOWN",
        "NOMINAL_OPERATION"
    )

# =========================================================================
# Pipeline: Streaming Nested GeoJSON Parser with Centroid Aggregation
# Memory Guarantee: O(1) memory usage regardless of raw JSON file size
# =========================================================================

import ijson
import json
from typing import Generator, Dict, Any

def stream_spatial_records(file_path: str) -> Generator[Dict[str, Any], None, None]:
    """Iteratively parse multi-gigabyte raw Timeline JSON without memory ballooning."""
    with open(file_path, 'rb') as fh:
        # Stream items directly from nested timelineObjects array
        objects = ijson.items(fh, 'timelineObjects.item')
        for item in objects:
            if 'placeVisit' in item:
                loc = item['placeVisit'].get('location', {})
                lat = loc.get('latitudeE7')
                lng = loc.get('longitudeE7')
                confidence = item['placeVisit'].get('confidence', 0)
                
                # Schema validation & GPS coordinate conversion
                if lat and lng and confidence >= 70:
                    yield {
                        'lat': lat / 1e7,
                        'lng': lng / 1e7,
                        'place_id': loc.get('placeId', 'UNKNOWN'),
                        'start_timestamp': item['placeVisit']['duration']['startTimestamp']
                    }

def build_compact_geojson(generator: Generator, output_path: str):
    features = []
    for point in generator:
        features.append({
            "type": "Feature",
            "geometry": {
                "type": "Point",
                "coordinates": [point['lng'], point['lat']]
            },
            "properties": {
                "id": point['place_id'],
                "ts": point['start_timestamp']
            }
        })
    
    geojson_doc = {"type": "FeatureCollection", "features": features}
    with open(output_path, 'w') as out:
        json.dump(geojson_doc, out, separators=(',', ':'))