Add temp.py

temp.py

@@ -0,0 +1,61 @@
+from influxdb_client import InfluxDBClient, Point
+from influxdb_client.client.write_api import SYNCHRONOUS
+import requests
+from datetime import datetime, timedelta
+import pytz
+
+# Fetch data from NOAA Radar API
+response = requests.get('https://api.weather.gov/radar/stations/SITE')
+data = response.json()
+
+# Extract relevant information
+radar_data = data['properties']
+
+# Convert Zulu time to Central Time
+zulu_time = datetime.fromisoformat(radar_data["latency"]["levelTwoLastReceivedTime"].replace("Z", "+00:00"))
+zulu_time = zulu_time.replace(tzinfo=pytz.utc)
+central_timezone = pytz.timezone('America/Chicago')
+central_time = zulu_time.astimezone(central_timezone)
+
+# Calculate data age
+current_time = datetime.now(tz=pytz.utc)
+current_time = current_time.astimezone(central_timezone)
+data_age = (current_time - central_time).total_seconds() / 60  # Convert seconds to minutes
+
+# Prepare data for InfluxDB
+measurement = 'radar_station'
+time = current_time.isoformat()
+
+# Create InfluxDB client
+client = InfluxDBClient(url="", token="", org="")
+
+# Create write API
+write_api = client.write_api(write_options=SYNCHRONOUS)
+
+# Define tags and fields
+tags = {"id": radar_data["id"]}
+fields = {
+    "name": str(radar_data["name"]),
+    "station_type": str(radar_data["stationType"]),
+    "elevation": float(radar_data["elevation"]["value"]),
+    "latency_current": float(radar_data["latency"]["current"]["value"]),
+    "latency_average": float(radar_data["latency"]["average"]["value"]),
+    "latency_max": float(radar_data["latency"]["max"]["value"]),
+    "resolution_version": str(radar_data["rda"]["properties"]["resolutionVersion"]),
+    "control_status": str(radar_data["rda"]["properties"]["controlStatus"]),
+    "shelter_temperature": float(radar_data["performance"]["properties"]["shelterTemperature"]["value"]),
+    "xmtr_temperature": float(radar_data["performance"]["properties"]["transmitterLeavingAirTemperature"]["value"]),
+    "output_power": float(radar_data["performance"]["properties"]["transmitterPeakPower"]["value"]),
+    "data_age_minutes": data_age,
+
+    # Check if volume_coverage_pattern starts with 'R' or 'L', remove prefix if exists and convert to float
+    "vcp": float(str(radar_data["rda"]["properties"]["volumeCoveragePattern"])[1:]) if str(radar_data["rda"]["properties"]["volumeCoveragePattern"]).startswith('R') or str(radar_data["rda"]["properties"]["volumeCoveragePattern"]).startswith('L') else float(rad>
+
+    # Add more fields as needed
+}
+
+# Write data to InfluxDB
+point = Point(measurement).time(time).tag("id", radar_data["id"])
+for field, value in fields.items():
+    point.field(field, value)
+write_api.write("Bucket", "Org", point)