database access for rooms and mqtt client + generator

mqtt_data_generator.py

@@ -0,0 +1,63 @@
+# test script to generate sensor data for testing
+# made to reprsent real world data
+
+from contextlib import asynccontextmanager
+from fastapi import FastAPI
+from fastapi_mqtt import MQTTConfig, FastMQTT
+from gmqtt import Client as MQTTClient
+import fastapi_mqtt as mqtt
+import uvicorn
+
+import datetime
+import logging
+import random
+import asyncio
+
+mqtt_config = mqtt.MQTTConfig(
+    host="localhost",
+    port=1883,
+    keepalive=60,
+)
+
+fast_mqtt = mqtt.FastMQTT(config=mqtt_config)
+
+@asynccontextmanager
+async def _lifespan(_app: FastAPI):
+    await fast_mqtt.mqtt_startup()
+    asyncio.create_task(main())
+    yield
+    await fast_mqtt.mqtt_shutdown()
+
+app = FastAPI(lifespan=_lifespan)
+
+
+# weights for hourly temps, based on LKTB sample on nov, 4th 2025
+TIME_WEIGHTS = [
+    4, 3, 3, 2, 2, 2, 2, 1, 3, 6, 8, 9, 11, 12, 12, 12, 11, 10, 9, 9, 8, 8, 5, 5
+]
+# weights for specific rooms, here inside/outside
+ROOM_WEIGHTS = {
+    "outside": 0,
+    "inside": 10
+}
+
+@fast_mqtt.on_connect()
+def connect(client: MQTTClient, flags, rc, properties):
+    print("Connected: ", client, flags, rc, properties)
+
+async def publish_sensor_data(inside: bool = True):
+    now = datetime.datetime.now()
+    base_temp = TIME_WEIGHTS[now.hour]
+    temp = base_temp + ROOM_WEIGHTS["inside" if inside else "outside"] + random.gauss(0,0.5)
+    logging.info(f"{now.isoformat()},{temp}")
+    fast_mqtt.publish("210/temp" if inside else "000/temp", f"{now.isoformat()},{temp}", qos=0)
+
+async def main():
+    while True:
+        await publish_sensor_data(inside=False)
+        await publish_sensor_data(inside=True)
+        await asyncio.sleep(300)
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.INFO)
+    uvicorn.run(app)