shelly hinzugefügt

data/.~lock.shelly_pro_3m_registers.xlsx#

@@ -0,0 +1 @@
+,nils,nils-ThinkPad-P52,26.05.2025 20:45,file:///home/nils/.config/libreoffice/4;

data_base_influx.py

@@ -10,8 +10,8 @@ class DataBaseInflux:
         self.client = InfluxDBClient(url=self.url, token=self.token, org=self.org)
         self.write_api = self.client.write_api()
 
-    def store_data(self, data: dict):
+    def store_data(self, device_name: str, data: dict):
-        measurement = "messungen"  # Fest auf "messungen" gesetzt
+        measurement = device_name # Fest auf "messungen" gesetzt
 
         point = Point(measurement)
 
@@ -25,9 +25,4 @@ class DataBaseInflux:
         # Punkt in InfluxDB schreiben
         self.write_api.write(bucket=self.bucket, org=self.org, record=point)
 
-db = DataBaseInflux(
+
-    url="http://localhost:8086",
-    token="Cw_naEZyvJ3isiAh1P4Eq3TsjcHmzzDFS7SlbKDsS6ZWL04fMEYixWqtNxGThDdG27S9aW5g7FP9eiq5z1rsGA==",
-    org="allmende",
-    bucket="allmende_db"
-)

heat_pump.py

@@ -3,7 +3,8 @@ import pandas as pd
 import time
 
 class HeatPump:
-    def __init__(self, ip_address: str):
+    def __init__(self, device_name: str, ip_address: str):
+        self.device_name = device_name
         self.ip = ip_address
         self.client = None
         self.connect_to_modbus()
@@ -25,7 +26,7 @@ class HeatPump:
 
     def get_registers(self):
         # Excel-Datei mit den Input-Registerinformationen
-        excel_path = "data/ModBus TCPIP 1.17(1).xlsx"
+        excel_path = "data/heat_pump_registers.xlsx"
         xls = pd.ExcelFile(excel_path)
         df_input_registers = xls.parse('04 Input Register')
 

main.py

@@ -3,22 +3,24 @@ from datetime import datetime
 from data_base_csv import DataBaseCsv
 from data_base_influx import DataBaseInflux
 from heat_pump import HeatPump
+from shelly_pro_3m import ShellyPro3m
 
-interval = 10  # z.B. alle 10 Sekunden
+interval = 10
 
-#db = DataBaseCsv('modbus_log.csv')
 db = DataBaseInflux(
     url="http://localhost:8086",
     token="Cw_naEZyvJ3isiAh1P4Eq3TsjcHmzzDFS7SlbKDsS6ZWL04fMEYixWqtNxGThDdG27S9aW5g7FP9eiq5z1rsGA==",
     org="allmende",
     bucket="allmende_db"
 )
-hp = HeatPump(ip_address='10.0.0.10')
+
+hp = HeatPump(device_name='hp_master', ip_address='10.0.0.10')
+shelly = ShellyPro3m(device_name='wohnung_2_6', ip_address='192.168.1.121')
 
 while True:
     now = datetime.now()
     if now.second % interval == 0 and now.microsecond < 100_000:
-       db.store_data(hp.get_data())
+       db.store_data(hp.device_name, hp.get_data())
-
+       db.store_data(shelly.device_name, shelly.get_data())
     time.sleep(0.1)
 

shelly_pro_3m.py

@@ -0,0 +1,60 @@
+from pymodbus.client import ModbusTcpClient
+import pandas as pd
+import time
+
+class ShellyPro3m:
+    def __init__(self, device_name: str, ip_address: str):
+        self.device_name = device_name
+        self.ip = ip_address
+        self.client = None
+        self.connect_to_modbus()
+        self.registers = None
+        self.get_registers()
+
+    def connect_to_modbus(self):
+        port = 502
+        self.client = ModbusTcpClient(self.ip, port=port)
+        try:
+            if not self.client.connect():
+                print("Verbindung zur Wärmepumpe fehlgeschlagen.")
+                exit(1)
+            print("Verbindung zur Wärmepumpe erfolgreich.")
+        except KeyboardInterrupt:
+            print("Beendet durch Benutzer (Ctrl+C).")
+        finally:
+            self.client.close()
+
+    def get_registers(self):
+        # Excel-Datei mit den Input-Registerinformationen
+        excel_path = "data/shelly_pro_3m_registers.xlsx"
+        xls = pd.ExcelFile(excel_path)
+        df_input_registers = xls.parse()
+
+        # Relevante Spalten bereinigen
+        df_clean = df_input_registers[['MB Adresse', 'Beschreibung', 'Variabel Typ']].dropna()
+        df_clean['MB Adresse'] = df_clean['MB Adresse'].astype(int)
+
+        # Dictionary aus Excel erzeugen
+        self.registers = {
+            row['MB Adresse']: {
+                'desc': row['Beschreibung'],
+                'type': 'REAL' if row['Variabel Typ'] == 'REAL' else 'INT'
+            }
+            for _, row in df_clean.iterrows()
+        }
+
+    def get_data(self):
+        data = {}
+        data['Zeit'] = time.strftime('%Y-%m-%d %H:%M:%S')
+        for address, info in self.registers.items():
+            reg_type = info['type']
+            result = self.client.read_input_registers(address, count=2 if reg_type == 'REAL' else 1)
+            if result.isError():
+                print(f"Fehler beim Lesen von Adresse {address}: {result}")
+                continue
+
+            value = result.registers[0] / 10.0
+
+            print(f"Adresse {address} - {info['desc']}: {value}")
+            data[f"{address} - {info['desc']}"] = value
+        return data