Add local_test.py

local_test.py

@@ -0,0 +1,114 @@
+### This file is used to test the aurora inverter (via TCP) locally without Homeassistant.
+
+from aurorapy.client import AuroraTCPClient, AuroraError
+import json
+from datetime import datetime, timedelta
+
+# Konfiguration
+TARGET_IP = "192.168.250.245"
+TARGET_PORT = 5000
+INVERTER_ADDRESS = 2  # Slave-ID deines Wechselrichters
+
+def test_comprehensive_data():
+    try:
+        client = AuroraTCPClient(ip=TARGET_IP, port=TARGET_PORT, address=INVERTER_ADDRESS, timeout=10)
+        client.connect()
+
+        # Daten abfragen
+        data = {}
+
+        # 50: State Request
+        try:
+            data["state"] = client.state_request()
+        except AttributeError:
+            data["state"] = "Methode nicht verfügbar"
+
+        # 58: Version Reading
+        try:
+            data["version"] = client.version()
+        except AttributeError:
+            data["version"] = "Methode nicht verfügbar"
+
+        # 63: Serial Number Reading
+        try:
+            data["serial_number"] = client.serial_number()
+        except AttributeError:
+            data["serial_number"] = "Methode nicht verfügbar"
+
+        # 65: Manufacturing Week and Year
+        try:
+            data["manufacturing_week_year"] = client.manufacturing_week_year()
+        except AttributeError:
+            try:
+                data["manufacturing_week_year"] = client.manufacturing_date()
+            except AttributeError:
+                data["manufacturing_week_year"] = "Methode nicht verfügbar"
+
+        # 68: Cumulated Float Energy Readings
+        try:
+            data["daily_energy_float"] = client.cumulated_energy(period=1)
+            data["week_energy_float"] = client.cumulated_energy(period=2)
+            data["month_energy_float"] = client.cumulated_energy(period=3)
+            data["year_energy_float_global"] = client.cumulated_energy(period=4, global_measure=True)
+            data["total_energy_float_global"] = client.cumulated_energy(period=6, global_measure=True)
+        except AttributeError:
+            data["cumulated_float_energy"] = "Methode nicht verfügbar"
+
+        # 70: Time/Date Reading
+        try:
+            seconds_since_2000 = client.time_date()
+            data["time_date"] = (datetime(2000, 1, 1) + timedelta(seconds=seconds_since_2000)).strftime("%Y-%m-%d %H:%M:%S")
+        except AttributeError:
+            data["time_date"] = "Methode nicht verfügbar"
+
+        # 72: Firmware Release Reading
+        try:
+            data["firmware_micro_release_C"] = client.firmware(3)
+        except AttributeError:
+            data["firmware_micro_release_C"] = "Methode nicht verfügbar"
+
+        # 78: Cumulated Energy Readings
+        try:
+            data["daily_energy"] = client.cumulated_energy(1)
+            data["week_energy"] = client.cumulated_energy(2)
+            data["month_energy"] = client.cumulated_energy(3)
+            data["year_energy"] = client.cumulated_energy(4)
+            data["total_energy"] = client.cumulated_energy(5)
+        except AttributeError:
+            data["cumulated_energy"] = "Methode nicht verfügbar"
+
+        # 86: Last Four Alarms
+        try:
+            data["last_four_alarms"] = client.alarms()
+        except AttributeError:
+            data["last_four_alarms"] = "Methode nicht verfügbar"
+
+        # 59: Measure Requests
+        try:
+            data["grid_voltage"] = client.measure(1)
+            data["grid_current"] = client.measure(2)
+            data["grid_power"] = client.measure(3)
+            data["frequency"] = client.measure(4)
+            data["inverter_temperature"] = client.measure(21)
+            data["booster_temperature"] = client.measure(22)
+            data["input_1_voltage"] = client.measure(23)
+            data["input_1_current"] = client.measure(25)
+            data["isolation_resistance"] = client.measure(30)
+        except AttributeError:
+            data["measure_requests"] = "Methode nicht verfügbar"
+
+        client.close()
+
+        # Daten als JSON speichern
+        with open('comprehensive_data.json', 'w') as f:
+            json.dump(data, f, indent=4)
+
+        print("Daten erfolgreich in 'comprehensive_data.json' gespeichert.")
+
+    except AuroraError as e:
+        print(f"Fehler bei der Kommunikation: {str(e)}")
+    except Exception as e:
+        print(f"Allgemeiner Fehler: {str(e)}")
+
+if __name__ == "__main__":
+    test_comprehensive_data()