Manual edits to remove remaining code style errors

modules/class_load_corrector.py

@@ -1,6 +1,3 @@
-import os
-import sys
-
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
@@ -16,12 +13,6 @@ from sklearn.metrics import mean_squared_error, r2_score
 # from sklearn.preprocessing import MinMaxScaler
 # from sqlalchemy import create_engine
 
-# Add the parent directory to sys.path
-sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-from config import *
-
-from modules.class_load import *
-
 
 class LoadPredictionAdjuster:
     def __init__(self, measured_data, predicted_data, load_forecast):

modules/class_optimize.py

@@ -1,34 +1,29 @@
 import os
+import sys
 
 import matplotlib
 import numpy as np
 
-from modules.class_akku import *
-from modules.class_ems import *
-from modules.class_haushaltsgeraet import *
-from modules.class_heatpump import *
-from modules.class_inverter import *
-from modules.class_load import *
-from modules.class_load_container import *
-from modules.class_pv_forecast import *
-from modules.class_sommerzeit import *
-from modules.visualize import *
+from modules.class_akku import PVAkku
+from modules.class_ems import EnergieManagementSystem, Wechselrichter
+from modules.class_haushaltsgeraet import Haushaltsgeraet
+from modules.visualize import visualisiere_ergebnisse
 
 matplotlib.use("Agg")  # Setzt das Backend auf Agg
 import random
-from datetime import datetime
+from datetime import datetime, timedelta
 
 from deap import algorithms, base, creator, tools
 
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-from config import *
+from config import moegliche_ladestroeme_in_prozent
 
 
 def isfloat(num):
     try:
         float(num)
         return True
-    except:
+    except ValueError:
         return False
 
 
@@ -213,7 +208,7 @@ class optimization_problem:
     def evaluate(self, individual, ems, parameter, start_hour, worst_case):
         try:
             o = self.evaluate_inner(individual, ems, start_hour)
-        except:
+        except Exception:
             return (100000.0,)
 
         gesamtbilanz = o["Gesamtbilanz_Euro"]
@@ -339,7 +334,7 @@ class optimization_problem:
         ############
         # Parameter
         ############
-        if startdate == None:
+        if startdate is None:
             date = (
                 datetime.now().date() + timedelta(hours=self.prediction_hours)
             ).strftime("%Y-%m-%d")
@@ -437,7 +432,7 @@ class optimization_problem:
         ##############
         opti_param = {}
         opti_param["haushaltsgeraete"] = 0
-        if spuelmaschine != None:
+        if spuelmaschine is not None:
             opti_param["haushaltsgeraete"] = 1
 
         self.setup_deap_environment(opti_param, start_hour)

modules/class_pv_forecast.py

@@ -69,7 +69,9 @@ class PVForecast:
                 f"Die Vorhersage muss mindestens {self.prediction_hours} Stunden umfassen, aber es wurden nur {len(self.forecast_data)} Stunden vorhergesagt."
             )
 
-    def update_ac_power_measurement(self, date_time=None, ac_power_measurement=None):
+    def update_ac_power_measurement(
+        self, date_time=None, ac_power_measurement=None
+    ) -> bool:
         found = False
         input_date_hour = date_time.replace(minute=0, second=0, microsecond=0)
 
@@ -81,6 +83,7 @@ class PVForecast:
                 forecast.ac_power_measurement = ac_power_measurement
                 found = True
                 break
+        return found
 
     def process_data(self, data):
         self.meta = data.get("meta", {})

modules/class_soc_calc.py

@@ -295,6 +295,7 @@ class BatteryDataProcessor:
 
 if __name__ == "__main__":
     # MariaDB Verbindungsdetails
+    config = {}
 
     # Parameter festlegen
     voltage_high_threshold = 55.4  # 100% SoC

modules/visualize.py

@@ -6,7 +6,7 @@ import matplotlib.pyplot as plt
 import numpy as np
 from matplotlib.backends.backend_pdf import PdfPages
 
-from modules.class_sommerzeit import *  # Ensure this matches the actual import path
+from modules.class_sommerzeit import ist_dst_wechsel
 
 matplotlib.use("Agg")