updated code style regarding flake8 comments

trial_json.py

 # -*- coding: utf-8 -*-
 """
-Created on Thu May  5 17:27:38 2022
+Created on Thu May  5 17:27:38 2022 .
 
 @author: Richter
 
 testfile for operating with json-files
 
 """
-#%% import moduls
+# %% import moduls
 import json
-import numpy as np
+# import numpy as np
 import pandas as pd
-import h5py as h5
+# import h5py as h5
+
+# %% define functions
+
 
-#%% define functions
 def findkeys(node, kv):
-    '''
-    https://stackoverflow.com/questions/9807634/find-all-occurrences-of-a-key-in-nested-dictionaries-and-lists 
+    """
+    https://stackoverflow.com/questions/9807634/find-all-occurrences-of-a-key-in-nested-dictionaries-and-lists.
 
     Parameters
     ----------
@@ -30,46 +32,84 @@ def findkeys(node, kv):
     TYPE
         DESCRIPTION.
 
-    '''
+    """
     if isinstance(node, list):
         for i in node:
             for x in findkeys(i, kv):
-               yield x
+                yield x
     elif isinstance(node, dict):
         if kv in node:
             yield node[kv]
         for j in node.values():
             for x in findkeys(j, kv):
                 yield x
-                
-                
-def find_attribut(data,attribut):
-        name_pump = list(findkeys(data, "Name"))
-        efficiency_pump = list(findkeys(data, attribut))
-        #print("Die Pumpe",name_pump[0],"besitzt den Wirkungsgrad", efficiency_pump[0])
-        return name_pump, efficiency_pump
-    
+
+
+def find_attribut(data, attribut):
+    """
+    Find attribute of .
+
+    ----------
+    data : TYPE
+        DESCRIPTION.
+    attribut : TYPE
+        DESCRIPTION.
+
+    Returns
+    -------
+    name_pump : TYPE
+        DESCRIPTION.
+    efficiency_pump : TYPE
+        DESCRIPTION.
+
+    """
+    name_pump = list(findkeys(data, "Name"))
+    efficiency_pump = list(findkeys(data, attribut))
+    # print("Die Pumpe",name_pump[0],"besitzt den Wirkungsgrad", efficiency_pump[0])
+    return name_pump, efficiency_pump
+
+
 def calculate_efficiency(eta_1, eta_2):
+    """
+
+    Parameters.
+
+    ----------
+    eta_1 : TYPE
+        DESCRIPTION.
+    eta_2 : TYPE
+        DESCRIPTION.
+
+    Returns
+
+    -------
+    eta : TYPE
+        DESCRIPTION.
+
+    """
     eta = eta_1 * eta_2
     return eta
 
-#%% main script
-with open("test_data.json","r+") as file:
+# %% main script
+
+
+with open("test_data.json", "r+") as file:
     data = json.load(file)
 
+
 a = data.keys()
-#print(a)
+# print(a)
 
 # read out key - value - pairs
 for i in a:
     key = data[i]
-    for j in range(0,len(key)):
-        #print(j)
+    for j in range(0, len(key)):
+        # print(j)
         dic = key[j]
         attrs = list(dic.keys())
         for x in attrs:
             name = list(findkeys(dic, x))
-            #print("Maschinenart", i, "Das Attribut",x, "hat den Wert", name)
+            # print("Maschinenart", i, "Das Attribut",x, "hat den Wert", name)
 
 # find specific data
 machine = "Motors"
@@ -77,16 +117,16 @@ attribut = "Efficiency"
 data_pumps = data["Pumps"]
 data_motors = data["Motors"]
 dataset = pd.DataFrame()
-#pump_1 = data_pumps[0]
+# pump_1 = data_pumps[0]
 # Iteration über Attribute einfügen
 
-for i in range(0,len(data_pumps)):
+for i in range(0, len(data_pumps)):
     attr_name = list(findkeys(data_pumps[i], "Name"))
     attr_value = list(findkeys(data_pumps[i], attribut))
-    #attr_name, attr_value = find_attribut(data_pumps[i], attribut)
-    #efficiency_pump)
-    print("Die",machine,attr_name[0],"besitzt das Attribut",attribut, "mit dem Wert", attr_value[0])
-    
+    # attr_name, attr_value = find_attribut(data_pumps[i], attribut)
+    # efficiency_pump)
+    print("Die", machine, attr_name[0], "besitzt das Attribut", attribut, "mit dem Wert", attr_value[0])
+
 
 # multiplicate the pump efficiency with the motor efficiency
 
@@ -97,29 +137,23 @@ eta_pumpe_2 = list(findkeys(data["Pumps"][1], "Efficiency"))[0]
 
 
 count = 0
-#iteration over all pumps and motors
-for p in range(0,len(data_pumps)):
-    for m in range(0,len(data_motors)):
-        eta_pumpe=list(findkeys(data_pumps[p], attribut))[0]/100
-        eta_motor=list(findkeys(data_motors[m], attribut))[0]/100
+# iteration over all pumps and motors
+for p in range(0, len(data_pumps)):
+    for m in range(0, len(data_motors)):
+        eta_pumpe = list(findkeys(data_pumps[p], attribut))[0]/100
+        eta_motor = list(findkeys(data_motors[m], attribut))[0]/100
         eta_ges = calculate_efficiency(eta_pumpe, eta_motor)
         scenario = "Szenario_" + str(count)
-        dataset[scenario] = [eta_pumpe,eta_motor,eta_ges]
-        dataset.index = ["eta_pumpe","eta_motor","eta_ges"]
-        count +=1
-        print(p,m,eta_ges)
-        
-        
-#%% store dataframe in hdf5-file
+        dataset[scenario] = [eta_pumpe, eta_motor, eta_ges]
+        dataset.index = ["eta_pumpe", "eta_motor", "eta_ges"]
+        count += 1
+        print(p, m, eta_ges)
+
+
+# %% store dataframe in hdf5-file
 filename = "example_kpi.h5"
 with pd.HDFStore(filename, "a") as hdf:
     try:
-        dataset.to_hdf(hdf,"Berechnung")
+        dataset.to_hdf(hdf, "Berechnung")
     except ValueError:
         print("Gruppe existiert bereits.")
-        
-
-with h5.File(filename, "a") as hdf:
-    grp = hdf.get("Test")
-    grp_2 = hdf.get("Berechnung")
-    print(grp, grp_2)
\ No newline at end of file