Black formatter :(

gcstruct/gcstruct.py

@@ -5,6 +5,7 @@ import json
 import csv
 import re
 import chevron
+
 # from shutil import copyfile
 from bs4 import BeautifulSoup
 from functools import reduce
@@ -12,202 +13,292 @@ from pathlib import Path
 
 
 def get_flat(node):
-    result = [{
-        'id': node['id'],
-        'text': node['text'],
-        'children': [x['id'] for x in node['children']],
-        'children2': [],
-        'parents': node['parents'],
-        'accounts': node['accounts'],
-        'costcenter': '',
-        'level': node['level'],
-        'drilldown': node['level'] < 2,    # (node['level'] != 2 and len(node['accounts']) == 0),
-        'form': node['form'],
-        'accountlevel': False,
-        'absolute': True,
-        'seasonal': True,
-        'status': "0",
-        'values': [],
-        'values2': {}
-    }]
-    for child in node['children']:
+    result = [
+        {
+            "id": node["id"],
+            "text": node["text"],
+            "children": [x["id"] for x in node["children"]],
+            "children2": [],
+            "parents": node["parents"],
+            "accounts": node["accounts"],
+            "costcenter": "",
+            "level": node["level"],
+            "drilldown": node["level"]
+            < 2,  # (node['level'] != 2 and len(node['accounts']) == 0),
+            "form": node["form"],
+            "accountlevel": False,
+            "absolute": True,
+            "seasonal": True,
+            "status": "0",
+            "values": [],
+            "values2": {},
+        }
+    ]
+    for child in node["children"]:
         result += get_flat(child)
     return result
 
 
 def get_parents_list(p_list):
-    id = ';'.join(p_list) + ';' * (10 - len(p_list))
+    id = ";".join(p_list) + ";" * (10 - len(p_list))
     if len(p_list) > 0:
         return [id] + get_parents_list(p_list[:-1])
-    return [';' * 9]
+    return [";" * 9]
 
 
 def structure_from_tree(node):
     result = []
-    result.append(node['id'])
-    for child in node['children']:
+    result.append(node["id"])
+    for child in node["children"]:
         result.extend(structure_from_tree(child))
     return result
 
 
 def xml_from_tree(xml_node, tree_node):
-    for child in tree_node['children']:
-        element = ET.SubElement(xml_node, 'Ebene')
-        element.set("Name", child['text'])
+    for child in tree_node["children"]:
+        element = ET.SubElement(xml_node, "Ebene")
+        element.set("Name", child["text"])
         xml_from_tree(element, child)
 
 
 def split_it(text, index):
     try:
-        return re.findall(r'([^;]+) - ([^;]*);;', text)[0][index]
+        return re.findall(r"([^;]+) - ([^;]*);;", text)[0][index]
     except Exception:
-        return ''
+        return ""
 
 
 def last_layer(text):
     try:
-        return re.findall(r'([^;]+);;', text)[0]
+        return re.findall(r"([^;]+);;", text)[0]
     except Exception:
-        return ''
+        return ""
 
 
 def get_default_cols(i):
-    return ['Ebene' + str(i) for i in range(i * 10 + 1, (i + 1) * 10 + 1)]
+    return ["Ebene" + str(i) for i in range(i * 10 + 1, (i + 1) * 10 + 1)]
 
 
 def get_structure_exports(s):
     result = {
-        'files': {},
-        'format': {
-            'KontoFormat': '{0} - {1}',
-            'HerstellerkontoFormat': '{{Herstellerkonto_Nr}}',
-            'HerstellerBezeichnungFormat': '{{Herstellerkonto_Bez}}',
-            'NeueHerstellerkontenAnlegen': False
-        }
+        "files": {},
+        "format": {
+            "KontoFormat": "{0} - {1}",
+            "HerstellerkontoFormat": "{{Herstellerkonto_Nr}}",
+            "HerstellerBezeichnungFormat": "{{Herstellerkonto_Bez}}",
+            "NeueHerstellerkontenAnlegen": False,
+        },
     }
-    export_files = ['ExportStk', 'ExportStrukturenStk', 'ExportAdjazenz', 'ExportUebersetzung',
-                    'ExportUebersetzungStk', 'ExportHerstellerKontenrahmen']
-    export_format = ['KontoFormat', 'HerstellerkontoFormat', 'HerstellerBezeichnungFormat', 'NeueHerstellerkontenAnlegen']
+    export_files = [
+        "ExportStk",
+        "ExportStrukturenStk",
+        "ExportAdjazenz",
+        "ExportUebersetzung",
+        "ExportUebersetzungStk",
+        "ExportHerstellerKontenrahmen",
+    ]
+    export_format = [
+        "KontoFormat",
+        "HerstellerkontoFormat",
+        "HerstellerBezeichnungFormat",
+        "NeueHerstellerkontenAnlegen",
+    ]
     for e in export_files:
-        if s.find(e) is not None and s.find(e).text is not None and s.find(e).text[-4:] == '.csv':
-            result['files'][e] = s.find(e).text
+        if (
+            s.find(e) is not None
+            and s.find(e).text is not None
+            and s.find(e).text[-4:] == ".csv"
+        ):
+            result["files"][e] = s.find(e).text
     for e in export_format:
-        if s.find(e) is not None and s.find(e).text != '':
-            result['format'][e] = s.find(e).text
+        if s.find(e) is not None and s.find(e).text != "":
+            result["format"][e] = s.find(e).text
 
-    result['format']['NeueHerstellerkontenAnlegen'] = (result['format']['NeueHerstellerkontenAnlegen'] == 'true')
+    result["format"]["NeueHerstellerkontenAnlegen"] = (
+        result["format"]["NeueHerstellerkontenAnlegen"] == "true"
+    )
     return result
 
 
-class GCStruct():
+class GCStruct:
     config = {
-        'path': 'c:/projekte/python/gcstruct',
-        'path2': 'c:/projekte/python/gcstruct',
-        'file': 'c:/projekte/python/gcstruct/config/config.xml',
-        'output': 'gcstruct.json',
-        'default': [],
-        'special': {},
-        'special2': {
-            'Planner': ['Kostenstelle', 'Ebene1', 'Ebene2'],
-            'Test': ['Ebene1', 'Ebene2']
+        "path": "c:/projekte/python/gcstruct",
+        "path2": "c:/projekte/python/gcstruct",
+        "file": "c:/projekte/python/gcstruct/config/config.xml",
+        "output": "gcstruct.json",
+        "default": [],
+        "special": {},
+        "special2": {
+            "Planner": ["Kostenstelle", "Ebene1", "Ebene2"],
+            "Test": ["Ebene1", "Ebene2"],
         },
-        'columns': ['Konto_Nr', 'Konto_Bezeichnung', 'Konto_Art', 'Konto_KST', 'Konto_STK',
-                    'Konto_1', 'Konto_2', 'Konto_3', 'Konto_4', 'Konto_5'],
-        'struct': {},
-        'export': {}
+        "columns": [
+            "Konto_Nr",
+            "Konto_Bezeichnung",
+            "Konto_Art",
+            "Konto_KST",
+            "Konto_STK",
+            "Konto_1",
+            "Konto_2",
+            "Konto_3",
+            "Konto_4",
+            "Konto_5",
+        ],
+        "struct": {},
+        "export": {},
     }
 
-    json_result = {'accounts': {}, 'tree': {}, 'flat': {}, 'struct_export': {}, 'skr51_vars': {}}
+    json_result = {
+        "accounts": {},
+        "tree": {},
+        "flat": {},
+        "struct_export": {},
+        "skr51_vars": {},
+    }
     structure_ids = []
 
-    translate = {'Konto_Nr': 'SKR51', 'Kostenstelle': 'KST', 'Absatzkanal': 'ABS',
-                 'Kostenträger': 'KTR', 'Marke': 'MAR', 'Standort': 'STA', 'Marke_HBV': 'MAR', 'Standort_HBV': 'BMC'}
+    translate = {
+        "Konto_Nr": "SKR51",
+        "Kostenstelle": "KST",
+        "Absatzkanal": "ABS",
+        "Kostenträger": "KTR",
+        "Marke": "MAR",
+        "Standort": "STA",
+        "Marke_HBV": "MAR",
+        "Standort_HBV": "BMC",
+    }
 
     def __init__(self, struct_dir, export_dir=None):
-        self.config['path'] = struct_dir
-        self.config['path2'] = struct_dir + '/export' if export_dir is None else export_dir
-
-        self.config['file'] = f"{self.config['path']}/config/gcstruct.xml"
-        if not Path(self.config['file']).exists():
-            self.config['file'] = f"{self.config['path']}/config/config.xml"
-
-        cfg = ET.parse(self.config['file'])
-        self.config['default'] = [s.find('Name').text for s in cfg.getroot().find('Strukturdefinitionen').findall('Struktur')]
-        self.config['export'] = dict([(s.find('Name').text, get_structure_exports(s)) for s in
-                                     cfg.getroot().find('Strukturdefinitionen').findall('Struktur')])
-
-        struct = dict([(x, get_default_cols(i)) for (i, x) in enumerate(self.config['default'])])
-        struct.update(self.config['special'])
-        self.config['struct'] = struct
+        self.config["path"] = struct_dir
+        self.config["path2"] = (
+            struct_dir + "/export" if export_dir is None else export_dir
+        )
+
+        self.config["file"] = f"{self.config['path']}/config/gcstruct.xml"
+        if not Path(self.config["file"]).exists():
+            self.config["file"] = f"{self.config['path']}/config/config.xml"
+
+        cfg = ET.parse(self.config["file"])
+        self.config["default"] = [
+            s.find("Name").text
+            for s in cfg.getroot().find("Strukturdefinitionen").findall("Struktur")
+        ]
+        self.config["export"] = dict(
+            [
+                (s.find("Name").text, get_structure_exports(s))
+                for s in cfg.getroot().find("Strukturdefinitionen").findall("Struktur")
+            ]
+        )
+
+        struct = dict(
+            [(x, get_default_cols(i)) for (i, x) in enumerate(self.config["default"])]
+        )
+        struct.update(self.config["special"])
+        self.config["struct"] = struct
         # print(self.config['struct'])
 
     def export_header(self, filetype):
         return {
-            'ExportStk': [],
-            'ExportStrukturenStk': [],
-            'ExportAdjazenz': [],
-            'ExportUebersetzung': ['Konto_Nr_Hersteller', 'Konto_Nr_Split', 'Konto_Nr_Haendler', 'Info'],
-            'ExportUebersetzungStk': ['Konto_Nr_Hersteller', 'Konto_Nr_Split', 'Konto_Nr_Haendler', 'Info'],
-            'ExportHerstellerKontenrahmen': ['Konto_Nr', 'Konto_Bezeichnung', 'Case', 'Info']
+            "ExportStk": [],
+            "ExportStrukturenStk": [],
+            "ExportAdjazenz": [],
+            "ExportUebersetzung": [
+                "Konto_Nr_Hersteller",
+                "Konto_Nr_Split",
+                "Konto_Nr_Haendler",
+                "Info",
+            ],
+            "ExportUebersetzungStk": [
+                "Konto_Nr_Hersteller",
+                "Konto_Nr_Split",
+                "Konto_Nr_Haendler",
+                "Info",
+            ],
+            "ExportHerstellerKontenrahmen": [
+                "Konto_Nr",
+                "Konto_Bezeichnung",
+                "Case",
+                "Info",
+            ],
         }[filetype]
 
     def accounts_from_csv(self, struct):
-        max_rows = (len(self.config['default']) + 1) * 10
-        with open(f"{self.config['path']}/Kontenrahmen/Kontenrahmen.csv", 'r', encoding='latin-1') as f:
-            csv_reader = csv.reader(f, delimiter=';')
+        max_rows = (len(self.config["default"]) + 1) * 10
+        with open(
+            f"{self.config['path']}/Kontenrahmen/Kontenrahmen.csv",
+            "r",
+            encoding="latin-1",
+        ) as f:
+            csv_reader = csv.reader(f, delimiter=";")
             imported_csv = [row[:max_rows] for row in csv_reader]
 
-        df = pd.DataFrame.from_records(np.array(imported_csv[1:], dtype='object'), columns=imported_csv[0]).fillna(value='')
-        df = df.rename(columns={'Kostenstelle': 'Konto_KST', 'STK': 'Konto_STK'})
+        df = pd.DataFrame.from_records(
+            np.array(imported_csv[1:], dtype="object"), columns=imported_csv[0]
+        ).fillna(value="")
+        df = df.rename(columns={"Kostenstelle": "Konto_KST", "STK": "Konto_STK"})
 
         for i, (s, cols) in enumerate(struct.items()):
-            df[s] = reduce(lambda x, y: x + ";" + df[y], cols, '')
+            df[s] = reduce(lambda x, y: x + ";" + df[y], cols, "")
             df[s] = df[s].apply(lambda x: x[1:])
-            df['LetzteEbene' + str(i + 1)] = df[s].apply(lambda x: last_layer(x))
-            df['LetzteEbene' + str(i + 1) + '_Nr'] = df[s].apply(lambda x: split_it(x, 0))
-            df['LetzteEbene' + str(i + 1) + '_Bez'] = df[s].apply(lambda x: split_it(x, 1))
-        df['Herstellerkonto_Nr'] = df['LetzteEbene1_Nr']
-        df['Herstellerkonto_Bez'] = df['LetzteEbene1_Bez']
+            df["LetzteEbene" + str(i + 1)] = df[s].apply(lambda x: last_layer(x))
+            df["LetzteEbene" + str(i + 1) + "_Nr"] = df[s].apply(
+                lambda x: split_it(x, 0)
+            )
+            df["LetzteEbene" + str(i + 1) + "_Bez"] = df[s].apply(
+                lambda x: split_it(x, 1)
+            )
+        df["Herstellerkonto_Nr"] = df["LetzteEbene1_Nr"]
+        df["Herstellerkonto_Bez"] = df["LetzteEbene1_Bez"]
         return df
 
     def tree_from_xml(self, struct, df):
         result = {}
-        for (s, cols) in struct.items():
+        for s, cols in struct.items():
             try:
                 tree = ET.parse(f"{self.config['path']}/Xml/{s}.xml")
                 result[s] = self.get_tree_root(tree.getroot(), s)
 
             except FileNotFoundError:
-                print('XML-Datei fehlt')
+                print("XML-Datei fehlt")
                 used_entries = [x.split(";")[1:] for x in set(df[s].to_numpy())]
                 print(used_entries)
-                root = ET.Element('Ebene')
-                root.set('Name', s)
+                root = ET.Element("Ebene")
+                root.set("Name", s)
                 result[s] = self.get_tree_root(root, s)
                 # self.json_result["tree"][s] = get_tree_from_accounts(cols, [])
         return result
 
     def get_structure_and_tree(self):
-        df = self.accounts_from_csv(self.config['struct'])
-        self.json_result['accounts'] = df.to_dict('records')
-        self.structure_ids = df.melt(id_vars=['Konto_Nr'], value_vars=self.config['struct'].keys(),
-                                     var_name='Struktur', value_name='id').groupby(by=['Struktur', 'id'])
-        self.json_result['tree'] = self.tree_from_xml(self.config['struct'], df)
-
-        for (s, cols) in self.config['struct'].items():
-            self.json_result['flat'][s] = get_flat(self.json_result['tree'][s])
-
-        for (s, entries) in self.json_result['flat'].items():
-            cols = self.config['struct'][s]
-            df_temp = pd.DataFrame([x['id'].split(';') for x in entries], columns=cols)
-            self.json_result['struct_export'][s] = df_temp.to_dict(orient='records')
+        df = self.accounts_from_csv(self.config["struct"])
+        self.json_result["accounts"] = df.to_dict("records")
+        self.structure_ids = df.melt(
+            id_vars=["Konto_Nr"],
+            value_vars=self.config["struct"].keys(),
+            var_name="Struktur",
+            value_name="id",
+        ).groupby(by=["Struktur", "id"])
+        self.json_result["tree"] = self.tree_from_xml(self.config["struct"], df)
+
+        for s, cols in self.config["struct"].items():
+            self.json_result["flat"][s] = get_flat(self.json_result["tree"][s])
+
+        for s, entries in self.json_result["flat"].items():
+            cols = self.config["struct"][s]
+            df_temp = pd.DataFrame([x["id"].split(";") for x in entries], columns=cols)
+            self.json_result["struct_export"][s] = df_temp.to_dict(orient="records")
 
         # {'accounts': {}, 'tree': {}, 'flat': {}, 'struct_export': {}, 'skr51_vars': {}}
-        json.dump(self.json_result, open(f"{self.config['path2']}/{self.config['output']}", 'w'), indent=2)
+        json.dump(
+            self.json_result,
+            open(f"{self.config['path2']}/{self.config['output']}", "w"),
+            indent=2,
+        )
         return self.json_result
 
     def get_accounts(self, structure, id):
-        return [x['Konto_Nr'] for x in self.json_result['accounts'] if x[structure] == id]
+        return [
+            x["Konto_Nr"] for x in self.json_result["accounts"] if x[structure] == id
+        ]
         # return []
         # res = self.structure_ids.groups.get((structure, id))
         # if res is None:
@@ -215,310 +306,544 @@ class GCStruct():
         # return res.values
 
     def export(self):
-        for s in self.config['export'].keys():
-            for (filetype, filename) in self.config['export'][s]['files'].items():
-                with open(self.config['path2'] + '/' + filename, 'w') as fwh:
-                    fwh.write('Konto_Nr_Hersteller;Konto_Nr_Split;Konto_Nr_Haendler;Info\n')
+        for s in self.config["export"].keys():
+            for filetype, filename in self.config["export"][s]["files"].items():
+                with open(self.config["path2"] + "/" + filename, "w") as fwh:
+                    fwh.write(
+                        "Konto_Nr_Hersteller;Konto_Nr_Split;Konto_Nr_Haendler;Info\n"
+                    )
                     # 'Hersteller'Konto_Nr;Konto_Bezeichnung;Case;Info'
-                    for a in self.json_result['accounts']:
-                        if a['Herstellerkonto_Nr'] != '':
-                            account = chevron.render(self.config['export']['SKR51']['format']['HerstellerkontoFormat'], a)
-                            fwh.write(account + ';' + account + ';' + a['Konto_Nr'] + ';' + '\n')   # a['Herstellerkonto_Bez']
+                    for a in self.json_result["accounts"]:
+                        if a["Herstellerkonto_Nr"] != "":
+                            account = chevron.render(
+                                self.config["export"]["SKR51"]["format"][
+                                    "HerstellerkontoFormat"
+                                ],
+                                a,
+                            )
+                            fwh.write(
+                                account
+                                + ";"
+                                + account
+                                + ";"
+                                + a["Konto_Nr"]
+                                + ";"
+                                + "\n"
+                            )  # a['Herstellerkonto_Bez']
 
     def get_tree(self, node, parents, structure):
         result = []
         for child in node:
             p = get_parents_list(parents)
-            parents.append(child.attrib['Name'])
-            id = ';'.join(parents) + ';' * (10 - len(parents))
-            result.append({
-                'id': id,
-                'text': child.attrib['Name'],
-                'children': self.get_tree(child, parents, structure),
-                'parents': p,
-                'accounts': self.get_accounts(structure, id),
-                'level': len(parents),
-                'form': child.attrib.get('Split', '')
-            })
+            parents.append(child.attrib["Name"])
+            id = ";".join(parents) + ";" * (10 - len(parents))
+            result.append(
+                {
+                    "id": id,
+                    "text": child.attrib["Name"],
+                    "children": self.get_tree(child, parents, structure),
+                    "parents": p,
+                    "accounts": self.get_accounts(structure, id),
+                    "level": len(parents),
+                    "form": child.attrib.get("Split", ""),
+                }
+            )
             parents.pop()
         return result
 
     def get_tree_root(self, node, structure):
-        id = ';' * 9
+        id = ";" * 9
         return {
-            'id': id,
-            'text': node.attrib['Name'],
-            'children': self.get_tree(node, [], structure),
-            'parents': [],
-            'accounts': [],
-            'level': 0,
-            'form': ''
+            "id": id,
+            "text": node.attrib["Name"],
+            "children": self.get_tree(node, [], structure),
+            "parents": [],
+            "accounts": [],
+            "level": 0,
+            "form": "",
         }
 
     def post_structure_and_tree(self):
-        json_post = json.load(open(f"{self.config['path']}/{self.config['output']}", 'r'))
+        json_post = json.load(
+            open(f"{self.config['path']}/{self.config['output']}", "r")
+        )
 
         # Kontenrahmen.csv
-        ebenen = ['Ebene' + str(i) for i in range(1, len(self.config['default']) * 10 + 1)]
-        header = ';'.join(self.config['columns'] + ebenen)
-        cols = self.config['columns'] + self.config['default']
-        with open(self.config['path'] + '/Kontenrahmen/Kontenrahmen_out.csv', 'w', encoding='latin-1') as f:
-            f.write(header + '\n')
-            for row in json_post['Kontenrahmen']:
-                f.write(';'.join([row[e] for e in cols]) + '\n')
+        ebenen = [
+            "Ebene" + str(i) for i in range(1, len(self.config["default"]) * 10 + 1)
+        ]
+        header = ";".join(self.config["columns"] + ebenen)
+        cols = self.config["columns"] + self.config["default"]
+        with open(
+            self.config["path"] + "/Kontenrahmen/Kontenrahmen_out.csv",
+            "w",
+            encoding="latin-1",
+        ) as f:
+            f.write(header + "\n")
+            for row in json_post["Kontenrahmen"]:
+                f.write(";".join([row[e] for e in cols]) + "\n")
         # print(header)
         # xml und evtl. Struktur.csv
-        for i, s in enumerate(self.config['default']):
-            with open(f"{self.config['path']}/Strukturen/Kontenrahmen.csv/{s}_out.csv", 'w', encoding='latin-1') as f:
-                f.write(';'.join(['Ebene' + str(i * 10 + j) for j in range(1, 11)]) + '\n')
-                rows = structure_from_tree({'id': ";" * 9, 'children': json_post[s]})
-                f.write('\n'.join(rows))
+        for i, s in enumerate(self.config["default"]):
+            with open(
+                f"{self.config['path']}/Strukturen/Kontenrahmen.csv/{s}_out.csv",
+                "w",
+                encoding="latin-1",
+            ) as f:
+                f.write(
+                    ";".join(["Ebene" + str(i * 10 + j) for j in range(1, 11)]) + "\n"
+                )
+                rows = structure_from_tree({"id": ";" * 9, "children": json_post[s]})
+                f.write("\n".join(rows))
 
             # with open(self.config['path'] + "/Strukturen/Kontenrahmen.csv/" + structure + "_2.csv", "w", encoding="latin-1") as f:
-            root = ET.Element('Ebene')
-            root.set('Name', s)
-            xml_from_tree(root, {'id': ";" * 9, 'children': json_post[s]})
+            root = ET.Element("Ebene")
+            root.set("Name", s)
+            xml_from_tree(root, {"id": ";" * 9, "children": json_post[s]})
 
-            with open(f"{self.config['path']}/Xml/{s}_out.xml", 'w', encoding='utf-8') as f:
-                f.write(BeautifulSoup(ET.tostring(root), 'xml').prettify())
+            with open(
+                f"{self.config['path']}/Xml/{s}_out.xml", "w", encoding="utf-8"
+            ) as f:
+                f.write(BeautifulSoup(ET.tostring(root), "xml").prettify())
 
     def skr51_translate(self, accounts_combined_files):
-        df = self.accounts_from_csv(self.config['struct'])
+        df = self.accounts_from_csv(self.config["struct"])
 
         df_translate = {}
         for i, (t_from, t_to) in enumerate(self.translate.items()):
-            last = 'LetzteEbene' + str(i + 1)
-            from_label = ['Konto_Nr', last, last + '_Nr', last + '_Bez', 'Ebene' + str(i * 10 + 1), 'Ebene' + str(i * 10 + 2)]
-            to_label = [t_to, t_to + '_Ebene', t_to + '_Nr', t_to + '_Bez', 'Ebene1', 'Ebene2']
-            df_translate[t_from] = df[df[last + '_Nr'] != ''][from_label].rename(columns=dict(zip(from_label, to_label)))
+            last = "LetzteEbene" + str(i + 1)
+            from_label = [
+                "Konto_Nr",
+                last,
+                last + "_Nr",
+                last + "_Bez",
+                "Ebene" + str(i * 10 + 1),
+                "Ebene" + str(i * 10 + 2),
+            ]
+            to_label = [
+                t_to,
+                t_to + "_Ebene",
+                t_to + "_Nr",
+                t_to + "_Bez",
+                "Ebene1",
+                "Ebene2",
+            ]
+            df_translate[t_from] = df[df[last + "_Nr"] != ""][from_label].rename(
+                columns=dict(zip(from_label, to_label))
+            )
             # print(df_translate[t_to].head())
 
         df2 = []
         for ac_file in accounts_combined_files:
-            df2.append(pd.read_csv(ac_file, decimal=',', sep=';', encoding='latin-1',
-                                   converters={i: str for i in range(0, 200)}))
+            df2.append(
+                pd.read_csv(
+                    ac_file,
+                    decimal=",",
+                    sep=";",
+                    encoding="latin-1",
+                    converters={i: str for i in range(0, 200)},
+                )
+            )
         df_source = pd.concat(df2)
         df3 = df_source.copy()
-        df3['Konto_Nr'] = df3['Konto_Nr'] + '_STK'
+        df3["Konto_Nr"] = df3["Konto_Nr"] + "_STK"
         df_source = pd.concat([df_source, df3])
 
         for t_from, t_to in self.translate.items():
-            if t_to == 'SKR51':
-                df_source['SKR51'] = df_source['Konto_Nr']
-            elif t_from in ['Marke_HBV']:
-                df_source['Marke_HBV'] = df_source['Marke']
-            elif t_from in ['Standort_HBV']:
-                df_source['Standort_HBV'] = df_source['Standort'] + '_' + df_source['Marke']
-                df_source['BMC'] = 'BMC_' + df_source['Standort_HBV']
-            elif t_to == 'KTR':
-                df_source['KTR'] = np.where(df_source['Kostenträger_Quelle'] == 'TZ', 'KTR_TZ_' + df_source['Kostenträger'], 'KTR_00')
-                df_source['KTR'] = np.where(df_source['Kostenträger_Quelle'].isin(['NW', 'SC']), 'KTR_' + df_source['Kostenträger_Quelle'] +
-                                            '_' + df_source['Marke'] + '_' + df_source['Kostenträger'], df_source['KTR'])
+            if t_to == "SKR51":
+                df_source["SKR51"] = df_source["Konto_Nr"]
+            elif t_from in ["Marke_HBV"]:
+                df_source["Marke_HBV"] = df_source["Marke"]
+            elif t_from in ["Standort_HBV"]:
+                df_source["Standort_HBV"] = (
+                    df_source["Standort"] + "_" + df_source["Marke"]
+                )
+                df_source["BMC"] = "BMC_" + df_source["Standort_HBV"]
+            elif t_to == "KTR":
+                df_source["KTR"] = np.where(
+                    df_source["Kostenträger_Quelle"] == "TZ",
+                    "KTR_TZ_" + df_source["Kostenträger"],
+                    "KTR_00",
+                )
+                df_source["KTR"] = np.where(
+                    df_source["Kostenträger_Quelle"].isin(["NW", "SC"]),
+                    "KTR_"
+                    + df_source["Kostenträger_Quelle"]
+                    + "_"
+                    + df_source["Marke"]
+                    + "_"
+                    + df_source["Kostenträger"],
+                    df_source["KTR"],
+                )
             else:
-                df_source[t_to] = t_to + '_' + df_source[t_from]
-            df_source = df_source.merge(df_translate[t_from], how='left', on=[t_to], suffixes=(None, '_' + t_to))
-            df_source[t_to + '_Nr'] = np.where(df_source[t_to + '_Nr'].isna(), df_source[t_from], df_source[t_to + '_Nr'])
-
-        df_source['Konto_Nr_SKR51'] = df_source['MAR_Nr'] + '-' + df_source['STA_Nr'] + '-' + df_source['SKR51_Nr'] + '-' + \
-            df_source['KST_Nr'] + '-' + df_source['ABS_Nr'] + '-' + df_source['KTR_Nr']
-        df_source['Konto_Nr_Händler'] = df_source['Marke'] + '-' + df_source['Standort'] + '-' + df_source['Konto_Nr'] + '-' + \
-            df_source['Kostenstelle'] + '-' + df_source['Absatzkanal'] + '-' + df_source['Kostenträger']
+                df_source[t_to] = t_to + "_" + df_source[t_from]
+            df_source = df_source.merge(
+                df_translate[t_from], how="left", on=[t_to], suffixes=(None, "_" + t_to)
+            )
+            df_source[t_to + "_Nr"] = np.where(
+                df_source[t_to + "_Nr"].isna(),
+                df_source[t_from],
+                df_source[t_to + "_Nr"],
+            )
+
+        df_source["Konto_Nr_SKR51"] = (
+            df_source["MAR_Nr"]
+            + "-"
+            + df_source["STA_Nr"]
+            + "-"
+            + df_source["SKR51_Nr"]
+            + "-"
+            + df_source["KST_Nr"]
+            + "-"
+            + df_source["ABS_Nr"]
+            + "-"
+            + df_source["KTR_Nr"]
+        )
+        df_source["Konto_Nr_Händler"] = (
+            df_source["Marke"]
+            + "-"
+            + df_source["Standort"]
+            + "-"
+            + df_source["Konto_Nr"]
+            + "-"
+            + df_source["Kostenstelle"]
+            + "-"
+            + df_source["Absatzkanal"]
+            + "-"
+            + df_source["Kostenträger"]
+        )
         # df_source.to_csv(f"{self.config['path2']}/SKR51_Uebersetzung.csv", sep=';', encoding='latin-1', index=False)
-        df_source['MAR_Nr_MAR'] = np.where(df_source['MAR_Nr_MAR'].isna(), '0000', df_source['MAR_Nr_MAR'])
-        from_label = ['MAR_Nr', 'STA_Nr', 'SKR51_Nr', 'KST_Nr', 'ABS_Nr', 'KTR_Nr', 'KTR_Ebene', 'Konto_Nr_Händler',
-                      'Konto_Nr_SKR51', 'MAR_Nr_MAR', 'BMC_Nr']
-        to_label = ['Marke', 'Standort', 'Konto_Nr', 'Kostenstelle', 'Absatzkanal', 'Kostenträger',
-                    'Kostenträger_Ebene', 'Konto_Nr_Händler', 'Konto_Nr_SKR51', 'Marke_HBV', 'Standort_HBV']
-        df_combined = df_source[from_label].rename(columns=dict(zip(from_label, to_label)))
-        df_combined.to_csv(f"{self.config['path2']}/Kontenrahmen_uebersetzt.csv", sep=';', encoding='latin-1', index=False)
+        df_source["MAR_Nr_MAR"] = np.where(
+            df_source["MAR_Nr_MAR"].isna(), "0000", df_source["MAR_Nr_MAR"]
+        )
+        from_label = [
+            "MAR_Nr",
+            "STA_Nr",
+            "SKR51_Nr",
+            "KST_Nr",
+            "ABS_Nr",
+            "KTR_Nr",
+            "KTR_Ebene",
+            "Konto_Nr_Händler",
+            "Konto_Nr_SKR51",
+            "MAR_Nr_MAR",
+            "BMC_Nr",
+        ]
+        to_label = [
+            "Marke",
+            "Standort",
+            "Konto_Nr",
+            "Kostenstelle",
+            "Absatzkanal",
+            "Kostenträger",
+            "Kostenträger_Ebene",
+            "Konto_Nr_Händler",
+            "Konto_Nr_SKR51",
+            "Marke_HBV",
+            "Standort_HBV",
+        ]
+        df_combined = df_source[from_label].rename(
+            columns=dict(zip(from_label, to_label))
+        )
+        df_combined.to_csv(
+            f"{self.config['path2']}/Kontenrahmen_uebersetzt.csv",
+            sep=";",
+            encoding="latin-1",
+            index=False,
+        )
 
     def skr51_translate2(self, accounts_combined_file):
-        df = self.accounts_from_csv(self.config['struct'])
+        df = self.accounts_from_csv(self.config["struct"])
 
         df_list = []
-        for i, s in enumerate(self.config['struct'].keys()):
-            from_label = ['Konto_Nr', 'Ebene' + str(i * 10 + 1), 'Ebene' + str(i * 10 + 2), 'Ebene' + str(i * 10 + 3)]
-            to_label = ['Konto_Nr', 'key', 'value', 'value2']
+        for i, s in enumerate(self.config["struct"].keys()):
+            from_label = [
+                "Konto_Nr",
+                "Ebene" + str(i * 10 + 1),
+                "Ebene" + str(i * 10 + 2),
+                "Ebene" + str(i * 10 + 3),
+            ]
+            to_label = ["Konto_Nr", "key", "value", "value2"]
             df_temp = df[from_label].rename(columns=dict(zip(from_label, to_label)))
-            df_temp['key'] = '{' + s + '/' + df_temp['key'] + '}'
-            df_list.append(df_temp[df_temp['value'] != ''])
+            df_temp["key"] = "{" + s + "/" + df_temp["key"] + "}"
+            df_list.append(df_temp[df_temp["value"] != ""])
         df_translate = pd.concat(df_list)
 
         # df_translate.to_csv(f"{self.config['path2']}/SKR51_Variablen.csv", sep=';', encoding='latin-1', index=False)
 
-        df_source = pd.read_csv(accounts_combined_file, decimal=',', sep=';', encoding='latin-1',
-                                converters={i: str for i in range(0, 200)})
-        df_source = df_source[df_source['Konto_Nr'].str.contains('_STK') == False]
-        df_source['Konto_Nr_Gesamt'] = df_source['Konto_Nr']
-        df_source['Konto_Nr'] = np.where(df_source['Konto_Nr'].str.contains(r'^[4578]'), df_source['Konto_Nr'] + '_' +
-                                         df_source['Kostenstelle'].str.slice(stop=1), df_source['Konto_Nr'])
-        df_source['Konto_Nr'] = np.where(df_source['Konto_Nr'].str.contains(r'^5\d+_4'), df_source['Konto_Nr'] +
-                                         df_source['Kostenstelle'].str.slice(start=1, stop=2), df_source['Konto_Nr'])
-
-        df_source = df_source.merge(df, how='left', on=['Konto_Nr'])
+        df_source = pd.read_csv(
+            accounts_combined_file,
+            decimal=",",
+            sep=";",
+            encoding="latin-1",
+            converters={i: str for i in range(0, 200)},
+        )
+        df_source = df_source[df_source["Konto_Nr"].str.contains("_STK") == False]
+        df_source["Konto_Nr_Gesamt"] = df_source["Konto_Nr"]
+        df_source["Konto_Nr"] = np.where(
+            df_source["Konto_Nr"].str.contains(r"^[4578]"),
+            df_source["Konto_Nr"] + "_" + df_source["Kostenstelle"].str.slice(stop=1),
+            df_source["Konto_Nr"],
+        )
+        df_source["Konto_Nr"] = np.where(
+            df_source["Konto_Nr"].str.contains(r"^5\d+_4"),
+            df_source["Konto_Nr"]
+            + df_source["Kostenstelle"].str.slice(start=1, stop=2),
+            df_source["Konto_Nr"],
+        )
+
+        df_source = df_source.merge(df, how="left", on=["Konto_Nr"])
         # rows = df_source.shape[0]
-        df_source['value'] = ''
+        df_source["value"] = ""
 
         cols = get_default_cols(0)
         for t_from, t_to in self.translate.items():
-            if t_from in ['Marke_HBV', 'Standort_HBV']:
+            if t_from in ["Marke_HBV", "Standort_HBV"]:
                 continue
-            if t_from == 'Konto_Nr':
+            if t_from == "Konto_Nr":
                 df_source[t_to] = df_source[t_from]
             else:
-                df_source[t_to] = t_to + '_' + df_source[t_from]
+                df_source[t_to] = t_to + "_" + df_source[t_from]
             for e in cols:
-                df_source = df_source.merge(df_translate, how='left', left_on=[t_to, e], right_on=['Konto_Nr', 'key'],
-                                            suffixes=(None, '_' + t_to + '_' + e))
-                df_source[e] = np.where(df_source['value_' + t_to + '_' + e].notna(), df_source['value_' + t_to + '_' + e], df_source[e])
+                df_source = df_source.merge(
+                    df_translate,
+                    how="left",
+                    left_on=[t_to, e],
+                    right_on=["Konto_Nr", "key"],
+                    suffixes=(None, "_" + t_to + "_" + e),
+                )
+                df_source[e] = np.where(
+                    df_source["value_" + t_to + "_" + e].notna(),
+                    df_source["value_" + t_to + "_" + e],
+                    df_source[e],
+                )
                 # if df_source.shape[0] > rows:
                 #     print(t_to + '_' + e + ': ' + str(df_source.shape[0]))
         # df_source.to_csv(f"{self.config['path2']}/SKR51_Variablen2.csv", sep=';', encoding='latin-1', index=False)
         # df_source[t_to + '_Nr'] = np.where(df_source[t_to + '_Nr'].isna(), df_source[t_from], df_source[t_to + '_Nr'])
         for e in cols:
-            df_source[e] = np.where(df_source[e].str.startswith('{'), df_source[e].str.extract(r'\/(.*)}', expand=False) +
-                                    ' falsch', df_source[e])    # df_source[e].str.extract(r'/(.*)}') +
-            df_source[e] = np.where(df_source[e] == '[KTR]', df_source['Kostenträger_Ebene'], df_source[e])
+            df_source[e] = np.where(
+                df_source[e].str.startswith("{"),
+                df_source[e].str.extract(r"\/(.*)}", expand=False) + " falsch",
+                df_source[e],
+            )  # df_source[e].str.extract(r'/(.*)}') +
+            df_source[e] = np.where(
+                df_source[e] == "[KTR]", df_source["Kostenträger_Ebene"], df_source[e]
+            )
         # df_all[df_all['Ebene1'] == ]
         # print(df_source.head())
-        df_source['Konto_neu'] = df_source['Marke'] + '-' + df_source['Standort'] + '-' + df_source['Konto_Nr'] + '-' + \
-            df_source['Kostenstelle'] + '-' + df_source['Absatzkanal'] + '-' + df_source['Kostenträger'] + ' - ' + \
-            df_source['Konto_Bezeichnung']
-        df_source['Ebene1_empty'] = df_source['Ebene1'].isna()    # , df_source['Ebene1'].map(lambda x: x == ''))
-        df_source['Konto_neu'] = np.where(df_source['Ebene1_empty'], 'keine Zuordnung', df_source['Konto_neu'])
-        df_source['Ebene1'] = np.where(df_source['Ebene1_empty'], 'keine Zuordnung', df_source['Ebene1'])
-        df_source['Konto_Gruppe'] = df_source['Konto_Nr'] + ' - ' + df_source['Konto_Bezeichnung']
-        df_source['Konto_Gruppe'] = np.where(df_source['Ebene1_empty'], 'keine Zuordnung', df_source['Konto_Gruppe'])
-        df_source['Konto_Gesamt'] = df_source['Konto_Nr_Gesamt'] + ' - ' + df_source['Konto_Bezeichnung']
-
-        df_amount = df_source[df_source['Ebene1'] == 'Umsatzerlöse'].reset_index()
-        df_amount['Ebene1'] = 'verkaufte Stückzahlen'
-        df_amount['Ebene72'] = 'verkaufte Stückzahlen'
-        df_amount['Konto_neu'] = 'STK ' + df_amount['Konto_neu']
-        df_amount['Konto_Nr_Händler'] = df_amount['Konto_Nr_Händler'] + '_STK'
-        df_amount['Konto_Gruppe'] = 'STK ' + df_amount['Konto_Gruppe']
-        df_amount['Konto_Gesamt'] = 'STK ' + df_amount['Konto_Gesamt']
+        df_source["Konto_neu"] = (
+            df_source["Marke"]
+            + "-"
+            + df_source["Standort"]
+            + "-"
+            + df_source["Konto_Nr"]
+            + "-"
+            + df_source["Kostenstelle"]
+            + "-"
+            + df_source["Absatzkanal"]
+            + "-"
+            + df_source["Kostenträger"]
+            + " - "
+            + df_source["Konto_Bezeichnung"]
+        )
+        df_source["Ebene1_empty"] = df_source[
+            "Ebene1"
+        ].isna()  # , df_source['Ebene1'].map(lambda x: x == ''))
+        df_source["Konto_neu"] = np.where(
+            df_source["Ebene1_empty"], "keine Zuordnung", df_source["Konto_neu"]
+        )
+        df_source["Ebene1"] = np.where(
+            df_source["Ebene1_empty"], "keine Zuordnung", df_source["Ebene1"]
+        )
+        df_source["Konto_Gruppe"] = (
+            df_source["Konto_Nr"] + " - " + df_source["Konto_Bezeichnung"]
+        )
+        df_source["Konto_Gruppe"] = np.where(
+            df_source["Ebene1_empty"], "keine Zuordnung", df_source["Konto_Gruppe"]
+        )
+        df_source["Konto_Gesamt"] = (
+            df_source["Konto_Nr_Gesamt"] + " - " + df_source["Konto_Bezeichnung"]
+        )
+
+        df_amount = df_source[df_source["Ebene1"] == "Umsatzerlöse"].reset_index()
+        df_amount["Ebene1"] = "verkaufte Stückzahlen"
+        df_amount["Ebene72"] = "verkaufte Stückzahlen"
+        df_amount["Konto_neu"] = "STK " + df_amount["Konto_neu"]
+        df_amount["Konto_Nr_Händler"] = df_amount["Konto_Nr_Händler"] + "_STK"
+        df_amount["Konto_Gruppe"] = "STK " + df_amount["Konto_Gruppe"]
+        df_amount["Konto_Gesamt"] = "STK " + df_amount["Konto_Gesamt"]
 
         df_source = pd.concat([df_source, df_amount])
 
-        df_source['GuV'] = (df_source['Ebene71'] == 'GuV')
-        df_source['Ebene81'] = np.where(df_source['GuV'], df_source['Ebene72'], 'Bilanz')
-        df_source['Ebene82'] = np.where(df_source['GuV'], df_source['Ebene73'], '')
-        df_source['Ebene83'] = np.where(df_source['GuV'], df_source['Ebene74'], '')
-        df_source['Ebene84'] = np.where(df_source['GuV'], df_source['Ebene75'], '')
-        df_source['Ebene85'] = np.where(df_source['GuV'], df_source['Ebene76'], '')
-        df_source['Ebene86'] = np.where(df_source['GuV'], df_source['Ebene77'], '')
-        df_source['Ebene87'] = np.where(df_source['GuV'], df_source['Ebene78'], '')
-        df_source['Ebene88'] = np.where(df_source['GuV'], df_source['Ebene79'], '')
-        df_source['Ebene89'] = np.where(df_source['GuV'], df_source['Ebene80'], '')
-        df_source['Ebene90'] = ''
-        df_source['Ebene71'] = np.where(df_source['GuV'], 'GuV', df_source['Ebene72'])
-        df_source['Ebene72'] = np.where(df_source['GuV'], '', df_source['Ebene73'])
-        df_source['Ebene73'] = np.where(df_source['GuV'], '', df_source['Ebene74'])
-        df_source['Ebene74'] = np.where(df_source['GuV'], '', df_source['Ebene75'])
-        df_source['Ebene75'] = np.where(df_source['GuV'], '', df_source['Ebene76'])
-        df_source['Ebene76'] = np.where(df_source['GuV'], '', df_source['Ebene77'])
-        df_source['Ebene77'] = np.where(df_source['GuV'], '', df_source['Ebene78'])
-        df_source['Ebene78'] = np.where(df_source['GuV'], '', df_source['Ebene79'])
-        df_source['Ebene79'] = np.where(df_source['GuV'], '', df_source['Ebene80'])
-        df_source['Ebene80'] = ''
-        df_source['Susa'] = df_source['Konto_Gruppe'].str.slice(stop=1)
-        df_source['Konto_KST'] = ''
-        df_source['GuV_Bilanz'] = df_source['Konto_Art']
-
-        from_label = ['Konto_neu', 'Konto_Nr_Händler']
-        to_label = ['Konto', 'Acct_Nr']
+        df_source["GuV"] = df_source["Ebene71"] == "GuV"
+        df_source["Ebene81"] = np.where(
+            df_source["GuV"], df_source["Ebene72"], "Bilanz"
+        )
+        df_source["Ebene82"] = np.where(df_source["GuV"], df_source["Ebene73"], "")
+        df_source["Ebene83"] = np.where(df_source["GuV"], df_source["Ebene74"], "")
+        df_source["Ebene84"] = np.where(df_source["GuV"], df_source["Ebene75"], "")
+        df_source["Ebene85"] = np.where(df_source["GuV"], df_source["Ebene76"], "")
+        df_source["Ebene86"] = np.where(df_source["GuV"], df_source["Ebene77"], "")
+        df_source["Ebene87"] = np.where(df_source["GuV"], df_source["Ebene78"], "")
+        df_source["Ebene88"] = np.where(df_source["GuV"], df_source["Ebene79"], "")
+        df_source["Ebene89"] = np.where(df_source["GuV"], df_source["Ebene80"], "")
+        df_source["Ebene90"] = ""
+        df_source["Ebene71"] = np.where(df_source["GuV"], "GuV", df_source["Ebene72"])
+        df_source["Ebene72"] = np.where(df_source["GuV"], "", df_source["Ebene73"])
+        df_source["Ebene73"] = np.where(df_source["GuV"], "", df_source["Ebene74"])
+        df_source["Ebene74"] = np.where(df_source["GuV"], "", df_source["Ebene75"])
+        df_source["Ebene75"] = np.where(df_source["GuV"], "", df_source["Ebene76"])
+        df_source["Ebene76"] = np.where(df_source["GuV"], "", df_source["Ebene77"])
+        df_source["Ebene77"] = np.where(df_source["GuV"], "", df_source["Ebene78"])
+        df_source["Ebene78"] = np.where(df_source["GuV"], "", df_source["Ebene79"])
+        df_source["Ebene79"] = np.where(df_source["GuV"], "", df_source["Ebene80"])
+        df_source["Ebene80"] = ""
+        df_source["Susa"] = df_source["Konto_Gruppe"].str.slice(stop=1)
+        df_source["Konto_KST"] = ""
+        df_source["GuV_Bilanz"] = df_source["Konto_Art"]
+
+        from_label = ["Konto_neu", "Konto_Nr_Händler"]
+        to_label = ["Konto", "Acct_Nr"]
 
         df_source = df_source.rename(columns=dict(zip(from_label, to_label)))
 
-        df_source = df_source[['Konto', 'Acct_Nr', 'Konto_Bezeichnung', 'GuV_Bilanz', 'Konto_KST', 'Konto_STK',
-                               'Konto_1', 'Konto_2', 'Konto_3', 'Konto_4', 'Konto_5'] +
-                              get_default_cols(0) + get_default_cols(7) + get_default_cols(8) +
-                              ['Konto_Gruppe', 'Konto_Nr_Gesamt', 'Konto_Gesamt', 'Susa']]
-        df_source.to_csv(f"{self.config['path2']}/SKR51_Uebersetzung.csv", sep=';', encoding='latin-1', index=False)
+        df_source = df_source[
+            [
+                "Konto",
+                "Acct_Nr",
+                "Konto_Bezeichnung",
+                "GuV_Bilanz",
+                "Konto_KST",
+                "Konto_STK",
+                "Konto_1",
+                "Konto_2",
+                "Konto_3",
+                "Konto_4",
+                "Konto_5",
+            ]
+            + get_default_cols(0)
+            + get_default_cols(7)
+            + get_default_cols(8)
+            + ["Konto_Gruppe", "Konto_Nr_Gesamt", "Konto_Gesamt", "Susa"]
+        ]
+        df_source.to_csv(
+            f"{self.config['path2']}/SKR51_Uebersetzung.csv",
+            sep=";",
+            encoding="latin-1",
+            index=False,
+        )
 
     def skr51_vars(self):
         self.get_structure_and_tree()
         cols = get_default_cols(0)
 
-        df_temp = pd.read_csv(f"{self.config['path']}/Export/Kostentraeger.csv", decimal=',', sep=';',
-                              encoding='latin-1', converters={i: str for i in range(0, 200)})
-        df_temp['value'] = df_temp['Ebene33']
-        df_temp['key'] = '[KTR]'
-        df_temp = df_temp[df_temp['value'].str.contains(' - ')]
-
-        df_list = [df_temp[['key', 'value']]]
-
-        for (s, entries) in self.json_result['flat'].items():
-            df = pd.DataFrame([x['id'].split(';') for x in entries], columns=cols)
-            df['key'] = df[cols[0]].apply(lambda x: '{' + s + '/' + x + '}')
-            df['value'] = df[cols[1]]
-            df_list.append(df[['key', 'value']])
+        df_temp = pd.read_csv(
+            f"{self.config['path']}/Export/Kostentraeger.csv",
+            decimal=",",
+            sep=";",
+            encoding="latin-1",
+            converters={i: str for i in range(0, 200)},
+        )
+        df_temp["value"] = df_temp["Ebene33"]
+        df_temp["key"] = "[KTR]"
+        df_temp = df_temp[df_temp["value"].str.contains(" - ")]
+
+        df_list = [df_temp[["key", "value"]]]
+
+        for s, entries in self.json_result["flat"].items():
+            df = pd.DataFrame([x["id"].split(";") for x in entries], columns=cols)
+            df["key"] = df[cols[0]].apply(lambda x: "{" + s + "/" + x + "}")
+            df["value"] = df[cols[1]]
+            df_list.append(df[["key", "value"]])
         df = pd.concat(df_list)
-        df_vars = df[df['value'] != '']
+        df_vars = df[df["value"] != ""]
         # df_vars.to_csv(f"{self.config['path2']}/SKR51_Variablen2.csv", sep=';', encoding='latin-1', index=False)
 
-        df_main = pd.DataFrame([x['id'].split(';') for x in self.json_result['flat']['SKR51']], columns=cols)
-        df_main['value'] = ''
+        df_main = pd.DataFrame(
+            [x["id"].split(";") for x in self.json_result["flat"]["SKR51"]],
+            columns=cols,
+        )
+        df_main["value"] = ""
         for c in cols:
-            df_main = df_main.merge(df_vars, how='left', left_on=c, right_on='key', suffixes=(None, '_' + c))
-            df_main[c] = np.where(df_main['value_' + c].isna(), df_main[c], df_main['value_' + c])
-
-        df_amount = df_main[df_main['Ebene1'] == 'Umsatzerlöse'].reset_index()
-        df_amount['Ebene1'] = 'verkaufte Stückzahlen'
+            df_main = df_main.merge(
+                df_vars, how="left", left_on=c, right_on="key", suffixes=(None, "_" + c)
+            )
+            df_main[c] = np.where(
+                df_main["value_" + c].isna(), df_main[c], df_main["value_" + c]
+            )
+
+        df_amount = df_main[df_main["Ebene1"] == "Umsatzerlöse"].reset_index()
+        df_amount["Ebene1"] = "verkaufte Stückzahlen"
         df_main = pd.concat([df_main, df_amount])
 
         # from_label = cols
-        to_label = cols   # get_default_cols(9)
+        to_label = cols  # get_default_cols(9)
         # df_main = df_main.rename(columns=dict(zip(from_label, to_label)))
-        df_main[to_label].to_csv(f"{self.config['path2']}/SKR51_Struktur.csv", sep=';', encoding='latin-1', index_label='Sortierung')
+        df_main[to_label].to_csv(
+            f"{self.config['path2']}/SKR51_Struktur.csv",
+            sep=";",
+            encoding="latin-1",
+            index_label="Sortierung",
+        )
 
 
-def gcstruct_uebersetzung():
+def gcstruct_uebersetzung(base_dir=None):
     # base_dir = 'P:/SKR51_GCStruct/'
-    base_dir = Path('.').absolute()
+    if base_dir is None:
+        base_dir = Path(".").absolute()
     import_dir = base_dir
-    if base_dir.name == 'scripts':
-        if base_dir.parent.parent.name == 'Portal':
+    if base_dir.name == "scripts":
+        if base_dir.parent.parent.name == "Portal":
             base_dir = base_dir.parent.parent.parent
-            import_dir = base_dir.joinpath('Portal/System/IQD/Belege/Kontenrahmen')
+            import_dir = base_dir.joinpath("Portal/System/IQD/Belege/Kontenrahmen")
         else:
             base_dir = base_dir.parent.parent
-            import_dir = base_dir.joinpath('System/OPTIMA/Export')
-    elif not base_dir.joinpath('GCStruct_Aufbereitung').exists():
-        base_dir = Path('//192.168.2.21/verwaltung/Kunden/Luchtenberg/1 Umstellung SKR51/')
+            import_dir = base_dir.joinpath("System/OPTIMA/Export")
+    elif not base_dir.joinpath("GCStruct_Aufbereitung").exists():
+        base_dir = Path(
+            "//192.168.2.21/verwaltung/Kunden/Luchtenberg/1 Umstellung SKR51/"
+        )
         if not base_dir.exists():
-            base_dir = Path('//media/fileserver1/verwaltung/Kunden/Luchtenberg/1 Umstellung SKR51/')
+            base_dir = Path(
+                "//media/fileserver1/verwaltung/Kunden/Luchtenberg/1 Umstellung SKR51/"
+            )
         import_dir = base_dir
 
-    struct = GCStruct(str(base_dir.joinpath('GCStruct_Aufbereitung')))
-    struct.skr51_translate(import_dir.glob('Kontenrahmen_kombiniert*.csv'))
-    print('Kontenrahmen_uebersetzt.csv erstellt.')
+    struct = GCStruct(str(base_dir.joinpath("GCStruct_Aufbereitung")))
+    struct.skr51_translate(import_dir.glob("Kontenrahmen_kombiniert*.csv"))
+    print("Kontenrahmen_uebersetzt.csv erstellt.")
     # copyfile('c:/Projekte/Python/Gcstruct/Kontenrahmen_kombiniert.csv', base_dir + 'GCStruct_Modell/Export/Kontenrahmen_kombiniert.csv')
 
-    struct2 = GCStruct(str(base_dir.joinpath('GCStruct_Modell')))
-    struct2.skr51_translate2(str(base_dir.joinpath('GCStruct_Aufbereitung/Export/Kontenrahmen_uebersetzt.csv')))
-    print('SKR51_Uebersetzung.csv erstellt.')
+    struct2 = GCStruct(str(base_dir.joinpath("GCStruct_Modell")))
+    struct2.skr51_translate2(
+        str(
+            base_dir.joinpath(
+                "GCStruct_Aufbereitung/Export/Kontenrahmen_uebersetzt.csv"
+            )
+        )
+    )
+    print("SKR51_Uebersetzung.csv erstellt.")
     struct2.skr51_vars()
-    print('SKR51_Struktur.csv erstellt.')
+    print("SKR51_Struktur.csv erstellt.")
 
 
 def dresen():
-    struct = GCStruct('c:/projekte/GCHRStruct_Hyundai_Export')
+    struct = GCStruct("c:/projekte/GCHRStruct_Hyundai_Export")
     struct.get_structure_and_tree()
     struct.export()
 
 
 def reisacher():
-    base_dir = 'X:/Robert/Planung Reisacher/GCStruct_neue_Struktur_Planung'
+    base_dir = "X:/Robert/Planung Reisacher/GCStruct_neue_Struktur_Planung"
     if not Path(base_dir).exists():
-        base_dir = '/media/fileserver1/austausch/Robert/Planung Reisacher/GCStruct_neue_Struktur_Planung'
+        base_dir = "/media/fileserver1/austausch/Robert/Planung Reisacher/GCStruct_neue_Struktur_Planung"
     struct = GCStruct(base_dir)
     struct.get_structure_and_tree()
     # json.dump(res['flat'], open(f"{self.config['path2']}/{self.config['output']}", 'w'), indent=2)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     # struct = GCStruct('c:/projekte/gcstruct_dresen')
     # struct = GCStruct('c:/projekte/python/gcstruct')
     # struct = GCStruct('c:/projekte/python/gcstruct_reisacher_planung')