Executing black over all jupyter notebook (#190)

Reverting black for the jupyter notebooks gets old. Can we just run
black over all of them?

Jupyter/API-tests/API research_Tristan.ipynb

@@ -51,6 +51,7 @@
    ],
    "source": [
     "from deutschland.bundesanzeiger import Bundesanzeiger\n",
+    "\n",
     "ba = Bundesanzeiger()\n",
     "# search term\n",
     "data = ba.get_reports(\"Atos IT-Dienstleistung & Beratung GmbH\")\n",
@@ -73,11 +74,13 @@
    ],
    "source": [
     "# Note: There can be multiple \"Aufsichtsrat\" entries per Company, the API however does only return one because the keys are overwritten\n",
-    "jahresabschluss = data['Jahresabschluss zum Geschäftsjahr vom 01.01.2019 bis zum 31.12.2019']\n",
+    "jahresabschluss = data[\n",
+    "    \"Jahresabschluss zum Geschäftsjahr vom 01.01.2019 bis zum 31.12.2019\"\n",
+    "]\n",
     "\n",
     "# Note: Although the report includes the entire text it lacks the formatting that would make extracting information a lot easier as the data is wrapped inside a <table> originally\n",
     "with open(\"./jahresabschluss-example.txt\", \"w\") as file:\n",
-    "    file.write(jahresabschluss['report'])\n",
+    "    file.write(jahresabschluss[\"report\"])\n",
     "print(jahresabschluss.keys())"
    ]
   },
@@ -96,6 +99,7 @@
    ],
    "source": [
     "from deutschland.handelsregister import Handelsregister\n",
+    "\n",
     "hr = Handelsregister()\n",
     "\n",
     "results = hr.search(keywords=\"BLUECHILLED Verwaltungs GmbH\")\n",
@@ -128,6 +132,7 @@
    "source": [
     "# SQLite export\n",
     "import sqlite3\n",
+    "\n",
     "con = sqlite3.connect(\"../data/openregister.db\")"
    ]
   },
@@ -176,7 +181,7 @@
    ],
    "source": [
     "schema = cur.execute(\"SELECT name FROM sqlite_master WHERE type='table';\")\n",
-    "schema.fetchall()\n"
+    "schema.fetchall()"
    ]
   },
   {
@@ -414,6 +419,7 @@
    ],
    "source": [
     "import pandas as pd\n",
+    "\n",
     "df = pd.read_sql_query(\"SELECT * FROM company LIMIT 100\", con)\n",
     "df.head()"
    ]