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 news_research_Tim.ipynb

@@ -31,8 +31,9 @@
    "outputs": [],
    "source": [
     "import requests\n",
-    "url = 'https://www.tagesschau.de/api2/'\n",
-    "r = requests.get(url +'homepage')\n",
+    "\n",
+    "url = \"https://www.tagesschau.de/api2/\"\n",
+    "r = requests.get(url + \"homepage\")\n",
     "r = r.json()"
    ]
   },
@@ -76,10 +77,11 @@
    "source": [
     "# Aggregieren der Titel und Beschreibungen\n",
     "import pandas as pd\n",
+    "\n",
     "data = {\"titles\": [], \"description\": []}\n",
-    "for i in range(len(r[\"news\"])): \n",
-    " data[\"titles\"].append(r[\"news\"][i][\"title\"])\n",
-    " data[\"description\"].append(r[\"news\"][i][\"content\"][0][\"value\"])\n",
+    "for i in range(len(r[\"news\"])):\n",
+    "    data[\"titles\"].append(r[\"news\"][i][\"title\"])\n",
+    "    data[\"description\"].append(r[\"news\"][i][\"content\"][0][\"value\"])\n",
     "df = pd.DataFrame(data)\n",
     "print(df.__len__)"
    ]
@@ -19323,7 +19325,7 @@
     }
    ],
    "source": [
-    "r = requests.get(url +'news').json()\n",
+    "r = requests.get(url + \"news\").json()\n",
     "r"
    ]
   },
@@ -19355,8 +19357,8 @@
    ],
    "source": [
     "data = {\"titles\": []}\n",
-    "for i in range(len(r[\"news\"])): \n",
-    " data[\"titles\"].append(r[\"news\"][i][\"title\"])\n",
+    "for i in range(len(r[\"news\"])):\n",
+    "    data[\"titles\"].append(r[\"news\"][i][\"title\"])\n",
     "#  data[\"description\"].append(r[\"news\"][i][\"content\"][0][\"value\"])\n",
     "df = pd.DataFrame(data)\n",
     "print(df)"
@@ -19391,7 +19393,7 @@
    ],
    "source": [
     "date = \"230425\"\n",
-    "r = requests.get(url +'newsfeed-101~_date-{date}.json').json()\n",
+    "r = requests.get(url + \"newsfeed-101~_date-{date}.json\").json()\n",
     "r"
    ]
   },
@@ -19989,7 +19991,7 @@
     "pageSize = 5\n",
     "resultPage = 2\n",
     "print(url)\n",
-    "txt = f'search/?searchText={searchtxt}&pageSize={pageSize}&resultPage={resultPage}'\n",
+    "txt = f\"search/?searchText={searchtxt}&pageSize={pageSize}&resultPage={resultPage}\"\n",
     "r = requests.get(url + txt).json()\n",
     "r"
    ]

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()"
    ]