cleared outputs

Nextcloud_Material/create_Bootsplätze_file.ipynb

@@ -0,0 +1,165 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f46948ac",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "import pandas as pd\n",
+    "from io import BytesIO"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3a1de802",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# --- Configuration ---\n",
+    "NEXTCLOUD_URL = \"https://nextcloud.karnelegger.eu\"\n",
+    "USERNAME = \"Georg Brantegger\"\n",
+    "with open('app_pw.txt','r') as f:\n",
+    "    APP_PASSWORD = f.readline()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1fdfef34",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# read list of boats\n",
+    "\n",
+    "FILE_PATH = \"Shared/Ruderverein/Material/Bootsliste.xlsx\"\n",
+    "\n",
+    "# Build the WebDAV URL\n",
+    "# Note: Path should be URL-encoded if it contains spaces or special characters\n",
+    "webdav_url = f\"{NEXTCLOUD_URL}/remote.php/dav/files/{USERNAME}/{FILE_PATH}\"\n",
+    "\n",
+    "# --- The Request ---\n",
+    "response = requests.get(webdav_url, auth=(USERNAME, APP_PASSWORD))\n",
+    "\n",
+    "if response.status_code == 200:\n",
+    "    # Use BytesIO to turn the raw binary content into a file-like object\n",
+    "    boats_df = pd.read_excel(BytesIO(response.content))\n",
+    "    print(\"File loaded successfully!\")\n",
+    "else:\n",
+    "    print(f\"Failed to fetch file. Status code: {response.status_code}\")\n",
+    "    print(response.text)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "80f97e18",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def analyse_class(row):\n",
+    "    boot_class = row['Bootsklasse']\n",
+    "\n",
+    "    number_seats = 0\n",
+    "    variable = False\n",
+    "\n",
+    "    for i in range(8+1):\n",
+    "        if str(i) in boot_class:\n",
+    "            number_seats = i\n",
+    "            break\n",
+    "    \n",
+    "    if '/' in boot_class:\n",
+    "        variable = True\n",
+    "\n",
+    "    return number_seats, variable\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "70fb2327",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "boats_df[['number_seats','variable']] = boats_df.apply(analyse_class,axis=1,result_type='expand')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bf18a0fd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "boat_names = []\n",
+    "variants = []\n",
+    "places = []\n",
+    "\n",
+    "for boat_name in df['Name'].unique():\n",
+    "    number_seats = df.loc[df['Name']==boat_name,'number_seats'].values[0]\n",
+    "    variable = df.loc[df['Name']==boat_name,'variable'].values[0]\n",
+    "\n",
+    "    if bool(variable) is False:\n",
+    "        for place in range(1,number_seats+1):\n",
+    "            boat_names.append(boat_name)\n",
+    "            variants.append(f\"{number_seats}x\")\n",
+    "            places.append(place)\n",
+    "    elif bool(variable) is True:\n",
+    "        for place in range(1,number_seats+1):\n",
+    "            boat_names.append(boat_name)\n",
+    "            variants.append(f\"{number_seats}x\")\n",
+    "            places.append(place)\n",
+    "        for place in range(1,number_seats+1):\n",
+    "            boat_names.append(boat_name)\n",
+    "            variants.append(f\"{number_seats}-\")\n",
+    "            places.append(place)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "85059518",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_dict = {'Bootsname':boat_names,'Trimmung':variants,'Bootsplatz':places,'Ruder-ID':[None for _ in boat_names]}\n",
+    "places_df = pd.DataFrame(data_dict)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3071bf52",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "places_df.to_excel('temp.xlsx')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}