{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1293f184",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "import requests\n",
    "import urllib\n",
    "import io\n",
    "import base64\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "import matplotlib.image as mpimg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2946897b",
   "metadata": {},
   "outputs": [],
   "source": [
    "for file in os.listdir('temp'):\n",
    "    os.remove(os.path.join('temp',file))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb57d754",
   "metadata": {},
   "outputs": [],
   "source": [
    "user = \"Georg Brantegger\"\n",
    "with open('app_pw.txt','r') as f:\n",
    "    app_pw = f.readline()\n",
    "\n",
    "\n",
    "base_url_csv = \"https://nextcloud.karnelegger.eu/remote.php/webdav\"\n",
    "folders = [\"Forms\",\"2 - Kontaktdatenerhebung Ruder-innen RV Villach\",\"Ergebnisse CSV\"]\n",
    "folder_string = '/'.join([urllib.parse.quote(folder) for folder in folders])\n",
    "filename_csv = \"Kontaktdatenerhebung Ruder-innen RV Villach (Antworten).csv\"\n",
    "\n",
    "url_csv = '/'.join([base_url_csv,folder_string,urllib.parse.quote(filename_csv)])\n",
    "\n",
    "\n",
    "r = requests.get(url_csv, auth=(user, app_pw))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "543d5103",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_tel(row,col):\n",
    "    # remove the first ' and all whitespaces within number\n",
    "\n",
    "    tel = str(row[col])\n",
    "\n",
    "    replace_dict = {\"'\":'',' ':''}\n",
    "    \n",
    "    for key, value in replace_dict.items():\n",
    "        tel = tel.replace(key,value)\n",
    "\n",
    "    # handle people who don't know how country codes work\n",
    "    if tel[0] == '0':\n",
    "        tel = '+43'+tel[1:]\n",
    "    if tel[0] == '6':\n",
    "        tel = '+43'+tel\n",
    "    if tel[0:4] == '+430':\n",
    "        tel = '+43'+tel[4:]\n",
    "    if tel[0:3] == '+49':\n",
    "        tel = '+43'+tel[3:]\n",
    "    if tel[0:2] == '43':\n",
    "        tel = '+43'+tel[2:]\n",
    "    if tel[0:2] == '+6':\n",
    "        tel = '+43'+tel[1:]\n",
    "        \n",
    "    return tel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a74d9129",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(io.StringIO(r.text))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ba590c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "name_replacement_dict = {',':'',\n",
    "                         'Christoph Spath-Glantschnig': 'Spath-Glantschnig Christoph',\n",
    "                         'Felix Assmann-Hafenscherer': 'Assmann-Hafenscherer Felix',\n",
    "                         'Elias Assmann': 'Assmann Elias',\n",
    "                         'Bernadette Assmann ': 'Assmann Bernadette',\n",
    "                         'Tropea Giuseppe Manfredi': 'Tropea Manfredi Giuseppe',\n",
    "                         'Sabrina': 'Bellotti Sabrina',\n",
    "                         'Ich bin 18': None,\n",
    "                         }\n",
    "\n",
    "df['Mein Name ist:'] = df['Mein Name ist:'].replace(name_replacement_dict,regex=True).str.strip()\n",
    "df['Name Kontaktperson/Kind 1'] = df['Name Kontaktperson/Kind 1'].replace(name_replacement_dict,regex=True).str.strip()\n",
    "df['Name Kontaktperson/Kind 2'] = df['Name Kontaktperson/Kind 2'].replace(name_replacement_dict,regex=True).str.strip()\n",
    "df['Name Kontaktperson/Kind 3'] = df['Name Kontaktperson/Kind 3'].replace(name_replacement_dict,regex=True).str.strip()\n",
    "\n",
    "df['Meine Telefonnummer ist:'] = df.apply(extract_tel,axis=1,args=('Meine Telefonnummer ist:',))\n",
    "df['Telefonnummer Kontaktperson 1'] = df.apply(extract_tel,axis=1,args=('Telefonnummer Kontaktperson 1',))\n",
    "df['Telefonnummer Kontaktperson 2'] = df.apply(extract_tel,axis=1,args=('Telefonnummer Kontaktperson 2',))\n",
    "df['Telefonnummer Kontaktperson 3'] = df.apply(extract_tel,axis=1,args=('Telefonnummer Kontaktperson 3',))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b664ba7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "58057da5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# manually fix_Felix row\n",
    "row = df.loc[df['Mein Name ist:'] == 'Hafenscherer Rita',:]\n",
    "row['Mein Name ist:'] = 'Assmann-Hafenscherer Felix'\n",
    "row['Ich bin:'] = 'Ruder:in'\n",
    "row['Meine Telefonnummer ist:'] = '+4367764409018'\n",
    "row['Name Kontaktperson/Kind 1'] = 'Hafenscherer Rita'\n",
    "row['Telefonnummer Kontaktperson 1'] = '+436509623400'\n",
    "df.loc[df['Mein Name ist:'] == 'Hafenscherer Rita',:] = row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "562a911b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fc8568d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "rowers_columns = ['Mein Name ist:',\n",
    "                'Mein Jahrgang ',\n",
    "                'Lade ein nettes Selfy hoch!',\n",
    "                'Meine Telefonnummer ist:',\n",
    "                'Name Kontaktperson/Kind 1',\n",
    "                'Telefonnummer Kontaktperson 1',\n",
    "                'Name Kontaktperson/Kind 2',\n",
    "                'Telefonnummer Kontaktperson 2',\n",
    "                'Name Kontaktperson/Kind 3',\n",
    "                'Telefonnummer Kontaktperson 3']\n",
    "\n",
    "rowers_dict = {key: [] for key in rowers_columns}\n",
    "\n",
    "parents_columns = ['Mein Name ist:',\n",
    "                'Lade ein nettes Selfy hoch!',\n",
    "                'Meine Telefonnummer ist:',\n",
    "                'Name Kontaktperson/Kind 1',\n",
    "                'Telefonnummer Kontaktperson 1',\n",
    "                'Name Kontaktperson/Kind 2',\n",
    "                'Telefonnummer Kontaktperson 2',\n",
    "                'Name Kontaktperson/Kind 3',\n",
    "                'Telefonnummer Kontaktperson 3']\n",
    "\n",
    "parents_dict = {key: [] for key in parents_columns}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d44beb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "for _,row in df.iterrows():\n",
    "    if (row['Ich bin:'] == 'Ruder:in') | (row['Mein Name ist:']=='Assmann-Hafenscherer Felix'):\n",
    "        for col in rowers_columns:\n",
    "            rowers_dict[col].append(row[col])\n",
    "            \n",
    "    elif row['Ich bin:'] == 'Elternteil/erwachsene Ansprechperson':\n",
    "        for col in parents_columns:\n",
    "            parents_dict[col].append(row[col])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "118dd1a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "rowers_df = pd.DataFrame(rowers_dict)\n",
    "parents_df = pd.DataFrame(parents_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1b7dd6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "rowers_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1e3f59d",
   "metadata": {},
   "outputs": [],
   "source": [
    "parents_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "df2c876c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# def get_photo_for_row(row):\n",
    "\n",
    "#     filename = row['Foto']\n",
    "\n",
    "#     found_photo = False\n",
    "#     i = 0\n",
    "#     while found_photo is False:\n",
    "#         print(f\"trying folder {i}\")\n",
    "#         base_url_photo = \"https://nextcloud.karnelegger.eu/remote.php/webdav\"\n",
    "#         folders = [\"Forms\",\"4 - Kontaktdatenerhebung Trainerteam\",f\"{i}\",\"19 - Foto\"]\n",
    "#         folder_string = '/'.join([urllib.parse.quote(folder) for folder in folders])\n",
    "#         filename_photo = urllib.parse.quote(filename)\n",
    "\n",
    "#         url_photo = '/'.join([base_url_photo,folder_string,urllib.parse.quote(filename_photo)])\n",
    "\n",
    "#         r = requests.get(url_photo, auth=(user, app_pw))\n",
    "#         if r.status_code != 200:\n",
    "#             i+=1\n",
    "#             if i > 100:\n",
    "#                 break\n",
    "#             continue\n",
    "#         else:\n",
    "#             photo_bytes = r.content\n",
    "#             found_photo = True\n",
    "#             photo_b64 = base64.b64encode(photo_bytes).decode(\"utf-8\")\n",
    "            \n",
    "#             i = base64.b64decode(photo_b64)\n",
    "#             i = io.BytesIO(i)\n",
    "#             i = mpimg.imread(i, format='JPG')\n",
    "\n",
    "#             plt.imshow(i, interpolation='nearest')\n",
    "#             plt.show()\n",
    "\n",
    "#             return photo_b64\n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c9db8d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# def convert_rows_to_vcf(row):\n",
    "#     # Map CSV columns to vCard fields\n",
    "#     first_name = row['Vorname']\n",
    "#     last_name = row['Nachname']\n",
    "#     phone = row['Telefonnummer']\n",
    "#     org = 'Ruderverein Villach von 1881'\n",
    "#     photo_b64 =  get_photo_for_row(row)\n",
    "    \n",
    "\n",
    "#     lines = [\n",
    "#         \"BEGIN:VCARD\",\n",
    "#         \"VERSION:3.0\",\n",
    "#         f\"FN:{first_name} {last_name}\",\n",
    "#         f\"N:{last_name};{first_name};;;\",\n",
    "#         f\"ORG:{org}\",\n",
    "#         f\"TEL;TYPE=CELL:{phone}\"]\n",
    "\n",
    "#     if photo_b64:\n",
    "#         lines.append(f\"PHOTO;ENCODING=b;TYPE=JPEG:{photo_b64}\")\n",
    "\n",
    "#     lines.append(\"END:VCARD\")\n",
    "\n",
    "#     vcard_content = \"\\n\".join(lines)\n",
    "\n",
    "#     # Save to file\n",
    "#     filename = f\"{last_name}_{first_name}.vcf\".replace(\" \", \"_\")\n",
    "#     with open(os.path.join('temp', filename), 'w') as f:\n",
    "#         f.write(vcard_content)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "61659f5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df.apply(convert_rows_to_vcf,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37b2a51b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# base_url = \"https://nextcloud.karnelegger.eu/remote.php/dav/addressbooks/users/Georg%20Brantegger/rv-villach-trainer/\"\n",
    "\n",
    "# for vcf_file in os.listdir('temp'):\n",
    "\n",
    "#     url = base_url + vcf_file\n",
    "\n",
    "#     with open(f'temp/{vcf_file}', \"rb\") as f:\n",
    "#         r = requests.put(\n",
    "#             url,\n",
    "#             data=f,\n",
    "#             auth=(user, app_pw),\n",
    "#             headers={\"Content-Type\": \"text/vcard\"}\n",
    "#         )\n",
    "\n",
    "#     print(vcf_file, r.status_code)"
   ]
  }
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