218 lines
6.7 KiB
Plaintext
218 lines
6.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 83,
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"id": "152c4ce0",
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"metadata": {},
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"outputs": [],
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"source": [
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"import requests\n",
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"import pandas as pd\n",
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"import datetime as dt\n",
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"import openpyxl.styles"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 84,
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"id": "041b0ab6",
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"metadata": {},
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"outputs": [],
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"source": [
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"# --- Configuration ---\n",
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"NEXTCLOUD_URL = \"https://nextcloud.karnelegger.eu\"\n",
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"USERNAME = \"Georg Brantegger\"\n",
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"with open('app_pw.txt','r') as f:\n",
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" APP_PASSWORD = f.readline()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 85,
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"id": "b4c04efb",
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"metadata": {},
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"outputs": [],
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"source": [
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"import requests\n",
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"import vobject\n",
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"\n",
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"\n",
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"# This is the \"URL slug\" of your address book. \n",
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"# Usually, if you name it \"Athletes\", the slug is \"athletes\" (lowercase).\n",
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"# You can find the exact name by going to Contacts -> Settings (bottom left) -> \n",
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"# Click the 3 dots next to your address book -> \"Copy link\". \n",
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"# The link will end with /addressbooks/users/username/THIS_PART/\n",
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"ADDRESSBOOK_NAME = \"rv-villach-athletinnen\" \n",
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"\n",
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"\n",
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"# The ?export parameter tells Nextcloud to dump the whole address book at once\n",
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"CARDDAV_URL = f\"{NEXTCLOUD_URL}/remote.php/dav/addressbooks/users/{USERNAME}/{ADDRESSBOOK_NAME}/?export\"\n",
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"\n",
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"def get_athlete_data():\n",
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" print(f\"Fetching contacts from the '{ADDRESSBOOK_NAME}' address book...\")\n",
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" response = requests.get(CARDDAV_URL, auth=(USERNAME, APP_PASSWORD))\n",
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" \n",
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" if response.status_code != 200:\n",
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" print(f\"❌ Error {response.status_code}: Could not fetch address book.\")\n",
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" print(\"Check your URL, credentials, and make sure the ADDRESSBOOK_NAME is exactly right.\")\n",
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" return []\n",
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"\n",
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" vcf_data = response.text\n",
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" first_names = []\n",
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" last_names = []\n",
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" genders = []\n",
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" years_of_birth = []\n",
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"\n",
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" # Parse the multi-contact VCF data\n",
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" for vcard in vobject.readComponents(vcf_data):\n",
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" # The 'n' property in a vCard holds the structured Name (First, Last, etc.)\n",
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" if hasattr(vcard, 'n'):\n",
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" first_name = vcard.n.value.given\n",
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" last_name = vcard.n.value.family\n",
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" \n",
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" first_names.append(first_name)\n",
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" last_names.append(last_name)\n",
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" else: print(vcard.fn.value)\n",
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" \n",
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" if hasattr(vcard, 'note'):\n",
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" [_,year_of_birth,gender] = vcard.note.value.split(' ')\n",
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" \n",
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" genders.append(gender)\n",
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" years_of_birth.append(int(year_of_birth))\n",
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" \n",
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" return last_names,first_names,genders,years_of_birth"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 86,
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"id": "3efe3bb1",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Fetching contacts from the 'rv-villach-athletinnen' address book...\n"
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]
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}
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],
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"source": [
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"a,b,c,d = get_athlete_data()\n",
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"data_dict = {'Nachname':a,'Vorname':b,'Gender':c,'Jahrgang':d}\n",
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"\n",
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"df = pd.DataFrame(data_dict)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 87,
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"id": "a65d7693",
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"metadata": {},
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"outputs": [],
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"source": [
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"def evaluate_class(row):\n",
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" gender = row['Gender']\n",
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" yob = row['Jahrgang']\n",
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" age = dt.datetime.now().year - yob\n",
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" \n",
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" if age <= 12:\n",
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" c1 = 'Sch'\n",
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" c2 = 'B'\n",
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" elif 12 < age <= 14:\n",
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" c1 = 'Sch'\n",
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" c2 = 'A'\n",
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" elif 14 < age <= 16:\n",
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" c1 = 'Jun'\n",
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" c2 = 'B'\n",
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" elif 16 < age <= 18:\n",
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" c1 = 'Jun'\n",
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" c2 = 'A'\n",
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" elif 18 < age <= 23:\n",
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" c1 = 'Sen'\n",
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" c2 = 'B'\n",
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" elif 23 < age <= 30:\n",
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" c1 = 'Sen'\n",
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" c2 = 'A'\n",
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" \n",
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" return f'{c1}-{gender}-{c2}'\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "529f37c2",
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"metadata": {},
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"outputs": [],
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"source": [
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"df['Klasse'] = df.apply(evaluate_class,axis=1)\n",
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"df[f'Ruderpass {dt.datetime.now().year}'] = 0"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 90,
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"id": "7ff6f41c",
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"metadata": {},
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"outputs": [],
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"source": [
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"file_name = 'temp.xlsx'\n",
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"\n",
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"with pd.ExcelWriter(file_name, engine='openpyxl') as writer:\n",
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" \n",
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" df_styled = df.style.set_properties(**{'text-align': 'center'})\n",
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" # 2 Write to xlsx\n",
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" df_styled.to_excel(writer, sheet_name=\"Athlet_innen\",index=False)\n",
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"\n",
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" # 3 after writing, change other formats\n",
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" # --- Access the openpyxl worksheet object ---\n",
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" worksheet = writer.sheets[\"Athlet_innen\"]\n",
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"\n",
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" # 3.2 format the header\n",
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" # Define a bold, larger font\n",
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" header_font = openpyxl.styles.Font(name='Arial', size=12, bold=True, color=\"000000\")\n",
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"\n",
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" worksheet.column_dimensions['A'].width = 18*1.63\n",
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" worksheet.column_dimensions['B'].width = 18*0.86\n",
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" worksheet.column_dimensions['C'].width = 18*0.72\n",
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" worksheet.column_dimensions['D'].width = 18*0.91\n",
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" worksheet.column_dimensions['E'].width = 18*0.72\n",
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" worksheet.column_dimensions['F'].width = 18*1.45\n",
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"\n",
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" \n",
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" # Iterate through the first row (Header)\n",
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" # worksheet[1] returns all cells in the first row\n",
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" for cell in worksheet[1]:\n",
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" cell.font = header_font\n",
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" cell.alignment = openpyxl.styles.Alignment(horizontal='center', vertical='center')\n",
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" cell.border = openpyxl.styles.Border(bottom=openpyxl.styles.Side(border_style='medium', color='000000'))\n",
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"\n",
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" # 3.3 freeze the first row\n",
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" worksheet.freeze_panes = 'A2' "
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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