84 lines
3.0 KiB
Python
84 lines
3.0 KiB
Python
import pandas as pd
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import requests
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import markdown
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from io import StringIO
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from datetime import datetime, timedelta
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from .config_loader import config
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_cache = {"events": None, "remarks": None, "timestamp": None}
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HEADERS = {"User-Agent": "Mozilla/5.0"}
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def invalidate_cache():
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global _cache
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_cache = {"events": None, "remarks": None, "timestamp": None}
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return "Cache gelöscht"
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def _is_cache_valid():
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if _cache["timestamp"] is None:
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return False
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return (datetime.now() - _cache["timestamp"]) < timedelta(hours=1)
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def get_upcoming_events(days_to_show=None, limit=None):
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# Sofort Standardwert aus Config setzen, falls None oder 0
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if not days_to_show:
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days_to_show = config['processing']['days_to_show']
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# 1. Daten laden (entweder aus Cache oder von Google)
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if not _is_cache_valid() or _cache["events"] is None:
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url = config['links']['times_csv']
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response = requests.get(url, headers=HEADERS)
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response.raise_for_status()
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response.encoding = 'utf-8'
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df = pd.read_csv(StringIO(response.text))
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# Typografie: Bindestrich durch En-Dash (–) ersetzen
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for col in ['Morgen', 'Nachmittag']:
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df[col] = df[col].fillna('').astype(str).str.replace('-', ' – ', regex=False)
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date_col = config['google_sheet']['date_column']
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df = df.dropna(subset=[date_col])
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df[date_col] = pd.to_datetime(df[date_col], dayfirst=True, errors='coerce')
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wt_map = {0: 'Mo', 1: 'Di', 2: 'Mi', 3: 'Do', 4: 'Fr', 5: 'Sa', 6: 'So'}
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df['Wochentag'] = df[date_col].dt.weekday.map(wt_map)
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_cache["events"] = df.sort_values(by=date_col).to_dict(orient='records')
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_cache["timestamp"] = datetime.now()
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heute = pd.Timestamp(datetime.now().date())
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date_col = config['google_sheet']['date_column']
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# PRIORITÄT 1: Zeilen-Limit (gewinnt immer)
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if limit and limit > 0:
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return [e for e in _cache["events"] if e[date_col] >= heute][:limit]
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# PRIORITÄT 2: Tage-Logik
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ende = heute + timedelta(days=int(days_to_show))
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return [e for e in _cache["events"] if heute <= e[date_col] < ende]
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def get_remarks():
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if _is_cache_valid() and _cache["remarks"] is not None:
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return _cache["remarks"]
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url = config['links']['remarks_csv']
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response = requests.get(url, headers=HEADERS)
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response.raise_for_status()
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response.encoding = 'utf-8'
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df = pd.read_csv(StringIO(response.text), skiprows=2, header=None)
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if not df.empty:
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raw_remarks = df[0].dropna().astype(str).tolist()
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processed = []
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for r in raw_remarks:
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html = markdown.markdown(r.strip())
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if html.startswith("<p>") and html.endswith("</p>"):
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html = html[3:-4]
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processed.append(html)
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_cache["remarks"] = processed
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_cache["timestamp"] = datetime.now()
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else:
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_cache["remarks"] = []
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return _cache["remarks"] |