import pandas as pd
import requests
from io import StringIO
from datetime import datetime, timedelta
from .config_loader import config

_cache = {"events": None, "remarks": None}
HEADERS = {"User-Agent": "Mozilla/5.0"}

def invalidate_cache():
    global _cache
    _cache = {"events": None, "remarks": None}
    print("DEBUG: Cache wurde manuell geleert.")
    return "Cache gelöscht"

def get_upcoming_events():
    if _cache["events"] is not None:
        return _cache["events"]
    
    url = config['links']['times_csv']
    print(f"DEBUG: Lade Zeiten von URL: {url}")
    
    response = requests.get(url, headers=HEADERS)
    df = pd.read_csv(StringIO(response.text))
    
    # Debug: Spaltennamen prüfen
    print(f"DEBUG: Spalten in Zeiten-Sheet gefunden: {df.columns.tolist()}")

    date_col = config['google_sheet']['date_column']
    df = df.dropna(subset=[date_col])
    df[date_col] = pd.to_datetime(df[date_col], dayfirst=True, errors='coerce')
    df = df.dropna(subset=[date_col]).fillna('')
    
    heute = pd.Timestamp(datetime.now().date())
    ende = heute + timedelta(days=config['processing']['days_to_show'])
    
    mask = (df[date_col] >= heute) & (df[date_col] <= ende)
    gefilterte = df.loc[mask].sort_values(by=date_col).copy()
    
    wt_map = {0: 'Mo', 1: 'Di', 2: 'Mi', 3: 'Do', 4: 'Fr', 5: 'Sa', 6: 'So'}
    gefilterte['Wochentag'] = gefilterte[date_col].dt.weekday.map(wt_map)
    
    _cache["events"] = gefilterte.to_dict(orient='records')
    return _cache["events"]

def get_remarks():
    if _cache["remarks"] is not None:
        return _cache["remarks"]
    
    url = config['links']['remarks_csv']
    print(f"DEBUG: Lade Bemerkungen von URL: {url}")
    
    response = requests.get(url, headers=HEADERS)
    
    # Debug: Die ersten 100 Zeichen der Antwort sehen
    print(f"DEBUG: Raw Data Bemerkungen (Anfang): {response.text[:100]}...")
    
    df = pd.read_csv(StringIO(response.text), skiprows=2, header=None)
    
    if not df.empty:
        print(f"DEBUG: Bemerkungen-DF Head:\n{df.head(3)}")
        remarks = df[0].dropna().astype(str).tolist()
        _cache["remarks"] = [r.strip() for r in remarks if r.strip()]
    else:
        _cache["remarks"] = []
        
    return _cache["remarks"]