📚 Improved backend structure & documentation, added new features, and refactored scripts. 🚀🔧📝💻🖥️
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@ -1,6 +1,6 @@
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import json
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from datetime import datetime, timedelta
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from flask import Blueprint, render_template, request, jsonify, redirect, url_for, abort
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from flask import Blueprint, render_template, request, jsonify, redirect, url_for, abort, make_response
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from flask_login import current_user, login_required
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from sqlalchemy import and_, or_, func
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@ -158,9 +158,9 @@ def calendar_view():
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def api_get_calendar_events():
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"""Kalendereinträge als JSON für FullCalendar zurückgeben."""
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try:
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# Datumsbereich aus Anfrage
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start_str = request.args.get('from')
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end_str = request.args.get('to')
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# Datumsbereich aus Anfrage - FullCalendar verwendet 'start' und 'end'
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start_str = request.args.get('start') or request.args.get('from')
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end_str = request.args.get('end') or request.args.get('to')
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if not start_str or not end_str:
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# Standardmäßig eine Woche anzeigen
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@ -168,6 +168,12 @@ def api_get_calendar_events():
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end_date = start_date + timedelta(days=7)
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else:
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try:
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# FullCalendar sendet ISO-Format mit Zeitzone, das muss geparst werden
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if start_str and start_str.endswith('+02:00'):
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start_str = start_str[:-6] # Zeitzone entfernen
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if end_str and end_str.endswith('+02:00'):
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end_str = end_str[:-6] # Zeitzone entfernen
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start_date = datetime.fromisoformat(start_str)
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end_date = datetime.fromisoformat(end_str)
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except ValueError:
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@ -233,12 +239,20 @@ def api_get_calendar_events():
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events.append(event)
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logger.info(f"📅 Kalender-Events abgerufen: {len(events)} Einträge für Zeitraum {start_date} bis {end_date}")
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return jsonify(events)
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except Exception as e:
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logger.error(f"Fehler beim Abrufen der Kalendereinträge: {str(e)}")
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return jsonify({"error": "Fehler beim Verarbeiten der Anfrage"}), 500
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# Zusätzliche Route für FullCalendar-Kompatibilität
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@calendar_blueprint.route('/api/calendar/events', methods=['GET'])
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@login_required
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def api_get_calendar_events_alt():
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"""Alternative Route für FullCalendar-Events - delegiert an api_get_calendar_events."""
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return api_get_calendar_events()
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@calendar_blueprint.route('/api/calendar/event', methods=['POST'])
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@login_required
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def api_create_calendar_event():
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@ -547,4 +561,281 @@ def api_get_smart_recommendation():
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except Exception as e:
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logger.error(f"Fehler beim Abrufen der intelligenten Empfehlung: {str(e)}")
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return jsonify({"error": "Fehler beim Verarbeiten der Anfrage"}), 500
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return jsonify({"error": "Fehler beim Verarbeiten der Anfrage"}), 500
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@calendar_blueprint.route('/api/calendar/export', methods=['GET'])
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@login_required
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def api_export_calendar():
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"""
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Exportiert Kalenderdaten in verschiedenen Formaten (CSV, JSON, Excel).
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URL-Parameter:
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- format: csv, json, excel (Standard: csv)
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- start_date: ISO-Format Start-Datum (Optional)
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- end_date: ISO-Format End-Datum (Optional)
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- printer_id: Spezifischer Drucker-Filter (Optional)
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- status: Status-Filter (Optional)
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"""
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try:
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# Parameter aus Request extrahieren
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export_format = request.args.get('format', 'csv').lower()
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start_str = request.args.get('start_date')
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end_str = request.args.get('end_date')
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printer_id = request.args.get('printer_id')
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status_filter = request.args.get('status')
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# Datumsbereich bestimmen (Standard: nächste 4 Wochen)
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if start_str and end_str:
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try:
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start_date = datetime.fromisoformat(start_str)
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end_date = datetime.fromisoformat(end_str)
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except ValueError:
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return jsonify({"error": "Ungültiges Datumsformat. Verwenden Sie ISO-Format."}), 400
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else:
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# Standard: Kommende 4 Wochen
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start_date = datetime.now()
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end_date = start_date + timedelta(days=28)
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with get_cached_session() as db_session:
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# Basis-Query für Jobs im Zeitraum
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query = db_session.query(Job).filter(
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or_(
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# Jobs, die im Zeitraum beginnen
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and_(Job.start_at >= start_date, Job.start_at <= end_date),
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# Jobs, die im Zeitraum enden
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and_(Job.end_at >= start_date, Job.end_at <= end_date),
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# Jobs, die den Zeitraum komplett umfassen
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and_(Job.start_at <= start_date, Job.end_at >= end_date)
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)
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)
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# Filter anwenden
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if printer_id:
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try:
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printer_id_int = int(printer_id)
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query = query.filter(Job.printer_id == printer_id_int)
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except ValueError:
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return jsonify({"error": "Ungültige Drucker-ID"}), 400
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if status_filter:
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query = query.filter(Job.status == status_filter)
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# Jobs abrufen und sortieren
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jobs = query.order_by(Job.start_at.asc()).all()
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if not jobs:
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return jsonify({"message": "Keine Daten im angegebenen Zeitraum gefunden"}), 404
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# Zusätzliche Daten für Export sammeln
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export_data = []
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for job in jobs:
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# Benutzerinformationen
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user = db_session.query(User).filter_by(id=job.user_id).first()
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user_name = user.name if user else "Unbekannt"
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user_email = user.email if user else ""
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# Druckerinformationen
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printer = db_session.query(Printer).filter_by(id=job.printer_id).first()
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printer_name = printer.name if printer else "Unbekannt"
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printer_location = printer.location if printer else ""
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printer_model = printer.model if printer else ""
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# Status-Übersetzung
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status_mapping = {
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"scheduled": "Geplant",
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"running": "Läuft",
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"finished": "Abgeschlossen",
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"cancelled": "Abgebrochen",
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"failed": "Fehlgeschlagen",
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"pending": "Wartend"
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}
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status_german = status_mapping.get(job.status, job.status)
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# Priorität-Übersetzung
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priority_mapping = {
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"urgent": "Dringend",
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"high": "Hoch",
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"normal": "Standard",
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"low": "Niedrig"
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}
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priority_german = priority_mapping.get(job.priority if hasattr(job, 'priority') and job.priority else 'normal', 'Standard')
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export_entry = {
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"Job_ID": job.id,
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"Auftragsname": job.name,
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"Beschreibung": job.description or "",
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"Status": status_german,
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"Priorität": priority_german,
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"Benutzer": user_name,
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"Benutzer_E-Mail": user_email,
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"Drucker": printer_name,
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"Drucker_Standort": printer_location,
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"Drucker_Modell": printer_model,
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"Startzeit": job.start_at.strftime('%d.%m.%Y %H:%M:%S') if job.start_at else "",
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"Endzeit": job.end_at.strftime('%d.%m.%Y %H:%M:%S') if job.end_at else "",
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"Dauer_Minuten": job.duration_minutes or 0,
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"Dauer_Stunden": round((job.duration_minutes or 0) / 60, 2),
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"Erstellt_am": job.created_at.strftime('%d.%m.%Y %H:%M:%S') if job.created_at else "",
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"Abgeschlossen_am": job.completed_at.strftime('%d.%m.%Y %H:%M:%S') if job.completed_at else "",
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"Dateiname": job.filename if hasattr(job, 'filename') and job.filename else "",
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"Materialverbrauch": getattr(job, 'material_used', "") or "",
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"Kosten_EUR": getattr(job, 'cost', "") or ""
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}
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export_data.append(export_entry)
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# Format-spezifischer Export
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timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
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if export_format == 'csv':
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import csv
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import io
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# CSV-Export implementierung
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output = io.StringIO()
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writer = csv.writer(output, delimiter=';', quoting=csv.QUOTE_MINIMAL)
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# Header-Zeile
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if export_data:
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headers = list(export_data[0].keys())
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writer.writerow(headers)
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# Daten-Zeilen
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for row in export_data:
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formatted_row = []
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for value in row.values():
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if value is None:
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formatted_row.append('')
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else:
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formatted_row.append(str(value))
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writer.writerow(formatted_row)
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# Response erstellen
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csv_content = output.getvalue()
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output.close()
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# BOM für UTF-8 hinzufügen (Excel-Kompatibilität)
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csv_content = '\ufeff' + csv_content
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response = make_response(csv_content)
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response.headers['Content-Type'] = 'text/csv; charset=utf-8'
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response.headers['Content-Disposition'] = f'attachment; filename="schichtplan_export_{timestamp}.csv"'
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logger.info(f"📊 CSV-Export erstellt: {len(export_data)} Einträge für Benutzer {current_user.username}")
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return response
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elif export_format == 'json':
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# JSON-Export implementierung
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export_metadata = {
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"export_info": {
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"erstellt_am": datetime.now().strftime('%d.%m.%Y %H:%M:%S'),
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"exportiert_von": current_user.username,
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"zeitraum_von": start_date.strftime('%d.%m.%Y'),
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"zeitraum_bis": end_date.strftime('%d.%m.%Y'),
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"anzahl_jobs": len(export_data),
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"filter_drucker_id": printer_id,
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"filter_status": status_filter
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},
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"produktionsplan": export_data
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}
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json_content = json.dumps(export_metadata, indent=2, ensure_ascii=False)
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response = make_response(json_content)
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response.headers['Content-Type'] = 'application/json; charset=utf-8'
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response.headers['Content-Disposition'] = f'attachment; filename="schichtplan_export_{timestamp}.json"'
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logger.info(f"📊 JSON-Export erstellt: {len(export_data)} Einträge für Benutzer {current_user.username}")
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return response
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elif export_format == 'excel':
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# Excel-Export implementierung
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try:
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import pandas as pd
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import io
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# DataFrame erstellen
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df = pd.DataFrame(export_data)
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# Excel-Datei in Memory erstellen
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output = io.BytesIO()
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with pd.ExcelWriter(output, engine='openpyxl') as writer:
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# Hauptdaten-Sheet
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df.to_excel(writer, sheet_name='Produktionsplan', index=False)
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# Zusammenfassung-Sheet
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summary_data = {
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'Metrik': [
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'Gesamte Jobs',
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'Geplante Jobs',
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'Laufende Jobs',
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'Abgeschlossene Jobs',
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'Abgebrochene Jobs',
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'Gesamte Produktionszeit (Stunden)',
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'Durchschnittliche Job-Dauer (Stunden)',
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'Anzahl verschiedener Drucker',
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'Anzahl verschiedener Benutzer',
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'Export erstellt am',
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'Zeitraum von',
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'Zeitraum bis'
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],
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'Wert': [
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len(export_data),
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len([j for j in export_data if j['Status'] == 'Geplant']),
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len([j for j in export_data if j['Status'] == 'Läuft']),
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len([j for j in export_data if j['Status'] == 'Abgeschlossen']),
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len([j for j in export_data if j['Status'] in ['Abgebrochen', 'Fehlgeschlagen']]),
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round(sum([j['Dauer_Stunden'] for j in export_data]), 2),
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round(sum([j['Dauer_Stunden'] for j in export_data]) / len(export_data), 2) if export_data else 0,
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len(set([j['Drucker'] for j in export_data])),
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len(set([j['Benutzer'] for j in export_data])),
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datetime.now().strftime('%d.%m.%Y %H:%M:%S'),
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start_date.strftime('%d.%m.%Y'),
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end_date.strftime('%d.%m.%Y')
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]
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}
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summary_df = pd.DataFrame(summary_data)
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summary_df.to_excel(writer, sheet_name='Zusammenfassung', index=False)
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# Auto-fit Spaltenbreite
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for sheet_name in writer.sheets:
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worksheet = writer.sheets[sheet_name]
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for column in worksheet.columns:
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max_length = 0
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column_letter = column[0].column_letter
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for cell in column:
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try:
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if len(str(cell.value)) > max_length:
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max_length = len(str(cell.value))
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except:
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pass
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adjusted_width = min(max_length + 2, 50)
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worksheet.column_dimensions[column_letter].width = adjusted_width
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output.seek(0)
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response = make_response(output.getvalue())
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response.headers['Content-Type'] = 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'
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response.headers['Content-Disposition'] = f'attachment; filename="schichtplan_export_{timestamp}.xlsx"'
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logger.info(f"📊 Excel-Export erstellt: {len(export_data)} Einträge für Benutzer {current_user.username}")
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return response
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except ImportError:
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return jsonify({
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"error": "Excel-Export nicht verfügbar. Pandas/openpyxl-Bibliotheken fehlen. "
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"Verwenden Sie CSV oder JSON Export."
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}), 501
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except Exception as e:
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logger.error(f"Fehler beim Excel-Export: {str(e)}")
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return jsonify({"error": f"Fehler beim Excel-Export: {str(e)}"}), 500
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else:
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return jsonify({"error": f"Unbekanntes Export-Format: {export_format}. Unterstützt: csv, json, excel"}), 400
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except Exception as e:
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logger.error(f"Fehler beim Kalender-Export: {str(e)}")
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return jsonify({"error": f"Fehler beim Export: {str(e)}"}), 500
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