feat: add batch CSV and image upload logic

- Created '/upload_csv_batch' endpoint to handle CSV parsing and multiple image uploads
- Added automatic WebP conversion and GridFS storage for batch images
- Implemented grouping logic via 'series_group_id' based on item name
- Created '/batch_upload' route and 'upload_batch.html' for a seamless async frontend

Web/app.py

@@ -11845,3 +11845,213 @@ def test_push_notification():
     except Exception as e:
         app.logger.error(f'Error sending test push: {e}')
         return jsonify({'success': False}), 500
+
+
+@app.route('/batch_upload', methods=['GET'])
+def batch_upload_page():
+    """
+    Serves the HTML frontend for the batch CSV and image upload.
+    """
+    # Check permissions if necessary, similar to your other routes
+    if 'username' not in session:
+        flash('Bitte melden Sie sich an.', 'error')
+        return redirect(url_for('login'))
+
+    return render_template('upload_batch.html')
+
+
+@app.route('/upload_csv_batch', methods=['POST'])
+def upload_csv_batch():
+    """
+    Route for batch adding new items to the inventory via CSV.
+    Handles CSV parsing, bulk image upload (conversion to WebP), GridFS storage,
+    and groups identical items based on their Name.
+    """
+    import pandas as pd
+    import ast
+    if 'username' not in session:
+        return jsonify({'success': False, 'message': 'Nicht angemeldet'}), 401
+
+    username = session['username']
+    # permissions = _get_current_user_permissions() ... (anpassen wie in Original)
+    # if not _action_access_allowed(permissions, 'can_insert'):
+    #     return jsonify({'success': False, 'message': 'Einfüge-Rechte erforderlich'}), 403
+
+    fs = get_gridfs()
+    upload_session_id = str(uuid.uuid4())[:8]
+    app.logger.info(f"Starting CSV Batch upload session {upload_session_id} - User: {username}")
+
+    # 1. Dateien aus dem Request empfangen
+    if 'csv_file' not in request.files:
+        return jsonify({"success": False, "message": "Keine CSV-Datei hochgeladen"}), 400
+
+    csv_file = request.files['csv_file']
+    uploaded_images = request.files.getlist('images')
+
+    # 2. CSV Einlesen und Validieren
+    try:
+        df = pd.read_csv(csv_file)
+    except Exception as e:
+        app.logger.error(f"[Upload {upload_session_id}] Fehler beim Lesen der CSV: {str(e)}")
+        return jsonify({"success": False, "message": f"Fehler beim Lesen der CSV: {str(e)}"}), 400
+
+    if 'Name' not in df.columns:
+        return jsonify({"success": False, "message": "Die CSV muss zwingend eine 'Name' Spalte enthalten."}), 400
+
+    # 3. Bilder verarbeiten, nach WebP konvertieren und in GridFS speichern
+    # Mapping: Original-Dateiname (ohne Pfad/Erweiterung) -> GridFS Filename (.webp)
+    image_mapping = {}
+    processed_count = 0
+    error_count = 0
+
+    for index, image in enumerate(uploaded_images):
+        if not image or not image.filename:
+            continue
+
+        original_secure_name = secure_filename(image.filename)
+        base_name_no_ext = os.path.splitext(original_secure_name)[0]
+        image_log_prefix = f"[Upload {upload_session_id}][Image {index + 1}/{len(uploaded_images)}]"
+
+        try:
+            # Annahme: is_allowed, error_message = allowed_file(...)
+
+            image.seek(0)
+            image_bytes = image.read()
+            if not image_bytes:
+                error_count += 1
+                continue
+
+            optimized_io = io.BytesIO()
+            with Image.open(io.BytesIO(image_bytes)) as img:
+                if img.mode not in ('RGB', 'RGBA'):
+                    img = img.convert('RGBA')
+
+                max_width = 500
+                if img.width > max_width:
+                    ratio = max_width / img.width
+                    new_size = (max_width, int(img.height * ratio))
+                    img = img.resize(new_size, Image.Resampling.LANCZOS)
+
+                img.save(optimized_io, format='WEBP', quality=85, optimize=True)
+
+            optimized_io.seek(0)
+            new_filename = f"{uuid.uuid4().hex}_{int(time.time())}.webp"
+
+            # Speichern in GridFS analog zu upload_item
+            file_id = fs.put(
+                optimized_io,
+                filename=new_filename,
+                content_type='image/webp',
+                metadata={
+                    'original_filename': original_secure_name,
+                    'upload_session': upload_session_id,
+                    'batch_upload': True
+                }
+            )
+
+            # Im Mapping speichern (damit wir sie später der CSV zuordnen können)
+            image_mapping[base_name_no_ext] = new_filename
+            processed_count += 1
+
+        except Exception as e:
+            app.logger.error(f"{image_log_prefix} Processing failed: {str(e)}")
+            error_count += 1
+
+    # 4. Items gruppieren (Analog zu series_group_id aus upload_item)
+    # Gruppierung über den Namen: Alle Zeilen mit demselben Namen gehören zur selben Serie
+    df['Name'] = df['Name'].fillna('Unbenannt').astype(str)
+
+    # Optional: Fülle NaN Werte in der CSV mit sinnvollen Defaults für die Datenbank
+    df = df.fillna({
+        'Ort': 'Unbekannt',
+        'Beschreibung': '',
+        'Code_4': '',
+        'Anschaffungsjahr': '',
+        'Anschaffungskosten': ''
+    })
+
+    created_item_ids = []
+
+    grouped_items = df.groupby('Name')
+
+    for name, group in grouped_items:
+        item_count = len(group)
+        series_group_id = str(uuid.uuid4()) if item_count > 1 else None
+        parent_item_id = None
+
+        for position, (index, row) in enumerate(group.iterrows(), start=1):
+
+            # Bilder aus der CSV-Zeile extrahieren und über das image_mapping mappen
+            item_image_filenames = []
+            if 'Images' in row and pd.notna(row['Images']):
+                try:
+                    # Aus "['Bild1.JPG', 'Bild2.JPG']" wird eine Liste
+                    img_list = ast.literal_eval(str(row['Images']))
+                    if isinstance(img_list, list):
+                        for img_name in img_list:
+                            base_img_name = os.path.splitext(img_name)[0]
+                            # Falls das Bild hochgeladen wurde, die WebP GridFS ID/Name nehmen
+                            if base_img_name in image_mapping:
+                                item_image_filenames.append(image_mapping[base_img_name])
+                            else:
+                                app.logger.warning(f"Bild {img_name} in CSV definiert, aber nicht hochgeladen.")
+                except (ValueError, SyntaxError):
+                    pass
+
+            # Filter extrahieren (falls vorhanden, erwarte string list wie "['HSU', '', '', '']")
+            def parse_filter_col(col_data):
+                try:
+                    res = ast.literal_eval(str(col_data))
+                    return res if isinstance(res, list) else []
+                except:
+                    return []
+
+            filter_upload = parse_filter_col(row.get('Filter', '[]'))
+            filter_upload2 = parse_filter_col(row.get('Filter2', '[]'))
+            filter_upload3 = parse_filter_col(row.get('Filter3', '[]'))
+
+            reservierbar = bool(row.get('Reservierbar', False))
+
+            # DB Insert Funktion aufrufen (orientiert an deiner upload_item)
+            item_id = it.add_item(
+                name=row['Name'],
+                ort=row['Ort'],
+                beschreibung=row['Beschreibung'],
+                image_filenames=item_image_filenames,
+                filter_upload=filter_upload,
+                filter_upload2=filter_upload2,
+                filter_upload3=filter_upload3,
+                anschaffungs_jahr=str(row['Anschaffungsjahr']) if row['Anschaffungsjahr'] else None,
+                anschaffungs_kosten=str(row['Anschaffungskosten']) if row['Anschaffungskosten'] else None,
+                code_4=str(row['Code_4']) if row['Code_4'] else None,
+                reservierbar=reservierbar,
+                series_group_id=series_group_id,
+                series_count=item_count,
+                series_position=position,
+                is_grouped_sub_item=(position > 1),
+                parent_item_id=parent_item_id,
+                # Default Werte, falls keine Bibliotheks-CSV
+                isbn='',
+                item_type='other',
+                library_category='',
+                is_library=False
+            )
+
+            if item_id:
+                created_item_ids.append(item_id)
+                # Das erste Item in einer Serie wird der Parent für die restlichen
+                if position == 1:
+                    parent_item_id = str(item_id)
+            else:
+                app.logger.error(f"Fehler beim Erstellen von Item: {row['Name']} (Index {index})")
+
+    app.logger.info(
+        f"Batch Upload abgeschlossen: {len(created_item_ids)} Items erstellt. {processed_count} Bilder verarbeitet.")
+
+    return jsonify({
+        "success": True,
+        "message": f"Upload erfolgreich. {len(created_item_ids)} Items importiert und {processed_count} Bilder konvertiert.",
+        "created_count": len(created_item_ids),
+        "images_processed": processed_count,
+        "images_failed": error_count
+    }), 200

Web/requirements.txt

@@ -17,4 +17,5 @@ cryptography>=42.0.0
 pywebpush
 py-vapid>=1.9.0
 beautifulsoup4
-pywebpush
+pywebpush
+pandas

Web/templates/upload_batch.html

@@ -0,0 +1,205 @@
+<!DOCTYPE html>
+<html lang="de">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Batch Upload - CSV & Bilder</title>
+    <style>
+        :root {
+            --primary-color: #4a90e2;
+            --background-color: #f4f7f6;
+            --text-color: #333;
+            --border-radius: 8px;
+        }
+
+        body {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            background-color: var(--background-color);
+            color: var(--text-color);
+            display: flex;
+            justify-content: center;
+            align-items: center;
+            min-height: 100vh;
+            margin: 0;
+        }
+
+        .upload-container {
+            background: white;
+            padding: 2rem;
+            border-radius: var(--border-radius);
+            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
+            width: 100%;
+            max-width: 500px;
+        }
+
+        h2 {
+            margin-top: 0;
+            color: var(--primary-color);
+            text-align: center;
+        }
+
+        .form-group {
+            margin-bottom: 1.5rem;
+        }
+
+        label {
+            display: block;
+            font-weight: 600;
+            margin-bottom: 0.5rem;
+        }
+
+        input[type="file"] {
+            display: block;
+            width: 100%;
+            padding: 0.5rem;
+            border: 1px dashed #ccc;
+            border-radius: var(--border-radius);
+            background: #fafafa;
+            cursor: pointer;
+        }
+
+        .btn-submit {
+            width: 100%;
+            padding: 0.75rem;
+            background-color: var(--primary-color);
+            color: white;
+            border: none;
+            border-radius: var(--border-radius);
+            font-size: 1rem;
+            font-weight: 600;
+            cursor: pointer;
+            transition: background-color 0.3s ease;
+        }
+
+        .btn-submit:hover {
+            background-color: #357abd;
+        }
+
+        .btn-submit:disabled {
+            background-color: #a0c4e8;
+            cursor: not-allowed;
+        }
+
+        /* Status & Feedback Messages */
+        #status-message {
+            margin-top: 1rem;
+            padding: 1rem;
+            border-radius: var(--border-radius);
+            display: none;
+            text-align: center;
+        }
+
+        .success {
+            background-color: #d4edda;
+            color: #155724;
+            border: 1px solid #c3e6cb;
+        }
+
+        .error {
+            background-color: #f8d7da;
+            color: #721c24;
+            border: 1px solid #f5c6cb;
+        }
+
+        .loading {
+            background-color: #e2e3e5;
+            color: #383d41;
+            border: 1px solid #d6d8db;
+        }
+
+        .spinner {
+            display: inline-block;
+            width: 1.5rem;
+            height: 1.5rem;
+            border: 3px solid rgba(0,0,0,0.1);
+            border-radius: 50%;
+            border-top-color: var(--primary-color);
+            animation: spin 1s ease-in-out infinite;
+            vertical-align: middle;
+            margin-right: 0.5rem;
+        }
+
+        @keyframes spin {
+            to { transform: rotate(360deg); }
+        }
+    </style>
+</head>
+<body>
+
+    <div class="upload-container">
+        <h2>Inventar Batch Upload</h2>
+
+        <form id="uploadForm">
+            <div class="form-group">
+                <label for="csv_file">1. items.csv Datei auswählen</label>
+                <!-- Akzeptiert nur CSV Dateien -->
+                <input type="file" id="csv_file" name="csv_file" accept=".csv" required>
+            </div>
+
+            <div class="form-group">
+                <label for="images">2. Bilder auswählen</label>
+                <!-- multiple erlaubt das Auswählen mehrerer Bilder gleichzeitig -->
+                <input type="file" id="images" name="images" accept="image/*" multiple required>
+                <small style="color: #666; display: block; margin-top: 5px;">Du kannst mehrere Bilder markieren (Strg/Cmd gedrückt halten).</small>
+            </div>
+
+            <button type="submit" id="submitBtn" class="btn-submit">Daten hochladen</button>
+        </form>
+
+        <div id="status-message"></div>
+    </div>
+
+    <script>
+        document.getElementById('uploadForm').addEventListener('submit', async function(e) {
+            e.preventDefault(); // Verhindert das Neuladen der Seite
+
+            const form = e.target;
+            const submitBtn = document.getElementById('submitBtn');
+            const statusDiv = document.getElementById('status-message');
+
+            // UI auf "Laden" setzen
+            submitBtn.disabled = true;
+            submitBtn.innerText = 'Wird verarbeitet...';
+            statusDiv.className = 'loading';
+            statusDiv.style.display = 'block';
+            statusDiv.innerHTML = '<div class="spinner"></div> Lade Dateien hoch und verarbeite Bilder... Bitte warten.';
+
+            // FormData sammelt alle Inputs aus dem Formular (csv_file und images)
+            const formData = new FormData(form);
+
+            try {
+                // Sende die Daten an den Flask-Endpoint
+                const response = await fetch('/upload_csv_batch', {
+                    method: 'POST',
+                    body: formData
+                });
+
+                const result = await response.json();
+
+                if (response.ok && result.success) {
+                    // Erfolgreicher Upload
+                    statusDiv.className = 'success';
+                    statusDiv.innerHTML = `
+                        <strong>Erfolg!</strong><br>
+                        ${result.message}
+                    `;
+                    form.reset(); // Formular nach Erfolg leeren
+                } else {
+                    // Fehler vom Server (z.B. falsches Format, fehlende Rechte)
+                    statusDiv.className = 'error';
+                    statusDiv.innerHTML = `<strong>Fehler:</strong> ${result.message || 'Ein unbekannter Fehler ist aufgetreten.'}`;
+                }
+            } catch (error) {
+                // Netzwerkfehler oder Server-Absturz
+                statusDiv.className = 'error';
+                statusDiv.innerHTML = `<strong>Verbindungsfehler:</strong> Konnte den Server nicht erreichen.`;
+                console.error('Upload Error:', error);
+            } finally {
+                // UI wieder freigeben
+                submitBtn.disabled = false;
+                submitBtn.innerText = 'Daten hochladen';
+            }
+        });
+    </script>
+</body>
+</html>

requirements.txt

@@ -17,4 +17,5 @@ cryptography>=42.0.0
 pywebpush
 py-vapid>=1.9.0
 beautifulsoup4
-pywebpush
+pywebpush
+pandas