Fix print_lost_labels compact styling and production data import
- Added compact table styling to print_lost_labels page (smaller fonts, reduced padding) - Fixed production data import missing fields (production_order_line, line_number) - Added better error handling and logging for Excel file imports - Skip empty rows in production data import - Log all columns and columns with data for debugging
This commit is contained in:
ske087
@@ -10,6 +10,7 @@ import os
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import json
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import tempfile
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from datetime import datetime
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import pandas as pd
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def get_db_connection():
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"""Get database connection using external server configuration"""
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@@ -73,8 +74,15 @@ def validate_order_row(row_data):
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data_livrare = row_data.get('data_livrare', '').strip()
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if data_livrare:
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try:
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# Try to parse common date formats
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for date_format in ['%Y-%m-%d', '%d/%m/%Y', '%m/%d/%Y', '%d.%m.%Y']:
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# Try to parse common date formats including Excel datetime format
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date_formats = [
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'%Y-%m-%d', # 2024-03-12
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'%Y-%m-%d %H:%M:%S', # 2024-03-12 00:00:00 (Excel format)
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'%d/%m/%Y', # 12/03/2024
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'%m/%d/%Y', # 03/12/2024
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'%d.%m.%Y' # 12.03.2024
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]
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for date_format in date_formats:
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try:
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datetime.strptime(data_livrare, date_format)
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break
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@@ -118,8 +126,15 @@ def add_order_to_database(order_data):
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data_livrare_str = order_data.get('data_livrare', '').strip()
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if data_livrare_str:
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try:
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# Try to parse common date formats and convert to YYYY-MM-DD
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for date_format in ['%Y-%m-%d', '%d/%m/%Y', '%m/%d/%Y', '%d.%m.%Y']:
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# Try to parse common date formats including Excel datetime and convert to YYYY-MM-DD
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date_formats = [
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'%Y-%m-%d', # 2024-03-12
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'%Y-%m-%d %H:%M:%S', # 2024-03-12 00:00:00 (Excel format)
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'%d/%m/%Y', # 12/03/2024
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'%m/%d/%Y', # 03/12/2024
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'%d.%m.%Y' # 12.03.2024
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]
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for date_format in date_formats:
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try:
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parsed_date = datetime.strptime(data_livrare_str, date_format)
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data_livrare_value = parsed_date.strftime('%Y-%m-%d')
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@@ -167,6 +182,141 @@ def add_order_to_database(order_data):
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except Exception as e:
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return False, f"Unexpected error: {str(e)}"
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def process_excel_file(file_path):
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"""
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Process uploaded Excel file (.xlsx) and return parsed data with validation
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Returns: (orders_data: list, validation_errors: list, validation_warnings: list)
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"""
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orders_data = []
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all_errors = []
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all_warnings = []
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try:
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# Read Excel file - try 'Sheet1' first (common data sheet), then fallback to first sheet
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try:
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df = pd.read_excel(file_path, sheet_name='Sheet1', engine='openpyxl')
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except:
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try:
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df = pd.read_excel(file_path, sheet_name=0, engine='openpyxl')
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except:
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# Last resort - try 'DataSheet'
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df = pd.read_excel(file_path, sheet_name='DataSheet', engine='openpyxl')
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# Column mapping for Excel files (case-insensitive)
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# Maps Excel column names to database field names
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column_mapping = {
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# Core order fields
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'comanda productie': 'comanda_productie',
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'comanda_productie': 'comanda_productie',
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'cod articol': 'cod_articol',
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'cod_articol': 'cod_articol',
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'descriere': 'descr_com_prod',
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'descr. com. prod': 'descr_com_prod',
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'descr com prod': 'descr_com_prod',
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'descr_com_prod': 'descr_com_prod',
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'description': 'descr_com_prod',
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'cantitate': 'cantitate',
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'cantitate ceruta': 'cantitate',
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'quantity': 'cantitate',
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'datalivrare': 'data_livrare',
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'data livrare': 'data_livrare',
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'data_livrare': 'data_livrare',
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'delivery date': 'data_livrare',
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'dimensiune': 'dimensiune',
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'dimension': 'dimensiune',
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# Customer and order info
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'customer': 'customer_name',
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'customer name': 'customer_name',
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'customer_name': 'customer_name',
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'comanda client': 'com_achiz_client',
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'com.achiz.client': 'com_achiz_client',
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'com achiz client': 'com_achiz_client',
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'com_achiz_client': 'com_achiz_client',
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'customer article number': 'customer_article_number',
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'customer_article_number': 'customer_article_number',
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# Status and dates
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'status': 'status',
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'end of quilting': 'end_of_quilting',
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'end of sewing': 'end_of_sewing',
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'data deschiderii': 'data_deschiderii',
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'data planific.': 'data_planific',
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'data planific': 'data_planific',
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# Machine and production info
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'masina cusut': 'masina_cusut',
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'masina cusut ': 'masina_cusut', # Note trailing space in Excel
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'tip masina': 'tip_masina',
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'numar masina': 'numar_masina',
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'clasificare': 'clasificare',
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'timp normat total': 'timp_normat_total',
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# Quality control stages (T1, T2, T3)
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't1': 't1',
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'data inregistrare t1': 'data_inregistrare_t1',
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'numele complet t1': 'numele_complet_t1',
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't2': 't2',
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'data inregistrare t2': 'data_inregistrare_t2',
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'numele complet t2': 'numele_complet_t2',
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't3': 't3',
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'data inregistrare t3': 'data_inregistrare_t3',
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'numele complet t3': 'numele_complet_t3',
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# Design and model info
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'model lb2': 'model_lb2',
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'design nr': 'design_nr',
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'needle position': 'needle_position',
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# Line references
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'nr. linie com. client': 'nr_linie_com_client',
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'nr linie com client': 'nr_linie_com_client',
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'nr_linie_com_client': 'nr_linie_com_client',
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'line': 'line_number',
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'line_number': 'line_number',
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'open for order': 'open_for_order',
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'open_for_order': 'open_for_order'
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}
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# Normalize column names
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df.columns = [col.lower().strip() if col else f'col_{i}' for i, col in enumerate(df.columns)]
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# Process each row
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for idx, row in df.iterrows():
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# Skip empty rows
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if row.isna().all():
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continue
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# Create normalized row data
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normalized_row = {}
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for col_name in df.columns:
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col_key = col_name.lower().strip()
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mapped_key = column_mapping.get(col_key, col_key.replace(' ', '_').replace('.', ''))
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# Get value and convert to string, handle NaN
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value = row[col_name]
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if pd.isna(value):
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normalized_row[mapped_key] = ''
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else:
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normalized_row[mapped_key] = str(value).strip()
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# Validate the row
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errors, warnings = validate_order_row(normalized_row)
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if errors:
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all_errors.extend([f"Row {idx + 2}: {error}" for error in errors])
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else:
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# Only add valid rows
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orders_data.append(normalized_row)
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if warnings:
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all_warnings.extend([f"Row {idx + 2}: {warning}" for warning in warnings])
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except Exception as e:
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all_errors.append(f"Error processing Excel file: {str(e)}")
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return orders_data, all_errors, all_warnings
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def process_csv_file(file_path):
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"""
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Process uploaded CSV file and return parsed data with validation
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@@ -268,7 +418,7 @@ def upload_orders_handler():
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if request.method == 'POST':
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# Handle file upload
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file = request.files.get('csv_file')
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if file and file.filename.endswith(('.csv', '.CSV')):
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if file and file.filename.endswith(('.csv', '.CSV', '.xlsx', '.XLSX', '.xls', '.XLS')):
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try:
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# Save uploaded file
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temp_path = os.path.join(temp_dir, file.filename)
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@@ -278,8 +428,11 @@ def upload_orders_handler():
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session['csv_filename'] = file.filename
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session['orders_csv_filepath'] = temp_path
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# Process the CSV file
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orders_data, validation_errors, validation_warnings = process_csv_file(temp_path)
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# Process the file based on extension
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if file.filename.lower().endswith(('.xlsx', '.xls')):
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orders_data, validation_errors, validation_warnings = process_excel_file(temp_path)
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else:
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orders_data, validation_errors, validation_warnings = process_csv_file(temp_path)
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# Store processed data in session
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session['orders_csv_data'] = orders_data
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