quality_app/view_dashboard.py

#!/usr/bin/env python3
"""
Excel Dashboard Viewer
Reads and displays the Dashboard sheet from Open .Orders WIZ  New.xlsb
"""

import pandas as pd
import sys
import os

def view_dashboard(file_path):
    """View the Dashboard sheet from the Excel file"""
    
    if not os.path.exists(file_path):
        print(f"❌ File not found: {file_path}")
        return
    
    try:
        print("=" * 80)
        print(f"📊 Loading Excel file: {os.path.basename(file_path)}")
        print("=" * 80)
        
        # First, list all sheets in the file
        print("\n📋 Available sheets:")
        xls = pd.ExcelFile(file_path, engine='pyxlsb')
        for i, sheet in enumerate(xls.sheet_names, 1):
            print(f"  {i}. {sheet}")
        
        # Try to find and read Daily Mirror sheet
        dashboard_sheet = None
        for sheet in xls.sheet_names:
            if 'daily mirror' in sheet.lower() or 'dashboard' in sheet.lower() or 'dash' in sheet.lower():
                dashboard_sheet = sheet
                break
        
        if not dashboard_sheet:
            print("\n⚠️  No 'Dashboard' sheet found. Available sheets listed above.")
            print("\nPlease select a sheet to view (enter number or name):")
            choice = input("> ").strip()
            
            if choice.isdigit():
                idx = int(choice) - 1
                if 0 <= idx < len(xls.sheet_names):
                    dashboard_sheet = xls.sheet_names[idx]
            else:
                if choice in xls.sheet_names:
                    dashboard_sheet = choice
        
        if not dashboard_sheet:
            print("❌ Invalid selection")
            return
        
        print(f"\n📊 Reading sheet: {dashboard_sheet}")
        print("=" * 80)
        
        # Read the sheet
        df = pd.read_excel(file_path, sheet_name=dashboard_sheet, engine='pyxlsb')
        
        # Display basic info
        print(f"\n📏 Sheet dimensions: {df.shape[0]} rows × {df.shape[1]} columns")
        print(f"\n📋 Column names:")
        for i, col in enumerate(df.columns, 1):
            print(f"  {i}. {col}")
        
        # Display first few rows
        print(f"\n📊 First 10 rows:")
        print("-" * 80)
        pd.set_option('display.max_columns', None)
        pd.set_option('display.width', None)
        pd.set_option('display.max_colwidth', 50)
        print(df.head(10).to_string())
        
        # Display data types
        print(f"\n📝 Data types:")
        print(df.dtypes)
        
        # Display summary statistics for numeric columns
        numeric_cols = df.select_dtypes(include=['number']).columns
        if len(numeric_cols) > 0:
            print(f"\n📈 Summary statistics (numeric columns):")
            print(df[numeric_cols].describe())
        
        # Check for date columns
        date_cols = []
        for col in df.columns:
            if 'date' in col.lower():
                date_cols.append(col)
        
        if date_cols:
            print(f"\n📅 Date columns found: {', '.join(date_cols)}")
            for col in date_cols:
                try:
                    df[col] = pd.to_datetime(df[col], errors='coerce')
                    print(f"  {col}: {df[col].min()} to {df[col].max()}")
                except:
                    pass
        
        # Interactive menu
        while True:
            print("\n" + "=" * 80)
            print("📋 Options:")
            print("  1. View more rows")
            print("  2. Filter data")
            print("  3. View specific columns")
            print("  4. Export to CSV")
            print("  5. View another sheet")
            print("  6. Exit")
            print("=" * 80)
            
            choice = input("Select option (1-6): ").strip()
            
            if choice == '1':
                n = input("How many rows to display? (default 20): ").strip()
                n = int(n) if n.isdigit() else 20
                print(df.head(n).to_string())
            
            elif choice == '2':
                print(f"Available columns: {', '.join(df.columns)}")
                col = input("Enter column name to filter: ").strip()
                if col in df.columns:
                    print(f"Unique values in {col}:")
                    print(df[col].value_counts().head(20))
                    val = input(f"Enter value to filter {col}: ").strip()
                    filtered = df[df[col].astype(str).str.contains(val, case=False, na=False)]
                    print(f"\nFiltered results ({len(filtered)} rows):")
                    print(filtered.to_string())
                else:
                    print("❌ Column not found")
            
            elif choice == '3':
                print(f"Available columns: {', '.join(df.columns)}")
                cols = input("Enter column names (comma-separated): ").strip()
                col_list = [c.strip() for c in cols.split(',')]
                valid_cols = [c for c in col_list if c in df.columns]
                if valid_cols:
                    print(df[valid_cols].head(20).to_string())
                else:
                    print("❌ No valid columns found")
            
            elif choice == '4':
                output_file = input("Enter output filename (default: dashboard_export.csv): ").strip()
                output_file = output_file if output_file else "dashboard_export.csv"
                df.to_csv(output_file, index=False)
                print(f"✅ Exported to {output_file}")
            
            elif choice == '5':
                print("\n📋 Available sheets:")
                for i, sheet in enumerate(xls.sheet_names, 1):
                    print(f"  {i}. {sheet}")
                sheet_choice = input("Select sheet (number or name): ").strip()
                
                if sheet_choice.isdigit():
                    idx = int(sheet_choice) - 1
                    if 0 <= idx < len(xls.sheet_names):
                        dashboard_sheet = xls.sheet_names[idx]
                        df = pd.read_excel(file_path, sheet_name=dashboard_sheet, engine='pyxlsb')
                        print(f"\n📊 Loaded sheet: {dashboard_sheet}")
                        print(f"Dimensions: {df.shape[0]} rows × {df.shape[1]} columns")
                        print(df.head(10).to_string())
                else:
                    if sheet_choice in xls.sheet_names:
                        df = pd.read_excel(file_path, sheet_name=sheet_choice, engine='pyxlsb')
                        print(f"\n📊 Loaded sheet: {sheet_choice}")
                        print(f"Dimensions: {df.shape[0]} rows × {df.shape[1]} columns")
                        print(df.head(10).to_string())
            
            elif choice == '6':
                print("👋 Goodbye!")
                break
            
            else:
                print("❌ Invalid option")
    
    except Exception as e:
        print(f"❌ Error reading file: {e}")
        import traceback
        traceback.print_exc()

if __name__ == "__main__":
    file_path = "/srv/quality_app/Open .Orders WIZ  New.xlsb"
    
    if len(sys.argv) > 1:
        file_path = sys.argv[1]
    
    view_dashboard(file_path)