Additional/format.py

@@ -1,232 +0,0 @@
-#!/usr/bin/env python
-"""
-Convert Excel format from network structure format to standardized format.
-
-The source file has network structure data that needs to be extracted and reformatted
-to match the target format with columns: DPM, DPM_IP, Name, PartNumber, IP
-
-Usage:
-    python format.py <source_file.xlsx> [output_file.xlsx]
-    
-Examples:
-    python format.py "Amazon CDW5_IP Addresses_Local.xlsx"
-    python format.py "input.xlsx" "output.xlsx"
-"""
-
-import argparse
-import pandas as pd
-from pathlib import Path
-from openpyxl import load_workbook
-from openpyxl.styles import Font, Alignment, PatternFill, Border, Side
-from openpyxl.utils import get_column_letter
-
-
-def convert_format(source_file, output_file):
-    """Convert source Excel format to target format."""
-    print(f"Reading source file: {source_file}")
-    # Read with header=2 to skip first 2 rows and use row 2 as header
-    source_df = pd.read_excel(source_file, header=2)
-    
-    print(f"Source file shape: {source_df.shape}")
-    print(f"Source columns: {list(source_df.columns)}")
-    
-    # Find the column names - they should be in row 2
-    print("\nFirst few rows of source:")
-    print(source_df.head(10).to_string())
-    
-    # Map source columns to target columns
-    # Based on the structure, we need to find columns by their actual header values
-    cols = list(source_df.columns)
-    
-    # Find columns by exact name match first
-    dpm_col = None
-    dpm_ip_col = None
-    name_col = None
-    part_number_col = None
-    ip_col = None
-    
-    for col in source_df.columns:
-        col_str = str(col).strip()
-        if col_str == 'DPM' and 'PORT' not in col_str:
-            dpm_col = col
-        elif col_str == 'IP' and dpm_ip_col is None and 'PORT' not in col_str:
-            # First IP column is DPM_IP
-            dpm_ip_col = col
-        elif col_str == 'Assigned Device':
-            name_col = col
-        elif col_str == 'Part Number':
-            part_number_col = col
-        elif col_str == 'IP.1' or (col_str == 'IP' and dpm_ip_col is not None):
-            # Second IP column is device IP (pandas renames duplicate columns)
-            ip_col = col
-    
-    # Fallback: use column indices if names don't match
-    # Based on the structure: columns are at indices 3, 4, 5, 6, 7
-    if dpm_col is None and len(cols) >= 8:
-        dpm_col = cols[3]  # 'DPM'
-        dpm_ip_col = cols[4]  # 'IP'
-        name_col = cols[5]  # 'Assigned Device'
-        part_number_col = cols[6]  # 'Part Number'
-        ip_col = cols[7]  # 'IP.1' (second IP column)
-    
-    print(f"\nColumn mapping:")
-    print(f"  DPM: {dpm_col}")
-    print(f"  DPM_IP: {dpm_ip_col}")
-    print(f"  Name: {name_col}")
-    print(f"  PartNumber: {part_number_col}")
-    print(f"  IP: {ip_col}")
-    
-    # Validate that we found the essential columns
-    if not dpm_col or not name_col:
-        raise ValueError(f"Could not find required columns. Found: DPM={dpm_col}, Name={name_col}")
-    
-    # Forward-fill DPM and DPM_IP values (they're merged across multiple rows)
-    source_df[dpm_col] = source_df[dpm_col].ffill()
-    if dpm_ip_col:
-        source_df[dpm_ip_col] = source_df[dpm_ip_col].ffill()
-    
-    # Extract data
-    output_data = []
-    for idx, row in source_df.iterrows():
-        dpm = row[dpm_col] if dpm_col and pd.notna(row[dpm_col]) else None
-        dpm_ip = row[dpm_ip_col] if dpm_ip_col and pd.notna(row[dpm_ip_col]) else None
-        name = row[name_col] if name_col and pd.notna(row[name_col]) else None
-        part_number = row[part_number_col] if part_number_col and pd.notna(row[part_number_col]) else None
-        ip = row[ip_col] if ip_col and pd.notna(row[ip_col]) else None
-        
-        # Only add rows that have at least DPM and Name (the essential data)
-        if pd.notna(dpm) and pd.notna(name):
-            output_data.append({
-                'DPM': str(dpm).strip(),
-                'DPM_IP': str(dpm_ip).strip() if pd.notna(dpm_ip) else '',
-                'Name': str(name).strip(),
-                'PartNumber': str(part_number).strip() if pd.notna(part_number) else '',
-                'IP': str(ip).strip() if pd.notna(ip) else ''
-            })
-    
-    # Create output dataframe
-    output_df = pd.DataFrame(output_data)
-    
-    print(f"\nExtracted {len(output_df)} rows of network data")
-    print("\nFirst few rows of output:")
-    print(output_df.head(10).to_string())
-    
-    # Write output with formatting
-    print(f"\nWriting output to: {output_file}")
-    
-    with pd.ExcelWriter(output_file, engine='openpyxl') as writer:
-        output_df.to_excel(writer, sheet_name='NETWORK_PLC', index=False)
-        
-        # Get the worksheet
-        output_ws = writer.sheets['NETWORK_PLC']
-        
-        # Set column widths (reasonable defaults)
-        column_widths = {
-            'A': 20,  # DPM
-            'B': 16,  # DPM_IP
-            'C': 30,  # Name
-            'D': 18,  # PartNumber
-            'E': 16   # IP
-        }
-        for col_letter, width in column_widths.items():
-            output_ws.column_dimensions[col_letter].width = width
-        
-        # Format header row
-        header_fill = PatternFill(start_color="D3D3D3", end_color="D3D3D3", fill_type="solid")
-        header_font = Font(bold=True, size=11)
-        header_alignment = Alignment(horizontal="center", vertical="center")
-        thin_border = Border(
-            left=Side(style="thin"),
-            right=Side(style="thin"),
-            top=Side(style="thin"),
-            bottom=Side(style="thin")
-        )
-        
-        for col_idx in range(1, len(output_df.columns) + 1):
-            header_cell = output_ws.cell(row=1, column=col_idx)
-            header_cell.font = header_font
-            header_cell.fill = header_fill
-            header_cell.alignment = header_alignment
-            header_cell.border = thin_border
-        
-        # Format data rows
-        data_alignment = Alignment(horizontal="left", vertical="center")
-        for row_idx in range(2, len(output_df) + 2):
-            for col_idx in range(1, len(output_df.columns) + 1):
-                data_cell = output_ws.cell(row=row_idx, column=col_idx)
-                data_cell.alignment = data_alignment
-                data_cell.border = thin_border
-        
-        # Center align IP columns (DPM_IP and IP)
-        for row_idx in range(2, len(output_df) + 2):
-            output_ws.cell(row=row_idx, column=2).alignment = Alignment(horizontal="center", vertical="center")  # DPM_IP
-            output_ws.cell(row=row_idx, column=5).alignment = Alignment(horizontal="center", vertical="center")  # IP
-    
-    print(f"\nConversion complete!")
-    print(f"  Output saved to: {output_file}")
-    print(f"  Total rows: {len(output_df)}")
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        description="Convert Excel network structure format to standardized format",
-        formatter_class=argparse.RawDescriptionHelpFormatter,
-        epilog="""
-Examples:
-  python format.py "Amazon CDW5_IP Addresses_Local.xlsx"
-  python format.py "input.xlsx" "output.xlsx"
-  python format.py "C:\\path\\to\\file.xlsx"
-        """
-    )
-    parser.add_argument(
-        "source_file",
-        help="Path to the source Excel file to convert"
-    )
-    parser.add_argument(
-        "output_file",
-        nargs="?",
-        default=None,
-        help="Path to the output Excel file (default: source_file with '_formatted' suffix)"
-    )
-    
-    args = parser.parse_args()
-    
-    # Resolve file paths
-    source_file = Path(args.source_file)
-    if not source_file.is_absolute():
-        # If relative, assume it's in the same directory as the script
-        source_file = Path(__file__).parent / source_file
-    
-    if not source_file.exists():
-        print(f"ERROR: Source file not found: {source_file}")
-        exit(1)
-    
-    # Determine output file
-    if args.output_file:
-        output_file = Path(args.output_file)
-        if not output_file.is_absolute():
-            output_file = Path(__file__).parent / output_file
-    else:
-        # Default: add "_formatted" before the extension
-        stem = source_file.stem
-        suffix = source_file.suffix
-        output_file = source_file.parent / f"{stem}_formatted{suffix}"
-    
-    print("=" * 60)
-    print("CONVERTING EXCEL FORMAT")
-    print("=" * 60)
-    print(f"Source: {source_file}")
-    print(f"Output: {output_file}")
-    print("=" * 60)
-    
-    try:
-        convert_format(source_file, output_file)
-    except Exception as e:
-        print(f"\nERROR: {e}")
-        import traceback
-        traceback.print_exc()
-        exit(1)
-
-
-if __name__ == "__main__":
-    main()