add separate function in excel to csv

src/preprocess/excel_to_csv_converter.py

@@ -2,124 +2,110 @@ import pandas as pd
 import os
 from pathlib import Path
 
-def analyze_excel_structure(excel_path):
+class ExcelToCsvConverter:
     """
-    Analyze the structure of an Excel file and return sheet information.
-    
-    Args:
-        excel_path (str): Path to the Excel file
-        
-    Returns:
-        dict: Dictionary with sheet names and their basic info
+    Convert an Excel file to CSV files.
     """
-    try:
-        # Read Excel file to get all sheet names
-        excel_file = pd.ExcelFile(excel_path)
-        sheet_info = {}
-        
-        print(f"📊 Analyzing Excel file: {excel_path}")
-        print(f"📋 Found {len(excel_file.sheet_names)} sheets:")
-        print("-" * 50)
+    
+    def __init__(self, excel_path, output_dir=None):
+        self.excel_path = excel_path
+        self.output_dir = output_dir
+    
+
+    def convert_excel_to_csv(excel_path, output_dir=None):
+        """
+        Convert each sheet of an Excel file to a separate CSV file.
         
-        for i, sheet_name in enumerate(excel_file.sheet_names, 1):
-            # Read each sheet to get basic information
-            df = pd.read_excel(excel_path, sheet_name=sheet_name)
+        Args:
+            excel_path (str): Path to the Excel file
+            output_dir (str): Output directory for CSV files. If None, uses same directory as Excel file
+        """
+        try:
+            # Set up output directory
+            if output_dir is None:
+                output_dir = os.path.dirname(excel_path)
             
-            sheet_info[sheet_name] = {
-                'rows': len(df),
-                'columns': len(df.columns),
-                'column_names': list(df.columns)
-            }
+            # Create output directory if it doesn't exist
+            Path(output_dir).mkdir(parents=True, exist_ok=True)
             
-            print(f"{i}. Sheet: '{sheet_name}'")
-            print(f"   - Rows: {len(df)}")
-            print(f"   - Columns: {len(df.columns)}")
-            print(f"   - Column names: {list(df.columns)}")
-        
-        return sheet_info
-        
-    except Exception as e:
-        print(f"❌ Error analyzing Excel file: {e}")
-        return None
+            # Read Excel file
+            excel_file = pd.ExcelFile(excel_path)
+            converted_files = []
+            
+            for i, sheet_name in enumerate(excel_file.sheet_names, 1):
+                # Read the sheet
+                df = pd.read_excel(excel_path, sheet_name=sheet_name)
+                
+                # Create a safe filename for the CSV
+                safe_filename = "".join(c for c in sheet_name if c.isalnum() or c in (' ', '-', '_')).rstrip()
+                #for specific sheet name, save the file name and use it later
+                self.sheet_name = sheet_name
+                self.safe_filename = safe_filename
+                safe_filename = safe_filename.replace(' ', '_')
+                csv_filename = f"{safe_filename}.csv"
+                csv_path = os.path.join(output_dir, csv_filename)
+                
+                # Save as CSV
+                df.to_csv(csv_path, index=False, encoding='utf-8')
+                converted_files.append(csv_path)
+                
+                print(f"✅ {i}. '{sheet_name}' → {csv_filename}")
+                print(f"   - Saved {len(df)} rows, {len(df.columns)} columns")
+            
+            print(f"\n🎉 Successfully converted {len(converted_files)} sheets to CSV files!")
+            return converted_files
+            
+        except Exception as e:
+            print(f"❌ Error converting Excel to CSV: {e}")
+            return None
 
-def convert_excel_to_csv(excel_path, output_dir=None):
-    """
-    Convert each sheet of an Excel file to a separate CSV file.
-    
-    Args:
-        excel_path (str): Path to the Excel file
-        output_dir (str): Output directory for CSV files. If None, uses same directory as Excel file
-    """
-    try:
-        # Set up output directory
+
+    def convert_specific_sheet_to_csv(excel_path, sheet_name, output_dir=None):
+        """
+        Convert a specific sheet of an Excel file to a CSV file.
+        """
         if output_dir is None:
             output_dir = os.path.dirname(excel_path)
+            
+        df = pd.read_excel(excel_path, sheet_name=sheet_name)
+        safe_filename = "".join(c for c in sheet_name if c.isalnum() or c in (' ', '-', '_')).rstrip()
+        safe_filename = safe_filename.replace(' ', '_')
+        csv_filename = f"{safe_filename}.csv"
+        csv_path = os.path.join(output_dir, csv_filename)
+        df.to_csv(csv_path, index=False, encoding='utf-8')
+        print(f"✅ {sheet_name} → {csv_filename}")
+
+        return csv_path
+
+    def main():
+        """Main function to analyze and convert Excel file"""
         
-        # Create output directory if it doesn't exist
-        Path(output_dir).mkdir(parents=True, exist_ok=True)
+        # Define paths
+        excel_path = "data/real_data_excel/AI Project document.xlsx"
+        output_dir = "data/real_data_excel/converted_csv"
         
-        # Read Excel file
-        excel_file = pd.ExcelFile(excel_path)
+        # Check if Excel file exists
+        if not os.path.exists(excel_path):
+            print(f"❌ Excel file not found: {excel_path}")
+            return
         
-        print(f"🔄 Converting Excel sheets to CSV...")
-        print(f"📁 Output directory: {output_dir}")
-        print("-" * 50)
+        print("=" * 60)
+        print("📊 EXCEL TO CSV CONVERTER")
+        print("=" * 60)
         
-        converted_files = []
+        # Step 1: Analyze Excel structure
+        sheet_info = analyze_excel_structure(excel_path)
         
-        for i, sheet_name in enumerate(excel_file.sheet_names, 1):
-            # Read the sheet
-            df = pd.read_excel(excel_path, sheet_name=sheet_name)
-            
-            # Create a safe filename for the CSV
-            safe_filename = "".join(c for c in sheet_name if c.isalnum() or c in (' ', '-', '_')).rstrip()
-            safe_filename = safe_filename.replace(' ', '_')
-            csv_filename = f"{safe_filename}.csv"
-            csv_path = os.path.join(output_dir, csv_filename)
-            
-            # Save as CSV
-            df.to_csv(csv_path, index=False, encoding='utf-8')
-            converted_files.append(csv_path)
-            
-            print(f"✅ {i}. '{sheet_name}' → {csv_filename}")
-            print(f"   - Saved {len(df)} rows, {len(df.columns)} columns")
+        if sheet_info is None:
+            return
         
-        print(f"\n🎉 Successfully converted {len(converted_files)} sheets to CSV files!")
-        return converted_files
+        # Step 2: Convert to CSV
+        converted_files = convert_excel_to_csv(excel_path, output_dir)
         
-    except Exception as e:
-        print(f"❌ Error converting Excel to CSV: {e}")
-        return None
-
-def main():
-    """Main function to analyze and convert Excel file"""
-    
-    # Define paths
-    excel_path = "data/real_data_excel/AI Project document.xlsx"
-    output_dir = "data/real_data_excel/converted_csv"
-    
-    # Check if Excel file exists
-    if not os.path.exists(excel_path):
-        print(f"❌ Excel file not found: {excel_path}")
-        return
-    
-    print("=" * 60)
-    print("📊 EXCEL TO CSV CONVERTER")
-    print("=" * 60)
-    
-    # Step 1: Analyze Excel structure
-    sheet_info = analyze_excel_structure(excel_path)
-    
-    if sheet_info is None:
-        return
-    
-    # Step 2: Convert to CSV
-    converted_files = convert_excel_to_csv(excel_path, output_dir)
-    
-    if converted_files:
-        print("\n📂 Converted files:")
-        for file_path in converted_files:
-            print(f"   - {file_path}")
+        if converted_files:
+            print("\n📂 Converted files:")
+            for file_path in converted_files:
+                print(f"   - {file_path}")
 
 if __name__ == "__main__":
     main()