app.py

import fitz  # PyMuPDF
import pandas as pd

# Function to convert PDF to DataFrame
def pdf_to_dataframe(pdf_path):
    # Open the PDF document
    doc = fitz.open(pdf_path)
    
    # Initialize an empty list to store text blocks
    text_blocks = []
    
    # Iterate through each page in the PDF
    for page_num in range(len(doc)):
        page = doc.load_page(page_num)
        text = page.get_text("text")
        text_blocks.append(text)
    
    # Join all text blocks into a single string
    full_text = "\n".join(text_blocks)
    
    # Split the text into lines
    lines = full_text.split('\n')
    
    # Create a DataFrame from the lines
    df = pd.DataFrame(lines, columns=['Text'])
    
    return df

# Function to save DataFrame to Excel
def dataframe_to_excel(df, excel_path):
    # Save the DataFrame to an Excel file
    df.to_excel(excel_path, index=False)

# Main function
def main():
    pdf_path = 'input.pdf'  # Path to your input PDF file
    excel_path = 'output.xlsx'  # Path where the Excel file will be saved
    
    # Convert PDF to DataFrame
    df = pdf_to_dataframe(pdf_path)
    
    # Save DataFrame to Excel
    dataframe_to_excel(df, excel_path)
    
    print(f"Excel saved to {excel_path}")

if __name__ == "__main__":
    main()