Pdf To Docx

from pdf2docx import Converter
# Basic conversioncv = Converter('input.pdf')cv.convert('output.docx')cv.close()
# Or using context managerwith Converter('input.pdf') as cv:    cv.convert('output.docx')

from pdf2docx import Converter
cv = Converter('input.pdf')
# Full documentcv.convert('output.docx')
# Specific pages (0-indexed)cv.convert('output.docx', start=0, end=5)
# Single pagecv.convert('output.docx', pages=[0])
# Multiple specific pagescv.convert('output.docx', pages=[0, 2, 4])
cv.close()

from pdf2docx import Converter
cv = Converter('input.pdf')
cv.convert(    'output.docx',    start=0,                    # Start page (0-indexed)    end=None,                   # End page (None = last page)    pages=None,                 # Specific pages list    password=None,              # PDF password if encrypted    min_section_height=20.0,    # Minimum height for section    connected_border_tolerance=0.5,  # Border detection tolerance    line_overlap_threshold=0.9, # Line merging threshold    line_break_width_ratio=0.5, # Line break detection    line_break_free_space_ratio=0.1,    line_separate_threshold=5,  # Vertical line separation    new_paragraph_free_space_ratio=0.85,    float_image_ignorable_gap=5,    page_margin_factor_top=0.5,    page_margin_factor_bottom=0.5,)
cv.close()

# Works best with native PDFscv = Converter('native_pdf.pdf')cv.convert('output.docx')cv.close()

# For scanned PDFs, use OCR first# pdf2docx works best with native text PDFs# Consider using pytesseract or PaddleOCR first
import pytesseractfrom pdf2image import convert_from_path
# Convert PDF pages to imagesimages = convert_from_path('scanned.pdf')
# OCR each pagetext = ''for img in images:    text += pytesseract.image_to_string(img)
# Then create Word document from text

from pdf2docx import Converterimport os
def pdf_to_word(pdf_path, output_path=None, pages=None):    """Convert PDF to Word document."""    if output_path is None:        output_path = pdf_path.replace('.pdf', '.docx')        cv = Converter(pdf_path)        if pages:        cv.convert(output_path, pages=pages)    else:        cv.convert(output_path)        cv.close()        return output_path
# Usageresult = pdf_to_word('document.pdf')print(f"Created: {result}")

from pdf2docx import Converterfrom pathlib import Pathfrom concurrent.futures import ThreadPoolExecutor
def convert_single(pdf_path, output_dir):    """Convert single PDF to Word."""    output_path = output_dir / pdf_path.with_suffix('.docx').name        try:        cv = Converter(str(pdf_path))        cv.convert(str(output_path))        cv.close()        return f"Success: {pdf_path.name}"    except Exception as e:        return f"Error: {pdf_path.name} - {e}"
def batch_convert(input_dir, output_dir, max_workers=4):    """Convert all PDFs in directory."""    input_path = Path(input_dir)    output_path = Path(output_dir)    output_path.mkdir(exist_ok=True)        pdf_files = list(input_path.glob('*.pdf'))        with ThreadPoolExecutor(max_workers=max_workers) as executor:        futures = [            executor.submit(convert_single, pdf, output_path)            for pdf in pdf_files        ]                for future in futures:            print(future.result())
batch_convert('./pdfs', './word_docs')

from pdf2docx import Converter
def analyze_pdf(pdf_path):    """Analyze PDF structure before conversion."""    cv = Converter(pdf_path)        for i, page in enumerate(cv.pages):        print(f"Page {i+1}:")        print(f"  Size: {page.width} x {page.height}")        print(f"  Blocks: {len(page.blocks)}")                for block in page.blocks:            if hasattr(block, 'text'):                print(f"    Text block: {block.text[:50]}...")            elif hasattr(block, 'image'):                print(f"    Image block")        cv.close()
analyze_pdf('document.pdf')

from pdf2docx import Converter
def convert_with_progress(pdf_path, output_path):    """Convert PDF with progress tracking."""    cv = Converter(pdf_path)        total_pages = len(cv.pages)    print(f"Converting {total_pages} pages...")        for i in range(total_pages):        cv.convert(output_path, start=i, end=i+1)        progress = (i + 1) / total_pages * 100        print(f"Progress: {progress:.1f}%")        cv.close()    print("Conversion complete!")

from pdf2docx import Converterfrom docx import Document
def extract_tables_to_word(pdf_path, output_path):    """Extract only tables from PDF to Word."""    cv = Converter(pdf_path)        # First do full conversion    temp_path = 'temp_full.docx'    cv.convert(temp_path)    cv.close()        # Open and extract tables    doc = Document(temp_path)    new_doc = Document()        for table in doc.tables:        # Copy table to new document        new_table = new_doc.add_table(rows=0, cols=len(table.columns))                for row in table.rows:            new_row = new_table.add_row()            for i, cell in enumerate(row.cells):                new_row.cells[i].text = cell.text                new_doc.add_paragraph()  # Add spacing        new_doc.save(output_path)    os.remove(temp_path)

from pdf2docx import Converterimport os
def convert_contract(pdf_path):    """Convert contract PDF to editable Word with metadata."""        # Define output path    base_name = os.path.splitext(pdf_path)[0]    output_path = f"{base_name}_editable.docx"        # Convert    cv = Converter(pdf_path)        # Check page count    page_count = len(cv.pages)    print(f"Processing {page_count} pages...")        # Convert all pages    cv.convert(output_path)    cv.close()        print(f"Created: {output_path}")    print(f"File size: {os.path.getsize(output_path) / 1024:.1f} KB")        return output_path
# Usageresult = convert_contract('contract.pdf')

from pdf2docx import Converter
def convert_selected_pages(pdf_path, page_ranges, output_path):    """Convert specific page ranges to Word.        page_ranges: List of tuples like [(1, 3), (5, 7)] for pages 1-3 and 5-7    """    cv = Converter(pdf_path)        # Convert pages (0-indexed internally)    all_pages = []    for start, end in page_ranges:        all_pages.extend(range(start - 1, end))  # Convert to 0-indexed        cv.convert(output_path, pages=all_pages)    cv.close()        print(f"Converted pages: {page_ranges}")    return output_path
# Convert pages 1-5 and 10-15convert_selected_pages(    'long_document.pdf',    [(1, 5), (10, 15)],    'selected_pages.docx')

from pdf2docx import Converterfrom docx import Document
def pdf_to_template(pdf_path, output_path):    """Convert PDF report to Word template with placeholders."""        # Convert PDF to Word    cv = Converter(pdf_path)    cv.convert(output_path)    cv.close()        # Open and add placeholder fields    doc = Document(output_path)        # Replace common fields with placeholders    replacements = {        'Company Name': '[COMPANY_NAME]',        'Date:': 'Date: [DATE]',        'Prepared by:': 'Prepared by: [AUTHOR]',    }        for para in doc.paragraphs:        for old, new in replacements.items():            if old in para.text:                para.text = para.text.replace(old, new)        # Also check tables    for table in doc.tables:        for row in table.rows:            for cell in row.cells:                for old, new in replacements.items():                    if old in cell.text:                        cell.text = cell.text.replace(old, new)        doc.save(output_path)    print(f"Template created: {output_path}")
pdf_to_template('annual_report.pdf', 'report_template.docx')

from pdf2docx import Converterfrom pathlib import Pathimport json
def process_invoices(input_folder, output_folder):    """Convert PDF invoices to editable Word documents."""        input_path = Path(input_folder)    output_path = Path(output_folder)    output_path.mkdir(exist_ok=True)        results = []        for pdf_file in input_path.glob('*.pdf'):        output_file = output_path / pdf_file.with_suffix('.docx').name                try:            cv = Converter(str(pdf_file))            cv.convert(str(output_file))            cv.close()                        results.append({                'file': pdf_file.name,                'status': 'success',                'output': str(output_file)            })                    except Exception as e:            results.append({                'file': pdf_file.name,                'status': 'error',                'error': str(e)            })        # Save results log    with open(output_path / 'conversion_log.json', 'w') as f:        json.dump(results, f, indent=2)        # Summary    success = sum(1 for r in results if r['status'] == 'success')    print(f"Converted {success}/{len(results)} files")        return results
results = process_invoices('./invoices_pdf', './invoices_word')