Python实现ODT自动化转换为DOCX的完整指南

from spire.doc import Document, FileFormat

def convert_odt_to_docx(input_path, output_path):
    doc = Document()
    doc.LoadFromFile(input_path)  # 加载ODT文件
    doc.SaveToFile(output_path, FileFormat.Docx)  # 保存为DOCX
    print(f"转换成功：{output_path}")

# 使用示例
convert_odt_to_docx("report.odt", "report.docx")

import os
from spire.doc import Document, FileFormat

def batch_convert(input_folder, output_folder):
    # 创建输出目录（若不存在）
    if not os.path.exists(output_folder):
        os.makedirs(output_folder)
    
    # 遍历输入目录
    for filename in os.listdir(input_folder):
        if filename.lower().endswith(".odt"):
            input_path = os.path.join(input_folder, filename)
            output_path = os.path.join(output_folder, 
                                      os.path.splitext(filename)[0] + ".docx")
            try:
                doc = Document()
                doc.LoadFromFile(input_path)
                doc.SaveToFile(output_path, FileFormat.Docx)
                print(f"✓ {filename} 转换完成")
            except Exception as e:
                print(f"✗ {filename} 转换失败: {str(e)}")

# 使用示例
batch_convert("input_odt", "output_docx")

import aspose.words as aw

def precise_conversion(input_path, output_path):
    doc = aw.Document(input_path)
    # 保留原始页眉页脚
    doc.first_section.headers_footers.link_to_previous(False)
    # 设置兼容性选项
    opts = aw.saving.DocxSaveOptions()
    opts.export_headers_footers_mode = aw.saving.ExportHeadersFootersMode.PER_SECTION
    doc.save(output_path, opts)

precise_conversion("complex.odt", "complex_precise.docx")

import pdfplumber

def extract_text(pdf_path):
    with pdfplumber.open(pdf_path) as pdf:
        full_text = []
        for page in pdf.pages:
            text = page.extract_text()
            if text:  # 跳过空白页
                full_text.append(text)
        return "\n".join(full_text)

# 使用示例
content = extract_text("annual_report.pdf")
print(content[:500])  # 打印前500字符

import camelot

def extract_tables(pdf_path):
    tables = camelot.read_pdf(pdf_path, flavor="lattice")
    for i, table in enumerate(tables):
        # 自动识别表头
        header = table.parsing_report["header"]
        # 导出为Excel
        table.to_excel(f"table_{i}.xlsx")
        print(f"提取表格{i+1}: {len(table.df)}行×{len(table.df.columns)}列")

extract_tables("financial_report.pdf")

from pdf2image import convert_from_path
import pytesseract

def ocr_pdf(pdf_path, lang='chi_sim+eng'):
    images = convert_from_path(pdf_path, dpi=300)
    full_text = []
    for i, image in enumerate(images):
        text = pytesseract.image_to_string(image, lang=lang)
        full_text.append(text)
    return "\n".join(full_text)

# 使用示例（需安装中文语言包）
chinese_content = ocr_pdf("scanned_contract.pdf")

def document_pipeline(odt_path):
    # 第一步：格式统一
    docx_path = odt_path.replace(".odt", ".docx")
    convert_odt_to_docx(odt_path, docx_path)
    
    # 第二步：生成PDF（使用ReportLab确保格式可控）
    from reportlab.lib.pagesizes import letter
    from reportlab.pdfgen import canvas
    doc = Document(docx_path)  # 重新加载DOCX（此处简化，实际需解析DOCX内容）
    pdf_path = odt_path.replace(".odt", ".pdf")
    c = canvas.Canvas(pdf_path, pagesize=letter)
    # 实际项目中需实现DOCX内容到PDF的映射逻辑
    c.drawString(100, 750, "Document Conversion Pipeline")
    c.save()
    
    # 第三步：结构化提取
    if is_text_pdf(pdf_path):  # 判断PDF类型
        content = extract_text(pdf_path)
        return {"text": content, "tables": []}
    else:
        return {"text": ocr_pdf(pdf_path), "tables": []}

# 简化示例，实际需完善各环节逻辑

from concurrent.futures import ProcessPoolExecutor

def parallel_conversion(input_paths, output_dir, workers=4):
    def process_file(input_path):
        output_path = os.path.join(output_dir, 
                                  os.path.basename(input_path).replace(".odt", ".docx"))
        convert_odt_to_docx(input_path, output_path)
        return output_path
    
    with ProcessPoolExecutor(max_workers=workers) as executor:
        results = list(executor.map(process_file, input_paths))
    return results

import hashlib

def safe_conversion(input_path, output_path):
    try:
        # 文件校验
        if not input_path.lower().endswith(".odt"):
            raise ValueError("非ODT文件")
        
        # 计算输入文件哈希
        with open(input_path, "rb") as f:
            input_hash = hashlib.md5(f.read()).hexdigest()
        
        # 执行转换
        convert_odt_to_docx(input_path, output_path)
        
        # 验证输出
        with open(output_path, "rb") as f:
            output_hash = hashlib.md5(f.read()).hexdigest()
        
        if not output_hash:
            raise RuntimeError("输出文件为空")
            
        return {"status": "success", "input_hash": input_hash, "output_hash": output_hash}
    
    except Exception as e:
        return {"status": "error", "message": str(e)}