Python实现多格式文本转为word

pip install python-docx PyPDF2 pandas

def text_to_word(input_file, output_file):
    with open(input_file, 'r', encoding='utf-8') as file:
        text_content = file.read()

    from docx import Document
    doc = Document()
    doc.add_paragraph(text_content)
    doc.save(output_file)

# 文本内容分析
def analyze_text_content(text_content):
    # 在这里加入你的文本分析逻辑
    pass

# 使用示例
text_to_word('input.txt', 'output.docx')
text_content = read_word_content('output.docx')
analyze_text_content(text_content)

from PyPDF2 import PdfReader
from docx import Document

def pdf_to_word_and_extract_info(input_file, output_file):
    pdf_reader = PdfReader(input_file)
    text_content = ""
    for page in pdf_reader.pages:
        text_content += page.extract_text()

    doc = Document()
    doc.add_paragraph(text_content)
    doc.save(output_file)

# 信息提取
def extract_info_from_pdf(text_content):
    # 在这里加入你的信息提取逻辑
    pass

# 使用示例
pdf_to_word_and_extract_info('input.pdf', 'output.docx')
text_content = read_word_content('output.docx')
extract_info_from_pdf(text_content)

import pandas as pd

def excel_to_word_and_analyze_data(input_file, output_file):
    excel_data = pd.read_excel(input_file)
    
    doc = Document()
    for column in excel_data.columns:
        doc.add_paragraph(column)
        for value in excel_data[column]:
            doc.add_paragraph(str(value))
    
    doc.save(output_file)

# 数据分析
def analyze_data_from_excel(excel_data):
    # 在这里加入你的数据分析逻辑
    pass

# 使用示例
excel_to_word_and_analyze_data('input.xlsx', 'output.docx')
excel_data = pd.read_excel('input.xlsx')
analyze_data_from_excel(excel_data)

from docx import Document

def deep_dive_into_word_content(input_file):
    doc = Document(input_file)
    for paragraph in doc.paragraphs:
        # 在这里加入更深层次的内容挖掘逻辑
        pass

# 使用示例
deep_dive_into_word_content('output.docx')