zbparse/flask_app/货物标/投标人须知正文条款提取成json文件货物标版.py

import json
import docx
import re
import os

import fitz
from PyPDF2 import PdfReader
from flask_app.货物标.货物标截取pdf import clean_page_content,extract_common_header

def extract_text_from_docx(file_path):
    doc = docx.Document(file_path)
    return '\n'.join([para.text for para in doc.paragraphs])

#PYPDF2版本
def extract_text_from_pdf(file_path, start_word, end_pattern):
    # 从PDF文件中提取文本
    common_header = extract_common_header(file_path)
    pdf_document = PdfReader(file_path)
    all_pages_text = []
    start_index = None
    # 处理所有页面
    for i, page in enumerate(pdf_document.pages):
        page_text = page.extract_text() if page.extract_text() else ""
        cleaned_text = clean_page_content(page_text, common_header)

        # 在第一页查找开始位置
        if i == 0 and start_index is None:
            start_match = re.search(start_word, cleaned_text, re.MULTILINE)
            if start_match:
                start_index = start_match.start()
                cleaned_text = cleaned_text[start_index:]

        # 在最后一页查找结束位置
        if i == len(pdf_document.pages) - 1:
            matches = list(re.finditer(end_pattern, cleaned_text, re.MULTILINE))
            if matches:
                end_index = matches[-1].start()
                cleaned_text = cleaned_text[:end_index]

        all_pages_text.append(cleaned_text)

    # 合并所有页面的文本
    full_text = "\n".join(all_pages_text)
    return full_text

#fitz库版本
# def extract_text_from_pdf(file_path, start_word, end_pattern):
#     # 从PDF文件中提取文本
#     common_header = extract_common_header(file_path)
#     doc = fitz.open(file_path)
#     all_pages_text = []
#     start_index = None
#
#     # 处理所有页面
#     for i in range(len(doc)):
#         page = doc[i]
#         page_text = page.get_text()
#         cleaned_text = clean_page_content(page_text, common_header)
#         print(cleaned_text)
#         print("yes")
#         # 在第一页查找开始位置
#         if i == 0 and start_index is None:
#             start_match = re.search(start_word, cleaned_text, re.MULTILINE)
#             if start_match:
#                 start_index = start_match.start()
#                 cleaned_text = cleaned_text[start_index:]
#
#         # 在最后一页查找结束位置
#         if i == len(doc) - 1:
#             for pattern in end_pattern:
#                 matches = list(re.finditer(pattern, cleaned_text, re.MULTILINE))
#                 if matches:
#                     end_index = matches[-1].start()
#                     cleaned_text = cleaned_text[:end_index]
#                     break
#
#         all_pages_text.append(cleaned_text)
#
#     # 合并所有页面的文本
#     full_text = "\n".join(all_pages_text)
#     # 关闭文档
#     doc.close()
#
#     return full_text


def compare_headings(current, new):
    # 使用过滤来确保只处理非空且为数字的部分
    current_nums = [int(num) for num in current.split('.') if num.isdigit()]
    new_nums = [int(num) for num in new.split('.') if num.isdigit()]

    # 比较数字序列以确定标题的层次关系
    for c, n in zip(current_nums, new_nums):
        if n > c:
            return True
        elif n < c:
            return False

    # 如果新标题有更多层次，认为是新的子章节
    return len(new_nums) > len(current_nums)


def should_add_newline(content, keywords, max_length=20):
    content_str = ''.join(content).strip()
    return any(keyword in content_str for keyword in keywords) or len(content_str) <= max_length

def handle_content_append(current_content, line_content, append_newline, keywords):
    if append_newline:
        if should_add_newline(current_content, keywords):
            current_content.append('\n')  # 添加换行符
        append_newline = False
    current_content.append(line_content)
    return append_newline

"""
保存换行符的具体逻辑：

对于二级标题（如 1.1），如果其后的内容包含关键词或内容较短（<=20字符），会在内容前添加一个换行符。
这个换行符会被保留在 current_content 列表中。
当处理下一个标题时，之前的内容（包括可能存在的换行符）会被合并并保存到 data 字典中。

解决了'一''二'这类标题出现在正文中的情况。但是目前的逻辑是如果'一'已有了，就加入正文，否则'一'作为新的标题。
"""
#提取json主函数
def parse_text_by_heading(text):
    keywords = ['包含', '以下']
    data = {}
    current_key = None
    current_key_chinese = None
    current_value_chinese = None
    current_content = []
    append_newline = False
    skip_subheadings = False
    last_main_number = None

    lines = text.split('\n')
    for i, line in enumerate(lines):
        line_stripped = line.strip().replace('．', '.')
        match = re.match(r'^(?<![a-zA-Z（(])(\d+(?:\.\d+)+)\s*(.*)', line_stripped)
        if not match:
            match = re.match(r'^(\d+\.)\s*(.+)$', line_stripped)

        # 新增：处理以点号开头的情况
        dot_match = re.match(r'^\.(\d+)\s*(.+)$', line_stripped)

        if match:
            new_key, line_content = match.groups()
            line_content = line_content.lstrip('.．、,')

            if any(keyword in line_content for keyword in keywords):
                skip_subheadings = True
            else:
                skip_subheadings = False

            # 保存中文标题的内容
            if current_key_chinese is not None:
                data[current_key_chinese] = current_value_chinese
                current_key_chinese = None

            # 保存阿拉伯数字的标题内容
            if current_key is None or (compare_headings(current_key, new_key) and (
                    len(current_content) == 0 or current_content[-1][-1] != '第')):
                if current_key is not None:
                    content_string = ''.join(current_content).strip()
                    data[current_key] = data.get(current_key, '') + content_string.replace(' ', '')
                current_key = new_key
                current_content = [line_content]
                append_newline = len(new_key.rstrip('.').split('.')) <= 2
                last_main_number = new_key.split('.')[0]
            else:
                append_newline = handle_content_append(current_content, line_stripped, append_newline, keywords)
        elif dot_match:
            # 处理以点号开头的情况
            sub_number, line_content = dot_match.groups()
            if last_main_number:
                new_key = f"{last_main_number}.{sub_number}"
                if current_key is not None:
                    content_string = ''.join(current_content).strip()
                    data[current_key] = data.get(current_key, '') + content_string.replace(' ', '')
                current_key = new_key
                current_content = [line_content]
                append_newline = True
            else:
                append_newline = handle_content_append(current_content, line_stripped, append_newline, keywords)
        else:
            if not skip_subheadings:
                # 合并了中文标题、字母标题、阿拉伯数字标题的匹配逻辑
                pattern_title = re.compile(r'^\s*(?:[（(]\s*([一二三四五六七八九十]{1,2})\s*[)）]\s*|([一二三四五六七八九十]{1,2})\s*、\s*)')
                chinese_match = pattern_title.match(line_stripped)
                letter_match = re.match(r'^([A-Z])\.\s*(.*)$', line_stripped)
                arabic_match = re.match(r'^(\d+、)\s*(.+)$', line_stripped)

                # 优化了处理逻辑，减少冗余
                if chinese_match or letter_match or arabic_match:
                    # 保存之前的 key 的内容（无论是中文标题还是阿拉伯数字标题）
                    if current_key is not None:
                        content_string = ''.join(current_content).strip()
                        data[current_key] = data.get(current_key, '') + content_string.replace(' ', '')
                    if current_key_chinese is not None:
                        data[current_key_chinese] = current_value_chinese
                    current_key_chinese = None

                    # 处理中文标题
                    if chinese_match:
                        current_key_chinese = chinese_match.group(1) or chinese_match.group(2)
                        current_value_chinese = line_stripped[chinese_match.end():].lstrip('.．、,').replace(' ', '')
                        if current_key_chinese in data:
                            handle_content_append(current_content, '\n' + line_stripped, append_newline, keywords)
                            current_key_chinese = None
                    # 处理字母标题
                    elif letter_match:
                        letter_key, letter_value = letter_match.groups()
                        letter_to_chinese = {
                            'A': '一', 'B': '二', 'C': '三', 'D': '四', 'E': '五',
                            'F': '六', 'G': '七', 'H': '八', 'I': '九', 'J': '十',
                            'K': '十一', 'L': '十二', 'M': '十三', 'N': '十四', 'O': '十五'
                        }
                        current_key_chinese = letter_to_chinese.get(letter_key, letter_key)
                        current_value_chinese = letter_value.lstrip('.．、,').replace(' ', '')
                        if current_key_chinese in data:
                            handle_content_append(current_content, '\n' + line_stripped, append_newline, keywords)
                            current_key_chinese = None
                    # 处理阿拉伯数字标题
                    elif arabic_match:
                        arabic_key, arabic_value = arabic_match.groups()
                        current_key = arabic_key.replace('、', '.')
                        current_content = [arabic_value]
                        append_newline = True
                        last_main_number = current_key.rstrip('.')
                    continue

            # 如果没有匹配标题，继续处理正文内容
            if line_stripped:
                append_newline = handle_content_append(current_content, line_stripped, append_newline, keywords)

    # 最后保存最后一个 key 对应的内容
    if current_key is not None:
        content_string = ''.join(current_content).strip()
        data[current_key] = data.get(current_key, '') + content_string.replace(' ', '')
    if current_key_chinese is not None:
        data[current_key_chinese] = current_value_chinese

    return data


#type=2时提取货物标的第一章招标公告时采用该逻辑
def parse_text_to_dict(text):
    """
    解析文本，根据大标题划分内容，生成字典。

    参数:
    text (str): 要解析的文本。

    返回:
    dict: 大标题作为键，内容作为值的字典。
    """
    # 正则表达式模式：匹配以一至十的汉字数字开头，后跟顿号和任意字符，且位于行首
    pattern = re.compile(r'^([一二三四五六七八九十]+\s*、\s*.*)$', re.MULTILINE)

    # 使用 re.finditer 找到所有大标题的位置
    matches = list(pattern.finditer(text))

    result = {}
    for i, match in enumerate(matches):
        title = match.group(1).strip()  # 获取大标题文本
        start = match.end()  # 内容的起始位置

        if i + 1 < len(matches):
            end = matches[i + 1].start()  # 下一个大标题的起始位置
        else:
            end = len(text)  # 最后一个大标题，内容到文本末尾

        content = text[start:end].strip()  # 获取内容并去除前后空白
        # 规范化换行符，并移除每行开头和结尾的空白
        content = content.replace('\r\n', '\n')  # 统一换行符
        content = re.sub(r'[ \t]+\n', '\n', content)  # 移除行尾空白
        content = re.sub(r'^[ \t]+|[ \t]+$', '', content, flags=re.MULTILINE)  # 移除行首和行尾空白
        content = clean_content(content)    # 处理内容中的换行符
        result[title] = content

    return result
def clean_content(content):
    """
    处理内容中的换行符：
    - 保留在子项编号前的换行符。
    - 保留在冒号 ':' 或全角冒号 '：' 前的第一个换行符。
    - 移除其他位置的换行符，不留下额外的空格。

    参数:
    content (str): 要处理的内容字符串。

    返回:
    str: 处理后的内容字符串。
    """
    # 定义子项编号的正则模式，包括：
    # - 数字+点号+数字（如 1.1 或 1．1）
    # - 数字+顿号（如 2、）
    # - 点号+数字（如 .3 或 ．3）
    # - 数字+右括号（如 1) 或 1））
    # - 圆括号包围的数字（如 (5)）
    # - 全角圆括号包围的数字（如 （5））
    # - 数字+点号（如 1. 或 1．）
    numbering_pattern = r'(?:\d+[．.]\d+(?:[．.]\d+)*|\d+、|[．.]\d+|\d+[)）]|\(\d+\)|（\d+）|\d+[．.])'

    # 定义需要保留换行符的情况：
    # 1. 换行符前面是子项编号
    # 2. 换行符前面是任意非空白字符，且后面跟着 ':' 或 '：'
    pattern_keep = r'\n(?=(?:' + numbering_pattern + r'|[^:\n\r\f\v]+[:：]))'

    # 定义占位符，用于暂时替换需要保留的换行符
    placeholder = "___PLACEHOLDER___"

    # Step 1: 将需要保留的换行符替换为占位符
    content_with_placeholder = re.sub(pattern_keep, placeholder, content)

    # Step 2: 移除所有剩余的换行符
    content_no_newlines = content_with_placeholder.replace('\n', '')

    # Step 3: 将占位符替换回换行符
    cleaned_content = content_no_newlines.replace(placeholder, '\n')

    return cleaned_content

# def convert_to_json(file_path, start_word, end_phrases):
#     if file_path.endswith('.docx'):
#         text = extract_text_from_docx(file_path)
#     elif file_path.endswith('.pdf'):
#         text = extract_text_from_pdf(file_path,start_word,end_phrases)
#     else:
#         raise ValueError("Unsupported file format")
#     # print(text)
#     parsed_data = parse_text_by_heading(text)
#     return parsed_data

def convert_clause_to_json(file_path,output_folder,type=1,suffix_counter="1.json"):
    if not os.path.exists(file_path):
        print(f"The specified file does not exist: {file_path}")
        return ""
    if type == 1:
        start_word = r'^\s*[（(]?\s*[一1]\s*[)）]?\s*[、.]*\s*(说\s*明|总\s*则)'
        end_pattern = r'^第[一二三四五六七八九十百千]+(?:章|部分)\s*[\u4e00-\u9fff]+'
        text = extract_text_from_pdf(file_path, start_word, end_pattern)
        result = parse_text_by_heading(text)
    else:
        start_word = r'^第[一二三四五六七八九十百千]+(?:章|部分).*?(?:公告|邀请书).*'
        end_pattern = r'^(?:第[一二三四五六七八九十百千]+(?:章|部分)\s*(?:投标人|磋商|供应商|谈判供应商|磋商供应商)须知+|(?:一\s*、\s*)?(?:投标人|磋商|供应商)须知前附表)'
        text = extract_text_from_pdf(file_path, start_word, end_pattern)
        result=parse_text_to_dict(text)
    # result = convert_to_json(input_path, start_word, end_pattern)
    # 检查输出文件夹是否存在，如果不存在则创建
    if not os.path.exists(output_folder):
        os.makedirs(output_folder)
        print(f"Created output folder: {output_folder}")
    file_name = "clause1.json" if type == 1 else "clause2.json"
    # file_name = f"clause{suffix_counter}.json"
    output_path = os.path.join(output_folder, file_name)
    with open(output_path, 'w', encoding='utf-8') as f:
        json.dump(result, f, indent=4, ensure_ascii=False)
    print(f"投标人须知正文条款提取成json文件: The data has been processed and saved to '{output_path}'.")
    return output_path


def process_folder(input_folder, output_folder):
    # 获取输入文件夹中的所有文件，过滤掉不以 'part2' 结尾的文件
    files = [f for f in os.listdir(input_folder) if os.path.isfile(os.path.join(input_folder, f)) and f.endswith('part2.pdf')]

    # 遍历文件并对每个文件进行处理
    for file_name in files:
        file_path = os.path.join(input_folder, file_name)
        # 去掉文件扩展名
        file_name_without_extension = os.path.splitext(file_name)[0]
        try:
            # 调用 convert_clause_to_json，传递文件路径、输出文件夹和递增的后缀
            output_path = convert_clause_to_json(file_path, output_folder, 1, file_name_without_extension)
            print(f"Processed file: {file_name}, JSON saved to: {output_path}")
        except ValueError as e:
            print(f"Error processing {file_name}: {e}")

#TODO:'C:\\Users\\Administrator\\Desktop\\货物标\\output4\\广水农商行门禁控制主机及基础验证设备采购项目——磋商文件（定稿）（三次）_tobidders_notice_part2.pdf' PYPDF2库读取有遗漏
#TODO:标题'一'应该越来越大，与'1.1'的逻辑分开'；
#TODO:911904c3-4d6e-47e0-acd8-b05e582209cb文件夹运行有问题，百炼出错了
if __name__ == "__main__":
    # file_path = 'D:\\flask_project\\flask_app\\static\\output\\cfd4959d-5ea9-4112-8b50-9e543803f029\\ztbfile_tobidders_notice.pdf'
    file_path='C:\\Users\\Administrator\\Desktop\\货物标\\output5\\094定稿-湖北工业大学轻武器模拟射击设备采购项目招标文件_notice.pdf'
    # file_path = 'C:\\Users\\Administrator\\Desktop\\货物标\\output4\\2-招标文件（2020年广水市中小学教师办公电脑系统及多媒体“班班通”设备采购安装项目）_tobidders_notice_part2.pdf'
    output_folder = 'C:\\Users\\Administrator\\Desktop\\货物标\\output5\\tmp2'
    try:
        output_path = convert_clause_to_json(file_path,output_folder,2)
        print(f"Final JSON result saved to: {output_path}")
    except ValueError as e:
        print("Error:", e)

    # input_folder = 'C:\\Users\\Administrator\\Desktop\\货物标\\output4'
    # output_folder = 'C:\\Users\\Administrator\\Desktop\\货物标\\output4\\tmp1'
    #
    # # 调用 process_folder 来处理整个文件夹中的所有文件
    # process_folder(input_folder, output_folder)