225 lines
9.4 KiB
Python
225 lines
9.4 KiB
Python
import json
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import re
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#提取两个大标题之间的内容
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def extract_between_sections(data, target_values):
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target_found = False
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extracted_data = {}
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current_section_title = ""
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section_pattern = re.compile(r'^[一二三四五六七八九十]+$') # 匹配 "一", "二", "三" 等大标题
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current_block = {}
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# 遍历所有键值对
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for key, value in data.items():
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# 只匹配形如 "一": "竞争性磋商响应文件" 的章节标题
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if section_pattern.match(key):
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if target_found:
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# 如果已经找到了符合的章节，并且遇到了另一个章节
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# 保存当前块并重置
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if current_block:
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extracted_data[current_section_title] = current_block
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current_block = {}
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target_found = False
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# 检查当前标题是否包含 target_values 中的任意关键词
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if any(tv in value for tv in target_values):
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target_found = True # 找到了目标章节，开始捕获后续内容
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current_section_title = value # 保存章节标题内容
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elif target_found: # 只捕获目标值之后的内容
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current_block[key] = value
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# 保存最后一个块（如果有的话）
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if current_block:
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extracted_data[current_section_title] = current_block
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return extracted_data
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def process_with_outer_key(data):
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processed_data = {}
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# 遍历外层的键值对
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for outer_key, inner_data in data.items():
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# 调用 transform_json 函数对内层数据进行处理
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processed_inner_data = transform_json(inner_data)
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# 将处理后的数据保留在外层键下
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processed_data[outer_key] = processed_inner_data
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return processed_data
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# 转换结构化的JSON数据
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def transform_json(data):
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result = {}
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temp = {0: result} # 初始化根字典
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# 首先,创建一个临时字典用于检查是否存在三级标题
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has_subkey = {}
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for key in data.keys():
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parts = key.split('.')
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if len(parts) > 2 and parts[1]:
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parent_key = parts[0] + '.' + parts[1]
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has_subkey[parent_key] = True
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for key, value in data.items():
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match = re.match(r'(\d+)(?:\.(\d+))?(?:\.(\d+))?', key)
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if match:
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levels = [int(l) for l in match.groups() if l is not None]
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if (len(levels) - 1) in temp:
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parent = temp[len(levels) - 1]
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else:
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print(f"No parent found at level {len(levels) - 1} for key '{key}'. Check the data structure.")
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continue
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if len(levels) == 1: # 一级标题
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# 新增逻辑：判断值中是否有 ':' 或 '：'，并进行拆分
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# 优先按 '\n' 拆分
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if '\n' in value:
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new_key, *new_value = value.split('\n', 1)
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new_key = new_key.strip()
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new_value = new_value[0].strip() if new_value else ""
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# 如果没有 '\n'，再检查 ':' 或 '：'，并进行拆分
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elif ':' in value or '：' in value:
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delimiter = ':' if ':' in value else '：'
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new_key, new_value = value.split(delimiter, 1)
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new_key = new_key.strip()
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new_value = new_value.strip()
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else:
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new_key = value.strip()
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new_value = ""
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parent[new_key] = {}
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if new_value:
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parent[new_key][new_key] = new_value # 使用 new_key 作为键名，而不是固定的 "content"
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temp[len(levels)] = parent[new_key]
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elif len(levels) == 2: # 二级标题
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new_key, *new_value = value.split('\n', 1)
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new_key = new_key.strip()
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new_value = new_value[0].strip() if new_value else ""
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if f"{levels[0]}.{levels[1]}" in has_subkey:
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parent[new_key] = [new_value] if new_value else []
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else:
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parent[new_key] = new_value
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temp[len(levels)] = parent[new_key]
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else: # 三级标题
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if isinstance(parent, dict):
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parent_key = list(parent.keys())[-1]
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if isinstance(parent[parent_key], list):
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parent[parent_key].append(value)
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elif parent[parent_key]:
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parent[parent_key] = [parent[parent_key], value]
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else:
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parent[parent_key] = [value]
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elif isinstance(parent, list):
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parent.append(value)
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def remove_single_item_lists(node):
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if isinstance(node, dict):
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for key in list(node.keys()):
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node[key] = remove_single_item_lists(node[key])
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if isinstance(node[key], list) and len(node[key]) == 1:
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node[key] = node[key][0]
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return node
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return remove_single_item_lists(result)
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#主要是处理键值中若存在若干序号且每个序号块的内容>=50字符的时候，用列表表示。
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def post_process(value):
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# 如果传入的是非字符串值，直接返回原值
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if not isinstance(value, str):
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return value
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# 定义可能的分割模式及其正则表达式
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patterns = [
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(r'\d+、', r'(?=\d+、)'), # 匹配 '1、'
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(r'[（(]\d+[）)]', r'(?=[（(]\d+[）)])'), # 匹配 '(1)' 或 '（1）'
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(r'\d+\.', r'(?=\d+\.)'), # 匹配 '1.'
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(r'[一二三四五六七八九十]、', r'(?=[一二三四五六七八九十]、)'), # 匹配 '一、'、'二、' 等
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(r'[一二三四五六七八九十]\.', r'(?=[一二三四五六七八九十]\.)') # 匹配 '一.'、'二.' 等
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]
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# 初始化用于保存最早匹配到的模式及其位置
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first_match = None
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first_match_position = len(value) # 初始值设为文本长度，确保任何匹配都会更新它
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# 遍历所有模式，找到第一个出现的位置
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for search_pattern, split_pattern_candidate in patterns:
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match = re.search(search_pattern, value)
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if match:
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# 如果这个匹配的位置比当前记录的更靠前，更新匹配信息
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if match.start() < first_match_position:
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first_match = split_pattern_candidate
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first_match_position = match.start()
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# 如果找到了最早出现的匹配模式，使用它来分割文本
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if first_match:
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blocks = re.split(first_match, value)
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else:
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# 如果没有匹配的模式，保留原文本
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blocks = [value]
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processed_blocks = []
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for block in blocks:
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if not block:
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continue
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# 计算中英文字符总数，如果大于50，则加入列表
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if block and len(re.findall(r'[\u4e00-\u9fff\w]', block)) >= 50:
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processed_blocks.append(block.strip())
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else:
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# 如果发现有块长度小于50，返回原数据
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return value
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# 如果所有的块都符合条件，返回分割后的列表
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return processed_blocks
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# 递归地处理嵌套结构
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def process_nested_data(data):
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# 先检查是否所有值都是 ""、"/" 或空列表
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if isinstance(data, dict) and all(v == "" or v == "/" or (isinstance(v, list) and not v) for v in data.values()):
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return list(data.keys())
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# 递归遍历字典，处理最内层的字符串
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if isinstance(data, dict):
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# 如果当前项是字典，继续递归遍历其键值对
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result = {}
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for key, value in data.items():
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result[key] = process_nested_data(value) # 递归处理子项
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return result
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elif isinstance(data, list):
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# 如果是列表，直接返回列表，保持原样
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return data
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else:
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# 到达最内层，处理非字典和非列表的元素（字符串）
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return post_process(data)
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# 读取JSON数据，提取内容，转换结构，并打印结果
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def extract_from_notice(clause_path, type):
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if type == 1:
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target_values = ["投标文件","响应文件","响应性文件"]
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elif type == 2:
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target_values = ["开标", "评标", "定标","磋商程序","中标","程序","步骤"]
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elif type == 3:
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target_values = ["重新招标、不再招标和终止招标", "重新招标", "不再招标", "终止招标"]
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elif type == 4:
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target_values = ["评标"] #测试
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else:
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raise ValueError("Invalid type specified. Use 1 for '投标文件, 投标' or 2 for '开标, 评标, 定标'or 3 for '重新招标'")
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with open(clause_path, 'r', encoding='utf-8') as file:
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data = json.load(file)
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extracted_data = extract_between_sections(data, target_values) # 读取json
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transformed_data=process_with_outer_key(extracted_data)
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final_result=process_nested_data(transformed_data)
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return final_result
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if __name__ == "__main__":
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file_path = 'D:\\flask_project\\flask_app\\static\\output\\87f48f9c-e6ee-4dc1-a981-5a10085c4635\\tmp\\clause1.json'
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# file_path = 'D:\\flask_project\\flask_app\\static\\output\\87f48f9c-e6ee-4dc1-a981-5a10085c4635\\clause1.json'
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try:
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res = extract_from_notice(file_path, 2) # 可以改变此处的 type 参数测试不同的场景
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res2=json.dumps(res,ensure_ascii=False,indent=4)
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print(res2)
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except ValueError as e:
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print(e)
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