139 lines
5.3 KiB
Python
139 lines
5.3 KiB
Python
import os
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from docx import Document
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import json
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def read_tables_from_docx(file_path):
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"""读取DOCX文件中的表格数据，并以嵌套字典的形式返回."""
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doc = Document(file_path)
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table_list = {}
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cur_title = []
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header = None
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for table in doc.tables:
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for i, row in enumerate(table.rows):
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cell_texts = [cell.text.strip() for cell in row.cells]
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# 检查是否是表头
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if header is None:
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header = cell_texts
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continue # 跳过第一个表头行
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# 如果遇到与第一个表头相同的行，跳过
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if cell_texts == header:
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continue
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cur_level = table_list
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temp_title = []
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for j, cell in enumerate(row.cells):
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text_str = cell.text.strip().replace(' ', '').replace('\n', '')
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if j < len(row.cells) - 1:
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if text_str == "":
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text_str = cur_title[j] if j < len(cur_title) else "<未识别到上级标题>"
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if text_str not in cur_level:
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cur_level[text_str] = {}
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cur_level = cur_level[text_str]
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temp_title.append(text_str)
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else:
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cell_text = cell.text.strip().replace(' ', '')
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if len(temp_title) > 0:
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last_key = temp_title[-1]
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if last_key in cur_level:
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if isinstance(cur_level[last_key], dict):
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cur_level[last_key] = f"\n{cell_text}"
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else:
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cur_level[last_key] += f"\n{cell_text}"
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else:
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cur_level[last_key] = cell_text
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else:
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last_key = f"第{i}行内容"
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if last_key in cur_level:
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if isinstance(cur_level[last_key], dict):
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cur_level[last_key] = f"\n{cell_text}"
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else:
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cur_level[last_key] += f"\n{cell_text}"
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else:
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cur_level[last_key] = cell_text
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cur_title = temp_title[:]
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return table_list
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def flatten_nested_dicts(d):
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"""平坦化嵌套字典，以便更简洁地保存为JSON."""
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keys_to_remove = []
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items_to_add = {}
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for key, value in list(d.items()):
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if isinstance(value, dict):
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value = flatten_nested_dicts(value)
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if len(value) == 1 and key in value:
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keys_to_remove.append(key)
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items_to_add[key] = value[key]
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elif len(value) == 1 and list(value.keys())[0] == list(value.values())[0]:
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items_to_add[key] = list(value.values())[0]
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for key in keys_to_remove:
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del d[key]
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d.update(items_to_add)
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return d
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def save_data_to_json(data, output_folder):
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filename = "truncate_output.json"
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output_filepath = os.path.join(output_folder, filename)
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"""将数据保存到JSON文件中."""
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with open(output_filepath, 'w', encoding='utf-8') as file:
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json.dump(data, file, ensure_ascii=False, indent=4)
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print(f"table_content_extraction: The data has been processed and saved to '{output_filepath}'.")
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return output_filepath
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def extract_tables_main(path, output_folder):
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if not os.path.exists(path):
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print(f"table_content_extraction: The specified file does not exist: {path}")
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return ""
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# 读取文档表格数据
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table_data = read_tables_from_docx(path)
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# 平坦化嵌套字典
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flattened_data = flatten_nested_dicts(table_data)
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# 保存平坦化后的数据到JSON文件
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return save_data_to_json(flattened_data, output_folder)
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#货物标批量生成truncate_output.json
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def process_all_part1_pdfs(folder_path, output_folder):
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"""遍历指定文件夹中的所有以part1.docx结尾的文件，执行extract_tables_main操作并创建子文件夹."""
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if not os.path.exists(folder_path):
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print(f"指定的文件夹不存在: {folder_path}")
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return
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for root, dirs, files in os.walk(folder_path):
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for file in files:
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if file.endswith("part1.docx"):
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file_path = os.path.join(root, file)
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print(f"正在处理文件: {file_path}")
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# 获取文件名（去除扩展名）
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base_filename = os.path.splitext(file)[0]
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# 在output_folder中创建对应的子文件夹
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subfolder_path = os.path.join(output_folder, base_filename)
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os.makedirs(subfolder_path, exist_ok=True)
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# 调用extract_tables_main，将子文件夹作为output_folder传递
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extract_tables_main(file_path, subfolder_path)
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if __name__ == "__main__":
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path = 'C:\\Users\\Administrator\\Desktop\\货物标\\zbfilesdocx\\2-招标文件.docx'
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output_folder = "C:\\Users\\Administrator\\Desktop\\货物标\\zbfilesdocx\\tmp" # 前附表json文件
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res=extract_tables_main(path, output_folder)
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#
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# folder_path='C:\\Users\\Administrator\\Desktop\\货物标\\output4'
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# output_folder="C:\\Users\\Administrator\\Desktop\\货物标\\output4\\tmp2"
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# process_all_part1_pdfs(folder_path, output_folder) |