156 lines
5.0 KiB
Python
156 lines
5.0 KiB
Python
#!/usr/bin/env python3
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"""
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精确提取PDF题目内容 - 改进版
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"""
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import re
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import json
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import os
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from pypdf import PdfReader, PdfWriter
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def split_pdf_and_extract_questions(pdf_path, topics_info_path, output_dir):
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"""
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按Topic切割PDF并精确提取题目内容
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"""
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with open(topics_info_path, 'r', encoding='utf-8') as f:
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topics = json.load(f)
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reader = PdfReader(pdf_path)
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total_pages = len(reader.pages)
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os.makedirs(output_dir, exist_ok=True)
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pdf_dir = os.path.join(output_dir, 'pdfs')
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os.makedirs(pdf_dir, exist_ok=True)
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all_questions = []
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for topic in topics:
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topic_num = topic['topic_num']
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start_page = topic['start_page']
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end_page = topic['end_page']
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writer = PdfWriter()
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for page_num in range(start_page, min(end_page + 1, total_pages)):
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writer.add_page(reader.pages[page_num])
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pdf_output_path = os.path.join(pdf_dir, f'topic_{topic_num:02d}.pdf')
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with open(pdf_output_path, 'wb') as f:
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writer.write(f)
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print(f"已保存: {pdf_output_path}")
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print(f"正在提取 Topic {topic_num} 的题目内容...")
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topic_questions = extract_questions_precise(reader, start_page, end_page, topic_num)
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all_questions.extend(topic_questions)
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print(f" Topic {topic_num}: 提取了 {len(topic_questions)} 道题")
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questions_json_path = os.path.join(output_dir, 'questions.json')
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with open(questions_json_path, 'w', encoding='utf-8') as f:
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json.dump(all_questions, f, ensure_ascii=False, indent=2)
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print(f"\n所有题目已保存到: {questions_json_path}")
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print(f"总共提取了 {len(all_questions)} 道题")
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return all_questions
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def extract_questions_precise(reader, start_page, end_page, topic_num):
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"""
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精确提取题目内容
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"""
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questions = []
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full_text = ""
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for page_num in range(start_page, end_page + 1):
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page = reader.pages[page_num]
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text = page.extract_text()
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if text:
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full_text += text + "\n"
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question_pattern = re.compile(
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r'Question\s+#(\d+)\s*\n(.*?)(?=Question\s+#\d+|Topic\s+\d+|$)',
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re.DOTALL | re.IGNORECASE
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)
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matches = question_pattern.findall(full_text)
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for match in matches:
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q_num = int(match[0])
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content = match[1].strip()
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question_data = parse_question_content(topic_num, q_num, content)
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if question_data:
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questions.append(question_data)
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return questions
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def parse_question_content(topic_num, q_num, content):
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"""
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解析题目内容，提取题干、选项和答案
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"""
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lines = content.split('\n')
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question_stem = ""
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options = []
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correct_answer = ""
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option_pattern = re.compile(r'^([A-Z])\.\s*(.*)', re.IGNORECASE)
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answer_pattern = re.compile(r'Correct Answer:\s*([A-Z,\s]+)', re.IGNORECASE)
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comments_pattern = re.compile(r'^Comments', re.IGNORECASE)
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current_section = "stem"
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current_option = None
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current_option_text = ""
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for line in lines:
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line = line.strip()
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if not line:
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continue
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if comments_pattern.match(line):
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break
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answer_match = answer_pattern.search(line)
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if answer_match:
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correct_answer = answer_match.group(1).strip().upper()
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continue
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option_match = option_pattern.match(line)
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if option_match:
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if current_option is not None and current_option_text:
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options.append({
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'label': current_option,
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'text': current_option_text.strip()
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})
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current_option = option_match.group(1).upper()
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current_option_text = option_match.group(2)
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current_section = "options"
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elif current_section == "options" and current_option is not None:
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if not line.startswith(('Most Voted', 'upvoted', 'Selected Answer:', 'Community vote')):
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current_option_text += " " + line
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elif current_section == "stem":
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if not line.startswith(('Most Voted', 'upvoted', 'Selected Answer:', 'Community vote', 'Correct Answer')):
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question_stem += " " + line
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if current_option is not None and current_option_text:
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options.append({
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'label': current_option,
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'text': current_option_text.strip()
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})
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question_stem = question_stem.strip()
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if not question_stem and not options:
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return None
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return {
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'topic': topic_num,
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'question_num': q_num,
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'stem': question_stem,
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'options': options,
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'answer': correct_answer
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}
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if __name__ == '__main__':
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pdf_path = '/Users/duguoyou/D365/MB-330_with_discussion.pdf'
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topics_info_path = '/Users/duguoyou/D365/topics_info.json'
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output_dir = '/Users/duguoyou/D365/exam_data'
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questions = split_pdf_and_extract_questions(pdf_path, topics_info_path, output_dir)
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