220 lines
7.9 KiB
Python
220 lines
7.9 KiB
Python
#!/usr/bin/env python3
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# 光湖视频AI系统 · .hdlp剧本解析器
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# 耳耳蛋 ICE-GL-EED · D181 · 解决管线①/②不兼容问题
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"""
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.hdlp格式 → 标准化剧本解析
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输入: EP01-SCRIPT-LOCK.hdlp
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输出:
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parse → 结构化JSON (集→场→角色→台词→场景描述)
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characters → 角色列表
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"""
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import re
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import json
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import sys
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def convert_hdlp_to_standard(text):
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"""将.hdlp剧本转换为script-parser.js能识别的标准格式"""
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lines = text.split('\n')
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result = []
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in_meta = False
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for line in lines:
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stripped = line.strip()
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# 跳过元数据和锁标记
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if not stripped:
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result.append('')
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continue
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if stripped.startswith('> ⊢') or stripped.startswith('HLDP:'):
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continue
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if stripped.startswith('---'):
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continue
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if stripped.startswith('# '):
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result.append(stripped.replace('# ', ''))
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continue
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# ## 1-1 日/内 地点 → 添加「第1集」标记 + 标准化场景
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scene_match = re.match(r'^##\s+(\d+)-(\d+)\s+(日|夜|晨|暮)\s*/\s*(内|外)\s+(.+)$', stripped)
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if scene_match:
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ep_num = scene_match.group(1)
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scene_id = f"{scene_match.group(1)}-{scene_match.group(2)}"
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time = scene_match.group(3)
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loc = scene_match.group(4)
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name = scene_match.group(5)
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# 添加集标记（如果还没加过）
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if f'第{ep_num}集' not in '\n'.join(result[-5:]):
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result.append(f"第{ep_num}集")
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result.append(f"{scene_id} {time} {loc} {name}")
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continue
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# **人物**：林昊（描述）→ 人物：林昊（描述）
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char_match = re.match(r'^\*\*人物\*\*[：:]\s*(.+)$', stripped)
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if char_match:
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result.append(f"人物：{char_match.group(1)}")
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continue
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# **角色名（情绪）**：台词 → 角色名（情绪）：台词
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dialogue_bold = re.match(r'^\*\*(.+?)\*\*[：:]\s*(.+)$', stripped)
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if dialogue_bold:
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# 提取角色名和情绪
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inner = re.match(r'(.+?)[（(](.+?)[）)]', dialogue_bold.group(1))
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if inner:
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result.append(f"{inner.group(1)}（{inner.group(2)}）：{dialogue_bold.group(2)}")
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else:
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result.append(f"{dialogue_bold.group(1)}：{dialogue_bold.group(2)}")
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continue
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# VO标记
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vo_match = re.match(r'^\*\*(.+?)（VO）\*\*[：:]?\s*(.*)$', stripped)
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if vo_match:
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result.append(f"{vo_match.group(1)}（VO）：{vo_match.group(2)}")
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continue
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# 音效标记
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sfx_match = re.match(r'^\*\*音效\*\*[：:]?\s*(.+)$', stripped)
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if sfx_match:
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result.append(f"△ 特效：音效 - {sfx_match.group(1)}")
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continue
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# 【特写：xxx】→ 保留
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if stripped.startswith('【特写') or stripped.startswith('【特寫'):
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result.append(f"△ 特写：{stripped}")
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continue
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# △ → 保留
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if stripped.startswith('△'):
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result.append(stripped)
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continue
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# 其他行原样保留
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result.append(stripped)
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# 去掉结尾的元数据行
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while result and (result[-1].startswith('⊢') or result[-1].startswith('>') or result[-1] == '---'):
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result.pop()
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return '\n'.join(result)
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def parse_hdlp(text):
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"""解析.hdlp剧本为结构化数据"""
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standard = convert_hdlp_to_standard(text)
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lines = standard.split('\n')
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episodes = []
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current_ep = None
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current_scene = None
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for line in lines:
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line = line.strip()
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if not line: continue
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# 第N集
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ep_match = re.match(r'^第(\d+)集$', line)
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if ep_match:
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if current_scene and current_ep:
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current_ep['scenes'].append(current_scene)
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current_scene = None
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if current_ep:
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episodes.append(current_ep)
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current_ep = {'episode': int(ep_match.group(1)), 'scenes': []}
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continue
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# 场景头
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sm = re.match(r'^(\d+-\d+)\s+(日|夜|晨|暮)\s+(内|外)\s+(.+)$', line)
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if sm:
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if current_scene and current_ep:
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current_ep['scenes'].append(current_scene)
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current_scene = {'id': sm.group(1), 'time': sm.group(2), 'loc': sm.group(3),
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'name': sm.group(4), 'characters': [], 'dialogues': [], 'descriptions': [], 'effects': []}
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continue
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if not current_scene or not current_ep:
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continue
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# 人物行: 用「)」而不是逗号做分割符
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cm = re.match(r'^人物[：:]\s*(.+)$', line)
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if cm:
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chars_raw = cm.group(1)
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# 先按「)」分割，再清理
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parts = []
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current = ''
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depth = 0
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for ch in chars_raw:
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if ch == '（' or ch == '(': depth += 1
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elif ch == '）' or ch == ')': depth -= 1
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if ch in ('，', ',', '、') and depth == 0:
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if current.strip(): parts.append(current.strip())
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current = ''
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else:
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current += ch
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if current.strip(): parts.append(current.strip())
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for part in parts:
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inner = re.match(r'(.+?)[（(](.+?)[）)]', part)
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if inner:
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current_scene['characters'].append({'name': inner.group(1).strip(), 'desc': inner.group(2).strip()})
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else:
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current_scene['characters'].append({'name': part, 'desc': ''})
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continue
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# 对话(带情绪): 角色（情绪）：台词
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dm = re.match(r'^(.+?)[（(](.+?)[）)]\s*[：:]\s*(.+)$', line)
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if dm:
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current_scene['dialogues'].append({'character': dm.group(1).strip(), 'emotion': dm.group(2).strip(), 'line': dm.group(3).strip()})
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continue
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# 对话(无情绪): 角色：台词
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dm2 = re.match(r'^(.+?)[：:]\s*(.+)$', line)
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if dm2 and not dm2.group(1).startswith('△') and not dm2.group(1).startswith('#'):
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current_scene['dialogues'].append({'character': dm2.group(1).strip(), 'emotion': '', 'line': dm2.group(2).strip()})
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continue
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# △描述/特效/特写
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if line.startswith('△') or line.startswith('【'):
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desc = line.lstrip('△').lstrip('【').strip().rstrip('】')
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current_scene['descriptions'].append(desc)
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# 特写也记录为特效
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if '特写' in line or '特寫' in line:
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current_scene['effects'].append({'type': 'closeup', 'description': desc})
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continue
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# flush
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if current_scene and current_ep:
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current_ep['scenes'].append(current_scene)
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if current_ep:
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episodes.append(current_ep)
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# 统计
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all_chars = set()
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for ep in episodes:
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for sc in ep['scenes']:
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for c in sc['characters']:
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all_chars.add(c['name'])
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for d in sc['dialogues']:
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all_chars.add(d['character'])
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return {
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'episodes': episodes,
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'characters': sorted(all_chars),
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'stats': {
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'episodes': len(episodes),
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'scenes': sum(len(ep['scenes']) for ep in episodes),
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'dialogues': sum(len(sc['dialogues']) for ep in episodes for sc in ep['scenes']),
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'characters': len(all_chars),
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}
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}
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if __name__ == '__main__':
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if len(sys.argv) < 2:
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print('Usage: python hdlp-parser.py <script.hdlp>')
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sys.exit(1)
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with open(sys.argv[1], 'r', encoding='utf-8') as f:
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text = f.read()
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result = parse_hdlp(text)
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print(json.dumps(result, ensure_ascii=False, indent=2))
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