91 lines
4.6 KiB
Python
91 lines
4.6 KiB
Python
import sys, os, re, json
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sys.stdout.reconfigure(encoding='utf-8')
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md_files = [
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("공통_제1장", "resources/knowledge/original/원가계산/건설공사_표준품셈/01_공통부문/제1장_적용기준.md"),
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("공통_제3장", "resources/knowledge/original/원가계산/건설공사_표준품셈/01_공통부문/제3장_토공사.md"),
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("공통_제4장", "resources/knowledge/original/원가계산/건설공사_표준품셈/01_공통부문/제4장_조경공사.md"),
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("공통_제6장", "resources/knowledge/original/원가계산/건설공사_표준품셈/01_공통부문/제6장_철근콘크리트공사.md"),
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("토목_제1장", "resources/knowledge/original/원가계산/건설공사_표준품셈/02_토목부문/제1장_도로포장공사.md"),
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("토목_제6장", "resources/knowledge/original/원가계산/건설공사_표준품셈/02_토목부문/제6장_관부설및접합공사.md"),
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("건축_제9장", "resources/knowledge/original/원가계산/건설공사_표준품셈/03_건축부문/제9장_미장공사.md"),
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("유지관리_제1장", "resources/knowledge/original/원가계산/건설공사_표준품셈/05_유지관리부문/제1장_공통.md"),
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("유지관리_제3장", "resources/knowledge/original/원가계산/건설공사_표준품셈/05_유지관리부문/제3장_건축.md"),
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]
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report = {}
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for label, path in md_files:
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if not os.path.exists(path):
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continue
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with open(path, 'r', encoding='utf-8') as f:
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lines = f.readlines()
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print(f"\n=======================================================")
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print(f"Scanning {label} ({os.path.basename(path)}) - {len(lines)} lines")
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file_issues = {
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"attached_section_headers": [],
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"collapsed_table_rows": [],
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"attached_notes_tail": [],
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"page_transition_artifacts": []
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}
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for idx, line in enumerate(lines):
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line_num = idx + 1
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line_clean = line.strip()
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# 1. Attached section headers: e.g. text ending immediately with 1-2-2 or 3-4-1 without newline
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m_sec = re.findall(r'([^\s#\-\*\>\|])(\d+-\d+(?:-\d+)?)', line)
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for prev_char, sec_num in m_sec:
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# check if it looks like a real section header
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if prev_char not in ['제', '표', '·', '(', '/', '-', ',', ':']:
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file_issues["attached_section_headers"].append({
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"line": line_num,
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"prev_char": prev_char,
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"sec_num": sec_num,
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"snippet": line_clean[:120]
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})
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# 2. Collapsed table rows: table row with extreme length or multiple repeated patterns in single cell
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if line_clean.startswith('|') and line_clean.endswith('|'):
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cells = [c.strip() for c in line_clean.split('|')[1:-1]]
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for c in cells:
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# if cell has multiple words separated by space that look like collapsed table rows (e.g. 5 or more items)
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tokens = c.split()
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if len(tokens) >= 15:
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file_issues["collapsed_table_rows"].append({
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"line": line_num,
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"token_count": len(tokens),
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"snippet": c[:100] + "..."
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})
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break
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# 3. Page transition artifacts: e.g. "→4공통부문" or "3제1장 적용기준"
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m_page = re.findall(r'(?:→\d+|\d+제\d+장|\d+공통부문|\d+토목부문|\d+건축부문|\d+유지관리부문)', line)
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if m_page:
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file_issues["page_transition_artifacts"].append({
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"line": line_num,
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"artifacts": m_page,
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"snippet": line_clean[:100]
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})
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# 4. Attached notes tail: [주] ending with next section immediately
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if '[주]' in line or '주]' in line:
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m_tail = re.findall(r'(\[주\].*?)(\d+-\d+)', line)
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if m_tail:
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file_issues["attached_notes_tail"].append({
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"line": line_num,
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"snippet": line_clean[:100]
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})
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print(f" - Attached section headers: {len(file_issues['attached_section_headers'])}")
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print(f" - Collapsed table rows: {len(file_issues['collapsed_table_rows'])}")
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print(f" - Attached notes tails: {len(file_issues['attached_notes_tail'])}")
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print(f" - Page transition artifacts: {len(file_issues['page_transition_artifacts'])}")
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report[label] = file_issues
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with open('scratch/const_md_flaws_scan.json', 'w', encoding='utf-8') as f:
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json.dump(report, f, ensure_ascii=False, indent=2)
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