213 lines
7.6 KiB
Python
213 lines
7.6 KiB
Python
#!/usr/bin/env python3
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"""
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国家学生体质健康标准（2014年修订）— 评分数据提取脚本
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教育部发布，适用于全日制小学至大学学生
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满分120分制（100基础分 + 20附加分）
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"""
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import json, os, re, sys
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from docx import Document
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BASE = '/home/songyi/Documents/ai_agent_scraper_study/data/国家学生体质健康标准'
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DOCX = os.path.join(BASE, '01_来源数据/国家学生体质健康标准（2014年修订）.docx')
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def parse_range(val):
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"""解析值域:'13.5~18.1', '≤13.4', '≥17.9'"""
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val = val.strip().replace(' ', '').replace('\n','')
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if re.match(r'[≥>]=?\s*([\d.]+)', val):
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m = re.match(r'[≥>]=?\s*([\d.]+)', val)
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return {"min": float(m.group(1))}
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if re.match(r'[≤<]=?\s*([\d.]+)', val):
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m = re.match(r'[≤<]=?\s*([\d.]+)', val)
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return {"max": float(m.group(1))}
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if re.match(r'([\d.]+)\s*[~-]\s*([\d.]+)', val):
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m = re.match(r'([\d.]+)\s*[~-]\s*([\d.]+)', val)
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lo, hi = float(m.group(1)), float(m.group(2))
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return {"min": min(lo, hi), "max": max(lo, hi)}
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if re.match(r'(\d+)[:：·]\s*(\d+[\']?[\d.]*)', val):
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m = re.match(r'(\d+)[:：·]\s*(\d+[\']?[\d.]*)', val)
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minutes = int(m.group(1))
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rest = m.group(2).replace("'", ".")
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seconds = float(rest) if '.' in rest else int(rest)
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return {"exact": minutes * 60 + seconds}
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if re.match(r'^([\d.]+)$', val):
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m = re.match(r'^([\d.]+)$', val)
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return {"exact": float(m.group(1))}
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return {"raw": val}
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def extract_all():
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doc = Document(DOCX)
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result = {
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'metadata': {
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'title': '国家学生体质健康标准（2014年修订）',
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'publisher': '教育部',
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'year': 2014,
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'total_tables': len(doc.tables),
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'scoring_system': '100分基础 + 20分附加 = 120分满分',
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'rating_levels': {
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'优秀': {'min': 90.0},
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'良好': {'min': 80.0, 'max': 89.9},
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'及格': {'min': 60.0, 'max': 79.9},
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'不及格': {'max': 59.9}
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}
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},
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'weight_table': {},
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'scoring_tables': [],
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'bonus_tables': [],
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'registration_tables': []
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}
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for i, table in enumerate(doc.tables):
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rows_data = []
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for row in table.rows:
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cells = [cell.text.strip().replace('\n', ' ') for cell in row.cells]
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rows_data.append(cells)
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if not rows_data:
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continue
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header = rows_data[0]
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header_str = ' '.join(str(h) for h in header).strip()
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# 权重表（表0）
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if i == 0:
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for row in rows_data[1:]:
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if len(row) >= 3:
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obj = row[0].strip()
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indicator = row[1].strip()
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weight = row[2].strip()
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try:
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w = float(weight)
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result['weight_table'].setdefault(obj, {})[indicator] = w
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except ValueError:
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pass
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continue
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# 登记卡表
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if '学校签章' in header_str or ('姓名' in header_str and '性别' in header_str):
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result['registration_tables'].append({
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'table_index': i, 'rows': len(rows_data), 'cols': len(header)
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})
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continue
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# 判断加分表
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is_bonus = '加分' in header_str and '成绩' not in header_str
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# 解析年级列
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grade_cols = []
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start_col = 1 if is_bonus else 2
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for ci, h in enumerate(header):
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h_clean = h.strip().replace('\n', ' ')
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if h_clean and ci >= start_col:
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# 跳过'单项得分'列
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if '单项' in h_clean or '得分' in h_clean:
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continue
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grade_cols.append((ci, h_clean))
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if not grade_cols:
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continue
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table_info = {
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'table_index': i,
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'header_sample': [h.strip() for h in header[:5]],
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'grade_names': [g[1] for g in grade_cols],
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'type': 'bonus' if is_bonus else 'standard',
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'rows_count': len(rows_data) - 1,
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'data': []
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}
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for row in rows_data[1:]:
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if is_bonus:
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if len(row) < 2:
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continue
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bonus_str = row[0].strip()
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try:
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bonus_score = int(bonus_str) if bonus_str.lstrip('-').isdigit() else 0
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except:
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continue
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entry = {'bonus_score': bonus_score, 'grades': {}}
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for ci, gname in grade_cols:
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if ci < len(row):
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val = row[ci].strip()
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if val and val not in ['—', '-', '', '------']:
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entry['grades'][gname] = parse_range(val)
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if entry['grades']:
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table_info['data'].append(entry)
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else:
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if len(row) < 3:
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continue
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level_name = row[0].strip()
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score_str = row[1].strip()
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try:
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score_val = int(score_str) if score_str.isdigit() else 0
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except:
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continue
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entry = {'level': level_name, 'score': score_val, 'grades': {}}
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for ci, gname in grade_cols:
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if ci < len(row):
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val = row[ci].strip()
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if val and val not in ['—', '-', '', '------']:
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entry['grades'][gname] = parse_range(val)
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if entry['grades']:
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table_info['data'].append(entry)
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if table_info['data']:
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if is_bonus:
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result['bonus_tables'].append(table_info)
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else:
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result['scoring_tables'].append(table_info)
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return result
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def print_summary(data):
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m = data['metadata']
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print(f"总Word表格: {m['total_tables']}")
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print(f"标准评分表: {len(data['scoring_tables'])} 个")
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print(f"加分评分表: {len(data['bonus_tables'])} 个")
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print(f"登记卡/附表: {len(data['registration_tables'])} 个")
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wt = data['weight_table']
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print(f"\n权重表 ({len(wt)}组):")
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for obj in sorted(wt.keys()):
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items = ', '.join(f"{k}={v}%" for k, v in sorted(wt[obj].items()))
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print(f" {obj}: {items}")
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print(f"\n标准评分表:")
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for t in data['scoring_tables']:
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gn = t['grade_names']
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gs = ', '.join(gn[:3])
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if len(gn) > 3:
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gs += f"...({len(gn)}个年级)"
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levels = sorted(set(e['level'] for e in t['data']))
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ti = t['table_index']
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rc = len(t['data'])
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print(f" [表{ti}] {rc}行x{len(gn)}年级 等级={levels} 年级={gs}")
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print(f"\n加分评分表:")
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for t in data['bonus_tables']:
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gn = t['grade_names']
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gs = ', '.join(gn[:3])
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if len(gn) > 3:
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gs += f"...({len(gn)}个年级)"
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ti = t['table_index']
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rc = len(t['data'])
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print(f" [表{ti}] {rc}行 年级={gs}")
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def output_json(data):
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path = os.path.join(BASE, '02_加工数据/评分标准结构化数据.json')
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with open(path, 'w', encoding='utf-8') as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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size = os.path.getsize(path)
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print(f"\nJSON输出: {path} ({size/1024:.0f}KB)")
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return path
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if __name__ == '__main__':
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data = extract_all()
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print_summary(data)
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output_json(data)
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