145 lines
5.4 KiB
Python
145 lines
5.4 KiB
Python
"""
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最终审校：单元挑战听力全部表格（P1-P7除P3）
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"""
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import json, urllib.request
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APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
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CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
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STD_HEARING_TAGS = {
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"显性事实理解｜关键词识别", "显性事实理解｜单句信息点抓取",
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"基础语境理解｜场景/物品/动作识别", "显性细节理解｜数字/时间/地点",
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"同义替换识别｜词/短语级", "目的/偏好识别｜显性 to/for/like",
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"干扰抑制｜多信息筛选", "语用推断｜否定与纠错",
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"多句保持｜信息整合", "情绪/态度理解", "长对话理解｜主旨+细节",
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}
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def get_token():
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with open(CRED_FILE) as f:
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cfg = json.load(f)
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req = urllib.request.Request(
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"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
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data=json.dumps({"app_id": cfg['apps'][0]['appId'], "app_secret": cfg['apps'][0]['appSecret']}).encode(),
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headers={"Content-Type": "application/json"})
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return json.loads(urllib.request.urlopen(req).read())['tenant_access_token']
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def api_call(url):
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token = get_token()
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req = urllib.request.Request(url, headers={"Authorization": f"Bearer {token}"})
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return json.loads(urllib.request.urlopen(req).read())
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tables = {
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"P1": ("tbliZAhcc9C43B23", "listening_choicePic"),
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"P2": ("tblzTLNH7f13uWQN", "listening_tableCloze"),
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"P4": ("tblVmeDtBDKsAEfz", "listening_choiceShort"),
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"P5": ("tblDssVmhGzc3UKd", "listening_matchInfo"),
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"P6": ("tbloiMcD0sBtGSTq", "listening_choicePic"),
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"P7": ("tbly9SvPEa44k3yX", "listening_drag"),
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}
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results = {}
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for name, (tid, etype) in tables.items():
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url = f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{tid}/records?page_size=100"
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resp = api_call(url)
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items = resp['data']['items']
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ok = 0
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missing_expl = 0
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bad_tags = 0
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json_err = 0
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empty = 0
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single_group = 0
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skip_010199 = 0
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for item in items:
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sid = item['fields'].get('题目集合 ID', '')
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if '010199' in str(sid):
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skip_010199 += 1
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continue
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jd_str = item['fields'].get('jsonData', '')
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if not jd_str or jd_str == 'None':
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empty += 1
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continue
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try:
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jd = json.loads(jd_str)
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except:
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json_err += 1
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continue
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has_issues = False
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# Check first/second questionSet
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for section in ['first', 'second']:
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sect = jd.get(section, {})
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if not sect:
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continue
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# Check section-level explanation (P5 style)
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if 'explanation' in sect:
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if not sect['explanation']:
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missing_expl += 1
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has_issues = True
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# Check section-level ability (P5 style)
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if 'ability' in sect and isinstance(sect['ability'], list):
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for a in sect['ability']:
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a_clean = a.split('¥¥')[0].strip()
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if a_clean not in STD_HEARING_TAGS:
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bad_tags += 1
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has_issues = True
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# Check question-level
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qs = sect.get('questionSet', [])
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if not qs:
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continue
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for q in qs:
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# Explanation
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if not q.get('explanation'):
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missing_expl += 1
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has_issues = True
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# Ability
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for a in q.get('ability', []):
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if isinstance(a, str):
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a_clean = a.split('¥¥')[0].strip()
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if a_clean not in STD_HEARING_TAGS:
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bad_tags += 1
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has_issues = True
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# Check root questionSet (P6 style)
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qs = jd.get('questionSet', [])
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for q in qs:
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if not q.get('explanation'):
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missing_expl += 1
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has_issues = True
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for a in q.get('ability', []):
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if isinstance(a, str) and a.split('¥¥')[0].strip() not in STD_HEARING_TAGS:
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bad_tags += 1
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has_issues = True
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# Check single group
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has_first = jd.get('first', {}).get('questionSet') or jd.get('first', {}).get('answerSet')
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has_second = jd.get('second', {}).get('questionSet')
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if has_first and not has_second and jd.get('second') is not None:
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single_group += 1
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if not has_issues:
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ok += 1
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results[name] = {
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'total': len(items), 'skip_010199': skip_010199, 'empty': empty,
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'ok': ok, 'missing_expl': missing_expl, 'bad_tags': bad_tags,
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'json_err': json_err, 'single_group': single_group
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}
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print(f"{'Table':<8} {'Total':>5} {'Skip':>5} {'Empty':>5} {'Pass':>5} {'!Expl':>5} {'!Tag':>5} {'!JSON':>5} {'1Grp':>5}")
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print("-" * 58)
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for name in ["P1","P2","P4","P5","P6","P7"]:
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r = results[name]
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print(f"{name:<8} {r['total']:>5} {r['skip_010199']:>5} {r['empty']:>5} {r['ok']:>5} {r['missing_expl']:>5} {r['bad_tags']:>5} {r['json_err']:>5} {r['single_group']:>5}")
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print(f"\nTotal: OK={sum(r['ok'] for r in results.values())}, MissingExpl={sum(r['missing_expl'] for r in results.values())}, BadTags={sum(r['bad_tags'] for r in results.values())}, JSONerr={sum(r['json_err'] for r in results.values())}")
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