157 lines
11 KiB
Python
157 lines
11 KiB
Python
"""
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最终修复：P1/P3/P4/P5 的能力标签+解析，使用直接 curl（tempfile 入参，无 shell 转义风险）
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"""
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import json, subprocess
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cred_file = '/root/.openclaw/credentials/xiaoyan/config.json'
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with open(cred_file) as f:
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cfg = json.load(f)
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app_id = cfg['apps'][0]['appId']
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app_secret = cfg['apps'][0]['appSecret']
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body = json.dumps({'app_id': app_id, 'app_secret': app_secret})
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r = subprocess.run(f"curl -s -X POST 'https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal' -H 'Content-Type: application/json' -d '{body}'", shell=True, capture_output=True, text=True, timeout=10)
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token = json.loads(r.stdout)['tenant_access_token']
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APP_TOKEN = 'CMHSbUUjka3TrUsaxxEc297ongf'
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def fetch(tid):
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r = subprocess.run(f"curl -s -X GET 'https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{tid}/records?page_size=500' -H 'Authorization: Bearer {token}'", shell=True, capture_output=True, text=True, timeout=15)
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return json.loads(r.stdout)
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def update(tid, rid, fields):
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tmpfile = '/tmp/bitable_fix.json'
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with open(tmpfile, 'w') as f:
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json.dump({"fields": fields}, f, ensure_ascii=False)
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r = subprocess.run(f"curl -s -X PUT 'https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{tid}/records/{rid}' -H 'Authorization: Bearer {token}' -H 'Content-Type: application/json' -d @{tmpfile}", shell=True, capture_output=True, text=True, timeout=15)
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return json.loads(r.stdout)
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# ============ P1 032501 ============
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data = fetch('tblCgfYDnnqwLfgH')
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for item in data['data']['items']:
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if item['record_id'] == 'recvjt0HzBBhYu' and item['fields'].get('题目集合 ID','') == '032501':
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jd = json.loads(item['fields']['jsonData'])
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for q in jd['first']['questionSet']:
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ab = [{'信息定位与提取':'扫读定位｜信息匹配','细节理解':'细节理解｜事实信息提取'}.get(a,a) for a in q['ability']]
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q['ability'] = ab
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resp = update('tblCgfYDnnqwLfgH', 'recvjt0HzBBhYu', {'jsonData': json.dumps(jd, ensure_ascii=False)})
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print(f"P1 032501: {'✅' if resp.get('code')==0 else '❌'+str(resp.get('msg',''))}")
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# ============ P3 032601 ============
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data = fetch('tbl4q0ZUV3HB54t1')
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for item in data['data']['items']:
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if item['record_id'] == 'recvjug1hWz2oG':
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jd = json.loads(item['fields']['jsonData'])
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TAG = {
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'信息定位':'扫读定位｜信息匹配','细节理解':'细节理解｜事实信息提取',
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'因果推断':'推理判断｜原因/结果','主旨归纳':'主旨理解｜段落/文本大意',
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'推理判断':'推理判断｜原因/结果',
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}
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# Also fix any corrupted tags by looking at original context
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# Q0: what did they plan → 细节理解｜事实信息提取
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# Q1: why late → 推理判断｜原因/结果
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# Q2: what did they do → 细节理解｜事实信息提取
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# Q3: what was favorite → 细节理解｜事实信息提取
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# Q4: what lesson → 主旨理解｜段落/文本大意
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CORRECT = [
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['扫读定位｜信息匹配', '细节理解｜事实信息提取'],
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['扫读定位｜信息匹配', '推理判断｜原因/结果'],
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['扫读定位｜信息匹配', '细节理解｜事实信息提取'],
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['扫读定位｜信息匹配', '细节理解｜事实信息提取'],
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['主旨理解｜段落/文本大意', '推理判断｜原因/结果'],
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]
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for qi, q in enumerate(jd['first']['questionSet']):
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q['ability'] = CORRECT[qi]
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resp = update('tbl4q0ZUV3HB54t1', 'recvjug1hWz2oG', {'jsonData': json.dumps(jd, ensure_ascii=False)})
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print(f"P3 032601: {'✅' if resp.get('code')==0 else '❌'+str(resp.get('msg',''))}")
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# ============ P4 032701 & 032801 ============
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EXPL_032701 = [
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"空白处需要表示赚钱的名词。get some cash 是地道表达，cash（现金）最符合学生售卖手链的情境。cheque（支票）语义过正式，bracelet（手链）是销售的商品而非获取的目标。考查名词在语境中的最佳语义选择。",
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"修饰可数名词bracelets应用many（许多）。much修饰不可数名词，only（只有）在此处语义不流畅，不符合带了一些手链去给朋友看的语境。考查可数名词数量修饰词的语法规则。",
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"表语位置需形容词。They were very popular（它们很受欢迎）才是完整句子。cash和sell均非形容词，不能直接作表语。考查词性辨别和上下文语义连贯。",
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"students是可数名词复数，需用many修饰表示很多学生。much用于不可数名词，only在so many结构后不合适。考查可数名词数量表达。",
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"bracelets是可数名词复数，需用many表示数量。didn't have many bracelets表示手链不够多，与后文promised to make more呼应。考查上下文逻辑与可数名词修饰。",
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"空白处需动词作谓语。She could sell a few（她能卖出几条）中sell是唯一动词。cheque和popular均为非动词。考查句子主干成分（谓语动词）的语法识别。",
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]
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EXPL_032801 = [
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"根据后文a local band was playing music和it was very noisy，可推断是一场派对。party最能描述这种热闹场景，car和sleep与乐队演奏、噪音等语境不符。考查名词的语境语义选择。",
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"I tried to sleep, but the sound was too loud——噪音太大导致睡不着，sleep是最合理的选择。drive和sing都偏离语境。考查动词的语义逻辑匹配。",
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"描述派对参与者身份，adult people（成年人）与午夜派对的情境相符，也为后文decided to be more understanding提供合理性。考查修饰词的语境判断。",
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"The party went on until midnight——派对持续到午夜是最符合逻辑的时间终点。morning和afternoon时间太早，不符合嘈杂派对的情境。考查时间名词的合理推断。",
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"前后分句存在转折关系：I was annoyed because I couldn't rest, but then I remembered...。but引导转折，because表示原因，so表示结果。考查连词的逻辑关系。",
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"此处需引导原因的连词。because the band members cleaned up解释为什么第二天心情好转。although表示让步，until表示时间。考查原因连词的选择。",
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]
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data = fetch('tblzKVm1FEukPgnN')
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for sid, rid, expls in [('032701','recvjueHm15HPu',EXPL_032701),('032801','recvjueN5QT1c5',EXPL_032801)]:
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for item in data['data']['items']:
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if item['record_id'] == rid:
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jd = json.loads(item['fields']['jsonData'])
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t1 = item['fields'].get('题目1','') or ''
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for qi, q in enumerate(jd['first']['questionSet']):
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q['ability'] = ['语法结构识别｜完形填空']
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q['explanation'] = expls[qi]
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# Build 题目1 with explanations
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if '【解析】' not in t1:
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t1_lines = [f"{qi+1}. {expls[qi]}" for qi in range(len(expls))]
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t1_new = t1 + '\n\n【解析】\n' + '\n'.join(t1_lines)
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else:
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t1_new = t1
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update_fields = {
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'jsonData': json.dumps(jd, ensure_ascii=False),
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'题目1': t1_new,
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}
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resp = update('tblzKVm1FEukPgnN', rid, update_fields)
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print(f"P4 {sid}: {'✅' if resp.get('code')==0 else '❌'+str(resp.get('msg',''))}")
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# ============ P5 032901 ============
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EXPL_032901_first = [
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"前后是因果关系：去野生动物园是因为想看小象。because引导原因状语从句最合适。but表示转折，so表示结果，均不符合语义。考查原因连词。",
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"had just been born是被动语态，表示刚刚出生。born是bear的过去分词，与a few weeks ago的时间状语呼应。grow up（长大）和top（顶端）语义不通。考查词义辨析与被动语态。",
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"reach the top of a tall tree——大象想够到高树的顶端。top表示顶部位置，与tall tree形成语义对应。bottom与reach矛盾，nose不是位置。考查方位词的选择。",
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"大象的长鼻子是标志性特征。nose是正确选项，banana和bottom明显不符。考查动物特征相关的核心词汇。",
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"could only touch the bottom——虽然用长鼻子去够，但只碰到了底部。bottom与top形成对比，体现够不到的落差感。考查反义词对（top↔bottom）的理解。",
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"小象吃黄色的香蕉是最自然的食物搭配。banana是常见动物投喂食物，elephant和nose均不符合吃的语义。考查动物食物相关词汇。",
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"when I grow up（等我长大）是固定表达。grow up表示成长、长大，born与when从句时态矛盾，bottom不相关。考查固定短语的掌握。",
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"根据上下文描述的美好回忆，bottom指从心底的比喻义。from the bottom of my heart是常见表达。top与情感表达不相配，nose属于干扰项。考查固定搭配和比喻义。",
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]
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EXPL_032901_second = [
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"前后分句是因果关系：姐姐喜欢美丽的东西，所以总戴首饰。so引导结果，because引导原因，but表示转折。考查结果连词。",
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"lost one of her favourite silver earrings——在首饰语境中，银色的earrings（耳环）是最典型的可丢失物品。painting和language与silver修饰和wear搭配都不符。考查语境词义推断。",
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"couldn't find it anywhere else——在否定句中else表示别的地方/其他任何地方，except含义不符，again重复逻辑不通。考查否定句中的词汇用法。",
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"I decided to make..., although I'm not very good——前后存在让步转折关系，虽然不擅长但还是决定做。although正确，because和so均表示因果。考查让步连词。",
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"She showed me how to use small silver pieces——朋友擅长的是首饰制作（jewellery），与silver pieces和earrings主题一致。painting和language偏离主题。考查上下文主题关联。",
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"I made a mistake, so I had to start again——犯错后重新开始，again表示再一次。else用于否定句表另外，except表除了。考查副词选择。",
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]
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data = fetch('tblLmUxzzUDe0QAJ')
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for item in data['data']['items']:
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if item['record_id'] == 'recvjueULrufNg':
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jd = json.loads(item['fields']['jsonData'])
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t1 = item['fields'].get('题目1','') or ''
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t2 = item['fields'].get('题目2','') or ''
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for qi, q in enumerate(jd['first']['questionSet']):
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q['ability'] = ['语法结构识别｜完形填空']
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q['explanation'] = EXPL_032901_first[qi]
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for qi, q in enumerate(jd['second']['questionSet']):
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q['ability'] = ['语法结构识别｜完形填空']
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q['explanation'] = EXPL_032901_second[qi]
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if '【解析】' not in t1:
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t1_new = t1 + '\n\n【解析】\n' + '\n'.join(f"{i+1}. {e}" for i,e in enumerate(EXPL_032901_first))
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else:
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t1_new = t1
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if '【解析】' not in t2:
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t2_new = t2 + '\n\n【解析】\n' + '\n'.join(f"{i+1}. {e}" for i,e in enumerate(EXPL_032901_second))
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else:
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t2_new = t2
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update_fields = {
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'jsonData': json.dumps(jd, ensure_ascii=False),
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'题目1': t1_new,
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'题目2': t2_new,
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}
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resp = update('tblLmUxzzUDe0QAJ', 'recvjueULrufNg', update_fields)
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print(f"P5 032901: {'✅' if resp.get('code')==0 else '❌'+str(resp.get('msg',''))}")
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