266 lines
13 KiB
Python
266 lines
13 KiB
Python
#!/usr/bin/env python3
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"""Produce reading_pic_judge for 4 IDs (121301-121601), L1 A级."""
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import json, requests, time
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CRED_FILE = "/root/.openclaw/credentials/xiaoyan/config.json"
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APP_TOKEN = "CMHSbUUjka3TrUsaxxEc297ongf"
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TABLE_ID = "tblJc60aO0T163MJ"
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# ============================================================
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# ALL QUESTIONS — L1 A级, 3-4词极简句, L1词汇
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# ============================================================
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ALL_DATA = {}
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# ---- 121301 ----
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ALL_DATA["121301"] = {
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"first": [
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{"qi": "121301-00.png", "q": "These are houses.", "a": "Yes",
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"x": "图上有三栋房子，句子说「这些是房子」，匹配。"},
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{"qi": "121301-01.png", "q": "This is a home.", "a": "No",
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"x": "图上是一个橱柜，不是家(home)，句子与图片不匹配。"},
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{"qi": "121301-02.png", "q": "This is a sofa.", "a": "Yes",
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"x": "图上是一张沙发，句子说「这是一张沙发」，匹配。"},
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{"qi": "121301-03.png", "q": "These are cupboards.", "a": "No",
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"x": "图上是一间卧室放着一张床，句子说「这些是橱柜」，与图片不匹配。"},
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{"qi": "121301-04.png", "q": "This is a bedroom.", "a": "Yes",
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"x": "图上是一间有床的卧室，句子说「这是一间卧室」，匹配。"},
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],
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"second": [
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{"qi": "121301-05.png", "q": "This is a zoo.", "a": "Yes",
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"x": "图上是动物园入口，能看到动物，句子说「这是一个动物园」，匹配。"},
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{"qi": "121301-06.png", "q": "This is a hippo.", "a": "Yes",
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"x": "图上是一只河马在水里，句子说「这是一只河马」，匹配。"},
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{"qi": "121301-07.png", "q": "This is a bear.", "a": "No",
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"x": "图上是一条牛仔裤，不是熊(bear)，句子与图片不匹配。"},
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{"qi": "121301-08.png", "q": "These are jeans.", "a": "Yes",
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"x": "图上是一条牛仔裤，句子说「这些是牛仔裤」，匹配。"},
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{"qi": "121301-09.png", "q": "This is a sock.", "a": "No",
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"x": "图上是一只大棕熊在森林里，不是袜子(sock)，句子与图片不匹配。"},
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],
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}
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# ---- 121401 ----
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ALL_DATA["121401"] = {
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"first": [
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{"qi": "121401-00.png", "q": "These are students.", "a": "Yes",
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"x": "图上是几个学生坐在教室里，句子说「这些是学生」，匹配。"},
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{"qi": "121401-01.png", "q": "This is a school.", "a": "Yes",
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"x": "图上是一所学校建筑，句子说「这是一所学校」，匹配。"},
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{"qi": "121401-02.png", "q": "This is a teacher.", "a": "No",
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"x": "图上是几支蜡笔，不是老师(teacher)，句子与图片不匹配。"},
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{"qi": "121401-03.png", "q": "These are crayons.", "a": "Yes",
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"x": "图上是几支彩色蜡笔放在桌上，句子说「这些是蜡笔」，匹配。"},
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{"qi": "121401-04.png", "q": "These are boards.", "a": "No",
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"x": "图上是一位老师在讲桌前，不是黑板(board)，句子与图片不匹配。"},
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],
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"second": [
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{"qi": "121401-05.png", "q": "This is a mat.", "a": "Yes",
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"x": "图上是一张地板上的垫子，句子说「这是一张垫子」，匹配。"},
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{"qi": "121401-06.png", "q": "This is a letter.", "a": "No",
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"x": "图上是一张课桌上面有台灯，不是信(letter)，句子与图片不匹配。"},
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{"qi": "121401-07.png", "q": "This is a desk.", "a": "Yes",
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"x": "图上是一张课桌，句子说「这是一张课桌」，匹配。"},
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{"qi": "121401-08.png", "q": "This is a schoolbag.", "a": "No",
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"x": "图上是一个女士手提包，不是书包(schoolbag)，句子与图片不匹配。"},
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{"qi": "121401-09.png", "q": "This is a handbag.", "a": "Yes",
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"x": "图上是一个手提包，句子说「这是一个手提包」，匹配。"},
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],
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}
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# ---- 121501 ----
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ALL_DATA["121501"] = {
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"first": [
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{"qi": "121501-00.png", "q": "This is a body.", "a": "Yes",
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"x": "图上是一个孩子的全身，句子说「这是一个身体」，匹配。"},
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{"qi": "121501-01.png", "q": "This is a head.", "a": "No",
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"x": "图上是一张嘴的特写，不是头(head)，句子与图片不匹配。"},
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{"qi": "121501-02.png", "q": "These are mouths.", "a": "No",
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"x": "图上是两个孩子在玩耍（朋友），不是嘴(mouth)，句子与图片不匹配。"},
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{"qi": "121501-03.png", "q": "This is an ear.", "a": "Yes",
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"x": "图上是一只耳朵的特写，句子说「这是一只耳朵」，匹配。"},
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{"qi": "121501-04.png", "q": "These are friends.", "a": "Yes",
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"x": "图上是两个小朋友在一起玩，句子说「这些是朋友」，匹配。"},
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],
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"second": [
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{"qi": "121501-05.png", "q": "This is a camera.", "a": "Yes",
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"x": "图上是一台相机，句子说「这是一台相机」，匹配。"},
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{"qi": "121501-06.png", "q": "This is a boy.", "a": "Yes",
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"x": "图上是一个小男孩，句子说「这是一个男孩」，匹配。"},
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{"qi": "121501-07.png", "q": "This is a girl.", "a": "No",
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"x": "图上是一个滑板，不是女孩(girl)，句子与图片不匹配。"},
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{"qi": "121501-08.png", "q": "These are skateboards.", "a": "No",
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"x": "图上是一个女孩在滑滑板，句子说「这些是滑板」但图中只有一个，且重点是人在滑板动作，与句子描述不符。"},
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{"qi": "121501-09.png", "q": "This is a skateboard.", "a": "Yes",
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"x": "图上是一个滑板，句子说「这是一个滑板」，匹配。"},
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],
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}
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# ---- 121601 ----
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ALL_DATA["121601"] = {
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"first": [
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{"qi": "121601-00.png", "q": "It is summer.", "a": "Yes",
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"x": "图上是阳光海滩夏天场景，句子说「现在是夏天」，匹配。"},
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{"qi": "121601-01.png", "q": "It is autumn.", "a": "No",
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"x": "图上是冬天白雪覆盖的场景，不是秋天(autumn)，句子与图片不匹配。"},
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{"qi": "121601-02.png", "q": "It is winter.", "a": "Yes",
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"x": "图上是一片雪景，句子说「现在是冬天」，匹配。"},
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{"qi": "121601-03.png", "q": "It is cold.", "a": "Yes",
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"x": "图上是一个孩子穿着厚棉衣冬天场景，句子说「天气冷」，匹配。"},
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{"qi": "121601-04.png", "q": "It is spring.", "a": "No",
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"x": "图上是秋天落叶满地，不是春天(spring)，句子与图片不匹配。"},
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],
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"second": [
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{"qi": "121601-05.png", "q": "This is a bus.", "a": "Yes",
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"x": "图上是一辆公交车，句子说「这是一辆公交车」，匹配。"},
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{"qi": "121601-06.png", "q": "This is a taxi.", "a": "No",
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"x": "图上是一条长裤，不是出租车(taxi)，句子与图片不匹配。"},
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{"qi": "121601-07.png", "q": "These are trousers.", "a": "Yes",
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"x": "图上是一条长裤，句子说「这些是长裤」，匹配。"},
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{"qi": "121601-08.png", "q": "These are shorts.", "a": "No",
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"x": "图上是白雪皑皑的下雪场景，不是短裤(shorts)，句子与图片不匹配。"},
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{"qi": "121601-09.png", "q": "This is snow.", "a": "Yes",
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"x": "图上是一片雪景，句子说「这是雪」，匹配。"},
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],
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}
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# ============================================================
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# Build JSON
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# ============================================================
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def build_json(qid, groups):
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return {
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"first": {
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"category": "reading",
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"type": "reading_pic_judge",
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"questionSetID": qid,
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"textTitle": "Look and read. Put a tick (Yes) or a cross (No) in the box.",
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"questionSet": [
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{
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"questionImage": item["qi"],
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"question": item["q"],
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"answerText": item["a"],
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"ability": ["图文匹配"],
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"explanation": item["x"],
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}
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for item in groups["first"]
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],
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},
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"second": {
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"category": "reading",
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"type": "reading_pic_judge",
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"questionSetID": qid,
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"textTitle": "Look and read. Put a tick (Yes) or a cross (No) in the box.",
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"questionSet": [
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{
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"questionImage": item["qi"],
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"question": item["q"],
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"answerText": item["a"],
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"ability": ["图文匹配"],
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"explanation": item["x"],
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}
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for item in groups["second"]
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],
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},
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}
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# ============================================================
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# Get token & find existing records
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# ============================================================
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with open(CRED_FILE) as f:
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cred = json.load(f)
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app_id = cred["apps"][0]["appId"]
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app_secret = cred["apps"][0]["appSecret"]
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token_resp = requests.post(
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"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
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json={"app_id": app_id, "app_secret": app_secret},
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)
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token = token_resp.json()["tenant_access_token"]
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# Find existing records
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resp = requests.get(
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f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records?page_size=20",
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headers={"Authorization": f"Bearer {token}"},
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)
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record_map = {}
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for item in resp.json()["data"]["items"]:
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fid = item["fields"].get("题目集合 ID", "")
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if fid in ALL_DATA:
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record_map[fid] = item["record_id"]
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print(f"Found: {fid} → {item['record_id']}")
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# ============================================================
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# Update each record with real jsonData
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# ============================================================
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for qid in sorted(ALL_DATA.keys()):
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rid = record_map.get(qid)
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if not rid:
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print(f"❌ {qid}: no existing record, creating new...")
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resp = requests.post(
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f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records",
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headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
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json={"fields": {"题目集合 ID": qid, "dataStatus": "0"}},
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)
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rid = resp.json()["data"]["record"]["record_id"]
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print(f" Created: {rid}")
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time.sleep(1.0)
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json_data = build_json(qid, ALL_DATA[qid])
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json_str = json.dumps(json_data, ensure_ascii=False)
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# Verify balance
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for grp in ("first", "second"):
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qs = json_data[grp]["questionSet"]
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yc = sum(1 for q in qs if q["answerText"] == "Yes")
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nc = sum(1 for q in qs if q["answerText"] == "No")
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print(f" {qid} {grp}: {yc}Y/{nc}N, json={len(json_str)}chars")
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# Update
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resp = requests.put(
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f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{rid}",
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headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
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json={"fields": {"jsonData": json_str}},
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)
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code = resp.json().get("code")
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print(f" Update: code={code}")
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time.sleep(0.5)
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# ============================================================
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# Wait & Verify
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# ============================================================
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print("\nWaiting 15s for verification...")
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time.sleep(15)
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token_resp = requests.post(
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"https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
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json={"app_id": app_id, "app_secret": app_secret},
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)
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token = token_resp.json()["tenant_access_token"]
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print("\n=== Final Verification ===")
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all_ok = True
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for qid in sorted(ALL_DATA.keys()):
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rid = record_map.get(qid)
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resp = requests.get(
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f"https://open.feishu.cn/open-apis/bitable/v1/apps/{APP_TOKEN}/tables/{TABLE_ID}/records/{rid}",
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headers={"Authorization": f"Bearer {token}"},
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)
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jd = resp.json()["data"]["record"]["fields"].get("jsonData", "")
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try:
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j = json.loads(jd)
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fq = len(j["first"]["questionSet"])
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sq = len(j["second"]["questionSet"])
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if fq == 5 and sq == 5:
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fq1 = j["first"]["questionSet"][0]["question"]
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sq1 = j["second"]["questionSet"][0]["question"]
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fy = sum(1 for q in j["first"]["questionSet"] if q["answerText"] == "Yes")
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fn = sum(1 for q in j["first"]["questionSet"] if q["answerText"] == "No")
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print(f"✅ {qid}: first={fq}q({fy}Y{fn}N) second={sq}q | Q1='{fq1}' | SQ1='{sq1}'")
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else:
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print(f"❌ {qid}: first={fq}q second={sq}q | jd={len(jd)}chars")
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all_ok = False
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except Exception as e:
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print(f"❌ {qid}: PARSE_ERROR {e} | jd={len(jd)}chars")
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all_ok = False
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print(f"\n{'✅ ALL VERIFIED' if all_ok else '❌ SOME CORRUPTED'}")
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