def wxbt_init_question(openid: str):
"""
生成一个current记录, 返回current对象本身
所有current记录到同一个用户上（[email protected], user_id: 5dfa0c005e3dd462f4755877）
另外创建字段记录其openid
"""
current_test = BtCurrentTestModel()
current_test.user_id = WxBtConfig.wx_user_id
current_test.openid = openid
current_test.test_start_time = datetime.datetime.utcnow()
current_test.questions = {}
xuanzeti = QuestionModel.objects(index=WxBtConfig.xuanzeti_index).first()
i = 1
for t in xuanzeti.questions:
tmp = {
"type": 4,
"content": t['text'],
"options": [{
"key": a,
"value": b
} for a, b in t['options'].items()],
"index": i
}
current_test.questions.update({str(i): tmp})
i += 1
q1 = QuestionModel.objects(index=WxBtConfig.q8_index).first()
q2 = QuestionModel.objects(index=WxBtConfig.q9_index).first()
q = q1
_upload_url = wxbt_gen_upload_url(openid, i)
_upload_url = 'audio/0-bt-christmas2019/8.m4a'
q_current = CurrentQuestionEmbed(q_id=str(q.id),
q_type=q.q_type,
q_text=q.text,
wav_upload_url=_upload_url,
file_location='BOS',
status='url_fetched')
current_test.questions.update({str(i): q_current})
q.update(inc__used_times=1) # update
i += 1
q = q2
_upload_url = wxbt_gen_upload_url(openid, i)
_upload_url = 'audio/0-bt-christmas2019/9.m4a'
q_current = CurrentQuestionEmbed(q_id=str(q.id),
q_type=q.q_type,
q_text=q.text,
wav_upload_url=_upload_url,
file_location='BOS',
status='url_fetched')
current_test.questions.update({str(i): q_current})
q.update(inc__used_times=1) # update
i += 1
# save
current_test.save()
return current_test
def admin_get_question():
question_index = int(request.form.get("questionId")) # todo: change api and param name
questions = QuestionModel.objects(index=question_index)
if len(questions) == 0:
resp = {"needDisplay": True, "tip": "没有此题号"}
return jsonify(errors.error(resp))
question = questions[0]
if question["q_type"] != 2:
resp = {"needDisplay": True, "tip": "暂时只支持题型2"}
return jsonify(errors.error(resp))
# 生成测试
test = CurrentTestModel()
test.user_id = str(current_user.id)
test.test_start_time = datetime.datetime.utcnow()
q_current = CurrentQuestionEmbed(q_id=str(question.id), q_type=question.q_type, q_text=question.text,
wav_upload_url='', wav_temp_url='')
test.questions = {"1": q_current}
test.save()
# 保存test id
# print("[DEBUG] save test id in session when admin get question, test id: %s" % test.id.__str__())
current_app.logger.debug("save test id in session when admin get question, test id: %s" % test.id.__str__())
session["test_id"] = test.id.__str__()
# wrap question
context = {"questionType": question.q_type,
"questionNumber": 1,
"questionLimitTime": ExamConfig.question_limit_time[question.q_type],
"lastQuestion": True,
"readLimitTime": ExamConfig.question_prepare_time[question.q_type],
"questionInfo": QuestionConfig.question_type_tip[question.q_type],
"questionContent": question.text
}
return jsonify(errors.success(json.dumps(context)))
def get_score_of_specific_questions(index):
"""获取某题目的成绩情况
:param index: 题号ID
:return: 该问题的成绩情况
"""
current_app.logger.info('get_score_of_specific_questions ' + index)
cur_question = QuestionModel.objects(index=index).first()
if not cur_question:
return jsonify(errors.Score_criteria_not_exist)
all_answers = AnalysisModel.objects(question_num=index).order_by('date')
if len(all_answers) == 0:
return jsonify(errors.Score_no_data)
mapper = DateMapper()
result_by_date = __generate_result_from_dict(
mapper.map_answers(all_answers), 'date')
result_all = []
for answer in all_answers:
result_all.append(
_generate_total_score(answer['score_key'], answer['score_detail']))
return jsonify(
errors.success({
'resultByDate': result_by_date,
'allResult': result_all
}))
def start_auto_optimize():
question_num = request.form.get("questionNum")
settings = json.loads(request.form.get("settings"))
print("start_auto_optimize: questionNum: " + str(question_num))
print(settings)
# 重新计算某道题目所有人的击中向量
question = QuestionModel.objects(index=question_num).first()
if not question:
return jsonify(errors.Question_not_exist)
analysis = Analysis()
analysis.re_analysis(question)
# 根据击中向量优化参数
analysis_list = AnalysisModel.objects(question_num=question_num).order_by(
'score_key') # !!!从低到高排序
if len(analysis_list) == 0:
return jsonify(errors.success(OptimizeConfig.EMPTY_SCORE_DATA))
key_hit_mat = []
for a in analysis_list:
key_hit_mat.append(a['key_hits'])
detail_hit_mat = []
analysis_list = analysis_list.order_by('score_detail') # !!!从低到高排序
for a in analysis_list:
detail_hits = reduce(lambda x, y: x + y, a['detail_hits'])
detail_hit_mat.append(detail_hits)
algorithm = GradientDescent(
) if settings['algorithm'] == 'gradient' else NormalEquation()
key_y = algorithm.get_gaussian_array(settings['keyMean'],
settings['keySigma'],
len(key_hit_mat))
detail_y = algorithm.get_gaussian_array(settings['detailMean'],
settings['detailSigma'],
len(detail_hit_mat))
settings[
'theta'] = question['weights']['key'] if settings['reuse'] else None
# 调用优化方法
key_theta, key_j = algorithm.optimize_param(key_hit_mat, key_y, settings)
detail_theta, detail_j = algorithm.optimize_param(detail_hit_mat, detail_y,
settings)
# 存储优化结果
question['weights']['key'] = key_theta
question['weights']['detail'] = detail_theta
question['last_optimize_time'] = datetime.datetime.utcnow()
question['auto_optimized'] = True
question.save()
# 存储cost
optimize = OptimizeModel()
optimize['question_num'] = question_num
optimize['wordbase'] = question['wordbase']
optimize['weights'] = question['weights']
optimize['key_history_cost'] = key_j
optimize['detail_history_cost'] = detail_j
optimize['complete_time'] = datetime.datetime.utcnow()
optimize['finish'] = True
optimize.save()
return jsonify(errors.success())
def collect_history_to_analysis():
"""将 current 表中新出现的已评分分析的题目搬运到 analysis
"""
print('[collect_history_to_analysis] start')
history_list = HistoryTestModel.objects()
for question in QuestionModel.objects(q_type=2).order_by('index'):
collect(question, history_list)
print('[collect_history_to_analysis] end')
def get_weight_data():
question_num = request.args.get("questionNum")
print("get_weight_data: questionNum: " + str(question_num))
question = QuestionModel.objects(index=question_num).first()
if not question:
return jsonify(errors.Question_not_exist)
data = __question2weight(question)
data['allHitTimes'] = len(AnalysisModel.objects(question_num=question_num))
# return jsonify(errors.success(mock_data.weight_data))
print(errors.success(data))
return jsonify(errors.success(data))
def get_cached_questions(q_type):
key = 'cached_questions:type_%s' % q_type
all_qs_bytes = redis_client.get(key)
if all_qs_bytes:
return pickle.loads(all_qs_bytes)
d = {'q_type': q_type, 'index': {'$lte': 10000}}
questions = QuestionModel.objects(__raw__=d).order_by(
'used_times') # 按使用次数倒序获得questions
cached_qs = []
for q in questions:
cached_qs.append(q)
redis_client.set(key, pickle.dumps(cached_qs), ex=7200, nx=True)
return cached_qs
def post(self):
'''
질문 검색
'''
uuid = request.json['uuid']
Quest = QuestionModel.objects(uuid=uuid).first()
name = QuestionModel.objects(uuid=uuid).first()
Num = 0
append_Dict = dict()
QNA_LIST = list()
if Quest is None:
abort(406)
for q in Quest['question']:
QNA_LIST.append((
Quest['question'][q]['question'],
Quest['question'][q]['answer']
))
Str = {
'title': str(name['name']),
'list': {
}
}
while True:
if not QNA_LIST:
break
else:
append_Dict[Num] = {'question': QNA_LIST[0][0], 'answer': QNA_LIST[0][1]}
del QNA_LIST[0]
Num += 1
Str['list'] = dict(append_Dict)
return jsonify(Str)
def update_weight():
question_num = request.form.get('questionNum')
weight = json.loads(request.form.get("weight"))
print("update_weight: questionNum: " + str(question_num))
print(weight)
question = QuestionModel.objects(index=question_num).first()
if not question:
return jsonify(errors.Question_not_exist)
question['weights']['key'] = weight['keyWeight']
question['weights']['detail'] = weight['detailWeight']
question['last_optimize_time'] = datetime.datetime.utcnow()
question.save()
# return jsonify(errors.success(mock_data.weight_data))
return jsonify(errors.success(__question2weight(question)))
def post(self):
user_id = get_jwt_identity()
uuid = request.json['uuid']
user = UserModel.objects(id=user_id).first()
if user is None:
abort(406)
quest_uuid = QuestionModel.objects(uuid=uuid).first()
if not quest_uuid['name'] == user_id:
abort(409)
pass
def post(self):
'''
문제 테이블 생성 및 수정
'''
user_identity = get_jwt_identity()
quest_uuid = request.json['uuid']
quest_name = request.json['title']
quest_list = request.json['list']
find = QuestionModel.objects(uuid=quest_uuid).first()
user = UserModel.objects(id=user_identity).first()
if user is None:
abort(406)
if find is None:
quest = {}
for a in quest_list:
quest[a] = {
'question': quest_list[str(a)]['q'],
'answer': quest_list[str(a)]['a']
}
QuestionModel(
gar=quest_uuid,
uuid=quest_uuid,
name=quest_name,
user=user_identity,
question=quest,
).save()
else:
quest = {}
for a in quest_list:
quest[a] = {
'question': quest_list[str(a)]['q'],
'answer': quest_list[str(a)]['a']
}
find.update(question=quest)
return {'uuid': quest_uuid}, 201
def post(self):
'''
유저 검색
'''
Num = 0
append_Dict = dict()
uuid_name_List = list()
search_user = request.json['search_id']
user = UserModel.objects(id=search_user).first()
QList = QuestionModel.objects(user=search_user).all()
if user is None:
abort(406)
for q in QList:
uuid_name_List.append((q['uuid'], q['name']))
Str = {
'user': {
'id': user['id'],
'name': user['name']
},
'workbook' : {
}
}
while True:
if not uuid_name_List:
break
else:
append_Dict[Num] = {'name': uuid_name_List[0][1], 'uuid': uuid_name_List[0][0]}
del uuid_name_List[0]
Num += 1
Str['workbook'] = dict(append_Dict)
return jsonify(Str)
def admin_get_result():
current_app.logger.info("admin_get_result: user_name: " + session.get("user_name", "NO USER"))
current_test_id = session.get("test_id")
tests = CurrentTestModel.objects(id=current_test_id)
if len(tests) == 0:
current_app.logger.error("upload_file ERROR: No Tests!, test_id: %s" % current_test_id)
return jsonify(errors.Exam_not_exist)
questions = tests[0]['questions']
if len(questions) == 0:
current_app.logger.error("upload_file ERROR: No Questions!, test_id: %s" % current_test_id)
return jsonify(errors.Exam_not_exist)
question = questions.get("1")
if question['status'] == 'finished':
score = question["score"]
raw_question = QuestionModel.objects(id=question.q_id)[0]
context = {"main": score["main"],
"detail": score["detail"],
"total": score["main"] * 0.7 + score["detail"] * 0.3,
"rcgText": question["feature"]["rcg_text"],
"text": question["q_text"],
"rcgKeyWords": question["feature"]["keywords"],
"keyWords": raw_question["wordbase"]["keywords"],
"rcgMainWords": question["feature"]["mainwords"],
"mainWords": raw_question["wordbase"]["mainwords"],
"rcgDetailWords": question["feature"]["detailwords"],
"detailWords": raw_question["wordbase"]["detailwords"]
}
result = json.dumps({"status": "Success", "result": context})
elif question['status'] not in ['none', 'url_fetched', 'handling']:
return jsonify(errors.Audio_process_failed)
else:
result = json.dumps({"status": "InProcess"})
return jsonify(errors.success(result))
def question_type4_test():
q = QuestionModel.objects(index=10001).first()
print(q)
print(q.questions)