mvp.py 31 KB

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  1. from mysql_db import MysqlDB
  2. from excel_util import ExcelUtil
  3. import time
  4. from entity import PeopleInfo
  5. class Mvp:
  6. """
  7. ce mvp 答题数据统计
  8. 城市特例 北京市,上海市, 重庆市,天津市
  9. """
  10. age_dict = {
  11. '00-04年生': '95后',
  12. '05-09年生': '05后',
  13. '50-59年生': '50后',
  14. '60-69年生': '60后',
  15. '70-74年生': '70后',
  16. '75-79年生': '75后',
  17. '80-84年生': '80后',
  18. '85-89年生': '85后',
  19. '90-94年生': '85后',
  20. '95-99年生': '95后'
  21. }
  22. age_list = ['85后', '95后']
  23. city_list = ['上海市', '上海周边']
  24. tag_table = {
  25. '用户画像-审美偏好': ['mvp_crowd_info_aesthetic_preference', 'aesthetic_preference'],
  26. '用户画像-行为兴趣': ['mvp_crowd_info_behavior', 'behavioral_interest'],
  27. '用户画像-观念': ['mvp_crowd_info_consumer_concept', 'consumer_concept'],
  28. '用户画像-社交模式': ['mvp_crowd_info_social_mode', 'social_module'],
  29. '用户画像-行业': ['mvp_crowd_info_trade', 'trade'],
  30. '用户画像-出行方式': ['mvp_crowd_info_trip_mode', 'trip_mode'],
  31. '空间需求图谱-色相': ['mvp_innovate_space_color_prefer', 'color'],
  32. '空间需求图谱-精装关注点': ['mvp_innovate_space_hardcover_focus', 'hardcover_focus'],
  33. '空间需求图谱-色调': ['mvp_innovate_space_hue_prefer', 'hue'],
  34. '空间需求图谱-单品偏好': ['mvp_innovate_space_item_preference', 'item_preference'],
  35. '空间需求图谱-材质': ['mvp_innovate_space_material_prefer', 'material'],
  36. '空间需求图谱-空间特性偏好': ['mvp_innovate_space_space_prefer', 'space_preference'],
  37. '模块分数': ['mvp_crowd_info_module', 'module_name']
  38. }
  39. crowd_info_1 = {
  40. '1973': 'A',
  41. '1974': 'B',
  42. '1975': 'C',
  43. '1976': 'D',
  44. '1977': 'E',
  45. '1978': 'F',
  46. '1979': 'G',
  47. '1813': 'A',
  48. '1814': 'B',
  49. '1815': 'C',
  50. '1816': 'D',
  51. '1817': 'E',
  52. '1818': 'F',
  53. '1819': 'G'
  54. }
  55. base_insert_sql = 'insert into {}(crowd_info_id, {}, standard_value, status) values(%s, %s, %s, ' \
  56. '1) '
  57. def get_table_name(self, name):
  58. """
  59. 获取表名
  60. :param name:
  61. :return:
  62. """
  63. params = self.tag_table.get(name)
  64. if params:
  65. return self.tag_table.get(name)[0]
  66. def get_insert_sql(self, tag_type_name):
  67. """
  68. 根据标签分类名称获取相应表的插入sql
  69. :param tag_type_name:
  70. :return:
  71. """
  72. params = self.tag_table.get(tag_type_name)
  73. if params:
  74. return self.base_insert_sql.format(params[0], params[1])
  75. crowd = ['A', 'B', 'C', 'D', 'E', 'F']
  76. # 获取答题记录中城市列表
  77. sql_1 = 'select city from f_t_daren_score_2 group by city'
  78. # 获取父选项和父题id
  79. sql_2 = 'select a.id, a.content, b.id, b.name from bq_option a left join bq_question b on a.question_id = b.id ' \
  80. 'where a.serial_number = %s and b.serial_number = %s and a.status = b.status = 1 '
  81. # 获取答题人的年龄段集合
  82. sql_4 = 'select nld from f_t_daren_score_2 group by nld'
  83. # 根据城市,年龄段,人群分类统计答题记录数
  84. sql_5 = 'select testcase_id, COUNT(uuid) from f_t_daren_score_2 where uuid in %s group by testcase_id '
  85. # 根据父选项获取子选项id列表
  86. sql_6 = '''
  87. SELECT
  88. c.id,
  89. c.sub_question_id,
  90. c.content
  91. FROM
  92. bq_sub_option c
  93. WHERE
  94. c.father_id IN (
  95. SELECT
  96. a.id
  97. FROM
  98. bq_option a
  99. LEFT JOIN bq_question b ON a.question_id = b.id
  100. WHERE
  101. a.serial_number = % s
  102. AND b.serial_number = % s
  103. AND a. STATUS = 1
  104. AND b. STATUS = 1
  105. )
  106. AND c. STATUS = 1
  107. '''
  108. # 根据子题id获取包含子题id的测试
  109. sql_7 = 'select id from bq_testcase where status = 1 and FIND_IN_SET(%s, question_ids)'
  110. # 根据子选项id统计答题数
  111. sql_8 = '''
  112. SELECT
  113. count(1)
  114. FROM
  115. f_t_daren_score_2 a
  116. LEFT JOIN d_shangju_tiku_02 b ON a.sub_question_id = b.sub_question_id
  117. AND (
  118. a.score = b.score
  119. OR a.score = b.sub_option_id
  120. )
  121. AND a.testcase_id = b.testcase_id
  122. WHERE
  123. b.sub_option_id IN % s
  124. AND a.uuid IN % s
  125. '''
  126. # 获取一个uuid下答题的子选项id列表
  127. sql_10 = 'select DISTINCT uuid, GROUP_CONCAT(DISTINCT b.sub_option_id) from f_t_daren_score_2 a left join ' \
  128. 'd_shangju_tiku_02 b on a.sub_question_id = b.sub_question_id and (a.score = b.score or a.score = ' \
  129. 'b.sub_option_id) where a.status = ' \
  130. 'b.status = 1 group by uuid '
  131. # 向表mvp_crowd_info插入数据
  132. sql_11 = 'insert into mvp_crowd_info(age_area, city_name, crowd_type, status) values(%s, %s, %s, 1)'
  133. # 向表mvp_crowd_info_behavior中插入数据
  134. sql_12 = 'insert into mvp_crowd_info_behavior(crowd_info_id, behavioral_interest, standard_value, status) values(' \
  135. '%s, %s, ' \
  136. '%s, 1) '
  137. # 向表mvp_crowd_info_module中插入数据
  138. sql_13 = 'insert into mvp_crowd_info_module(crowd_info_id, module_name, standard_value, status) values (%s, %s, ' \
  139. '%s, 1) '
  140. sql_14 = 'select a.id, a.age_area, a.city_name, a.crowd_type from mvp_crowd_info a where a.status = 1'
  141. # 获取答题城市信息from city
  142. sql_15 = '''
  143. SELECT
  144. a.uuid,
  145. IFNULL(GROUP_CONCAT(DISTINCT a.city, a.province), 00) AS city,
  146. IFNULL(GROUP_CONCAT(DISTINCT a.nld), 00) AS nld,
  147. IFNULL(GROUP_CONCAT(DISTINCT a.sex), 00) AS sex,
  148. IFNULL(GROUP_CONCAT(DISTINCT b.sub_option_id), 00) as sub_option_ids,
  149. IFNULL(GROUP_CONCAT(DISTINCT a.testcase_id), 00) as testcase_ids
  150. FROM
  151. f_t_daren_score_2 a
  152. LEFT JOIN d_shangju_tiku_02 b ON a.testcase_id = b.testcase_id
  153. WHERE
  154. a.testcase_id = b.testcase_id
  155. AND a.sub_question_id = b.sub_question_id
  156. AND (
  157. a.score = b.score
  158. OR a.score = b.sub_option_id
  159. )
  160. GROUP BY
  161. a.uuid
  162. '''
  163. # 根据用户uuid获取城市信息
  164. sql_16 = '''
  165. SELECT
  166. a.uuid,
  167. b.sub_option_content
  168. FROM
  169. f_t_daren_score_2 a
  170. LEFT JOIN d_shangju_tiku_02 b ON a.testcase_id = b.testcase_id
  171. WHERE
  172. a.sub_question_id = b.sub_question_id
  173. AND (
  174. a.score = b.score
  175. OR a.score = b.sub_option_id
  176. )
  177. AND a.uuid = %s
  178. AND b.father_id = 249
  179. AND a. STATUS = b. STATUS = 1
  180. '''
  181. # 答题人人群分类信息
  182. sql_17 = '''
  183. SELECT
  184. a.uuid,
  185. b.sub_option_id
  186. FROM
  187. f_t_daren_score_2 a
  188. LEFT JOIN d_shangju_tiku_02 b ON a.testcase_id = b.testcase_id
  189. WHERE
  190. a.sub_question_id = b.sub_question_id
  191. AND (
  192. a.score = b.score
  193. OR a.score = b.sub_option_id
  194. )
  195. AND a.uuid = %s
  196. AND b.father_id = 236
  197. AND a.STATUS = b.STATUS = 1
  198. '''
  199. sql_18 = '''
  200. DELETE
  201. FROM
  202. mvp_crowd_info_behavior
  203. WHERE
  204. crowd_info_id not IN (
  205. SELECT
  206. GROUP_CONCAT(id)
  207. FROM
  208. mvp_crowd_info
  209. WHERE
  210. city_name = '上海市'
  211. AND age_area = '85后'
  212. AND STATUS = 1
  213. )
  214. '''
  215. """
  216. 数据debug SQL
  217. 1:
  218. SELECT
  219. c.id,
  220. c.sub_question_id,
  221. c.content
  222. FROM
  223. bq_sub_option c
  224. WHERE
  225. c.father_id IN (
  226. SELECT
  227. a.id
  228. FROM
  229. bq_option a
  230. LEFT JOIN bq_question b ON a.question_id = b.id
  231. WHERE
  232. a.serial_number ='FA001'
  233. AND b.serial_number = 'F00245'
  234. AND a. STATUS = 1
  235. AND b. STATUS = 1
  236. )
  237. AND c.STATUS = 1
  238. 2:
  239. select id from bq_testcase where status = 1 and FIND_IN_SET(%s, question_ids)
  240. 3:
  241. SELECT
  242. count(1)
  243. FROM
  244. f_t_daren_score_2 a
  245. LEFT JOIN d_shangju_tiku_02 b ON a.sub_question_id = b.sub_question_id
  246. AND (
  247. a.score = b.score
  248. OR a.score = b.sub_option_id
  249. )
  250. AND a.testcase_id = b.testcase_id
  251. WHERE
  252. b.sub_option_id IN (1964,1965,1966,1967,1968,1969,1970,1971,1972)
  253. """
  254. def __init__(self, path=None):
  255. self.shangju_db = MysqlDB('shangju')
  256. self.marketing_db = MysqlDB('bi_report')
  257. # self.shangju_db.truncate('mvp_standard_score')
  258. self.tag_data = ExcelUtil(file_name=path).init_mvp_data()
  259. self.crowd_info = ExcelUtil(file_name=path, sheet_name='选项-人群分类对应表').init_crowd_info()
  260. self.citys = self.init_city()
  261. self.age = self.init_age()
  262. self.people_sub_option_ids = self.marketing_db.select(self.sql_10)
  263. self.crowd_contain_sub_option_ids = self.get_crowd_contain_sub_option_ids()
  264. self.module_scores = ExcelUtil(file_name='set-behavior-tag.xlsx', sheet_name='算法关系表').init_module_info()
  265. # self.scores_tag = ExcelUtil(file_name='行为与模块分值汇总.xlsx', sheet_name='行为').init_scores()
  266. # self.score_module = ExcelUtil(file_name='行为与模块分值汇总.xlsx', sheet_name='模块').init_scores()
  267. self.scores_tag = None
  268. self.score_module = None
  269. def close(self):
  270. self.shangju_db.close()
  271. self.marketing_db.close()
  272. def init_city(self):
  273. """
  274. 获取答题数据中的城市。
  275. :return:
  276. """
  277. citys = ['上海市', '上海周边']
  278. # citys_info = self.marketing_db.select(self.sql_1)
  279. # citys.extend([x[0] for x in citys_info if x[0] is not None])
  280. return citys
  281. def query_behavioral_info(self, city=None, age=None, crowd=None):
  282. """
  283. 查询行为兴趣信息
  284. :return:
  285. """
  286. # datas = []
  287. # for key in self.tag_data.keys():
  288. # values = self.tag_data[key]
  289. # for value in values:
  290. # question = value[0].split('-')[0]
  291. # option = value[0].split('-')[1]
  292. # corr = value[1]
  293. # data = self.shangju_db.select(self.sql_2, [option, question])
  294. # if len(data) > 0:
  295. # print([question, option, data[0][3], data[0][1], key, corr])
  296. # datas.append([question, option, data[0][3], data[0][1], key, corr])
  297. # self.shangju_db.truncate('mvp_question_classification')
  298. # self.shangju_db.add_some(self.sql_3, datas)
  299. scores_behavioral = self.city_age_crowd(city, age, crowd)
  300. # scores_module = self.module_score(crowd, city, age, scores_behavioral['score'])
  301. # result = {'行为兴趣分值': scores_behavioral['score'], '模块分值': scores_module}
  302. print('update finished!!!')
  303. return scores_behavioral
  304. def people_info(self):
  305. """
  306. 答题人个人信息获取
  307. :return:
  308. """
  309. people_info_city = self.marketing_db.select(self.sql_15)
  310. people_infos = []
  311. for people in people_info_city:
  312. uuid = people[0]
  313. city = people[1]
  314. nld = people[2]
  315. sex = people[3]
  316. sub_option_ids_1 = people[4]
  317. testcaseid = people[5]
  318. if str(city).find('市') != -1:
  319. city = str(city).split('市')[0] + '市'
  320. if str(nld).find(',') != -1:
  321. nld_1 = list(str(nld).split(','))
  322. if len(nld_1) > 0:
  323. nld = nld_1[0]
  324. else:
  325. pass
  326. crowd = []
  327. if testcaseid:
  328. testcastids = list(map(int, str(testcaseid).split(',')))
  329. if len(testcastids) > 0:
  330. gt_75 = [x for x in testcastids if x > 74]
  331. if len(gt_75) > 0:
  332. # 从答题结果中获取城市信息
  333. citys = self.marketing_db.select(self.sql_16, [uuid])
  334. if len(citys) > 0:
  335. city = '上海市' if citys[0][1] == '一线' else '上海周边'
  336. # 根据用户子选项id集合,获取用户的人群分类
  337. if len(gt_75) > 0:
  338. # 特定的测试人群分类从答题结果中获取
  339. sub_option_ids = self.marketing_db.select(self.sql_17, [uuid])
  340. for option in sub_option_ids:
  341. crowd_type = self.crowd_info_1.get(option[1])
  342. if crowd_type:
  343. crowd.append(crowd_type)
  344. else:
  345. crowd.append('A')
  346. else:
  347. if sub_option_ids_1 is not None:
  348. crowd.extend(self.get_people_uuid_by_sub_option_ids(sub_option_ids_1))
  349. if city is None:
  350. city = '上海市'
  351. people_info = PeopleInfo(uuid, city, nld, sex, crowd)
  352. people_infos.append(people_info)
  353. # people_infos.append([uuid, city, nld, sex, crowd])
  354. return people_infos
  355. def people_filter(self, city, nld, crowd):
  356. uuids = []
  357. for people in self.people_info_1:
  358. if people.city == city and people.age == nld and crowd in people.crowd:
  359. uuids.append(people.uuid)
  360. return uuids
  361. def get_people_uuid_by_sub_option_ids(self, sub_ids):
  362. types = []
  363. for key in self.crowd_contain_sub_option_ids.keys():
  364. type_sub_option_ids = self.crowd_contain_sub_option_ids[key]
  365. sub_option_ids = list(map(int, str(sub_ids).split(',')))
  366. # list(set(a).intersection(set(b)))
  367. if len(list(set(sub_option_ids).intersection(set(type_sub_option_ids)))) > 0 and key not in types:
  368. types.append(key)
  369. return types
  370. def update_data(self):
  371. """
  372. 定时更新分值
  373. :return:
  374. """
  375. self.insert_table = []
  376. self.linshi_db = MysqlDB('linshi', db_type=1)
  377. for city in self.city_list:
  378. for age in self.age_list:
  379. for crowd in self.crowd:
  380. result = self.city_age_crowd(city, age, crowd)
  381. self.insert_score_to_db(result)
  382. print('{}数据关系完成...'.format(time.time()))
  383. def insert_score_to_db(self, scores):
  384. """
  385. 行为、模块分数写入数据库
  386. :return:
  387. """
  388. ids = self.query_data()
  389. behavior_score = scores['behavior_score']
  390. module_score = scores['module_score']
  391. module_insert_sql = self.get_insert_sql('模块分数')
  392. if module_insert_sql:
  393. module_insert_data = []
  394. for module in module_score:
  395. city_2 = module[0]
  396. age_2 = module[1]
  397. crowd_2 = module[2]
  398. module_name_2 = module[3]
  399. module_score_2 = module[4]
  400. for id in ids:
  401. city_1 = id[2]
  402. age_1 = id[1]
  403. crowd_1 = id[3]
  404. id_1 = id[0]
  405. if city_2 == city_1 and age_2 == age_1 and crowd_2 == crowd_1:
  406. module_insert_data.append([id_1, module_name_2, module_score_2])
  407. # 先清空之前的数据
  408. if len(module_insert_data) > 0:
  409. table_name = self.get_table_name('模块分数')
  410. if table_name is not None and table_name not in self.insert_table:
  411. self.linshi_db.truncate(table_name)
  412. self.linshi_db.add_some(module_insert_sql, module_insert_data)
  413. self.insert_table.append(table_name)
  414. print('模块分数更新完成...')
  415. for b_score in behavior_score:
  416. for key in b_score.keys():
  417. insert_sql = self.get_insert_sql(key)
  418. if insert_sql:
  419. insert_data = []
  420. score = b_score[key]
  421. for data in score:
  422. city = data[0]
  423. age = data[1]
  424. tag_name = data[2]
  425. crowd = data[3]
  426. tag_score = data[4]
  427. if key == '用户画像-行为兴趣' and city == '上海市' and age == '85后':
  428. pass
  429. else:
  430. for id in ids:
  431. city_1 = id[2]
  432. age_1 = id[1]
  433. crowd_1 = id[3]
  434. id_1 = id[0]
  435. if city == city_1 and age == age_1 and crowd == crowd_1:
  436. insert_data.append([id_1, tag_name, tag_score])
  437. if len(insert_data) > 0:
  438. table_name = self.get_table_name(key)
  439. if table_name and table_name not in self.insert_table:
  440. if table_name == 'mvp_crowd_info_behavior':
  441. self.linshi_db.delete(self.sql_18)
  442. else:
  443. self.linshi_db.truncate(table_name)
  444. self.linshi_db.add_some(insert_sql, insert_data)
  445. self.insert_table.append(table_name)
  446. else:
  447. print('未找到对应的表,数据无法插入...')
  448. print('行为分数更新完成...')
  449. def module_score(self, crowd, city, age, scores):
  450. """
  451. 模块分数计算
  452. 城市 年龄 人群分类 模块名称 分数
  453. :return:
  454. """
  455. # import json
  456. # print(json.dumps(scores, ensure_ascii=False))
  457. modules = self.module_scores[crowd]
  458. result = []
  459. for key in modules.keys():
  460. values = modules[key]
  461. module_name = key
  462. score = 0
  463. for value in values:
  464. behavioral_name = value[0]
  465. weight = float(value[2])
  466. standard_score = [x[4] for x in scores if x[2] == behavioral_name]
  467. if len(standard_score) > 0:
  468. score += standard_score[0] * weight
  469. result.append([city, age, crowd, module_name, score])
  470. return result
  471. # def insert_data(self, scores_behavioral, scores_module):
  472. def insert(self):
  473. """
  474. 计算数据写入数据库中,供接口查看
  475. :return:
  476. """
  477. infos = []
  478. for city in self.city_list:
  479. for age in self.age_list:
  480. for c_type in self.crowd:
  481. age_area = self.age_dict.get(age)
  482. if age_area:
  483. infos.append([age_area, city, c_type])
  484. self.shangju_db.add_some(self.sql_11, infos)
  485. def query_data(self):
  486. ids = self.linshi_db.select(self.sql_14)
  487. return ids
  488. def shanghai_85_module_score_insert(self):
  489. """
  490. 上海市,85后模块分数计算
  491. :return:
  492. """
  493. result = []
  494. for crowd in self.crowd:
  495. modules = self.module_scores[crowd]
  496. for key in modules.keys():
  497. values = modules[key]
  498. module_name = key
  499. score = 0
  500. for value in values:
  501. behavioral_name = value[0]
  502. weight = float(value[2])
  503. # standard_score = [x[4] for x in scores if x[2] == behavioral_name]
  504. standard_score = float(value[1])
  505. if standard_score is not None:
  506. score += standard_score * weight
  507. result.append(['上海市', '85后', crowd, module_name, score])
  508. return {'score': result, 'data': self.module_scores}
  509. def tag_module_score_insert(self):
  510. """
  511. 标签模块分数写入数据库
  512. :return:
  513. """
  514. ids = self.query_data()
  515. insert_data = []
  516. insert_data_1 = []
  517. for tag, module in zip(self.scores_tag, self.score_module):
  518. city = tag[0]
  519. age = tag[1]
  520. crowd = tag[2]
  521. tag_name = tag[3]
  522. tag_score = tag[4]
  523. city_2 = module[0]
  524. age_2 = module[1]
  525. crowd_2 = module[2]
  526. module_name_2 = module[3]
  527. module_score_2 = module[4]
  528. for id in ids:
  529. city_1 = id[2]
  530. age_1 = id[1]
  531. crowd_1 = id[3]
  532. id_1 = id[0]
  533. if city == city_1 and self.age_dict[age] == age_1 and crowd == crowd_1:
  534. insert_data.append([id_1, tag_name, tag_score])
  535. if city_2 == city_1 and self.age_dict[age_2] == age_1 and crowd_2 == crowd_1:
  536. insert_data_1.append([id_1, module_name_2, module_score_2])
  537. self.shangju_db.add_some(self.sql_12, insert_data)
  538. self.shangju_db.add_some(self.sql_13, insert_data_1)
  539. def init_age(self):
  540. """
  541. 获取答题数据中的年龄
  542. """
  543. return ['95后', '85后']
  544. # age_info = self.marketing_db.select(self.sql_4)
  545. # # print([x[0] for x in age_info])
  546. # return [x[0] for x in age_info if x[0] is not None]
  547. def city_age_crowd(self, city=None, age=None, crowd=None):
  548. data_start = []
  549. result = []
  550. module_scores = []
  551. self.people_info_1 = self.people_info()
  552. if city is not None and age is not None and crowd is not None:
  553. print('获取指定城市,年龄段,人群类型的数据...')
  554. # people_uuids = self.get_people_uuid_by_type(crowd)
  555. people_uuids = self.people_filter(city, age, crowd)
  556. behavior_data = None
  557. if len(people_uuids) > 0:
  558. print('{}-{}-{}'.format(city, age, crowd))
  559. datas = self.behavior_tag_init(city, age, people_uuids)
  560. data_start.append(datas)
  561. all_data, behavior_data_1 = self.calculation_standard_score(datas, city, age, crowd)
  562. result.append(all_data)
  563. behavior_data = behavior_data_1
  564. if behavior_data:
  565. module_scores.extend(self.module_score(crowd, city, age, behavior_data))
  566. # data_list = []
  567. # for e in data_start:
  568. # for key in e.keys():
  569. # values = e[key]
  570. # for sub_e in values:
  571. # ele = [key]
  572. # ele.extend(sub_e)
  573. # data_list.append(ele)
  574. # pass
  575. return {'behavior_score': result, 'module_score': module_scores}
  576. # return {'score': result, 'data': data_list}
  577. def scores(self):
  578. behavior_score = []
  579. module_scores = []
  580. for city in self.city_list:
  581. for age in self.age_list:
  582. for crowd in self.crowd:
  583. data = self.city_age_crowd(city, age, crowd)
  584. behavior_score.extend(data['behavior_score'])
  585. module_scores.extend(data['module_score'])
  586. return {'behavior_score': behavior_score, 'module_score': module_scores}
  587. def behavior_tag_init(self, city, age, people_uuids):
  588. result = {}
  589. self.group_type_count = self.marketing_db.select(self.sql_5, [people_uuids])
  590. # 表名
  591. for key in self.tag_data.keys():
  592. values = self.tag_data[key]
  593. result_sub = {}
  594. # 标签
  595. for key_tag_name in values.keys():
  596. questions = values[key_tag_name]
  597. elements = []
  598. for value in questions:
  599. question = value[0].split('-')[0]
  600. option = value[0].split('-')[1]
  601. corr = value[1]
  602. fz, fm = self.molecular_value(question, option, city, age, people_uuids)
  603. if fm == 0:
  604. c = 0
  605. else:
  606. c = fz / fm
  607. elements.append([question, option, corr, fz, fm, c])
  608. result_sub[key_tag_name] = elements
  609. result[key] = self.indicator_calculation_d_e(result_sub)
  610. return result
  611. def molecular_value(self, queston, option, city, age, people_uuids):
  612. # 获取当前父选项包含的子选项id和子题id列表
  613. result = self.shangju_db.select(self.sql_6, [option, queston])
  614. sub_option_ids = []
  615. group_types = []
  616. for rt in result:
  617. sub_option_id, sub_question_id, content = rt[0], rt[1], rt[2]
  618. grouptypes = self.shangju_db.select(self.sql_7, [sub_question_id])
  619. for g_t in grouptypes:
  620. if str(g_t[0]) not in group_types:
  621. group_types.append(str(g_t[0]))
  622. sub_option_ids.append(sub_option_id)
  623. # 计算子选项在答题记录中的点击数
  624. sub_options_count = 0
  625. if len(sub_option_ids) > 0:
  626. result_1 = self.marketing_db.select(self.sql_8, [sub_option_ids, people_uuids])
  627. sub_options_count = result_1[0][0]
  628. # 计算父选项包含的子选项对应的子题所在的测试gt包含的点击数。
  629. denominator_value = 0
  630. for info in self.group_type_count:
  631. if str(info[0]) in group_types:
  632. denominator_value += info[1]
  633. return sub_options_count, denominator_value
  634. def indicator_calculation_d_e(self, data):
  635. result = {}
  636. for key in data.keys():
  637. values = data[key]
  638. c_list = []
  639. for x in values:
  640. _x = x[5]
  641. if _x is not None and x != 0:
  642. c_list.append(_x)
  643. fm_list = [x[4] for x in values]
  644. sum_c = sum(fm_list)
  645. if len(c_list) == 0:
  646. min_c = 0
  647. else:
  648. min_c = min(c_list)
  649. elements = []
  650. for value in values:
  651. _value = []
  652. c = value[5]
  653. if sum_c == 0:
  654. d = 0
  655. else:
  656. d = c / sum_c
  657. e = c - min_c
  658. _value.extend(value)
  659. _value.append(d)
  660. _value.append(e)
  661. elements.append(_value)
  662. result[key] = elements
  663. return result
  664. def calculation_standard_score(self, datas, city, age, crowd_type):
  665. scores = {}
  666. for key_tag_type in datas.keys():
  667. print(key_tag_type)
  668. tag_type_data = datas[key_tag_type]
  669. scores_sub = []
  670. for key_tag in tag_type_data.keys():
  671. key_tag_data = tag_type_data[key_tag]
  672. print(key_tag)
  673. print(' 父题序号 父选项序号 相关系系数 分子值 分母值 百分比 人数权重 偏离值')
  674. values = [x[5] for x in key_tag_data]
  675. min_c = min(values)
  676. f = min_c
  677. for value in key_tag_data:
  678. print(' {}'.format(value))
  679. if value[2] is not None and value[7] is not None:
  680. f += float(value[2] * value[7])
  681. print(' 标准分:{}'.format(f))
  682. scores_sub.append([city, age, key_tag, crowd_type, f])
  683. scores[key_tag_type] = scores_sub
  684. # self.shangju_db.add_some(self.sql_9, scores)
  685. return scores, scores['用户画像-行为兴趣']
  686. def people_data(self):
  687. result = self.people_info()
  688. a = 0
  689. b = 0
  690. c = 0
  691. d = 0
  692. e = 0
  693. f = 0
  694. result_1 = []
  695. for rt in result:
  696. crowds = rt.crowd
  697. if rt.uuid in [
  698. 'ae9db26b-3606-497c-83c5-56341d487a91',
  699. '9fb33b6c-bd7a-4114-b225-3ee380943517',
  700. '84636488-1307-47fe-a238-4f9cf279a908',
  701. '4a5b6654-eb99-46ed-8dcf-777648d6baca',
  702. 'ba181da0-c91a-4430-84c6-9612a693f659',
  703. '32eae583-474c-4dca-8b36-d74314f45cee',
  704. 'b07f6ff2-ccd5-44ee-9b7c-b2e1f40d777f',
  705. '149a0e40-5639-4771-8a27-60821e14a1d5',
  706. '4795b731-3e75-4f08-90bc-8ee4a0c366c6',
  707. '4795b731-3e75-4f08-90bc-8ee4a0c366c6',
  708. '47cbd398-1c39-4dc0-8d97-98fe19457516']:
  709. result_1.append([rt.uuid, rt.city, rt.age, rt.crowd])
  710. if 'A' in crowds:
  711. a += 1
  712. if 'B' in crowds:
  713. b += 1
  714. if 'C' in crowds:
  715. c += 1
  716. if 'D' in crowds:
  717. d += 1
  718. if 'E' in crowds:
  719. e += 1
  720. if 'F' in crowds:
  721. f += 1
  722. return result_1
  723. # return {'A': a, 'B': b, 'C': b, 'D': d, 'E': e, 'F': f}
  724. def get_crowd_people(self):
  725. result = {}
  726. for type in self.crowd:
  727. uuids = self.get_people_uuid_by_type(type)
  728. result[type] = len(uuids)
  729. return result
  730. def get_people_uuid_by_type(self, type):
  731. uuids = []
  732. type_sub_option_ids = self.crowd_contain_sub_option_ids[type]
  733. for people in self.people_sub_option_ids:
  734. uuid = people[0]
  735. sub_option_ids = list(map(int, str(people[1]).split(',')))
  736. # list(set(a).intersection(set(b)))
  737. if len(list(set(sub_option_ids).intersection(set(type_sub_option_ids)))) > 0 and uuid not in uuids:
  738. uuids.append(uuid)
  739. return uuids
  740. def get_crowd_contain_sub_option_ids(self):
  741. """
  742. 获取ABCDEF人群包含的子选项id
  743. :return:
  744. """
  745. infos = {}
  746. for key in self.crowd_info.keys():
  747. values = self.crowd_info[key]
  748. sub_option_ids = []
  749. for value in values:
  750. if value is not None:
  751. vals = str(value).split('-')
  752. option, question = vals[1], vals[0]
  753. query_result = self.shangju_db.select(self.sql_6, [option, question])
  754. for qr in query_result:
  755. sub_option_id, sub_question_id, content = qr[0], qr[1], qr[2]
  756. sub_option_ids.append(int(sub_option_id))
  757. infos[key] = sub_option_ids
  758. return infos
  759. if __name__ == '__main__':
  760. pass