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 and testcase_id > 74 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 id > 74 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 and a.testcase_id > 74
  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. and a.testcase_id > 74
  161. GROUP BY
  162. a.uuid
  163. '''
  164. # 根据用户uuid获取城市信息
  165. sql_16 = '''
  166. SELECT
  167. a.uuid,
  168. b.sub_option_content
  169. FROM
  170. f_t_daren_score_2 a
  171. LEFT JOIN d_shangju_tiku_02 b ON a.testcase_id = b.testcase_id
  172. WHERE
  173. a.sub_question_id = b.sub_question_id
  174. AND (
  175. a.score = b.score
  176. OR a.score = b.sub_option_id
  177. )
  178. AND a.uuid = %s
  179. AND b.father_id = 249
  180. AND a. STATUS = b. STATUS = 1
  181. '''
  182. # 答题人人群分类信息
  183. sql_17 = '''
  184. SELECT
  185. a.uuid,
  186. b.sub_option_id
  187. FROM
  188. f_t_daren_score_2 a
  189. LEFT JOIN d_shangju_tiku_02 b ON a.testcase_id = b.testcase_id
  190. WHERE
  191. a.sub_question_id = b.sub_question_id
  192. AND (
  193. a.score = b.score
  194. OR a.score = b.sub_option_id
  195. )
  196. AND a.uuid = %s
  197. AND b.father_id = 236
  198. AND a.STATUS = b.STATUS = 1
  199. '''
  200. sql_18 = '''
  201. DELETE
  202. FROM
  203. mvp_crowd_info_behavior
  204. WHERE
  205. crowd_info_id not IN (
  206. SELECT
  207. GROUP_CONCAT(id)
  208. FROM
  209. mvp_crowd_info
  210. WHERE
  211. city_name = '上海市'
  212. AND age_area = '85后'
  213. AND STATUS = 1
  214. )
  215. '''
  216. """
  217. 数据debug SQL
  218. 1:
  219. SELECT
  220. c.id,
  221. c.sub_question_id,
  222. c.content
  223. FROM
  224. bq_sub_option c
  225. WHERE
  226. c.father_id IN (
  227. SELECT
  228. a.id
  229. FROM
  230. bq_option a
  231. LEFT JOIN bq_question b ON a.question_id = b.id
  232. WHERE
  233. a.serial_number ='FA001'
  234. AND b.serial_number = 'F00245'
  235. AND a. STATUS = 1
  236. AND b. STATUS = 1
  237. )
  238. AND c.STATUS = 1
  239. 2:
  240. select id from bq_testcase where status = 1 and FIND_IN_SET(%s, question_ids)
  241. 3:
  242. SELECT
  243. count(1)
  244. FROM
  245. f_t_daren_score_2 a
  246. LEFT JOIN d_shangju_tiku_02 b ON a.sub_question_id = b.sub_question_id
  247. AND (
  248. a.score = b.score
  249. OR a.score = b.sub_option_id
  250. )
  251. AND a.testcase_id = b.testcase_id
  252. WHERE
  253. b.sub_option_id IN (1964,1965,1966,1967,1968,1969,1970,1971,1972)
  254. """
  255. def __init__(self, path=None):
  256. self.shangju_db = MysqlDB('shangju')
  257. self.marketing_db = MysqlDB('bi_report')
  258. # self.shangju_db.truncate('mvp_standard_score')
  259. self.tag_data = ExcelUtil(file_name=path).init_mvp_data()
  260. self.crowd_info = ExcelUtil(file_name=path, sheet_name='选项-人群分类对应表').init_crowd_info()
  261. self.citys = self.init_city()
  262. self.age = self.init_age()
  263. self.people_sub_option_ids = self.marketing_db.select(self.sql_10)
  264. self.crowd_contain_sub_option_ids = self.get_crowd_contain_sub_option_ids()
  265. self.module_scores = ExcelUtil(file_name='set-behavior-tag.xlsx', sheet_name='算法关系表').init_module_info()
  266. # self.scores_tag = ExcelUtil(file_name='行为与模块分值汇总.xlsx', sheet_name='行为').init_scores()
  267. # self.score_module = ExcelUtil(file_name='行为与模块分值汇总.xlsx', sheet_name='模块').init_scores()
  268. self.scores_tag = None
  269. self.score_module = None
  270. def close(self):
  271. self.shangju_db.close()
  272. self.marketing_db.close()
  273. def init_city(self):
  274. """
  275. 获取答题数据中的城市。
  276. :return:
  277. """
  278. citys = ['上海市', '上海周边']
  279. # citys_info = self.marketing_db.select(self.sql_1)
  280. # citys.extend([x[0] for x in citys_info if x[0] is not None])
  281. return citys
  282. def query_behavioral_info(self, city=None, age=None, crowd=None):
  283. """
  284. 查询行为兴趣信息
  285. :return:
  286. """
  287. # datas = []
  288. # for key in self.tag_data.keys():
  289. # values = self.tag_data[key]
  290. # for value in values:
  291. # question = value[0].split('-')[0]
  292. # option = value[0].split('-')[1]
  293. # corr = value[1]
  294. # data = self.shangju_db.select(self.sql_2, [option, question])
  295. # if len(data) > 0:
  296. # print([question, option, data[0][3], data[0][1], key, corr])
  297. # datas.append([question, option, data[0][3], data[0][1], key, corr])
  298. # self.shangju_db.truncate('mvp_question_classification')
  299. # self.shangju_db.add_some(self.sql_3, datas)
  300. scores_behavioral = self.city_age_crowd(city, age, crowd)
  301. # scores_module = self.module_score(crowd, city, age, scores_behavioral['score'])
  302. # result = {'行为兴趣分值': scores_behavioral['score'], '模块分值': scores_module}
  303. print('update finished!!!')
  304. return scores_behavioral
  305. def people_info(self):
  306. """
  307. 答题人个人信息获取
  308. :return:
  309. """
  310. people_info_city = self.marketing_db.select(self.sql_15)
  311. people_infos = []
  312. for people in people_info_city:
  313. uuid = people[0]
  314. city = people[1]
  315. nld = people[2]
  316. sex = people[3]
  317. sub_option_ids_1 = people[4]
  318. testcaseid = people[5]
  319. if str(city).find('市') != -1:
  320. city = str(city).split('市')[0] + '市'
  321. if str(nld).find(',') != -1:
  322. nld_1 = list(str(nld).split(','))
  323. if len(nld_1) > 0:
  324. nld = nld_1[0]
  325. else:
  326. pass
  327. crowd = []
  328. if testcaseid:
  329. testcastids = list(map(int, str(testcaseid).split(',')))
  330. if len(testcastids) > 0:
  331. gt_75 = [x for x in testcastids if x > 74]
  332. if len(gt_75) > 0:
  333. # 从答题结果中获取城市信息
  334. citys = self.marketing_db.select(self.sql_16, [uuid])
  335. if len(citys) > 0:
  336. city = '上海市' if citys[0][1] == '一线' else '上海周边'
  337. # 根据用户子选项id集合,获取用户的人群分类
  338. if len(gt_75) > 0:
  339. # 特定的测试人群分类从答题结果中获取
  340. sub_option_ids = self.marketing_db.select(self.sql_17, [uuid])
  341. for option in sub_option_ids:
  342. crowd_type = self.crowd_info_1.get(option[1])
  343. if crowd_type:
  344. crowd.append(crowd_type)
  345. else:
  346. crowd.append('A')
  347. else:
  348. if sub_option_ids_1 is not None:
  349. crowd.extend(self.get_people_uuid_by_sub_option_ids(sub_option_ids_1))
  350. if city is None:
  351. city = '上海市'
  352. people_info = PeopleInfo(uuid, city, nld, sex, crowd)
  353. people_infos.append(people_info)
  354. # people_infos.append([uuid, city, nld, sex, crowd])
  355. return people_infos
  356. def people_filter(self, city, nld, crowd):
  357. uuids = []
  358. for people in self.people_info_1:
  359. if people.city == city and people.age == nld and crowd in people.crowd:
  360. uuids.append(people.uuid)
  361. return uuids
  362. def get_people_uuid_by_sub_option_ids(self, sub_ids):
  363. types = []
  364. for key in self.crowd_contain_sub_option_ids.keys():
  365. type_sub_option_ids = self.crowd_contain_sub_option_ids[key]
  366. sub_option_ids = list(map(int, str(sub_ids).split(',')))
  367. # list(set(a).intersection(set(b)))
  368. if len(list(set(sub_option_ids).intersection(set(type_sub_option_ids)))) > 0 and key not in types:
  369. types.append(key)
  370. return types
  371. def update_data(self):
  372. """
  373. 定时更新分值
  374. :return:
  375. """
  376. self.insert_table = []
  377. self.linshi_db = MysqlDB('linshi', db_type=1)
  378. for city in self.city_list:
  379. for age in self.age_list:
  380. for crowd in self.crowd:
  381. result = self.city_age_crowd(city, age, crowd)
  382. self.insert_score_to_db(result)
  383. print('{}数据关系完成...'.format(time.time()))
  384. def insert_score_to_db(self, scores):
  385. """
  386. 行为、模块分数写入数据库
  387. :return:
  388. """
  389. ids = self.query_data()
  390. behavior_score = scores['behavior_score']
  391. module_score = scores['module_score']
  392. module_insert_sql = self.get_insert_sql('模块分数')
  393. if module_insert_sql:
  394. module_insert_data = []
  395. for module in module_score:
  396. city_2 = module[0]
  397. age_2 = module[1]
  398. crowd_2 = module[2]
  399. module_name_2 = module[3]
  400. module_score_2 = module[4]
  401. for id in ids:
  402. city_1 = id[2]
  403. age_1 = id[1]
  404. crowd_1 = id[3]
  405. id_1 = id[0]
  406. if city_2 == city_1 and age_2 == age_1 and crowd_2 == crowd_1:
  407. module_insert_data.append([id_1, module_name_2, module_score_2])
  408. # 先清空之前的数据
  409. if len(module_insert_data) > 0:
  410. table_name = self.get_table_name('模块分数')
  411. if table_name is not None and table_name not in self.insert_table:
  412. self.linshi_db.truncate(table_name)
  413. self.linshi_db.add_some(module_insert_sql, module_insert_data)
  414. self.insert_table.append(table_name)
  415. print('模块分数更新完成...')
  416. for b_score in behavior_score:
  417. for key in b_score.keys():
  418. insert_sql = self.get_insert_sql(key)
  419. if insert_sql:
  420. insert_data = []
  421. score = b_score[key]
  422. for data in score:
  423. city = data[0]
  424. age = data[1]
  425. tag_name = data[2]
  426. crowd = data[3]
  427. tag_score = data[4]
  428. if key == '用户画像-行为兴趣' and city == '上海市' and age == '85后':
  429. pass
  430. else:
  431. for id in ids:
  432. city_1 = id[2]
  433. age_1 = id[1]
  434. crowd_1 = id[3]
  435. id_1 = id[0]
  436. if city == city_1 and age == age_1 and crowd == crowd_1:
  437. insert_data.append([id_1, tag_name, tag_score])
  438. if len(insert_data) > 0:
  439. table_name = self.get_table_name(key)
  440. if table_name and table_name not in self.insert_table:
  441. if table_name == 'mvp_crowd_info_behavior':
  442. self.linshi_db.delete(self.sql_18)
  443. else:
  444. self.linshi_db.truncate(table_name)
  445. self.linshi_db.add_some(insert_sql, insert_data)
  446. self.insert_table.append(table_name)
  447. else:
  448. print('未找到对应的表,数据无法插入...')
  449. print('行为分数更新完成...')
  450. def module_score(self, crowd, city, age, scores):
  451. """
  452. 模块分数计算
  453. 城市 年龄 人群分类 模块名称 分数
  454. :return:
  455. """
  456. # import json
  457. # print(json.dumps(scores, ensure_ascii=False))
  458. modules = self.module_scores[crowd]
  459. result = []
  460. for key in modules.keys():
  461. values = modules[key]
  462. module_name = key
  463. score = 0
  464. for value in values:
  465. behavioral_name = value[0]
  466. weight = float(value[2])
  467. standard_score = [x[4] for x in scores if x[2] == behavioral_name]
  468. if len(standard_score) > 0:
  469. score += standard_score[0] * weight
  470. result.append([city, age, crowd, module_name, score])
  471. return result
  472. # def insert_data(self, scores_behavioral, scores_module):
  473. def insert(self):
  474. """
  475. 计算数据写入数据库中,供接口查看
  476. :return:
  477. """
  478. infos = []
  479. for city in self.city_list:
  480. for age in self.age_list:
  481. for c_type in self.crowd:
  482. age_area = self.age_dict.get(age)
  483. if age_area:
  484. infos.append([age_area, city, c_type])
  485. self.shangju_db.add_some(self.sql_11, infos)
  486. def query_data(self):
  487. ids = self.linshi_db.select(self.sql_14)
  488. return ids
  489. def shanghai_85_module_score_insert(self):
  490. """
  491. 上海市,85后模块分数计算
  492. :return:
  493. """
  494. result = []
  495. for crowd in self.crowd:
  496. modules = self.module_scores[crowd]
  497. for key in modules.keys():
  498. values = modules[key]
  499. module_name = key
  500. score = 0
  501. for value in values:
  502. behavioral_name = value[0]
  503. weight = float(value[2])
  504. # standard_score = [x[4] for x in scores if x[2] == behavioral_name]
  505. standard_score = float(value[1])
  506. if standard_score is not None:
  507. score += standard_score * weight
  508. result.append(['上海市', '85后', crowd, module_name, score])
  509. return {'score': result, 'data': self.module_scores}
  510. def tag_module_score_insert(self):
  511. """
  512. 标签模块分数写入数据库
  513. :return:
  514. """
  515. ids = self.query_data()
  516. insert_data = []
  517. insert_data_1 = []
  518. for tag, module in zip(self.scores_tag, self.score_module):
  519. city = tag[0]
  520. age = tag[1]
  521. crowd = tag[2]
  522. tag_name = tag[3]
  523. tag_score = tag[4]
  524. city_2 = module[0]
  525. age_2 = module[1]
  526. crowd_2 = module[2]
  527. module_name_2 = module[3]
  528. module_score_2 = module[4]
  529. for id in ids:
  530. city_1 = id[2]
  531. age_1 = id[1]
  532. crowd_1 = id[3]
  533. id_1 = id[0]
  534. if city == city_1 and self.age_dict[age] == age_1 and crowd == crowd_1:
  535. insert_data.append([id_1, tag_name, tag_score])
  536. if city_2 == city_1 and self.age_dict[age_2] == age_1 and crowd_2 == crowd_1:
  537. insert_data_1.append([id_1, module_name_2, module_score_2])
  538. self.shangju_db.add_some(self.sql_12, insert_data)
  539. self.shangju_db.add_some(self.sql_13, insert_data_1)
  540. def init_age(self):
  541. """
  542. 获取答题数据中的年龄
  543. """
  544. return ['95后', '85后']
  545. # age_info = self.marketing_db.select(self.sql_4)
  546. # # print([x[0] for x in age_info])
  547. # return [x[0] for x in age_info if x[0] is not None]
  548. def city_age_crowd(self, city=None, age=None, crowd=None):
  549. data_start = []
  550. result = []
  551. module_scores = []
  552. self.people_info_1 = self.people_info()
  553. if city is not None and age is not None and crowd is not None:
  554. print('获取指定城市,年龄段,人群类型的数据...')
  555. # people_uuids = self.get_people_uuid_by_type(crowd)
  556. people_uuids = self.people_filter(city, age, crowd)
  557. behavior_data = None
  558. if len(people_uuids) > 0:
  559. print('{}-{}-{}'.format(city, age, crowd))
  560. datas = self.behavior_tag_init(city, age, people_uuids)
  561. data_start.append(datas)
  562. all_data, behavior_data_1 = self.calculation_standard_score(datas, city, age, crowd)
  563. result.append(all_data)
  564. behavior_data = behavior_data_1
  565. if behavior_data:
  566. module_scores.extend(self.module_score(crowd, city, age, behavior_data))
  567. # data_list = []
  568. # for e in data_start:
  569. # for key in e.keys():
  570. # values = e[key]
  571. # for sub_e in values:
  572. # ele = [key]
  573. # ele.extend(sub_e)
  574. # data_list.append(ele)
  575. # pass
  576. return {'behavior_score': result, 'module_score': module_scores}
  577. # return {'score': result, 'data': data_list}
  578. def scores(self):
  579. behavior_score = []
  580. module_scores = []
  581. for city in self.city_list:
  582. for age in self.age_list:
  583. for crowd in self.crowd:
  584. data = self.city_age_crowd(city, age, crowd)
  585. behavior_score.extend(data['behavior_score'])
  586. module_scores.extend(data['module_score'])
  587. return {'behavior_score': behavior_score, 'module_score': module_scores}
  588. def behavior_tag_init(self, city, age, people_uuids):
  589. result = {}
  590. self.group_type_count = self.marketing_db.select(self.sql_5, [people_uuids])
  591. # 表名
  592. for key in self.tag_data.keys():
  593. values = self.tag_data[key]
  594. result_sub = {}
  595. # 标签
  596. for key_tag_name in values.keys():
  597. questions = values[key_tag_name]
  598. elements = []
  599. for value in questions:
  600. question = value[0].split('-')[0]
  601. option = value[0].split('-')[1]
  602. corr = value[1]
  603. fz, fm = self.molecular_value(question, option, city, age, people_uuids)
  604. if fm == 0:
  605. c = 0
  606. else:
  607. c = fz / fm
  608. elements.append([question, option, corr, fz, fm, c])
  609. result_sub[key_tag_name] = elements
  610. result[key] = self.indicator_calculation_d_e(result_sub)
  611. return result
  612. def molecular_value(self, queston, option, city, age, people_uuids):
  613. # 获取当前父选项包含的子选项id和子题id列表
  614. result = self.shangju_db.select(self.sql_6, [option, queston])
  615. sub_option_ids = []
  616. group_types = []
  617. for rt in result:
  618. sub_option_id, sub_question_id, content = rt[0], rt[1], rt[2]
  619. grouptypes = self.shangju_db.select(self.sql_7, [sub_question_id])
  620. for g_t in grouptypes:
  621. if str(g_t[0]) not in group_types:
  622. group_types.append(str(g_t[0]))
  623. sub_option_ids.append(sub_option_id)
  624. # 计算子选项在答题记录中的点击数
  625. sub_options_count = 0
  626. if len(sub_option_ids) > 0:
  627. result_1 = self.marketing_db.select(self.sql_8, [sub_option_ids, people_uuids])
  628. sub_options_count = result_1[0][0]
  629. # 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。
  630. denominator_value = 0
  631. for info in self.group_type_count:
  632. if str(info[0]) in group_types:
  633. denominator_value += info[1]
  634. return sub_options_count, denominator_value
  635. def indicator_calculation_d_e(self, data):
  636. result = {}
  637. for key in data.keys():
  638. values = data[key]
  639. c_list = []
  640. for x in values:
  641. _x = x[5]
  642. if _x is not None and x != 0:
  643. c_list.append(_x)
  644. fm_list = [x[4] for x in values]
  645. sum_c = sum(fm_list)
  646. if len(c_list) == 0:
  647. min_c = 0
  648. else:
  649. min_c = min(c_list)
  650. elements = []
  651. for value in values:
  652. _value = []
  653. c = value[5]
  654. if sum_c == 0:
  655. d = 0
  656. else:
  657. d = c / sum_c
  658. e = c - min_c
  659. _value.extend(value)
  660. _value.append(d)
  661. _value.append(e)
  662. elements.append(_value)
  663. result[key] = elements
  664. return result
  665. def calculation_standard_score(self, datas, city, age, crowd_type):
  666. scores = {}
  667. for key_tag_type in datas.keys():
  668. print(key_tag_type)
  669. tag_type_data = datas[key_tag_type]
  670. scores_sub = []
  671. for key_tag in tag_type_data.keys():
  672. key_tag_data = tag_type_data[key_tag]
  673. print(key_tag)
  674. 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')
  675. values = [x[5] for x in key_tag_data]
  676. min_c = min(values)
  677. f = min_c
  678. for value in key_tag_data:
  679. print(' {}'.format(value))
  680. if value[2] is not None and value[7] is not None:
  681. f += float(value[2] * value[7])
  682. print(' 标准分:{}'.format(f))
  683. scores_sub.append([city, age, key_tag, crowd_type, f])
  684. scores[key_tag_type] = scores_sub
  685. # self.shangju_db.add_some(self.sql_9, scores)
  686. return scores, scores['用户画像-行为兴趣']
  687. def people_data(self):
  688. result = self.people_info()
  689. a = 0
  690. b = 0
  691. c = 0
  692. d = 0
  693. e = 0
  694. f = 0
  695. result_1 = []
  696. for rt in result:
  697. crowds = rt.crowd
  698. if rt.uuid in [
  699. 'ae9db26b-3606-497c-83c5-56341d487a91',
  700. '9fb33b6c-bd7a-4114-b225-3ee380943517',
  701. '84636488-1307-47fe-a238-4f9cf279a908',
  702. '4a5b6654-eb99-46ed-8dcf-777648d6baca',
  703. 'ba181da0-c91a-4430-84c6-9612a693f659',
  704. '32eae583-474c-4dca-8b36-d74314f45cee',
  705. 'b07f6ff2-ccd5-44ee-9b7c-b2e1f40d777f',
  706. '149a0e40-5639-4771-8a27-60821e14a1d5',
  707. '4795b731-3e75-4f08-90bc-8ee4a0c366c6',
  708. '4795b731-3e75-4f08-90bc-8ee4a0c366c6',
  709. '47cbd398-1c39-4dc0-8d97-98fe19457516']:
  710. result_1.append([rt.uuid, rt.city, rt.age, rt.crowd])
  711. if 'A' in crowds:
  712. a += 1
  713. if 'B' in crowds:
  714. b += 1
  715. if 'C' in crowds:
  716. c += 1
  717. if 'D' in crowds:
  718. d += 1
  719. if 'E' in crowds:
  720. e += 1
  721. if 'F' in crowds:
  722. f += 1
  723. return result_1
  724. # return {'A': a, 'B': b, 'C': b, 'D': d, 'E': e, 'F': f}
  725. def get_crowd_people(self):
  726. result = {}
  727. for type in self.crowd:
  728. uuids = self.get_people_uuid_by_type(type)
  729. result[type] = len(uuids)
  730. return result
  731. def get_people_uuid_by_type(self, type):
  732. uuids = []
  733. type_sub_option_ids = self.crowd_contain_sub_option_ids[type]
  734. for people in self.people_sub_option_ids:
  735. uuid = people[0]
  736. sub_option_ids = list(map(int, str(people[1]).split(',')))
  737. # list(set(a).intersection(set(b)))
  738. if len(list(set(sub_option_ids).intersection(set(type_sub_option_ids)))) > 0 and uuid not in uuids:
  739. uuids.append(uuid)
  740. return uuids
  741. def get_crowd_contain_sub_option_ids(self):
  742. """
  743. 获取ABCDEF人群包含的子选项id
  744. :return:
  745. """
  746. infos = {}
  747. for key in self.crowd_info.keys():
  748. values = self.crowd_info[key]
  749. sub_option_ids = []
  750. for value in values:
  751. if value is not None:
  752. vals = str(value).split('-')
  753. option, question = vals[1], vals[0]
  754. query_result = self.shangju_db.select(self.sql_6, [option, question])
  755. for qr in query_result:
  756. sub_option_id, sub_question_id, content = qr[0], qr[1], qr[2]
  757. sub_option_ids.append(int(sub_option_id))
  758. infos[key] = sub_option_ids
  759. return infos
  760. if __name__ == '__main__':
  761. pass