mvp.py 33 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. # 用户画像-消费结构 用户画像-生活方式
  25. # 需要更新的模块:用户画像-性别、用户画像-行业、用户画像-出行方式、
  26. # 用户画像-消费结构、用户画像-生活方式、用户画像-社交模式、用户画像-审美偏好
  27. tag_table = {
  28. '用户画像-审美偏好': ['mvp_crowd_info_aesthetic_preference', 'aesthetic_preference'],
  29. '用户画像-行为兴趣': ['mvp_crowd_info_behavior', 'behavioral_interest'],
  30. '用户画像-消费观念': ['mvp_crowd_info_consumer_concept', 'consumer_concept'],
  31. '用户画像-社交模式': ['mvp_crowd_info_social_mode', 'social_module'],
  32. '用户画像-行业': ['mvp_crowd_info_trade', 'trade'],
  33. '用户画像-出行方式': ['mvp_crowd_info_trip_mode', 'trip_mode'],
  34. '空间需求图谱-色相': ['mvp_innovate_space_hue_prefer', 'hue'],
  35. '空间需求图谱-精装关注点': ['mvp_innovate_space_hardcover_focus', 'hardcover_focus'],
  36. '空间需求图谱-色调': ['mvp_innovate_space_hue_prefer', 'hue'],
  37. '空间需求图谱-单品偏好': ['mvp_innovate_space_item_preference', 'item_preference'],
  38. '空间需求图谱-材质': ['mvp_innovate_space_material_prefer', 'material'],
  39. '空间需求图谱-空间特性偏好': ['mvp_innovate_space_space_prefer', 'space_preference'],
  40. '模块分数': ['mvp_crowd_info_module', 'module_name'],
  41. '用户画像-生活方式': ['mvp_crowd_info_life_style', 'life_style'],
  42. '用户画像-消费结构': ['mvp_crowd_info_consumer_structure', 'consumer_structure']
  43. }
  44. crowd_info_1 = {
  45. '1973': 'A',
  46. '1974': 'B',
  47. '1975': 'C',
  48. '1976': 'D',
  49. '1977': 'E',
  50. '1978': 'F',
  51. '1979': 'G',
  52. '1813': 'A',
  53. '1814': 'B',
  54. '1815': 'C',
  55. '1816': 'D',
  56. '1817': 'E',
  57. '1818': 'F',
  58. '1819': 'G'
  59. }
  60. base_insert_sql = '''
  61. INSERT INTO {} (
  62. crowd_info_id,
  63. {},
  64. standard_value,
  65. STATUS,
  66. creator,
  67. created
  68. )
  69. VALUES
  70. (%s, %s, %s, 1, 'binren', now())
  71. '''
  72. def get_table_name(self, name):
  73. """
  74. 获取表名
  75. :param name:
  76. :return:
  77. """
  78. params = self.tag_table.get(name)
  79. if params:
  80. return self.tag_table.get(name)[0]
  81. def get_insert_sql(self, tag_type_name):
  82. """
  83. 根据标签分类名称获取相应表的插入sql
  84. :param tag_type_name:
  85. :return:
  86. """
  87. params = self.tag_table.get(tag_type_name)
  88. if params:
  89. return self.base_insert_sql.format(params[0], params[1])
  90. crowd = ['A', 'B', 'C', 'D', 'E', 'F']
  91. # 获取答题记录中城市列表
  92. sql_1 = 'select city from f_t_daren_score_2 group by city'
  93. # 获取父选项和父题id
  94. 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 ' \
  95. 'where a.serial_number = %s and b.serial_number = %s and a.status = b.status = 1 '
  96. # 获取答题人的年龄段集合
  97. sql_4 = 'select nld from f_t_daren_score_2 group by nld'
  98. # 根据城市,年龄段,人群分类统计答题记录数
  99. sql_5 = 'select testcase_id, COUNT(DISTINCT uuid) from f_t_daren_score_2 where uuid in %s group by testcase_id '
  100. # 根据父选项获取子选项id列表
  101. sql_6 = '''
  102. SELECT
  103. c.id,
  104. c.sub_question_id,
  105. c.content
  106. FROM
  107. bq_sub_option c
  108. WHERE
  109. c.father_id IN (
  110. SELECT
  111. a.id
  112. FROM
  113. bq_option a
  114. LEFT JOIN bq_question b ON a.question_id = b.id
  115. WHERE
  116. a.serial_number = % s
  117. AND b.serial_number = % s
  118. AND a. STATUS = 1
  119. AND b. STATUS = 1
  120. )
  121. AND c. STATUS = 1
  122. '''
  123. # 根据子题id获取包含子题id的测试
  124. sql_7 = 'select id from bq_testcase where status = 1 and FIND_IN_SET(%s, question_ids)'
  125. # 根据子选项id统计答题数
  126. sql_8 = '''
  127. SELECT
  128. count(DISTINCT a.uuid)
  129. FROM
  130. f_t_daren_score_2 a
  131. LEFT JOIN d_shangju_tiku_02 b ON a.sub_question_id = b.sub_question_id
  132. AND (
  133. a.score = b.score
  134. OR a.score = b.sub_option_id
  135. )
  136. AND a.testcase_id = b.testcase_id
  137. WHERE
  138. b.sub_option_id IN % s
  139. AND a.uuid IN % s
  140. '''
  141. # 获取一个uuid下答题的子选项id列表
  142. sql_10 = 'select DISTINCT uuid, GROUP_CONCAT(DISTINCT b.sub_option_id) from f_t_daren_score_2 a left join ' \
  143. 'd_shangju_tiku_02 b on a.sub_question_id = b.sub_question_id and (a.score = b.score or a.score = ' \
  144. 'b.sub_option_id) where a.status = ' \
  145. 'b.status = 1 group by uuid '
  146. # 向表mvp_crowd_info插入数据
  147. sql_11 = 'insert into mvp_crowd_info(age_area, city_name, crowd_type, status) values(%s, %s, %s, 1)'
  148. # 向表mvp_crowd_info_behavior中插入数据
  149. sql_12 = 'insert into mvp_crowd_info_behavior(crowd_info_id, behavioral_interest, standard_value, status) values(' \
  150. '%s, %s, ' \
  151. '%s, 1) '
  152. # 向表mvp_crowd_info_module中插入数据
  153. sql_13 = 'insert into mvp_crowd_info_module(crowd_info_id, module_name, standard_value, status) values (%s, %s, ' \
  154. '%s, 1) '
  155. sql_14 = 'select a.id, a.age_area, a.city_name, a.crowd_type from mvp_crowd_info a where a.status = 1'
  156. # 获取答题城市信息from city
  157. sql_15 = '''
  158. SELECT
  159. a.uuid,
  160. IFNULL(GROUP_CONCAT(DISTINCT a.city, a.province), 00) AS city,
  161. IFNULL(GROUP_CONCAT(DISTINCT a.nld), 00) AS nld,
  162. IFNULL(GROUP_CONCAT(DISTINCT a.sex), 00) AS sex,
  163. IFNULL(GROUP_CONCAT(DISTINCT b.sub_option_id), 00) as sub_option_ids,
  164. IFNULL(GROUP_CONCAT(DISTINCT a.testcase_id), 00) as testcase_ids
  165. FROM
  166. f_t_daren_score_2 a
  167. LEFT JOIN d_shangju_tiku_02 b ON a.testcase_id = b.testcase_id
  168. WHERE
  169. a.testcase_id = b.testcase_id
  170. AND a.sub_question_id = b.sub_question_id
  171. AND (
  172. a.score = b.score
  173. OR a.score = b.sub_option_id
  174. )
  175. GROUP BY
  176. a.uuid
  177. '''
  178. # 根据用户uuid获取城市信息
  179. sql_16 = '''
  180. SELECT
  181. a.uuid,
  182. b.sub_option_content
  183. FROM
  184. f_t_daren_score_2 a
  185. LEFT JOIN d_shangju_tiku_02 b ON a.testcase_id = b.testcase_id
  186. WHERE
  187. a.sub_question_id = b.sub_question_id
  188. AND (
  189. a.score = b.score
  190. OR a.score = b.sub_option_id
  191. )
  192. AND a.uuid = %s
  193. AND b.father_id = 249
  194. AND a. STATUS = b. STATUS = 1
  195. '''
  196. # 答题人人群分类信息
  197. sql_17 = '''
  198. SELECT
  199. a.uuid,
  200. b.sub_option_id
  201. FROM
  202. f_t_daren_score_2 a
  203. LEFT JOIN d_shangju_tiku_02 b ON a.testcase_id = b.testcase_id
  204. WHERE
  205. a.sub_question_id = b.sub_question_id
  206. AND (
  207. a.score = b.score
  208. OR a.score = b.sub_option_id
  209. )
  210. AND a.uuid = %s
  211. AND b.father_id = 236
  212. AND a.STATUS = b.STATUS = 1
  213. '''
  214. sql_18 = '''
  215. DELETE
  216. FROM
  217. mvp_crowd_info_behavior
  218. WHERE
  219. FIND_IN_SET(crowd_info_id, (
  220. SELECT
  221. GROUP_CONCAT(id)
  222. FROM
  223. mvp_crowd_info
  224. WHERE
  225. city_name = '上海市'
  226. AND age_area = '85后'
  227. AND STATUS = 1
  228. ))
  229. '''
  230. # 根据名称获取图标
  231. sql_19 = '''
  232. SELECT
  233. id,
  234. NAME
  235. FROM
  236. mvp_icon
  237. WHERE status = 1
  238. '''
  239. # 行为更新图标
  240. sql_20 = '''
  241. UPDATE mvp_crowd_info_behavior
  242. SET icon_id = % s
  243. WHERE
  244. behavioral_interest = % s
  245. '''
  246. # 模块图标更新
  247. sql_21 = '''
  248. '''
  249. # 更新性别占比数据
  250. sql_22 = '''
  251. INSERT INTO mvp_crowd_info_gender_rate (
  252. crowd_info_id,
  253. gender,
  254. standard_value,
  255. status,
  256. creator,
  257. created
  258. )
  259. VALUES
  260. (%s, %s, %s, 1, 'binren', now())
  261. '''
  262. sql_23 = '''
  263. DELETE
  264. FROM
  265. mvp_crowd_info_module
  266. WHERE
  267. FIND_IN_SET(crowd_info_id, (
  268. SELECT
  269. GROUP_CONCAT(id)
  270. FROM
  271. mvp_crowd_info
  272. WHERE
  273. city_name = '上海市'
  274. AND age_area = '85后'
  275. AND STATUS = 1
  276. ))
  277. '''
  278. """
  279. 数据debug SQL
  280. 1:
  281. SELECT
  282. c.id,
  283. c.sub_question_id,
  284. c.content
  285. FROM
  286. bq_sub_option c
  287. WHERE
  288. c.father_id IN (
  289. SELECT
  290. a.id
  291. FROM
  292. bq_option a
  293. LEFT JOIN bq_question b ON a.question_id = b.id
  294. WHERE
  295. a.serial_number ='FA001'
  296. AND b.serial_number = 'F00245'
  297. AND a. STATUS = 1
  298. AND b. STATUS = 1
  299. )
  300. AND c.STATUS = 1
  301. 2:
  302. select id from bq_testcase where status = 1 and FIND_IN_SET(%s, question_ids)
  303. 3:
  304. SELECT
  305. count(1)
  306. FROM
  307. f_t_daren_score_2 a
  308. LEFT JOIN d_shangju_tiku_02 b ON a.sub_question_id = b.sub_question_id
  309. AND (
  310. a.score = b.score
  311. OR a.score = b.sub_option_id
  312. )
  313. AND a.testcase_id = b.testcase_id
  314. WHERE
  315. b.sub_option_id IN (1964,1965,1966,1967,1968,1969,1970,1971,1972)
  316. """
  317. def __init__(self, path=None):
  318. self.shangju_db = MysqlDB('shangju')
  319. self.marketing_db = MysqlDB('bi_report')
  320. self.linshi_db = MysqlDB('linshi', db_type=1)
  321. # self.shangju_db.truncate('mvp_standard_score')
  322. self.tag_data = ExcelUtil(file_name=path).init_mvp_data()
  323. self.crowd_info = ExcelUtil(file_name=path, sheet_name='选项-人群分类对应表').init_crowd_info()
  324. self.citys = self.init_city()
  325. self.age = self.init_age()
  326. self.people_sub_option_ids = self.marketing_db.select(self.sql_10)
  327. self.crowd_contain_sub_option_ids = self.get_crowd_contain_sub_option_ids()
  328. self.module_scores = ExcelUtil(file_name='set-behavior-tag.xlsx', sheet_name='算法关系表').init_module_info()
  329. # self.scores_tag = ExcelUtil(file_name='行为与模块分值汇总.xlsx', sheet_name='行为').init_scores()
  330. # self.score_module = ExcelUtil(file_name='行为与模块分值汇总.xlsx', sheet_name='模块').init_scores()
  331. self.people_info_1 = self.people_info()
  332. def close(self):
  333. self.shangju_db.close()
  334. self.marketing_db.close()
  335. self.linshi_db.close()
  336. def init_city(self):
  337. """
  338. 获取答题数据中的城市。
  339. :return:
  340. """
  341. citys = ['上海市', '上海周边']
  342. # citys_info = self.marketing_db.select(self.sql_1)
  343. # citys.extend([x[0] for x in citys_info if x[0] is not None])
  344. return citys
  345. def query_behavioral_info(self, city=None, age=None, crowd=None):
  346. """
  347. 查询行为兴趣信息
  348. :return:
  349. """
  350. # datas = []
  351. # for key in self.tag_data.keys():
  352. # values = self.tag_data[key]
  353. # for value in values:
  354. # question = value[0].split('-')[0]
  355. # option = value[0].split('-')[1]
  356. # corr = value[1]
  357. # data = self.shangju_db.select(self.sql_2, [option, question])
  358. # if len(data) > 0:
  359. # print([question, option, data[0][3], data[0][1], key, corr])
  360. # datas.append([question, option, data[0][3], data[0][1], key, corr])
  361. # self.shangju_db.truncate('mvp_question_classification')
  362. # self.shangju_db.add_some(self.sql_3, datas)
  363. scores_behavioral = self.city_age_crowd(city, age, crowd)
  364. # scores_module = self.module_score(crowd, city, age, scores_behavioral['score'])
  365. # result = {'行为兴趣分值': scores_behavioral['score'], '模块分值': scores_module}
  366. print('update finished!!!')
  367. return scores_behavioral
  368. def people_info(self):
  369. """
  370. 答题人个人信息获取
  371. :return:
  372. """
  373. people_info_city = self.marketing_db.select(self.sql_15)
  374. people_infos = []
  375. for people in people_info_city:
  376. uuid = people[0]
  377. city = people[1]
  378. nld = people[2]
  379. sex = people[3]
  380. if sex and len(str(sex).split(',')) > 0:
  381. sex = str(sex).split(',')[0]
  382. else:
  383. sex = '3'
  384. sub_option_ids_1 = people[4]
  385. testcaseid = people[5]
  386. if str(city).find('市') != -1:
  387. city = str(city).split('市')[0] + '市'
  388. if str(nld).find(',') != -1:
  389. nld_1 = list(str(nld).split(','))
  390. if len(nld_1) > 0:
  391. nld = nld_1[0]
  392. else:
  393. pass
  394. crowd = []
  395. if testcaseid:
  396. testcastids = list(map(int, str(testcaseid).split(',')))
  397. if len(testcastids) > 0:
  398. gt_75 = [x for x in testcastids if x > 74]
  399. if len(gt_75) > 0:
  400. # 从答题结果中获取城市信息
  401. citys = self.marketing_db.select(self.sql_16, [uuid])
  402. if len(citys) > 0:
  403. city = '上海市' if citys[0][1] == '一线' else '上海周边'
  404. # 根据用户子选项id集合,获取用户的人群分类
  405. if len(gt_75) > 0:
  406. # 特定的测试人群分类从答题结果中获取
  407. sub_option_ids = self.marketing_db.select(self.sql_17, [uuid])
  408. for option in sub_option_ids:
  409. crowd_type = self.crowd_info_1.get(option[1])
  410. if crowd_type:
  411. crowd.append(crowd_type)
  412. else:
  413. crowd.append('A')
  414. else:
  415. if sub_option_ids_1 is not None:
  416. crowd.extend(self.get_people_uuid_by_sub_option_ids(sub_option_ids_1))
  417. if city is None:
  418. city = '上海市'
  419. people_info = PeopleInfo(uuid, city, nld, sex, crowd)
  420. people_infos.append(people_info)
  421. # people_infos.append([uuid, city, nld, sex, crowd])
  422. return people_infos
  423. def people_filter(self, city, nld, crowd):
  424. uuids = []
  425. for people in self.people_info_1:
  426. if people.city == city and people.age == nld and crowd in people.crowd:
  427. uuids.append(people.uuid)
  428. return uuids
  429. def get_people_uuid_by_sub_option_ids(self, sub_ids):
  430. types = []
  431. for key in self.crowd_contain_sub_option_ids.keys():
  432. type_sub_option_ids = self.crowd_contain_sub_option_ids[key]
  433. sub_option_ids = list(map(int, str(sub_ids).split(',')))
  434. # list(set(a).intersection(set(b)))
  435. if len(list(set(sub_option_ids).intersection(set(type_sub_option_ids)))) > 0 and key not in types:
  436. types.append(key)
  437. return types
  438. def update_data(self):
  439. """
  440. 定时更新分值
  441. 使用真实数据模块名称:用户画像-行为兴趣,空间需求图谱-材质,空间需求图谱-色调,空间需求图谱-色相
  442. 用户画像-行业,用户画像-出行方式,用户画像-消费结构,用户画像-生活方式,用户画像-社交模式, 模块分数
  443. :return:
  444. """
  445. message = {}
  446. try:
  447. self.insert_table = []
  448. self.ids = self.query_data()
  449. for city in self.city_list:
  450. for age in self.age_list:
  451. for crowd in self.crowd:
  452. result = self.city_age_crowd(city, age, crowd)
  453. self.insert_score_to_db(result)
  454. self.linshi_db.delete(self.sql_18)
  455. message['实际分值'] = '更新完成'
  456. insert_data = self.shanghai_85_module_score_insert()
  457. self.linshi_db.delete(self.sql_23)
  458. self.insert_score_to_db(insert_data)
  459. message['模块模拟分值'] = '更新完成'
  460. self.update_gender_rate()
  461. message['性别信息'] = '更新完成'
  462. self.update_icon()
  463. message['行为图标'] = '更新完成'
  464. return message
  465. except Exception as e:
  466. message['error'] = str(e)
  467. return message
  468. def update_gender_rate(self, ids=None):
  469. """
  470. 更新性别占比
  471. :return:
  472. """
  473. if ids:
  474. self.ids = self.query_data()
  475. insert_data = []
  476. for city in self.city_list:
  477. for age in self.age_list:
  478. for crowd in self.crowd:
  479. boy = 0
  480. girl = 0
  481. for people in self.people_info_1:
  482. if people.sex is not None and city == people.city and crowd in people.crowd and age == people.age:
  483. if people.sex == '1':
  484. boy += 1
  485. if people.sex == '2':
  486. girl += 1
  487. crowd_info_id = self.get_crowd_info_id([city, age, crowd])
  488. if crowd_info_id and (boy + girl) > 0:
  489. boy_rate = boy / (boy + girl)
  490. insert_data.append([crowd_info_id, 1, boy_rate])
  491. girl_rate = girl / (boy + girl)
  492. insert_data.append([crowd_info_id, 0, girl_rate])
  493. if len(insert_data) > 0:
  494. self.linshi_db.truncate('mvp_crowd_info_gender_rate')
  495. self.linshi_db.add_some(self.sql_22, insert_data)
  496. print('性别占比更新完成...')
  497. else:
  498. print('无数据更新...')
  499. def get_crowd_info_id(self, people_info):
  500. for id_data in self.ids:
  501. city_1 = id_data[2]
  502. age_1 = id_data[1]
  503. crowd_1 = id_data[3]
  504. id_1 = id_data[0]
  505. if people_info[0] == city_1 and people_info[1] == age_1 and people_info[2] == crowd_1:
  506. return id_1
  507. def update_image(self):
  508. """
  509. 更新标签关联的图片信息
  510. :return:
  511. """
  512. pass
  513. def update_icon(self):
  514. """
  515. 标签关联图标
  516. :return:
  517. """
  518. icons = self.linshi_db.select(self.sql_19)
  519. for ic in icons:
  520. id = ic[0]
  521. name = ic[1]
  522. self.linshi_db.update(self.sql_20, [id, name])
  523. print('行为标签关联图标完成...')
  524. def insert_score_to_db(self, scores):
  525. """
  526. 行为、模块分数写入数据库
  527. :return:
  528. """
  529. behavior_score = scores['behavior_score']
  530. module_score = scores['module_score']
  531. module_insert_sql = self.get_insert_sql('模块分数')
  532. if module_insert_sql:
  533. module_insert_data = []
  534. for module in module_score:
  535. data = self.need_inert(module)
  536. if data:
  537. module_insert_data.append(data)
  538. # 先清空之前的数据
  539. if len(module_insert_data) > 0:
  540. table_name = self.get_table_name('模块分数')
  541. if table_name is not None and table_name not in self.insert_table:
  542. # self.linshi_db.delete(self.sql_23)
  543. self.linshi_db.truncate(table_name)
  544. self.linshi_db.add_some(module_insert_sql, module_insert_data)
  545. self.insert_table.append(table_name)
  546. print('模块分数更新完成...')
  547. for b_score in behavior_score:
  548. for key in b_score.keys():
  549. insert_sql = self.get_insert_sql(key)
  550. if insert_sql:
  551. insert_data = []
  552. score = b_score[key]
  553. for data in score:
  554. insert_data_element = self.need_inert(data)
  555. if insert_data_element:
  556. insert_data.append(insert_data_element)
  557. if len(insert_data) > 0:
  558. table_name = self.get_table_name(key)
  559. if table_name and table_name not in self.insert_table:
  560. # if table_name == 'mvp_crowd_info_behavior':
  561. # self.linshi_db.delete(self.sql_18)
  562. # else:
  563. self.linshi_db.truncate(table_name)
  564. self.linshi_db.add_some(insert_sql, insert_data)
  565. self.insert_table.append(table_name)
  566. else:
  567. print('未找到对应的表,数据无法插入...')
  568. print('行为分数更新完成...')
  569. def need_inert(self, data):
  570. city = data[0]
  571. age = data[1]
  572. crowd = data[2]
  573. tag_name = data[3]
  574. tag_score = data[4]
  575. # if key == '用户画像-行为兴趣' and city == '上海市' and age == '85后':
  576. # pass
  577. # else:
  578. for id_data in self.ids:
  579. city_1 = id_data[2]
  580. age_1 = id_data[1]
  581. crowd_1 = id_data[3]
  582. id_1 = id_data[0]
  583. if city == city_1 and age == age_1 and crowd == crowd_1:
  584. return [id_1, tag_name, tag_score]
  585. def module_score(self, crowd, city, age, scores):
  586. """
  587. 模块分数计算
  588. 城市 年龄 人群分类 模块名称 分数
  589. :return:
  590. """
  591. # import json
  592. # print(json.dumps(scores, ensure_ascii=False))
  593. modules = self.module_scores[crowd]
  594. result = []
  595. for key in modules.keys():
  596. values = modules[key]
  597. module_name = key
  598. score = 0
  599. for value in values:
  600. behavioral_name = value[0]
  601. weight = float(value[2])
  602. standard_score = [x[4] for x in scores if x[3] == behavioral_name]
  603. if len(standard_score) > 0:
  604. score += standard_score[0] * weight
  605. result.append([city, age, crowd, module_name, score])
  606. return result
  607. # def insert_data(self, scores_behavioral, scores_module):
  608. def insert(self):
  609. """
  610. 计算数据写入数据库中,供接口查看
  611. :return:
  612. """
  613. infos = []
  614. for city in self.city_list:
  615. for age in self.age_list:
  616. for c_type in self.crowd:
  617. age_area = self.age_dict.get(age)
  618. if age_area:
  619. infos.append([age_area, city, c_type])
  620. self.shangju_db.add_some(self.sql_11, infos)
  621. def query_data(self):
  622. ids = self.linshi_db.select(self.sql_14)
  623. return ids
  624. def shanghai_85_module_score_insert(self):
  625. """
  626. 上海市,85后模块分数计算
  627. :return:
  628. """
  629. result = []
  630. for crowd in self.crowd:
  631. modules = self.module_scores[crowd]
  632. for key in modules.keys():
  633. values = modules[key]
  634. module_name = key
  635. score = 0
  636. for value in values:
  637. # behavioral_name = value[0]
  638. weight = float(value[2])
  639. # standard_score = [x[4] for x in scores if x[2] == behavioral_name]
  640. standard_score = float(value[1])
  641. if standard_score is not None:
  642. score += standard_score * weight
  643. result.append(['上海市', '85后', crowd, module_name, score])
  644. # return result
  645. return {'behavior_score': [], 'module_score': result}
  646. def init_age(self):
  647. """
  648. 获取答题数据中的年龄
  649. """
  650. return ['95后', '85后']
  651. # age_info = self.marketing_db.select(self.sql_4)
  652. # # print([x[0] for x in age_info])
  653. # return [x[0] for x in age_info if x[0] is not None]
  654. def city_age_crowd(self, city=None, age=None, crowd=None):
  655. data_start = []
  656. result = []
  657. module_scores = []
  658. if city is not None and age is not None and crowd is not None:
  659. print('获取指定城市,年龄段,人群类型的数据...')
  660. # people_uuids = self.get_people_uuid_by_type(crowd)
  661. people_uuids = self.people_filter(city, age, crowd)
  662. behavior_data = None
  663. if len(people_uuids) > 0:
  664. print('{}-{}-{}'.format(city, age, crowd))
  665. datas = self.behavior_tag_init(city, age, people_uuids)
  666. data_start.append(datas)
  667. all_data, behavior_data_1 = self.calculation_standard_score(datas, city, age, crowd)
  668. result.append(all_data)
  669. behavior_data = behavior_data_1
  670. if behavior_data:
  671. module_scores.extend(self.module_score(crowd, city, age, behavior_data))
  672. # data_list = []
  673. # for e in data_start:
  674. # for key in e.keys():
  675. # values = e[key]
  676. # for sub_e in values:
  677. # ele = [key]
  678. # ele.extend(sub_e)
  679. # data_list.append(ele)
  680. # pass
  681. return {'behavior_score': result, 'module_score': module_scores}
  682. # return {'score': result, 'data': data_list}
  683. def scores(self):
  684. behavior_score = []
  685. module_scores = []
  686. for city in self.city_list:
  687. for age in self.age_list:
  688. for crowd in self.crowd:
  689. data = self.city_age_crowd(city, age, crowd)
  690. behavior_score.extend(data['behavior_score'])
  691. module_scores.extend(data['module_score'])
  692. return {'behavior_score': behavior_score, 'module_score': module_scores}
  693. def behavior_tag_init(self, city, age, people_uuids):
  694. result = {}
  695. self.group_type_count = self.marketing_db.select(self.sql_5, [people_uuids])
  696. # 表名
  697. for key in self.tag_data.keys():
  698. values = self.tag_data[key]
  699. result_sub = {}
  700. for key_tag_name in values.keys():
  701. questions = values[key_tag_name]
  702. elements = []
  703. for value in questions:
  704. question = value[0].split('-')[0]
  705. option = value[0].split('-')[1]
  706. corr = value[1]
  707. fz, fm = self.molecular_value(question, option, city, age, people_uuids)
  708. if fm == 0:
  709. c = 0
  710. else:
  711. c = fz / fm
  712. elements.append([question, option, corr, fz, fm, c])
  713. result_sub[key_tag_name] = elements
  714. result[key] = self.indicator_calculation_d_e(result_sub)
  715. return result
  716. def molecular_value(self, queston, option, city, age, people_uuids):
  717. # 获取当前父选项包含的子选项id和子题id列表
  718. result = self.shangju_db.select(self.sql_6, [option, queston])
  719. sub_option_ids = []
  720. group_types = []
  721. for rt in result:
  722. sub_option_id, sub_question_id, content = rt[0], rt[1], rt[2]
  723. grouptypes = self.shangju_db.select(self.sql_7, [sub_question_id])
  724. for g_t in grouptypes:
  725. if str(g_t[0]) not in group_types:
  726. group_types.append(str(g_t[0]))
  727. sub_option_ids.append(sub_option_id)
  728. # 计算子选项在答题记录中的点击数
  729. sub_options_count = 0
  730. if len(sub_option_ids) > 0:
  731. result_1 = self.marketing_db.select(self.sql_8, [sub_option_ids, people_uuids])
  732. sub_options_count = result_1[0][0]
  733. # 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。
  734. denominator_value = 0
  735. for info in self.group_type_count:
  736. if str(info[0]) in group_types:
  737. denominator_value += info[1]
  738. return sub_options_count, denominator_value
  739. def indicator_calculation_d_e(self, data):
  740. result = {}
  741. for key in data.keys():
  742. values = data[key]
  743. c_list = []
  744. for x in values:
  745. _x = x[5]
  746. if _x is not None and x != 0:
  747. c_list.append(_x)
  748. fm_list = [x[4] for x in values]
  749. sum_c = sum(fm_list)
  750. if len(c_list) == 0:
  751. min_c = 0
  752. else:
  753. min_c = min(c_list)
  754. elements = []
  755. for value in values:
  756. _value = []
  757. c = value[5]
  758. if sum_c == 0:
  759. d = 0
  760. else:
  761. d = c / sum_c
  762. e = c - min_c
  763. _value.extend(value)
  764. _value.append(d)
  765. _value.append(e)
  766. elements.append(_value)
  767. result[key] = elements
  768. return result
  769. def calculation_standard_score(self, datas, city, age, crowd_type):
  770. scores = {}
  771. for key_tag_type in datas.keys():
  772. print(key_tag_type)
  773. tag_type_data = datas[key_tag_type]
  774. scores_sub = []
  775. for key_tag in tag_type_data.keys():
  776. key_tag_data = tag_type_data[key_tag]
  777. print(key_tag)
  778. 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')
  779. values = [x[5] for x in key_tag_data]
  780. min_c = min(values)
  781. f = min_c
  782. for value in key_tag_data:
  783. print(' {}'.format(value))
  784. if value[2] is not None and value[7] is not None:
  785. f += float(value[2] * value[7])
  786. print(' 标准分:{}'.format(f))
  787. scores_sub.append([city, age, crowd_type, key_tag, f])
  788. scores[key_tag_type] = scores_sub
  789. # self.shangju_db.add_some(self.sql_9, scores)
  790. return scores, scores['用户画像-行为兴趣']
  791. def people_data(self):
  792. result = self.people_info()
  793. a = 0
  794. b = 0
  795. c = 0
  796. d = 0
  797. e = 0
  798. f = 0
  799. for rt in result:
  800. crowds = rt.crowd
  801. if 'A' in crowds:
  802. a += 1
  803. if 'B' in crowds:
  804. b += 1
  805. if 'C' in crowds:
  806. c += 1
  807. if 'D' in crowds:
  808. d += 1
  809. if 'E' in crowds:
  810. e += 1
  811. if 'F' in crowds:
  812. f += 1
  813. return {'A': a, 'B': b, 'C': b, 'D': d, 'E': e, 'F': f}
  814. def get_crowd_people(self):
  815. result = {}
  816. for type in self.crowd:
  817. uuids = self.get_people_uuid_by_type(type)
  818. result[type] = len(uuids)
  819. return result
  820. def get_people_uuid_by_type(self, type):
  821. uuids = []
  822. type_sub_option_ids = self.crowd_contain_sub_option_ids[type]
  823. for people in self.people_sub_option_ids:
  824. uuid = people[0]
  825. sub_option_ids = list(map(int, str(people[1]).split(',')))
  826. # list(set(a).intersection(set(b)))
  827. if len(list(set(sub_option_ids).intersection(set(type_sub_option_ids)))) > 0 and uuid not in uuids:
  828. uuids.append(uuid)
  829. return uuids
  830. def get_crowd_contain_sub_option_ids(self):
  831. """
  832. 获取ABCDEF人群包含的子选项id
  833. :return:
  834. """
  835. infos = {}
  836. for key in self.crowd_info.keys():
  837. values = self.crowd_info[key]
  838. sub_option_ids = []
  839. for value in values:
  840. if value is not None:
  841. vals = str(value).split('-')
  842. option, question = vals[1], vals[0]
  843. query_result = self.shangju_db.select(self.sql_6, [option, question])
  844. for qr in query_result:
  845. sub_option_id, sub_question_id, content = qr[0], qr[1], qr[2]
  846. sub_option_ids.append(int(sub_option_id))
  847. infos[key] = sub_option_ids
  848. return infos
  849. if __name__ == '__main__':
  850. pass