elab_mvp/flask_app.py

from flask import Flask, request, render_template
import os
from werkzeug.utils import secure_filename
import time
import json
import pandas as pd
import openpyxl as ox
from itertools import groupby
import os
import pymysql as ps

app = Flask(__name__)


class Mvp:
    """
     ce mvp 答题数据统计
     城市特例 北京市，上海市， 重庆市，天津市
    """

    age_dict = {
        '00-04年生': '00后',
        '05-09年生': '05后',
        '50-59年生': '50后',
        '60-69年生': '60后',
        '70-74年生': '70后',
        '75-79年生': '75后',
        '80-84年生': '80后',
        '85-89年生': '85后',
        '90-94年生': '90后',
        '95-99年生': '95后'
    }

    crowd = ['A', 'B', 'C', 'D', 'E', 'F']

    # 获取答题记录中城市列表
    sql_1 = 'select city from f_t_daren_score_2 group by city'

    # 获取父选项和父题id
    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 ' \
            'where a.serial_number = %s and b.serial_number = %s and a.status = b.status = 1 '
    # 数据插入表mvp_question_classification
    sql_3 = 'insert into mvp_question_classification(question_serial_number, question_content, ' \
            'option_serial_number, option_content, tag, corr) values(%s, %s, %s, %s, %s, %s) '

    # 获取答题人的年龄段集合
    sql_4 = 'select nld from f_t_daren_score_2 group by nld'

    # 根据城市，年龄段，人群分类统计答题记录数
    sql_5 = 'select group_type, COUNT(uuid) from f_t_daren_score_2 where (city = %s or province = %s) and nld ' \
            '= %s and uuid in %s group by group_type '

    # 根据父选项获取子选项id列表
    sql_6 = 'SELECT c.id, c.sub_question_id, c.content FROM bq_sub_option c WHERE c.father_id in (SELECT a.id FROM ' \
            'bq_option a ' \
            'LEFT JOIN bq_question b ON a.question_id = b.id WHERE a.serial_number = %s AND b.serial_number = %s ' \
            'and a.status = 1 and b.status = 1) and c.status = 1 '

    # 根据子题id获取包含子题id的测试
    sql_7 = 'select group_type from bq_testcase where status = 1 and FIND_IN_SET(%s, question_ids)'

    # 根据子选项id统计答题数
    sql_8 = 'SELECT count(uuid) FROM f_t_daren_score_2 a LEFT JOIN d_shangju_tiku_02 b ON a.sub_question_id = ' \
            'b.sub_question_id AND a.score  = b.score WHERE a.testcase_id = b.testcase_id and b.sub_option_id in %s' \
            'and (a.city = %s or a.province = %s) and a.nld = %s and a.uuid in %s'

    # 计算值写入表汇总
    sql_9 = 'insert into mvp_standard_score(city, age, tag, crowd_type, score)  VALUES(%s, %s, %s, %s, %s)'

    # 获取一个uuid下答题的子选项id列表
    sql_10 = 'select  DISTINCT uuid, GROUP_CONCAT(DISTINCT b.sub_option_id)  from f_t_daren_score_2 a left join ' \
             'd_shangju_tiku_02 b on a.sub_question_id = b.sub_question_id and a.score = b.score where a.status = ' \
             'b.status = 1 group by uuid '

    def __init__(self, path=None):
        self.shangju_db = MysqlDB('shangju')
        self.marketing_db = MysqlDB('bi_report')
        # self.shangju_db.truncate('mvp_standard_score')
        self.tag_data = ExcelUtil(path=path).init_mvp_data()
        self.crowd_info = ExcelUtil(path=path, sheet_name='选项-人群分类对应表').init_crowd_info()
        self.citys = self.init_city()
        self.age = self.init_age()
        self.people_sub_option_ids = self.marketing_db.select(self.sql_10)
        self.crowd_contain_sub_option_ids = self.get_crowd_contain_sub_option_ids()

    def init_city(self):
        """
            获取答题数据中的城市。
        :return:
        """
        citys = ['北京市', '上海市', '重庆市', '天津市']
        citys_info = self.marketing_db.select(self.sql_1)
        citys.extend([x[0] for x in citys_info if x[0] is not None])
        return citys

    def query_behavioral_info(self, city=None, age=None, crowd=None):
        """
            查询行为兴趣信息
        :return:
        """
        # datas = []
        # for key in self.tag_data.keys():
        #     values = self.tag_data[key]
        #     for value in values:
        #         question = value[0].split('-')[0]
        #         option = value[0].split('-')[1]
        #         corr = value[1]
        #         data = self.shangju_db.select(self.sql_2, [option, question])
        #         if len(data) > 0:
        #             print([question, option, data[0][3], data[0][1], key, corr])
        #             datas.append([question, option, data[0][3], data[0][1], key, corr])
        # self.shangju_db.truncate('mvp_question_classification')
        # self.shangju_db.add_some(self.sql_3, datas)
        result = self.city_age_crowd(city, age, crowd)
        print('update finished!!!')
        return result

    def write_behavioral_data_into_table(self):
        """
            行为兴趣计算数据写入数据库
        :return:
        """
        scores_all = []
        for city in self.citys:
            for age in self.age:
                if city != '上海市' and age != '85-89年生':
                    for crowd_type in self.crowd:
                        # print(' {}{}'.format(city, age))
                        people_uuids = self.get_people_uuid_by_type(crowd_type)
                        if len(people_uuids) > 0:
                            print('{}-{}-{}'.format(city, age, crowd_type))
                            datas = self.behavior_tag_init(city, age, people_uuids)
                            scores = self.calculation_standard_score(datas, city, age, crowd_type)
                            scores_all.extend(scores)

    def insert(self, scores):
        """
            计算数据写入数据库中，供接口查看
        :param scores:
        :return:
        """
        # todo
        pass

    def init_age(self):
        """
           获取答题数据中的年龄
        """
        age_info = self.marketing_db.select(self.sql_4)
        # print([x[0] for x in age_info])
        return [x[0] for x in age_info if x[0] is not None]

    def city_age_crowd(self, city=None, age=None, crowd=None):
        result = []
        if city is not None and age is not None and crowd is not None:
            print('获取指定城市，年龄段，人群类型的数据...')
            people_uuids = self.get_people_uuid_by_type(crowd)
            if len(people_uuids) > 0:
                print('{}-{}-{}'.format(city, age, crowd))
                datas = self.behavior_tag_init(city, age, people_uuids)
                result.extend(self.calculation_standard_score(datas, city, age, crowd))
            pass
        else:
            print('获取所有case的数据...')
            for city in self.citys:
                for age in self.age:
                    if city != '上海市' and age != '85-89年生':
                        for crowd_type in self.crowd:
                            # print(' {}{}'.format(city, age))
                            people_uuids = self.get_people_uuid_by_type(crowd_type)
                            if len(people_uuids) > 0:
                                print('{}-{}-{}'.format(city, age, crowd_type))
                                datas = self.behavior_tag_init(city, age, people_uuids)
                                result.extend(self.calculation_standard_score(datas, city, age, crowd_type))
        return result

    def behavior_tag_init(self, city, age, people_uuids):
        result = {}
        self.group_type_count = self.marketing_db.select(self.sql_5, [city, city, age, people_uuids])
        for key in self.tag_data:
            values = self.tag_data[key]
            elements = []
            for value in values:
                question = value[0].split('-')[0]
                option = value[0].split('-')[1]
                corr = value[1]
                fz, fm = self.molecular_value(question, option, city, age, people_uuids)
                if fm == 0:
                    c = 0
                else:
                    c = fz / fm
                elements.append([question, option, corr, fz, fm, c])
            result[key] = elements
        return self.indicator_calculation_d_e(result)

    def molecular_value(self, queston, option, city, age, people_uuids):
        # 获取当前父选项包含的子选项id和子题id列表
        result = self.shangju_db.select(self.sql_6, [option, queston])
        sub_option_ids = []
        group_types = []
        for rt in result:
            sub_option_id, sub_question_id, content = rt[0], rt[1], rt[2]
            grouptypes = self.shangju_db.select(self.sql_7, [sub_question_id])
            for g_t in grouptypes:
                if g_t[0] not in group_types:
                    group_types.append(g_t[0])
            sub_option_ids.append(sub_option_id)
        # 计算子选项在答题记录中的点击数

        sub_options_count = 0
        if len(sub_option_ids) > 0:
            result_1 = self.marketing_db.select(self.sql_8, [sub_option_ids, city, city, age, people_uuids])
            sub_options_count = result_1[0][0]
        # 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。
        denominator_value = 0
        for info in self.group_type_count:
            if info[0] in group_types:
                denominator_value += info[1]
        return sub_options_count, denominator_value

    def indicator_calculation_d_e(self, data):
        result = {}
        for key in data.keys():
            values = data[key]
            c_list = [x[5] for x in values]
            fm_list = [x[4] for x in values]
            sum_c = sum(fm_list)
            min_c = min(c_list)
            elements = []
            for value in values:
                _value = []
                c = value[5]
                if sum_c == 0:
                    d = 0
                else:
                    d = c / sum_c
                e = c - min_c
                _value.extend(value)
                _value.append(d)
                _value.append(e)
                elements.append(_value)
            result[key] = elements
        return result

    def calculation_standard_score(self, datas, city, age, crowd_type):
        scores = []
        for key in datas.keys():
            print(key)
            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')
            values = [x[5] for x in datas[key]]
            min_c = min(values)
            f = min_c
            for value in datas[key]:
                print('     {}'.format(value))
                if value[2] is not None and value[7] is not None:
                    f += float(value[2] * value[7])
            print('     标准分：{}'.format(f))
            scores.append([city, age, key, crowd_type, f])
        # self.shangju_db.add_some(self.sql_9, scores)
        return scores

    def get_crowd_people(self):
        result = {}
        for type in self.crowd:
            uuids = self.get_people_uuid_by_type(type)
            result[type] = len(uuids)
        return result

    def get_people_uuid_by_type(self, type):
        uuids = []
        type_sub_option_ids = self.crowd_contain_sub_option_ids[type]
        for people in self.people_sub_option_ids:
            uuid = people[0]
            sub_option_ids = list(map(int, str(people[1]).split(',')))
            # list(set(a).intersection(set(b)))
            if len(list(set(sub_option_ids).intersection(set(type_sub_option_ids)))) > 0:
                uuids.append(uuid)
        return uuids

    def get_crowd_contain_sub_option_ids(self):
        """
            获取ABCDEF人群包含的子选项id
        :return:
        """
        infos = {}
        for key in self.crowd_info.keys():
            values = self.crowd_info[key]
            sub_option_ids = []
            for value in values:
                if value is not None:
                    vals = str(value).split('-')
                    option, question = vals[1], vals[0]
                    query_result = self.shangju_db.select(self.sql_6, [option, question])
                    for qr in query_result:
                        sub_option_id, sub_question_id, content = qr[0], qr[1], qr[2]
                        sub_option_ids.append(int(sub_option_id))
            infos[key] = sub_option_ids
        print(infos)
        return infos


class ExcelUtil:
    # 当前项目路径
    dir_path = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) + r'/elab_mvp/resources'
    """
        解析excel文件
    """

    def __init__(self, sheet_name=None, path=None):
        if path:
            self.path = path
        else:
            self.path = os.path.join(self.dir_path, 'mvp.xlsx')
        if sheet_name:
            self.sheet_name = sheet_name
        else:
            self.sheet_name = '硬标签+行为'

    def read_excel_by_pd(self):
        df = pd.read_excel(self.path)
        data = df.head()
        print('获取到的数据{}'.format(data))

    def read_excel_by_ox(self):
        work_book = ox.load_workbook(self.path, data_only=True)
        work_sheet = work_book.get_sheet_by_name(self.sheet_name)
        # print('max_row:{}, max_col:{}'.format(work_sheet.max_row, work_sheet.max_column))
        return work_sheet

    def init_crowd_info(self):
        """
            整理不同人群包含的父选序号
        :return:
        """
        rows = [row for row in self.read_excel_by_ox().rows]
        crowd_a = []
        crowd_b = []
        crowd_c = []
        crowd_d = []
        crowd_e = []
        crowd_f = []

        for row in rows[2:]:
            option = row[4].value
            a = row[6].value
            if a is not None and a == 1 and option not in crowd_a:
                crowd_a.append(option)
            b = row[7].value
            if b is not None and b == 1 and option not in crowd_b:
                crowd_b.append(option)
            c = row[8].value
            if c is not None and c == 1 and option not in crowd_d:
                crowd_c.append(option)
            d = row[9].value
            if d is not None and d == 1 and option not in crowd_d:
                crowd_d.append(option)
            e = row[10].value
            if e is not None and e == 1 and option not in crowd_e:
                crowd_e.append(option)
            f = row[11].value
            if f is not None and f == 1 and option not in crowd_f:
                crowd_f.append(option)
        return {'A': crowd_a, 'B': crowd_b, 'C': crowd_c, 'D': crowd_d, 'E': crowd_e, 'F': crowd_f}

    def init_mvp_data(self):
        """
            获取每个标签包括的父题父选项编号
        :return:
        """
        rows = [row for row in self.read_excel_by_ox().rows][24:]
        tag_name = None
        datas = []
        for row in rows:
            tag = row[1].value
            values = row[3].value
            corr = row[4].value
            if tag:
                tag_name = tag
            if values is not None:
                datas.append([tag_name, values, corr])
        result = {}
        for name, items in groupby(datas, key=lambda obj: obj[0]):
            orders = []
            for n in items:
                orders.append([n[1], n[2]])
            result[name] = orders
        return result


class MysqlDB:
    """
        mysql操作
    """
    con = None
    cursor = None

    def __init__(self, db_name):
        self.db_name = db_name
        self.con = ps.connect(host='172.19.189.136', port=3306, user='bi_etl', password='XPtpswuU5lwGo4kx',
                              db=self.db_name, charset='utf8')
        # self.con = ps.connect(host='192.168.0.13', port=3306, user='root', password='elab@123'
        #                       , db=self.db_name, charset='utf8')
        self.cursor = self.con.cursor()

    def show_tables(self):
        self.cursor.execute('show tables')
        for talbe in self.cursor.fetchall():
            print(talbe)

    def select(self, sql, params=None):
        if params:
            self.cursor.execute(sql, params)
        else:
            self.cursor.execute(sql)
        return self.cursor.fetchall()

    def add_some(self, sql, data):
        try:
            self.cursor.executemany(sql, data)
            self.con.commit()
        except:
            print('数据插入异常...')
            self.con.rollback()

    def add_one(self, sql, data):
        try:
            self.cursor.execute(sql, data)
            self.con.commit()
        except:
            self.con.rollback()

    def truncate(self, table_name):
        sql = 'truncate table {}'.format(table_name)
        self.cursor.execute(sql)
        self.con.commit()

    def close(self):
        self.cursor.close()
        self.con.close()


@app.route('/behavioral_statistics', methods=['GET', 'POST'])
def behavioral_statistics():
    city = request.args.get('city', default=None, type=str)
    age = request.args.get('age', default=None, type=str)
    crowd = request.args.get('crowd', default=None, type=str)
    print(city, age, crowd)
    mvp = Mvp()
    scores = mvp.query_behavioral_info(city, age, crowd)
    mvp.shangju_db.close()
    mvp.marketing_db.close()
    return json.dumps(scores, ensure_ascii=False)


@app.route('/infos', methods=["GET", 'POST'])
def get_city_age_crowd():
    mvp = Mvp()
    infos = {'城市': mvp.citys, '年龄段': mvp.age}
    mvp.shangju_db.close()
    mvp.marketing_db.close()
    return json.dumps(infos, ensure_ascii=False)


@app.route('/crowd_people', methods=['GET', 'POST'])
def crowd_people():
    mvp = Mvp()
    people_count = mvp.get_crowd_people()
    return json.dumps(people_count, ensure_ascii=False)


if __name__ == '__main__':
    app.run(
        host='0.0.0.0',
        port=5001
    )