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@@ -372,8 +372,8 @@ class Mvp:
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城市 年龄 人群分类 模块名称 分数
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:return:
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"""
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- import json
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- print(json.dumps(scores, ensure_ascii=False))
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+ # import json
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+ # print(json.dumps(scores, ensure_ascii=False))
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modules = self.module_scores[crowd]
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result = []
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for key in modules.keys():
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@@ -496,25 +496,25 @@ class Mvp:
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print('获取所有case的数据...')
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# for city in self.citys:
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for cy in self.city_list:
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- for age in self.age_list:
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+ for age_1 in self.age_list:
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for crowd_type in self.crowd:
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- if age == '85-89年生' and cy == '上海市':
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+ if age_1 == '85-89年生' and cy == '上海市':
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print('上海市85后数据导入人工值，无需计算...')
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pass
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else:
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# print(' {}{}'.format(city, age))
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# people_uuids = self.get_people_uuid_by_type(crowd_type)
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- people_uuids = self.people_filter(cy, age, crowd)
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+ people_uuids = self.people_filter(cy, age_1, crowd)
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behavior_data = None
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if len(people_uuids) > 0:
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- print('{}-{}-{}'.format(cy, age, crowd_type))
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- datas = self.behavior_tag_init(cy, age, people_uuids)
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+ print('{}-{}-{}'.format(cy, age_1, crowd_type))
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+ datas = self.behavior_tag_init(cy, age_1, people_uuids)
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data_start.append(datas)
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- all_data, behavior_data_1 = self.calculation_standard_score(datas, cy, age, crowd_type)
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+ all_data, behavior_data_1 = self.calculation_standard_score(datas, cy, age_1, crowd_type)
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result.append(all_data)
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behavior_data = behavior_data_1
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if behavior_data:
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- module_scores.extend(self.module_score(crowd_type, cy, age, behavior_data))
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+ module_scores.extend(self.module_score(crowd_type, cy, age_1, behavior_data))
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# data_list = []
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# for e in data_start:
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# for key in e.keys():
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