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@@ -132,7 +132,8 @@ 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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- behavioral_score = scores['用户画像-行为兴趣']
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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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@@ -142,7 +143,7 @@ class Mvp:
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for value in values:
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behavioral_name = value[0]
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weight = float(value[2])
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- standard_score = [x[4] for x in behavioral_score if x[2] == behavioral_name]
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+ standard_score = [x[4] for x in scores if x[2] == behavioral_name]
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if len(standard_score) > 0:
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score += standard_score[0] * weight
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result.append([city, age, crowd, module_name, score])
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@@ -239,12 +240,16 @@ class Mvp:
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if city is not None and age is not None and crowd is not None:
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print('获取指定城市，年龄段，人群类型的数据...')
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people_uuids = self.get_people_uuid_by_type(crowd)
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+ behavior_data = None
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if len(people_uuids) > 0:
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print('{}-{}-{}'.format(city, age, crowd))
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datas = self.behavior_tag_init(city, age, people_uuids)
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data_start.append(datas)
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- result.extend(self.calculation_standard_score(datas, city, age, crowd))
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- module_scores.extend(self.module_score(crowd, city, age, result))
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+ all_data, behavior_data_1 = self.calculation_standard_score(datas, city, age, crowd)
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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, city, age, behavior_data))
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pass
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else:
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print('获取所有case的数据...')
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@@ -258,12 +263,16 @@ class Mvp:
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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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+ behavior_data = None
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if len(people_uuids) > 0:
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print('{}-{}-{}'.format(city, age, crowd_type))
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datas = self.behavior_tag_init(city, age, people_uuids)
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data_start.append(datas)
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- result.extend(self.calculation_standard_score(datas, city, age, crowd_type))
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- module_scores.extend(self.module_score(crowd_type, city, age, result))
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+ all_data, behavior_data_1 = self.calculation_standard_score(datas, city, age, crowd)
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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, city, age, behavior_data))
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# return result
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# data_list = []
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# for e in data_start:
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@@ -360,6 +369,7 @@ class Mvp:
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def calculation_standard_score(self, datas, city, age, crowd_type):
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scores = {}
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for key_tag_type in datas.keys():
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+ print(key_tag_type)
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tag_type_data = datas[key_tag_type]
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scores_sub = []
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for key_tag in tag_type_data.keys():
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@@ -377,7 +387,7 @@ class Mvp:
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scores_sub.append([city, age, key_tag, crowd_type, f])
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scores[key_tag_type] = scores_sub
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# self.shangju_db.add_some(self.sql_9, scores)
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- return scores
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+ return scores, scores['用户画像-行为兴趣']
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def get_crowd_people(self):
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result = {}
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