DataFushion的python算法插件
Project description
DataFushion_Plugins_Python说明
1.简介
针对Python算法在DataFushion平台使用所给出的插件,主要用于规范化算法的输入输出
2.使用
- Step1:引入datafushon包中的operation模块
- Step2:使用资源管理器进行数据拆解处理,并在其中实现自己需要实现的业务算法逻辑
from datafushion import operation
if __name__ == '__main__':
with operation() as destruction:
input_data_struct_list = destruction.input_data_struct_list
param_map = destruction.param_map
param_multiply = float(param_map['multiply'])
data_result = []
for input_data_struct in input_data_struct_list:
file_input_mapping = input_data_struct.file_input_mapping
data_list = input_data_struct.data_list
field_x = file_input_mapping['x'][0]
field_y = file_input_mapping['y'][0]
for data in data_list:
x = float(data[field_x])
y = float(data[field_y])
sum_result = param_multiply * (x + y)
res = {
"sum": sum_result,
"x": x,
"y": y,
}
data_result.append(res)
destruction.data_result = data_result
注意:
destruction为解构的HandleDataSet
实体类,
input_data_struct_list中包含了输入数据的封装,其类型为List
其元素为HandleInputDataStruct
类,包含的属性为file_type,file_path,file_input_mapping,data_list
算法需要使用的是file_input_mapping和data_list
data_list是输入数据的字典列表
file_input_mapping为输入数据字段的映射
param_map为算法的参数字典
在对数据进行业务算法处理完成后,需要将拆解的destruction中的data_result属性赋值为业务算法的最终数据结果
3.模型
DataFushion_Plugins_Python基础包中加入对PMML格式模型的依赖,以便后续需要在算法中读取已有的模型做准备
from pypmml import Model
if __name__ == '__main__':
model = Model.fromFile('model_file')
for item in model.inputFields:
print(item.name)
predict = model.predict({
'sepalWidth': 1.33,
'sepalLength': 2.44,
'petalsWidth': 5.87,
'petalsLength': 7.11,
})
print(predict)
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