Python推荐算法脚本与Springboot的java接口封装（非常重要）

1、推荐算法的Python脚本文件（.py文件）：

ModelPredictAllLinux.py的Python脚本文件

import sys
import jieba
import joblib
import operator

#按照个数多少排序算法
def SortList(merge_predict_id_list):
    set_a = list(set(merge_predict_id_list))  # 去重得到一个集合
    count_set_a = {}  # 存放元素和出现次数的字典，key为元素,value为出现次数
    for item in set_a:
        count_set_a[item] = merge_predict_id_list.count(item)
    sorted_list_a = sorted(count_set_a.items(), key=operator.itemgetter(1))
    result_id_list = []  # 存放最后的结果
    for item in sorted_list_a[::-1]:  # 按value值从大到小排序
        result_id_list.append(item[0])
    return result_id_list
#预测主方法
def ModelPredict(newQuestionText):
    # 部署服务器存放机器学习模型的位置
    ModelSavePath = "/home/biiuser/ImmediateAction/ModelSave/"
    #对新工单的内容细节进行分词处理
    newQuestionJieba = jieba.cut(newQuestionText)
    newQuestionList = list(newQuestionJieba)
    newQuestionJiebaString = ' '.join(newQuestionList)
    tfChar = joblib.load("/home/biiuser/ImmediateAction/ModelSave/TFChar.pkl")
    textData = tfChar.transform([newQuestionJiebaString])
    newQuestionVec = textData.toarray()

    # 正常加载各个模型模型
    TargetNameList=["IS_RETURN","ORG_CODE","RETURN_REASON_CODE","RETURN_COMPANY_CODE","RETURN_REASON_CODE","CATEGORY_ID"]
    TargetNameList = ["IS_RETURN"]
    for i in range(len(TargetNameList)):
        TargetName=TargetNameList[i]
        log_OVO = joblib.load(ModelSavePath + TargetName + "_LogOVO_Model.pkl")
        svm = joblib.load(ModelSavePath + TargetName + "_SVM_Model.pkl")
        rf = joblib.load(ModelSavePath + TargetName + "_Bagging_Model.pkl")
        xgboost = joblib.load(ModelSavePath + TargetName + "_Boosting_Model.pkl")

        # 对预测结果进行合并去重处理
        if TargetName == "IS_RETURN":
            merge_predict_id_list = [xgboost.predict(newQuestionVec)[0]]
        else:
            merge_predict_id_list = [xgboost.predict(newQuestionVec)[0], rf.predict(newQuestionVec)[0],
                                     svm.predict(newQuestionVec)[0],
                                     log_OVO.predict(newQuestionVec)[0]]
        result_id_list=SortList(merge_predict_id_list)
        # 返回打印的结果
        print(result_id_list)

if __name__ == '__main__':
    ModelPredict(sys.argv[1]) #使用sys.argv实现java输入参数到Python脚本所需输入参数的传参

　　# for i in range(1, len(sys.argv)):
　　#     TargetName = sys.argv[i]
　　#     ModelTrain(TargetName)

2、springboot后端项目的java接口封装

package com.test.demo.controller;

import com.test.demo.annotation.AutoLog;
import com.test.demo.entity.CSVUtils;
import com.test.demo.entity.Result;
import io.swagger.annotations.ApiOperation;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.Calendar;
import java.util.regex.Matcher;
import java.util.regex.Pattern;

@RestController
@RequestMapping("/WorkOrderRecommendate")
public class WorkOrderRecommendateController {

    @AutoLog(value = "工单特定目标推荐算法调用接口（本地测试接口）")
    @ApiOperation(value = "工单特定目标推荐算法调用接口", notes = "工单党支部推荐算法调用接口")
    @GetMapping(value ="/ModelPredict")
    public Result> ModelPredict(@RequestParam(name = "detail") String detail,
                                                  @RequestParam(name = "targetName") String targetName) {
        Result> result= new Result>();
        try {
            long startTime=System.currentTimeMillis();   //获取开始时间
            String[] args1=new String[]{"python","./src/main/resources/ModelPredictLinux.py",detail,targetName};
            Process pr=Runtime.getRuntime().exec(args1);
            BufferedReader in = new BufferedReader(new InputStreamReader(pr.getInputStream(),"GBK"));
            String line;
            while ((line = in.readLine()) != null) {
                System.out.println("输出的结果是："+line);
                Pattern pattern= Pattern.compile("'(.*?)'");
                Matcher m = pattern.matcher(line);
                ArrayList list = new ArrayList();
                while (m.find()) {
                    list.add(m.group().trim().replace("'","")+"");
                }
                result.setResult(list);
            }
            in.close();
            pr.waitFor();
            System.out.println("end");
            long endTime=System.currentTimeMillis(); //获取结束时间
            result.setMessage("推荐算法的运行时间为:"+(endTime-startTime)/1000+"s");
        } catch (Exception e) {
            System.out.printf("接口调用失败");
            result.setMessage(e.getMessage());
        }
        return result;
    }

    @AutoLog(value = "工单综合推荐算法调用接口（本地测试接口）")
    @ApiOperation(value = "工单综合推荐算法调用接口", notes = "工单综合推荐算法调用接口")
    @GetMapping(value ="/ModelPredictAll")
    public Result> ModelPredictAll(@RequestParam(name = "detail") String detail) {
        Result> result= new Result>();
        try {
            long startTime=System.currentTimeMillis();   //获取开始时间
            String[] args1=new String[]{"python","./src/main/resources/ModelPredictAllLinux.py",detail};
            Process pr=Runtime.getRuntime().exec(args1);
            BufferedReader in = new BufferedReader(new InputStreamReader(pr.getInputStream(),"GBK"));
            String line;
            ArrayList listAll = new ArrayList();
            while ((line = in.readLine()) != null) {
                System.out.println("输出的结果是："+line);
                Pattern pattern= Pattern.compile("'(.*?)'");
                Matcher m = pattern.matcher(line);
                ArrayList list = new ArrayList();
                while (m.find()) {
                    list.add(m.group().trim().replace("'","")+"");
                }
                listAll.add(list);
                result.setResult(listAll);
            }
            in.close();
            pr.waitFor();
            System.out.println("end");
            long endTime=System.currentTimeMillis(); //获取结束时间
            result.setMessage("推荐算法的运行时间为:"+(endTime-startTime)/1000+"s");
        } catch (Exception e) {
            System.out.printf("接口调用失败");
            result.setMessage(e.getMessage());
        }
        return result;
    }

    @AutoLog(value = "工单特定目标推荐算法调用接口（服务器部署）")
    @ApiOperation(value = "工单特定目标推荐算法调用接口", notes = "工单特定目标推荐算法调用接口")
    @GetMapping(value ="/ModelPredictLinux")
    public Result> ModelPredictLinux(@RequestParam(name = "detail") String detail,
                                                       @RequestParam(name = "targetName") String targetName) {
        Result> result= new Result>();
        try {
            long startTime=System.currentTimeMillis();   //获取开始时间
            String[] args1=new String[]{"python3","/home/biiuser/ImmediateAction/PythonModel/ModelPredictLinux.py",detail,targetName};
            Process pr=Runtime.getRuntime().exec(args1);
            BufferedReader in = new BufferedReader(new InputStreamReader(pr.getInputStream(),"UTF-8"));
            String line;
            while ((line = in.readLine()) != null) {
                System.out.println("输出的结果是："+line);
                Pattern pattern= Pattern.compile("'(.*?)'");
                Matcher m = pattern.matcher(line);
                ArrayList list = new ArrayList();
                while (m.find()) {
                    list.add(m.group().trim().replace("'","")+"");
                }
                result.setResult(list);
            }
            in.close();
            pr.waitFor();
            System.out.println("end");
            long endTime=System.currentTimeMillis(); //获取结束时间
            result.setMessage("推荐算法的运行时间为:"+(endTime-startTime)/1000+"s");
        } catch (Exception e) {
            System.out.printf("接口调用失败");
            result.setMessage(e.getMessage());
        }
        return result;
    }

    @AutoLog(value = "工单综合推荐调用接口（服务器部署）")
    @ApiOperation(value = "工单综合推荐接口", notes = "工单综合推荐接口")
    @GetMapping(value ="/ModelPredictAllLinux")
    public Result> ModelPredictAllLinux(@RequestParam(name = "detail") String detail) {
        Result> result= new Result>();
        try {
            long startTime=System.currentTimeMillis();   //获取开始时间
            String[] args1=new String[]{"python3","/home/biiuser/ImmediateAction/PythonModel/ModelPredictAllLinux.py",detail};                #部署服务器上Python脚本的存放文件夹，需注意部署服务器上必须安装Python和推荐算法的运行环境
            Process pr=Runtime.getRuntime().exec(args1);
            BufferedReader in = new BufferedReader(new InputStreamReader(pr.getInputStream(),"UTF-8"));
            String line;
            ArrayList listAll = new ArrayList();
            while ((line = in.readLine()) != null) {
                System.out.println("输出的结果是："+line);
                Pattern pattern= Pattern.compile("'(.*?)'");
                Matcher m = pattern.matcher(line);
                ArrayList list = new ArrayList();
                while (m.find()) {
                    list.add(m.group().trim().replace("'","")+"");     //将Python脚本print输出的字符串列表进行逐个选取，实现Python脚本输出结果到java接口输出结果的传参
                }
                listAll.add(list);
                result.setResult(listAll);
            }
            in.close();
            pr.waitFor();
            System.out.println("end");
            long endTime=System.currentTimeMillis(); //获取结束时间
            result.setMessage("推荐算法的运行时间为:"+(endTime-startTime)/1000+"s");
        } catch (Exception e) {
            System.out.printf("接口调用失败");
            result.setMessage(e.getMessage());
        }
        return result;
    }

    @AutoLog(value = "推荐算法模型训练接口（本地测试）")
    @ApiOperation(value = "推荐算法模型训练接口", notes = "推荐算法模型训练接口")
    @GetMapping(value ="/ModelTrain")
    public  Result> modelTrain() {
        Result> result= new Result>();
        try {
            Calendar c_begin = Calendar.getInstance();//可以对每个时间域单独修改
            int year = c_begin.get(Calendar.YEAR);
            int month = c_begin.get(Calendar.MONTH);
            int date = c_begin.get(Calendar.DATE);
            int hour = c_begin.get(Calendar.HOUR_OF_DAY);
            int minute = c_begin.get(Calendar.MINUTE);
            int second = c_begin.get(Calendar.SECOND);
            System.out.println("开始时间为："+year + "/" + month + "/" + date + " " +hour + ":" +minute + ":" + second);

            System.out.println("startTraining...");
            long startTime=System.currentTimeMillis();   //获取模型开始训练的时间
            String[] args1=new String[]{"python","./src/main/resources/ModelTrainLinux.py"};
            Process pr=Runtime.getRuntime().exec(args1);
            BufferedReader in = new BufferedReader(new InputStreamReader(pr.getInputStream(),"GBK"));
            String line;
            ArrayList list = new ArrayList();
            while ((line = in.readLine()) != null) {
                System.out.println("输出的结果是："+line);
                list.add(line);
                result.setResult(list);
            }
            in.close();
            pr.waitFor();
            System.out.println("endTraining...");
            long endTime=System.currentTimeMillis(); //获取结束时间
            Calendar c_end = Calendar.getInstance();//可以对每个时间域单独修改
            int end_year = c_end.get(Calendar.YEAR);
            int end_month = c_end.get(Calendar.MONTH);
            int end_date = c_end.get(Calendar.DATE);
            int end_hour = c_end.get(Calendar.HOUR_OF_DAY);
            int end_minute = c_end.get(Calendar.MINUTE);
            int end_second = c_end.get(Calendar.SECOND);
            System.out.println("结束时间为："+end_year + "/" + end_month + "/" + end_date + " " +end_hour + ":" +end_minute + ":" + end_second);
            result.setMessage("推荐算法训练的时间为:"+(endTime-startTime)/60000+"min");
        } catch (Exception e) {
            e.printStackTrace();
        }
        return result;
    }

    @AutoLog(value = "推荐算法模型训练接口（服务器部署）")
    @ApiOperation(value = "推荐算法模型训练接口", notes = "推荐算法模型训练接口")
    @GetMapping(value ="/ModelTrainLinux")
    public  Result> modelTrainLinux() {
        Result> result= new Result>();
        try {
            Calendar c_begin = Calendar.getInstance();//可以对每个时间域单独修改
            int year = c_begin.get(Calendar.YEAR);
            int month = c_begin.get(Calendar.MONTH);
            int date = c_begin.get(Calendar.DATE);
            int hour = c_begin.get(Calendar.HOUR_OF_DAY);
            int minute = c_begin.get(Calendar.MINUTE);
            int second = c_begin.get(Calendar.SECOND);
            System.out.println("开始时间为："+year + "/" + month + "/" + date + " " +hour + ":" +minute + ":" + second);
            System.out.println("startTraining...");
            long startTime=System.currentTimeMillis();
            //获取模型开始训练的时间
            String[] args1=new String[]{"python3","/home/biiuser/ImmediateAction/PythonModel/ModelTrainLinux.py"};
            Process pr=Runtime.getRuntime().exec(args1);
            BufferedReader in = new BufferedReader(new InputStreamReader(pr.getInputStream(),"GBK"));
            String line;
            ArrayList list = new ArrayList();
            while ((line = in.readLine()) != null) {
                System.out.println("输出的结果是："+line);
                list.add(line);
                result.setResult(list);
            }
            in.close();
            pr.waitFor();
            System.out.println("endTraining...");
            long endTime=System.currentTimeMillis(); //获取结束时间
            Calendar c_end = Calendar.getInstance();//可以对每个时间域单独修改
            int end_year = c_end.get(Calendar.YEAR);
            int end_month = c_end.get(Calendar.MONTH);
            int end_date = c_end.get(Calendar.DATE);
            int end_hour = c_end.get(Calendar.HOUR_OF_DAY);
            int end_minute = c_end.get(Calendar.MINUTE);
            int end_second = c_end.get(Calendar.SECOND);
            System.out.println("结束时间为："+end_year + "/" + end_month + "/" + end_date + " " +end_hour + ":" +end_minute + ":" + end_second);
            result.setMessage("推荐算法训练的时间为:"+(endTime-startTime)/60000+"min");
        } catch (Exception e) {
            e.printStackTrace();
        }
        return result;
    }

    @AutoLog(value = "导出CSV文件类")
    @ApiOperation(value = "导出CSV文件类", notes = "导出SCV类")
    @GetMapping(value ="/testCSV")
    public void TestCSV(){
        System.err.printf("接口调用成功！");
        CSVUtils.writeCSV();
        return ;
    }
}

3、实现java接口的调用与测试