package org.kojh;

import java.nio.file.Files;
import java.nio.file.Path;
import jep.Interpreter;
import jep.SharedInterpreter;

public class Main {

    public static void main(String[] args) throws Exception{
        try (Interpreter interp = new SharedInterpreter()) {
            interp.exec("import pandas as pd");
            interp.exec("import numpy as np");
            interp.exec("dates = pd.date_range('1/1/2000', periods=8)");
            interp.exec("df = pd.DataFrame(np.random.randn(8, 4), index=dates, columns=['A', 'B', 'C', 'D'])");
            Object result1 = interp.getValue("df");
            System.out.println(result1);
        }
    }
}

try (Interpreter interp = new SharedInterpreter()) {
    interp.runScript("test.py");
    System.out.println( interp.getValue("merged1"));
    Object result = interp.getValue("merged1");
    System.out.println(result);
    System.out.println( interp.getValue("asof_result"));
}

try (Interpreter interp = new SharedInterpreter()) {
    interp.set("input1", "123");
    interp.set("input2", Arrays.asList(1,2,3,4,5));
    interp.exec("type1 = type(input1)");
    interp.exec("type2 = type(input2)");
    System.out.println( interp.getValue("type1"));  // <class 'str'>
    System.out.println( interp.getValue("type2"));  // <class 'java.util.Arrays$ArrayList'>
    System.out.println( interp.getValue("input1")); // "123"
    System.out.println( interp.getValue("input2")); // [1, 2, 3, 4, 5]
}

try (Interpreter interp = new SharedInterpreter()) {
    interp.exec("import pandas as pd");
    interp.exec("import numpy as np");
    interp.exec("import io");

    // --------------------------------------------------------------
    // java 에서 데이터를 넘겨서 python 에서 pandas dataframe 생성하기
    // 방법 1. map 을 전달해서 dataframe 생성
    Map<String, List<Object> > df = new HashMap<>();
    df.put("col1", Arrays.asList("val1","val2"));
    df.put("col2", Arrays.asList("val3","val4"));
    df.put("col3", Arrays.asList("val5","val6"));
    interp.set("input_map", df);
    interp.exec("dic = {} ");
    interp.exec("for key in input_map : dic[key] = input_map[key]");
    interp.exec("df_from_map = pd.DataFrame( dic ) ");
    interp.exec("df_from_map = df_from_map.sort_index(axis=1) ");
    System.out.println("\ndf from map ==> \n" + interp.getValue("df_from_map"));

    // 방법 2. json 을 전달해서 dataframe 생성
    String jsonDf ="{  \"col1\": {\"0\": \"val1\", \"1\": \"val2\"}, \"col2\": " +
        "{\"0\": \"val3\", \"1\": \"val4\"}, \"col3\": {\"0\": \"val5\", \"1\": \"val6\"}}";

    interp.set("input_json", jsonDf);
    interp.exec("df_from_json =  pd.read_json( io.StringIO(input_json) )");

    interp.exec("type = type(input_json)"); // <class 'str'>
    interp.exec("df_from_json = df_from_json.sort_index(axis=1) ");
    System.out.println("\ndf from json ==> \n" + interp.getValue("df_from_json"));

    // --------------------------------------------------------------
    // python 에서 json 으로 결과를 받고, 변경해서 다시 python 에 전달
    interp.exec("json_result = df_from_json.to_json() ");
    String json_result_from_python = interp.getValue("json_result", String.class);
    System.out.println("\njson result from python ==> \n" + json_result_from_python);

    JSONParser parser = new JSONParser();
    JSONObject jsonObject = (JSONObject) parser.parse(json_result_from_python);
    JSONObject col1JsonObj= (JSONObject) jsonObject.get("col1");

    // 받은 값을 변경해본다
    col1JsonObj.put("0", "XXX");
    col1JsonObj.put("1", "YYY");

    // 다시 python으로 전달..
    interp.set("input_json", jsonObject.toJSONString());
    interp.exec("df_from_json =  pd.read_json( io.StringIO(input_json) )");

    // 변경한 값이 제대로 전달 됐는지 확인
    interp.exec("type = type(input_json)"); // <class 'str'>
    interp.exec("df_from_json = df_from_json.sort_index(axis=1) ");
    System.out.println("\ndf from json ==> \n" + interp.getValue("df_from_json"));
}

interp.exec("result = jep.JEP_NUMPY_ENABLED");
System.out.println( interp.getValue("result")); // 0 or 1

try(SharedInterpreter interp = new SharedInterpreter()) {
   float[] f = new float[] { 1.0f, 2.1f, 3.3f, 4.5f, 5.6f, 6.7f };
   NDArray<float[]> nd = new NDArray<>(f, 3, 2);
   interp.set("x", nd);

   interp.exec("type = type(x)");
   System.out.println( interp.getValue("type"));
}

// <class 'jep.NDArray'>

try (Interpreter interp = new SharedInterpreter()) {
    interp.exec("import pandas as pd");
    interp.exec("import numpy as np");
    interp.exec("result = jep.JEP_NUMPY_ENABLED");
    System.out.println( interp.getValue("result"));

    // For ease and speed of copying the arrays between the two languages,
    // the Java arrays must be one dimensional.
    float[] f = new float[] { 1.0f, 2.1f, 3.3f, 4.5f, 5.6f, 6.7f };

    NDArray<float[]> nd = new NDArray<>(f, 3, 2);
    interp.set("x", nd);
    interp.exec("type = type(x)");
    interp.exec("shape = x.shape");
    interp.exec("df = pd.DataFrame( np.array(x) ) ");
    System.out.println( interp.getValue("type"));
    System.out.println( interp.getValue("shape"));
    System.out.println( interp.getValue("df"));
}
// 1
// <class 'numpy.ndarray'>
// [3, 2]

try (Interpreter interp = new SharedInterpreter()) {
    //python 에서 java 함수 호출
    interp.exec("from java.lang import System");
    interp.exec("s = 'Hello World'");
    interp.exec("System.out.println(s)");
    interp.exec("print(s)");
    interp.exec("print(s[1:-1])");
    interp.exec("System.out.println(s[1:-1])");
}
// Hello World
// ello Worl