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void Main()
{
	// Write code to test your extensions here. Press F5 to compile and run.
}

public static class MyExtensions
{
	// Write custom extension methods here. They will be available to all queries.
	public static IEnumerable<T> ForEach<T>(this IEnumerable<T> source, Action<T> consumer)
	{

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using System.Collections.Concurrent;
using System.Net;
using System.Net.Sockets;
using System.Threading.Tasks;
using System.Collections.Generic;

async Task Main()
{
	Task.Factory.StartNew(ProcessWork, TaskCreationOptions.LongRunning);
	var listener = new TcpListener(IPAddress.Any, 12345);

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package me.line.music.support.cache.spring.providers.arcus;

import static org.junit.Assert.assertEquals;

import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.util.List;

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#!/usr/bin/env cppscript

std::cout << "hello world! << std::endl;

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{
  "query": {
    "function_score": {
      "query": {
        "bool": {
          "must": [{
              "multi_match": {
                "query": "구현",
                "type": "best_fields",
                "fuzziness": "0",

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{
  "query": {
    "function_score": {
      "query": {
        "multi_match": {
          "query": "c++",
          "type": "best_fields",
          "fuzziness": "auto",
          "analyzer": "sj_analyzer",
          "fields": ["title^1", "article^0.5", "tag^0.3"],

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{
  "query":{
    "match" : {
      "article": {
        "query": "reflection",
        "analyzer": "sj_analyzer"
      }
    }
  }
}

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{
  "properties": {
    "title": {
      "type": "text",
      "analyzer": "sj_analyzer"
    },
    "article": {
      "type": "text",
      "analyzer": "sj_analyzer"
    },

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{
  "number_of_shards": 1,
  "number_of_replicas": 0,
  "analysis": {
    "analyzer": {
      "sj_analyzer": {
        "type": "custom",
        "tokenizer": "sj_tokenizer",
        "filter": [
          "lowercase",

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from gensim.models import Word2Vec
from sklearn.cluster import KMeans
from flask import Flask, jsonify, request
import numpy

default_step_size=20
default_min_similarity=0.4
default_search_depth=1

app = Flask(__name__)