Merge pull request #342 from softeerbootcamp-2nd/feat/recommend

추천 알고리즘 구현 및 flask 웹서버로 http통신 구현

backend-recommend/app.py

@@ -0,0 +1,12 @@
+from flask import Flask, request
+import recommend
+
+app = Flask(__name__)
+
+@app.route('/recommend/apriori', methods=['POST'])
+def apriori():
+    data = request.get_json()
+    return recommend.recByApriori(data)
+
+if __name__ == '__main__':
+    app.run(port=5001, debug=True)

backend-recommend/recommend.py

@@ -0,0 +1,63 @@
+import pandas as pd
+from mlxtend.preprocessing import TransactionEncoder
+from mlxtend.frequent_patterns import apriori, fpgrowth
+from mlxtend.frequent_patterns import association_rules
+import pymysql
+import time
+import os
+from dotenv import load_dotenv
+
+load_dotenv(verbose=True)
+
+conn = pymysql.connect(host=os.getenv('host'), user=os.getenv('user'), password=os.getenv('password'), db=os.getenv('db'))
+cur = conn.cursor()
+
+def recByApriori(body):
+    start = time.time()
+    carId = int(body['carId'])
+    powerTrainId = int(body['powerTrain'])
+    bodyTypeId = int(body['bodyType'])
+    operationId = int(body['operation'])
+
+    input = []
+
+    optionList = body['options']
+
+    for i in range(len(optionList)):
+        input.append(optionList[i]['subOptionId'])
+
+    input = set(input)
+    dataset = []
+    cur.execute('SELECT hm.history_id, sh.sold_count, sh.sold_options_id FROM SalesHistory sh INNER JOIN HistoryModelMapper hm ON sh.history_id = hm.history_id WHERE sh.car_id = %s AND hm.model_id IN (%s, %s, %s) GROUP BY hm.history_id HAVING COUNT(DISTINCT hm.model_id) = 3;', (carId, powerTrainId, bodyTypeId, operationId))
+    dbRow = cur.fetchall()
+    for j in range(len(dbRow)):
+        oneRow = dbRow[j][2]
+        if(oneRow == ''):
+            continue
+        options = oneRow.split(",")
+        for i in range(int(dbRow[j][1])):
+            dataset.append(options)
+
+    start = time.time()
+    te = TransactionEncoder()
+    te_ary = te.fit(dataset).transform(dataset)
+    df = pd.DataFrame(te_ary, columns=te.columns_)
+    frequent_itemsets = fpgrowth(df, min_support=0.05, use_colnames=True)
+
+    result_itemsets = association_rules(frequent_itemsets, metric="confidence", min_threshold=0.05) 
+    matching_itemsets = {}
+
+    consequent_results = set()
+
+    for idx, row in result_itemsets.iterrows():
+        confidence = row.confidence
+
+        if set(row.antecedents).issubset(input) and len(row.consequents) <= 2 and not set(row.antecedents).union(set(row.consequents)).issubset(input):
+            key = tuple(row.consequents)
+            if key not in matching_itemsets or confidence > matching_itemsets[key]:
+                matching_itemsets[key] = confidence
+
+    sorted_items = sorted(matching_itemsets.items(), key=lambda x: x[1], reverse=True)
+    top_items = sorted_items[:4]
+    top_consequents = [consequent for consequent, _ in top_items]
+    return top_consequents

backend-recommend/templates/index.html

@@ -0,0 +1 @@
+Invalid Access

backend/build.gradle

@@ -32,6 +32,7 @@ dependencies {
 	testImplementation 'org.springframework.boot:spring-boot-starter-test'
 	testImplementation group: 'com.h2database', name: 'h2', version: '2.2.220'
 	implementation 'org.springdoc:springdoc-openapi-ui:1.6.9'
+	implementation group: 'com.googlecode.json-simple', name: 'json-simple', version: '1.1.1'
 
 }
 

backend/src/main/java/autoever2/cartag/OpenApiConfig.java

@@ -12,7 +12,7 @@ public class OpenApiConfig {
     public OpenAPI openAPI() {
         Info info = new Info()
                 .version("v1.0.0")
-                .title("API 타이틀")
+                .title("A2-CARTAG API 명세서")
                 .description("API Description");
 
         return new OpenAPI()

backend/src/main/java/autoever2/cartag/controller/RecommendController.java

@@ -0,0 +1,20 @@
+package autoever2.cartag.controller;
+
+import autoever2.cartag.service.RecommendService;
+import lombok.RequiredArgsConstructor;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RestController;
+
+@RestController
+@RequestMapping("/api/recommend")
+@RequiredArgsConstructor
+public class RecommendController {
+
+    private final RecommendService recommendService;
+
+    @PostMapping("/list")
+    public String getRecommendedList() {
+        return recommendService.getList();
+    }
+}

backend/src/main/java/autoever2/cartag/service/RecommendService.java

@@ -0,0 +1,56 @@
+package autoever2.cartag.service;
+
+import org.json.simple.JSONArray;
+import org.json.simple.JSONObject;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.stereotype.Service;
+
+import java.net.URI;
+import java.net.http.HttpClient;
+import java.net.http.HttpRequest;
+import java.net.http.HttpResponse;
+
+@Service
+public class RecommendService {
+
+    @Value("${python.url")
+    private String requestURL;
+
+    //TODO: 응답 존재 안할 시 예외처리
+    public String getList() {
+        HttpClient client = HttpClient.newHttpClient();
+        HttpRequest request = HttpRequest.newBuilder()
+                .uri(URI.create(requestURL))
+                .POST(HttpRequest.BodyPublishers.ofString(getJsonFromEstimate())).build();
+
+        try {
+            HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
+            String body = response.body();
+            return body;
+        } catch (Exception e) {
+            e.getMessage();
+        }
+
+        return null;
+    }
+
+    public String getJsonFromEstimate() {
+        JSONObject jsonObject = new JSONObject();
+        jsonObject.put("carId", 1);
+        jsonObject.put("powerTrain", 1);
+        jsonObject.put("bodyType", 3);
+        jsonObject.put("operation", 5);
+
+        JSONArray jsonArray = new JSONArray();
+        JSONObject subOption = new JSONObject();
+        subOption.put("subOptionId", 69);
+        jsonArray.add(subOption);
+        subOption.put("subOptionId", 70);
+        jsonArray.add(subOption);
+
+        jsonObject.put("options", jsonArray);
+
+
+        return jsonObject.toJSONString();
+    }
+}