test(recommend): RecommendServiceImpl Mockito 单测（11 项）

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

mango-application/src/test/java/com/mangoo/rating/recommend/cart/RecommendServiceImplTest.java

@@ -0,0 +1,268 @@
+package com.mangoo.rating.recommend.cart;
+
+import com.mangoo.rating.recommend.AjaxResult;
+import com.mangoo.rating.recommend.config.RecommendProperties;
+import com.mangoo.rating.recommend.enums.MatchLevelEnum;
+import com.mangoo.rating.recommend.manager.RatingRecommendRuleManager;
+import com.mangoo.rating.recommend.po.RatingRecommendRulePO;
+import com.mangoo.rating.recommend.request.recommend.RecommendCardDTO;
+import com.mangoo.rating.recommend.request.recommend.RecommendRequest;
+import com.mangoo.rating.recommend.response.recommend.OrderSuggestionVO;
+import com.mangoo.rating.recommend.response.recommend.RecommendResultVO;
+import com.mangoo.rating.recommend.service.impl.RecommendServiceImpl;
+import com.mangoo.rating.recommend.service.recommend.EfficiencyPriceProvider;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.extension.ExtendWith;
+import org.mockito.InjectMocks;
+import org.mockito.Mock;
+import org.mockito.junit.jupiter.MockitoExtension;
+
+import java.math.BigDecimal;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.Map;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertNotEquals;
+import static org.junit.jupiter.api.Assertions.assertNull;
+import static org.mockito.ArgumentMatchers.any;
+import static org.mockito.ArgumentMatchers.anyString;
+import static org.mockito.Mockito.lenient;
+import static org.mockito.Mockito.when;
+
+/**
+ * RecommendServiceImpl Mockito 单测（11 项）
+ *
+ * 覆盖：入参校验、L1/L2/L3/兜底降级、规则时效非法跳过、价格缺失、
+ *      多档分组、同档合并、图片透传。
+ *
+ * 备注：AjaxResult 同时继承 HashMap 且提供 getCode() Bean 方法，
+ *      这里统一采用 Map 风格 .get("code") / .get("data") 取值。
+ *
+ * @author gengjintao
+ * @date 2026/06/24
+ */
+@ExtendWith(MockitoExtension.class)
+class RecommendServiceImplTest {
+
+    /** 规则查询 Manager Mock */
+    @Mock
+    private RatingRecommendRuleManager ruleManager;
+
+    /** 价格 Provider Mock */
+    @Mock
+    private EfficiencyPriceProvider priceProvider;
+
+    /** 配置属性 Mock */
+    @Mock
+    private RecommendProperties recommendProperties;
+
+    /** 被测对象：按类型注入上述 3 个 Mock */
+    @InjectMocks
+    private RecommendServiceImpl recommendService;
+
+    /**
+     * 公共桩：默认兜底档=1，上限=50，价格 Map={1:50.00, 2:100.00, 3:200.00}。
+     * 用 lenient() 避免严格模式下"未使用 stub"告警。
+     */
+    @BeforeEach
+    void setUp() {
+        lenient().when(recommendProperties.getDefaultEfficiency()).thenReturn(1);
+        lenient().when(recommendProperties.getBatchMax()).thenReturn(50);
+        Map<Integer, BigDecimal> defaultPrices = new HashMap<>();
+        defaultPrices.put(1, new BigDecimal("50.00"));
+        defaultPrices.put(2, new BigDecimal("100.00"));
+        defaultPrices.put(3, new BigDecimal("200.00"));
+        lenient().when(priceProvider.loadEfficiencyPrices()).thenReturn(defaultPrices);
+    }
+
+    /** 构造卡入参 DTO 的便捷方法 */
+    private RecommendCardDTO card(String id, String player, String year, String series, String cardSet) {
+        RecommendCardDTO d = new RecommendCardDTO();
+        d.setClientCardId(id);
+        d.setPlayer(player);
+        d.setYear(year);
+        d.setSeries(series);
+        d.setCardSet(cardSet);
+        return d;
+    }
+
+    /** 构造请求体 */
+    private RecommendRequest req(RecommendCardDTO... cards) {
+        RecommendRequest r = new RecommendRequest();
+        r.setCards(new ArrayList<>(Arrays.asList(cards)));
+        return r;
+    }
+
+    /** 构造规则 PO（只填推荐时效字段即可） */
+    private RatingRecommendRulePO rule(Integer eff) {
+        RatingRecommendRulePO po = new RatingRecommendRulePO();
+        po.setRecommendEfficiency(eff);
+        return po;
+    }
+
+    /** 从 AjaxResult（Map 风格）取出 code 数值 */
+    private int code(AjaxResult r) {
+        return ((Number) r.get("code")).intValue();
+    }
+
+    /** 从 AjaxResult（Map 风格）取出 data 数据体 */
+    private RecommendResultVO data(AjaxResult r) {
+        return (RecommendResultVO) r.get("data");
+    }
+
+    @Test
+    void 空入参_返回error() {
+        // null 请求
+        AjaxResult result = recommendService.recommendEfficiency(null);
+        assertNotEquals(0, code(result));
+
+        // 空卡列表
+        result = recommendService.recommendEfficiency(new RecommendRequest());
+        assertNotEquals(0, code(result));
+    }
+
+    @Test
+    void 超限_返回error() {
+        // 上限设置为 1，但传入 2 张卡 → 应返回 error
+        when(recommendProperties.getBatchMax()).thenReturn(1);
+        AjaxResult result = recommendService.recommendEfficiency(
+                req(card("c1", "p", "y", "s", "cs"), card("c2", "p", "y", "s", "cs")));
+        assertNotEquals(0, code(result));
+    }
+
+    @Test
+    void L1全等命中_单卡_单订单_含价格() {
+        // 四字段全等命中 → 推荐档 3（闪评），单价 200.00
+        when(ruleManager.selectByExact("Jordan", "1986", "Fleer", "Base")).thenReturn(rule(3));
+
+        AjaxResult result = recommendService.recommendEfficiency(req(card("c1", "Jordan", "1986", "Fleer", "Base")));
+        RecommendResultVO d = data(result);
+
+        assertEquals(1, d.getTotalCards());
+        assertEquals(1, d.getOrderCount());
+        OrderSuggestionVO order = d.getOrders().get(0);
+        assertEquals(3, order.getEfficiency());
+        assertEquals(MatchLevelEnum.EXACT.getCode(), order.getCards().get(0).getMatchLevel());
+        assertEquals(new BigDecimal("200.00"), order.getUnitPrice());
+        assertEquals(new BigDecimal("200.00"), order.getTotalAmount());
+        assertEquals(new BigDecimal("200.00"), d.getGrandTotal());
+    }
+
+    @Test
+    void L1未命中_L2命中_matchLevel为L2() {
+        // L1 返回 null → 走 L2，L2 命中 rule(2)
+        when(ruleManager.selectByExact(anyString(), anyString(), anyString(), anyString())).thenReturn(null);
+        when(ruleManager.selectBySeriesSetYear("Fleer", "Base", "1986")).thenReturn(rule(2));
+
+        AjaxResult result = recommendService.recommendEfficiency(req(card("c1", "Jordan", "1986", "Fleer", "Base")));
+        RecommendResultVO d = data(result);
+        assertEquals(MatchLevelEnum.L2.getCode(), d.getOrders().get(0).getCards().get(0).getMatchLevel());
+        assertEquals(2, d.getOrders().get(0).getEfficiency());
+    }
+
+    @Test
+    void L1L2未命中_L3命中_matchLevel为L3() {
+        // L1、L2 均返回 null → 走 L3，L3 命中 rule(2)
+        when(ruleManager.selectByExact(anyString(), anyString(), anyString(), anyString())).thenReturn(null);
+        when(ruleManager.selectBySeriesSetYear(anyString(), anyString(), anyString())).thenReturn(null);
+        when(ruleManager.selectBySeriesSet("Fleer", "Base")).thenReturn(rule(2));
+
+        AjaxResult result = recommendService.recommendEfficiency(req(card("c1", "Jordan", "1986", "Fleer", "Base")));
+        RecommendResultVO d = data(result);
+        assertEquals(MatchLevelEnum.L3.getCode(), d.getOrders().get(0).getCards().get(0).getMatchLevel());
+    }
+
+    @Test
+    void 三层均未命中_走兜底_matchLevel为DEFAULT() {
+        // 三层全 null → 走 DEFAULT，时效=defaultEfficiency=1
+        when(ruleManager.selectByExact(any(), any(), any(), any())).thenReturn(null);
+        when(ruleManager.selectBySeriesSetYear(any(), any(), any())).thenReturn(null);
+        when(ruleManager.selectBySeriesSet(any(), any())).thenReturn(null);
+
+        AjaxResult result = recommendService.recommendEfficiency(req(card("c1", "X", "Y", "Z", "W")));
+        RecommendResultVO d = data(result);
+        assertEquals(MatchLevelEnum.DEFAULT.getCode(), d.getOrders().get(0).getCards().get(0).getMatchLevel());
+        assertEquals(1, d.getOrders().get(0).getEfficiency());
+    }
+
+    @Test
+    void 规则时效非法_跳过该层继续降级() {
+        // L1 命中 rule(99) → recommendEfficiency=99 不在 EvaluateEfficiencyEnum 范围内 → isLegalRule=false
+        // → 继续 L2，L2 返回合法 rule(2) → matchLevel=L2
+        when(ruleManager.selectByExact(any(), any(), any(), any())).thenReturn(rule(99));
+        when(ruleManager.selectBySeriesSetYear(any(), any(), any())).thenReturn(rule(2));
+        AjaxResult result = recommendService.recommendEfficiency(req(card("c1", "p", "y", "s", "cs")));
+        RecommendResultVO d = data(result);
+        assertEquals(MatchLevelEnum.L2.getCode(), d.getOrders().get(0).getCards().get(0).getMatchLevel());
+    }
+
+    @Test
+    void 价格Map为空_订单与卡的单价均为null_grandTotal为null() {
+        // 全等命中 rule(3)，但价格 Map 为空 → 该档无价
+        // → 订单 unitPrice/totalAmount=null，卡级 unitPrice=null，grandTotal=null
+        when(ruleManager.selectByExact(any(), any(), any(), any())).thenReturn(rule(3));
+        when(priceProvider.loadEfficiencyPrices()).thenReturn(Collections.emptyMap());
+
+        AjaxResult result = recommendService.recommendEfficiency(req(card("c1", "p", "y", "s", "cs")));
+        RecommendResultVO d = data(result);
+        assertNull(d.getOrders().get(0).getUnitPrice());
+        assertNull(d.getOrders().get(0).getTotalAmount());
+        assertNull(d.getOrders().get(0).getCards().get(0).getUnitPrice());
+        assertNull(d.getGrandTotal());
+    }
+
+    @Test
+    void 多卡多档_按档位升序分3单_总计正确() {
+        // 三张卡分别命中 1/2/3 档 → 分 3 单（按档位升序）
+        // grandTotal = 50 + 100 + 200 = 350.00
+        when(ruleManager.selectByExact("p1", "y", "s", "cs")).thenReturn(rule(1));
+        when(ruleManager.selectByExact("p2", "y", "s", "cs")).thenReturn(rule(2));
+        when(ruleManager.selectByExact("p3", "y", "s", "cs")).thenReturn(rule(3));
+
+        AjaxResult result = recommendService.recommendEfficiency(req(
+                card("c1", "p1", "y", "s", "cs"),
+                card("c2", "p2", "y", "s", "cs"),
+                card("c3", "p3", "y", "s", "cs")));
+        RecommendResultVO d = data(result);
+        assertEquals(3, d.getOrderCount());
+        assertEquals(1, d.getOrders().get(0).getEfficiency());
+        assertEquals(2, d.getOrders().get(1).getEfficiency());
+        assertEquals(3, d.getOrders().get(2).getEfficiency());
+        assertEquals(new BigDecimal("350.00"), d.getGrandTotal());
+    }
+
+    @Test
+    void 同档多卡_合并为一单_单价不变_总计为单价乘以数量() {
+        // 3 张同档 2 卡 → 合并为 1 单，cardCount=3，unitPrice=100.00，totalAmount=300.00
+        when(ruleManager.selectByExact(any(), any(), any(), any())).thenReturn(rule(2));
+        AjaxResult result = recommendService.recommendEfficiency(req(
+                card("c1", "p", "y", "s", "cs"),
+                card("c2", "p", "y", "s", "cs"),
+                card("c3", "p", "y", "s", "cs")));
+        RecommendResultVO d = data(result);
+        assertEquals(1, d.getOrderCount());
+        OrderSuggestionVO order = d.getOrders().get(0);
+        assertEquals(3, order.getCardCount());
+        assertEquals(new BigDecimal("100.00"), order.getUnitPrice());
+        assertEquals(new BigDecimal("300.00"), order.getTotalAmount());
+    }
+
+    @Test
+    void 图片透传_前端clientCardId与图片原样返回() {
+        // 验证 clientCardId、frontImageUrl、backImageUrl 原样透传
+        when(ruleManager.selectByExact(any(), any(), any(), any())).thenReturn(rule(1));
+        RecommendCardDTO c = card("MY-CARD-1", "p", "y", "s", "cs");
+        c.setFrontImageUrl("http://x/f.jpg");
+        c.setBackImageUrl("http://x/b.jpg");
+
+        AjaxResult result = recommendService.recommendEfficiency(req(c));
+        RecommendResultVO d = data(result);
+        assertEquals("MY-CARD-1", d.getOrders().get(0).getCards().get(0).getClientCardId());
+        assertEquals("http://x/f.jpg", d.getOrders().get(0).getCards().get(0).getFrontImageUrl());
+        assertEquals("http://x/b.jpg", d.getOrders().get(0).getCards().get(0).getBackImageUrl());
+    }
+}