项目框架生成专家

{ "response": "需求解析与设计结论：\n- 项目目标：实时数据枢纽平台，支持多源接入、清洗、指标汇总与可视化。性能优先，强调批量写入、异步IO、缓存、消息压缩、分区与并行度调优。\n- 技术栈：Python（FastAPI + SQLAlchemy 2.x Async）、Kafka、Redis、PostgreSQL、Celery、OpenTelemetry、PyTest + Playwright、Docker Compose、Helm、前端 Vue3 + Vite + ECharts、数据格式 Parquet。\n- 目录结构：frontend、api、ingestion、jobs、infra。初始化模块：数据源管理、主题/分区配置、ETL模板、指标模型与维表。配置：Kafka、Redis、PostgreSQL、对象存储（MinIO/S3）、权限策略、环境变量模板。工程化：代码规范、单元/集成测试、性能基准、容器化与部署脚本、指标与日志采集。\n\n关键架构与优化策略：\n1) 后端（FastAPI）：\n- 使用 SQLAlchemy Async + 单次批量查询（IN 查询），避免 N+1。\n- CPU 密集计算通过 ProcessPoolExecutor 并行化，避免 GIL 限制；如超大批次通过 Celery 异步离线计算。\n- Redis 缓存：MGET 批量读取、Pipeline 批量写入、TTL 与版本号做失效管理。\n- OpenTelemetry：HTTP、DB、Redis、Kafka 自动/手动埋点，OTLP 输出到 Collector。\n- 指标与日志：Prometheus FastAPI exporter 或 OTEL Metric，JSON 结构化日志。\n\n2) 消息与调度：\n- Kafka 生产与消费使用压缩（zstd），在分区上按业务键（如用户/主题）做分区，提高局部性与并行度。\n- 消费者使用 aiokafka 异步消费 + 幂等写入（基于业务键 + 去重表/Redis 短期去重）。\n- 死信队列：主题 xxx.dlq，配合重试策略（指数退避、最大重试次数）。\n- Celery：任务用于离线批计算与补偿任务（任务幂等：task_id+参数签名）。\n\n3) 数据层：\n- PostgreSQL：分区表（按日期/业务键），批量写入（executemany + COPY）、索引优化（组合索引）。\n- 对象存储：Parquet 数据湖（MinIO 本地，S3 生产），ETL 模板将原始数据清洗后落 Parquet 并建 Delta 目录结构。\n\n4) 前端：\n- Vue3 + Vite + ECharts：仪表盘、图表与查询面板；Playwright 端到端测试；支持深链接与筛选参数。\n\n5) 工程化：\n- 代码规范：Black、isort、Flake8、mypy（可选）；pre-commit 钩子。\n- 测试：PyTest（unit/integration），Playwright（frontend），pytest-benchmark（性能基准）。\n- 容器化：Docker Compose（本地），Helm（生产）；OTEL Collector、Prometheus、Grafana。\n\n初始化代码与配置要点（摘要）：\n- api/app/config.py：集中读取环境变量（Postgres、Redis、Kafka、S3/MinIO、OTLP）。\n- api/app/tracing.py：OpenTelemetry FastAPI Instrumentation + OTLP exporter。\n- api/app/models：指标模型与维表，如 Metric, Dimension, MetricFact；维表（TimeDim, UserDim, SourceDim）。\n- ingestion/consumers/kafka_consumer.py：aiokafka 消费、幂等、重试与 DLQ。\n- ingestion/pipelines/etl_template.py：读取多源，清洗，写入 Parquet（pyarrow + fastparquet），并可触发下游指标计算。\n- jobs/celery_app.py：Celery 配置 broker=Redis/Kafka（推荐 Redis）+ backend=Redis；OpenTelemetry 集成。\n- infra/configs/kafka/topics.yaml：主题与分区配置（生产建议 12-48 分区，根据吞吐与消费者数调优），压缩 zstd。\n- infra/docker-compose.yml：包含 api、ingestion、jobs（worker+beat）、postgres、redis、kafka+zookeeper、minio、otel-collector、prometheus、grafana、frontend。\n- infra/env/.env.example：环境变量模板（见下）。\n\n示例环境变量模板（摘录）：\nPOSTGRES_DSN=postgresql+asyncpg://hub:hub@postgres:5432/hub\nREDIS_URL=redis://redis:6379/0\nKAFKA_BOOTSTRAP_SERVERS=kafka:9092\nKAFKA_COMPRESSION=zstd\nS3_ENDPOINT=http://minio:9000\nS3_ACCESS_KEY=minioadmin\nS3_SECRET_KEY=minioadmin\nS3_BUCKET=hub-raw\nOTLP_ENDPOINT=http://otel-collector:4317\nCELERY_BROKER_URL=redis://redis:6379/1\nCELERY_RESULT_BACKEND=redis://redis:6379/2\n\n权限策略：\n- RBAC：roles={admin, analyst, viewer}；基于路由声明权限，资源粒度到数据源与主题。策略文件 infra/configs/auth/policy.json。\n\n开发指南（快速开始）：\n1) 克隆与初始化：\n- 填写 infra/env/.env（复制 .env.example）。\n- 安装 pre-commit：pre-commit install。\n2) 本地启动：\n- docker compose up -d（首次会初始化 Postgres/Redis/Kafka/MinIO/OTEL）。\n- 前端：cd frontend && pnpm i && pnpm dev。\n3) 数据示例与字典：\n- 运行 infra/scripts/load_sample_data.py 导入样例数据集到 MinIO/Parquet 与 Postgres 维表。\n- data/dictionary.md 提供字段含义、业务口径与指标定义。\n4) 测试与基准：\n- 后端：pytest；性能：pytest -k benchmark。\n- 前端：pnpm test:e2e（Playwright）。\n5) 部署生产：\n- Helm：helm install data-hub infra/helm -f infra/helm/values.yaml。\n- 配置 Kafka ACL、Prometheus 抓取、Grafana dashboard 导入。\n\n性能调优默认值：\n- Kafka：compression.type=zstd；acks=all；linger.ms=50；batch.size=256KB；max.in.flight.requests.per.connection=1（保证顺序）。\n- Redis：合理 TTL；Pipeline 批量写；热点键加随机后缀防击穿；BloomFilter/Set 去重（可选）。\n- DB：连接池大小=CPU*2；prepared statements；COPY 批导；维表用主键+必要索引。\n- 并行：ProcessPoolExecutor(max_workers=os.cpu_count())；消费者并行度=分区数；避免过度切分导致上下文切换开销。\n", "optimized_code": "from typing import List, Dict, Any\nimport os\nimport asyncio\nfrom fastapi import APIRouter, Depends, Query, HTTPException\nfrom pydantic import BaseModel\nfrom sqlalchemy import select\nfrom sqlalchemy.orm import load_only\nfrom sqlalchemy.ext.asyncio import AsyncSession\nfrom concurrent.futures import ProcessPoolExecutor\n\n# ---- Dependencies & placeholders (wire these in your app) ----\n# Provide actual implementations in api/app/deps.py\nasync def get_session() -> AsyncSession: ...\nasync def get_redis() -> "Redis": ... # aioredis client\n\n# ORM model and CPU-heavy compute function\nclass Model: # SQLAlchemy ORM mapped class\n id: int\n a: float\n b: float\n\n# Example CPU-heavy function (must be pure & picklable)\ndef compute(a: float, b: float) -> float:\n # Simulate expensive calculation\n return (a ** 2 + b ** 2) ** 0.5\n\n# Batch compute helper to minimize IPC overhead\ndef compute_many(payloads: List[Dict[str, Any]]) -> Dict[int, float]:\n return {p["id"]: compute(p["a"], p["b"]) for p in payloads}\n\nclass MetricOut(BaseModel):\n id: int\n value: float\n\nrouter = APIRouter()\n\nCACHE_TTL_SECONDS = 300\n\n@router.get("/metrics", response_model=List[MetricOut])\nasync def metrics(\n ids: List[int] = Query(..., description="Metric IDs to compute"),\n session: AsyncSession = Depends(get_session),\n redis = Depends(get_redis),\n):\n if not ids:\n raise HTTPException(status_code=400, detail="ids cannot be empty")\n\n # 1) Batch cache lookup\n keys = [f"metric:v1:{i}" for i in ids]\n cached_vals = await redis.mget(keys)\n cache_hit: Dict[int, float] = {}\n missing_ids: List[int] = []\n for i, raw in zip(ids, cached_vals):\n if raw is not None:\n try:\n cache_hit[i] = float(raw)\n except ValueError:\n missing_ids.append(i)\n else:\n missing_ids.append(i)\n\n # 2) Single DB batch query for missing ids\n payloads: List[Dict[str, Any]] = []\n if missing_ids:\n result = await session.execute(\n select(Model)\n .options(load_only(Model.id, Model.a, Model.b))\n .where(Model.id.in_(missing_ids))\n )\n items: List[Model] = result.scalars().all()\n if len(items) != len(missing_ids):\n found_ids = {m.id for m in items}\n not_found = [mid for mid in missing_ids if mid not in found_ids]\n if not_found:\n # Soft-fail the missing ids; you may choose to 404 instead\n missing_ids = [mid for mid in missing_ids if mid in found_ids]\n payloads = [{"id": m.id, "a": m.a, "b": m.b} for m in items]\n\n # 3) Parallel CPU compute in process pool (avoid GIL)\n computed: Dict[int, float] = {}\n if payloads:\n loop = asyncio.get_running_loop()\n # Use a shared executor; in production create it once per app\n with ProcessPoolExecutor(max_workers=os.cpu_count()) as executor:\n computed = await loop.run_in_executor(executor, compute_many, payloads)\n\n # 4) Batch cache set with pipeline\n pipe = redis.pipeline()\n for mid, val in computed.items():\n pipe.set(f"metric:v1:{mid}", val, ex=CACHE_TTL_SECONDS)\n await pipe.execute()\n\n # 5) Assemble response preserving input order\n values: Dict[int, float] = {**cache_hit, **computed}\n rows = [MetricOut(id=i, value=values[i]) for i in ids if i in values]\n\n return rows\n", "project_structure": [ "数据枢纽平台/", "├── frontend/", "│ ├── src/", "│ │ ├── main.ts", "│ │ ├── App.vue", "│ │ ├── pages/", "│ │ │ ├── Dashboard.vue", "│ │ │ └── QueryPanel.vue", "│ │ ├── components/", "│ │ │ ├── charts/", "│ │ │ │ ├── MetricLine.vue", "│ │ │ │ └── TopKBar.vue", "│ │ │ └── layout/", "│ │ │ └── PageShell.vue", "│ │ ├── services/", "│ │ │ └── api.ts", "│ │ └── router/", "│ │ └── index.ts", "│ ├── vite.config.ts", "│ ├── package.json", "│ ├── tsconfig.json", "│ └── tests/", "│ └── e2e/", "│ ├── playwright.config.ts", "│ └── dashboard.spec.ts", "├── api/", "│ ├── app/", "│ │ ├── main.py", "│ │ ├── config.py", "│ │ ├── deps.py", "│ │ ├── tracing.py", "│ │ ├── logging.py", "│ │ ├── routers/", "│ │ │ ├── metrics.py", "│ │ │ ├── datasources.py", "│ │ │ ├── topics.py", "│ │ │ └── auth.py", "│ │ ├── models/", "│ │ │ ├── base.py", "│ │ │ ├── dimension.py", "│ │ │ └── metric.py", "│ │ ├── schemas/", "│ │ │ ├── metric.py", "│ │ │ └── datasource.py", "│ │ ├── services/", "│ │ │ ├── cache.py", "│ │ │ ├── compute.py", "│ │ │ ├── storage.py", "│ │ │ └── kafka_producer.py", "│ │ ├── auth/", "│ │ │ ├── rbac.py", "│ │ │ └── policy_loader.py", "│ │ ├── tests/", "│ │ │ ├── unit/", "│ │ │ │ └── test_metrics.py", "│ │ │ └── integration/", "│ │ │ └── test_api_integration.py", "│ │ └── alembic/", "│ │ ├── env.py", "│ │ ├── script.py.mako", "│ │ └── versions/", "│ ├── pyproject.toml", "│ ├── requirements.txt", "│ └── pre-commit-config.yaml", "├── ingestion/", "│ ├── consumers/", "│ │ ├── kafka_consumer.py", "│ │ └── dlq_handler.py", "│ ├── pipelines/", "│ │ ├── etl_template.py", "│ │ └── parquet_writer.py", "│ ├── schemas/", "│ │ └── datasource.json", "│ └── tests/", "│ └── test_ingestion.py", "├── jobs/", "│ ├── celery_app.py", "│ ├── tasks/", "│ │ ├── metrics.py", "│ │ └── housekeeping.py", "│ └── schedules/", "│ └── beat_schedule.py", "├── infra/", "│ ├── docker-compose.yml", "│ ├── helm/", "│ │ ├── Chart.yaml", "│ │ ├── values.yaml", "│ │ └── templates/", "│ │ ├── deployment-api.yaml", "│ │ ├── deployment-ingestion.yaml", "│ │ ├── deployment-jobs.yaml", "│ │ ├── service-api.yaml", "│ │ └── configmap-env.yaml", "│ ├── k8s/", "│ │ ├── api-deployment.yaml", "│ │ └── otel-collector.yaml", "│ ├── configs/", "│ │ ├── kafka/", "│ │ │ ├── topics.yaml", "│ │ │ └── client.properties", "│ │ ├── postgres/", "│ │ │ └── init.sql", "│ │ ├── redis/", "│ │ │ └── redis.conf", "│ │ ├── auth/", "│ │ │ └── policy.json", "│ │ ├── otel/", "│ │ │ └── collector-config.yaml", "│ │ └── grafana/", "│ │ └── dashboards/", "│ │ └── hub-overview.json", "│ ├── env/", "│ │ └── .env.example", "│ ├── scripts/", "│ │ ├── init.sh", "│ │ ├── load_sample_data.py", "│ │ └── benchmark_metrics.py", "│ └── Makefile", "├── data/", "│ ├── sample/", "│ │ ├── sources.csv", "│ │ └── metrics.parquet", "│ └── dictionary.md", "└── README.md" ] }

{ "response": "已解析需求并为“移动零售套件”生成与 Go + Flutter 技术栈匹配的项目框架，优先保证快速开发。整体采用前后端分域分层与可观测性内建：移动端 Flutter + Riverpod 离线优先、主题切换；后端采用 Gin + GORM + REST，MySQL/Redis/Meilisearch/NATS，JWT 认证，OpenTelemetry + Prometheus。工程化包含统一代码规范、脚手架、测试、CI、Docker 镜像与 K8s 部署。关键设计建议：1) 领域分层：gateway(BFF/认证/聚合) + services(订单/库存/支付/用户) + infra(配置/部署/数据)；2) 状态管理约束：Riverpod ReadOnly/Notifier 分层，离线队列与缓存隔离(core/storage)，网络状态与合并策略独立(core/sync)；3) 幂等：服务端以 Idempotency-Key + 请求哈希表 + 唯一索引保证订单创建幂等；4) 离线数据合并：客户端维护操作队列与版本戳，采用“服务器权威 + 客户端补偿”策略，冲突时按字段级合并与重试；5) 可观测性：Gin/GORM 接入 OTel tracing，NATS 消费与接口指标暴露到 Prometheus，并在 mobile 埋点登录、下单、同步时序。以下提供项目结构、后端初始化与移动端初始化示例，以及优化后的订单创建代码。", "optimized_code": "package order\n\nimport (\n "crypto/sha256"\n "encoding/hex"\n "encoding/json"\n "errors"\n "net/http"\n "time"\n\n "github.com/gin-gonic/gin"\n "github.com/google/uuid"\n "gorm.io/gorm"\n)\n\n// Models\ntype Order struct {\n ID string gorm:\"primaryKey;size:36\" json:\"id\"\n StoreID string gorm:\"index;size:36\" json:\"store_id\"\n UserID string gorm:\"index;size:36\" json:\"user_id\"\n Status string gorm:\"index;size:16\" json:\"status\"\n TotalCents int64 json:\"total_cents\"\n Items []OrderItem gorm:\"foreignKey:OrderID\" json:\"items\"\n CreatedAt time.Time json:\"created_at\"\n}\n\ntype OrderItem struct {\n ID uint gorm:\"primaryKey\" json:\"-\"\n OrderID string gorm:\"index;size:36\" json:\"-\"\n SKU string gorm:\"index;size:64\" json:\"sku\"\n Name string gorm:\"size:128\" json:\"name\"\n UnitPriceCents int64 json:\"unit_price_cents\"\n Qty int json:\"qty\"\n SubtotalCents int64 json:\"subtotal_cents\"\n}\n\n// Idempotency record\ntype OrderRequest struct {\n ID uint gorm:\"primaryKey\"\n Key string gorm:\"uniqueIndex;size:128\"\n PayloadHash string gorm:\"size:128\"\n OrderID *string\n Status string gorm:\"size:16\" // pending/succeeded/failed\n CreatedAt time.Time\n}\n\n// Request DTO (price由服务端计算，客户端不传价格)\ntype CreateOrderRequest struct {\n StoreID string json:\"store_id\" binding:\"required\"\n Items []CreateOrderItem json:\"items\" binding:\"required,min=1,dive\"\n}\n\ntype CreateOrderItem struct {\n SKU string json:\"sku\" binding:\"required\"\n Qty int json:\"qty\" binding:\"required,min=1\"\n}\n\n// Product for price lookup\ntype Product struct {\n SKU string gorm:\"primaryKey;size:64\"\n Name string\n PriceCents int64\n Active bool\n}\n\n// Dependencies injected\ntype Handler struct {\n DB *gorm.DB\n // MsgBus, Cache, etc.\n}\n\nfunc NewHandler(db *gorm.DB) *Handler { return &Handler{DB: db} }\n\n// Utility\nfunc sha256Hex(b []byte) string { h := sha256.Sum256(b); return hex.EncodeToString(h[:]) }\n\n// Middleware should set userID from JWT to context key "userID"\n\n// CreateOrder implements robust, idempotent order creation.\nfunc (h *Handler) CreateOrder(c *gin.Context) {\n // Idempotency-Key required\n idemKey := c.GetHeader("Idempotency-Key")\n if idemKey == "" {\n c.JSON(http.StatusBadRequest, gin.H{"error": "Idempotency-Key header required"})\n return\n }\n\n var req CreateOrderRequest\n if err := c.ShouldBindJSON(&req); err != nil {\n c.JSON(http.StatusBadRequest, gin.H{"error": "invalid request", "detail": err.Error()})\n return\n }\n userID := c.GetString("userID")\n if userID == "" {\n c.JSON(http.StatusUnauthorized, gin.H{"error": "unauthorized"})\n return\n }\n\n payloadBytes, _ := json.Marshal(req)\n payloadHash := sha256Hex(payloadBytes)\n\n var existing OrderRequest\n tx := h.DB.WithContext(c.Request.Context())\n if err := tx.Where("key = ?", idemKey).First(&existing).Error; err == nil {\n // If request exists, return consistent result\n if existing.PayloadHash != payloadHash {\n c.JSON(http.StatusConflict, gin.H{"error": "idempotency key conflict"})\n return\n }\n if existing.OrderID != nil {\n var ord Order\n if err := tx.Preload("Items").First(&ord, "id = ?", *existing.OrderID).Error; err == nil {\n c.JSON(http.StatusOK, ord)\n return\n }\n }\n // pending: fallthrough to attempt completion\n } else if !errors.Is(err, gorm.ErrRecordNotFound) {\n c.JSON(http.StatusInternalServerError, gin.H{"error": "db error"})\n return\n }\n\n // transactional creation\n var created Order\n err := tx.Transaction(func(t *gorm.DB) error {\n // create placeholder idempotency record (unique key enforces single winner)\n reqRec := OrderRequest{Key: idemKey, PayloadHash: payloadHash, Status: "pending"}\n if err := t.Create(&reqRec).Error; err != nil {\n // another concurrent request won; re-read and return\n if errors.Is(err, gorm.ErrDuplicatedKey) {\n if err := t.Where("key = ?", idemKey).First(&existing).Error; err == nil && existing.OrderID != nil {\n return nil // will read after tx\n }\n }\n return err\n }\n\n // price lookup\n skus := make([]string, 0, len(req.Items))\n for _, it := range req.Items { skus = append(skus, it.SKU) }\n var products []Product\n if err := t.Where("sku IN ? AND active = ?", skus, true).Find(&products).Error; err != nil { return err }\n priceMap := map[string]Product{}\n for _, p := range products { priceMap[p.SKU] = p }\n // validate all items exist\n var items []OrderItem\n var total int64\n for _, it := range req.Items {\n p, ok := priceMap[it.SKU]\n if !ok { return errors.New("product not found: " + it.SKU) }\n subtotal := p.PriceCents * int64(it.Qty)\n items = append(items, OrderItem{\n SKU: p.SKU,\n Name: p.Name,\n UnitPriceCents: p.PriceCents,\n Qty: it.Qty,\n SubtotalCents: subtotal,\n })\n total += subtotal\n }\n\n ord := Order{\n ID: uuid.NewString(),\n StoreID: req.StoreID,\n UserID: userID,\n Status: "created",\n TotalCents: total,\n Items: items,\n }\n if err := t.Create(&ord).Error; err != nil { return err }\n\n // link idempotency record\n oid := ord.ID\n if err := t.Model(&OrderRequest{}).Where("id = ?", reqRec.ID).\n Updates(map[string]interface{}{"order_id": oid, "status": "succeeded"}).Error; err != nil { return err }\n\n created = ord\n return nil\n })\n\n if err != nil {\n if errors.Is(err, gorm.ErrRecordNotFound) {\n c.JSON(http.StatusBadRequest, gin.H{"error": "invalid items"})\n return\n }\n c.JSON(http.StatusInternalServerError, gin.H{"error": "failed to create order", "detail": err.Error()})\n return\n }\n\n // reload items (if we returned early on duplicate)\n if created.ID == "" && existing.OrderID != nil {\n var ord Order\n if err := tx.Preload("Items").First(&ord, "id = ?", *existing.OrderID).Error; err == nil {\n c.JSON(http.StatusOK, ord)\n return\n }\n c.JSON(http.StatusInternalServerError, gin.H{"error": "idempotent order retrieval failed"})\n return\n }\n\n c.JSON(http.StatusCreated, created)\n}\n\n// Router setup example\n// func SetupRoutes(r *gin.Engine, h Handler) {\n// r.Use(otelgin.Middleware("order-service")) // tracing\n// api := r.Group("/api").Use(JWTMiddleware())\n// api.POST("/orders", h.CreateOrder)\n// }\n", "project_structure": [ "移动零售套件/", "├─ mobile/", "│ ├─ app/", "│ │ ├─ lib/", "│ │ │ ├─ main.dart", "│ │ │ ├─ core/", "│ │ │ │ ├─ config/app_config.dart", "│ │ │ │ ├─ theme/theme_provider.dart", "│ │ │ │ ├─ network/http_client.dart", "│ │ │ │ ├─ storage/hive_box.dart", "│ │ │ │ ├─ sync/offline_queue.dart", "│ │ │ │ ├─ sync/conflict_resolver.dart", "│ │ │ │ ├─ auth/jwt_manager.dart", "│ │ │ ├─ features/", "│ │ │ │ ├─ auth/login_page.dart", "│ │ │ │ ├─ store/store_switcher.dart", "│ │ │ │ ├─ catalog/product_list_page.dart", "│ │ │ │ ├─ cart/cart_provider.dart", "│ │ │ │ ├─ order/order_submit_service.dart", "│ │ │ │ ├─ inventory/inventory_sync_task.dart", "│ │ │ ├─ routes/app_router.dart", "│ │ │ ├─ analytics/otel_exporter_stub.dart", "│ │ ├─ pubspec.yaml", "│ │ ├─ analysis_options.yaml", "│ │ ├─ test/", "│ │ │ ├─ integration/", "│ │ │ │ ├─ login_flow_test.dart", "│ │ │ │ ├─ order_submit_test.dart", "│ │ │ ├─ unit/", "│ │ │ │ ├─ cart_provider_test.dart", "│ ├─ android/ (Flutter 默认)", "│ ├─ ios/ (Flutter 默认)", "├─ services/", "│ ├─ order/", "│ │ ├─ cmd/order-service/main.go", "│ │ ├─ internal/", "│ │ │ ├─ http/router.go", "│ │ │ ├─ http/middleware/jwt.go", "│ │ │ ├─ domain/order.go", "│ │ │ ├─ app/handlers.go", "│ │ │ ├─ repo/order_repo.go", "│ │ │ ├─ pricing/product_repo.go", "│ │ │ ├─ idempotency/store.go", "│ │ │ ├─ events/nats_publisher.go", "│ │ │ ├─ observability/tracing.go", "│ │ ├─ pkg/", "│ │ │ ├─ config/config.go", "│ │ │ ├─ db/gorm_mysql.go", "│ │ │ ├─ cache/redis.go", "│ │ │ ├─ search/meilisearch.go", "│ │ │ ├─ msg/nats.go", "│ │ │ ├─ logger/logger.go", "│ │ ├─ migrations/", "│ │ │ ├─ 0001_init.sql", "│ │ │ ├─ 0002_products.sql", "│ ├─ inventory/", "│ │ ├─ cmd/inventory-service/main.go", "│ │ ├─ internal/... (库存预留/盘点接口)", "│ ├─ payment/", "│ │ ├─ cmd/payment-service/main.go", "│ │ ├─ internal/... (支付下单/回调)", "│ ├─ user/", "│ │ ├─ cmd/user-service/main.go", "│ │ ├─ internal/... (登录/JWT发放/门店绑定)", "├─ gateway/", "│ ├─ cmd/gateway/main.go", "│ ├─ internal/", "│ │ ├─ http/gin_server.go", "│ │ ├─ bff/aggregators.go", "│ │ ├─ middleware/auth.go", "│ │ ├─ observability/tracing.go", "│ ├─ pkg/", "│ │ ├─ config/config.go", "│ │ ├─ rate/limiter.go", "│ │ ├─ cache/redis.go", "├─ infra/", "│ ├─ config/", "│ │ ├─ .env.example", "│ │ ├─ app.yaml", "│ │ ├─ db.yaml", "│ │ ├─ redis.yaml", "│ │ ├─ meilisearch.yaml", "│ │ ├─ nats.yaml", "│ │ ├─ otel-collector.yaml", "│ │ ├─ prometheus.yaml", "│ ├─ deploy/", "│ │ ├─ docker/", "│ │ │ ├─ order.Dockerfile", "│ │ │ ├─ inventory.Dockerfile", "│ │ │ ├─ payment.Dockerfile", "│ │ │ ├─ gateway.Dockerfile", "│ │ │ ├─ mobile.Dockerfile (可选用于Web打包)", "│ │ │ ├─ docker-compose.dev.yml", "│ │ ├─ k8s/", "│ │ │ ├─ namespace.yaml", "│ │ │ ├─ order-deploy.yaml", "│ │ │ ├─ inventory-deploy.yaml", "│ │ │ ├─ payment-deploy.yaml", "│ │ │ ├─ gateway-deploy.yaml", "│ │ │ ├─ mysql-statefulset.yaml", "│ │ │ ├─ redis-deploy.yaml", "│ │ │ ├─ meilisearch-deploy.yaml", "│ │ │ ├─ nats-deploy.yaml", "│ │ │ ├─ otel-collector-deploy.yaml", "│ │ │ ├─ prometheus-deploy.yaml", "│ │ ├─ helm/ (可选)", "│ ├─ db/", "│ │ ├─ seed/", "│ │ │ ├─ products.json", "│ │ ├─ migrations/ (复用 services//migrations)", "│ ├─ scripts/", "│ │ ├─ migrate.sh", "│ │ ├─ seed.sh", "│ │ ├─ dev_up.sh", "│ │ ├─ fmt_lint.sh", "├─ scripts/", "│ ├─ scaffold.sh (生成模块/handler/测试样板)", "│ ├─ makefile", "│ ├─ ci/", "│ │ ├─ github/", "│ │ │ ├─ workflows/ci.yml", "│ │ ├─ gitlab-ci.yml (可选)", "├─ pkg/ (后端共享库)", "│ ├─ auth/", "│ │ ├─ jwt.go", "│ ├─ observability/", "│ │ ├─ otel.go", "│ │ ├─ metrics.go", "│ ├─ http/", "│ │ ├─ response.go", "│ ├─ idempotency/", "│ │ ├─ middleware.go", "├─ .golangci.yml", "├─ go.work (多模块管理)", "├─ README.md" ] }