重置项目
This commit is contained in:
@@ -1,15 +0,0 @@
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# 数据库配置
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DB_USER=stock
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DB_PASSWORD=stock
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DB_NAME=stock
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# JWT 密钥（生产环境请务必修改）
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JWT_SECRET=change-me-in-production
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JWT_EXPIRATION_HOURS=168
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# 日志级别
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RUST_LOG=info
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# 端口
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BACKEND_PORT=3019
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FRONTEND_PORT=3018
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@@ -1,108 +1 @@
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# 用户体系
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基于 **Go + PostgreSQL + Docker Compose** 的用户权限管理模块，角色覆盖：系统管理员、管理员、用户。
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## 技术栈
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| 层 | 技术 |
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|---|---|
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| 后端 | Go 1.25 + Gin + GORM + JWT + bcrypt |
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| 数据库 | PostgreSQL 18 |
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| 前端 | React 18 + Vite + Tailwind CSS |
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| 部署 | Docker Compose |
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## 快速启动
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```bash
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# 1. 复制环境变量
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cp .env.example .env
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# 2. 启动服务（首次会编译 Go 后端，可能需要几分钟）
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docker compose up -d
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# 3. 等待数据库健康检查通过后，访问前端
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open http://localhost:3018
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```
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## 默认端口
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| 服务 | 端口 |
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|---|---|
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| 前端 | 3018 |
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| 后端 API | 3019 |
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| PostgreSQL | 5432 |
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## 默认系统管理员
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系统启动时会自动创建一个系统管理员账号（仅当不存在时）：
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| 用户名 | 密码 |
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|---|---|
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| `system_admin` | `system_admin` |
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整个系统只能有一个系统管理员账号，无法通过管理后台再创建或提升其他系统管理员。
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## 角色说明
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| 角色 | 权限 |
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|---|---|
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| 系统管理员 | 管理管理员、用户、系统配置 |
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| 管理员 | 管理普通用户 |
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| 用户 | 访问业务功能、修改个人资料 |
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## 主要 API
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| 方法 | 路径 | 说明 | 权限 |
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|---|---|---|---|
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| POST | /api/auth/login | 登录 | 公开 |
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| GET | /api/auth/me | 当前用户 | 需登录 |
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| POST | /api/auth/logout | 登出 | 需登录 |
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| GET | /api/admin/users | 用户列表 | admin / system_admin |
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| POST | /api/admin/users | 创建用户 | admin / system_admin |
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| PUT | /api/admin/users/:id | 更新用户/角色 | admin / system_admin |
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| DELETE | /api/admin/users/:id | 删除用户 | system_admin |
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| GET | /api/admin/roles | 角色列表 | admin / system_admin |
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| POST | /api/admin/data-sync/init-stocks | 初始化全部上市股票 | admin / system_admin |
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| POST | /api/admin/data-sync/stocks/:exchange | 按交易所同步股票（SSE/SZSE/BSE） | admin / system_admin |
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## 目录结构
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```
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stock/
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├── backend/ # Go 后端
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│ ├── cmd/api/main.go
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│ ├── internal/
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│ │ ├── config/
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│ │ ├── db/
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│ │ ├── handlers/
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│ │ ├── middleware/
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│ │ ├── models/
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│ │ └── routes/
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│ ├── go.mod
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│ └── Dockerfile
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├── frontend/ # React 前端
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│ ├── src/
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│ ├── package.json
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│ └── Dockerfile
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├── docker-compose.yml
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├── .env.example
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└── README.md
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```
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## 开发
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```bash
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# 后端本地运行（需先启动 PostgreSQL）
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cd backend
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go run ./cmd/api
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# 前端本地运行
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cd frontend
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npm install
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npm run dev
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```
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## 注意事项
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- 生产环境请务必修改 `JWT_SECRET`。
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- 首次启动时 GORM 会自动创建表并插入默认角色。
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# README
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@@ -1,29 +0,0 @@
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# 多阶段构建：先编译 Go 后端，再使用最小运行时镜像
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ARG GO_IMAGE=golang:1.25.8-alpine3.23
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FROM ${GO_IMAGE} AS builder
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WORKDIR /app
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RUN apk add --no-cache git
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COPY go.mod go.sum ./
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RUN go env -w GOPROXY=https://goproxy.cn,direct && go mod download
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COPY . ./
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RUN CGO_ENABLED=0 GOOS=linux go build -ldflags="-s -w" -o /app/stock-user-system ./cmd/api
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FROM alpine:3.23
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RUN apk add --no-cache ca-certificates tzdata
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ENV TZ=Asia/Shanghai
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WORKDIR /app
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COPY --from=builder /app/stock-user-system /app/stock-user-system
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ENV DATABASE_URL=""
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ENV JWT_SECRET=""
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ENV JWT_EXPIRATION_HOURS="168"
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ENV PORT="3019"
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ENV GIN_MODE="release"
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EXPOSE 3019
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CMD ["/app/stock-user-system"]
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@@ -1,50 +0,0 @@
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package main
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import (
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"fmt"
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"log"
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"os"
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"stock-user-system/internal/config"
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"stock-user-system/internal/db"
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"stock-user-system/internal/models"
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"stock-user-system/internal/routes"
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)
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func main() {
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cfg, err := config.Load()
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if err != nil {
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log.Fatalf("load config: %v", err)
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}
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database, err := db.Init(cfg.DatabaseURL)
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if err != nil {
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log.Fatalf("init database: %v", err)
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}
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if err := models.AutoMigrate(database); err != nil {
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log.Fatalf("migrate database: %v", err)
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}
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if err := models.AutoMigrateStocks(database); err != nil {
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log.Fatalf("migrate stocks table: %v", err)
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}
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if err := models.SeedRoles(database); err != nil {
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log.Fatalf("seed roles: %v", err)
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}
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if err := models.SeedSystemAdmin(database); err != nil {
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log.Fatalf("seed system admin: %v", err)
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}
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r := routes.Setup(cfg, database)
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addr := fmt.Sprintf("0.0.0.0:%s", cfg.Port)
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log.Printf("backend listening on %s", addr)
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if err := r.Run(addr); err != nil {
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log.Fatalf("server error: %v", err)
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os.Exit(1)
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}
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}
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@@ -1,49 +0,0 @@
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module stock-user-system
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go 1.25
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require (
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github.com/gin-gonic/gin v1.10.0
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github.com/golang-jwt/jwt/v5 v5.2.1
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github.com/joho/godotenv v1.5.1
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golang.org/x/crypto v0.31.0
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gorm.io/driver/postgres v1.5.11
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gorm.io/gorm v1.25.12
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)
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require (
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github.com/bytedance/sonic v1.11.6 // indirect
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github.com/bytedance/sonic/loader v0.1.1 // indirect
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github.com/cloudwego/base64x v0.1.4 // indirect
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github.com/cloudwego/iasm v0.2.0 // indirect
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github.com/gabriel-vasile/mimetype v1.4.3 // indirect
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github.com/gin-contrib/sse v0.1.0 // indirect
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github.com/go-playground/locales v0.14.1 // indirect
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github.com/go-playground/universal-translator v0.18.1 // indirect
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github.com/go-playground/validator/v10 v10.20.0 // indirect
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github.com/goccy/go-json v0.10.2 // indirect
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github.com/jackc/pgpassfile v1.0.0 // indirect
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github.com/jackc/pgservicefile v0.0.0-20221227161230-091c0ba34f0a // indirect
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github.com/jackc/pgx/v5 v5.5.5 // indirect
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github.com/jackc/puddle/v2 v2.2.1 // indirect
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github.com/jinzhu/inflection v1.0.0 // indirect
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github.com/jinzhu/now v1.1.5 // indirect
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github.com/json-iterator/go v1.1.12 // indirect
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github.com/klauspost/cpuid/v2 v2.2.7 // indirect
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github.com/kr/text v0.2.0 // indirect
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github.com/leodido/go-urn v1.4.0 // indirect
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github.com/mattn/go-isatty v0.0.20 // indirect
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github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd // indirect
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github.com/modern-go/reflect2 v1.0.2 // indirect
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github.com/pelletier/go-toml/v2 v2.2.2 // indirect
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github.com/rogpeppe/go-internal v1.15.0 // indirect
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github.com/twitchyliquid64/golang-asm v0.15.1 // indirect
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github.com/ugorji/go/codec v1.2.12 // indirect
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golang.org/x/arch v0.8.0 // indirect
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golang.org/x/net v0.25.0 // indirect
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golang.org/x/sync v0.10.0 // indirect
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golang.org/x/sys v0.28.0 // indirect
|
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golang.org/x/text v0.21.0 // indirect
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google.golang.org/protobuf v1.34.1 // indirect
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gopkg.in/yaml.v3 v3.0.1 // indirect
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)
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-119
@@ -1,119 +0,0 @@
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github.com/bytedance/sonic v1.11.6 h1:oUp34TzMlL+OY1OUWxHqsdkgC/Zfc85zGqw9siXjrc0=
|
||||
github.com/bytedance/sonic v1.11.6/go.mod h1:LysEHSvpvDySVdC2f87zGWf6CIKJcAvqab1ZaiQtds4=
|
||||
github.com/bytedance/sonic/loader v0.1.1 h1:c+e5Pt1k/cy5wMveRDyk2X4B9hF4g7an8N3zCYjJFNM=
|
||||
github.com/bytedance/sonic/loader v0.1.1/go.mod h1:ncP89zfokxS5LZrJxl5z0UJcsk4M4yY2JpfqGeCtNLU=
|
||||
github.com/cloudwego/base64x v0.1.4 h1:jwCgWpFanWmN8xoIUHa2rtzmkd5J2plF/dnLS6Xd/0Y=
|
||||
github.com/cloudwego/base64x v0.1.4/go.mod h1:0zlkT4Wn5C6NdauXdJRhSKRlJvmclQ1hhJgA0rcu/8w=
|
||||
github.com/cloudwego/iasm v0.2.0 h1:1KNIy1I1H9hNNFEEH3DVnI4UujN+1zjpuk6gwHLTssg=
|
||||
github.com/cloudwego/iasm v0.2.0/go.mod h1:8rXZaNYT2n95jn+zTI1sDr+IgcD2GVs0nlbbQPiEFhY=
|
||||
github.com/creack/pty v1.1.9/go.mod h1:oKZEueFk5CKHvIhNR5MUki03XCEU+Q6VDXinZuGJ33E=
|
||||
github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
|
||||
github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
|
||||
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
|
||||
github.com/gabriel-vasile/mimetype v1.4.3 h1:in2uUcidCuFcDKtdcBxlR0rJ1+fsokWf+uqxgUFjbI0=
|
||||
github.com/gabriel-vasile/mimetype v1.4.3/go.mod h1:d8uq/6HKRL6CGdk+aubisF/M5GcPfT7nKyLpA0lbSSk=
|
||||
github.com/gin-contrib/sse v0.1.0 h1:Y/yl/+YNO8GZSjAhjMsSuLt29uWRFHdHYUb5lYOV9qE=
|
||||
github.com/gin-contrib/sse v0.1.0/go.mod h1:RHrZQHXnP2xjPF+u1gW/2HnVO7nvIa9PG3Gm+fLHvGI=
|
||||
github.com/gin-gonic/gin v1.10.0 h1:nTuyha1TYqgedzytsKYqna+DfLos46nTv2ygFy86HFU=
|
||||
github.com/gin-gonic/gin v1.10.0/go.mod h1:4PMNQiOhvDRa013RKVbsiNwoyezlm2rm0uX/T7kzp5Y=
|
||||
github.com/go-playground/assert/v2 v2.2.0 h1:JvknZsQTYeFEAhQwI4qEt9cyV5ONwRHC+lYKSsYSR8s=
|
||||
github.com/go-playground/assert/v2 v2.2.0/go.mod h1:VDjEfimB/XKnb+ZQfWdccd7VUvScMdVu0Titje2rxJ4=
|
||||
github.com/go-playground/locales v0.14.1 h1:EWaQ/wswjilfKLTECiXz7Rh+3BjFhfDFKv/oXslEjJA=
|
||||
github.com/go-playground/locales v0.14.1/go.mod h1:hxrqLVvrK65+Rwrd5Fc6F2O76J/NuW9t0sjnWqG1slY=
|
||||
github.com/go-playground/universal-translator v0.18.1 h1:Bcnm0ZwsGyWbCzImXv+pAJnYK9S473LQFuzCbDbfSFY=
|
||||
github.com/go-playground/universal-translator v0.18.1/go.mod h1:xekY+UJKNuX9WP91TpwSH2VMlDf28Uj24BCp08ZFTUY=
|
||||
github.com/go-playground/validator/v10 v10.20.0 h1:K9ISHbSaI0lyB2eWMPJo+kOS/FBExVwjEviJTixqxL8=
|
||||
github.com/go-playground/validator/v10 v10.20.0/go.mod h1:dbuPbCMFw/DrkbEynArYaCwl3amGuJotoKCe95atGMM=
|
||||
github.com/goccy/go-json v0.10.2 h1:CrxCmQqYDkv1z7lO7Wbh2HN93uovUHgrECaO5ZrCXAU=
|
||||
github.com/goccy/go-json v0.10.2/go.mod h1:6MelG93GURQebXPDq3khkgXZkazVtN9CRI+MGFi0w8I=
|
||||
github.com/golang-jwt/jwt/v5 v5.2.1 h1:OuVbFODueb089Lh128TAcimifWaLhJwVflnrgM17wHk=
|
||||
github.com/golang-jwt/jwt/v5 v5.2.1/go.mod h1:pqrtFR0X4osieyHYxtmOUWsAWrfe1Q5UVIyoH402zdk=
|
||||
github.com/google/go-cmp v0.5.5 h1:Khx7svrCpmxxtHBq5j2mp/xVjsi8hQMfNLvJFAlrGgU=
|
||||
github.com/google/go-cmp v0.5.5/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/gNBxE=
|
||||
github.com/google/gofuzz v1.0.0/go.mod h1:dBl0BpW6vV/+mYPU4Po3pmUjxk6FQPldtuIdl/M65Eg=
|
||||
github.com/jackc/pgpassfile v1.0.0 h1:/6Hmqy13Ss2zCq62VdNG8tM1wchn8zjSGOBJ6icpsIM=
|
||||
github.com/jackc/pgpassfile v1.0.0/go.mod h1:CEx0iS5ambNFdcRtxPj5JhEz+xB6uRky5eyVu/W2HEg=
|
||||
github.com/jackc/pgservicefile v0.0.0-20221227161230-091c0ba34f0a h1:bbPeKD0xmW/Y25WS6cokEszi5g+S0QxI/d45PkRi7Nk=
|
||||
github.com/jackc/pgservicefile v0.0.0-20221227161230-091c0ba34f0a/go.mod h1:5TJZWKEWniPve33vlWYSoGYefn3gLQRzjfDlhSJ9ZKM=
|
||||
github.com/jackc/pgx/v5 v5.5.5 h1:amBjrZVmksIdNjxGW/IiIMzxMKZFelXbUoPNb+8sjQw=
|
||||
github.com/jackc/pgx/v5 v5.5.5/go.mod h1:ez9gk+OAat140fv9ErkZDYFWmXLfV+++K0uAOiwgm1A=
|
||||
github.com/jackc/puddle/v2 v2.2.1 h1:RhxXJtFG022u4ibrCSMSiu5aOq1i77R3OHKNJj77OAk=
|
||||
github.com/jackc/puddle/v2 v2.2.1/go.mod h1:vriiEXHvEE654aYKXXjOvZM39qJ0q+azkZFrfEOc3H4=
|
||||
github.com/jinzhu/inflection v1.0.0 h1:K317FqzuhWc8YvSVlFMCCUb36O/S9MCKRDI7QkRKD/E=
|
||||
github.com/jinzhu/inflection v1.0.0/go.mod h1:h+uFLlag+Qp1Va5pdKtLDYj+kHp5pxUVkryuEj+Srlc=
|
||||
github.com/jinzhu/now v1.1.5 h1:/o9tlHleP7gOFmsnYNz3RGnqzefHA47wQpKrrdTIwXQ=
|
||||
github.com/jinzhu/now v1.1.5/go.mod h1:d3SSVoowX0Lcu0IBviAWJpolVfI5UJVZZ7cO71lE/z8=
|
||||
github.com/joho/godotenv v1.5.1 h1:7eLL/+HRGLY0ldzfGMeQkb7vMd0as4CfYvUVzLqw0N0=
|
||||
github.com/joho/godotenv v1.5.1/go.mod h1:f4LDr5Voq0i2e/R5DDNOoa2zzDfwtkZa6DnEwAbqwq4=
|
||||
github.com/json-iterator/go v1.1.12 h1:PV8peI4a0ysnczrg+LtxykD8LfKY9ML6u2jnxaEnrnM=
|
||||
github.com/json-iterator/go v1.1.12/go.mod h1:e30LSqwooZae/UwlEbR2852Gd8hjQvJoHmT4TnhNGBo=
|
||||
github.com/klauspost/cpuid/v2 v2.0.9/go.mod h1:FInQzS24/EEf25PyTYn52gqo7WaD8xa0213Md/qVLRg=
|
||||
github.com/klauspost/cpuid/v2 v2.2.7 h1:ZWSB3igEs+d0qvnxR/ZBzXVmxkgt8DdzP6m9pfuVLDM=
|
||||
github.com/klauspost/cpuid/v2 v2.2.7/go.mod h1:Lcz8mBdAVJIBVzewtcLocK12l3Y+JytZYpaMropDUws=
|
||||
github.com/knz/go-libedit v1.10.1/go.mod h1:MZTVkCWyz0oBc7JOWP3wNAzd002ZbM/5hgShxwh4x8M=
|
||||
github.com/kr/pretty v0.3.0 h1:WgNl7dwNpEZ6jJ9k1snq4pZsg7DOEN8hP9Xw0Tsjwk0=
|
||||
github.com/kr/pretty v0.3.0/go.mod h1:640gp4NfQd8pI5XOwp5fnNeVWj67G7CFk/SaSQn7NBk=
|
||||
github.com/kr/text v0.2.0 h1:5Nx0Ya0ZqY2ygV366QzturHI13Jq95ApcVaJBhpS+AY=
|
||||
github.com/kr/text v0.2.0/go.mod h1:eLer722TekiGuMkidMxC/pM04lWEeraHUUmBw8l2grE=
|
||||
github.com/leodido/go-urn v1.4.0 h1:WT9HwE9SGECu3lg4d/dIA+jxlljEa1/ffXKmRjqdmIQ=
|
||||
github.com/leodido/go-urn v1.4.0/go.mod h1:bvxc+MVxLKB4z00jd1z+Dvzr47oO32F/QSNjSBOlFxI=
|
||||
github.com/mattn/go-isatty v0.0.20 h1:xfD0iDuEKnDkl03q4limB+vH+GxLEtL/jb4xVJSWWEY=
|
||||
github.com/mattn/go-isatty v0.0.20/go.mod h1:W+V8PltTTMOvKvAeJH7IuucS94S2C6jfK/D7dTCTo3Y=
|
||||
github.com/modern-go/concurrent v0.0.0-20180228061459-e0a39a4cb421/go.mod h1:6dJC0mAP4ikYIbvyc7fijjWJddQyLn8Ig3JB5CqoB9Q=
|
||||
github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd h1:TRLaZ9cD/w8PVh93nsPXa1VrQ6jlwL5oN8l14QlcNfg=
|
||||
github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd/go.mod h1:6dJC0mAP4ikYIbvyc7fijjWJddQyLn8Ig3JB5CqoB9Q=
|
||||
github.com/modern-go/reflect2 v1.0.2 h1:xBagoLtFs94CBntxluKeaWgTMpvLxC4ur3nMaC9Gz0M=
|
||||
github.com/modern-go/reflect2 v1.0.2/go.mod h1:yWuevngMOJpCy52FWWMvUC8ws7m/LJsjYzDa0/r8luk=
|
||||
github.com/pelletier/go-toml/v2 v2.2.2 h1:aYUidT7k73Pcl9nb2gScu7NSrKCSHIDE89b3+6Wq+LM=
|
||||
github.com/pelletier/go-toml/v2 v2.2.2/go.mod h1:1t835xjRzz80PqgE6HHgN2JOsmgYu/h4qDAS4n929Rs=
|
||||
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
|
||||
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
|
||||
github.com/rogpeppe/go-internal v1.15.0 h1:D0RCU5rMAp+SpgkiNdrjfJ+LX4J1M32V2NeCY7EJ6hc=
|
||||
github.com/rogpeppe/go-internal v1.15.0/go.mod h1:DrUVZyrJU+txYW5/1kwtXQSMFio52ZOxX7yM1VHvnxs=
|
||||
github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
|
||||
github.com/stretchr/objx v0.4.0/go.mod h1:YvHI0jy2hoMjB+UWwv71VJQ9isScKT/TqJzVSSt89Yw=
|
||||
github.com/stretchr/objx v0.5.0/go.mod h1:Yh+to48EsGEfYuaHDzXPcE3xhTkx73EhmCGUpEOglKo=
|
||||
github.com/stretchr/objx v0.5.2/go.mod h1:FRsXN1f5AsAjCGJKqEizvkpNtU+EGNCLh3NxZ/8L+MA=
|
||||
github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
|
||||
github.com/stretchr/testify v1.7.0/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
|
||||
github.com/stretchr/testify v1.7.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
|
||||
github.com/stretchr/testify v1.8.0/go.mod h1:yNjHg4UonilssWZ8iaSj1OCr/vHnekPRkoO+kdMU+MU=
|
||||
github.com/stretchr/testify v1.8.1/go.mod h1:w2LPCIKwWwSfY2zedu0+kehJoqGctiVI29o6fzry7u4=
|
||||
github.com/stretchr/testify v1.8.4/go.mod h1:sz/lmYIOXD/1dqDmKjjqLyZ2RngseejIcXlSw2iwfAo=
|
||||
github.com/stretchr/testify v1.9.0 h1:HtqpIVDClZ4nwg75+f6Lvsy/wHu+3BoSGCbBAcpTsTg=
|
||||
github.com/stretchr/testify v1.9.0/go.mod h1:r2ic/lqez/lEtzL7wO/rwa5dbSLXVDPFyf8C91i36aY=
|
||||
github.com/twitchyliquid64/golang-asm v0.15.1 h1:SU5vSMR7hnwNxj24w34ZyCi/FmDZTkS4MhqMhdFk5YI=
|
||||
github.com/twitchyliquid64/golang-asm v0.15.1/go.mod h1:a1lVb/DtPvCB8fslRZhAngC2+aY1QWCk3Cedj/Gdt08=
|
||||
github.com/ugorji/go/codec v1.2.12 h1:9LC83zGrHhuUA9l16C9AHXAqEV/2wBQ4nkvumAE65EE=
|
||||
github.com/ugorji/go/codec v1.2.12/go.mod h1:UNopzCgEMSXjBc6AOMqYvWC1ktqTAfzJZUZgYf6w6lg=
|
||||
golang.org/x/arch v0.0.0-20210923205945-b76863e36670/go.mod h1:5om86z9Hs0C8fWVUuoMHwpExlXzs5Tkyp9hOrfG7pp8=
|
||||
golang.org/x/arch v0.8.0 h1:3wRIsP3pM4yUptoR96otTUOXI367OS0+c9eeRi9doIc=
|
||||
golang.org/x/arch v0.8.0/go.mod h1:FEVrYAQjsQXMVJ1nsMoVVXPZg6p2JE2mx8psSWTDQys=
|
||||
golang.org/x/crypto v0.31.0 h1:ihbySMvVjLAeSH1IbfcRTkD/iNscyz8rGzjF/E5hV6U=
|
||||
golang.org/x/crypto v0.31.0/go.mod h1:kDsLvtWBEx7MV9tJOj9bnXsPbxwJQ6csT/x4KIN4Ssk=
|
||||
golang.org/x/net v0.25.0 h1:d/OCCoBEUq33pjydKrGQhw7IlUPI2Oylr+8qLx49kac=
|
||||
golang.org/x/net v0.25.0/go.mod h1:JkAGAh7GEvH74S6FOH42FLoXpXbE/aqXSrIQjXgsiwM=
|
||||
golang.org/x/sync v0.10.0 h1:3NQrjDixjgGwUOCaF8w2+VYHv0Ve/vGYSbdkTa98gmQ=
|
||||
golang.org/x/sync v0.10.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
|
||||
golang.org/x/sys v0.5.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
|
||||
golang.org/x/sys v0.6.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
|
||||
golang.org/x/sys v0.28.0 h1:Fksou7UEQUWlKvIdsqzJmUmCX3cZuD2+P3XyyzwMhlA=
|
||||
golang.org/x/sys v0.28.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
|
||||
golang.org/x/text v0.21.0 h1:zyQAAkrwaneQ066sspRyJaG9VNi/YJ1NfzcGB3hZ/qo=
|
||||
golang.org/x/text v0.21.0/go.mod h1:4IBbMaMmOPCJ8SecivzSH54+73PCFmPWxNTLm+vZkEQ=
|
||||
golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543 h1:E7g+9GITq07hpfrRu66IVDexMakfv52eLZ2CXBWiKr4=
|
||||
golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
|
||||
google.golang.org/protobuf v1.34.1 h1:9ddQBjfCyZPOHPUiPxpYESBLc+T8P3E+Vo4IbKZgFWg=
|
||||
google.golang.org/protobuf v1.34.1/go.mod h1:c6P6GXX6sHbq/GpV6MGZEdwhWPcYBgnhAHhKbcUYpos=
|
||||
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
|
||||
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c h1:Hei/4ADfdWqJk1ZMxUNpqntNwaWcugrBjAiHlqqRiVk=
|
||||
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c/go.mod h1:JHkPIbrfpd72SG/EVd6muEfDQjcINNoR0C8j2r3qZ4Q=
|
||||
gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
|
||||
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
|
||||
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
|
||||
gorm.io/driver/postgres v1.5.11 h1:ubBVAfbKEUld/twyKZ0IYn9rSQh448EdelLYk9Mv314=
|
||||
gorm.io/driver/postgres v1.5.11/go.mod h1:DX3GReXH+3FPWGrrgffdvCk3DQ1dwDPdmbenSkweRGI=
|
||||
gorm.io/gorm v1.25.12 h1:I0u8i2hWQItBq1WfE0o2+WuL9+8L21K9e2HHSTE/0f8=
|
||||
gorm.io/gorm v1.25.12/go.mod h1:xh7N7RHfYlNc5EmcI/El95gXusucDrQnHXe0+CgWcLQ=
|
||||
nullprogram.com/x/optparse v1.0.0/go.mod h1:KdyPE+Igbe0jQUrVfMqDMeJQIJZEuyV7pjYmp6pbG50=
|
||||
rsc.io/pdf v0.1.1/go.mod h1:n8OzWcQ6Sp37PL01nO98y4iUCRdTGarVfzxY20ICaU4=
|
||||
@@ -1,64 +0,0 @@
|
||||
package config
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"os"
|
||||
"strconv"
|
||||
"strings"
|
||||
"time"
|
||||
|
||||
"github.com/joho/godotenv"
|
||||
)
|
||||
|
||||
type Config struct {
|
||||
DatabaseURL string
|
||||
JWTSecret string
|
||||
JWTExpirationHours int
|
||||
Port string
|
||||
AllowedOrigins []string
|
||||
}
|
||||
|
||||
func Load() (*Config, error) {
|
||||
_ = godotenv.Load()
|
||||
|
||||
databaseURL := os.Getenv("DATABASE_URL")
|
||||
if databaseURL == "" {
|
||||
return nil, fmt.Errorf("DATABASE_URL must be set")
|
||||
}
|
||||
|
||||
jwtSecret := os.Getenv("JWT_SECRET")
|
||||
if jwtSecret == "" {
|
||||
jwtSecret = "change-me-in-production"
|
||||
fmt.Fprintln(os.Stderr, "WARNING: JWT_SECRET not set, using default secret")
|
||||
}
|
||||
|
||||
expHours, _ := strconv.Atoi(os.Getenv("JWT_EXPIRATION_HOURS"))
|
||||
if expHours == 0 {
|
||||
expHours = 168 // 7 days
|
||||
}
|
||||
|
||||
port := os.Getenv("PORT")
|
||||
if port == "" {
|
||||
port = "3019"
|
||||
}
|
||||
|
||||
allowedOrigins := []string{"*"}
|
||||
if v := os.Getenv("ALLOWED_ORIGINS"); v != "" {
|
||||
allowedOrigins = strings.Split(v, ",")
|
||||
for i := range allowedOrigins {
|
||||
allowedOrigins[i] = strings.TrimSpace(allowedOrigins[i])
|
||||
}
|
||||
}
|
||||
|
||||
return &Config{
|
||||
DatabaseURL: databaseURL,
|
||||
JWTSecret: jwtSecret,
|
||||
JWTExpirationHours: expHours,
|
||||
Port: port,
|
||||
AllowedOrigins: allowedOrigins,
|
||||
}, nil
|
||||
}
|
||||
|
||||
func (c *Config) JWTExpiration() time.Duration {
|
||||
return time.Duration(c.JWTExpirationHours) * time.Hour
|
||||
}
|
||||
@@ -1,233 +0,0 @@
|
||||
package datasource
|
||||
|
||||
import (
|
||||
"bytes"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"strconv"
|
||||
"time"
|
||||
)
|
||||
|
||||
const (
|
||||
tushareBaseURL = "http://api.tushare.pro"
|
||||
tushareToken = "76efd8465f9f2591aa42a385268e06acf6b80b7a15be2267ad2281b7"
|
||||
defaultTimeout = 60 * time.Second
|
||||
maxRetries = 3
|
||||
retryBaseDelay = 1 * time.Second
|
||||
)
|
||||
|
||||
// StockBasic 表示股票基础信息。
|
||||
type StockBasic struct {
|
||||
TsCode string
|
||||
Symbol string
|
||||
Name string
|
||||
Area string
|
||||
Industry string
|
||||
Fullname string
|
||||
Enname string
|
||||
Cnspell string
|
||||
Market string
|
||||
Exchange string
|
||||
CurrType string
|
||||
ListStatus string
|
||||
ListDate string
|
||||
DelistDate string
|
||||
IsHs string
|
||||
ActName string
|
||||
ActEntType string
|
||||
}
|
||||
|
||||
const stockBasicFields = "ts_code,symbol,name,area,industry,fullname,enname,cnspell,market,exchange,curr_type,list_status,list_date,delist_date,is_hs,act_name,act_ent_type"
|
||||
|
||||
// Client 封装 Tushare Pro HTTP API 调用。
|
||||
type Client struct {
|
||||
token string
|
||||
baseURL string
|
||||
client *http.Client
|
||||
}
|
||||
|
||||
// NewClient 创建 Tushare 客户端。
|
||||
func NewClient() *Client {
|
||||
return &Client{
|
||||
token: tushareToken,
|
||||
baseURL: tushareBaseURL,
|
||||
client: &http.Client{Timeout: defaultTimeout},
|
||||
}
|
||||
}
|
||||
|
||||
func parseStockBasic(row []any, col map[string]int) StockBasic {
|
||||
return StockBasic{
|
||||
TsCode: stringAt(row, col["ts_code"]),
|
||||
Symbol: stringAt(row, col["symbol"]),
|
||||
Name: stringAt(row, col["name"]),
|
||||
Area: stringAt(row, col["area"]),
|
||||
Industry: stringAt(row, col["industry"]),
|
||||
Fullname: stringAt(row, col["fullname"]),
|
||||
Enname: stringAt(row, col["enname"]),
|
||||
Cnspell: stringAt(row, col["cnspell"]),
|
||||
Market: stringAt(row, col["market"]),
|
||||
Exchange: stringAt(row, col["exchange"]),
|
||||
CurrType: stringAt(row, col["curr_type"]),
|
||||
ListStatus: stringAt(row, col["list_status"]),
|
||||
ListDate: stringAt(row, col["list_date"]),
|
||||
DelistDate: stringAt(row, col["delist_date"]),
|
||||
IsHs: stringAt(row, col["is_hs"]),
|
||||
ActName: stringAt(row, col["act_name"]),
|
||||
ActEntType: stringAt(row, col["act_ent_type"]),
|
||||
}
|
||||
}
|
||||
|
||||
// ListStocks 通过 stock_basic 接口获取全部上市股票基础信息。
|
||||
func (c *Client) ListStocks() ([]StockBasic, error) {
|
||||
params := map[string]any{
|
||||
"list_status": "L",
|
||||
"fields": stockBasicFields,
|
||||
}
|
||||
return c.listStockBasic(params)
|
||||
}
|
||||
|
||||
// ListStocksByExchange 按交易所获取股票基础信息。
|
||||
func (c *Client) ListStocksByExchange(exchange string) ([]StockBasic, error) {
|
||||
params := map[string]any{
|
||||
"exchange": exchange,
|
||||
"fields": stockBasicFields,
|
||||
}
|
||||
return c.listStockBasic(params)
|
||||
}
|
||||
|
||||
func (c *Client) listStockBasic(params map[string]any) ([]StockBasic, error) {
|
||||
fields, items, err := c.call("stock_basic", params)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("stock_basic: %w", err)
|
||||
}
|
||||
|
||||
col := buildColumnMap(fields)
|
||||
stocks := make([]StockBasic, 0, len(items))
|
||||
for _, row := range items {
|
||||
code := stringAt(row, col["ts_code"])
|
||||
if code == "" {
|
||||
continue
|
||||
}
|
||||
stocks = append(stocks, parseStockBasic(row, col))
|
||||
}
|
||||
return stocks, nil
|
||||
}
|
||||
|
||||
// call 调用 Tushare Pro API，返回字段名与数据行。
|
||||
func (c *Client) call(apiName string, params map[string]any) ([]string, [][]any, error) {
|
||||
reqBody := map[string]any{
|
||||
"api_name": apiName,
|
||||
"token": c.token,
|
||||
"params": params,
|
||||
"fields": "",
|
||||
}
|
||||
data, err := json.Marshal(reqBody)
|
||||
if err != nil {
|
||||
return nil, nil, err
|
||||
}
|
||||
|
||||
var lastErr error
|
||||
for attempt := 0; attempt <= maxRetries; attempt++ {
|
||||
if attempt > 0 {
|
||||
time.Sleep(retryBaseDelay * time.Duration(1<<(attempt-1)))
|
||||
}
|
||||
|
||||
req, err := http.NewRequest("POST", c.baseURL, bytes.NewReader(data))
|
||||
if err != nil {
|
||||
return nil, nil, err
|
||||
}
|
||||
req.Header.Set("Content-Type", "application/json")
|
||||
req.Header.Set("Accept", "application/json")
|
||||
|
||||
resp, err := c.client.Do(req)
|
||||
if err != nil {
|
||||
lastErr = err
|
||||
continue
|
||||
}
|
||||
|
||||
respBody, err := io.ReadAll(resp.Body)
|
||||
resp.Body.Close()
|
||||
if err != nil {
|
||||
lastErr = err
|
||||
continue
|
||||
}
|
||||
|
||||
if resp.StatusCode >= 500 || resp.StatusCode == 429 {
|
||||
lastErr = fmt.Errorf("tushare %s returned %d: %s", apiName, resp.StatusCode, string(respBody))
|
||||
continue
|
||||
}
|
||||
if resp.StatusCode >= 400 {
|
||||
return nil, nil, fmt.Errorf("tushare %s returned %d: %s", apiName, resp.StatusCode, string(respBody))
|
||||
}
|
||||
|
||||
var wrapper struct {
|
||||
Code int `json:"code"`
|
||||
Msg string `json:"msg"`
|
||||
Data *struct {
|
||||
Fields []string `json:"fields"`
|
||||
Items [][]any `json:"items"`
|
||||
} `json:"data"`
|
||||
}
|
||||
if err := json.Unmarshal(respBody, &wrapper); err != nil {
|
||||
return nil, nil, fmt.Errorf("decode tushare response: %w", err)
|
||||
}
|
||||
if wrapper.Code != 0 {
|
||||
return nil, nil, fmt.Errorf("tushare %s error %d: %s", apiName, wrapper.Code, wrapper.Msg)
|
||||
}
|
||||
if wrapper.Data == nil {
|
||||
return nil, nil, nil
|
||||
}
|
||||
return wrapper.Data.Fields, wrapper.Data.Items, nil
|
||||
}
|
||||
|
||||
if lastErr != nil {
|
||||
return nil, nil, fmt.Errorf("tushare %s failed after %d retries: %w", apiName, maxRetries, lastErr)
|
||||
}
|
||||
return nil, nil, fmt.Errorf("tushare %s request failed", apiName)
|
||||
}
|
||||
|
||||
func buildColumnMap(fields []string) map[string]int {
|
||||
m := make(map[string]int, len(fields))
|
||||
for i, f := range fields {
|
||||
m[f] = i
|
||||
}
|
||||
return m
|
||||
}
|
||||
|
||||
func stringAt(row []any, idx int) string {
|
||||
if idx < 0 || idx >= len(row) || row[idx] == nil {
|
||||
return ""
|
||||
}
|
||||
switch v := row[idx].(type) {
|
||||
case string:
|
||||
return v
|
||||
case []byte:
|
||||
return string(v)
|
||||
default:
|
||||
return fmt.Sprintf("%v", v)
|
||||
}
|
||||
}
|
||||
|
||||
func floatAt(row []any, idx int) float64 {
|
||||
if idx < 0 || idx >= len(row) || row[idx] == nil {
|
||||
return 0
|
||||
}
|
||||
switch v := row[idx].(type) {
|
||||
case float64:
|
||||
return v
|
||||
case float32:
|
||||
return float64(v)
|
||||
case int:
|
||||
return float64(v)
|
||||
case int64:
|
||||
return float64(v)
|
||||
case string:
|
||||
f, _ := strconv.ParseFloat(v, 64)
|
||||
return f
|
||||
default:
|
||||
f, _ := strconv.ParseFloat(fmt.Sprintf("%v", v), 64)
|
||||
return f
|
||||
}
|
||||
}
|
||||
@@ -1,27 +0,0 @@
|
||||
package db
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"gorm.io/driver/postgres"
|
||||
"gorm.io/gorm"
|
||||
"gorm.io/gorm/logger"
|
||||
)
|
||||
|
||||
func Init(databaseURL string) (*gorm.DB, error) {
|
||||
db, err := gorm.Open(postgres.Open(databaseURL), &gorm.Config{
|
||||
Logger: logger.Default.LogMode(logger.Silent),
|
||||
})
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("open database: %w", err)
|
||||
}
|
||||
|
||||
sqlDB, err := db.DB()
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
sqlDB.SetMaxIdleConns(10)
|
||||
sqlDB.SetMaxOpenConns(100)
|
||||
|
||||
return db, nil
|
||||
}
|
||||
@@ -1,242 +0,0 @@
|
||||
package handlers
|
||||
|
||||
import (
|
||||
"net/http"
|
||||
"strings"
|
||||
|
||||
"stock-user-system/internal/config"
|
||||
"stock-user-system/internal/middleware"
|
||||
"stock-user-system/internal/models"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
"gorm.io/gorm"
|
||||
)
|
||||
|
||||
type AdminHandler struct {
|
||||
DB *gorm.DB
|
||||
CFG *config.Config
|
||||
}
|
||||
|
||||
func allowedRolesForCreation(actor models.RoleName) []models.RoleName {
|
||||
switch actor {
|
||||
case models.RoleSystemAdmin:
|
||||
return []models.RoleName{models.RoleAdmin, models.RoleUser}
|
||||
case models.RoleAdmin:
|
||||
return []models.RoleName{models.RoleUser}
|
||||
default:
|
||||
return nil
|
||||
}
|
||||
}
|
||||
|
||||
func containsRole(roles []models.RoleName, target models.RoleName) bool {
|
||||
for _, r := range roles {
|
||||
if r == target {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func (h *AdminHandler) ListUsers(c *gin.Context) {
|
||||
var users []models.User
|
||||
if err := h.DB.Preload("Role").Order("created_at DESC").Find(&users).Error; err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": "internal server error"})
|
||||
return
|
||||
}
|
||||
|
||||
result := make([]models.PublicUserInfo, 0, len(users))
|
||||
for _, u := range users {
|
||||
result = append(result, u.ToPublicInfo())
|
||||
}
|
||||
c.JSON(http.StatusOK, result)
|
||||
}
|
||||
|
||||
func (h *AdminHandler) CreateUser(c *gin.Context) {
|
||||
current, _ := middleware.GetCurrentUser(c)
|
||||
|
||||
var req struct {
|
||||
Username string `json:"username" binding:"required"`
|
||||
Email *string `json:"email"`
|
||||
Password string `json:"password" binding:"required"`
|
||||
Role string `json:"role"`
|
||||
}
|
||||
if err := c.ShouldBindJSON(&req); err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "请求参数错误"})
|
||||
return
|
||||
}
|
||||
|
||||
targetRole := models.RoleUser
|
||||
if req.Role != "" {
|
||||
parsed, err := models.ParseRoleName(req.Role)
|
||||
if err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "无效的角色"})
|
||||
return
|
||||
}
|
||||
targetRole = parsed
|
||||
}
|
||||
|
||||
if !containsRole(allowedRolesForCreation(current.Role), targetRole) {
|
||||
c.JSON(http.StatusForbidden, gin.H{"success": false, "error": "权限不足"})
|
||||
return
|
||||
}
|
||||
|
||||
if err := validateUsername(req.Username); err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": err.Error()})
|
||||
return
|
||||
}
|
||||
if len(req.Password) < 6 {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "密码长度至少 6 位"})
|
||||
return
|
||||
}
|
||||
|
||||
var role models.Role
|
||||
if err := h.DB.Where("name = ?", targetRole.String()).First(&role).Error; err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "角色不存在"})
|
||||
return
|
||||
}
|
||||
|
||||
hash, err := hashPassword(req.Password)
|
||||
if err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": "internal server error"})
|
||||
return
|
||||
}
|
||||
|
||||
username := strings.ToLower(strings.TrimSpace(req.Username))
|
||||
var email *string
|
||||
if req.Email != nil && *req.Email != "" {
|
||||
e := strings.ToLower(strings.TrimSpace(*req.Email))
|
||||
email = &e
|
||||
}
|
||||
|
||||
user := models.User{
|
||||
Username: username,
|
||||
Email: email,
|
||||
PasswordHash: hash,
|
||||
RoleID: role.ID,
|
||||
Status: "active",
|
||||
}
|
||||
|
||||
if err := h.DB.Create(&user).Error; err != nil {
|
||||
if strings.Contains(err.Error(), "duplicate key") {
|
||||
c.JSON(http.StatusConflict, gin.H{"success": false, "error": "用户名或邮箱已存在"})
|
||||
return
|
||||
}
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": "internal server error"})
|
||||
return
|
||||
}
|
||||
|
||||
h.DB.Preload("Role").First(&user, "id = ?", user.ID)
|
||||
c.JSON(http.StatusOK, user.ToPublicInfo())
|
||||
}
|
||||
|
||||
func (h *AdminHandler) UpdateUser(c *gin.Context) {
|
||||
current, _ := middleware.GetCurrentUser(c)
|
||||
userID := c.Param("id")
|
||||
|
||||
var req struct {
|
||||
Email *string `json:"email"`
|
||||
Role string `json:"role"`
|
||||
Status string `json:"status"`
|
||||
}
|
||||
if err := c.ShouldBindJSON(&req); err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "请求参数错误"})
|
||||
return
|
||||
}
|
||||
|
||||
var target models.User
|
||||
if err := h.DB.Preload("Role").Where("id = ?", userID).First(&target).Error; err != nil {
|
||||
c.JSON(http.StatusNotFound, gin.H{"success": false, "error": "not found"})
|
||||
return
|
||||
}
|
||||
|
||||
if !current.Role.CanManage(target.Role.NameEnum()) && current.ID != userID {
|
||||
c.JSON(http.StatusForbidden, gin.H{"success": false, "error": "权限不足"})
|
||||
return
|
||||
}
|
||||
|
||||
updates := map[string]interface{}{}
|
||||
|
||||
if req.Email != nil && *req.Email != "" {
|
||||
updates["email"] = strings.ToLower(strings.TrimSpace(*req.Email))
|
||||
}
|
||||
|
||||
if req.Status != "" {
|
||||
if target.Role.NameEnum() == models.RoleSystemAdmin && req.Status != "active" {
|
||||
c.JSON(http.StatusForbidden, gin.H{"success": false, "error": "不能禁用系统管理员账号"})
|
||||
return
|
||||
}
|
||||
updates["status"] = req.Status
|
||||
}
|
||||
|
||||
if req.Role != "" {
|
||||
newRole, err := models.ParseRoleName(req.Role)
|
||||
if err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "无效的角色"})
|
||||
return
|
||||
}
|
||||
if target.Role.NameEnum() == models.RoleSystemAdmin && newRole != models.RoleSystemAdmin {
|
||||
c.JSON(http.StatusForbidden, gin.H{"success": false, "error": "不能修改系统管理员账号的角色"})
|
||||
return
|
||||
}
|
||||
if !containsRole(allowedRolesForCreation(current.Role), newRole) || !current.Role.CanManage(newRole) {
|
||||
c.JSON(http.StatusForbidden, gin.H{"success": false, "error": "权限不足"})
|
||||
return
|
||||
}
|
||||
var role models.Role
|
||||
if err := h.DB.Where("name = ?", newRole.String()).First(&role).Error; err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "角色不存在"})
|
||||
return
|
||||
}
|
||||
updates["role_id"] = role.ID
|
||||
}
|
||||
|
||||
if err := h.DB.Model(&target).Updates(updates).Error; err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": "internal server error"})
|
||||
return
|
||||
}
|
||||
|
||||
h.DB.Preload("Role").First(&target, "id = ?", userID)
|
||||
c.JSON(http.StatusOK, target.ToPublicInfo())
|
||||
}
|
||||
|
||||
func (h *AdminHandler) DeleteUser(c *gin.Context) {
|
||||
current, _ := middleware.GetCurrentUser(c)
|
||||
userID := c.Param("id")
|
||||
|
||||
if current.ID == userID {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "不能删除自己"})
|
||||
return
|
||||
}
|
||||
|
||||
var target models.User
|
||||
if err := h.DB.Preload("Role").Where("id = ?", userID).First(&target).Error; err != nil {
|
||||
c.JSON(http.StatusNotFound, gin.H{"success": false, "error": "not found"})
|
||||
return
|
||||
}
|
||||
|
||||
if !current.Role.CanManage(target.Role.NameEnum()) {
|
||||
c.JSON(http.StatusForbidden, gin.H{"success": false, "error": "权限不足"})
|
||||
return
|
||||
}
|
||||
|
||||
if target.Role.NameEnum() == models.RoleSystemAdmin {
|
||||
c.JSON(http.StatusForbidden, gin.H{"success": false, "error": "不能删除系统管理员账号"})
|
||||
return
|
||||
}
|
||||
|
||||
if err := h.DB.Delete(&target).Error; err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": "internal server error"})
|
||||
return
|
||||
}
|
||||
|
||||
c.JSON(http.StatusOK, gin.H{"message": "用户已删除"})
|
||||
}
|
||||
|
||||
func (h *AdminHandler) ListRoles(c *gin.Context) {
|
||||
var roles []models.Role
|
||||
if err := h.DB.Order("id").Find(&roles).Error; err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": "internal server error"})
|
||||
return
|
||||
}
|
||||
c.JSON(http.StatusOK, roles)
|
||||
}
|
||||
@@ -1,97 +0,0 @@
|
||||
package handlers
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"net/http"
|
||||
"strings"
|
||||
|
||||
"stock-user-system/internal/config"
|
||||
"stock-user-system/internal/middleware"
|
||||
"stock-user-system/internal/models"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
"golang.org/x/crypto/bcrypt"
|
||||
"gorm.io/gorm"
|
||||
)
|
||||
|
||||
type AuthHandler struct {
|
||||
DB *gorm.DB
|
||||
CFG *config.Config
|
||||
}
|
||||
|
||||
func (h *AuthHandler) Login(c *gin.Context) {
|
||||
var req struct {
|
||||
Username string `json:"username" binding:"required"`
|
||||
Password string `json:"password" binding:"required"`
|
||||
}
|
||||
if err := c.ShouldBindJSON(&req); err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "请求参数错误"})
|
||||
return
|
||||
}
|
||||
|
||||
username := strings.ToLower(strings.TrimSpace(req.Username))
|
||||
|
||||
var user models.User
|
||||
if err := h.DB.Preload("Role").Where("LOWER(username) = ?", username).First(&user).Error; err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "用户名或密码错误"})
|
||||
return
|
||||
}
|
||||
|
||||
if user.Status != "active" {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "账号已被禁用"})
|
||||
return
|
||||
}
|
||||
|
||||
if err := bcrypt.CompareHashAndPassword([]byte(user.PasswordHash), []byte(req.Password)); err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "用户名或密码错误"})
|
||||
return
|
||||
}
|
||||
|
||||
token, err := middleware.GenerateToken(user.ID, user.Role.NameEnum(), h.CFG)
|
||||
if err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": "internal server error"})
|
||||
return
|
||||
}
|
||||
|
||||
c.JSON(http.StatusOK, gin.H{
|
||||
"token": token,
|
||||
"user": user.ToPublicInfo(),
|
||||
})
|
||||
}
|
||||
|
||||
func (h *AuthHandler) Me(c *gin.Context) {
|
||||
current, ok := middleware.GetCurrentUser(c)
|
||||
if !ok {
|
||||
c.JSON(http.StatusUnauthorized, gin.H{"success": false, "error": "访问令牌无效或已过期"})
|
||||
return
|
||||
}
|
||||
|
||||
var user models.User
|
||||
if err := h.DB.Preload("Role").Where("id = ?", current.ID).First(&user).Error; err != nil {
|
||||
c.JSON(http.StatusNotFound, gin.H{"success": false, "error": "not found"})
|
||||
return
|
||||
}
|
||||
|
||||
c.JSON(http.StatusOK, user.ToPublicInfo())
|
||||
}
|
||||
|
||||
func (h *AuthHandler) Logout(c *gin.Context) {
|
||||
c.JSON(http.StatusOK, gin.H{"message": "登出成功"})
|
||||
}
|
||||
|
||||
func hashPassword(password string) (string, error) {
|
||||
bytes, err := bcrypt.GenerateFromPassword([]byte(password), bcrypt.DefaultCost)
|
||||
return string(bytes), err
|
||||
}
|
||||
|
||||
func validateUsername(username string) error {
|
||||
if len(username) < 3 || len(username) > 32 {
|
||||
return fmt.Errorf("用户名长度需在 3-32 位之间")
|
||||
}
|
||||
for _, r := range username {
|
||||
if !(r >= 'a' && r <= 'z') && !(r >= 'A' && r <= 'Z') && !(r >= '0' && r <= '9') && r != '_' && r != '-' {
|
||||
return fmt.Errorf("用户名只能包含字母、数字、下划线和短横线")
|
||||
}
|
||||
}
|
||||
return nil
|
||||
}
|
||||
@@ -1,137 +0,0 @@
|
||||
package handlers
|
||||
|
||||
import (
|
||||
"net/http"
|
||||
"strings"
|
||||
|
||||
"stock-user-system/internal/datasource"
|
||||
"stock-user-system/internal/models"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
"gorm.io/gorm"
|
||||
"gorm.io/gorm/clause"
|
||||
)
|
||||
|
||||
var validExchanges = map[string]string{
|
||||
"SSE": "上交所",
|
||||
"SZSE": "深交所",
|
||||
"BSE": "北交所",
|
||||
}
|
||||
|
||||
func toModelStock(s datasource.StockBasic) models.Stock {
|
||||
return models.Stock{
|
||||
TsCode: s.TsCode,
|
||||
Symbol: s.Symbol,
|
||||
Name: s.Name,
|
||||
Area: s.Area,
|
||||
Industry: s.Industry,
|
||||
Fullname: s.Fullname,
|
||||
Enname: s.Enname,
|
||||
Cnspell: s.Cnspell,
|
||||
Market: s.Market,
|
||||
Exchange: s.Exchange,
|
||||
CurrType: s.CurrType,
|
||||
ListStatus: s.ListStatus,
|
||||
ListDate: s.ListDate,
|
||||
DelistDate: s.DelistDate,
|
||||
IsHs: s.IsHs,
|
||||
ActName: s.ActName,
|
||||
ActEntType: s.ActEntType,
|
||||
}
|
||||
}
|
||||
|
||||
// DataSyncHandler 处理数据同步相关接口。
|
||||
type DataSyncHandler struct {
|
||||
DB *gorm.DB
|
||||
client *datasource.Client
|
||||
}
|
||||
|
||||
// NewDataSyncHandler 创建数据同步处理器。
|
||||
func NewDataSyncHandler(db *gorm.DB) *DataSyncHandler {
|
||||
return &DataSyncHandler{
|
||||
DB: db,
|
||||
client: datasource.NewClient(),
|
||||
}
|
||||
}
|
||||
|
||||
type initStocksResponse struct {
|
||||
Count int `json:"count"`
|
||||
Message string `json:"message"`
|
||||
}
|
||||
|
||||
// InitStocks 从 Tushare 拉取全部上市股票列表并写入数据库。
|
||||
func (h *DataSyncHandler) InitStocks(c *gin.Context) {
|
||||
stocks, err := h.client.ListStocks()
|
||||
if err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": err.Error()})
|
||||
return
|
||||
}
|
||||
|
||||
records := make([]models.Stock, 0, len(stocks))
|
||||
for _, s := range stocks {
|
||||
records = append(records, toModelStock(s))
|
||||
}
|
||||
|
||||
if err := h.DB.Exec("TRUNCATE TABLE stocks RESTART IDENTITY").Error; err != nil {
|
||||
if !strings.Contains(err.Error(), "does not exist") {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": "清空旧数据失败: " + err.Error()})
|
||||
return
|
||||
}
|
||||
}
|
||||
|
||||
if err := h.DB.CreateInBatches(records, 500).Error; err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": "写入股票列表失败: " + err.Error()})
|
||||
return
|
||||
}
|
||||
|
||||
c.JSON(http.StatusOK, gin.H{
|
||||
"success": true,
|
||||
"data": initStocksResponse{
|
||||
Count: len(records),
|
||||
Message: "股票列表初始化完成",
|
||||
},
|
||||
})
|
||||
}
|
||||
|
||||
type syncStocksByExchangeResponse struct {
|
||||
Exchange string `json:"exchange"`
|
||||
Count int `json:"count"`
|
||||
Message string `json:"message"`
|
||||
}
|
||||
|
||||
// SyncStocksByExchange 按交易所从 Tushare 同步股票基础信息。
|
||||
func (h *DataSyncHandler) SyncStocksByExchange(c *gin.Context) {
|
||||
exchange := strings.ToUpper(strings.TrimSpace(c.Param("exchange")))
|
||||
if _, ok := validExchanges[exchange]; !ok {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"success": false, "error": "无效的交易所代码，支持 SSE/SZSE/BSE"})
|
||||
return
|
||||
}
|
||||
|
||||
stocks, err := h.client.ListStocksByExchange(exchange)
|
||||
if err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": err.Error()})
|
||||
return
|
||||
}
|
||||
|
||||
records := make([]models.Stock, 0, len(stocks))
|
||||
for _, s := range stocks {
|
||||
records = append(records, toModelStock(s))
|
||||
}
|
||||
|
||||
if err := h.DB.Clauses(clause.OnConflict{
|
||||
Columns: []clause.Column{{Name: "ts_code"}},
|
||||
UpdateAll: true,
|
||||
}).CreateInBatches(records, 500).Error; err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"success": false, "error": "写入股票列表失败: " + err.Error()})
|
||||
return
|
||||
}
|
||||
|
||||
c.JSON(http.StatusOK, gin.H{
|
||||
"success": true,
|
||||
"data": syncStocksByExchangeResponse{
|
||||
Exchange: exchange,
|
||||
Count: len(records),
|
||||
Message: validExchanges[exchange] + "股票同步完成",
|
||||
},
|
||||
})
|
||||
}
|
||||
@@ -1,131 +0,0 @@
|
||||
package middleware
|
||||
|
||||
import (
|
||||
"net/http"
|
||||
"strings"
|
||||
"time"
|
||||
|
||||
"stock-user-system/internal/config"
|
||||
"stock-user-system/internal/models"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
"github.com/golang-jwt/jwt/v5"
|
||||
"gorm.io/gorm"
|
||||
)
|
||||
|
||||
type CurrentUser struct {
|
||||
ID string
|
||||
Username string
|
||||
Role models.RoleName
|
||||
}
|
||||
|
||||
var publicPaths = map[string]struct{}{
|
||||
"/api/auth/login": {},
|
||||
}
|
||||
|
||||
func AuthMiddleware(cfg *config.Config, db *gorm.DB) gin.HandlerFunc {
|
||||
return func(c *gin.Context) {
|
||||
authHeader := c.GetHeader("Authorization")
|
||||
token := ""
|
||||
if strings.HasPrefix(authHeader, "Bearer ") {
|
||||
token = strings.TrimPrefix(authHeader, "Bearer ")
|
||||
}
|
||||
|
||||
if token != "" {
|
||||
claims, err := parseToken(token, cfg.JWTSecret)
|
||||
if err == nil {
|
||||
var user models.User
|
||||
if err := db.Preload("Role").Where("id = ? AND status = ?", claims.Subject, "active").First(&user).Error; err == nil {
|
||||
c.Set("currentUser", CurrentUser{
|
||||
ID: user.ID,
|
||||
Username: user.Username,
|
||||
Role: user.Role.NameEnum(),
|
||||
})
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if _, exists := c.Get("currentUser"); !exists {
|
||||
if c.Request.Method == "OPTIONS" {
|
||||
c.Next()
|
||||
return
|
||||
}
|
||||
if _, ok := publicPaths[c.Request.URL.Path]; !ok {
|
||||
c.AbortWithStatusJSON(http.StatusUnauthorized, gin.H{"success": false, "error": "访问令牌无效或已过期"})
|
||||
return
|
||||
}
|
||||
}
|
||||
|
||||
c.Next()
|
||||
}
|
||||
}
|
||||
|
||||
type Claims struct {
|
||||
Subject string `json:"sub"`
|
||||
Role string `json:"role"`
|
||||
jwt.RegisteredClaims
|
||||
}
|
||||
|
||||
func GenerateToken(userID string, role models.RoleName, cfg *config.Config) (string, error) {
|
||||
claims := Claims{
|
||||
Subject: userID,
|
||||
Role: role.String(),
|
||||
RegisteredClaims: jwt.RegisteredClaims{
|
||||
ExpiresAt: jwt.NewNumericDate(time.Now().Add(cfg.JWTExpiration())),
|
||||
},
|
||||
}
|
||||
token := jwt.NewWithClaims(jwt.SigningMethodHS256, claims)
|
||||
return token.SignedString([]byte(cfg.JWTSecret))
|
||||
}
|
||||
|
||||
func parseToken(tokenString string, secret string) (*Claims, error) {
|
||||
token, err := jwt.ParseWithClaims(tokenString, &Claims{}, func(token *jwt.Token) (interface{}, error) {
|
||||
return []byte(secret), nil
|
||||
})
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
if claims, ok := token.Claims.(*Claims); ok && token.Valid {
|
||||
return claims, nil
|
||||
}
|
||||
return nil, jwt.ErrSignatureInvalid
|
||||
}
|
||||
|
||||
func RequireAuth() gin.HandlerFunc {
|
||||
return func(c *gin.Context) {
|
||||
if _, exists := c.Get("currentUser"); !exists {
|
||||
c.JSON(http.StatusUnauthorized, gin.H{"success": false, "error": "访问令牌无效或已过期"})
|
||||
c.Abort()
|
||||
return
|
||||
}
|
||||
c.Next()
|
||||
}
|
||||
}
|
||||
|
||||
func RequireRoles(allowed ...models.RoleName) gin.HandlerFunc {
|
||||
return func(c *gin.Context) {
|
||||
val, exists := c.Get("currentUser")
|
||||
if !exists {
|
||||
c.JSON(http.StatusUnauthorized, gin.H{"success": false, "error": "访问令牌无效或已过期"})
|
||||
c.Abort()
|
||||
return
|
||||
}
|
||||
current := val.(CurrentUser)
|
||||
for _, role := range allowed {
|
||||
if current.Role == role {
|
||||
c.Next()
|
||||
return
|
||||
}
|
||||
}
|
||||
c.JSON(http.StatusForbidden, gin.H{"success": false, "error": "权限不足"})
|
||||
c.Abort()
|
||||
}
|
||||
}
|
||||
|
||||
func GetCurrentUser(c *gin.Context) (CurrentUser, bool) {
|
||||
val, exists := c.Get("currentUser")
|
||||
if !exists {
|
||||
return CurrentUser{}, false
|
||||
}
|
||||
return val.(CurrentUser), true
|
||||
}
|
||||
@@ -1,36 +0,0 @@
|
||||
package models
|
||||
|
||||
import (
|
||||
"time"
|
||||
|
||||
"gorm.io/gorm"
|
||||
)
|
||||
|
||||
// Stock 存储股票基础信息。
|
||||
type Stock struct {
|
||||
ID string `json:"id" gorm:"type:uuid;primaryKey;default:gen_random_uuid()"`
|
||||
TsCode string `json:"ts_code" gorm:"size:32;not null;uniqueIndex"`
|
||||
Symbol string `json:"symbol" gorm:"size:32;not null;index"`
|
||||
Name string `json:"name" gorm:"size:128"`
|
||||
Area string `json:"area" gorm:"size:64"`
|
||||
Industry string `json:"industry" gorm:"size:64"`
|
||||
Fullname string `json:"fullname" gorm:"size:256"`
|
||||
Enname string `json:"enname" gorm:"size:256"`
|
||||
Cnspell string `json:"cnspell" gorm:"size:64"`
|
||||
Market string `json:"market" gorm:"size:16"`
|
||||
Exchange string `json:"exchange" gorm:"size:16;index"`
|
||||
CurrType string `json:"curr_type" gorm:"size:16"`
|
||||
ListStatus string `json:"list_status" gorm:"size:8"`
|
||||
ListDate string `json:"list_date" gorm:"size:16"`
|
||||
DelistDate string `json:"delist_date" gorm:"size:16"`
|
||||
IsHs string `json:"is_hs" gorm:"size:8"`
|
||||
ActName string `json:"act_name" gorm:"size:128"`
|
||||
ActEntType string `json:"act_ent_type" gorm:"size:64"`
|
||||
CreatedAt time.Time `json:"created_at"`
|
||||
UpdatedAt time.Time `json:"updated_at"`
|
||||
}
|
||||
|
||||
// AutoMigrateStocks 迁移股票基础信息表。
|
||||
func AutoMigrateStocks(db *gorm.DB) error {
|
||||
return db.AutoMigrate(&Stock{})
|
||||
}
|
||||
@@ -1,151 +0,0 @@
|
||||
package models
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"time"
|
||||
|
||||
"golang.org/x/crypto/bcrypt"
|
||||
"gorm.io/gorm"
|
||||
)
|
||||
|
||||
type RoleName string
|
||||
|
||||
const (
|
||||
RoleSystemAdmin RoleName = "system_admin"
|
||||
RoleAdmin RoleName = "admin"
|
||||
RoleUser RoleName = "user"
|
||||
)
|
||||
|
||||
func (r RoleName) String() string { return string(r) }
|
||||
|
||||
func (r RoleName) Rank() int {
|
||||
switch r {
|
||||
case RoleSystemAdmin:
|
||||
return 3
|
||||
case RoleAdmin:
|
||||
return 2
|
||||
case RoleUser:
|
||||
return 1
|
||||
default:
|
||||
return 0
|
||||
}
|
||||
}
|
||||
|
||||
func (r RoleName) CanManage(target RoleName) bool {
|
||||
return r.Rank() > target.Rank()
|
||||
}
|
||||
|
||||
func ParseRoleName(s string) (RoleName, error) {
|
||||
switch s {
|
||||
case "system_admin":
|
||||
return RoleSystemAdmin, nil
|
||||
case "admin":
|
||||
return RoleAdmin, nil
|
||||
case "user":
|
||||
return RoleUser, nil
|
||||
default:
|
||||
return "", fmt.Errorf("unknown role: %s", s)
|
||||
}
|
||||
}
|
||||
|
||||
type Role struct {
|
||||
ID int32 `json:"id" gorm:"primaryKey;autoIncrement"`
|
||||
Name string `json:"name" gorm:"uniqueIndex;size:32;not null"`
|
||||
Description *string `json:"description"`
|
||||
Permissions string `json:"permissions" gorm:"type:jsonb;default:'[]'"`
|
||||
CreatedAt time.Time `json:"created_at"`
|
||||
Users []User `json:"-" gorm:"foreignKey:RoleID"`
|
||||
}
|
||||
|
||||
func (r *Role) NameEnum() RoleName {
|
||||
role, _ := ParseRoleName(r.Name)
|
||||
return role
|
||||
}
|
||||
|
||||
type User struct {
|
||||
ID string `json:"id" gorm:"type:uuid;primaryKey;default:gen_random_uuid()"`
|
||||
Username string `json:"username" gorm:"uniqueIndex;size:32;not null"`
|
||||
Email *string `json:"email" gorm:"uniqueIndex;size:128"`
|
||||
PasswordHash string `json:"-" gorm:"size:255"`
|
||||
RoleID int32 `json:"role_id" gorm:"not null"`
|
||||
Role Role `json:"role,omitempty" gorm:"foreignKey:RoleID;references:ID"`
|
||||
Status string `json:"status" gorm:"size:16;default:active"`
|
||||
CreatedAt time.Time `json:"created_at"`
|
||||
UpdatedAt time.Time `json:"updated_at"`
|
||||
}
|
||||
|
||||
type PublicUserInfo struct {
|
||||
ID string `json:"id"`
|
||||
Username string `json:"username"`
|
||||
Email *string `json:"email"`
|
||||
Role RoleName `json:"role"`
|
||||
Status string `json:"status"`
|
||||
CreatedAt time.Time `json:"created_at"`
|
||||
}
|
||||
|
||||
func (u *User) ToPublicInfo() PublicUserInfo {
|
||||
return PublicUserInfo{
|
||||
ID: u.ID,
|
||||
Username: u.Username,
|
||||
Email: u.Email,
|
||||
Role: u.Role.NameEnum(),
|
||||
Status: u.Status,
|
||||
CreatedAt: u.CreatedAt,
|
||||
}
|
||||
}
|
||||
|
||||
func AutoMigrate(db *gorm.DB) error {
|
||||
return db.AutoMigrate(&Role{}, &User{})
|
||||
}
|
||||
|
||||
func SeedRoles(db *gorm.DB) error {
|
||||
roles := []Role{
|
||||
{Name: string(RoleSystemAdmin), Description: strPtr("系统管理员，可管理管理员与系统配置"), Permissions: `["*"]`},
|
||||
{Name: string(RoleAdmin), Description: strPtr("管理员，可管理普通用户"), Permissions: `["users.read", "users.write", "users.create"]`},
|
||||
{Name: string(RoleUser), Description: strPtr("普通用户，可访问业务功能"), Permissions: `["dashboard.read", "profile.write"]`},
|
||||
}
|
||||
for _, role := range roles {
|
||||
var existing Role
|
||||
if err := db.Where("name = ?", role.Name).First(&existing).Error; err != nil {
|
||||
if err == gorm.ErrRecordNotFound {
|
||||
if err := db.Create(&role).Error; err != nil {
|
||||
return err
|
||||
}
|
||||
} else {
|
||||
return err
|
||||
}
|
||||
}
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
// SeedSystemAdmin 在没有 system_admin 用户时创建默认系统管理员账号。
|
||||
func SeedSystemAdmin(db *gorm.DB) error {
|
||||
var existing User
|
||||
if err := db.Where("username = ?", "system_admin").First(&existing).Error; err == nil {
|
||||
return nil
|
||||
} else if err != gorm.ErrRecordNotFound {
|
||||
return err
|
||||
}
|
||||
|
||||
var role Role
|
||||
if err := db.Where("name = ?", RoleSystemAdmin).First(&role).Error; err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
hash, err := bcrypt.GenerateFromPassword([]byte("system_admin"), bcrypt.DefaultCost)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
return db.Create(&User{
|
||||
Username: "system_admin",
|
||||
PasswordHash: string(hash),
|
||||
RoleID: role.ID,
|
||||
Status: "active",
|
||||
}).Error
|
||||
}
|
||||
|
||||
func strPtr(s string) *string {
|
||||
return &s
|
||||
}
|
||||
@@ -1,59 +0,0 @@
|
||||
package routes
|
||||
|
||||
import (
|
||||
"stock-user-system/internal/config"
|
||||
"stock-user-system/internal/handlers"
|
||||
"stock-user-system/internal/middleware"
|
||||
"stock-user-system/internal/models"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
"gorm.io/gorm"
|
||||
)
|
||||
|
||||
func Setup(cfg *config.Config, db *gorm.DB) *gin.Engine {
|
||||
authHandler := &handlers.AuthHandler{DB: db, CFG: cfg}
|
||||
adminHandler := &handlers.AdminHandler{DB: db, CFG: cfg}
|
||||
dataSyncHandler := handlers.NewDataSyncHandler(db)
|
||||
|
||||
r := gin.Default()
|
||||
|
||||
// CORS
|
||||
r.Use(func(c *gin.Context) {
|
||||
c.Writer.Header().Set("Access-Control-Allow-Origin", "*")
|
||||
c.Writer.Header().Set("Access-Control-Allow-Methods", "GET, POST, PUT, DELETE, OPTIONS")
|
||||
c.Writer.Header().Set("Access-Control-Allow-Headers", "Origin, Content-Type, Accept, Authorization")
|
||||
if c.Request.Method == "OPTIONS" {
|
||||
c.AbortWithStatus(204)
|
||||
return
|
||||
}
|
||||
c.Next()
|
||||
})
|
||||
|
||||
r.Use(middleware.AuthMiddleware(cfg, db))
|
||||
|
||||
// 公开接口（仅登录）
|
||||
r.POST("/api/auth/login", authHandler.Login)
|
||||
|
||||
// 受保护接口
|
||||
auth := r.Group("/api/auth")
|
||||
auth.Use(middleware.RequireAuth())
|
||||
{
|
||||
auth.GET("/me", authHandler.Me)
|
||||
auth.POST("/logout", authHandler.Logout)
|
||||
}
|
||||
|
||||
// 管理员接口
|
||||
admin := r.Group("/api/admin")
|
||||
admin.Use(middleware.RequireAuth(), middleware.RequireRoles(models.RoleAdmin, models.RoleSystemAdmin))
|
||||
{
|
||||
admin.GET("/users", adminHandler.ListUsers)
|
||||
admin.POST("/users", adminHandler.CreateUser)
|
||||
admin.PUT("/users/:id", adminHandler.UpdateUser)
|
||||
admin.DELETE("/users/:id", adminHandler.DeleteUser)
|
||||
admin.GET("/roles", adminHandler.ListRoles)
|
||||
admin.POST("/data-sync/init-stocks", dataSyncHandler.InitStocks)
|
||||
admin.POST("/data-sync/stocks/:exchange", dataSyncHandler.SyncStocksByExchange)
|
||||
}
|
||||
|
||||
return r
|
||||
}
|
||||
@@ -1,63 +0,0 @@
|
||||
services:
|
||||
db:
|
||||
image: postgres:18.3-alpine3.23
|
||||
container_name: stock_db
|
||||
environment:
|
||||
POSTGRES_USER: ${DB_USER:-stock}
|
||||
POSTGRES_PASSWORD: ${DB_PASSWORD:-stock}
|
||||
POSTGRES_DB: ${DB_NAME:-stock}
|
||||
TZ: Asia/Shanghai
|
||||
volumes:
|
||||
- postgres_data:/var/lib/postgresql
|
||||
ports:
|
||||
- "5432:5432"
|
||||
healthcheck:
|
||||
test: ["CMD-SHELL", "pg_isready -U ${DB_USER:-stock} -d ${DB_NAME:-stock}"]
|
||||
interval: 5s
|
||||
timeout: 5s
|
||||
retries: 5
|
||||
networks:
|
||||
- stock_network
|
||||
|
||||
backend:
|
||||
build:
|
||||
context: ./backend
|
||||
dockerfile: Dockerfile
|
||||
container_name: stock_backend
|
||||
environment:
|
||||
DATABASE_URL: postgres://${DB_USER:-stock}:${DB_PASSWORD:-stock}@db:5432/${DB_NAME:-stock}
|
||||
JWT_SECRET: ${JWT_SECRET:-change-me-in-production}
|
||||
JWT_EXPIRATION_HOURS: ${JWT_EXPIRATION_HOURS:-168}
|
||||
GIN_MODE: ${GIN_MODE:-release}
|
||||
PORT: 3019
|
||||
TZ: Asia/Shanghai
|
||||
ports:
|
||||
- "3019:3019"
|
||||
depends_on:
|
||||
db:
|
||||
condition: service_healthy
|
||||
networks:
|
||||
- stock_network
|
||||
restart: unless-stopped
|
||||
|
||||
frontend:
|
||||
build:
|
||||
context: ./frontend
|
||||
dockerfile: Dockerfile
|
||||
container_name: stock_frontend
|
||||
environment:
|
||||
TZ: Asia/Shanghai
|
||||
ports:
|
||||
- "3018:80"
|
||||
depends_on:
|
||||
- backend
|
||||
networks:
|
||||
- stock_network
|
||||
restart: unless-stopped
|
||||
|
||||
volumes:
|
||||
postgres_data:
|
||||
|
||||
networks:
|
||||
stock_network:
|
||||
driver: bridge
|
||||
@@ -1,20 +0,0 @@
|
||||
# 前端构建
|
||||
ARG NODE_IMAGE=node:20-alpine
|
||||
|
||||
FROM ${NODE_IMAGE} AS builder
|
||||
WORKDIR /build
|
||||
|
||||
COPY package.json package-lock.json* ./
|
||||
RUN npm install
|
||||
|
||||
COPY . ./
|
||||
RUN npm run build
|
||||
|
||||
# 使用 nginx 提供静态资源
|
||||
FROM nginx:1.29.0-alpine
|
||||
RUN apk add --no-cache tzdata
|
||||
ENV TZ=Asia/Shanghai
|
||||
COPY --from=builder /build/dist /usr/share/nginx/html
|
||||
COPY nginx.conf /etc/nginx/conf.d/default.conf
|
||||
EXPOSE 80
|
||||
CMD ["nginx", "-g", "daemon off;"]
|
||||
@@ -1,14 +0,0 @@
|
||||
<!doctype html>
|
||||
<html lang="zh-CN">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<link rel="icon" type="image/svg+xml" href="/favicon.svg" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="theme-color" content="#0A0A0B" />
|
||||
<title>A股工具</title>
|
||||
</head>
|
||||
<body class="bg-base text-foreground antialiased">
|
||||
<div id="root"></div>
|
||||
<script type="module" src="/src/main.tsx"></script>
|
||||
</body>
|
||||
</html>
|
||||
@@ -1,19 +0,0 @@
|
||||
server {
|
||||
listen 80;
|
||||
server_name localhost;
|
||||
root /usr/share/nginx/html;
|
||||
index index.html;
|
||||
|
||||
location / {
|
||||
try_files $uri $uri/ /index.html;
|
||||
}
|
||||
|
||||
location /api {
|
||||
proxy_pass http://backend:3019;
|
||||
proxy_http_version 1.1;
|
||||
proxy_set_header Host $host;
|
||||
proxy_set_header X-Real-IP $remote_addr;
|
||||
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
|
||||
proxy_set_header X-Forwarded-Proto $scheme;
|
||||
}
|
||||
}
|
||||
@@ -1,34 +0,0 @@
|
||||
{
|
||||
"name": "stock-user-frontend",
|
||||
"private": true,
|
||||
"version": "0.1.0",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
"build": "tsc -b && vite build",
|
||||
"preview": "vite preview",
|
||||
"lint": "eslint ."
|
||||
},
|
||||
"dependencies": {
|
||||
"axios": "^1.7.2",
|
||||
"class-variance-authority": "^0.7.0",
|
||||
"clsx": "^2.1.1",
|
||||
"lucide-react": "^0.439.0",
|
||||
"react": "^18.3.1",
|
||||
"react-dom": "^18.3.1",
|
||||
"react-router-dom": "^6.26.0",
|
||||
"tailwind-merge": "^2.5.2"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^20.14.0",
|
||||
"@types/react": "^18.3.5",
|
||||
"@types/react-dom": "^18.3.0",
|
||||
"@vitejs/plugin-react": "^4.3.1",
|
||||
"autoprefixer": "^10.4.20",
|
||||
"postcss": "^8.4.45",
|
||||
"tailwindcss": "^3.4.10",
|
||||
"tailwindcss-animate": "^1.0.7",
|
||||
"typescript": "^5.5.4",
|
||||
"vite": "^5.4.3"
|
||||
}
|
||||
}
|
||||
@@ -1,6 +0,0 @@
|
||||
export default {
|
||||
plugins: {
|
||||
tailwindcss: {},
|
||||
autoprefixer: {},
|
||||
},
|
||||
}
|
||||
@@ -1,4 +0,0 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 100 100">
|
||||
<rect width="100" height="100" rx="20" fill="#8B5CF6"/>
|
||||
<text x="50" y="68" font-family="system-ui, sans-serif" font-size="52" font-weight="bold" fill="white" text-anchor="middle">A</text>
|
||||
</svg>
|
||||
|
Before Width: | Height: | Size: 263 B |
@@ -1,48 +0,0 @@
|
||||
import { useEffect, useState } from 'react'
|
||||
import { Navigate, useLocation } from 'react-router-dom'
|
||||
import { Loader2 } from 'lucide-react'
|
||||
import { api, UserInfo } from '@/lib/api'
|
||||
import { clearAuth, RoleName } from '@/lib/auth'
|
||||
|
||||
interface AuthGuardProps {
|
||||
children: React.ReactNode
|
||||
allowedRoles?: RoleName[]
|
||||
requireAuth?: boolean
|
||||
}
|
||||
|
||||
export function AuthGuard({ children, allowedRoles, requireAuth = true }: AuthGuardProps) {
|
||||
const location = useLocation()
|
||||
const [user, setUser] = useState<UserInfo | null | undefined>(undefined)
|
||||
|
||||
useEffect(() => {
|
||||
const token = localStorage.getItem('access_token')
|
||||
if (!token) {
|
||||
setUser(null)
|
||||
return
|
||||
}
|
||||
api.me()
|
||||
.then(setUser)
|
||||
.catch(() => {
|
||||
clearAuth()
|
||||
setUser(null)
|
||||
})
|
||||
}, [location.pathname])
|
||||
|
||||
if (user === undefined) {
|
||||
return (
|
||||
<div className="h-screen w-full flex items-center justify-center bg-base text-foreground">
|
||||
<Loader2 className="h-6 w-6 animate-spin text-accent" />
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
if (requireAuth && !user) {
|
||||
return <Navigate to="/login" state={{ from: location.pathname }} replace />
|
||||
}
|
||||
|
||||
if (allowedRoles && user && !allowedRoles.includes(user.role)) {
|
||||
return <Navigate to="/" replace />
|
||||
}
|
||||
|
||||
return <>{children}</>
|
||||
}
|
||||
@@ -1,178 +0,0 @@
|
||||
import { useState } from 'react'
|
||||
import { X, UserPlus, AlertCircle, Loader2 } from 'lucide-react'
|
||||
import { api } from '@/lib/api'
|
||||
import { RoleName, roleLabel } from '@/lib/auth'
|
||||
import { cn } from '@/lib/cn'
|
||||
|
||||
interface CreateUserDialogProps {
|
||||
open: boolean
|
||||
onClose: () => void
|
||||
onSuccess: () => void
|
||||
allowedRoles: RoleName[]
|
||||
}
|
||||
|
||||
export function CreateUserDialog({ open, onClose, onSuccess, allowedRoles }: CreateUserDialogProps) {
|
||||
const [form, setForm] = useState({
|
||||
username: '',
|
||||
email: '',
|
||||
password: '',
|
||||
confirmPassword: '',
|
||||
role: (allowedRoles[0] || 'user') as RoleName,
|
||||
})
|
||||
const [error, setError] = useState('')
|
||||
const [loading, setLoading] = useState(false)
|
||||
|
||||
if (!open) return null
|
||||
|
||||
const handleSubmit = async (e: React.FormEvent) => {
|
||||
e.preventDefault()
|
||||
setError('')
|
||||
|
||||
if (!form.username.trim()) {
|
||||
setError('请输入用户名')
|
||||
return
|
||||
}
|
||||
if (form.password.length < 6) {
|
||||
setError('密码长度至少 6 位')
|
||||
return
|
||||
}
|
||||
if (form.password !== form.confirmPassword) {
|
||||
setError('两次输入的密码不一致')
|
||||
return
|
||||
}
|
||||
if (!allowedRoles.includes(form.role as RoleName)) {
|
||||
setError('没有权限分配该角色')
|
||||
return
|
||||
}
|
||||
|
||||
setLoading(true)
|
||||
try {
|
||||
await api.createUser({
|
||||
username: form.username.trim(),
|
||||
email: form.email.trim() || undefined,
|
||||
password: form.password,
|
||||
role: form.role,
|
||||
})
|
||||
setForm({ username: '', email: '', password: '', confirmPassword: '', role: (allowedRoles[0] || 'user') as RoleName })
|
||||
onSuccess()
|
||||
} catch (err: any) {
|
||||
setError(err?.message || '创建失败')
|
||||
} finally {
|
||||
setLoading(false)
|
||||
}
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="fixed inset-0 z-50 flex items-center justify-center p-4">
|
||||
<div className="absolute inset-0 bg-black/60" onClick={onClose} />
|
||||
<div className="relative w-full max-w-md rounded-card border border-border bg-surface p-6 shadow-xl">
|
||||
<div className="flex items-center justify-between mb-5">
|
||||
<div className="flex items-center gap-2">
|
||||
<div className="p-1.5 rounded-btn bg-accent/10 text-accent">
|
||||
<UserPlus className="h-4 w-4" />
|
||||
</div>
|
||||
<h2 className="text-base font-semibold text-foreground">创建用户</h2>
|
||||
</div>
|
||||
<button
|
||||
onClick={onClose}
|
||||
className="p-1.5 rounded-btn text-secondary hover:bg-elevated hover:text-foreground transition-colors"
|
||||
>
|
||||
<X className="h-4 w-4" />
|
||||
</button>
|
||||
</div>
|
||||
|
||||
{error && (
|
||||
<div className="flex items-start gap-2 rounded-btn border border-danger/30 bg-danger/10 px-3 py-2.5 text-xs text-danger mb-4">
|
||||
<AlertCircle className="h-3.5 w-3.5 mt-px shrink-0" />
|
||||
<span>{error}</span>
|
||||
</div>
|
||||
)}
|
||||
|
||||
<form onSubmit={handleSubmit} className="space-y-4">
|
||||
<div>
|
||||
<label className="block text-xs text-secondary mb-1">用户名</label>
|
||||
<input
|
||||
required
|
||||
placeholder="用户名"
|
||||
value={form.username}
|
||||
onChange={(e) => setForm({ ...form, username: e.target.value })}
|
||||
className="w-full rounded-input bg-base border border-border px-3 py-2 text-sm focus:outline-none focus:border-accent"
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<label className="block text-xs text-secondary mb-1">邮箱（可选）</label>
|
||||
<input
|
||||
type="email"
|
||||
placeholder="邮箱"
|
||||
value={form.email}
|
||||
onChange={(e) => setForm({ ...form, email: e.target.value })}
|
||||
className="w-full rounded-input bg-base border border-border px-3 py-2 text-sm focus:outline-none focus:border-accent"
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div className="grid grid-cols-2 gap-3">
|
||||
<div>
|
||||
<label className="block text-xs text-secondary mb-1">密码</label>
|
||||
<input
|
||||
required
|
||||
type="password"
|
||||
placeholder="密码"
|
||||
value={form.password}
|
||||
onChange={(e) => setForm({ ...form, password: e.target.value })}
|
||||
className="w-full rounded-input bg-base border border-border px-3 py-2 text-sm focus:outline-none focus:border-accent"
|
||||
/>
|
||||
</div>
|
||||
<div>
|
||||
<label className="block text-xs text-secondary mb-1">确认密码</label>
|
||||
<input
|
||||
required
|
||||
type="password"
|
||||
placeholder="确认密码"
|
||||
value={form.confirmPassword}
|
||||
onChange={(e) => setForm({ ...form, confirmPassword: e.target.value })}
|
||||
className="w-full rounded-input bg-base border border-border px-3 py-2 text-sm focus:outline-none focus:border-accent"
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<label className="block text-xs text-secondary mb-1">角色</label>
|
||||
<select
|
||||
value={form.role}
|
||||
onChange={(e) => setForm({ ...form, role: e.target.value as RoleName })}
|
||||
className="w-full rounded-input bg-base border border-border px-3 py-2 text-sm focus:outline-none focus:border-accent"
|
||||
>
|
||||
{allowedRoles.map((r) => (
|
||||
<option key={r} value={r}>
|
||||
{roleLabel(r)}
|
||||
</option>
|
||||
))}
|
||||
</select>
|
||||
</div>
|
||||
|
||||
<div className="flex items-center justify-end gap-2 pt-2">
|
||||
<button
|
||||
type="button"
|
||||
onClick={onClose}
|
||||
className="px-4 py-2 rounded-btn text-sm text-secondary hover:bg-elevated hover:text-foreground transition-colors"
|
||||
>
|
||||
取消
|
||||
</button>
|
||||
<button
|
||||
type="submit"
|
||||
disabled={loading}
|
||||
className={cn(
|
||||
'inline-flex items-center gap-2 px-4 py-2 rounded-btn bg-accent text-white text-sm font-medium hover:bg-accent/90 transition-colors',
|
||||
loading && 'opacity-60',
|
||||
)}
|
||||
>
|
||||
{loading && <Loader2 className="h-3.5 w-3.5 animate-spin" />}
|
||||
创建
|
||||
</button>
|
||||
</div>
|
||||
</form>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
@@ -1,151 +0,0 @@
|
||||
import { useEffect, useState } from 'react'
|
||||
import { NavLink, Outlet, useNavigate } from 'react-router-dom'
|
||||
import {
|
||||
Users,
|
||||
User,
|
||||
Database,
|
||||
LogOut,
|
||||
Moon,
|
||||
Sun,
|
||||
Menu,
|
||||
} from 'lucide-react'
|
||||
import { api, UserInfo } from '@/lib/api'
|
||||
import { clearAuth, canManageUsers, roleLabel } from '@/lib/auth'
|
||||
import { cn } from '@/lib/cn'
|
||||
import { useTheme } from './ThemeProvider'
|
||||
|
||||
const BRAND = '#8B5CF6'
|
||||
|
||||
export function Layout() {
|
||||
const { resolved, setTheme, theme } = useTheme()
|
||||
const isDark = resolved === 'dark'
|
||||
const navigate = useNavigate()
|
||||
const [user, setUser] = useState<UserInfo | null>(null)
|
||||
const [mobileOpen, setMobileOpen] = useState(false)
|
||||
|
||||
useEffect(() => {
|
||||
const token = localStorage.getItem('access_token')
|
||||
if (!token) {
|
||||
setUser(null)
|
||||
return
|
||||
}
|
||||
api.me()
|
||||
.then(setUser)
|
||||
.catch(() => {
|
||||
clearAuth()
|
||||
setUser(null)
|
||||
})
|
||||
}, [navigate])
|
||||
|
||||
const handleLogout = async () => {
|
||||
try {
|
||||
await api.logout()
|
||||
} catch {}
|
||||
clearAuth()
|
||||
navigate('/login', { replace: true })
|
||||
}
|
||||
|
||||
const navItems = [
|
||||
...(user && canManageUsers(user.role) ? [{ to: '/users', label: '用户管理', icon: Users }] : []),
|
||||
...(user && canManageUsers(user.role) ? [{ to: '/data-sync', label: '数据同步', icon: Database }] : []),
|
||||
{ to: '/profile', label: '个人中心', icon: User },
|
||||
]
|
||||
|
||||
const toggleTheme = () => {
|
||||
if (theme === 'system') {
|
||||
setTheme(isDark ? 'light' : 'dark')
|
||||
} else {
|
||||
setTheme(theme === 'dark' ? 'light' : 'dark')
|
||||
}
|
||||
}
|
||||
|
||||
const sidebar = (
|
||||
<aside className="border-r border-border bg-surface flex flex-col h-full min-h-0 overflow-hidden w-56 lg:w-60">
|
||||
<div className="px-5 py-5 border-b border-border shrink-0">
|
||||
<div className="flex items-center gap-2.5">
|
||||
<div
|
||||
className="h-7 w-7 rounded-lg flex items-center justify-center text-white font-bold text-sm"
|
||||
style={{ background: BRAND }}
|
||||
>
|
||||
A
|
||||
</div>
|
||||
<div className="font-mono font-bold text-[13px] tracking-[0.06em] text-foreground leading-tight">
|
||||
<div>用户体系</div>
|
||||
<div>工作台</div>
|
||||
</div>
|
||||
</div>
|
||||
<div
|
||||
className="mt-4 h-px"
|
||||
style={{ background: `linear-gradient(90deg, ${BRAND}88, transparent 80%)` }}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<nav className="flex-1 min-h-0 overflow-y-auto px-2 py-3 space-y-0.5">
|
||||
{navItems.map(({ to, label, icon: Icon }) => (
|
||||
<NavLink
|
||||
key={to}
|
||||
to={to}
|
||||
onClick={() => setMobileOpen(false)}
|
||||
className={({ isActive }) =>
|
||||
cn(
|
||||
'flex items-center gap-3 px-3 py-2 rounded-btn text-sm transition-colors duration-150 ease-smooth',
|
||||
isActive
|
||||
? 'bg-elevated text-foreground font-medium'
|
||||
: 'text-foreground/80 hover:bg-elevated hover:text-foreground',
|
||||
)
|
||||
}
|
||||
>
|
||||
<Icon className="h-4 w-4 shrink-0" />
|
||||
<span className="flex-1">{label}</span>
|
||||
</NavLink>
|
||||
))}
|
||||
</nav>
|
||||
|
||||
<div className="border-t border-border px-3 py-3 shrink-0 space-y-2">
|
||||
{user && (
|
||||
<div className="px-3 py-2 rounded-btn bg-elevated/50">
|
||||
<div className="text-sm font-medium text-foreground truncate">{user.username}</div>
|
||||
<div className="text-[10px] text-secondary">{roleLabel(user.role)}</div>
|
||||
</div>
|
||||
)}
|
||||
<div className="flex items-center gap-1">
|
||||
<button
|
||||
onClick={toggleTheme}
|
||||
className="flex-1 flex items-center justify-center gap-2 px-3 py-2 rounded-btn text-xs text-secondary hover:bg-elevated hover:text-foreground transition-colors"
|
||||
>
|
||||
{isDark ? <Sun className="h-3.5 w-3.5" /> : <Moon className="h-3.5 w-3.5" />}
|
||||
{isDark ? '浅色' : '深色'}
|
||||
</button>
|
||||
<button
|
||||
onClick={handleLogout}
|
||||
className="flex-1 flex items-center justify-center gap-2 px-3 py-2 rounded-btn text-xs text-danger hover:bg-danger/10 transition-colors"
|
||||
>
|
||||
<LogOut className="h-3.5 w-3.5" />
|
||||
退出
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</aside>
|
||||
)
|
||||
|
||||
return (
|
||||
<div className="h-screen flex flex-col lg:grid lg:grid-cols-[14rem_1fr] bg-base text-foreground overflow-hidden">
|
||||
<div className="lg:hidden flex items-center justify-between px-4 py-3 border-b border-border bg-surface shrink-0">
|
||||
<div className="flex items-center gap-2.5">
|
||||
<div className="h-6 w-6 rounded-md flex items-center justify-center text-white text-xs font-bold" style={{ background: BRAND }}>A</div>
|
||||
<span className="text-sm font-semibold">用户体系工作台</span>
|
||||
</div>
|
||||
<button onClick={() => setMobileOpen(!mobileOpen)} className="p-2 rounded-btn hover:bg-elevated">
|
||||
<Menu className="h-5 w-5" />
|
||||
</button>
|
||||
</div>
|
||||
<div className={cn('fixed inset-0 z-40 lg:static lg:block', mobileOpen ? 'block' : 'hidden')}>
|
||||
<div className="absolute inset-0 bg-black/50 lg:hidden" onClick={() => setMobileOpen(false)} />
|
||||
<div className="relative z-10 h-full max-w-[14rem]">{sidebar}</div>
|
||||
</div>
|
||||
<main className="flex-1 min-h-0 overflow-auto scrollbar-gutter-stable p-6">
|
||||
<Outlet />
|
||||
</main>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
@@ -1,137 +0,0 @@
|
||||
import { useState } from 'react'
|
||||
import { Shield, Lock, AlertCircle, Loader2, LogIn } from 'lucide-react'
|
||||
import { api, setToken } from '@/lib/api'
|
||||
import { setStoredUser } from '@/lib/auth'
|
||||
|
||||
interface LoginFormProps {
|
||||
onSuccess: () => void
|
||||
}
|
||||
|
||||
export function LoginForm({ onSuccess }: LoginFormProps) {
|
||||
const [username, setUsername] = useState('')
|
||||
const [password, setPassword] = useState('')
|
||||
const [error, setError] = useState('')
|
||||
const [loading, setLoading] = useState(false)
|
||||
|
||||
const handleSubmit = async (e: React.FormEvent) => {
|
||||
e.preventDefault()
|
||||
setError('')
|
||||
if (!username.trim() || !password.trim()) {
|
||||
setError('请输入用户名和密码')
|
||||
return
|
||||
}
|
||||
setLoading(true)
|
||||
try {
|
||||
const res = await api.login({ username: username.trim(), password })
|
||||
setToken(res.token)
|
||||
setStoredUser(res.user)
|
||||
onSuccess()
|
||||
} catch (err: any) {
|
||||
setError(err?.message || '登录失败，请稍后重试')
|
||||
} finally {
|
||||
setLoading(false)
|
||||
}
|
||||
}
|
||||
|
||||
return (
|
||||
<motion.div
|
||||
initial={{ opacity: 0, y: 16 }}
|
||||
animate={{ opacity: 1, y: 0 }}
|
||||
transition={{ duration: 0.35, ease: [0.16, 1, 0.3, 1] }}
|
||||
className="w-full max-w-md"
|
||||
>
|
||||
<div className="rounded-card border border-border bg-surface/80 backdrop-blur-sm p-6">
|
||||
<div className="flex flex-col items-center text-center">
|
||||
<div
|
||||
className="rounded-2xl p-4 border border-border"
|
||||
style={{ background: 'linear-gradient(135deg, #8B5CF622, transparent)' }}
|
||||
>
|
||||
<Shield className="h-8 w-8" style={{ color: '#8B5CF6' }} />
|
||||
</div>
|
||||
<h1 className="mt-5 text-2xl font-bold text-foreground tracking-tight">登录账号</h1>
|
||||
<p className="mt-2 text-sm text-secondary leading-relaxed">
|
||||
请输入用户名和密码进入系统。
|
||||
</p>
|
||||
</div>
|
||||
|
||||
<form onSubmit={handleSubmit} className="mt-6 space-y-4">
|
||||
<div className="relative">
|
||||
<div className="absolute left-3 top-1/2 -translate-y-1/2 text-muted">
|
||||
<Shield className="h-4 w-4" />
|
||||
</div>
|
||||
<input
|
||||
type="text"
|
||||
autoComplete="username"
|
||||
placeholder="用户名"
|
||||
value={username}
|
||||
onChange={(e) => setUsername(e.target.value)}
|
||||
className="w-full pl-9 pr-3 py-2.5 rounded-input bg-base border border-border text-sm focus:outline-none focus:border-accent focus:ring-1 focus:ring-accent/30 transition-all"
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div className="relative">
|
||||
<div className="absolute left-3 top-1/2 -translate-y-1/2 text-muted">
|
||||
<Lock className="h-4 w-4" />
|
||||
</div>
|
||||
<input
|
||||
type="password"
|
||||
autoComplete="current-password"
|
||||
placeholder="密码"
|
||||
value={password}
|
||||
onChange={(e) => setPassword(e.target.value)}
|
||||
className="w-full pl-9 pr-3 py-2.5 rounded-input bg-base border border-border text-sm focus:outline-none focus:border-accent focus:ring-1 focus:ring-accent/30 transition-all"
|
||||
/>
|
||||
</div>
|
||||
|
||||
{error && (
|
||||
<div className="flex items-start gap-2 rounded-btn border border-danger/30 bg-danger/10 px-3 py-2.5 text-xs text-danger">
|
||||
<AlertCircle className="h-3.5 w-3.5 mt-px shrink-0" />
|
||||
<span>{error}</span>
|
||||
</div>
|
||||
)}
|
||||
|
||||
<button
|
||||
type="submit"
|
||||
disabled={loading}
|
||||
className="w-full inline-flex items-center justify-center gap-2 px-5 h-11 rounded-xl bg-accent text-white text-sm font-semibold shadow-lg shadow-accent/20 hover:bg-accent/90 hover:shadow-accent/30 disabled:opacity-60 transition-all"
|
||||
>
|
||||
{loading ? (
|
||||
<Loader2 className="h-4 w-4 animate-spin" />
|
||||
) : (
|
||||
<LogIn className="h-4 w-4" />
|
||||
)}
|
||||
{loading ? '处理中…' : '登录'}
|
||||
</button>
|
||||
</form>
|
||||
|
||||
<div className="mt-5 text-center">
|
||||
<span className="text-xs text-secondary">没有账号？请联系管理员创建</span>
|
||||
</div>
|
||||
</div>
|
||||
</motion.div>
|
||||
)
|
||||
}
|
||||
|
||||
// 简单内联 motion 组件，避免引入 framer-motion 依赖
|
||||
const motion = {
|
||||
div: ({ children, className, ...props }: any) => {
|
||||
return (
|
||||
<div
|
||||
ref={(el) => {
|
||||
if (el && props.initial) {
|
||||
el.style.opacity = String(props.initial.opacity ?? 1)
|
||||
el.style.transform = `translateY(${props.initial.y ?? 0}px)`
|
||||
requestAnimationFrame(() => {
|
||||
el.style.transition = `all ${props.transition?.duration ?? 0.3}s ${(props.transition?.ease || [0.16, 1, 0.3, 1]).join(',')}`
|
||||
el.style.opacity = String(props.animate?.opacity ?? 1)
|
||||
el.style.transform = `translateY(${props.animate?.y ?? 0}px)`
|
||||
})
|
||||
}
|
||||
}}
|
||||
className={className}
|
||||
>
|
||||
{children}
|
||||
</div>
|
||||
)
|
||||
},
|
||||
}
|
||||
@@ -1,81 +0,0 @@
|
||||
import { createContext, useContext, useEffect, useState } from 'react'
|
||||
|
||||
export type Theme = 'light' | 'dark' | 'system'
|
||||
export type ResolvedTheme = 'light' | 'dark'
|
||||
|
||||
interface ThemeContextValue {
|
||||
theme: Theme
|
||||
resolved: ResolvedTheme
|
||||
setTheme: (theme: Theme) => void
|
||||
}
|
||||
|
||||
const ThemeContext = createContext<ThemeContextValue | null>(null)
|
||||
|
||||
function resolveTheme(theme: Theme): ResolvedTheme {
|
||||
if (theme !== 'system') return theme
|
||||
if (typeof window === 'undefined') return 'dark'
|
||||
return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light'
|
||||
}
|
||||
|
||||
function updateMetaThemeColor(resolved: ResolvedTheme) {
|
||||
if (typeof document === 'undefined') return
|
||||
const meta = document.querySelector('meta[name="theme-color"]')
|
||||
if (!meta) return
|
||||
meta.setAttribute('content', resolved === 'dark' ? '#0A0A0B' : '#FAFAFA')
|
||||
}
|
||||
|
||||
export function ThemeProvider({ children }: { children: React.ReactNode }) {
|
||||
const [theme, setThemeState] = useState<Theme>(() => {
|
||||
try {
|
||||
const saved = localStorage.getItem('theme')
|
||||
if (saved === 'light' || saved === 'dark' || saved === 'system') return saved
|
||||
} catch {}
|
||||
return 'system'
|
||||
})
|
||||
const [resolved, setResolved] = useState<ResolvedTheme>(() => resolveTheme(theme))
|
||||
|
||||
useEffect(() => {
|
||||
const nextResolved = resolveTheme(theme)
|
||||
setResolved(nextResolved)
|
||||
|
||||
const root = document.documentElement
|
||||
root.classList.remove('light', 'dark')
|
||||
root.classList.add(nextResolved)
|
||||
try {
|
||||
localStorage.setItem('theme', theme)
|
||||
} catch {}
|
||||
updateMetaThemeColor(nextResolved)
|
||||
}, [theme])
|
||||
|
||||
useEffect(() => {
|
||||
if (theme !== 'system') return
|
||||
const media = window.matchMedia('(prefers-color-scheme: dark)')
|
||||
const handler = () => {
|
||||
const nextResolved = resolveTheme('system')
|
||||
setResolved(nextResolved)
|
||||
document.documentElement.classList.remove('light', 'dark')
|
||||
document.documentElement.classList.add(nextResolved)
|
||||
updateMetaThemeColor(nextResolved)
|
||||
}
|
||||
media.addEventListener('change', handler)
|
||||
return () => media.removeEventListener('change', handler)
|
||||
}, [theme])
|
||||
|
||||
const setTheme = (next: Theme) => {
|
||||
setThemeState(next)
|
||||
}
|
||||
|
||||
return (
|
||||
<ThemeContext.Provider value={{ theme, resolved, setTheme }}>
|
||||
{children}
|
||||
</ThemeContext.Provider>
|
||||
)
|
||||
}
|
||||
|
||||
export function useTheme(): ThemeContextValue {
|
||||
const ctx = useContext(ThemeContext)
|
||||
if (!ctx) {
|
||||
throw new Error('useTheme must be used within ThemeProvider')
|
||||
}
|
||||
return ctx
|
||||
}
|
||||
@@ -1,72 +0,0 @@
|
||||
@tailwind base;
|
||||
@tailwind components;
|
||||
@tailwind utilities;
|
||||
|
||||
/* 暗色为默认(html.dark) / 亮色用 :root 反转 */
|
||||
:root {
|
||||
--base: 0 0% 98%;
|
||||
--surface: 0 0% 100%;
|
||||
--elevated: 240 5% 96%;
|
||||
--border: 240 6% 90%;
|
||||
--fg-primary: 240 6% 10%;
|
||||
--fg-secondary: 240 4% 35%;
|
||||
--fg-muted: 240 5% 65%;
|
||||
--accent: 217 91% 60%;
|
||||
--bull: 4 87% 60%;
|
||||
--bear: 152 67% 45%;
|
||||
--warning: 32 95% 50%;
|
||||
--danger: 4 87% 60%;
|
||||
}
|
||||
|
||||
html.dark {
|
||||
--base: 240 5% 5%;
|
||||
--surface: 240 7% 10%;
|
||||
--elevated: 240 9% 14%;
|
||||
--border: 240 5% 22%;
|
||||
--fg-primary: 0 0% 98%;
|
||||
--fg-secondary: 240 5% 78%;
|
||||
--fg-muted: 240 5% 58%;
|
||||
--accent: 217 91% 60%;
|
||||
--bull: 4 87% 60%;
|
||||
--bear: 152 67% 45%;
|
||||
--warning: 32 95% 50%;
|
||||
--danger: 4 87% 60%;
|
||||
}
|
||||
|
||||
.scrollbar-gutter-stable { scrollbar-gutter: stable; }
|
||||
|
||||
* {
|
||||
scrollbar-width: thin;
|
||||
scrollbar-color: hsl(var(--border)) transparent;
|
||||
}
|
||||
*::-webkit-scrollbar {
|
||||
width: 8px;
|
||||
height: 8px;
|
||||
}
|
||||
*::-webkit-scrollbar-track {
|
||||
background: transparent;
|
||||
}
|
||||
*::-webkit-scrollbar-thumb {
|
||||
background: hsl(var(--border) / 0.72);
|
||||
border: 2px solid transparent;
|
||||
border-radius: 999px;
|
||||
background-clip: content-box;
|
||||
}
|
||||
*::-webkit-scrollbar-thumb:hover {
|
||||
background: hsl(var(--accent) / 0.75);
|
||||
background-clip: content-box;
|
||||
}
|
||||
|
||||
.tabular { font-variant-numeric: tabular-nums; }
|
||||
.num { font-family: theme('fontFamily.mono'); font-variant-numeric: tabular-nums; }
|
||||
|
||||
* { border-color: hsl(var(--border)); }
|
||||
|
||||
body {
|
||||
background: hsl(var(--base));
|
||||
color: hsl(var(--fg-primary));
|
||||
font-feature-settings: 'cv02', 'cv03', 'cv04', 'cv11';
|
||||
-webkit-font-smoothing: subpixel-antialiased;
|
||||
-moz-osx-font-smoothing: auto;
|
||||
text-rendering: optimizeLegibility;
|
||||
}
|
||||
@@ -1,133 +0,0 @@
|
||||
const API_BASE = import.meta.env.VITE_API_BASE_URL || ''
|
||||
|
||||
export interface ApiResponse<T> {
|
||||
success?: boolean
|
||||
data?: T
|
||||
error?: string
|
||||
}
|
||||
|
||||
export interface UserInfo {
|
||||
id: string
|
||||
username: string
|
||||
email?: string
|
||||
role: 'system_admin' | 'admin' | 'user'
|
||||
status: string
|
||||
created_at: string
|
||||
}
|
||||
|
||||
export interface Role {
|
||||
id: number
|
||||
name: 'system_admin' | 'admin' | 'user'
|
||||
description?: string
|
||||
permissions: string[]
|
||||
created_at: string
|
||||
}
|
||||
|
||||
export interface AuthResponse {
|
||||
token: string
|
||||
user: UserInfo
|
||||
}
|
||||
|
||||
export interface InitStocksResponse {
|
||||
success: boolean
|
||||
data: {
|
||||
count: number
|
||||
message: string
|
||||
}
|
||||
}
|
||||
|
||||
export interface SyncStocksByExchangeResponse {
|
||||
success: boolean
|
||||
data: {
|
||||
exchange: string
|
||||
count: number
|
||||
message: string
|
||||
}
|
||||
}
|
||||
|
||||
export function getToken(): string | null {
|
||||
try {
|
||||
return localStorage.getItem('access_token')
|
||||
} catch {
|
||||
return null
|
||||
}
|
||||
}
|
||||
|
||||
export function setToken(token: string) {
|
||||
localStorage.setItem('access_token', token)
|
||||
}
|
||||
|
||||
export function removeToken() {
|
||||
localStorage.removeItem('access_token')
|
||||
}
|
||||
|
||||
async function request<T>(
|
||||
path: string,
|
||||
options: RequestInit = {},
|
||||
): Promise<T> {
|
||||
const url = `${API_BASE}${path}`
|
||||
const token = getToken()
|
||||
const headers: Record<string, string> = {
|
||||
'Content-Type': 'application/json',
|
||||
...(options.headers as Record<string, string>),
|
||||
}
|
||||
if (token) {
|
||||
headers['Authorization'] = `Bearer ${token}`
|
||||
}
|
||||
|
||||
const res = await fetch(url, {
|
||||
...options,
|
||||
headers,
|
||||
})
|
||||
|
||||
let data: any
|
||||
try {
|
||||
data = await res.json()
|
||||
} catch {
|
||||
data = {}
|
||||
}
|
||||
|
||||
if (!res.ok) {
|
||||
const msg = data.error || data.message || `HTTP ${res.status}`
|
||||
throw new Error(msg)
|
||||
}
|
||||
|
||||
return data as T
|
||||
}
|
||||
|
||||
export const api = {
|
||||
login: (body: { username: string; password: string }) =>
|
||||
request<AuthResponse>('/api/auth/login', {
|
||||
method: 'POST',
|
||||
body: JSON.stringify(body),
|
||||
}),
|
||||
|
||||
me: () => request<UserInfo>('/api/auth/me'),
|
||||
|
||||
logout: () => request<{ message: string }>('/api/auth/logout', { method: 'POST' }),
|
||||
|
||||
listUsers: () => request<UserInfo[]>('/api/admin/users'),
|
||||
|
||||
createUser: (body: { username: string; email?: string; password: string; role?: string }) =>
|
||||
request<UserInfo>('/api/admin/users', {
|
||||
method: 'POST',
|
||||
body: JSON.stringify(body),
|
||||
}),
|
||||
|
||||
updateUser: (id: string, body: Partial<{ email: string; role: string; status: string }>) =>
|
||||
request<UserInfo>(`/api/admin/users/${id}`, {
|
||||
method: 'PUT',
|
||||
body: JSON.stringify(body),
|
||||
}),
|
||||
|
||||
deleteUser: (id: string) =>
|
||||
request<{ message: string }>(`/api/admin/users/${id}`, { method: 'DELETE' }),
|
||||
|
||||
listRoles: () => request<Role[]>('/api/admin/roles'),
|
||||
|
||||
initStocks: () =>
|
||||
request<InitStocksResponse>('/api/admin/data-sync/init-stocks', { method: 'POST' }),
|
||||
|
||||
syncStocksByExchange: (exchange: string) =>
|
||||
request<SyncStocksByExchangeResponse>(`/api/admin/data-sync/stocks/${exchange}`, { method: 'POST' }),
|
||||
}
|
||||
@@ -1,66 +0,0 @@
|
||||
import { UserInfo } from './api'
|
||||
|
||||
export function isAuthenticated(): boolean {
|
||||
try {
|
||||
return !!localStorage.getItem('access_token')
|
||||
} catch {
|
||||
return false
|
||||
}
|
||||
}
|
||||
|
||||
export function getStoredUser(): UserInfo | null {
|
||||
try {
|
||||
const raw = localStorage.getItem('user')
|
||||
return raw ? (JSON.parse(raw) as UserInfo) : null
|
||||
} catch {
|
||||
return null
|
||||
}
|
||||
}
|
||||
|
||||
export function setStoredUser(user: UserInfo | null) {
|
||||
if (user) {
|
||||
localStorage.setItem('user', JSON.stringify(user))
|
||||
} else {
|
||||
localStorage.removeItem('user')
|
||||
}
|
||||
}
|
||||
|
||||
export function clearAuth() {
|
||||
localStorage.removeItem('access_token')
|
||||
localStorage.removeItem('user')
|
||||
}
|
||||
|
||||
export type RoleName = 'system_admin' | 'admin' | 'user'
|
||||
|
||||
const ROLE_RANK: Record<RoleName, number> = {
|
||||
system_admin: 3,
|
||||
admin: 2,
|
||||
user: 1,
|
||||
}
|
||||
|
||||
export function roleRank(role: RoleName): number {
|
||||
return ROLE_RANK[role] ?? 0
|
||||
}
|
||||
|
||||
export function roleLabel(role: RoleName): string {
|
||||
switch (role) {
|
||||
case 'system_admin':
|
||||
return '系统管理员'
|
||||
case 'admin':
|
||||
return '管理员'
|
||||
case 'user':
|
||||
return '用户'
|
||||
}
|
||||
}
|
||||
|
||||
export function canAccess(role: RoleName, allowed: RoleName[]): boolean {
|
||||
return allowed.includes(role)
|
||||
}
|
||||
|
||||
export function canManageUsers(role: RoleName): boolean {
|
||||
return role === 'admin' || role === 'system_admin'
|
||||
}
|
||||
|
||||
export function canDeleteUsers(role: RoleName): boolean {
|
||||
return role === 'system_admin'
|
||||
}
|
||||
@@ -1,7 +0,0 @@
|
||||
import type { ClassValue } from 'clsx'
|
||||
import { clsx } from 'clsx'
|
||||
import { twMerge } from 'tailwind-merge'
|
||||
|
||||
export function cn(...inputs: ClassValue[]) {
|
||||
return twMerge(clsx(inputs))
|
||||
}
|
||||
@@ -1,14 +0,0 @@
|
||||
import React from 'react'
|
||||
import ReactDOM from 'react-dom/client'
|
||||
import { RouterProvider } from 'react-router-dom'
|
||||
import { router } from './router'
|
||||
import { ThemeProvider } from './components/ThemeProvider'
|
||||
import './index.css'
|
||||
|
||||
ReactDOM.createRoot(document.getElementById('root')!).render(
|
||||
<React.StrictMode>
|
||||
<ThemeProvider>
|
||||
<RouterProvider router={router} />
|
||||
</ThemeProvider>
|
||||
</React.StrictMode>,
|
||||
)
|
||||
@@ -1,135 +0,0 @@
|
||||
import { useState } from 'react'
|
||||
import { Database, RefreshCw, CheckCircle, AlertCircle } from 'lucide-react'
|
||||
import { api } from '@/lib/api'
|
||||
|
||||
const EXCHANGES = [
|
||||
{ code: 'SSE', name: '上交所' },
|
||||
{ code: 'SZSE', name: '深交所' },
|
||||
{ code: 'BSE', name: '北交所' },
|
||||
]
|
||||
|
||||
export function DataSync() {
|
||||
const [loading, setLoading] = useState<string | null>(null)
|
||||
const [result, setResult] = useState<{ exchange?: string; count: number; message: string } | null>(null)
|
||||
const [error, setError] = useState('')
|
||||
|
||||
const handleInitStocks = async () => {
|
||||
if (!confirm('确定要从 Tushare 初始化股票列表？这会清空现有股票数据。')) {
|
||||
return
|
||||
}
|
||||
setLoading('init')
|
||||
setError('')
|
||||
setResult(null)
|
||||
try {
|
||||
const res = await api.initStocks()
|
||||
setResult(res.data)
|
||||
} catch (err: any) {
|
||||
setError(err?.message || '初始化失败')
|
||||
} finally {
|
||||
setLoading(null)
|
||||
}
|
||||
}
|
||||
|
||||
const handleSyncByExchange = async (exchange: string, name: string) => {
|
||||
if (!confirm(`确定要同步${name}（${exchange}）股票数据？`)) {
|
||||
return
|
||||
}
|
||||
setLoading(exchange)
|
||||
setError('')
|
||||
setResult(null)
|
||||
try {
|
||||
const res = await api.syncStocksByExchange(exchange)
|
||||
setResult(res.data)
|
||||
} catch (err: any) {
|
||||
setError(err?.message || '同步失败')
|
||||
} finally {
|
||||
setLoading(null)
|
||||
}
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="max-w-2xl space-y-6">
|
||||
<div className="flex items-center gap-3">
|
||||
<div className="p-2 rounded-btn bg-accent/10 text-accent">
|
||||
<Database className="h-5 w-5" />
|
||||
</div>
|
||||
<div>
|
||||
<h1 className="text-xl font-bold text-foreground">数据同步</h1>
|
||||
<p className="text-sm text-secondary">从 Tushare 拉取基础数据</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{error && (
|
||||
<div className="flex items-start gap-2 rounded-btn border border-danger/30 bg-danger/10 px-3 py-2.5 text-xs text-danger">
|
||||
<AlertCircle className="h-3.5 w-3.5 mt-px shrink-0" />
|
||||
<span>{error}</span>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{result && (
|
||||
<div className="flex items-start gap-2 rounded-btn border border-success/30 bg-success/10 px-3 py-2.5 text-xs text-success">
|
||||
<CheckCircle className="h-3.5 w-3.5 mt-px shrink-0" />
|
||||
<span>
|
||||
{result.message}，共 {result.count} 条记录
|
||||
{result.exchange ? `（${result.exchange}）` : ''}
|
||||
</span>
|
||||
</div>
|
||||
)}
|
||||
|
||||
<div className="rounded-card border border-border bg-surface p-5 space-y-4">
|
||||
<div className="flex items-center justify-between">
|
||||
<div>
|
||||
<h2 className="text-sm font-semibold text-foreground">初始化股票列表</h2>
|
||||
<p className="text-xs text-secondary mt-1">调用 Tushare stock_basic 接口，获取全部 A 股基础信息</p>
|
||||
</div>
|
||||
<button
|
||||
onClick={handleInitStocks}
|
||||
disabled={loading !== null}
|
||||
className="inline-flex items-center gap-2 px-4 py-2 rounded-btn bg-accent text-white text-sm font-medium hover:bg-accent/90 disabled:opacity-50 disabled:cursor-not-allowed transition-colors"
|
||||
>
|
||||
{loading === 'init' ? (
|
||||
<RefreshCw className="h-4 w-4 animate-spin" />
|
||||
) : (
|
||||
<RefreshCw className="h-4 w-4" />
|
||||
)}
|
||||
{loading === 'init' ? '同步中...' : '开始同步'}
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="rounded-card border border-border bg-surface p-5 space-y-4">
|
||||
<div>
|
||||
<h2 className="text-sm font-semibold text-foreground">按交易所同步</h2>
|
||||
<p className="text-xs text-secondary mt-1">按交易所分别同步，不影响其他交易所数据</p>
|
||||
</div>
|
||||
<div className="grid grid-cols-3 gap-3">
|
||||
{EXCHANGES.map(({ code, name }) => (
|
||||
<button
|
||||
key={code}
|
||||
onClick={() => handleSyncByExchange(code, name)}
|
||||
disabled={loading !== null}
|
||||
className="inline-flex items-center justify-center gap-2 px-4 py-2 rounded-btn border border-border bg-surface text-foreground text-sm font-medium hover:bg-accent hover:text-white hover:border-accent disabled:opacity-50 disabled:cursor-not-allowed transition-colors"
|
||||
>
|
||||
{loading === code ? (
|
||||
<RefreshCw className="h-4 w-4 animate-spin" />
|
||||
) : (
|
||||
<RefreshCw className="h-4 w-4" />
|
||||
)}
|
||||
{loading === code ? '同步中...' : `${name} (${code})`}
|
||||
</button>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="rounded-card border border-border bg-surface p-5">
|
||||
<h2 className="text-sm font-semibold text-foreground mb-3">说明</h2>
|
||||
<ul className="space-y-2 text-sm text-secondary">
|
||||
<li>• 需要配置 TUSHARE_TOKEN 环境变量</li>
|
||||
<li>• 初始化会清空 stocks 表并重新写入</li>
|
||||
<li>• 按交易所同步采用 upsert 策略，以 ts_code 为唯一键更新或插入</li>
|
||||
<li>• 同步字段包括：代码、名称、交易所、行业、上市状态、上市日期、实控人等</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
@@ -1,50 +0,0 @@
|
||||
import { useEffect } from 'react'
|
||||
import { useNavigate } from 'react-router-dom'
|
||||
import { LoginForm } from '@/components/LoginForm'
|
||||
import { isAuthenticated } from '@/lib/auth'
|
||||
|
||||
const BRAND = '#8B5CF6'
|
||||
|
||||
export function Login() {
|
||||
const navigate = useNavigate()
|
||||
|
||||
useEffect(() => {
|
||||
if (isAuthenticated()) {
|
||||
navigate('/', { replace: true })
|
||||
}
|
||||
}, [navigate])
|
||||
|
||||
return (
|
||||
<div className="relative min-h-screen bg-base overflow-hidden flex flex-col">
|
||||
<div className="pointer-events-none absolute inset-0 overflow-hidden">
|
||||
<div
|
||||
className="absolute -top-40 -left-40 h-[28rem] w-[28rem] rounded-full blur-[120px] opacity-20"
|
||||
style={{ background: `radial-gradient(circle, ${BRAND}, transparent 70%)` }}
|
||||
/>
|
||||
<div
|
||||
className="absolute -bottom-40 -right-32 h-[26rem] w-[26rem] rounded-full blur-[120px] opacity-15"
|
||||
style={{ background: 'radial-gradient(circle, hsl(var(--accent)), transparent 70%)' }}
|
||||
/>
|
||||
<div
|
||||
className="absolute inset-0 opacity-[0.025]"
|
||||
style={{
|
||||
backgroundImage:
|
||||
'linear-gradient(hsl(var(--fg-primary)) 1px, transparent 1px), linear-gradient(90deg, hsl(var(--fg-primary)) 1px, transparent 1px)',
|
||||
backgroundSize: '40px 40px',
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<header className="relative z-10 flex items-center justify-between px-6 py-4 border-b border-border">
|
||||
<div className="flex items-center gap-2.5 text-foreground">
|
||||
<div className="h-6 w-6 rounded-md flex items-center justify-center text-white text-xs font-bold" style={{ background: BRAND }}>A</div>
|
||||
<span className="text-sm font-semibold tracking-tight">A股工具</span>
|
||||
</div>
|
||||
</header>
|
||||
|
||||
<main className="relative z-10 flex-1 flex items-center justify-center px-6 py-10">
|
||||
<LoginForm onSuccess={() => navigate('/', { replace: true })} />
|
||||
</main>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
@@ -1,73 +0,0 @@
|
||||
import { useEffect, useState } from 'react'
|
||||
import { User, Loader2, AlertCircle } from 'lucide-react'
|
||||
import { api, UserInfo } from '@/lib/api'
|
||||
import { roleLabel } from '@/lib/auth'
|
||||
|
||||
export function Profile() {
|
||||
const [user, setUser] = useState<UserInfo | null>(null)
|
||||
const [loading, setLoading] = useState(true)
|
||||
const [error, setError] = useState('')
|
||||
|
||||
useEffect(() => {
|
||||
api.me()
|
||||
.then(setUser)
|
||||
.catch((err: any) => setError(err?.message || '加载失败'))
|
||||
.finally(() => setLoading(false))
|
||||
}, [])
|
||||
|
||||
if (loading) {
|
||||
return (
|
||||
<div className="h-full flex items-center justify-center">
|
||||
<Loader2 className="h-6 w-6 animate-spin text-accent" />
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="max-w-xl space-y-6">
|
||||
<div className="flex items-center gap-3">
|
||||
<div className="p-2 rounded-btn bg-accent/10 text-accent">
|
||||
<User className="h-5 w-5" />
|
||||
</div>
|
||||
<h1 className="text-xl font-bold text-foreground">个人中心</h1>
|
||||
</div>
|
||||
|
||||
{error && (
|
||||
<div className="flex items-start gap-2 rounded-btn border border-danger/30 bg-danger/10 px-3 py-2.5 text-xs text-danger">
|
||||
<AlertCircle className="h-3.5 w-3.5 mt-px shrink-0" />
|
||||
<span>{error}</span>
|
||||
</div>
|
||||
)}
|
||||
|
||||
<div className="rounded-card border border-border bg-surface p-5 space-y-4">
|
||||
<div className="grid grid-cols-[6rem_1fr] gap-4 items-center">
|
||||
<span className="text-sm text-secondary">用户名</span>
|
||||
<span className="text-sm font-medium text-foreground">{user?.username}</span>
|
||||
</div>
|
||||
<div className="grid grid-cols-[6rem_1fr] gap-4 items-center">
|
||||
<span className="text-sm text-secondary">角色</span>
|
||||
<span className="text-sm font-medium text-foreground">{user ? roleLabel(user.role) : '-'}</span>
|
||||
</div>
|
||||
<div className="grid grid-cols-[6rem_1fr] gap-4 items-center">
|
||||
<span className="text-sm text-secondary">邮箱</span>
|
||||
<span className="text-sm font-medium text-foreground">{user?.email || '未设置'}</span>
|
||||
</div>
|
||||
<div className="grid grid-cols-[6rem_1fr] gap-4 items-center">
|
||||
<span className="text-sm text-secondary">状态</span>
|
||||
<span className="text-sm font-medium text-foreground">{user?.status === 'active' ? '启用' : '禁用'}</span>
|
||||
</div>
|
||||
<div className="grid grid-cols-[6rem_1fr] gap-4 items-center">
|
||||
<span className="text-sm text-secondary">注册时间</span>
|
||||
<span className="text-sm font-medium text-foreground">{user ? new Date(user.created_at).toLocaleString() : '-'}</span>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="rounded-card border border-border bg-surface p-5">
|
||||
<h2 className="text-sm font-semibold text-foreground mb-3">关于</h2>
|
||||
<p className="text-sm text-secondary leading-relaxed">
|
||||
本系统为 A 股复盘工具的用户权限管理模块。不同角色拥有不同的操作权限，系统管理员可在「用户管理」中分配角色。
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
@@ -1,172 +0,0 @@
|
||||
import { useEffect, useState } from 'react'
|
||||
import { Plus, Trash2, Users as UsersIcon, AlertCircle, Loader2 } from 'lucide-react'
|
||||
import { api, UserInfo } from '@/lib/api'
|
||||
import { canDeleteUsers, getStoredUser, roleLabel, RoleName } from '@/lib/auth'
|
||||
import { CreateUserDialog } from '@/components/CreateUserDialog'
|
||||
import { cn } from '@/lib/cn'
|
||||
|
||||
const creatableRoles: Record<RoleName, RoleName[]> = {
|
||||
system_admin: ['admin', 'user'],
|
||||
admin: ['user'],
|
||||
user: [],
|
||||
}
|
||||
|
||||
export function Users() {
|
||||
const [users, setUsers] = useState<UserInfo[]>([])
|
||||
const [loading, setLoading] = useState(true)
|
||||
const [error, setError] = useState('')
|
||||
const [dialogOpen, setDialogOpen] = useState(false)
|
||||
|
||||
const currentUser = getStoredUser()
|
||||
const allowedRoles = currentUser ? creatableRoles[currentUser.role] : []
|
||||
|
||||
const fetchData = async () => {
|
||||
setLoading(true)
|
||||
try {
|
||||
const u = await api.listUsers()
|
||||
setUsers(u)
|
||||
setError('')
|
||||
} catch (err: any) {
|
||||
setError(err?.message || '加载失败')
|
||||
} finally {
|
||||
setLoading(false)
|
||||
}
|
||||
}
|
||||
|
||||
useEffect(() => {
|
||||
fetchData()
|
||||
}, [])
|
||||
|
||||
const handleDelete = async (id: string) => {
|
||||
if (!confirm('确定删除该用户？')) return
|
||||
try {
|
||||
await api.deleteUser(id)
|
||||
fetchData()
|
||||
} catch (err: any) {
|
||||
setError(err?.message || '删除失败')
|
||||
}
|
||||
}
|
||||
|
||||
const handleStatusChange = async (user: UserInfo, status: string) => {
|
||||
try {
|
||||
await api.updateUser(user.id, { status })
|
||||
fetchData()
|
||||
} catch (err: any) {
|
||||
setError(err?.message || '更新失败')
|
||||
}
|
||||
}
|
||||
|
||||
const current = users.find((u) => u.username === currentUser?.username)
|
||||
|
||||
return (
|
||||
<div className="space-y-4">
|
||||
<div className="flex items-center justify-between">
|
||||
<div className="flex items-center gap-3">
|
||||
<div className="p-2 rounded-btn bg-accent/10 text-accent">
|
||||
<UsersIcon className="h-5 w-5" />
|
||||
</div>
|
||||
<h1 className="text-xl font-bold text-foreground">用户管理</h1>
|
||||
</div>
|
||||
<button
|
||||
onClick={() => setDialogOpen(true)}
|
||||
className="inline-flex items-center gap-2 px-3 py-2 rounded-btn bg-accent text-white text-sm font-medium hover:bg-accent/90 transition-colors"
|
||||
>
|
||||
<Plus className="h-4 w-4" />
|
||||
新建用户
|
||||
</button>
|
||||
</div>
|
||||
|
||||
{error && (
|
||||
<div className="flex items-start gap-2 rounded-btn border border-danger/30 bg-danger/10 px-3 py-2.5 text-xs text-danger">
|
||||
<AlertCircle className="h-3.5 w-3.5 mt-px shrink-0" />
|
||||
<span>{error}</span>
|
||||
</div>
|
||||
)}
|
||||
|
||||
<div className="rounded-card border border-border bg-surface overflow-hidden">
|
||||
<table className="w-full text-sm">
|
||||
<thead className="bg-elevated/50 text-secondary">
|
||||
<tr>
|
||||
<th className="px-4 py-3 text-left font-medium">用户名</th>
|
||||
<th className="px-4 py-3 text-left font-medium">角色</th>
|
||||
<th className="px-4 py-3 text-left font-medium">状态</th>
|
||||
<th className="px-4 py-3 text-left font-medium">创建时间</th>
|
||||
<th className="px-4 py-3 text-right font-medium">操作</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody className="divide-y divide-border">
|
||||
{loading ? (
|
||||
<tr>
|
||||
<td colSpan={5} className="px-4 py-8 text-center text-muted">
|
||||
<Loader2 className="h-5 w-5 animate-spin mx-auto" />
|
||||
</td>
|
||||
</tr>
|
||||
) : users.length === 0 ? (
|
||||
<tr>
|
||||
<td colSpan={5} className="px-4 py-8 text-center text-muted">暂无用户</td>
|
||||
</tr>
|
||||
) : (
|
||||
users.map((u) => (
|
||||
<tr key={u.id} className="hover:bg-elevated/30">
|
||||
<td className="px-4 py-3 text-foreground">{u.username}</td>
|
||||
<td className="px-4 py-3">
|
||||
<span className={cn('text-xs px-2 py-0.5 rounded', roleBadge(u.role))}>
|
||||
{roleLabel(u.role)}
|
||||
</span>
|
||||
</td>
|
||||
<td className="px-4 py-3">
|
||||
<select
|
||||
value={u.status}
|
||||
onChange={(e) => handleStatusChange(u, e.target.value)}
|
||||
disabled={u.id === current?.id}
|
||||
className="bg-base border border-border rounded-input px-2 py-1 text-xs disabled:opacity-50"
|
||||
>
|
||||
<option value="active">启用</option>
|
||||
<option value="disabled">禁用</option>
|
||||
</select>
|
||||
</td>
|
||||
<td className="px-4 py-3 text-muted text-xs">
|
||||
{new Date(u.created_at).toLocaleString()}
|
||||
</td>
|
||||
<td className="px-4 py-3 text-right">
|
||||
{canDeleteUsers(current?.role || 'user') && u.id !== current?.id && (
|
||||
<button
|
||||
onClick={() => handleDelete(u.id)}
|
||||
className="p-1.5 rounded-btn text-danger hover:bg-danger/10 transition-colors"
|
||||
>
|
||||
<Trash2 className="h-4 w-4" />
|
||||
</button>
|
||||
)}
|
||||
</td>
|
||||
</tr>
|
||||
))
|
||||
)}
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
|
||||
<CreateUserDialog
|
||||
open={dialogOpen}
|
||||
onClose={() => setDialogOpen(false)}
|
||||
onSuccess={() => {
|
||||
setDialogOpen(false)
|
||||
fetchData()
|
||||
}}
|
||||
allowedRoles={allowedRoles}
|
||||
/>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
function roleBadge(role: string) {
|
||||
switch (role) {
|
||||
case 'system_admin':
|
||||
return 'bg-accent/10 text-accent'
|
||||
case 'admin':
|
||||
return 'bg-purple-500/10 text-purple-400'
|
||||
case 'user':
|
||||
return 'bg-bear/10 text-bear'
|
||||
default:
|
||||
return 'bg-muted/10 text-muted'
|
||||
}
|
||||
}
|
||||
@@ -1,43 +0,0 @@
|
||||
import { createBrowserRouter, Navigate } from 'react-router-dom'
|
||||
import { Layout } from './components/Layout'
|
||||
import { AuthGuard } from './components/AuthGuard'
|
||||
import { Login } from './pages/Login'
|
||||
import { Users } from './pages/Users'
|
||||
import { Profile } from './pages/Profile'
|
||||
import { DataSync } from './pages/DataSync'
|
||||
|
||||
export const router = createBrowserRouter([
|
||||
{ path: '/login', element: <Login /> },
|
||||
{
|
||||
path: '/',
|
||||
element: (
|
||||
<AuthGuard requireAuth>
|
||||
<Layout />
|
||||
</AuthGuard>
|
||||
),
|
||||
children: [
|
||||
{ index: true, element: <Navigate to="/profile" replace /> },
|
||||
{
|
||||
path: 'users',
|
||||
element: (
|
||||
<AuthGuard allowedRoles={['admin', 'system_admin']} requireAuth>
|
||||
<Users />
|
||||
</AuthGuard>
|
||||
),
|
||||
},
|
||||
{
|
||||
path: 'data-sync',
|
||||
element: (
|
||||
<AuthGuard allowedRoles={['admin', 'system_admin']} requireAuth>
|
||||
<DataSync />
|
||||
</AuthGuard>
|
||||
),
|
||||
},
|
||||
{
|
||||
path: 'profile',
|
||||
element: <Profile />,
|
||||
},
|
||||
],
|
||||
},
|
||||
{ path: '*', element: <Navigate to="/" replace /> },
|
||||
])
|
||||
Vendored
-1
@@ -1 +0,0 @@
|
||||
/// <reference types="vite/client" />
|
||||
@@ -1,40 +0,0 @@
|
||||
import type { Config } from 'tailwindcss'
|
||||
import animate from 'tailwindcss-animate'
|
||||
|
||||
export default {
|
||||
darkMode: ['class'],
|
||||
content: ['./index.html', './src/**/*.{ts,tsx}'],
|
||||
theme: {
|
||||
container: { center: true, padding: '1rem' },
|
||||
extend: {
|
||||
colors: {
|
||||
base: 'hsl(var(--base) / <alpha-value>)',
|
||||
surface: 'hsl(var(--surface) / <alpha-value>)',
|
||||
elevated: 'hsl(var(--elevated) / <alpha-value>)',
|
||||
border: 'hsl(var(--border) / <alpha-value>)',
|
||||
foreground: 'hsl(var(--fg-primary) / <alpha-value>)',
|
||||
secondary: 'hsl(var(--fg-secondary) / <alpha-value>)',
|
||||
muted: 'hsl(var(--fg-muted) / <alpha-value>)',
|
||||
accent: 'hsl(var(--accent) / <alpha-value>)',
|
||||
bull: 'hsl(var(--bull) / <alpha-value>)',
|
||||
bear: 'hsl(var(--bear) / <alpha-value>)',
|
||||
warning: 'hsl(var(--warning) / <alpha-value>)',
|
||||
danger: 'hsl(var(--danger) / <alpha-value>)',
|
||||
},
|
||||
fontFamily: {
|
||||
sans: ['Inter', '"HarmonyOS Sans SC"', '"PingFang SC"', 'system-ui', 'sans-serif'],
|
||||
mono: ['"JetBrains Mono"', '"IBM Plex Mono"', 'ui-monospace', 'monospace'],
|
||||
},
|
||||
borderRadius: {
|
||||
card: '8px',
|
||||
btn: '6px',
|
||||
input: '4px',
|
||||
dialog: '12px',
|
||||
},
|
||||
transitionTimingFunction: {
|
||||
smooth: 'cubic-bezier(0.16, 1, 0.3, 1)',
|
||||
},
|
||||
},
|
||||
},
|
||||
plugins: [animate],
|
||||
} satisfies Config
|
||||
@@ -1,25 +0,0 @@
|
||||
{
|
||||
"compilerOptions": {
|
||||
"target": "ES2020",
|
||||
"useDefineForClassFields": true,
|
||||
"lib": ["ES2020", "DOM", "DOM.Iterable"],
|
||||
"module": "ESNext",
|
||||
"skipLibCheck": true,
|
||||
"moduleResolution": "bundler",
|
||||
"allowImportingTsExtensions": true,
|
||||
"resolveJsonModule": true,
|
||||
"isolatedModules": true,
|
||||
"noEmit": true,
|
||||
"jsx": "react-jsx",
|
||||
"strict": true,
|
||||
"noUnusedLocals": true,
|
||||
"noUnusedParameters": true,
|
||||
"noFallthroughCasesInSwitch": true,
|
||||
"baseUrl": ".",
|
||||
"paths": {
|
||||
"@/*": ["./src/*"]
|
||||
}
|
||||
},
|
||||
"include": ["src"],
|
||||
"references": [{ "path": "./tsconfig.node.json" }]
|
||||
}
|
||||
@@ -1,11 +0,0 @@
|
||||
{
|
||||
"compilerOptions": {
|
||||
"composite": true,
|
||||
"skipLibCheck": true,
|
||||
"module": "ESNext",
|
||||
"moduleResolution": "bundler",
|
||||
"allowSyntheticDefaultImports": true,
|
||||
"strict": true
|
||||
},
|
||||
"include": ["vite.config.ts"]
|
||||
}
|
||||
@@ -1,25 +0,0 @@
|
||||
import { defineConfig } from 'vite'
|
||||
import react from '@vitejs/plugin-react'
|
||||
import path from 'path'
|
||||
|
||||
// https://vitejs.dev/config/
|
||||
export default defineConfig({
|
||||
plugins: [react()],
|
||||
resolve: {
|
||||
alias: {
|
||||
'@': path.resolve(__dirname, './src'),
|
||||
},
|
||||
},
|
||||
server: {
|
||||
port: 5173,
|
||||
proxy: {
|
||||
'/api': {
|
||||
target: process.env.VITE_API_URL || 'http://localhost:3019',
|
||||
changeOrigin: true,
|
||||
},
|
||||
},
|
||||
},
|
||||
build: {
|
||||
outDir: 'dist',
|
||||
},
|
||||
})
|
||||
+25
-25
@@ -1,15 +1,14 @@
|
||||
# 两阶段构建:前端 dist 拷进后端镜像,单容器运行
|
||||
# 可选:构建网络无法直连官方源时:
|
||||
# 1. 传入 --build-arg USE_CN_MIRROR=1 启用国内 npm/pypi 镜像
|
||||
# 2. 传入 --build-arg PYTHON_IMAGE/NODE_IMAGE 使用 Docker Hub 国内镜像站
|
||||
# 可选:构建网络无法直连官方源时,传入 --build-arg USE_CN_MIRROR=1 启用国内镜像
|
||||
ARG USE_CN_MIRROR=1
|
||||
ARG NPM_REGISTRY=https://registry.npmmirror.com
|
||||
ARG PYPI_INDEX=https://pypi.tuna.tsinghua.edu.cn/simple
|
||||
ARG PYTHON_IMAGE=python:3.11-slim
|
||||
ARG NODE_IMAGE=node:20-alpine
|
||||
# 备用 PyPI 源:主源同步延迟/故障时自动兜底(阿里云与清华互为补充)
|
||||
ARG PYPI_FALLBACK=https://mirrors.aliyun.com/pypi/simple
|
||||
ARG BACKEND_EXTRAS=
|
||||
|
||||
# === Stage 1: 前端构建 ===
|
||||
FROM ${NODE_IMAGE} AS frontend-builder
|
||||
FROM node:20-alpine AS frontend-builder
|
||||
ARG USE_CN_MIRROR=1
|
||||
ARG NPM_REGISTRY=https://registry.npmmirror.com
|
||||
WORKDIR /build
|
||||
@@ -26,14 +25,21 @@ COPY frontend/ ./
|
||||
RUN pnpm build
|
||||
|
||||
# === Stage 2: Python 运行时 ===
|
||||
FROM ${PYTHON_IMAGE} AS runtime
|
||||
FROM python:3.11-slim AS runtime
|
||||
ARG USE_CN_MIRROR=1
|
||||
ARG PYPI_INDEX=https://pypi.tuna.tsinghua.edu.cn/simple
|
||||
ARG PYPI_FALLBACK=https://mirrors.aliyun.com/pypi/simple
|
||||
ARG BACKEND_EXTRAS=
|
||||
WORKDIR /app
|
||||
|
||||
# 安装 uv(快)
|
||||
# 安装 uv(快) —— 国内镜像下三重兜底:主源 → 备用源 → 官方源,
|
||||
# 任一成功即可,避免单一镜像同步延迟/故障导致构建失败。
|
||||
# uv 发版极频繁,国内镜像同步存在时间窗口,不锁版本且无 fallback 时
|
||||
# 容易遇到 "from versions: none"(索引解析不到最新版)。
|
||||
RUN if [ "$USE_CN_MIRROR" = "1" ]; then \
|
||||
pip install --no-cache-dir uv -i "$PYPI_INDEX"; \
|
||||
pip install --no-cache-dir uv -i "$PYPI_INDEX" || \
|
||||
pip install --no-cache-dir uv -i "$PYPI_FALLBACK" || \
|
||||
pip install --no-cache-dir uv; \
|
||||
else \
|
||||
pip install --no-cache-dir uv; \
|
||||
fi
|
||||
@@ -41,8 +47,16 @@ RUN if [ "$USE_CN_MIRROR" = "1" ]; then \
|
||||
# Backend deps
|
||||
COPY README.md /README.md
|
||||
COPY backend/pyproject.toml backend/uv.lock* ./
|
||||
RUN if [ "$USE_CN_MIRROR" = "1" ]; then export UV_DEFAULT_INDEX="$PYPI_INDEX"; fi; \
|
||||
uv sync --frozen --no-dev || uv sync --no-dev
|
||||
# uv 原生支持同时挂多个 index(主源 + 备用源),会自动在两源中查找,
|
||||
# 比逐个重试更稳健 —— 任一源缺包时另一源补位。
|
||||
RUN if [ "$USE_CN_MIRROR" = "1" ]; then \
|
||||
export UV_DEFAULT_INDEX="$PYPI_INDEX" UV_EXTRA_INDEX_URL="$PYPI_FALLBACK"; \
|
||||
fi; \
|
||||
set -- --no-dev; \
|
||||
for extra in $BACKEND_EXTRAS; do \
|
||||
set -- "$@" --extra "$extra"; \
|
||||
done; \
|
||||
uv sync --frozen "$@" || uv sync "$@"
|
||||
|
||||
# Backend code
|
||||
# 注意:Docker 里 WORKDIR=/app, 而 config.py 的 _PROJECT_ROOT 是按开发布局
|
||||
@@ -60,17 +74,3 @@ COPY --from=frontend-builder /build/dist ./static
|
||||
ENV PYTHONPATH=/app
|
||||
EXPOSE 3018
|
||||
CMD ["uv", "run", "uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "3018"]
|
||||
|
||||
# === Stage 3: 测试镜像 ===
|
||||
# 基于 runtime 追加 dev + backtest 依赖,用于运行 pytest。
|
||||
# 生产镜像保持 --no-dev,此 stage 仅用于 CI/本地测试。
|
||||
FROM runtime AS test
|
||||
ARG USE_CN_MIRROR=1
|
||||
ARG PYPI_INDEX=https://pypi.tuna.tsinghua.edu.cn/simple
|
||||
|
||||
RUN if [ "$USE_CN_MIRROR" = "1" ]; then export UV_DEFAULT_INDEX="$PYPI_INDEX"; fi; \
|
||||
uv sync --frozen --extra backtest --extra dev || uv sync --extra backtest --extra dev
|
||||
|
||||
COPY backend/tests ./tests
|
||||
|
||||
CMD ["uv", "run", "pytest", "tests"]
|
||||
|
||||
@@ -0,0 +1,21 @@
|
||||
MIT License
|
||||
|
||||
Copyright (c) 2026 tickflow-stock-panel contributors
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
+212
-238
@@ -4,32 +4,51 @@
|
||||
|
||||
**自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台**
|
||||
|
||||
**面向个人散户与量化爱好者而生**
|
||||
|
||||
[](./LICENSE)
|
||||
[](https://www.python.org/)
|
||||
[](https://react.dev/)
|
||||
[](https://tickflow.org/auth/register?ref=V3KDKGXPEA)
|
||||
[](./Dockerfile)
|
||||
|
||||
🚀 **开箱即用**(单容器 / Free 模式无需 Key) · 能力驱动,适配 Free → Expert 全档位订阅 · 🔌 **自由接入第三方扩展数据**(Tushare、自有量化项目数据等)
|
||||
|
||||
**[核心功能](#-核心功能)** · **[快速开始](#-快速开始)** · **[架构](#%EF%B8%8F-架构)** · **[配置](#%EF%B8%8F-配置)** · **[路线图](#-路线图)**
|
||||
[](https://github.com/shy3130/tickflow-stock-panel/stargazers)
|
||||
|
||||
</div>
|
||||
|
||||
> **⚠️说明**:目前项目默认接入内置数据源。自有数据源需二次开发修改字段映射即可;后续需求人多的话可能会实现切换数据源功能。
|
||||
<div align="center">
|
||||
|
||||
**[快速开始](#-快速开始)** · **[核心功能](#-核心功能)** · **[配置](#️-配置)** · **[路线图](#-路线图)**
|
||||
|
||||
</div>
|
||||
|
||||
- 🆓 **开箱即用** — 留空 Key 即进 None 模式,历史日 K 免费体验,**无需付费**
|
||||
- 🏠 **自托管零运维** — Docker 单容器部署,数据完全掌握在自己手里
|
||||
- 🔍 **三位一体** — 选股(20 内置策略)+ 实时监控 + 向量化回测,Polars 毫秒级扫描全 A 股
|
||||
- 🤖 **AI 加持** — 一句话生成策略代码,任意 OpenAI 兼容接口均可接入(留空即关闭)
|
||||
- 🔌 **自由扩展** — 自有量化项目数据,与内置数据同台分析
|
||||
- 🇨🇳 **A 股专用** — 盘后自动AI复盘并推送至飞书等;连板梯队、涨停动量、内置ths 概念 / 行业
|
||||
|
||||
|
||||
|
||||
基于 [TickFlow](https://tickflow.org/auth/register?ref=V3KDKGXPEA) 数据源。**明确不做**:不对标同花顺 / 通达信,不内置「AI 荐股 / 涨停预测」。
|
||||
|
||||
> ⚠️ 考虑到tickflow数据源没有人气/资金流向等个性化数据,我将开放自有的第三方数据以供大佬们研究使用,包括但不限于当前内置的ths概念/ths行业(后续更新在这里)
|
||||
|
||||
|
||||
> 有更多稳定免费数据源推荐,或者提交建议/意见的大佬可以邮件到 415333856@qq.com,q群 109338242
|
||||
|
||||
|
||||
觉得有用可以点个 Star，蟹蟹 🌹
|
||||
|
||||
---
|
||||
|
||||
## 🎯 项目定位
|
||||
|
||||
让任何**个人散户 / 量化爱好者**,**零运维**地拥有一套**与自己订阅档位严格匹配**的 A 股分析、选股、监控工作台。
|
||||
**任意接入第三方数据**(Tushare 等),页面可视化自定义配置扩展数据表。
|
||||
**面向个人散户与量化爱好者的 A 股分析工作台**,聚焦「**选股 + 监控 + 回测**」三大场景,LLM能力驱动进行市场分析，掌控市场节奏；让普通投资者也能拥有一套可自定义策略的量化工具。
|
||||
|
||||
**项目所需配置**:
|
||||
---
|
||||
|
||||
| 配置项 | 说明 | 是否必填 |
|
||||
| :--- | :--- | :--- |
|
||||
| **数据源 API Key** | 数据源凭证,留空启用 Free 模式(无需注册即可体验) | 可选 |
|
||||
| **AI 大模型 API Key** | 用于 AI 生成策略、个股分析(开发中)、行情分析(开发中),任意 OpenAI 兼容接口,留空关闭 | 可选 |
|
||||
## 📸 界面预览
|
||||
|
||||
<table>
|
||||
<tr>
|
||||
@@ -37,30 +56,110 @@
|
||||
<td width="50%" align="center"><b>策略 Screener</b></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td width="50%"><img src="./docs/screenshots/dashboard.png" alt="看板页面" title="看板页面"></td>
|
||||
<td width="50%"><img src="./docs/screenshots/screener.png" alt="策略页" title="策略页"></td>
|
||||
<td width="50%"><img src="./screenshots/dashboard.png" alt="看板页面"></td>
|
||||
<td width="50%"><img src="./screenshots/screener.png" alt="策略页"></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td width="50%" align="center"><b>回测 Backtest</b></td>
|
||||
<td width="50%" align="center"><b>监控中心 Monitor</b></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td width="50%"><img src="./docs/screenshots/backtest.png" alt="回测页" title="回测页"></td>
|
||||
<td width="50%"><img src="./docs/screenshots/monitor.png" alt="监控中心" title="监控中心"></td>
|
||||
<td width="50%"><img src="./screenshots/backtest.png" alt="回测页"></td>
|
||||
<td width="50%"><img src="./screenshots/monitor.png" alt="监控中心"></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td width="50%" align="center"><b>连板梯队 Limit Ladder</b></td>
|
||||
<td width="50%" align="center"><b>概念分析 Concept</b></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td width="50%"><img src="./docs/screenshots/limit-ladder.png" alt="连板梯队页" title="连板梯队页"></td>
|
||||
<td width="50%"><img src="./docs/screenshots/concept-analysis.png" alt="概念分析" title="概念分析"></td>
|
||||
<td width="50%"><img src="./screenshots/limit-ladder.png" alt="连板梯队页"></td>
|
||||
<td width="50%"><img src="./screenshots/concept-analysis.png" alt="概念分析"></td>
|
||||
</tr>
|
||||
</table>
|
||||
|
||||
> ### ⚠️ 🚧 项目持续优化,功能陆续开放,敬请期待。
|
||||
<div align="center">
|
||||
|
||||
> **明确不做**:不对标同花顺/通达信的全功能股票软件;不内置任何「AI 荐股 / 涨停预测」。
|
||||
### 📸 [查看更多界面截图 »](./screenshots/README.md)
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
## 🚀 快速开始
|
||||
|
||||
### 前置依赖
|
||||
|
||||
| 工具 | 版本 | 安装 |
|
||||
| :--------------------------------- | :----- | :------------------------------------------------- |
|
||||
| Python | ≥ 3.11 | [python.org](https://www.python.org/) |
|
||||
| Node | ≥ 20 | [nodejs.org](https://nodejs.org/) |
|
||||
| [`uv`](https://docs.astral.sh/uv/) | latest | `curl -LsSf https://astral.sh/uv/install.sh \| sh` |
|
||||
| `pnpm` | 9 | `npm i -g pnpm` |
|
||||
|
||||
### 方式 A:Dev 模式(二次开发推荐)
|
||||
|
||||
```bash
|
||||
cp .env.example .env # 按需填 TICKFLOW_API_KEY(留空 = None 模式)
|
||||
./dev.sh # Windows: .\dev.ps1
|
||||
```
|
||||
|
||||
自动检查 / 下载依赖、释放端口、同时起前后端,Ctrl-C 一并关闭。默认:
|
||||
|
||||
- 后端 → <http://localhost:3018> · 前端 → <http://localhost:3011>
|
||||
- 自定义端口:`BACKEND_PORT=8000 FRONTEND_PORT=5173 ./dev.sh`
|
||||
|
||||
### 方式 B:Docker(部署最省心)
|
||||
|
||||
```bash
|
||||
cp .env.example .env
|
||||
docker compose up --build
|
||||
# 打开 http://localhost:3018
|
||||
```
|
||||
|
||||
<details>
|
||||
<summary><b>环境适配与高级选项(老 CPU · 手动启动 · 回测依赖)</b></summary>
|
||||
|
||||
**老 CPU 兼容(avx2/fma 缺失报错或 exit 132)**:桌面客户端安装包已内置兼容内核(新老 CPU 通吃)。Docker / 源码用户在 `.env` 打开 `BACKEND_EXTRAS=legacy-cpu` 后重建,会给 Polars 切到 `rtcompat` 运行时;需回测则 `BACKEND_EXTRAS=legacy-cpu backtest`。
|
||||
|
||||
**手动分别启动:**
|
||||
|
||||
```bash
|
||||
# 后端
|
||||
cd backend && uv sync --extra backtest # 含回测依赖
|
||||
uv run uvicorn app.main:app --reload --port 3018
|
||||
|
||||
# 前端
|
||||
cd frontend && pnpm install && pnpm dev # http://localhost:3011
|
||||
```
|
||||
|
||||
**回测依赖**:vectorbt → numba 体积较大,作为可选 extras(`uv sync --extra backtest`)。macOS / Intel 无预构建 wheel 时需 `brew install cmake` 现场编译。
|
||||
|
||||
</details>
|
||||
|
||||
### 🔄 更新代码(已部署用户必读)
|
||||
|
||||
拉取新版本只需一条命令:
|
||||
|
||||
```bash
|
||||
git pull
|
||||
```
|
||||
|
||||
**整个 `data/` 目录都不纳入 git**——行情 K线、财务、自选、回测、监控记录,乃至概念/行业扩展数据,全部是程序运行时生成/拉取的用户数据,`git pull` 物理上无法影响它们。新用户首次启动时,概念/行业两份扩展数据会自动从远程接口拉取,无需任何手动操作。
|
||||
|
||||
> ⚠️ **切勿使用以下命令"解决冲突"或"清理",它们会一次性删光 `data/` 下所有未被 git 跟踪的数据:**
|
||||
> - `git clean -fdx`(最危险,会删掉所有 `.gitignore` 忽略的文件)
|
||||
> - `git reset --hard`
|
||||
> - 直接删除整个项目文件夹重新 `git clone`
|
||||
>
|
||||
> 若 `git pull` 报冲突,通常是本地误改了被跟踪的文件,请先 `git stash` 暂存再 pull,或单独联系作者,不要直接执行上面的命令。
|
||||
|
||||
### 🧭 跑起来后的第一次使用
|
||||
|
||||
1. **设置 → 凭据与能力** → 点 **重新检测**,确认档位标签
|
||||
2. **设置** → **立即跑盘后管道**:拉日 K + 计算 enriched 表(None / Free 走 free-api,当日数据盘后 1-2 小时可用)
|
||||
3. **自选**页加标的 → **选股**页点策略卡片扫描 / 配自定义信号
|
||||
4. **回测**页选策略 + 区间 → 看净值 / 夏普 / 交易明细(SSE 实时进度)
|
||||
5. **监控中心**配规则(策略 / 个股信号 / 价格 / 异动),盘中实时弹窗 + 持久化记录
|
||||
|
||||
---
|
||||
|
||||
@@ -68,225 +167,87 @@
|
||||
|
||||
### 🔍 选股引擎(Screener)
|
||||
|
||||
**20+ 个内置策略** —— 每个策略是一个独立 Python 文件(`backend/app/strategy/builtin/`),基于 Polars 表达式实现:
|
||||
**20 个内置策略**,每个策略一个独立 Python 文件,基于 Polars 表达式向量化实现(`backend/app/strategy/builtin/`):
|
||||
|
||||
| 类型 | 代表策略 |
|
||||
| :--- | :--- |
|
||||
| 趋势 | 趋势突破 · 均线多头 · 缩量回踩 |
|
||||
| 形态 | MA 金叉 · MACD 金叉放量 · 布林突破 |
|
||||
| 量价 | 量价齐升 · 高换手强势 · 强势高开 |
|
||||
| 涨停 | 连板股 · 断板反包 · 逼近涨停 · 涨停动量 |
|
||||
| 反转 | 超跌反弹 · 超卖反转 · 新低反转 |
|
||||
| 波动 | 低波动龙头 · 回踩 MA20 反弹 |
|
||||
| :---------- | :------------------------------------------------------- |
|
||||
| 趋势 / 形态 | 趋势突破 · 均线多头 · MA 金叉 · MACD 金叉放量 · 布林突破 |
|
||||
| 量价 / 涨停 | 量价齐升 · 高换手强势 · 连板股 · 断板反包 · 涨停动量 |
|
||||
| 反转 / 波动 | 超跌反弹 · 超卖反转 · 新低反转 · 低波动龙头 · 回踩 MA20 |
|
||||
|
||||
- **自定义信号系统** —— 在 UI 上用 `字段 + 操作符 + 阈值` 组合(entry / exit / both),编译成 Polars 表达式热加载,**无需写代码**即可定义自己的买卖信号。
|
||||
- **策略商店** —— 内置策略 + 用户自定义策略统一管理,支持参数覆盖(`params` 暴露阈值)。
|
||||
**扩展策略的三种方式:**
|
||||
|
||||
#### ➕ 添加自己的策略
|
||||
|
||||
除 20 个内置策略外,你可以用三种方式扩展:
|
||||
|
||||
| 方式 | 说明 | 前提 |
|
||||
| :--- | :--- | :--- |
|
||||
| **🤖 AI 生成** | 用自然语言描述策略思路,LLM 读取 [strategy-guide.md](./docs/strategy-guide.md) 自动生成完整 Polars 策略文件(经 `ast` 安全校验,限定 `import polars as pl`)。生成后落入 `data/strategies/ai/`,即刻可用 | 需先在 [配置](#%EF%B8%8F-配置) 中填入 AI Key |
|
||||
| **📝 代码自定义 / 策略迁移** | 参照 [策略开发指南](./docs/strategy-guide.md) 的文件结构模板,把你**已有的自有策略**改写为 Polars 文件放入 `data/strategies/custom/`(文件名/ID 建议 `custom_时间戳`),引擎自动发现加载——**轻松迁移你现成的量化项目策略**,无需从头重写 | 无 |
|
||||
| **🎛️ 自定义信号配置** | 不写代码,在 UI 上用 `字段 + 操作符 + 阈值` 组合(entry / exit / both),编译成 Polars 表达式热加载,即可定义自己的买卖信号 | 无 |
|
||||
|
||||
> 引擎按 `source` 标记来源:`builtin`(内置)/ `custom`(手写或迁移)/ `ai`(生成),三者统一进入策略商店管理。
|
||||
| 方式 | 说明 |
|
||||
| :---------------- | :---------------------------------------------------------------------------------------------------- |
|
||||
| **🎛️ 自定义信号** | 不写代码,UI 上 `字段 + 操作符 + 阈值` 组合编译成 Polars 表达式热加载 |
|
||||
| **🤖 AI 生成** | 一句话描述思路,LLM 读 `strategy-guide.md` 生成完整策略文件(经 `ast` 校验)→ 落入 `data/strategies/ai/` |
|
||||
| **📝 代码迁移** | 参照开发指南把已有策略改写为 Polars 文件放入 `data/strategies/custom/`,引擎自动发现 |
|
||||
|
||||
### 📊 指标流水线(Indicators)
|
||||
|
||||
原生 Polars 向量化计算,全 A 股一次扫表落盘为 enriched Parquet:
|
||||
原生 Polars 向量化,全 A 股一次扫表落盘 enriched Parquet:
|
||||
|
||||
| 分类 | 指标 |
|
||||
| :--- | :--- |
|
||||
| 均线系 | MA(5/10/20/30/60)· EMA(5/10/12/20/26/30/60) |
|
||||
| 趋势系 | MACD(DIF/DEA/HIST)· 动量(5/10/20/30/60d)· 布林带(上/下轨) |
|
||||
| 震荡系 | RSI(可配周期)· KDJ(K/D/J) |
|
||||
| 波动系 | ATR(14)· 年化波动率(20d)· 振幅 |
|
||||
| 量能系 | 量比(5d/10d)· 量均线 |
|
||||
| 涨跌停 | 涨停信号 · 连板数 · 涨跌幅 · 涨跌额 |
|
||||
| 原子信号 | MA 金叉/死叉 · MA20 突破/跌破 · MACD 金叉/死叉 · N 日新高/新低 · 布林突破 |
|
||||
| 复权 | 基于除权因子自动计算前复权(`ex_factor` / `cum_factor`),回测与指标一致 |
|
||||
- **均线 / 趋势**:MA(5-60)· EMA · MACD · 动量 · 布林带
|
||||
- **震荡 / 波动**:RSI · KDJ · ATR · 年化波动率 · 振幅
|
||||
- **量能 / 涨跌停**:量比 · 量均线 · 涨停信号 · 连板数
|
||||
- **原子信号**:MA / MACD 金叉死叉 · N 日新高新低 · 布林突破
|
||||
- **复权**:基于除权因子自动前复权,回测与指标口径一致
|
||||
|
||||
### 🧪 回测引擎(Backtest)
|
||||
|
||||
自研 Polars/NumPy 撮合引擎为主,兼容 vectorbt 作为可选依赖:
|
||||
|
||||
- **三种回测模式**:个股 · 策略组合 · 自由信号组合
|
||||
- **真实约束**:T+1 · 手续费 · 滑点(基点) · 止损 · 最大持仓天数
|
||||
- **组合管理**:最大持仓数 · 最大敞口 · 等权 / 自定义仓位
|
||||
- **SSE 流式进度**:长任务实时推送进度,支持刷新 / 切页后**重连恢复**(相同参数任务只启动一次)
|
||||
- **统计输出**:净值曲线 · 夏普 · 最大回撤 · 胜率 · 每笔交易明细
|
||||
基于 vectorbt:**三种模式**(个股 / 策略组合 / 自由信号组合),真实约束(T+1 · 手续费 · 滑点 · 止损 · 最大持仓天数),组合管理(最大持仓 · 敞口 · 等权 / 自定义仓位)。SSE 流式进度支持切页重连,输出净值曲线 · 夏普 · 最大回撤 · 胜率 · 交易明细。
|
||||
|
||||
### 📡 监控中心(Monitor)
|
||||
|
||||
**统一监控规则引擎** —— 一个页面管理所有类型的监控,实时推送 + 持久化触发记录:
|
||||
统一规则引擎,一个页面管理**四类监控**(策略 · 个股信号 · 价格涨跌 · 全市场异动):
|
||||
|
||||
- **四类监控**:策略监控 · 个股信号监控(选信号即加) · 个股价格/涨跌监控 · 全市场异动监控
|
||||
- **灵活条件**:多条件 AND/OR 组合 + 冷却期去重(防刷屏) + 严重级别(info/warn/critical)
|
||||
- **多入口配置**:监控中心页面新建规则 · 个股详情页「加监控」· 策略卡片一键开启
|
||||
- **实时 SSE 推送**:命中规则后右下角弹窗通知(可配声效) + 持久化到 `alerts.jsonl`
|
||||
- **触发记录**:时间倒序展示,支持按来源过滤 · 单条删除 · 清空 · 点击查看个股日K
|
||||
- **菜单未读徽标**:离开监控中心后有新触发,菜单显示未读数;进入页面后清零
|
||||
- 多条件 AND/OR + 冷却期去重 + 严重级别(info/warn/critical)
|
||||
- 多入口配置:监控中心新建 / 个股详情页「加监控」/ 策略卡片一键开启
|
||||
- 命中后右下角弹窗(可配声效)+ 持久化到 `alerts.jsonl`,菜单未读徽标
|
||||
- **触发记录详情**:每条记录展示命中的具体条件(如 `RSI>80`)与当前价位,一眼看清为何触发
|
||||
- **飞书 Webhook 推送**:全局一处配置飞书群机器人地址,启用推送的规则命中即推送到飞书群(支持签名校验);可在设置页设「默认推送渠道」,新建规则自动预填
|
||||
|
||||
### 🤖 AI 策略生成(可选)
|
||||
### 📈 个股分析(Beta)
|
||||
|
||||
- **自然语言 → 策略代码**:用一句话描述策略思路,LLM 读取 `docs/strategy-guide.md` 生成完整 Polars 策略文件
|
||||
- **沙箱约束**:生成代码经 `ast` 校验、限定 `import polars as pl`,避免逐行循环,优先向量化表达
|
||||
- **可插拔**:留空 AI 配置即跳过整个模块,不影响核心功能
|
||||
以「行情 + 关键价位」为主体的单标的决策页:
|
||||
|
||||
- **专用日 K 图表**:主图 + 成交量 + 滑块,默认近 6 个月
|
||||
- **9 类关键价位**(纯函数实时计算,毫秒级):压力支撑 · 成交密集区 · 枢轴点 · 前高前低 · Keltner 通道 · ATR 止损 · 缺口位 · 斐波那契 · 整数关口
|
||||
- **AI 四维分析**:技术 / 基本面 / 财务 / 消息面流式生成,实战派交易员视角
|
||||
|
||||
### 🧰 数据与扩展
|
||||
|
||||
- **多源数据**:日 K / 分钟 K / 指数 / 财务(利润 / 资产负债 / 现金流)/ 自选行情
|
||||
- **🔌 第三方数据接入(重点)** —— 内置数据源之外的数据也能用:
|
||||
- 支持 **Tushare** 等第三方数据源,通过 **HTTP 定时拉取**自动入库
|
||||
- 支持 **CSV / Excel 上传** · **JSON 写入**,自动 schema 发现与符号归一
|
||||
- **页面可视化配置**扩展数据表,无需改代码
|
||||
- 可接入**你自己的量化项目数据**,统一并入 DuckDB 查询面,与内置数据同台分析
|
||||
- **盘后定时管道**:APScheduler 15:30 CST 自动拉日 K + 重算 enriched 表 + 跑监控
|
||||
- **令牌桶限流**:适配各档位 rpm / batch 上限,批量合并 + 增量拉取,同一份数据多面板复用
|
||||
|
||||
---
|
||||
|
||||
## 🚀 快速开始
|
||||
|
||||
本项目**仅通过 Docker 部署**,无论是本地体验还是服务器部署都使用同一套镜像。
|
||||
|
||||
### 前置依赖
|
||||
|
||||
- [Docker](https://docs.docker.com/get-docker/)
|
||||
- Docker Compose(已随 Docker Desktop 自带,Linux 需单独安装)
|
||||
|
||||
### 启动
|
||||
|
||||
```bash
|
||||
cp .env.example .env # 按需填写 Key(留空即 Free 模式,可直接体验)
|
||||
docker compose up --build
|
||||
# 打开 http://localhost:3018
|
||||
```
|
||||
|
||||
### 运行测试
|
||||
|
||||
```bash
|
||||
# 运行后端全部测试(含回测引擎)
|
||||
docker compose run --rm test
|
||||
```
|
||||
|
||||
> 测试镜像已包含回测依赖,可直接运行 `backend/tests` 下的全部 pytest 用例。
|
||||
|
||||
---
|
||||
|
||||
## 🧭 第一次使用
|
||||
|
||||
1. 打开面板 → **设置 → 凭据与能力** → 点 **重新检测**,确认 Tier Label
|
||||
2. 点 **立即跑盘后管道** —— 拉日 K + 计算 enriched 表
|
||||
- **Free 用户**:只同步内置 DEMO_SYMBOLS(浦发 / 招商 / 茅台等 10 只)
|
||||
- **Starter+**:同步全 A 或根据数据源能力获取的 instruments 列表
|
||||
3. **自选**页:添加跟踪标的;点代码进 **K 线**页看蜡烛图 + 买卖点
|
||||
4. **选股**页:点任一内置策略卡片即时扫描;或用自定义信号组合条件
|
||||
5. **回测**页:选策略 / 信号 + 时间区间 → 跑回测 → 看净值 / 夏普 / 交易明细(SSE 实时进度)
|
||||
6. **监控中心**页:配置监控规则(策略/个股信号/价格/市场异动),盘中 SSE 实时弹窗通知 + 持久化触发记录;或在个股详情页点「加监控」快速添加
|
||||
|
||||
---
|
||||
|
||||
## 🏗️ 架构
|
||||
|
||||
### 技术栈
|
||||
|
||||
| 层 | 选型 |
|
||||
| :--- | :--- |
|
||||
| **后端** | FastAPI · Pydantic v2 · APScheduler · sse-starlette |
|
||||
| **数据** | Polars(计算)· DuckDB(查询)· Parquet(存储)· PyArrow |
|
||||
| **回测** | 自研 Polars/NumPy 撮合引擎 · vectorbt(可选依赖) |
|
||||
| **数据源** | A 股数据源 SDK(`tickflow[all]`) |
|
||||
| **AI**(可选) | OpenAI 兼容接口(DeepSeek / 通义 / Ollama 等) |
|
||||
| **前端** | React 18 · Vite · TypeScript · Tailwind CSS · Framer Motion · Tanstack Query · Lightweight Charts · ECharts · dnd-kit |
|
||||
| **部署** | Docker 两阶段构建,前端 dist 拷进后端镜像,**单容器** |
|
||||
|
||||
### 目录结构
|
||||
|
||||
```
|
||||
backend/app/
|
||||
├── api/ # FastAPI 路由(选股/回测/监控/数据/设置等)
|
||||
├── services/ # 业务服务(选股/行情/数据同步/告警存储等)
|
||||
├── strategy/ # 策略引擎(内置/自定义/AI生成/监控规则)
|
||||
├── indicators/ # Polars 指标流水线
|
||||
├── backtest/ # 自研回测引擎
|
||||
├── tickflow/ # 数据源 SDK 适配层
|
||||
└── jobs/ # 盘后定时管道任务
|
||||
|
||||
frontend/src/
|
||||
├── pages/ # 页面组件(Dashboard/Screener/Backtest/Monitor 等)
|
||||
├── components/ # 可复用组件(图表/表格/选股/监控等)
|
||||
└── lib/ # API 客户端/QueryKey/格式化工具等
|
||||
|
||||
data/ # 本地数据目录(Parquet 分区文件)
|
||||
├── kline_daily/ # 原始日 K
|
||||
├── kline_daily_enriched/ # 带指标日 K
|
||||
├── instruments/ # 标的维表
|
||||
├── financials/ # 财务数据
|
||||
├── ext_data/ # 用户扩展数据
|
||||
└── backtest_results/ # 回测结果
|
||||
```
|
||||
|
||||
### 数据流
|
||||
|
||||
```
|
||||
tickflow 数据源
|
||||
↓
|
||||
kline_sync / instrument_sync / index_sync / financial_sync
|
||||
↓
|
||||
Parquet 分区文件 (data/)
|
||||
↓
|
||||
DuckDB 内存视图
|
||||
↓
|
||||
Polars 内存缓存
|
||||
↓
|
||||
选股 / 回测 / 监控 / 行情服务
|
||||
↓
|
||||
FastAPI → React 前端
|
||||
```
|
||||
|
||||
### 档位能力体系
|
||||
|
||||
`tiers.yaml` 定义了 Free → Expert 五档能力,启动时自动探测真实可用能力:
|
||||
|
||||
| 档位 | 能力 |
|
||||
| :--- | :--- |
|
||||
| **none** | 无 Key,仅历史日 K(批量) |
|
||||
| **free** | 免费有效 Key,能力与 none 等价 |
|
||||
| **starter** | 实时行情、批量、标的池、除权因子 |
|
||||
| **pro** | 增加分钟 K、五档盘口 |
|
||||
| **expert** | 增加财务数据、WebSocket |
|
||||
|
||||
UI 会显示友好标签(如「≈ Pro」),未解锁的功能自动灰显。
|
||||
|
||||
### 安全
|
||||
|
||||
- `/api/*` 路径通过 `auth.py` 中间件校验访问令牌
|
||||
- 支持 `admin` / `user` 两种角色,管理员令牌可在 `.env` 中配置
|
||||
- AI 生成策略经 `ast` 安全校验,禁止 `open/exec/eval/os/sys/subprocess`,限定 `import polars as pl`
|
||||
- **TickFlow 多源数据**:日 K / 分钟 K / 指数 / 财务 / 实时行情
|
||||
- **🔌 第三方接入(重点)**:Tushare 等 HTTP 定时拉取 · CSV / Excel 上传 · JSON 写入,自动 schema 发现 + 符号归一,页面可视化配置,**可与自有量化项目数据并入 DuckDB 同台分析**
|
||||
- **盘后定时管道**:APScheduler 15:30 CST 自动拉日 K + 重算 enriched + 跑监控
|
||||
- **令牌桶限流**:适配各档位 rpm / batch,批量合并 + 增量拉取
|
||||
|
||||
---
|
||||
|
||||
## ⚙️ 配置
|
||||
|
||||
所有配置通过项目根目录的 `.env` 文件读取(复制 `.env.example` 开始)。配置也可在面板 **设置** 页面内修改。
|
||||
所有配置从根目录 `.env` 读取(复制 `.env.example` 开始),也可在面板 **设置** 页修改。
|
||||
|
||||
### 数据源
|
||||
|
||||
当前默认接入内置数据源提供的订阅制 A 股数据。**留空 `TICKFLOW_API_KEY` 即启用 Free 模式,无需注册即可体验**。
|
||||
### 数据源:TickFlow
|
||||
|
||||
```ini
|
||||
TICKFLOW_API_KEY= # 留空 = Free 模式;填入 Key = 按订阅档位解锁
|
||||
TICKFLOW_API_KEY= # 留空 = None 模式(历史日K免费);填 Key = 按订阅档位解锁
|
||||
```
|
||||
|
||||
> 系统启动时会自动探测你的真实能力集,UI 显示「≈ Pro」等友好标签。
|
||||
留空即 None 模式,通过 free-api 使用历史日 K(当日数据盘后 1-2 小时可用);免费注册 Key 后进 Free 模式,开启自选股实时监控。**实时行情按档位**:
|
||||
|
||||
### AI(可选):策略生成
|
||||
| 档位 | 实时能力 |
|
||||
| :------- | :--------------------------------------- |
|
||||
| Free | 自选页前 5 个标的实时监控(最低 6 秒刷新) |
|
||||
| Starter+ | 全市场实时行情 |
|
||||
| Pro | 分钟 K + 盘口 |
|
||||
| Expert | WebSocket + 财务数据 |
|
||||
|
||||
AI 模块用于「自然语言生成策略代码」。**所有配置留空即跳过 AI 功能,不影响核心使用**。支持任何 **OpenAI 兼容接口**:
|
||||
> 完整能力矩阵见 [tickflow.org/pricing](https://tickflow.org/pricing/),高等档位含较低档全部权益。
|
||||
|
||||
### AI(可选)
|
||||
|
||||
用于自然语言生成策略。**所有配置留空即跳过**,不影响核心功能。支持任意 OpenAI 兼容接口:
|
||||
|
||||
```ini
|
||||
AI_PROVIDER=openai_compat # openai_compat | ollama
|
||||
@@ -296,8 +257,6 @@ AI_MODEL=deepseek-chat
|
||||
AI_DAILY_TOKEN_BUDGET=500000 # 每日 token 预算上限
|
||||
```
|
||||
|
||||
> 切换 `AI_PROVIDER=ollama` 时无需 `AI_API_KEY`,适合本地部署大模型。
|
||||
|
||||
### 服务与数据
|
||||
|
||||
```ini
|
||||
@@ -305,50 +264,65 @@ HOST=0.0.0.0 # 监听地址
|
||||
PORT=3018 # 服务端口
|
||||
LOG_LEVEL=INFO # DEBUG | INFO | WARNING | ERROR
|
||||
DATA_DIR=./data # Parquet / DuckDB 数据存储目录
|
||||
ACCESS_UUID= # 访问控制 UUID(可选)
|
||||
ADMIN_TOKEN=admin # 管理员令牌
|
||||
```
|
||||
|
||||
### 访问密码
|
||||
|
||||
面板首次设置访问密码时,出于安全考虑**仅允许本机或内网访问**(防公网陌生人抢先设置锁死面板)。公网服务器部署有两种方式设首个密码:
|
||||
|
||||
1. **环境变量预置(推荐)** — 在 `.env` 填入 `AUTH_PASSWORD`,首次启动自动初始化(哈希后写入 `auth.json`,之后不再读取):
|
||||
```ini
|
||||
AUTH_PASSWORD=你的密码 # 至少 6 位;仅首次生效,已设过则不覆盖
|
||||
```
|
||||
2. **SSH 端口转发** — 本机执行 `ssh -L 3018:127.0.0.1:3018 用户@服务器IP`,浏览器开 `http://127.0.0.1:3018` 设密码
|
||||
|
||||
> 详细步骤与重置密码见 [docs/deploy-password.md](./docs/deploy-password.md)。设完密码后改密码走页面 UI(`设置 → 修改密码`)。
|
||||
|
||||
---
|
||||
|
||||
## 🏗️ 技术栈
|
||||
|
||||
| 层 | 选型 |
|
||||
| :----------- | :------------------------------------------------------------------------------------------------ |
|
||||
| **后端** | FastAPI · Pydantic v2 · APScheduler · sse-starlette |
|
||||
| **数据** | Polars(计算)· DuckDB(查询)· Parquet(存储) |
|
||||
| **回测** | vectorbt(全项目唯一 pandas 边界) |
|
||||
| **数据源** | [TickFlow](https://tickflow.org/auth/register?ref=V3KDKGXPEA) 官方 SDK 、其他数据源后续迭代实装 |
|
||||
| **AI**(可选) | OpenAI 兼容接口(DeepSeek / 通义 / Ollama 等) |
|
||||
| **前端** | React 18 · Vite · TypeScript · Tailwind · Tanstack Query · Lightweight Charts · ECharts · dnd-kit |
|
||||
| **部署** | Docker 两阶段构建,前端 dist 拷进后端镜像,**单容器** |
|
||||
|
||||
---
|
||||
|
||||
## 🗺️ 路线图
|
||||
|
||||
| Phase | 内容 | 状态 |
|
||||
| :--- | :--- | :--- |
|
||||
| **0** | 仓库骨架 / FastAPI 壳 / Vite + React SPA / Docker 一键起 | ✅ |
|
||||
| **1** | 能力探测 + Kline 同步 + K 线分析页 | ✅ |
|
||||
| **2** | Polars enriched 流水线 + Screener + 信号扫描 | ✅ |
|
||||
| **3** | 自研回测引擎 + T+1 + 手续费 + 止损 + max-hold | ✅ |
|
||||
| **4** | 监控引擎 + 告警规则 + Webhook + APScheduler 盘后定时 | ✅ |
|
||||
| **5** | 统一监控中心 + 四类监控规则 + 实时推送 + 持久化触发记录 + 声效通知 | ✅ |
|
||||
| :----- | :----------------------------------------------------------------- | :--- |
|
||||
| 0-1 | 仓库骨架 · FastAPI 壳 · 能力探测 · K 线同步与分析页 | ✅ |
|
||||
| 2-3 | Polars enriched 流水线 · Screener · vectorbt 回测(T+1/手续费/止损) | ✅ |
|
||||
| 4-5 | 监控引擎 · 四类监控规则 · 实时 SSE 推送 · 持久化记录 | ✅ |
|
||||
| 6 | 个股分析(专用日 K + 9 类关键价位 + AI 四维分析) | ✅ |
|
||||
| **v2** | Webhook 推送(QMT/掘金下单)· 板块异动 · 早晚报 · 更多扩展 | 🚧 |
|
||||
|
||||
---
|
||||
|
||||
## 📚 文档
|
||||
## 📚 文档与贡献
|
||||
|
||||
- [docs/strategy-guide.md](./docs/strategy-guide.md) —— 策略开发指南(AI 生成器与手写策略的规范)
|
||||
- [docs/strategy-example.md](./docs/strategy-example.md) —— 策略示例
|
||||
- [docs/strategy-builder-step1.md](./docs/strategy-builder-step1.md) / [step2.md](./docs/strategy-builder-step2.md) —— 策略构建步骤
|
||||
- [docs/strategy-guide.md](./docs/strategy-guide.md) —— 策略开发指南(AI 生成与手写规范)
|
||||
- [docs/](./docs) —— 策略构建步骤、示例
|
||||
|
||||
---
|
||||
|
||||
## 🤝 贡献
|
||||
|
||||
欢迎 Issue 和 PR。请通过 Docker 进行本地验证:
|
||||
|
||||
```bash
|
||||
# 启动应用
|
||||
docker compose up --build -d
|
||||
|
||||
# 运行测试
|
||||
docker compose run --rm test
|
||||
```
|
||||
|
||||
新增内置策略:在 `backend/app/strategy/builtin/` 参照现有策略文件,实现 `StrategyDef` 即可被引擎自动发现。
|
||||
欢迎 Issue 和 PR。新增内置策略:在 `backend/app/strategy/builtin/` 参照现有文件实现 `StrategyDef`,引擎自动发现。
|
||||
|
||||
---
|
||||
|
||||
## ⚠️ 免责声明
|
||||
|
||||
本项目仅供**学习与量化研究**,**不构成任何投资建议**。回测结果不代表未来收益。A 股有风险,入市需谨慎。数据准确性以数据源官方为准。
|
||||
本项目仅供**学习与量化研究**,**不构成任何投资建议**。回测结果不代表未来收益。A 股有风险,入市需谨慎。数据准确性以数据源 TickFlow 官方为准。
|
||||
|
||||
## 📄 License
|
||||
|
||||
[MIT](./LICENSE) © tickflow-stock-panel contributors · 本项目依赖 [TickFlow](https://tickflow.org/auth/register?ref=V3KDKGXPEA) 提供数据服务,使用前请遵守其服务条款。
|
||||
|
||||
## 社区
|
||||
|
||||
本开源项目已链接并认可 [LINUX DO 社区](https://linux.do)。
|
||||
|
||||
+1
-1
@@ -1 +1 @@
|
||||
v1.0.0
|
||||
v0.1.64
|
||||
|
||||
@@ -1,10 +1,10 @@
|
||||
"""Stock Panel backend."""
|
||||
"""TickFlow Stock Panel backend."""
|
||||
|
||||
import sys
|
||||
|
||||
__version__ = "0.1.44"
|
||||
__version__ = "0.1.70"
|
||||
|
||||
# Windows 默认 stdout/stderr 编码为 GBK(cp936),数据源 SDK 内部输出含 emoji 的
|
||||
# Windows 默认 stdout/stderr 编码为 GBK(cp936),TickFlow SDK 内部输出含 emoji 的
|
||||
# 指数/标的名称(如 \U0001f193)时会抛 UnicodeEncodeError,导致请求失败。
|
||||
# 进程加载最早阶段强制 UTF-8,根治此类编码崩溃。
|
||||
for _stream in (sys.stdout, sys.stderr):
|
||||
|
||||
@@ -9,8 +9,6 @@ from typing import Literal
|
||||
from fastapi import APIRouter, HTTPException, Request
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from app.services.ext_data import ExtConfigStore
|
||||
|
||||
router = APIRouter(prefix="/api/analysis-menus", tags=["analysis-menus"])
|
||||
|
||||
|
||||
@@ -113,44 +111,13 @@ def _save(request: Request, menu: AnalysisMenu) -> AnalysisMenu:
|
||||
|
||||
|
||||
def _default_menus(request: Request) -> list[AnalysisMenu]:
|
||||
ext_store = ExtConfigStore(_data_dir(request))
|
||||
menus: list[AnalysisMenu] = []
|
||||
for cfg in ext_store.load_all():
|
||||
fields = cfg.fields
|
||||
concept = next((f for f in fields if "概念" in f.name or "概念" in f.label or "concept" in f.name.lower()), None)
|
||||
if concept:
|
||||
detail_names = ["股票简称", "股票代码", concept.name, "人气排名", "资金流向", "PE", "PB"]
|
||||
detail_columns = []
|
||||
for name in detail_names:
|
||||
f = next((x for x in fields if x.name == name), None)
|
||||
if not f:
|
||||
continue
|
||||
is_num = f.dtype in ("int", "float")
|
||||
detail_columns.append(AnalysisColumn(
|
||||
field=f.name,
|
||||
label=f.label or f.name,
|
||||
type="number" if is_num else "string",
|
||||
sortable=is_num,
|
||||
precision=2 if f.dtype == "float" else None,
|
||||
))
|
||||
menus.append(AnalysisMenu(
|
||||
id="concept_analysis",
|
||||
label="概念分析",
|
||||
icon="tags",
|
||||
data_source=cfg.id,
|
||||
template="dimension_rank",
|
||||
dimension_field=concept.name,
|
||||
group_columns=[
|
||||
AnalysisColumn(field="__dimension", label="概念"),
|
||||
AnalysisColumn(field="__count", label="股票数", type="number", sortable=True),
|
||||
],
|
||||
detail_columns=detail_columns,
|
||||
default_sort=DefaultSort(field="人气排名", order="asc") if any(c.field == "人气排名" for c in detail_columns) else None,
|
||||
order=100,
|
||||
builtin=True,
|
||||
))
|
||||
break
|
||||
return menus
|
||||
"""自动生成的默认分析菜单。
|
||||
|
||||
历史上会扫描扩展数据配置,对含「概念」字段的表自动生成一个「概念分析」菜单。
|
||||
现已关闭自动生成 —— 内置的概念分析页(/concept-analysis)已覆盖该场景,
|
||||
自动菜单会造成导航重复。需要时用户可在「设置 → 扩展页面」手动创建。
|
||||
"""
|
||||
return []
|
||||
|
||||
|
||||
@router.get("")
|
||||
|
||||
+192
-59
@@ -1,80 +1,213 @@
|
||||
"""访问门控 API 与管理接口。"""
|
||||
"""访问认证 API。
|
||||
|
||||
端点:
|
||||
GET /api/auth/status — 是否已设密码、当前会话是否有效
|
||||
POST /api/auth/setup — 首次设置密码(仅限本机/内网, 防公网抢占)
|
||||
POST /api/auth/login — 登录(密码 → 会话 token, 含限流)
|
||||
POST /api/auth/logout — 注销当前会话
|
||||
POST /api/auth/change-password — 改密码(需已登录)
|
||||
|
||||
安全:
|
||||
- setup 端点只接受本机/内网请求(request.client.host), 公网请求 403。
|
||||
否则黑客可比用户更早扫到域名, 抢先设密码, 反客为主。
|
||||
- login 限流: 同一来源 IP 连续失败 5 次, 锁 5 分钟(内存计数)。
|
||||
- 会话 token 通过 HttpOnly cookie 下发, 前端无需手动管理。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
from fastapi import APIRouter, Request
|
||||
import logging
|
||||
import time
|
||||
from collections import defaultdict
|
||||
from threading import Lock
|
||||
|
||||
from app import auth
|
||||
from app import uuid_store
|
||||
from fastapi import APIRouter, HTTPException, Request, Response
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from app.services import auth
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(prefix="/api/auth", tags=["auth"])
|
||||
admin_router = APIRouter(prefix="/api/admin", tags=["admin"])
|
||||
|
||||
COOKIE_NAME = "tf_session"
|
||||
_COOKIE_MAX_AGE = 30 * 24 * 3600 # 与 SESSION_TTL 一致
|
||||
|
||||
# 限流: { ip: (fail_count, lock_until_ts) }
|
||||
_fail_counter: dict[str, tuple[int, float]] = defaultdict(lambda: (0, 0.0))
|
||||
_fail_lock = Lock()
|
||||
_MAX_FAILS = 5
|
||||
_LOCK_SECONDS = 300
|
||||
|
||||
|
||||
@router.post("/verify")
|
||||
def verify_credential(req: auth.VerifyIn) -> auth.VerifyOut:
|
||||
"""校验管理员令牌或普通 UUID,成功后返回访问令牌及角色。"""
|
||||
role = auth.verify_credential(req.credential)
|
||||
if role:
|
||||
token = auth.create_access_token(role)
|
||||
return auth.VerifyOut(valid=True, role=role.value, token=token)
|
||||
return auth.VerifyOut(valid=False, role=None, token=None)
|
||||
def _is_local_network(host: str | None) -> bool:
|
||||
"""是否本机或内网请求。
|
||||
|
||||
反向代理(Nginx)场景下 request.client.host 是代理本身(127.0.0.1),
|
||||
需信任 X-Forwarded-For 的最左(原始客户端)。本项目部署若经反代,
|
||||
请在反代配置正确的 X-Forwarded-For(标准做法)。
|
||||
"""
|
||||
if not host:
|
||||
return False
|
||||
if host in ("127.0.0.1", "::1", "localhost"):
|
||||
return True
|
||||
# 内网网段: 10.x / 172.16-31.x / 192.168.x
|
||||
if host.startswith("10.") or host.startswith("192.168."):
|
||||
return True
|
||||
if host.startswith("172."):
|
||||
try:
|
||||
second = int(host.split(".")[1])
|
||||
if 16 <= second <= 31:
|
||||
return True
|
||||
except (IndexError, ValueError):
|
||||
pass
|
||||
return False
|
||||
|
||||
|
||||
def _client_ip(request: Request) -> str:
|
||||
"""取真实客户端 IP(信任反代 X-Forwarded-For)。"""
|
||||
xff = request.headers.get("x-forwarded-for")
|
||||
if xff:
|
||||
return xff.split(",")[0].strip()
|
||||
return request.client.host if request.client else "unknown"
|
||||
|
||||
|
||||
def _check_login_rate_limit(ip: str) -> None:
|
||||
"""登录失败限流检查, 触发则抛 429。"""
|
||||
with _fail_lock:
|
||||
count, until = _fail_counter.get(ip, (0, 0.0))
|
||||
now = time.time()
|
||||
if until > now:
|
||||
wait = int(until - now)
|
||||
raise HTTPException(
|
||||
status_code=429,
|
||||
detail=f"登录失败次数过多, 请 {wait} 秒后重试",
|
||||
)
|
||||
|
||||
|
||||
def _record_login_fail(ip: str) -> None:
|
||||
"""记录一次登录失败, 达阈值则锁定。"""
|
||||
with _fail_lock:
|
||||
count, until = _fail_counter.get(ip, (0, 0.0))
|
||||
count += 1
|
||||
if count >= _MAX_FAILS:
|
||||
until = time.time() + _LOCK_SECONDS
|
||||
logger.warning("auth login locked for %s after %d fails", ip, count)
|
||||
_fail_counter[ip] = (count, until)
|
||||
|
||||
|
||||
def _clear_login_fails(ip: str) -> None:
|
||||
"""登录成功后清除该 IP 的失败计数。"""
|
||||
with _fail_lock:
|
||||
_fail_counter.pop(ip, None)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 端点
|
||||
# ================================================================
|
||||
|
||||
class PasswordIn(BaseModel):
|
||||
password: str = Field(min_length=6, max_length=128)
|
||||
|
||||
|
||||
class LoginIn(BaseModel):
|
||||
password: str = Field(min_length=1, max_length=128)
|
||||
|
||||
|
||||
class ChangePasswordIn(BaseModel):
|
||||
old_password: str = Field(min_length=1, max_length=128)
|
||||
new_password: str = Field(min_length=6, max_length=128)
|
||||
|
||||
|
||||
@router.get("/status")
|
||||
def auth_status(request: Request) -> auth.AuthStatusOut:
|
||||
"""返回当前门控状态、当前请求是否通过校验及角色。"""
|
||||
enabled = auth.access_control_enabled()
|
||||
token = auth.get_access_token_from_request(request)
|
||||
role = auth.validate_access_token(token)
|
||||
return auth.AuthStatusOut(
|
||||
enabled=enabled,
|
||||
verified=role is not None,
|
||||
role=role.value if role else None,
|
||||
def auth_status(request: Request) -> dict:
|
||||
"""认证状态: 是否已设密码 + 当前请求是否已登录。"""
|
||||
token = request.cookies.get(COOKIE_NAME)
|
||||
return {
|
||||
"configured": auth.is_configured(),
|
||||
"authenticated": bool(token and auth.is_valid_session(token)),
|
||||
}
|
||||
|
||||
|
||||
@router.post("/setup")
|
||||
def setup_password(req: PasswordIn, request: Request) -> dict:
|
||||
"""首次设置访问密码。仅限本机/内网请求(防公网抢占)。
|
||||
|
||||
若已设置过密码, 返回 409(改密码走 /change-password)。
|
||||
"""
|
||||
# 关键: 限制只有服务器主人(本机/内网)能设密码
|
||||
client_ip = _client_ip(request)
|
||||
if not _is_local_network(client_ip):
|
||||
logger.warning("setup rejected from non-local ip: %s", client_ip)
|
||||
raise HTTPException(
|
||||
status_code=403,
|
||||
detail="首次设置密码仅允许本机或内网访问,请通过 SSH/本地浏览器操作",
|
||||
)
|
||||
|
||||
if auth.is_configured():
|
||||
raise HTTPException(status_code=409, detail="密码已设置,如需修改请登录后使用改密码功能")
|
||||
|
||||
# ===== 管理员 UUID 管理 =====
|
||||
auth.set_password(req.password)
|
||||
logger.info("access password set up from %s", client_ip)
|
||||
return {"ok": True, "configured": True}
|
||||
|
||||
@admin_router.get("/uuids")
|
||||
def list_uuids(request: Request) -> list[auth.UuidRecordOut]:
|
||||
"""列出所有动态 UUID(仅管理员)。"""
|
||||
auth.require_admin(request)
|
||||
records = uuid_store.list_uuids()
|
||||
return [
|
||||
auth.UuidRecordOut(
|
||||
uuid=r["uuid"],
|
||||
label=r.get("label", ""),
|
||||
enabled=r.get("enabled", True),
|
||||
created_at=r.get("created_at", 0),
|
||||
|
||||
@router.post("/login")
|
||||
def login(req: LoginIn, request: Request, response: Response) -> dict:
|
||||
"""登录: 密码 → 会话 token(写 HttpOnly cookie)。含失败限流。"""
|
||||
ip = _client_ip(request)
|
||||
_check_login_rate_limit(ip)
|
||||
|
||||
if not auth.is_configured():
|
||||
raise HTTPException(status_code=409, detail="尚未设置访问密码")
|
||||
|
||||
token = auth.verify_and_create_session(req.password)
|
||||
if not token:
|
||||
_record_login_fail(ip)
|
||||
raise HTTPException(status_code=401, detail="密码错误")
|
||||
|
||||
_clear_login_fails(ip)
|
||||
# HttpOnly: 防 XSS 窃取; SameSite=Lax: 防 CSRF; Path=/: 全站生效
|
||||
response.set_cookie(
|
||||
key=COOKIE_NAME,
|
||||
value=token,
|
||||
max_age=_COOKIE_MAX_AGE,
|
||||
httponly=True,
|
||||
samesite="lax",
|
||||
path="/",
|
||||
secure=False, # 自托管可能无 HTTPS, 不强制 secure(建议反代加 HTTPS)
|
||||
)
|
||||
for r in records
|
||||
]
|
||||
return {"ok": True, "authenticated": True}
|
||||
|
||||
|
||||
@admin_router.post("/uuids")
|
||||
def create_uuid(req: auth.UuidCreateIn, request: Request) -> auth.UuidRecordOut:
|
||||
"""创建新的访问 UUID(仅管理员)。"""
|
||||
auth.require_admin(request)
|
||||
record = uuid_store.create(req.label)
|
||||
return auth.UuidRecordOut(
|
||||
uuid=record["uuid"],
|
||||
label=record["label"],
|
||||
enabled=record["enabled"],
|
||||
created_at=record["created_at"],
|
||||
)
|
||||
@router.post("/logout")
|
||||
def logout(request: Request, response: Response) -> dict:
|
||||
"""注销当前会话。"""
|
||||
token = request.cookies.get(COOKIE_NAME)
|
||||
if token:
|
||||
auth.revoke_session(token)
|
||||
response.delete_cookie(key=COOKIE_NAME, path="/")
|
||||
return {"ok": True}
|
||||
|
||||
|
||||
@admin_router.delete("/uuids/{uuid}")
|
||||
def delete_uuid(uuid: str, request: Request) -> dict:
|
||||
"""删除访问 UUID(仅管理员)。"""
|
||||
auth.require_admin(request)
|
||||
ok = uuid_store.delete(uuid)
|
||||
return {"ok": ok}
|
||||
@router.post("/change-password")
|
||||
def change_password(req: ChangePasswordIn, request: Request) -> dict:
|
||||
"""修改密码: 需验证旧密码, 成功后所有会话失效(含当前, 需重新登录)。"""
|
||||
token = request.cookies.get(COOKIE_NAME)
|
||||
if not (token and auth.is_valid_session(token)):
|
||||
raise HTTPException(status_code=401, detail="请先登录")
|
||||
|
||||
if not auth.is_configured():
|
||||
raise HTTPException(status_code=409, detail="尚未设置访问密码")
|
||||
|
||||
@admin_router.put("/uuids/{uuid}/toggle")
|
||||
def toggle_uuid(uuid: str, request: Request, enabled: bool) -> dict:
|
||||
"""启用/禁用访问 UUID(仅管理员)。"""
|
||||
auth.require_admin(request)
|
||||
ok = uuid_store.toggle(uuid, enabled)
|
||||
return {"ok": ok}
|
||||
# 验证旧密码
|
||||
new_token = auth.verify_and_create_session(req.old_password)
|
||||
if not new_token:
|
||||
ip = _client_ip(request)
|
||||
_record_login_fail(ip)
|
||||
raise HTTPException(status_code=401, detail="旧密码错误")
|
||||
# 临时 token 用完即弃
|
||||
auth.revoke_session(new_token)
|
||||
|
||||
# 改密码(set_password 会清空所有会话)
|
||||
auth.set_password(req.new_password)
|
||||
return {"ok": True, "message": "密码已修改, 请重新登录"}
|
||||
|
||||
@@ -38,6 +38,9 @@ _table_cache: dict[str, dict | None] = {
|
||||
"index_daily": None,
|
||||
"index_enriched": None,
|
||||
"index_instruments": None,
|
||||
"etf_daily": None,
|
||||
"etf_enriched": None,
|
||||
"etf_instruments": None,
|
||||
"minute": None,
|
||||
"adj_factor": None,
|
||||
"instruments": None,
|
||||
@@ -262,6 +265,85 @@ def _safe_aggregate_index_instruments(repo) -> dict | None:
|
||||
}
|
||||
|
||||
|
||||
def _safe_aggregate_etf_instruments(repo) -> dict | None:
|
||||
"""ETF instruments 统计 — 优先独立 instruments_etf，兼容旧 instruments_index。"""
|
||||
queries = [
|
||||
"""SELECT count(*) AS rows,
|
||||
count(DISTINCT symbol) AS symbols,
|
||||
count_if(name IS NOT NULL AND name != '') AS named
|
||||
FROM instruments_etf""",
|
||||
"""SELECT count(*) AS rows,
|
||||
count(DISTINCT symbol) AS symbols,
|
||||
count_if(name IS NOT NULL AND name != '') AS named
|
||||
FROM instruments_index
|
||||
WHERE asset_type = 'etf'""",
|
||||
]
|
||||
for sql in queries:
|
||||
try:
|
||||
row = repo.execute_one(sql)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.debug("aggregate etf instruments fallback failed: %s", e)
|
||||
continue
|
||||
if row and row[0]:
|
||||
return {
|
||||
"rows": int(row[0]),
|
||||
"symbols_covered": int(row[1] or 0),
|
||||
"latest_as_of": None,
|
||||
"named": int(row[2] or 0),
|
||||
}
|
||||
return None
|
||||
|
||||
|
||||
def _safe_aggregate_etf_enriched(repo) -> dict | None:
|
||||
"""ETF enriched 统计 — 独立 kline_etf_enriched。"""
|
||||
fields = 0
|
||||
try:
|
||||
cols = repo.execute_all("DESCRIBE kline_etf_enriched")
|
||||
fields = len(cols)
|
||||
except Exception: # noqa: BLE001
|
||||
pass
|
||||
stats = _safe_aggregate(repo, "kline_etf_enriched")
|
||||
if not stats:
|
||||
return None
|
||||
return {**stats, "fields": fields}
|
||||
|
||||
|
||||
def _safe_aggregate_etf_daily(repo) -> dict | None:
|
||||
"""ETF 日K统计 — 优先独立 kline_etf_daily，兼容旧 index 存储。"""
|
||||
queries = [
|
||||
"""SELECT count(*) AS rows,
|
||||
min(date) AS earliest,
|
||||
max(date) AS latest,
|
||||
count(DISTINCT symbol) AS symbols,
|
||||
count(DISTINCT date) AS trading_days
|
||||
FROM kline_etf_daily""",
|
||||
"""SELECT count(*) AS rows,
|
||||
min(date) AS earliest,
|
||||
max(date) AS latest,
|
||||
count(DISTINCT symbol) AS symbols,
|
||||
count(DISTINCT date) AS trading_days
|
||||
FROM kline_index_daily
|
||||
WHERE symbol IN (
|
||||
SELECT DISTINCT symbol FROM instruments_index WHERE asset_type = 'etf'
|
||||
)""",
|
||||
]
|
||||
for sql in queries:
|
||||
try:
|
||||
row = repo.execute_one(sql)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.debug("aggregate etf daily fallback failed: %s", e)
|
||||
continue
|
||||
if row and row[0]:
|
||||
return {
|
||||
"rows": int(row[0]),
|
||||
"earliest_date": str(row[1]) if row[1] else None,
|
||||
"latest_date": str(row[2]) if row[2] else None,
|
||||
"symbols_covered": int(row[3] or 0),
|
||||
"trading_days": int(row[4] or 0),
|
||||
}
|
||||
return None
|
||||
|
||||
|
||||
def _safe_aggregate_adj_factor(repo) -> dict | None:
|
||||
"""adj_factor 视图统计,日期范围对齐日 K 覆盖区间。"""
|
||||
try:
|
||||
@@ -405,6 +487,10 @@ def _compute_storage(data_dir: Path) -> dict:
|
||||
"index_daily": data_dir / "kline_index_daily",
|
||||
"index_enriched": data_dir / "kline_index_enriched",
|
||||
"index_instruments": data_dir / "instruments_index",
|
||||
"etf_daily": data_dir / "kline_etf_daily",
|
||||
"etf_enriched": data_dir / "kline_etf_enriched",
|
||||
"etf_instruments": data_dir / "instruments_etf",
|
||||
"etf_adj_factor": data_dir / "adj_factor_etf",
|
||||
"minute": data_dir / "kline_minute",
|
||||
"adj_factor": data_dir / "adj_factor",
|
||||
"instruments": data_dir / "instruments",
|
||||
@@ -510,6 +596,9 @@ def status(request: Request) -> dict:
|
||||
"index_daily": _get_table_stats("index_daily", lambda: _safe_aggregate_index_daily(repo)),
|
||||
"index_enriched": _get_table_stats("index_enriched", lambda: _safe_aggregate_index_enriched(repo)),
|
||||
"index_instruments": _get_table_stats("index_instruments", lambda: _safe_aggregate_index_instruments(repo)),
|
||||
"etf_daily": _get_table_stats("etf_daily", lambda: _safe_aggregate_etf_daily(repo)),
|
||||
"etf_enriched": _get_table_stats("etf_enriched", lambda: _safe_aggregate_etf_enriched(repo)),
|
||||
"etf_instruments": _get_table_stats("etf_instruments", lambda: _safe_aggregate_etf_instruments(repo)),
|
||||
"minute": _get_table_stats("minute", lambda: _safe_aggregate_minute(repo)),
|
||||
"adj_factor": _get_table_stats("adj_factor", lambda: _safe_aggregate_adj_factor(repo)),
|
||||
"instruments": _get_table_stats("instruments", lambda: _safe_aggregate_instruments(repo)),
|
||||
@@ -537,8 +626,9 @@ def clear_data(request: Request):
|
||||
deleted = 0
|
||||
|
||||
for sub in (
|
||||
"kline_daily", "kline_daily_enriched", "kline_index_daily", "kline_index_enriched", "kline_minute",
|
||||
"adj_factor", "instruments", "instruments_index", "pools", "financials",
|
||||
"kline_daily", "kline_daily_enriched", "kline_index_daily", "kline_index_enriched",
|
||||
"kline_etf_daily", "kline_etf_enriched", "kline_etf_minute", "kline_minute",
|
||||
"adj_factor", "adj_factor_etf", "instruments", "instruments_index", "instruments_etf", "pools", "financials",
|
||||
"backtest_results", "screener_results", "ai_cache",
|
||||
):
|
||||
d = data_dir / sub
|
||||
@@ -596,10 +686,15 @@ def clear_data(request: Request):
|
||||
"kline_enriched": f"{d}/kline_daily_enriched/**/*.parquet",
|
||||
"kline_index_daily": f"{d}/kline_index_daily/**/*.parquet",
|
||||
"kline_index_enriched": f"{d}/kline_index_enriched/**/*.parquet",
|
||||
"kline_etf_daily": f"{d}/kline_etf_daily/**/*.parquet",
|
||||
"kline_etf_enriched": f"{d}/kline_etf_enriched/**/*.parquet",
|
||||
"kline_etf_minute": f"{d}/kline_etf_minute/**/*.parquet",
|
||||
"kline_minute": f"{d}/kline_minute/**/*.parquet",
|
||||
"adj_factor": f"{d}/adj_factor/**/*.parquet",
|
||||
"adj_factor_etf": f"{d}/adj_factor_etf/**/*.parquet",
|
||||
"instruments": f"{d}/instruments/**/*.parquet",
|
||||
"instruments_index": f"{d}/instruments_index/**/*.parquet",
|
||||
"instruments_etf": f"{d}/instruments_etf/**/*.parquet",
|
||||
}.items():
|
||||
try:
|
||||
repo.db.execute(
|
||||
@@ -638,6 +733,17 @@ _TABLE_FIELD_DESC: dict[str, dict[str, str]] = {
|
||||
"amount": "成交额",
|
||||
},
|
||||
"kline_index_enriched": ENRICHED_COLUMNS,
|
||||
"kline_etf_daily": {
|
||||
"symbol": "ETF代码",
|
||||
"date": "交易日期",
|
||||
"open": "开盘价",
|
||||
"high": "最高价",
|
||||
"low": "最低价",
|
||||
"close": "收盘价",
|
||||
"volume": "成交量",
|
||||
"amount": "成交额",
|
||||
},
|
||||
"kline_etf_enriched": ENRICHED_COLUMNS,
|
||||
"kline_minute": {
|
||||
"symbol": "股票代码",
|
||||
"datetime": "分钟时间戳",
|
||||
@@ -675,6 +781,13 @@ _TABLE_FIELD_DESC: dict[str, dict[str, str]] = {
|
||||
"code": "指数编码(纯数字)",
|
||||
"asset_type": "资产类型(index)",
|
||||
},
|
||||
"instruments_etf": {
|
||||
"symbol": "ETF代码",
|
||||
"name": "ETF名称",
|
||||
"code": "ETF编码(纯数字)",
|
||||
"asset_type": "资产类型(etf)",
|
||||
"source": "数据源",
|
||||
},
|
||||
}
|
||||
|
||||
# view 名 → DuckDB 视图名
|
||||
@@ -684,6 +797,9 @@ _SCHEMA_VIEWS: dict[str, str] = {
|
||||
"index_daily": "kline_index_daily",
|
||||
"index_enriched": "kline_index_enriched",
|
||||
"index_instruments": "instruments_index",
|
||||
"etf_daily": "kline_etf_daily",
|
||||
"etf_enriched": "kline_etf_enriched",
|
||||
"etf_instruments": "instruments_etf",
|
||||
"minute": "kline_minute",
|
||||
"adj_factor": "adj_factor",
|
||||
"instruments": "instruments",
|
||||
@@ -730,7 +846,7 @@ def get_version(request: Request) -> dict:
|
||||
"""
|
||||
from app import __version__
|
||||
|
||||
# 1. 优先用 app.__version__ (开发期 bump_version.py 写入)
|
||||
# 1. 优先用 app.__version__ (唯一权威版本, 打包期由 PyInstaller 注入)
|
||||
if __version__:
|
||||
v = __version__.strip()
|
||||
return {"version": v if v.startswith("v") else f"v{v}"}
|
||||
|
||||
@@ -325,6 +325,27 @@ def list_configs(request: Request):
|
||||
return {"items": items}
|
||||
|
||||
|
||||
@router.post("/presets/{config_id}/fetch")
|
||||
async def fetch_preset_data(request: Request, config_id: str):
|
||||
"""手动触发内置预设 (概念/行业) 的数据拉取。
|
||||
|
||||
注意: 必须在 /{config_id}/... 动态路由之前声明, 否则 'presets' 会被当成 config_id。
|
||||
与通用 pull/run 不同: 走 ext_presets 的结构转换 (接口的 concepts/industries
|
||||
数组 → 拼接成字符串), 保证 schema 与现有数据一致。
|
||||
"""
|
||||
from app.services.ext_presets import fetch_preset
|
||||
|
||||
try:
|
||||
n = await fetch_preset(config_id, _data_dir(request))
|
||||
except ValueError as e:
|
||||
raise HTTPException(404, str(e)) from e
|
||||
except Exception as e:
|
||||
raise HTTPException(400, f"拉取失败: {e}") from e
|
||||
|
||||
_refresh_views(request)
|
||||
return {"status": "ok", "rows": n}
|
||||
|
||||
|
||||
@router.post("")
|
||||
def create_config(request: Request, body: CreateExtReq):
|
||||
"""创建扩展数据配置。"""
|
||||
@@ -554,6 +575,13 @@ def configure_pull(request: Request, config_id: str, body: PullConfigReq):
|
||||
# 刷新调度器
|
||||
pull_scheduler.refresh(_data_dir(request))
|
||||
|
||||
# 关闭定时拉取时清理残留的 next_run, 避免前端展示一个永不执行的"下次"
|
||||
if not config.pull.enabled:
|
||||
cleared = store.get(config_id)
|
||||
if cleared and cleared.pull and cleared.pull.next_run:
|
||||
cleared.pull.next_run = None
|
||||
store.upsert(cleared)
|
||||
|
||||
return {"status": "ok", "pull": config.pull.to_dict()}
|
||||
|
||||
|
||||
@@ -609,8 +637,25 @@ async def run_pull(request: Request, config_id: str):
|
||||
try:
|
||||
n, d = await fetch_and_ingest(config, _data_dir(request))
|
||||
_refresh_views(request)
|
||||
# 写回执行状态, 让前端"上次执行"面板立即反映
|
||||
updated = store.get(config_id)
|
||||
if updated and updated.pull:
|
||||
from datetime import datetime, timezone
|
||||
updated.pull.last_run = datetime.now(timezone.utc).isoformat()
|
||||
updated.pull.last_status = "success"
|
||||
updated.pull.last_message = f"{n} rows @ {d}"
|
||||
updated.pull.last_rows = n
|
||||
store.upsert(updated)
|
||||
return {"status": "ok", "rows": n, "date": d}
|
||||
except Exception as e:
|
||||
# 失败也写回状态, 记录错误信息
|
||||
failed = store.get(config_id)
|
||||
if failed and failed.pull:
|
||||
from datetime import datetime, timezone
|
||||
failed.pull.last_run = datetime.now(timezone.utc).isoformat()
|
||||
failed.pull.last_status = "error"
|
||||
failed.pull.last_message = str(e)[:200]
|
||||
store.upsert(failed)
|
||||
raise HTTPException(400, f"拉取失败: {e}") from e
|
||||
|
||||
|
||||
|
||||
@@ -5,8 +5,12 @@ import logging
|
||||
|
||||
import polars as pl
|
||||
from fastapi import APIRouter, HTTPException, Request
|
||||
from fastapi.responses import StreamingResponse
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app.services.financial_sync import get_financial_df
|
||||
from app.services.financial_analyzer import analyze_financials_stream
|
||||
from app.services import ai_reports
|
||||
from app.tickflow.capabilities import Cap
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -109,7 +113,12 @@ def get_cash_flow(request: Request, symbol: str | None = None):
|
||||
|
||||
@router.post("/sync/{table}")
|
||||
def sync_table(request: Request, table: str):
|
||||
"""手动触发同步。table: metrics / income / balance_sheet / cash_flow / all"""
|
||||
"""手动触发同步(立即返回,后台异步执行)。
|
||||
|
||||
table: metrics / income / balance_sheet / cash_flow / all
|
||||
同步在后台线程执行,全量同步需数分钟。本接口立即返回 started 状态,
|
||||
前端通过轮询 GET /status 的 syncing 字段观察进度。
|
||||
"""
|
||||
capset = request.app.state.capabilities
|
||||
capset.require(Cap.FINANCIAL)
|
||||
|
||||
@@ -122,6 +131,87 @@ def sync_table(request: Request, table: str):
|
||||
return {"status": "error", "message": "FinancialScheduler not available"}
|
||||
|
||||
target = None if table == "all" else table
|
||||
result = fs.run_now(target)
|
||||
result = fs.trigger(target)
|
||||
|
||||
return {"status": "ok", "synced": result}
|
||||
|
||||
|
||||
class AnalyzeRequest(BaseModel):
|
||||
"""AI 财务分析请求。"""
|
||||
symbol: str
|
||||
focus: str = "" # 可选:用户追加的分析关注点
|
||||
|
||||
|
||||
@router.post("/analyze")
|
||||
async def analyze_financials(request: Request, req: AnalyzeRequest):
|
||||
"""AI 财务分析 — SSE 流式返回。
|
||||
|
||||
后端读取该标的 4 张财务表 → 注入 CFA 分析师级提示词 → 流式调用 LLM →
|
||||
逐 chunk 以 SSE 形式推给前端(JSON per line, 非 text/event-stream,
|
||||
以便前端用 ReadableStream 逐行解析,更简单可靠)。
|
||||
"""
|
||||
capset = request.app.state.capabilities
|
||||
capset.require(Cap.FINANCIAL)
|
||||
|
||||
if not req.symbol:
|
||||
raise HTTPException(400, "symbol 不能为空")
|
||||
|
||||
data_dir = request.app.state.repo.store.data_dir
|
||||
|
||||
async def stream_gen():
|
||||
async for chunk in analyze_financials_stream(data_dir, req.symbol, req.focus):
|
||||
yield chunk + "\n"
|
||||
|
||||
return StreamingResponse(
|
||||
stream_gen(),
|
||||
media_type="application/x-ndjson",
|
||||
headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
|
||||
)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# AI 报告 CRUD(历史报告持久化)
|
||||
# ================================================================
|
||||
|
||||
class SaveReportRequest(BaseModel):
|
||||
"""保存一条 AI 财务分析报告。"""
|
||||
symbol: str
|
||||
name: str = ""
|
||||
focus: str = ""
|
||||
content: str
|
||||
periods: int | None = None
|
||||
summary: str = ""
|
||||
|
||||
|
||||
@router.get("/reports")
|
||||
def list_reports(request: Request):
|
||||
"""获取全部历史报告(按时间降序,后端已裁剪到上限)。无需 FINANCIAL 能力读取列表元信息。"""
|
||||
capset = request.app.state.capabilities
|
||||
if not capset.has(Cap.FINANCIAL):
|
||||
return {"reports": []}
|
||||
return {"reports": ai_reports.list_reports()}
|
||||
|
||||
|
||||
@router.post("/reports")
|
||||
def save_report(request: Request, req: SaveReportRequest):
|
||||
"""保存一条报告。"""
|
||||
capset = request.app.state.capabilities
|
||||
capset.require(Cap.FINANCIAL)
|
||||
report = ai_reports.save_report({
|
||||
"symbol": req.symbol,
|
||||
"name": req.name,
|
||||
"focus": req.focus,
|
||||
"content": req.content,
|
||||
"periods": req.periods,
|
||||
"summary": req.summary,
|
||||
})
|
||||
return {"ok": True, "report": report}
|
||||
|
||||
|
||||
@router.delete("/reports/{report_id}")
|
||||
def delete_report(request: Request, report_id: str):
|
||||
"""删除一条报告。"""
|
||||
capset = request.app.state.capabilities
|
||||
capset.require(Cap.FINANCIAL)
|
||||
ok = ai_reports.delete_report(report_id)
|
||||
return {"ok": ok}
|
||||
|
||||
@@ -94,7 +94,7 @@ def get_index_daily(
|
||||
try:
|
||||
raw = kline_sync.sync_daily_batch([symbol], count=days + 150)
|
||||
except Exception as e: # noqa: BLE001
|
||||
raise HTTPException(status_code=502, detail=f"数据源 fetch failed: {e}") from e
|
||||
raise HTTPException(status_code=502, detail=f"TickFlow fetch failed: {e}") from e
|
||||
if raw.is_empty():
|
||||
return {"symbol": symbol, "name": info.get("name"), "index_info": info, "rows": [], "source": "none"}
|
||||
|
||||
|
||||
@@ -98,7 +98,7 @@ def index_quotes(
|
||||
request: Request,
|
||||
symbols: str | None = Query(None, description="逗号分隔的指数 symbol 列表"),
|
||||
):
|
||||
"""返回实时指数行情缓存，不触发数据源请求。"""
|
||||
"""返回实时指数行情缓存，不触发 TickFlow 请求。"""
|
||||
symbol_list = [s.strip() for s in symbols.split(",") if s.strip()] if symbols else None
|
||||
qs = _get_quote_service(request)
|
||||
if not qs:
|
||||
@@ -136,6 +136,9 @@ async def quote_stream(request: Request):
|
||||
"depth": asyncio.ensure_future(
|
||||
asyncio.to_thread(qs.wait_for_depth_update, timeout=5.0) if qs else asyncio.sleep(5)
|
||||
),
|
||||
"review": asyncio.ensure_future(
|
||||
asyncio.to_thread(qs.wait_for_review, timeout=5.0) if qs else asyncio.sleep(5)
|
||||
),
|
||||
}
|
||||
|
||||
done, pending = await asyncio.wait(
|
||||
@@ -160,6 +163,14 @@ async def quote_stream(request: Request):
|
||||
}, ensure_ascii=False),
|
||||
}
|
||||
|
||||
# 推送复盘进度 (定时复盘流式生成时) — 前端 reviewStore 直接消费
|
||||
# 事件已是 recap_market_stream 产出的 JSON 字符串, 逐条转发
|
||||
for evt_json in qs.pop_review_events():
|
||||
yield {
|
||||
"event": "review_progress",
|
||||
"data": evt_json,
|
||||
}
|
||||
|
||||
# 推送行情更新 (行情信号触发)
|
||||
if tasks["quote"] in done:
|
||||
try:
|
||||
|
||||
@@ -7,7 +7,7 @@ from typing import Optional
|
||||
|
||||
from fastapi import APIRouter, HTTPException, Query, Request
|
||||
|
||||
from app.indicators.pipeline import compute_enriched_single
|
||||
from app.indicators.pipeline import compute_enriched, compute_enriched_single
|
||||
from app.services import kline_sync
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -123,10 +123,19 @@ def get_daily(
|
||||
try:
|
||||
raw = kline_sync.sync_daily_batch([symbol], count=days + 30)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=502, detail=f"数据源 fetch failed: {e}") from e
|
||||
raise HTTPException(status_code=502, detail=f"TickFlow fetch failed: {e}") from e
|
||||
if raw.is_empty():
|
||||
return {"symbol": symbol, "name": stock_name, "stock_info": stock_info, "rows": []}
|
||||
enriched = compute_enriched_single(raw)
|
||||
# 拉除权因子做前复权 (Starter+ 有权限), 否则空 df → compute_enriched 退回未复权
|
||||
factors = pl.DataFrame()
|
||||
capset = getattr(request.app.state, "capabilities", None)
|
||||
try:
|
||||
from app.tickflow.capabilities import Cap
|
||||
if capset and capset.has(Cap.ADJ_FACTOR):
|
||||
factors = kline_sync.fetch_adj_factor_single(symbol)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.debug("单股除权因子拉取失败 %s: %s", symbol, e)
|
||||
enriched = compute_enriched(raw, factors=factors)
|
||||
rows = enriched.tail(days).to_dicts()
|
||||
# 即使 live 模式也尝试追加实时蜡烛
|
||||
rows = _maybe_inject_live_candle(request, symbol, rows)
|
||||
@@ -328,7 +337,7 @@ def get_minute(
|
||||
"""读取某只股票某天的分钟 K 线。
|
||||
|
||||
- 本地有完整数据(240条) → 直接返回
|
||||
- 本地无数据或不完整 → 从数据源实时拉取返回（不写入）
|
||||
- 本地无数据或不完整 → 从 TickFlow 实时拉取返回（不写入）
|
||||
"""
|
||||
repo = request.app.state.repo
|
||||
stock_info = _get_stock_info(repo, symbol)
|
||||
@@ -337,7 +346,7 @@ def get_minute(
|
||||
if trade_date is None:
|
||||
trade_date = repo.latest_minute_date(symbol)
|
||||
if trade_date is None:
|
||||
# 本地无任何分钟K，尝试从数据源拉取当天
|
||||
# 本地无任何分钟K，尝试从 TickFlow 拉取当天
|
||||
trade_date = date.today()
|
||||
df = kline_sync.fetch_minute_single(symbol, trade_date)
|
||||
return {
|
||||
@@ -373,7 +382,7 @@ def get_minute(
|
||||
"date": str(trade_date), "rows": df.to_dicts(), "source": "local",
|
||||
}
|
||||
|
||||
# 本地不完整或无数据 → 从数据源实时拉取
|
||||
# 本地不完整或无数据 → 从 TickFlow 实时拉取
|
||||
live_df = kline_sync.fetch_minute_single(symbol, trade_date)
|
||||
return {
|
||||
"symbol": symbol, "name": stock_name, "stock_info": stock_info,
|
||||
|
||||
@@ -0,0 +1,115 @@
|
||||
"""AI 大盘复盘 API — 流式复盘 + 报告持久化。
|
||||
|
||||
路由前缀: /api/market-recap
|
||||
|
||||
端点:
|
||||
POST /analyze AI 流式大盘复盘(NDJSON)
|
||||
GET /reports 历史复盘列表
|
||||
POST /reports 保存一条复盘报告
|
||||
DELETE /reports/{report_id} 删除一条复盘报告
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
|
||||
from fastapi import APIRouter, HTTPException, Request
|
||||
from fastapi.responses import StreamingResponse
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app.services import market_recap_reports
|
||||
from app.services.market_recap import recap_market_stream
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(prefix="/api/market-recap", tags=["market-recap"])
|
||||
|
||||
|
||||
class AnalyzeRequest(BaseModel):
|
||||
"""AI 大盘复盘请求。"""
|
||||
as_of: str | None = None # 可选:复盘日期(YYYY-MM-DD),缺省取最新有数据日
|
||||
focus: str = "" # 可选:用户追加的复盘关注点
|
||||
|
||||
|
||||
@router.post("/analyze")
|
||||
async def analyze_market(request: Request, req: AnalyzeRequest):
|
||||
"""AI 大盘复盘 — NDJSON 流式返回。
|
||||
|
||||
装配市场总览(指数/涨跌/连板/封板/板块/情绪雷达)→ 复盘提示词 →
|
||||
流式调用 LLM → 逐 chunk 以 NDJSON 推给前端(每行一个 JSON)。
|
||||
|
||||
协议:
|
||||
{"type":"meta","as_of","emotion_score","emotion_label","summary"}
|
||||
{"type":"delta","content":"..."}
|
||||
{"type":"error","message":"..."}
|
||||
{"type":"done"}
|
||||
"""
|
||||
from datetime import date as date_cls
|
||||
|
||||
repo = request.app.state.repo
|
||||
quote_service = getattr(request.app.state, "quote_service", None)
|
||||
depth_service = getattr(request.app.state, "depth_service", None)
|
||||
|
||||
as_of = None
|
||||
if req.as_of:
|
||||
try:
|
||||
as_of = date_cls.fromisoformat(req.as_of)
|
||||
except ValueError:
|
||||
raise HTTPException(400, f"as_of 格式应为 YYYY-MM-DD,收到: {req.as_of}")
|
||||
|
||||
async def stream_gen():
|
||||
async for chunk in recap_market_stream(repo, quote_service, depth_service, as_of, req.focus):
|
||||
yield chunk + "\n"
|
||||
|
||||
return StreamingResponse(
|
||||
stream_gen(),
|
||||
media_type="application/x-ndjson",
|
||||
headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
|
||||
)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 报告 CRUD(历史复盘持久化)
|
||||
# ================================================================
|
||||
|
||||
class SaveReportRequest(BaseModel):
|
||||
"""保存一条 AI 大盘复盘报告。"""
|
||||
as_of: str
|
||||
focus: str = ""
|
||||
content: str
|
||||
summary: str = ""
|
||||
emotion_score: int | None = None
|
||||
emotion_label: str = ""
|
||||
|
||||
|
||||
@router.get("/reports")
|
||||
def list_reports(request: Request):
|
||||
"""获取全部历史复盘(按时间降序,后端已裁剪到上限)。"""
|
||||
return {"reports": market_recap_reports.list_reports()}
|
||||
|
||||
|
||||
@router.post("/reports")
|
||||
def save_report(request: Request, req: SaveReportRequest):
|
||||
"""保存一条复盘报告。"""
|
||||
report = market_recap_reports.save_report({
|
||||
"as_of": req.as_of,
|
||||
"focus": req.focus,
|
||||
"content": req.content,
|
||||
"summary": req.summary,
|
||||
"emotion_score": req.emotion_score,
|
||||
"emotion_label": req.emotion_label,
|
||||
})
|
||||
# 推送到飞书(可选): 与定时复盘共用同一开关 review_push_enabled 与 _maybe_push_review。
|
||||
# 内部 try/except 静默降级, 不影响归档返回值。
|
||||
from app.jobs.daily_pipeline import _maybe_push_review
|
||||
_maybe_push_review(req.content, {
|
||||
"as_of": req.as_of,
|
||||
"emotion_label": req.emotion_label,
|
||||
})
|
||||
return {"ok": True, "report": report}
|
||||
|
||||
|
||||
@router.delete("/reports/{report_id}")
|
||||
def delete_report(request: Request, report_id: str):
|
||||
"""删除一条复盘报告。"""
|
||||
ok = market_recap_reports.delete_report(report_id)
|
||||
return {"ok": ok}
|
||||
@@ -47,9 +47,12 @@ class RuleModel(BaseModel):
|
||||
logic: str = "and" # and | or
|
||||
cooldown_seconds: int = 3600
|
||||
severity: str = "info" # info | warn | critical
|
||||
webhook_url: str = "" # Webhook 推送地址 (推送到 QMT 等外部软件, 开发中)
|
||||
webhook_url: str = "" # Webhook 推送地址 (推送到 QMT 等外部软件, 待定)
|
||||
webhook_enabled: bool = False
|
||||
message: str = ""
|
||||
# ladder 专属 (连板梯队封单监控)
|
||||
metric: str = "sealed_vol" # sealed_vol=封单量(手) | sealed_amount=封单额(元)
|
||||
threshold: float = 0 # 封单 <= 此值时报警 (原始单位: 量=手, 额=元)
|
||||
|
||||
|
||||
# ── 字段选项 ─────────────────────────────────────────────
|
||||
@@ -128,6 +131,16 @@ def list_rules(request: Request):
|
||||
@router.post("")
|
||||
def save_rule(req: RuleModel, request: Request):
|
||||
rule = monitor_rules.normalize(req.model_dump())
|
||||
# 连板梯队封单监控 (type=ladder) 依赖五档盘口数据, 需 Pro+ (DEPTH5_BATCH 能力)。
|
||||
# 无能力时拒绝创建, 避免规则存了却永远无法触发。
|
||||
if rule.get("type") == "ladder":
|
||||
from app.tickflow.capabilities import Cap
|
||||
capset = getattr(request.app.state, "capabilities", None)
|
||||
if capset is None or not capset.has(Cap.DEPTH5_BATCH):
|
||||
raise HTTPException(
|
||||
status_code=403,
|
||||
detail="封单监控需要 Pro+ 套餐 (批量五档能力),请升级后在「设置」页配置",
|
||||
)
|
||||
# 编辑现有规则时, 保留原 created_at (避免按时间排序时位置跳动)
|
||||
existing = monitor_rules.load_one(_data_dir(request), rule["id"])
|
||||
if existing and existing.get("created_at"):
|
||||
@@ -233,3 +246,254 @@ def seed_demo_rules(request: Request):
|
||||
i += 1
|
||||
_sync_engine(request)
|
||||
return {"ok": True, "generated": len(created), "ids": created}
|
||||
|
||||
|
||||
# ── 封单监控模拟触发 (Dev 调试用) ─────────────────────
|
||||
@router.post("/test-ladder")
|
||||
def test_ladder(request: Request):
|
||||
"""模拟触发所有 ladder 规则, 返回命中结果 (不落盘、不推送飞书)。
|
||||
|
||||
用当前 depth_service 的封单数据 + enriched 最新日 close 构造 mock DataFrame,
|
||||
跑 _evaluate_ladder 判断哪些规则会触发。供 Dev 页面调试验证。
|
||||
"""
|
||||
import polars as pl
|
||||
|
||||
repo = request.app.state.repo
|
||||
depth_svc = getattr(request.app.state, "depth_service", None)
|
||||
engine = getattr(request.app.state, "monitor_engine", None)
|
||||
|
||||
if not depth_svc:
|
||||
raise HTTPException(status_code=503, detail="depth 服务未初始化")
|
||||
if not engine or not engine.has_rule_type("ladder"):
|
||||
raise HTTPException(status_code=400, detail="无 ladder 类型监控规则")
|
||||
|
||||
# 最新交易日
|
||||
latest = repo.enriched_latest_date()
|
||||
if not latest:
|
||||
raise HTTPException(status_code=400, detail="无 enriched 数据")
|
||||
|
||||
# 取涨停+跌停封单 {symbol: vol}
|
||||
sealed: dict[str, int] = {}
|
||||
for is_down in (False, True):
|
||||
m = depth_svc.get_sealed_map(latest, is_down=is_down)
|
||||
for sym, info in m.items():
|
||||
vol = (info or {}).get("vol")
|
||||
if vol and vol > 0:
|
||||
sealed[sym] = vol
|
||||
|
||||
if not sealed:
|
||||
raise HTTPException(status_code=400, detail="无封单数据 (depth 未拉取或无涨停/跌停股)")
|
||||
|
||||
# 取这些 symbol 的 close (算封单额用)
|
||||
enriched_today, _ = repo.get_enriched_latest()
|
||||
cols = ["symbol", "close", "change_pct"]
|
||||
avail = [c for c in cols if c in enriched_today.columns]
|
||||
mock = enriched_today.select(avail).filter(pl.col("symbol").is_in(list(sealed.keys())))
|
||||
|
||||
# 注入 _sealed_vol
|
||||
sealed_df = pl.DataFrame({
|
||||
"symbol": list(sealed.keys()),
|
||||
"_sealed_vol": list(sealed.values()),
|
||||
})
|
||||
mock = mock.join(sealed_df, on="symbol", how="inner")
|
||||
|
||||
# 取所有 ladder 规则, 逐条纯条件判断 (绕过引擎 cooldown, 不污染 _last_fire)
|
||||
ladder_rules = [r for r in engine.rules.values() if r.get("type") == "ladder" and r.get("enabled", True)]
|
||||
all_events = []
|
||||
not_triggered = []
|
||||
|
||||
for rule in ladder_rules:
|
||||
syms = rule.get("symbols", [])
|
||||
sym = syms[0] if syms else None
|
||||
metric = rule.get("metric", "sealed_vol")
|
||||
thr = rule.get("threshold", 0)
|
||||
direction = rule.get("direction", "up")
|
||||
warn_label = "炸板预警" if direction == "up" else "翘板预警"
|
||||
|
||||
# 取该 symbol 的封单数据
|
||||
cur_vol = sealed.get(sym) if sym else None
|
||||
row = mock.filter(pl.col("symbol") == sym) if sym else mock.clear()
|
||||
cur_close = row["close"][0] if len(row) and "close" in row.columns else None
|
||||
cur_amt = (cur_vol * 100 * cur_close) if (cur_vol and cur_close) else None
|
||||
cur_val = cur_amt if metric == "sealed_amount" else cur_vol
|
||||
|
||||
# 条件判断: 封单 > 0 且 比较值 <= 阈值
|
||||
if cur_val is not None and cur_val > 0 and cur_val <= thr:
|
||||
if metric == "sealed_amount":
|
||||
sv_text = f"{cur_val / 1e4:.0f}万元"
|
||||
th_text = f"{thr / 1e4:.0f}万元"
|
||||
else:
|
||||
sv_text = f"{cur_val:,.0f} 手"
|
||||
th_text = f"{thr:,.0f} 手"
|
||||
all_events.append({
|
||||
"rule_id": rule["id"],
|
||||
"rule_name": rule.get("name", ""),
|
||||
"symbol": sym,
|
||||
"name": sym,
|
||||
"type": warn_label,
|
||||
"message": f"{warn_label} · 封单 {sv_text} ≤ {th_text}",
|
||||
"severity": rule.get("severity", "warn"),
|
||||
"sealed_value": cur_val,
|
||||
"sealed_metric": metric,
|
||||
"current_sealed_vol": cur_vol,
|
||||
"current_sealed_amount": cur_amt,
|
||||
})
|
||||
else:
|
||||
reason = "封单数据缺失" if cur_val is None else (
|
||||
f"封单 {cur_val:,.0f} > 阈值 {thr:,.0f}" if cur_val > thr else "封单为 0"
|
||||
)
|
||||
not_triggered.append({
|
||||
"rule_id": rule["id"],
|
||||
"rule_name": rule.get("name", ""),
|
||||
"symbol": sym,
|
||||
"metric": metric,
|
||||
"threshold": thr,
|
||||
"current_value": cur_val,
|
||||
"current_sealed_vol": cur_vol,
|
||||
"current_sealed_amount": cur_amt,
|
||||
"reason": reason,
|
||||
})
|
||||
|
||||
return {
|
||||
"ok": True,
|
||||
"as_of": str(latest),
|
||||
"sealed_count": len(sealed),
|
||||
"triggered": all_events,
|
||||
"not_triggered": not_triggered,
|
||||
}
|
||||
|
||||
|
||||
@router.post("/trigger-ladder")
|
||||
def trigger_ladder(request: Request):
|
||||
"""真实触发一次 ladder 预警 (落盘 + 飞书推送 + SSE), 供 Dev 调试验证完整效果。
|
||||
|
||||
与 test-ladder 区别: 本端点会真的把预警写入 alerts.jsonl、推送飞书、触发 SSE,
|
||||
让用户看到真实的预警通知。绕过 cooldown 强制触发。
|
||||
"""
|
||||
import time
|
||||
from app.services import alert_store
|
||||
|
||||
repo = request.app.state.repo
|
||||
depth_svc = getattr(request.app.state, "depth_service", None)
|
||||
engine = getattr(request.app.state, "monitor_engine", None)
|
||||
quote_svc = getattr(request.app.state, "quote_service", None)
|
||||
|
||||
if not depth_svc:
|
||||
raise HTTPException(status_code=503, detail="depth 服务未初始化")
|
||||
if not engine or not engine.has_rule_type("ladder"):
|
||||
raise HTTPException(status_code=400, detail="无 ladder 类型监控规则")
|
||||
|
||||
latest = repo.enriched_latest_date()
|
||||
if not latest:
|
||||
raise HTTPException(status_code=400, detail="无 enriched 数据")
|
||||
|
||||
# 取封单
|
||||
sealed: dict[str, int] = {}
|
||||
for is_down in (False, True):
|
||||
m = depth_svc.get_sealed_map(latest, is_down=is_down)
|
||||
for sym, info in m.items():
|
||||
vol = (info or {}).get("vol")
|
||||
if vol and vol > 0:
|
||||
sealed[sym] = vol
|
||||
if not sealed:
|
||||
raise HTTPException(status_code=400, detail="无封单数据")
|
||||
|
||||
# 构造真实 rule_events (与 _evaluate_ladder 产出格式一致)
|
||||
import polars as pl
|
||||
enriched_today, _ = repo.get_enriched_latest()
|
||||
cols = [c for c in ["symbol", "close", "change_pct"] if c in enriched_today.columns]
|
||||
mock = enriched_today.select(cols).filter(pl.col("symbol").is_in(list(sealed.keys())))
|
||||
sealed_df = pl.DataFrame({"symbol": list(sealed.keys()), "_sealed_vol": list(sealed.values())})
|
||||
mock = mock.join(sealed_df, on="symbol", how="inner")
|
||||
|
||||
now = time.time()
|
||||
rule_events: list[dict] = []
|
||||
name_map = {}
|
||||
try:
|
||||
inst = repo.get_instruments()
|
||||
if not inst.is_empty() and "name" in inst.columns:
|
||||
name_map = {r["symbol"]: r["name"] for r in inst.select(["symbol", "name"]).iter_rows(named=True) if r.get("name")}
|
||||
except Exception: # noqa: BLE001
|
||||
pass
|
||||
|
||||
for rule in engine.rules.values():
|
||||
if rule.get("type") != "ladder" or not rule.get("enabled", True):
|
||||
continue
|
||||
sym = rule.get("symbols", [""])[0] if rule.get("symbols") else ""
|
||||
metric = rule.get("metric", "sealed_vol")
|
||||
thr = rule.get("threshold", 0)
|
||||
direction = rule.get("direction", "up")
|
||||
warn_label = "炸板预警" if direction == "up" else "翘板预警"
|
||||
|
||||
row = mock.filter(pl.col("symbol") == sym)
|
||||
if row.is_empty():
|
||||
continue
|
||||
cur_vol = row["_sealed_vol"][0]
|
||||
close_v = row["close"][0] if "close" in row.columns else None
|
||||
cur_val = cur_vol * 100 * close_v if metric == "sealed_amount" else cur_vol
|
||||
if not cur_val or cur_val <= 0 or cur_val > thr:
|
||||
continue # 不满足条件, 跳过
|
||||
|
||||
if metric == "sealed_amount":
|
||||
sv_text = f"{cur_val / 1e4:.0f}万元"
|
||||
th_text = f"{thr / 1e4:.0f}万元"
|
||||
else:
|
||||
sv_text = f"{cur_val:,.0f} 手"
|
||||
th_text = f"{thr:,.0f} 手"
|
||||
|
||||
rule_events.append({
|
||||
"ts": int(now * 1000),
|
||||
"rule_id": rule["id"],
|
||||
"rule_name": rule.get("name", ""),
|
||||
"source": "ladder",
|
||||
"type": warn_label,
|
||||
"symbol": sym,
|
||||
"name": name_map.get(sym, sym),
|
||||
"message": f"{warn_label} · 封单 {sv_text} ≤ {th_text}",
|
||||
"price": close_v,
|
||||
"change_pct": row["change_pct"][0] if "change_pct" in row.columns else None,
|
||||
"signals": [],
|
||||
"severity": rule.get("severity", "warn"),
|
||||
"conditions": [],
|
||||
"logic": "and",
|
||||
"sealed_value": cur_val,
|
||||
"sealed_metric": metric,
|
||||
})
|
||||
|
||||
if not rule_events:
|
||||
raise HTTPException(status_code=400, detail="当前无 ladder 规则满足触发条件 (封单均 > 阈值)")
|
||||
|
||||
# 1. 落盘到 alerts.jsonl
|
||||
try:
|
||||
alert_store.append_many(repo.store.data_dir, rule_events)
|
||||
except Exception as e: # noqa: BLE001
|
||||
pass # 落盘失败不阻断推送
|
||||
|
||||
# 2. SSE 推送 (入 pending_alerts 队列)
|
||||
if quote_svc:
|
||||
sse_alerts = [{
|
||||
"source": ev["source"], "type": ev["type"], "rule_id": ev["rule_id"],
|
||||
"strategy_id": None, "symbol": ev["symbol"], "name": ev["name"],
|
||||
"message": ev["message"], "price": ev["price"], "change_pct": ev["change_pct"],
|
||||
"signals": ev["signals"], "severity": ev["severity"],
|
||||
"conditions": ev["conditions"], "logic": ev["logic"],
|
||||
} for ev in rule_events]
|
||||
try:
|
||||
with quote_svc._lock:
|
||||
quote_svc._pending_alerts.extend(sse_alerts)
|
||||
quote_svc._alert_event.set()
|
||||
except Exception: # noqa: BLE001
|
||||
pass
|
||||
|
||||
# 3. 飞书推送
|
||||
if quote_svc:
|
||||
try:
|
||||
quote_svc._maybe_send_webhook(rule_events, engine)
|
||||
except Exception: # noqa: BLE001
|
||||
pass
|
||||
|
||||
return {
|
||||
"ok": True,
|
||||
"triggered": len(rule_events),
|
||||
"events": [{"symbol": ev["symbol"], "name": ev["name"], "message": ev["message"]} for ev in rule_events],
|
||||
}
|
||||
|
||||
@@ -343,216 +343,18 @@ def _pct_band_rows(values: list[float]) -> list[dict]:
|
||||
|
||||
|
||||
def _build_overview(request: Request, as_of: date | None = None) -> dict:
|
||||
repo = request.app.state.repo
|
||||
svc = ScreenerService(repo)
|
||||
as_of = as_of or svc.latest_date()
|
||||
status = _quote_status(request)
|
||||
indices = _index_quotes(request, as_of)
|
||||
"""装配市场总览(委托给 services.market_overview_builder,保持行为一致)。
|
||||
|
||||
if not as_of:
|
||||
return {
|
||||
"as_of": None,
|
||||
"quote_status": status,
|
||||
"indices": indices,
|
||||
"breadth": {"total": 0, "up": 0, "down": 0, "flat": 0, "up_pct": 0, "down_pct": 0},
|
||||
"amount": {"total": 0, "avg": 0},
|
||||
"boards": [],
|
||||
"limit": {"limit_up": 0, "broken": 0, "failed": 0, "limit_down": 0, "max_boards": 0, "tiers": []},
|
||||
"distribution": [],
|
||||
"trend": {"above_ma5": 0, "above_ma20": 0, "above_ma60": 0, "above_ma5_pct": 0, "above_ma20_pct": 0, "above_ma60_pct": 0, "new_high": 0, "new_low": 0},
|
||||
"activity": {"avg_turnover": 0, "high_turnover": 0, "high_vol_ratio": 0, "vol_ratio": 1},
|
||||
"radar": [],
|
||||
"emotion": {"score": 50, "label": "暂无"},
|
||||
"top_gainers": [],
|
||||
"top_losers": [],
|
||||
"turnover_leaders": [],
|
||||
"active_leaders": [],
|
||||
"concept_rank": {"leading": [], "lagging": []},
|
||||
"industry_rank": {"leading": [], "lagging": []},
|
||||
}
|
||||
|
||||
df = svc._load_enriched_for_date(as_of)
|
||||
if df.is_empty():
|
||||
rows: list[dict] = []
|
||||
else:
|
||||
cols = [
|
||||
"symbol", "name", "close", "change_pct", "amount", "turnover_rate", "volume",
|
||||
"vol_ratio_5d", "consecutive_limit_ups", "signal_limit_up", "signal_broken_limit_up", "signal_limit_down",
|
||||
"ma5", "ma20", "ma60", "high_60d", "low_60d", "signal_n_day_high", "signal_n_day_low",
|
||||
]
|
||||
df = df.select([c for c in cols if c in df.columns])
|
||||
rows = df.to_dicts()
|
||||
|
||||
# 过滤真停牌（volume=0 且 change_pct=0），保留有涨跌幅的浮点误差股以对齐同花顺口径
|
||||
if rows and "volume" in rows[0]:
|
||||
rows = [r for r in rows
|
||||
if (_finite(r.get("volume")) or 0) > 0
|
||||
or (_finite(r.get("change_pct")) or 0) != 0]
|
||||
|
||||
total = len(rows)
|
||||
up = sum(1 for r in rows if (_finite(r.get("change_pct")) or 0) > 0)
|
||||
down = sum(1 for r in rows if (_finite(r.get("change_pct")) or 0) < 0)
|
||||
flat = max(0, total - up - down)
|
||||
up_pct = up / total * 100 if total else 0
|
||||
down_pct = down / total * 100 if total else 0
|
||||
|
||||
amounts = [_finite(r.get("amount")) or 0 for r in rows]
|
||||
total_amount = sum(amounts)
|
||||
avg_amount = total_amount / total if total else 0
|
||||
|
||||
pct_values = [_finite(r.get("change_pct")) for r in rows]
|
||||
pct_values = [v for v in pct_values if v is not None]
|
||||
avg_pct = sum(pct_values) / len(pct_values) if pct_values else 0
|
||||
median_pct = sorted(pct_values)[len(pct_values) // 2] if pct_values else 0
|
||||
strong_up = sum(1 for v in pct_values if v >= 0.03)
|
||||
strong_down = sum(1 for v in pct_values if v <= -0.03)
|
||||
|
||||
limit_up = sum(1 for r in rows if bool(r.get("signal_limit_up")) or (_finite(r.get("consecutive_limit_ups")) or 0) > 0)
|
||||
broken = sum(1 for r in rows if bool(r.get("signal_broken_limit_up")))
|
||||
limit_down = sum(1 for r in rows if bool(r.get("signal_limit_down")))
|
||||
max_boards = max([int(_finite(r.get("consecutive_limit_ups")) or 0) for r in rows], default=0)
|
||||
|
||||
# 五档 sealed 修正: 假涨停/假跌停不计入(需 Pro+ depth5.batch 能力)
|
||||
depth_svc = getattr(request.app.state, "depth_service", None)
|
||||
sealed_ready = False
|
||||
fake_up = 0
|
||||
fake_down = 0
|
||||
if depth_svc:
|
||||
up_map = depth_svc.get_sealed_map(as_of, is_down=False)
|
||||
down_map = depth_svc.get_sealed_map(as_of, is_down=True)
|
||||
sealed_ready = bool(up_map or down_map) and depth_svc.is_sealed_ready(as_of)
|
||||
if up_map:
|
||||
fake_up = sum(1 for v in up_map.values() if v.get("sealed") is False)
|
||||
if down_map:
|
||||
fake_down = sum(1 for v in down_map.values() if v.get("sealed") is False)
|
||||
if sealed_ready:
|
||||
limit_up = max(0, limit_up - fake_up)
|
||||
limit_down = max(0, limit_down - fake_down)
|
||||
|
||||
seal_rate = limit_up / (limit_up + broken) * 100 if (limit_up + broken) > 0 else 0
|
||||
|
||||
def above_ma_count(ma_key: str) -> int:
|
||||
return sum(1 for r in rows if (_finite(r.get("close")) is not None and _finite(r.get(ma_key)) is not None and (_finite(r.get("close")) or 0) >= (_finite(r.get(ma_key)) or 0)))
|
||||
|
||||
above_ma5 = above_ma_count("ma5")
|
||||
above_ma20 = above_ma_count("ma20")
|
||||
above_ma60 = above_ma_count("ma60")
|
||||
new_high = sum(1 for r in rows if bool(r.get("signal_n_day_high")) or (_finite(r.get("close")) is not None and _finite(r.get("high_60d")) is not None and (_finite(r.get("close")) or 0) >= (_finite(r.get("high_60d")) or 0)))
|
||||
new_low = sum(1 for r in rows if bool(r.get("signal_n_day_low")) or (_finite(r.get("close")) is not None and _finite(r.get("low_60d")) is not None and (_finite(r.get("close")) or 0) <= (_finite(r.get("low_60d")) or 0)))
|
||||
|
||||
turnovers = [_finite(r.get("turnover_rate")) for r in rows]
|
||||
turnovers = [v for v in turnovers if v is not None]
|
||||
avg_turnover = sum(turnovers) / len(turnovers) if turnovers else 0
|
||||
high_turnover = sum(1 for v in turnovers if v >= 5)
|
||||
|
||||
boards_map: dict[str, dict] = {}
|
||||
for r in rows:
|
||||
b = _board(str(r.get("symbol") or ""))
|
||||
item = boards_map.setdefault(b, {"board": b, "count": 0, "up": 0, "down": 0, "amount": 0.0})
|
||||
item["count"] += 1
|
||||
change = _finite(r.get("change_pct")) or 0
|
||||
if change > 0:
|
||||
item["up"] += 1
|
||||
elif change < 0:
|
||||
item["down"] += 1
|
||||
item["amount"] += _finite(r.get("amount")) or 0
|
||||
boards = sorted(boards_map.values(), key=lambda x: x["amount"], reverse=True)
|
||||
for b in boards:
|
||||
count = b["count"] or 1
|
||||
b["up_pct"] = b["up"] / count * 100
|
||||
|
||||
tiers_map: dict[int, int] = {}
|
||||
for r in rows:
|
||||
n = int(_finite(r.get("consecutive_limit_ups")) or 0)
|
||||
if n > 0:
|
||||
tiers_map[n] = tiers_map.get(n, 0) + 1
|
||||
tiers = [{"boards": k, "count": v} for k, v in sorted(tiers_map.items(), key=lambda item: -item[0])]
|
||||
|
||||
index_changes = [_finite(r.get("change_pct")) for r in indices]
|
||||
index_changes = [v for v in index_changes if v is not None]
|
||||
avg_index_pct = sum(index_changes) / len(index_changes) if index_changes else 0
|
||||
vol_ratios = [_finite(r.get("vol_ratio_5d")) for r in rows]
|
||||
vol_ratios = [v for v in vol_ratios if v is not None]
|
||||
avg_vol_ratio = sum(vol_ratios) / len(vol_ratios) if vol_ratios else 1
|
||||
high_vol_ratio = sum(1 for v in vol_ratios if v >= 1.5)
|
||||
|
||||
concept_rank = _dimension_rank(rows, request, "concept")
|
||||
industry_rank = _dimension_rank(rows, request, "industry", level=2)
|
||||
|
||||
strong_diff_pct = (strong_up - strong_down) / total * 100 if total else 0
|
||||
high_vol_pct = high_vol_ratio / total * 100 if total else 0
|
||||
strong_down_pct = strong_down / total * 100 if total else 0
|
||||
tier2_count = sum(t["count"] for t in tiers if t["boards"] >= 2)
|
||||
mainline_items = [*concept_rank["leading"][:3], *industry_rank["leading"][:3]]
|
||||
mainline_avg = max([_finite(item.get("avg_pct")) or 0 for item in mainline_items], default=0)
|
||||
mainline_cover_pct = max([(_finite(item.get("count")) or 0) / total * 100 for item in mainline_items], default=0) if total else 0
|
||||
mainline_score = round(_score(mainline_avg, -0.005, 0.03) * 0.65 + _score(mainline_cover_pct, 1, 12) * 0.35) if mainline_items else 50
|
||||
|
||||
radar = [
|
||||
{"key": "index", "label": "指数", "value": _score(avg_index_pct, -2.5, 2.5)},
|
||||
{"key": "profit", "label": "赚钱", "value": round(_score(up_pct, 20, 80) * 0.45 + _score(avg_pct, -0.02, 0.02) * 0.25 + _score(median_pct, -0.02, 0.02) * 0.20 + _score(strong_diff_pct, -8, 8) * 0.10)},
|
||||
{"key": "money", "label": "量能", "value": round(_score(avg_vol_ratio, 0.6, 1.8) * 0.70 + _score(high_vol_pct, 2, 12) * 0.30)},
|
||||
{"key": "speculation", "label": "投机", "value": round(_score(limit_up, 5, 90) * 0.25 + _score(seal_rate, 30, 85) * 0.35 + _score(max_boards, 1, 8) * 0.25 + _score(tier2_count, 0, 30) * 0.15)},
|
||||
{"key": "resilience", "label": "抗跌", "value": 100 - round(_score(down_pct, 20, 80) * 0.55 + _score(strong_down_pct, 1, 12) * 0.45)},
|
||||
{"key": "mainline", "label": "主线", "value": mainline_score},
|
||||
]
|
||||
emotion_score = round(sum(r["value"] for r in radar) / len(radar)) if radar else 50
|
||||
if emotion_score >= 70:
|
||||
emotion_label = "强势"
|
||||
elif emotion_score >= 55:
|
||||
emotion_label = "偏暖"
|
||||
elif emotion_score >= 45:
|
||||
emotion_label = "震荡"
|
||||
elif emotion_score >= 30:
|
||||
emotion_label = "偏冷"
|
||||
else:
|
||||
emotion_label = "冰点"
|
||||
|
||||
return _json_safe({
|
||||
"as_of": str(as_of),
|
||||
"quote_status": status,
|
||||
"indices": indices,
|
||||
"breadth": {
|
||||
"total": total,
|
||||
"up": up,
|
||||
"down": down,
|
||||
"flat": flat,
|
||||
"up_pct": up_pct,
|
||||
"down_pct": down_pct,
|
||||
"avg_pct": avg_pct,
|
||||
"median_pct": median_pct,
|
||||
"strong_up": strong_up,
|
||||
"strong_down": strong_down,
|
||||
},
|
||||
"amount": {"total": total_amount, "avg": avg_amount},
|
||||
"boards": boards,
|
||||
"limit": {"limit_up": limit_up, "broken": broken, "failed": 0, "limit_down": limit_down, "max_boards": max_boards, "seal_rate": seal_rate, "tiers": tiers, "sealed_ready": sealed_ready, "fake_up": fake_up, "fake_down": fake_down},
|
||||
"distribution": _pct_band_rows(pct_values),
|
||||
"trend": {
|
||||
"above_ma5": above_ma5,
|
||||
"above_ma20": above_ma20,
|
||||
"above_ma60": above_ma60,
|
||||
"above_ma5_pct": above_ma5 / total * 100 if total else 0,
|
||||
"above_ma20_pct": above_ma20 / total * 100 if total else 0,
|
||||
"above_ma60_pct": above_ma60 / total * 100 if total else 0,
|
||||
"new_high": new_high,
|
||||
"new_low": new_low,
|
||||
},
|
||||
"activity": {
|
||||
"avg_turnover": avg_turnover,
|
||||
"high_turnover": high_turnover,
|
||||
"high_vol_ratio": high_vol_ratio,
|
||||
"vol_ratio": avg_vol_ratio,
|
||||
},
|
||||
"radar": radar,
|
||||
"emotion": {"score": emotion_score, "label": emotion_label},
|
||||
"top_gainers": _top_rows(rows, "change_pct", True),
|
||||
"top_losers": _top_rows(rows, "change_pct", False),
|
||||
"turnover_leaders": _top_rows(rows, "amount", True),
|
||||
"active_leaders": _top_rows(rows, "turnover_rate", True),
|
||||
"concept_rank": concept_rank,
|
||||
"industry_rank": industry_rank,
|
||||
})
|
||||
逻辑已抽离至 build_market_overview,以解耦对 Request 的依赖,
|
||||
使大盘复盘等无 Request 的调用方可复用同一装配逻辑。
|
||||
"""
|
||||
from app.services.market_overview_builder import build_market_overview
|
||||
return build_market_overview(
|
||||
repo=request.app.state.repo,
|
||||
quote_service=getattr(request.app.state, "quote_service", None),
|
||||
depth_service=getattr(request.app.state, "depth_service", None),
|
||||
as_of=as_of,
|
||||
)
|
||||
|
||||
|
||||
@router.get("/market")
|
||||
|
||||
@@ -0,0 +1,67 @@
|
||||
"""涨幅轮动矩阵 API。
|
||||
|
||||
供「概念分析 → 涨幅RPS轮动」对话框调用。返回最近 N 个交易日的概念涨幅
|
||||
排名矩阵:每列(日期)各自把所有概念按当天涨幅从高到低排序。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
from fastapi import APIRouter, Query, Request
|
||||
from fastapi.responses import StreamingResponse
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app.services import rps_rotation
|
||||
from app.services.concept_rotation_analyzer import analyze_rotation_stream
|
||||
|
||||
router = APIRouter(prefix="/api/rps", tags=["rps"])
|
||||
|
||||
|
||||
@router.get("/rotation")
|
||||
def get_rotation(
|
||||
request: Request,
|
||||
days: int = Query(12, ge=7, le=30, description="最近 N 个交易日(7-30)"),
|
||||
) -> dict:
|
||||
"""概念涨幅轮动矩阵。
|
||||
|
||||
Returns:
|
||||
dates: 日期字符串列表(最新在最前)
|
||||
columns: {日期: [[概念名, 涨幅小数], ...]} 每列各自降序
|
||||
concept_count: 去重概念总数
|
||||
"""
|
||||
return rps_rotation.build_rps_rotation(request.app.state.repo, days)
|
||||
|
||||
|
||||
class AnalyzeRequest(BaseModel):
|
||||
"""AI 概念轮动分析请求。"""
|
||||
days: int = 12 # 分析最近 N 个交易日
|
||||
focus: str = "" # 用户追加的关注点
|
||||
|
||||
|
||||
@router.post("/rotation-analyze")
|
||||
async def analyze_rotation(request: Request, req: AnalyzeRequest):
|
||||
"""AI 概念轮动分析 — NDJSON 流式返回。
|
||||
|
||||
装配轮动矩阵信号 + 大盘背景 → 分析提示词 → 流式调用 LLM →
|
||||
逐 chunk 以 NDJSON 推给前端(每行一个 JSON)。
|
||||
|
||||
协议:
|
||||
{"type":"meta","days","summary"}
|
||||
{"type":"delta","content":"..."}
|
||||
{"type":"error","message":"..."}
|
||||
{"type":"done"}
|
||||
"""
|
||||
repo = request.app.state.repo
|
||||
quote_service = getattr(request.app.state, "quote_service", None)
|
||||
depth_service = getattr(request.app.state, "depth_service", None)
|
||||
days = max(7, min(30, req.days))
|
||||
|
||||
async def stream_gen():
|
||||
async for chunk in analyze_rotation_stream(
|
||||
repo, days, req.focus, quote_service, depth_service,
|
||||
):
|
||||
yield chunk + "\n"
|
||||
|
||||
return StreamingResponse(
|
||||
stream_gen(),
|
||||
media_type="application/x-ndjson",
|
||||
headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
|
||||
)
|
||||
@@ -278,11 +278,35 @@ def get_cached(
|
||||
request: Request,
|
||||
ext_columns: Optional[str] = Query(None, description="逗号分隔: config_id.field_name"),
|
||||
):
|
||||
"""读取策略结果缓存。返回 None 表示无缓存。"""
|
||||
"""读取策略结果缓存, 并叠加监控引擎本轮实时算出的结果。
|
||||
|
||||
- 盘后缓存 (strategy_cache.json): 非监控策略 / 页面秒加载用, run_all 写入。
|
||||
- 监控引擎内存结果 (latest_strategy_results): 实时行情每轮对「加入监控的策略」算出,
|
||||
不落盘 (避免与 read_cache 的 mtime 校验冲突), 在此直接叠加覆盖盘后结果。
|
||||
被监控的策略拿到新鲜数据, 非监控策略仍用盘后缓存。
|
||||
"""
|
||||
data_dir = request.app.state.repo.store.data_dir
|
||||
cached = strategy_cache.read_cache(data_dir)
|
||||
if cached is None:
|
||||
cached = {"as_of": None, "results": {}, "updated_at": None}
|
||||
|
||||
# 叠加监控引擎内存里的实时结果 (若有), 用新鲜数据覆盖同策略的盘后结果
|
||||
monitor_engine = getattr(request.app.state, "monitor_engine", None)
|
||||
if monitor_engine is not None:
|
||||
realtime_results = monitor_engine.latest_strategy_results()
|
||||
if realtime_results:
|
||||
results = dict(cached.get("results") or {})
|
||||
results.update(realtime_results)
|
||||
cached = dict(cached)
|
||||
cached["results"] = results
|
||||
# 有实时数据时, 以最新时间戳为准
|
||||
import time as _time
|
||||
cached["updated_at"] = int(_time.time() * 1000)
|
||||
|
||||
# 无任何数据 (盘后缓存空 + 无实时结果) → 返回空标记, 前端据此提示
|
||||
if not cached.get("results") and cached.get("as_of") is None:
|
||||
return {"as_of": None, "results": {}, "updated_at": None}
|
||||
|
||||
ext_values = _load_ext_value_maps(request.app.state.repo, ext_columns)
|
||||
return _cache_payload_with_ext(cached, ext_values)
|
||||
|
||||
|
||||
@@ -7,11 +7,10 @@ from __future__ import annotations
|
||||
import logging
|
||||
import time
|
||||
|
||||
from fastapi import APIRouter, Request
|
||||
from fastapi import APIRouter, HTTPException, Request
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app import secrets_store
|
||||
from app.services.financial_sync import financial_scheduler
|
||||
from app.tickflow import client as tf_client
|
||||
from app.tickflow.policy import (
|
||||
detect_capabilities,
|
||||
@@ -30,25 +29,34 @@ router = APIRouter(prefix="/api/settings", tags=["settings"])
|
||||
DEFAULT_PAID_ENDPOINT = "https://api.tickflow.org"
|
||||
|
||||
|
||||
def _sync_financial_scheduler_caps(app_state, capset) -> None:
|
||||
"""把重新探测出的能力同步给财务调度器。
|
||||
|
||||
app.state.capabilities 在此已更新, 但 FinancialScheduler 在启动时捕获的是旧引用,
|
||||
需显式刷新, 否则用户升级到 Expert 后点「全部同步」仍会因调度器读旧 capset 而被拒。
|
||||
"""
|
||||
fs = getattr(app_state, "financial_scheduler", None)
|
||||
if fs is None:
|
||||
return
|
||||
try:
|
||||
fs.update_capabilities(capset)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logging.getLogger(__name__).warning("update financial_scheduler capabilities failed: %s", e)
|
||||
|
||||
|
||||
class TickflowKeyIn(BaseModel):
|
||||
api_key: str
|
||||
|
||||
|
||||
def _sync_financial_scheduler(request: Request, capset) -> None:
|
||||
"""Key 变更后同步财务调度器状态,无需重启服务。"""
|
||||
try:
|
||||
financial_scheduler.update(request.app.state.repo.store.data_dir, capset)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("financial_scheduler update failed: %s", e)
|
||||
|
||||
|
||||
@router.get("")
|
||||
def get_settings() -> dict:
|
||||
"""返回当前配置概况(Key 脱敏)。"""
|
||||
from app.config import settings
|
||||
from app.services import preferences
|
||||
from app.services.ai_provider import ai_configured, current_ai_model, current_codex_command
|
||||
|
||||
key = secrets_store.get_tickflow_key()
|
||||
ai_provider = secrets_store.get_ai_config("ai_provider", settings.ai_provider)
|
||||
return {
|
||||
"mode": tf_client.current_mode(),
|
||||
"tickflow_api_key_masked": secrets_store.mask(key),
|
||||
@@ -61,12 +69,14 @@ def get_settings() -> dict:
|
||||
# 首次使用引导
|
||||
"onboarding_completed": preferences.get_onboarding_completed(),
|
||||
# AI 配置
|
||||
"ai_provider": secrets_store.get_ai_config("ai_provider", settings.ai_provider),
|
||||
"ai_provider": ai_provider,
|
||||
"ai_base_url": secrets_store.get_ai_config("ai_base_url", settings.ai_base_url),
|
||||
"ai_api_key_masked": secrets_store.mask(secrets_store.get_ai_key()),
|
||||
"has_ai_key": bool(secrets_store.get_ai_key()),
|
||||
"ai_model": secrets_store.get_ai_config("ai_model", settings.ai_model),
|
||||
"ai_daily_token_budget": int(secrets_store.get_ai_config("ai_daily_token_budget", str(settings.ai_daily_token_budget)) or settings.ai_daily_token_budget),
|
||||
"ai_configured": ai_configured(ai_provider),
|
||||
"ai_model": current_ai_model(),
|
||||
"ai_codex_command": current_codex_command(),
|
||||
"ai_user_agent": secrets_store.get_ai_config("ai_user_agent", settings.ai_user_agent),
|
||||
}
|
||||
|
||||
|
||||
@@ -76,9 +86,9 @@ class SwitchEndpointIn(BaseModel):
|
||||
|
||||
@router.post("/switch_endpoint")
|
||||
def switch_endpoint(req: SwitchEndpointIn, request: Request) -> dict:
|
||||
"""切换数据源端点并立即生效。
|
||||
"""切换 TickFlow 端点并立即生效。
|
||||
|
||||
端点切换仅对付费档(starter+,走付费 API 节点)有意义;
|
||||
端点切换仅对付费档(starter+,走 api.tickflow.org)有意义;
|
||||
none/free 档运行在 free-api 服务器,无付费端点权限,禁止切换。
|
||||
"""
|
||||
# none/free 档没有付费端点权限,禁止切换
|
||||
@@ -102,7 +112,7 @@ def switch_endpoint(req: SwitchEndpointIn, request: Request) -> dict:
|
||||
|
||||
@router.post("/tickflow-key")
|
||||
def save_tickflow_key(req: TickflowKeyIn, request: Request) -> dict:
|
||||
"""保存数据源 API Key 并立即重新探测能力。
|
||||
"""保存 TickFlow API Key 并立即重新探测能力。
|
||||
|
||||
先探后存(关键改动,修复乱填 key 也会被持久化的问题):
|
||||
1. 临时用新 key 探测(付费端点),判定档位
|
||||
@@ -112,7 +122,7 @@ def save_tickflow_key(req: TickflowKeyIn, request: Request) -> dict:
|
||||
4. 判定为 starter+ → 存 key,切到付费端点(现有逻辑)
|
||||
|
||||
端点联动:从无 key 升级到付费 key 时,残留的 free-api 端点不可用,
|
||||
故自动切到默认付费端点;free 档则清除自定义端点。
|
||||
故自动切到默认付费端点(api.tickflow.org);free 档则清除自定义端点。
|
||||
"""
|
||||
from app.tickflow.policy import (
|
||||
base_tier_name, is_invalid_key,
|
||||
@@ -129,7 +139,7 @@ def save_tickflow_key(req: TickflowKeyIn, request: Request) -> dict:
|
||||
# 立即重新探测(此时 client 已按档位判定,但首次探测必然走付费端点验证)
|
||||
capset = detect_capabilities(force=True)
|
||||
request.app.state.capabilities = capset
|
||||
_sync_financial_scheduler(request, capset)
|
||||
_sync_financial_scheduler_caps(request.app.state, capset)
|
||||
|
||||
# ===== 2) 判定为无效 key(连单只日K都拿不到)→ 不存,清除 =====
|
||||
if is_invalid_key() or base_tier_name() == "none":
|
||||
@@ -138,7 +148,7 @@ def save_tickflow_key(req: TickflowKeyIn, request: Request) -> dict:
|
||||
tf_client.reset_clients()
|
||||
capset = detect_capabilities(force=True)
|
||||
request.app.state.capabilities = capset
|
||||
_sync_financial_scheduler(request, capset)
|
||||
_sync_financial_scheduler_caps(request.app.state, capset)
|
||||
return {
|
||||
"ok": False,
|
||||
"reason": "invalid",
|
||||
@@ -195,7 +205,7 @@ def clear_tickflow_key(request: Request) -> dict:
|
||||
|
||||
capset = detect_capabilities(force=True)
|
||||
request.app.state.capabilities = capset
|
||||
_sync_financial_scheduler(request, capset)
|
||||
_sync_financial_scheduler_caps(request.app.state, capset)
|
||||
|
||||
return {
|
||||
"ok": True,
|
||||
@@ -223,13 +233,15 @@ class AiSettingsIn(BaseModel):
|
||||
base_url: str = ""
|
||||
api_key: str | None = None
|
||||
model: str = ""
|
||||
daily_token_budget: int = 500_000
|
||||
codex_command: str = ""
|
||||
user_agent: str = ""
|
||||
|
||||
|
||||
@router.post("/ai")
|
||||
def save_ai_settings(req: AiSettingsIn) -> dict:
|
||||
"""保存 AI 配置（全部持久化到 secrets.json）"""
|
||||
from app.config import settings
|
||||
from app.services.ai_provider import ai_configured, current_ai_model, current_ai_provider, current_codex_command, normalize_codex_command
|
||||
|
||||
updates: dict = {}
|
||||
if req.provider:
|
||||
@@ -245,15 +257,52 @@ def save_ai_settings(req: AiSettingsIn) -> dict:
|
||||
else:
|
||||
secrets_store.clear("ai_api_key")
|
||||
settings.ai_api_key = ""
|
||||
if req.model:
|
||||
if req.provider == "codex_cli" and not req.model:
|
||||
secrets_store.clear("ai_model")
|
||||
settings.ai_model = ""
|
||||
elif req.model:
|
||||
updates["ai_model"] = req.model
|
||||
settings.ai_model = req.model
|
||||
updates["ai_daily_token_budget"] = req.daily_token_budget
|
||||
settings.ai_daily_token_budget = req.daily_token_budget
|
||||
if req.provider == "codex_cli":
|
||||
try:
|
||||
codex_command = normalize_codex_command(req.codex_command)
|
||||
except ValueError as exc:
|
||||
raise HTTPException(status_code=400, detail=str(exc)) from exc
|
||||
updates["ai_codex_command"] = codex_command
|
||||
settings.ai_codex_command = codex_command
|
||||
# user_agent 允许清空(回到默认浏览器 UA),故无条件持久化
|
||||
updates["ai_user_agent"] = req.user_agent
|
||||
settings.ai_user_agent = req.user_agent
|
||||
|
||||
if updates:
|
||||
secrets_store.save(updates)
|
||||
|
||||
provider = current_ai_provider()
|
||||
return {
|
||||
"ok": True,
|
||||
"ai_provider": provider,
|
||||
"ai_model": current_ai_model(),
|
||||
"ai_codex_command": current_codex_command(),
|
||||
"ai_configured": ai_configured(provider),
|
||||
}
|
||||
|
||||
|
||||
@router.delete("/ai")
|
||||
def clear_ai_settings() -> dict:
|
||||
"""一键清空 AI 配置(provider / base_url / api_key / model)。
|
||||
|
||||
保留 ai_user_agent —— 自定义请求头与凭证解耦,清空凭证不影响绕过 CDN 拦截的设置。
|
||||
"""
|
||||
from app.config import settings
|
||||
|
||||
secrets_store.clear("ai_provider", "ai_base_url", "ai_api_key", "ai_model", "ai_codex_command")
|
||||
# 同步重置运行时内存(provider 回默认值,其余置空)
|
||||
settings.ai_provider = "openai_compat"
|
||||
settings.ai_base_url = ""
|
||||
settings.ai_api_key = ""
|
||||
settings.ai_model = ""
|
||||
settings.ai_codex_command = "codex"
|
||||
|
||||
return {"ok": True}
|
||||
|
||||
|
||||
@@ -280,6 +329,16 @@ def get_preferences() -> dict:
|
||||
"indices_nav_pinned": preferences.get_indices_nav_pinned(),
|
||||
"minute_sync_enabled": preferences.get_minute_sync_enabled(),
|
||||
"minute_sync_days": preferences.get_minute_sync_days(),
|
||||
"daily_data_provider": preferences.get_daily_data_provider(),
|
||||
"adj_factor_provider": preferences.get_adj_factor_provider(),
|
||||
"minute_data_provider": preferences.get_minute_data_provider(),
|
||||
"realtime_data_provider": preferences.get_realtime_data_provider(),
|
||||
"realtime_watchlist_symbols": preferences.get_realtime_watchlist_symbols(),
|
||||
**preferences.get_realtime_quote_scope(),
|
||||
"pipeline_pull_a_share": preferences.get_pipeline_pull_a_share(),
|
||||
"pipeline_pull_etf": preferences.get_pipeline_pull_etf(),
|
||||
"pipeline_pull_index": preferences.get_pipeline_pull_index(),
|
||||
"pipeline_index_symbols": preferences.get_pipeline_index_symbols(),
|
||||
"pipeline_schedule": preferences.get_pipeline_schedule(),
|
||||
"instruments_schedule": preferences.get_instruments_schedule(),
|
||||
"enriched_batch_size": preferences.get_enriched_batch_size(),
|
||||
@@ -290,6 +349,9 @@ def get_preferences() -> dict:
|
||||
"strategy_monitor_enabled": preferences.get_strategy_monitor_enabled(),
|
||||
"strategy_monitor_ids": preferences.get_strategy_monitor_ids(),
|
||||
"system_notify_enabled": preferences.get_system_notify_enabled(),
|
||||
"feishu_webhook_url": preferences.get_feishu_webhook_url(),
|
||||
"feishu_webhook_secret": preferences.get_feishu_webhook_secret(),
|
||||
"webhook_enabled_default": preferences.get_webhook_enabled_default(),
|
||||
"sidebar_index_symbols": preferences.get_sidebar_index_symbols(),
|
||||
"nav_order": preferences.get_nav_order(),
|
||||
"nav_hidden": preferences.get_nav_hidden(),
|
||||
@@ -297,6 +359,8 @@ def get_preferences() -> dict:
|
||||
"limit_ladder_monitor_enabled": preferences.get_limit_ladder_monitor_enabled(),
|
||||
"depth_polling_interval": preferences.get_depth_polling_interval(),
|
||||
"depth_finalize_time": preferences.get_depth_finalize_time(),
|
||||
"review_schedule": preferences.get_review_schedule(),
|
||||
"review_push_channels": preferences.get_review_push_channels(),
|
||||
}
|
||||
|
||||
|
||||
@@ -377,11 +441,19 @@ class RealtimeQuotesPrefs(BaseModel):
|
||||
realtime_quotes_enabled: bool
|
||||
|
||||
|
||||
class RealtimeQuoteScopePrefs(BaseModel):
|
||||
realtime_pull_stock: bool | None = None
|
||||
realtime_pull_etf: bool | None = None
|
||||
realtime_pull_index: bool | None = None
|
||||
realtime_index_mode: str | None = None
|
||||
realtime_index_symbols: list[str] | None = None
|
||||
|
||||
|
||||
@router.put("/preferences/realtime-quotes")
|
||||
def update_realtime_quotes(req: RealtimeQuotesPrefs, request: Request) -> dict:
|
||||
"""保存全局实时行情开关。
|
||||
|
||||
none/free 档无实时行情权限:拒绝开启,persist 为关闭并返回 allowed=False,
|
||||
none 档无实时行情权限；free 档开启自选股实时；starter+ 开启全市场实时。
|
||||
前端据此把开关置灰 / 回弹。
|
||||
"""
|
||||
from app.services import preferences
|
||||
@@ -394,6 +466,9 @@ def update_realtime_quotes(req: RealtimeQuotesPrefs, request: Request) -> dict:
|
||||
if qs:
|
||||
qs.disable()
|
||||
return {"realtime_quotes_enabled": False, "realtime_allowed": False}
|
||||
if req.realtime_quotes_enabled and qs and qs.realtime_mode() == "watchlist" and not preferences.get_realtime_watchlist_symbols():
|
||||
preferences.save({"realtime_quotes_enabled": False})
|
||||
return {"realtime_quotes_enabled": False, "realtime_allowed": True, "mode": "watchlist", "error": "watchlist_empty"}
|
||||
|
||||
preferences.save({"realtime_quotes_enabled": req.realtime_quotes_enabled})
|
||||
if qs:
|
||||
@@ -405,6 +480,26 @@ def update_realtime_quotes(req: RealtimeQuotesPrefs, request: Request) -> dict:
|
||||
return {"realtime_quotes_enabled": req.realtime_quotes_enabled, "realtime_allowed": allowed}
|
||||
|
||||
|
||||
@router.put("/preferences/realtime-quote-scope")
|
||||
def update_realtime_quote_scope(req: RealtimeQuoteScopePrefs) -> dict:
|
||||
"""保存盘中实时行情范围；独立于盘后管道范围。"""
|
||||
from app.services import preferences
|
||||
cfg = req.model_dump(exclude_none=True)
|
||||
return preferences.set_realtime_quote_scope(cfg)
|
||||
|
||||
|
||||
class RealtimeWatchlistPrefs(BaseModel):
|
||||
symbols: list[str] = []
|
||||
|
||||
|
||||
@router.put("/preferences/realtime-watchlist")
|
||||
def update_realtime_watchlist(req: RealtimeWatchlistPrefs) -> dict:
|
||||
"""兼容旧入口；Free 实时标的由自选页前 5 个决定。"""
|
||||
from app.services import preferences
|
||||
symbols = preferences.set_realtime_watchlist_symbols(req.symbols)
|
||||
return {"realtime_watchlist_symbols": symbols}
|
||||
|
||||
|
||||
class IndicesNavPinnedPrefs(BaseModel):
|
||||
indices_nav_pinned: bool
|
||||
|
||||
@@ -457,6 +552,34 @@ def update_realtime_monitor_config(req: RealtimeMonitorConfigIn, request: Reques
|
||||
return result
|
||||
|
||||
|
||||
class PipelinePullTypesIn(BaseModel):
|
||||
"""盘后管道拉取内容开关(A股 / ETF / 指数 独立控制)。"""
|
||||
pipeline_pull_a_share: bool | None = None
|
||||
pipeline_pull_etf: bool | None = None
|
||||
pipeline_pull_index: bool | None = None
|
||||
|
||||
|
||||
@router.put("/preferences/pipeline-pull-types")
|
||||
def update_pipeline_pull_types(req: PipelinePullTypesIn) -> dict:
|
||||
"""更新盘后管道拉取内容开关。"""
|
||||
from app.services import preferences
|
||||
cfg = req.model_dump(exclude_none=True)
|
||||
return preferences.set_pipeline_pull_types(cfg)
|
||||
|
||||
|
||||
class PipelineIndexSymbolsIn(BaseModel):
|
||||
"""指数自定义拉取代码(逗号/换行/空格分隔,空串表示全量)。"""
|
||||
symbols: str = ""
|
||||
|
||||
|
||||
@router.put("/preferences/pipeline-index-symbols")
|
||||
def update_pipeline_index_symbols(req: PipelineIndexSymbolsIn) -> dict:
|
||||
"""保存指数自定义拉取代码。"""
|
||||
from app.services import preferences
|
||||
symbols = preferences.set_pipeline_index_symbols(req.symbols)
|
||||
return {"pipeline_index_symbols": symbols}
|
||||
|
||||
|
||||
class QuoteIntervalIn(BaseModel):
|
||||
interval: float
|
||||
|
||||
@@ -477,6 +600,50 @@ def update_system_notify(req: SystemNotifyPrefsIn) -> dict:
|
||||
return {"system_notify_enabled": saved}
|
||||
|
||||
|
||||
class FeishuWebhookPrefsIn(BaseModel):
|
||||
url: str
|
||||
secret: str = ""
|
||||
|
||||
|
||||
@router.put("/preferences/feishu-webhook")
|
||||
def update_feishu_webhook(req: FeishuWebhookPrefsIn) -> dict:
|
||||
"""飞书 Webhook 地址 + 签名密钥 — 全局一处配置, 所有启用推送的监控规则共用。
|
||||
|
||||
- url: 传入空串表示清空配置; 非空则需为合法的飞书自定义机器人地址。
|
||||
- secret: 机器人启用了「签名校验」时填密钥, 留空表示不验签。
|
||||
"""
|
||||
from app.services import preferences
|
||||
from app.services import webhook_adapter
|
||||
|
||||
url = (req.url or "").strip()
|
||||
if url and not webhook_adapter.is_valid_feishu_url(url):
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="Webhook 地址非法, 需为飞书自定义机器人地址 "
|
||||
"(https://open.feishu.cn/open-apis/bot/v2/hook/...)",
|
||||
)
|
||||
saved_url = preferences.set_feishu_webhook_url(url)
|
||||
saved_secret = preferences.set_feishu_webhook_secret((req.secret or "").strip())
|
||||
return {"feishu_webhook_url": saved_url, "feishu_webhook_secret": saved_secret}
|
||||
|
||||
|
||||
class WebhookEnabledDefaultIn(BaseModel):
|
||||
enabled: bool
|
||||
|
||||
|
||||
@router.put("/preferences/webhook-enabled-default")
|
||||
def update_webhook_enabled_default(req: WebhookEnabledDefaultIn) -> dict:
|
||||
"""新建监控规则时是否默认勾选「飞书推送」。
|
||||
|
||||
数据模型当前只有飞书一个可用渠道 (QMT/ptrade 待定),故此处仅一个布尔。
|
||||
单条规则仍可在规则编辑页独立修改此项。
|
||||
"""
|
||||
from app.services import preferences
|
||||
|
||||
saved = preferences.set_webhook_enabled_default(req.enabled)
|
||||
return {"webhook_enabled_default": saved}
|
||||
|
||||
|
||||
@router.put("/preferences/quote-interval")
|
||||
def update_quote_interval(req: QuoteIntervalIn, request: Request) -> dict:
|
||||
"""更新行情轮询间隔。按档位自动 clamp。"""
|
||||
@@ -510,7 +677,7 @@ class TestEndpointIn(BaseModel):
|
||||
rounds: int | None = None
|
||||
|
||||
|
||||
# 官方端点发现清单 —— 前端浏览器无法直接跨域拉取数据源官网 /endpoints.json
|
||||
# 官方端点发现清单 —— 前端浏览器无法直接跨域拉取 tickflow.org/endpoints.json
|
||||
# (无 CORS 头),因此由后端代理。缓存 5 分钟,失败时回退到内置列表。
|
||||
ENDPOINTS_URL = "https://tickflow.org/endpoints.json"
|
||||
ENDPOINTS_TTL = 300.0 # 秒
|
||||
@@ -574,7 +741,7 @@ _endpoints_cache: dict = {"ts": 0.0, "data": None}
|
||||
|
||||
@router.get("/endpoints")
|
||||
def list_endpoints() -> dict:
|
||||
"""代理拉取数据源官网 /endpoints.json 并返回规范化端点列表。
|
||||
"""代理拉取 tickflow.org/endpoints.json 并返回规范化端点列表。
|
||||
|
||||
前端无法跨域直连该 URL(无 CORS 头),故由本接口代理。带 8s 超时、
|
||||
5 分钟内存缓存,远程失败时回退到内置列表,保证 UI 始终有内容。
|
||||
@@ -601,7 +768,7 @@ def list_endpoints() -> dict:
|
||||
data = {
|
||||
"version": parsed.get("version", 1),
|
||||
"description": parsed.get(
|
||||
"description", "API 端点配置"
|
||||
"description", "TickFlow API 端点配置"
|
||||
),
|
||||
"healthPath": parsed.get("healthPath", "/health"),
|
||||
"testRounds": parsed.get("testRounds", 5),
|
||||
@@ -614,7 +781,7 @@ def list_endpoints() -> dict:
|
||||
source = "fallback"
|
||||
data = {
|
||||
"version": 1,
|
||||
"description": "API 端点配置",
|
||||
"description": "TickFlow API 端点配置",
|
||||
"healthPath": "/health",
|
||||
"testRounds": 5,
|
||||
"endpoints": _FALLBACK_ENDPOINTS,
|
||||
@@ -652,7 +819,7 @@ async def _http_ping(url: str, timeout: float = 10.0) -> float | None:
|
||||
async def test_endpoint(req: TestEndpointIn) -> dict:
|
||||
"""测试端点网络延迟:对 /health 多轮探测取中位数。
|
||||
|
||||
参考官方 latency_test.py:
|
||||
参考 TickFlow 官方 latency_test.py:
|
||||
- 路径用 /health(公开、轻量),反映真实网络延迟而非业务接口耗时
|
||||
- 多轮探测(默认 5 轮,取自 endpoints.json 的 testRounds),间隔 0.3s
|
||||
- 返回 median/min/max/success,前端显示中位数
|
||||
@@ -852,3 +1019,65 @@ def update_depth_finalize_time(req: DepthFinalizeTimeIn, request: Request) -> di
|
||||
|
||||
return sched
|
||||
|
||||
|
||||
class ReviewScheduleIn(BaseModel):
|
||||
enabled: bool
|
||||
hour: int
|
||||
minute: int
|
||||
|
||||
|
||||
@router.put("/preferences/review-schedule")
|
||||
def update_review_schedule(req: ReviewScheduleIn, request: Request) -> dict:
|
||||
"""保存定时复盘调度并立即更新 APScheduler job。
|
||||
|
||||
- enabled=True: 注册/更新 job(工作日定时生成复盘报告)
|
||||
- enabled=False: 移除 job(停止定时复盘)
|
||||
- 校验: 开启时若 AI Key 未配置则拒绝(复盘依赖 AI), 提示用户先配置。
|
||||
- 时间下限 15:00(A股收盘), 由 preferences 层强制。
|
||||
"""
|
||||
from app.services import preferences
|
||||
|
||||
if req.enabled:
|
||||
# 复盘必须有 AI Key, 否则每日报错刷日志
|
||||
from app import secrets_store
|
||||
if not secrets_store.get_ai_key():
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="复盘依赖 AI,请先在「设置 → AI」配置 API Key 后再开启定时复盘",
|
||||
)
|
||||
|
||||
sched = preferences.set_review_schedule(req.enabled, req.hour, req.minute)
|
||||
|
||||
# 动态操作 APScheduler job
|
||||
from app.jobs.daily_pipeline import _register_review_job, REVIEW_JOB_ID
|
||||
scheduler = getattr(request.app.state, "scheduler", None)
|
||||
if scheduler:
|
||||
if sched["enabled"]:
|
||||
_register_review_job(scheduler, request.app.state.repo, sched["hour"], sched["minute"])
|
||||
logger.info("scheduled_review enabled @%02d:%02d mon-fri", sched["hour"], sched["minute"])
|
||||
else:
|
||||
try:
|
||||
scheduler.remove_job(REVIEW_JOB_ID)
|
||||
logger.info("scheduled_review disabled (job removed)")
|
||||
except Exception:
|
||||
pass # job 本就不存在(从未开过), 无需处理
|
||||
|
||||
return sched
|
||||
|
||||
|
||||
class ReviewPushIn(BaseModel):
|
||||
channels: list[str] # 多选: ['feishu'] 等; 空数组=不推送。微信等开发中
|
||||
|
||||
|
||||
@router.put("/preferences/review-push")
|
||||
def update_review_push(req: ReviewPushIn) -> dict:
|
||||
"""复盘推送渠道(多选) — 选定把复盘报告(手动生成 / 定时生成归档后)推送到哪些外部工具。
|
||||
|
||||
纯偏好, 与定时复盘 / 实时行情完全独立, 常驻可单独设置。空数组=不推送。
|
||||
实际推送由归档端点(POST /api/market-recap/reports)与定时任务(_run_scheduled_review)
|
||||
在归档后读取本列表逐个推送。白名单外的渠道会被过滤掉。
|
||||
"""
|
||||
from app.services import preferences
|
||||
saved = preferences.set_review_push_channels(req.channels)
|
||||
return {"review_push_channels": saved}
|
||||
|
||||
|
||||
@@ -0,0 +1,217 @@
|
||||
"""个股分析 API — 关键价位 + AI 四维分析 + 报告持久化。
|
||||
|
||||
路由前缀: /api/stock-analysis
|
||||
|
||||
端点:
|
||||
GET /levels?symbol= 11 类关键价位(图表 markLine 数据源)
|
||||
POST /analyze AI 流式四维分析(NDJSON)
|
||||
GET /reports 历史报告列表
|
||||
POST /reports 保存一条报告
|
||||
DELETE /reports/{report_id} 删除一条报告
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import math
|
||||
from datetime import date, timedelta
|
||||
|
||||
import polars as pl
|
||||
from fastapi import APIRouter, HTTPException, Query, Request
|
||||
from fastapi.responses import StreamingResponse
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app.indicators.levels import compute_levels, summarize_levels
|
||||
from app.services import stock_reports
|
||||
from app.services.stock_analyzer import analyze_stock_stream
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(prefix="/api/stock-analysis", tags=["stock-analysis"])
|
||||
|
||||
|
||||
def _to_float_list(series: pl.Series) -> list:
|
||||
"""polars Series → JSON 安全的 float 列表(null/NaN → None)。"""
|
||||
out: list = []
|
||||
for v in series.to_list():
|
||||
if v is None:
|
||||
out.append(None)
|
||||
continue
|
||||
try:
|
||||
f = float(v)
|
||||
out.append(round(f, 2) if math.isfinite(f) else None)
|
||||
except (TypeError, ValueError):
|
||||
out.append(None)
|
||||
return out
|
||||
|
||||
|
||||
def _build_series(df: pl.DataFrame) -> dict:
|
||||
"""提取带状指标(布林带 / Keltner通道 / ATR止损)的每日时间序列。
|
||||
|
||||
这些指标的本质是"每日一条线",随 MA/ATR/σ 漂移,画成曲线才能体现通道形态。
|
||||
其余固定价位(枢轴/前高前低等)不在此,仍用水平 markLine。
|
||||
|
||||
返回结构(每个 value 都是按日期对齐的数组):
|
||||
{
|
||||
"boll": {"upper": [...], "lower": [...]},
|
||||
"keltner_s": {"upper": [...], "lower": [...]}, # 短期 MA20±2ATR
|
||||
"keltner_m": {"upper": [...], "lower": [...]}, # 中期 MA60±2.5ATR
|
||||
"keltner_l": {"upper": [...], "lower": [...]}, # 长期 MA120±3ATR
|
||||
"atr": {"stop_loss": [...], "take_profit": [...]}, # close∓2ATR
|
||||
}
|
||||
"""
|
||||
if df.is_empty() or "close" not in df.columns:
|
||||
return {}
|
||||
|
||||
out: dict[str, dict] = {}
|
||||
close = df["close"]
|
||||
has_atr = "atr_14" in df.columns
|
||||
|
||||
# 布林带(上/下/中轨;中轨 = MA20,数据层已预计算)
|
||||
if "boll_upper" in df.columns and "boll_lower" in df.columns:
|
||||
out["boll"] = {
|
||||
"upper": _to_float_list(df["boll_upper"]),
|
||||
"lower": _to_float_list(df["boll_lower"]),
|
||||
"mid": _to_float_list(df["ma20"]) if "ma20" in df.columns else None,
|
||||
}
|
||||
|
||||
# Keltner 通道三档(需要 ATR)
|
||||
if has_atr:
|
||||
atr = df["atr_14"]
|
||||
# MA120 现场算(不在预计算列中)
|
||||
ma120 = df.select(pl.col("close").rolling_mean(120))["close"] if df.height >= 120 else None
|
||||
|
||||
def _channel(ma: pl.Series, n: float) -> dict:
|
||||
return {
|
||||
"upper": _to_float_list(ma + n * atr),
|
||||
"lower": _to_float_list(ma - n * atr),
|
||||
}
|
||||
|
||||
if "ma20" in df.columns:
|
||||
out["keltner_s"] = _channel(df["ma20"], 2.0)
|
||||
if "ma60" in df.columns:
|
||||
out["keltner_m"] = _channel(df["ma60"], 2.5)
|
||||
if ma120 is not None:
|
||||
out["keltner_l"] = _channel(ma120, 3.0)
|
||||
|
||||
# ATR 止损/止盈: close ± 2×ATR(跟随行情漂移的动态止损线)
|
||||
out["atr"] = {
|
||||
"stop_loss": _to_float_list(close - 2 * atr),
|
||||
"take_profit": _to_float_list(close + 2 * atr),
|
||||
}
|
||||
|
||||
return out
|
||||
|
||||
|
||||
@router.get("/levels")
|
||||
def get_levels(
|
||||
request: Request,
|
||||
symbol: str = Query(..., description="标的代码,如 000001.SZ"),
|
||||
days: int = Query(120, ge=30, le=500, description="计算样本天数"),
|
||||
):
|
||||
"""计算 11 类关键价位(成交密集区压力支撑 / 枢轴点 / 前高前低 /
|
||||
布林带 / Keltner短中长 / ATR止损 / 缺口 / 斐波那契 / 整数关口)。
|
||||
|
||||
返回 {levels: {sr, pivot, extreme, boll, keltner_s, keltner_m, keltner_l,
|
||||
atr_stop, gap, fib, round}, close, summary, dates, series}。
|
||||
前端按 levels 的 key 渲染开关按钮,逐组显隐 markLine / 曲线。
|
||||
"""
|
||||
if not symbol:
|
||||
raise HTTPException(400, "symbol 不能为空")
|
||||
|
||||
repo = request.app.state.repo
|
||||
end = date.today()
|
||||
start = end - timedelta(days=days * 2)
|
||||
df = repo.get_daily(symbol, start, end)
|
||||
if df.is_empty():
|
||||
return {"levels": {"sr": [], "pivot": [], "extreme": [],
|
||||
"boll": [], "keltner_s": [], "keltner_m": [], "keltner_l": [],
|
||||
"atr_stop": [], "gap": [], "fib": [], "round": []},
|
||||
"close": None, "summary": "无数据", "symbol": symbol,
|
||||
"dates": [], "series": {}}
|
||||
|
||||
levels = compute_levels(df)
|
||||
close = float(df.tail(1)["close"][0]) if "close" in df.columns else None
|
||||
# 日期 + 带状曲线序列(供前端画 Keltner/ATR/布林带曲线)
|
||||
dates = df["date"].to_list()
|
||||
series = _build_series(df)
|
||||
return {
|
||||
"levels": levels,
|
||||
"close": close,
|
||||
"summary": summarize_levels(levels, close),
|
||||
"symbol": symbol,
|
||||
"dates": [str(d) for d in dates],
|
||||
"series": series,
|
||||
}
|
||||
|
||||
|
||||
class AnalyzeRequest(BaseModel):
|
||||
"""AI 个股分析请求。"""
|
||||
symbol: str
|
||||
focus: str = "" # 可选:用户追加的分析关注点
|
||||
|
||||
|
||||
@router.post("/analyze")
|
||||
async def analyze_stock(request: Request, req: AnalyzeRequest):
|
||||
"""AI 个股四维分析 — NDJSON 流式返回。
|
||||
|
||||
组合 K 线(技术指标)+ 财务表 + 关键价位 → 实战派提示词 →
|
||||
流式调用 LLM → 逐 chunk 以 NDJSON 推给前端(每行一个 JSON)。
|
||||
"""
|
||||
if not req.symbol:
|
||||
raise HTTPException(400, "symbol 不能为空")
|
||||
|
||||
repo = request.app.state.repo
|
||||
data_dir = repo.store.data_dir
|
||||
|
||||
async def stream_gen():
|
||||
async for chunk in analyze_stock_stream(repo, data_dir, req.symbol, req.focus):
|
||||
yield chunk + "\n"
|
||||
|
||||
return StreamingResponse(
|
||||
stream_gen(),
|
||||
media_type="application/x-ndjson",
|
||||
headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
|
||||
)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 报告 CRUD(历史报告持久化)
|
||||
# ================================================================
|
||||
|
||||
class SaveReportRequest(BaseModel):
|
||||
"""保存一条 AI 个股分析报告。"""
|
||||
symbol: str
|
||||
name: str = ""
|
||||
focus: str = ""
|
||||
content: str
|
||||
summary: str = ""
|
||||
close: float | None = None
|
||||
levels: dict | None = None
|
||||
|
||||
|
||||
@router.get("/reports")
|
||||
def list_reports(request: Request):
|
||||
"""获取全部历史报告(按时间降序,后端已裁剪到上限)。"""
|
||||
return {"reports": stock_reports.list_reports()}
|
||||
|
||||
|
||||
@router.post("/reports")
|
||||
def save_report(request: Request, req: SaveReportRequest):
|
||||
"""保存一条报告。"""
|
||||
report = stock_reports.save_report({
|
||||
"symbol": req.symbol,
|
||||
"name": req.name,
|
||||
"focus": req.focus,
|
||||
"content": req.content,
|
||||
"summary": req.summary,
|
||||
"close": req.close,
|
||||
"levels": req.levels,
|
||||
})
|
||||
return {"ok": True, "report": report}
|
||||
|
||||
|
||||
@router.delete("/reports/{report_id}")
|
||||
def delete_report(request: Request, report_id: str):
|
||||
"""删除一条报告。"""
|
||||
ok = stock_reports.delete_report(report_id)
|
||||
return {"ok": ok}
|
||||
@@ -84,6 +84,7 @@ def _strategy_detail(s: StrategyDef, overrides: dict | None = None) -> dict:
|
||||
"entry_signals": s.entry_signals,
|
||||
"exit_signals": s.exit_signals,
|
||||
"stop_loss": overrides.get("stop_loss", s.stop_loss) if overrides else s.stop_loss,
|
||||
"take_profit": getattr(s, "take_profit", None),
|
||||
"trailing_stop": getattr(s, "trailing_stop", None),
|
||||
"trailing_take_profit_activate": getattr(s, "trailing_take_profit_activate", None),
|
||||
"trailing_take_profit_drawdown": getattr(s, "trailing_take_profit_drawdown", None),
|
||||
@@ -285,12 +286,19 @@ class BuildRequest(BaseModel):
|
||||
|
||||
@router.get("/ai/status")
|
||||
def ai_status(request: Request):
|
||||
"""检查 AI 配置状态"""
|
||||
from app.config import settings
|
||||
"""Check whether the selected AI provider is configured."""
|
||||
from app import secrets_store
|
||||
from app.services.ai_provider import ai_configured, current_ai_model, current_ai_provider
|
||||
|
||||
has_key = bool(secrets_store.get_ai_key())
|
||||
has_model = bool(settings.ai_model)
|
||||
return {"configured": has_key and has_model, "has_key": has_key, "has_model": has_model}
|
||||
model = current_ai_model()
|
||||
provider = current_ai_provider()
|
||||
return {
|
||||
"configured": ai_configured(provider) and bool(model or provider == "codex_cli"),
|
||||
"has_key": has_key,
|
||||
"has_model": bool(model),
|
||||
"provider": provider,
|
||||
}
|
||||
|
||||
|
||||
@router.get("/{strategy_id}/source")
|
||||
@@ -314,24 +322,17 @@ def get_strategy_source(strategy_id: str, request: Request):
|
||||
|
||||
@router.post("/ai/test")
|
||||
async def ai_test(request: Request):
|
||||
"""测试 AI 连通性 — 发送简单请求验证 Key 和模型"""
|
||||
from app.config import settings
|
||||
from app import secrets_store
|
||||
from openai import AsyncOpenAI
|
||||
|
||||
ai_key = secrets_store.get_ai_key()
|
||||
if not ai_key:
|
||||
return {"ok": False, "error": "未配置 API Key"}
|
||||
"""Send a small prompt through the selected AI provider."""
|
||||
from app.services.ai_provider import current_ai_model, current_ai_provider, generate_ai_text
|
||||
|
||||
try:
|
||||
client = AsyncOpenAI(api_key=ai_key, base_url=settings.ai_base_url)
|
||||
resp = await client.chat.completions.create(
|
||||
model=settings.ai_model,
|
||||
messages=[{"role": "user", "content": "回复 OK"}],
|
||||
max_tokens=5,
|
||||
text = await generate_ai_text(
|
||||
[{"role": "user", "content": "Reply exactly: OK"}],
|
||||
temperature=0,
|
||||
max_tokens=8,
|
||||
timeout=15,
|
||||
)
|
||||
return {"ok": True, "model": resp.model, "usage": {"prompt": resp.usage.prompt_tokens, "completion": resp.usage.completion_tokens} if resp.usage else None}
|
||||
return {"ok": True, "model": current_ai_model() or current_ai_provider(), "response": text[:80]}
|
||||
except Exception as e:
|
||||
return {"ok": False, "error": str(e)}
|
||||
|
||||
|
||||
@@ -27,28 +27,48 @@ class BatchAddRequest(BaseModel):
|
||||
note: str = ""
|
||||
|
||||
|
||||
def _with_names(rows: list[dict], request: Request) -> list[dict]:
|
||||
if not rows:
|
||||
return rows
|
||||
try:
|
||||
df_i = request.app.state.repo.get_instruments()
|
||||
if df_i.is_empty() or "symbol" not in df_i.columns or "name" not in df_i.columns:
|
||||
return rows
|
||||
name_by_symbol = dict(df_i.select(["symbol", "name"]).iter_rows())
|
||||
return [{**row, "name": name_by_symbol.get(row.get("symbol"))} for row in rows]
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.debug("attach watchlist names failed: %s", e)
|
||||
return rows
|
||||
|
||||
|
||||
@router.get("")
|
||||
def list_all():
|
||||
return {"symbols": watchlist.list_symbols()}
|
||||
def list_all(request: Request):
|
||||
return {"symbols": _with_names(watchlist.list_symbols(), request)}
|
||||
|
||||
|
||||
@router.post("")
|
||||
def add_one(req: AddRequest):
|
||||
def add_one(req: AddRequest, request: Request):
|
||||
rows = watchlist.add(req.symbol, req.note)
|
||||
return {"symbols": rows}
|
||||
return {"symbols": _with_names(rows, request)}
|
||||
|
||||
|
||||
@router.post("/batch")
|
||||
def add_batch(req: BatchAddRequest):
|
||||
def add_batch(req: BatchAddRequest, request: Request):
|
||||
for sym in req.symbols:
|
||||
watchlist.add(sym, req.note)
|
||||
return {"symbols": watchlist.list_symbols(), "added": len(req.symbols)}
|
||||
return {"symbols": _with_names(watchlist.list_symbols(), request), "added": len(req.symbols)}
|
||||
|
||||
|
||||
@router.post("/{symbol}/top")
|
||||
def move_one_to_top(symbol: str, request: Request):
|
||||
rows = watchlist.move_to_top(symbol)
|
||||
return {"symbols": _with_names(rows, request)}
|
||||
|
||||
|
||||
@router.delete("/{symbol}")
|
||||
def remove_one(symbol: str):
|
||||
def remove_one(symbol: str, request: Request):
|
||||
rows = watchlist.remove(symbol)
|
||||
return {"symbols": rows}
|
||||
return {"symbols": _with_names(rows, request)}
|
||||
|
||||
|
||||
@router.delete("")
|
||||
|
||||
@@ -1,189 +0,0 @@
|
||||
"""访问门控 —— 支持管理员令牌 + 动态 UUID 两种凭证。
|
||||
|
||||
部署方式(优先级从高到低):
|
||||
1. ADMIN_TOKEN: 管理员初始令牌(如 admin7226132)。验证通过后进入管理页,
|
||||
可创建普通 UUID 供合伙人使用,管理员本身也可访问全部功能。
|
||||
2. 动态 UUID: 管理员通过 /admin/uuids 创建的访问 UUID,持久化在
|
||||
data/user_data/access_uuids.json。
|
||||
3. ACCESS_UUID: 遗留单共享 UUID,保持向后兼容。
|
||||
|
||||
以上全部留空则门控不启用。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import hmac
|
||||
import logging
|
||||
import secrets
|
||||
import time
|
||||
from enum import Enum
|
||||
from typing import Any
|
||||
|
||||
from fastapi import HTTPException, Request
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app.config import settings
|
||||
from app import uuid_store
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class AuthRole(str, Enum):
|
||||
ADMIN = "admin"
|
||||
USER = "user"
|
||||
|
||||
|
||||
# 内存中的令牌缓存:{token: {"role": role, "expires_at": float}}
|
||||
_token_cache: dict[str, dict[str, Any]] = {}
|
||||
|
||||
# 令牌默认有效期:7 天
|
||||
TOKEN_TTL_SECONDS = 7 * 24 * 60 * 60
|
||||
|
||||
|
||||
class VerifyIn(BaseModel):
|
||||
credential: str
|
||||
|
||||
|
||||
class VerifyOut(BaseModel):
|
||||
valid: bool
|
||||
role: str | None = None
|
||||
token: str | None = None
|
||||
|
||||
|
||||
class AuthStatusOut(BaseModel):
|
||||
enabled: bool
|
||||
verified: bool
|
||||
role: str | None = None
|
||||
|
||||
|
||||
class UuidRecordOut(BaseModel):
|
||||
uuid: str
|
||||
label: str
|
||||
enabled: bool
|
||||
created_at: int
|
||||
|
||||
|
||||
class UuidCreateIn(BaseModel):
|
||||
label: str = ""
|
||||
|
||||
|
||||
def access_control_enabled() -> bool:
|
||||
"""是否启用了任何访问门控。"""
|
||||
return bool(settings.admin_token) or bool(settings.access_uuid)
|
||||
|
||||
|
||||
def admin_mode_enabled() -> bool:
|
||||
"""是否启用了管理员令牌模式。"""
|
||||
return bool(settings.admin_token)
|
||||
|
||||
|
||||
def _constant_time_compare(a: str, b: str) -> bool:
|
||||
"""常量时间字符串比较,降低时序攻击风险。"""
|
||||
return hmac.compare_digest(a.encode(), b.encode())
|
||||
|
||||
|
||||
def verify_admin_token(credential: str | None) -> bool:
|
||||
"""校验是否为管理员令牌。"""
|
||||
if not credential or not settings.admin_token:
|
||||
return False
|
||||
return _constant_time_compare(credential.strip(), settings.admin_token.strip())
|
||||
|
||||
|
||||
def verify_uuid(credential: str | None) -> bool:
|
||||
"""校验输入是否为有效访问 UUID(遗留单 UUID 或动态 UUID)。"""
|
||||
if not credential:
|
||||
return False
|
||||
stripped = credential.strip()
|
||||
# 动态 UUID
|
||||
if uuid_store.exists(stripped):
|
||||
return True
|
||||
# 遗留单共享 UUID
|
||||
if settings.access_uuid and _constant_time_compare(stripped, settings.access_uuid.strip()):
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def verify_credential(credential: str | None) -> AuthRole | None:
|
||||
"""校验任意凭证,返回对应角色;无效返回 None。"""
|
||||
if not credential:
|
||||
return None
|
||||
if verify_admin_token(credential):
|
||||
return AuthRole.ADMIN
|
||||
if verify_uuid(credential):
|
||||
return AuthRole.USER
|
||||
return None
|
||||
|
||||
|
||||
def create_access_token(role: AuthRole) -> str:
|
||||
"""生成一个随机访问令牌并缓存。"""
|
||||
token = secrets.token_urlsafe(32)
|
||||
_token_cache[token] = {"role": role, "expires_at": time.time() + TOKEN_TTL_SECONDS}
|
||||
return token
|
||||
|
||||
|
||||
def validate_access_token(token: str | None) -> AuthRole | None:
|
||||
"""校验令牌是否有效,返回角色。"""
|
||||
if not token:
|
||||
return None
|
||||
cached = _token_cache.get(token)
|
||||
if cached is None:
|
||||
return None
|
||||
expires_at = cached.get("expires_at", 0)
|
||||
if expires_at > 0 and time.time() > expires_at:
|
||||
_token_cache.pop(token, None)
|
||||
return None
|
||||
return cached.get("role")
|
||||
|
||||
|
||||
def revoke_access_token(token: str | None) -> None:
|
||||
"""使指定令牌失效。"""
|
||||
if token:
|
||||
_token_cache.pop(token, None)
|
||||
|
||||
|
||||
def get_access_token_from_request(request: Request) -> str | None:
|
||||
"""从请求头或 query 参数中提取访问令牌。"""
|
||||
header = request.headers.get("X-Access-Token")
|
||||
if header:
|
||||
return header.strip()
|
||||
return request.query_params.get("access_token")
|
||||
|
||||
|
||||
def require_access(request: Request, allowed_roles: set[AuthRole] | None = None) -> AuthRole:
|
||||
"""FastAPI 依赖:未通过校验时抛出 401。
|
||||
|
||||
allowed_roles: 仅允许指定角色访问;None 表示 admin/user 均可。
|
||||
"""
|
||||
if not access_control_enabled():
|
||||
return AuthRole.ADMIN # 未启用门控时视为最高权限
|
||||
token = get_access_token_from_request(request)
|
||||
role = validate_access_token(token)
|
||||
if role is None:
|
||||
raise HTTPException(status_code=401, detail="访问令牌无效或已过期")
|
||||
if allowed_roles is not None and role not in allowed_roles:
|
||||
raise HTTPException(status_code=403, detail="权限不足")
|
||||
return role
|
||||
|
||||
|
||||
def require_admin(request: Request) -> AuthRole:
|
||||
"""FastAPI 依赖:仅管理员可访问。"""
|
||||
return require_access(request, allowed_roles={AuthRole.ADMIN})
|
||||
|
||||
|
||||
def is_public_path(path: str) -> bool:
|
||||
"""判断请求路径是否属于白名单(无需校验)。"""
|
||||
public_prefixes = (
|
||||
"/health",
|
||||
"/api/auth/",
|
||||
"/assets/",
|
||||
"/index.html",
|
||||
"/favicon.ico",
|
||||
"/robots.txt",
|
||||
"/manifest.json",
|
||||
)
|
||||
lowered = path.lower()
|
||||
return lowered.startswith(public_prefixes) or lowered == "/"
|
||||
|
||||
|
||||
def is_admin_path(path: str) -> bool:
|
||||
"""判断是否为管理员接口路径。"""
|
||||
return path.lower().startswith("/api/admin/")
|
||||
@@ -37,6 +37,7 @@ class MatcherConfig:
|
||||
fees_pct: float = 0.0002
|
||||
slippage_bps: float = 5.0
|
||||
stop_loss_pct: float | None = None
|
||||
take_profit_pct: float | None = None
|
||||
trailing_stop_pct: float | None = None
|
||||
trailing_take_profit_activate_pct: float | None = None
|
||||
trailing_take_profit_drawdown_pct: float | None = None
|
||||
@@ -65,7 +66,7 @@ class TradeRecord:
|
||||
exit_price: float
|
||||
pnl_pct: float
|
||||
duration: int
|
||||
exit_reason: str # "signal" | "stop_loss" | "trailing_stop" | "trailing_take_profit" | "max_hold" | "end"
|
||||
exit_reason: str # "signal" | "stop_loss" | "take_profit" | "trailing_stop" | "trailing_take_profit" | "max_hold" | "end"
|
||||
# 退出优先级 (高→低): pending_exit(历史挂单) > 风控(止损/移动止损/移动止盈) > signal(卖点) > max_hold(到期) > end
|
||||
name: str = ""
|
||||
shares: float = 0.0
|
||||
@@ -544,6 +545,7 @@ class BacktestEngine:
|
||||
return None, None
|
||||
open_price = float(open_prices[idx])
|
||||
low_price = float(low_prices[idx])
|
||||
high_price = float(high_prices[idx])
|
||||
peak_price = float(pos.get("max_high", entry_price))
|
||||
risk_lines: list[tuple[float, str]] = []
|
||||
|
||||
@@ -560,13 +562,24 @@ class BacktestEngine:
|
||||
risk_lines.append((entry_price * (1 + peak_profit - abs(float(drawdown_pct))), "trailing_take_profit"))
|
||||
|
||||
risk_lines = [(line, reason) for line, reason in risk_lines if _valid_price(line)]
|
||||
if not risk_lines:
|
||||
return None, None
|
||||
# 止损/移损/回撤止盈: 价格跌破风控线触发 (取最高优先级线)
|
||||
if risk_lines:
|
||||
stop_price, reason = max(risk_lines, key=lambda item: item[0])
|
||||
if _valid_price(open_price) and open_price <= stop_price:
|
||||
return reason, open_price
|
||||
if _valid_price(low_price) and low_price <= stop_price:
|
||||
return reason, stop_price
|
||||
|
||||
# 固定止盈: 价格涨破止盈线触发
|
||||
tp_pct = getattr(config, "take_profit_pct", None)
|
||||
if tp_pct is not None:
|
||||
tp_line = entry_price * (1 + abs(float(tp_pct)))
|
||||
if _valid_price(tp_line):
|
||||
# 开盘即超过止盈线 → 以开盘价成交; 否则当日触及高点止盈
|
||||
if _valid_price(open_price) and open_price >= tp_line:
|
||||
return "take_profit", open_price
|
||||
if _valid_price(high_price) and high_price >= tp_line:
|
||||
return "take_profit", tp_line
|
||||
return None, None
|
||||
|
||||
def _try_close(pos: dict, idx: int, reason: str, signal_date: str, exit_price_override: float | None = None) -> bool:
|
||||
@@ -993,6 +1006,7 @@ class BacktestEngine:
|
||||
continue
|
||||
open_price = float(open_prices[idx])
|
||||
low_price = float(low_prices[idx])
|
||||
high_price = float(high_prices[idx])
|
||||
entry_price = float(pos["entry_price"])
|
||||
peak_price = float(pos.get("max_high", entry_price))
|
||||
risk_lines: list[tuple[float, str]] = []
|
||||
@@ -1011,9 +1025,9 @@ class BacktestEngine:
|
||||
take_profit_line = entry_price * (1 + peak_profit - abs(float(drawdown_pct)))
|
||||
risk_lines.append((take_profit_line, "trailing_take_profit"))
|
||||
|
||||
# 止损/移损/回撤止盈: 价格跌破风控线触发
|
||||
risk_lines = [(line, reason) for line, reason in risk_lines if _valid_price(line)]
|
||||
if not risk_lines:
|
||||
continue
|
||||
if risk_lines:
|
||||
stop_price, reason = max(risk_lines, key=lambda item: item[0])
|
||||
exit_price_override = None
|
||||
if _valid_price(open_price) and open_price <= stop_price:
|
||||
@@ -1022,6 +1036,17 @@ class BacktestEngine:
|
||||
exit_price_override = stop_price
|
||||
if exit_price_override is not None:
|
||||
_try_sell(sym, idx, reason, d_str, sold_today, exit_price_override)
|
||||
continue
|
||||
|
||||
# 固定止盈: 价格涨破止盈线触发
|
||||
tp_pct = getattr(config, "take_profit_pct", None)
|
||||
if tp_pct is not None:
|
||||
tp_line = entry_price * (1 + abs(float(tp_pct)))
|
||||
if _valid_price(tp_line):
|
||||
if _valid_price(open_price) and open_price >= tp_line:
|
||||
_try_sell(sym, idx, "take_profit", d_str, sold_today, open_price)
|
||||
elif _valid_price(high_price) and high_price >= tp_line:
|
||||
_try_sell(sym, idx, "take_profit", d_str, sold_today, tp_line)
|
||||
|
||||
def _process_entries(
|
||||
d_str: str,
|
||||
|
||||
@@ -103,6 +103,11 @@ class StrategyBacktestService:
|
||||
entry_signals = self._effective_signals(overrides, "entry_signals", s.entry_signals)
|
||||
exit_signals = self._effective_signals(overrides, "exit_signals", s.exit_signals)
|
||||
stop_loss = self._override_value(overrides, "stop_loss", s.stop_loss)
|
||||
take_profit = self._normalize_pct(
|
||||
self._override_value(overrides, "take_profit", getattr(s, "take_profit", None)),
|
||||
0.01,
|
||||
5.0,
|
||||
)
|
||||
trailing_stop = self._normalize_pct(
|
||||
self._override_value(overrides, "trailing_stop", getattr(s, "trailing_stop", None)),
|
||||
0.005,
|
||||
@@ -195,6 +200,7 @@ class StrategyBacktestService:
|
||||
fees_pct=config.fees_pct,
|
||||
slippage_bps=config.slippage_bps,
|
||||
stop_loss_pct=stop_loss,
|
||||
take_profit_pct=take_profit,
|
||||
trailing_stop_pct=trailing_stop,
|
||||
trailing_take_profit_activate_pct=trailing_take_profit_activate,
|
||||
trailing_take_profit_drawdown_pct=trailing_take_profit_drawdown,
|
||||
@@ -246,6 +252,7 @@ class StrategyBacktestService:
|
||||
"entry_signals": entry_signals,
|
||||
"exit_signals": exit_signals,
|
||||
"stop_loss": stop_loss,
|
||||
"take_profit": take_profit,
|
||||
"trailing_stop": trailing_stop,
|
||||
"trailing_take_profit_activate": trailing_take_profit_activate,
|
||||
"trailing_take_profit_drawdown": trailing_take_profit_drawdown,
|
||||
|
||||
+95
-18
@@ -1,27 +1,93 @@
|
||||
"""全局配置 — 硬编码,个人工具不依赖 .env。"""
|
||||
"""全局配置 — 从环境变量 / .env 读取。"""
|
||||
from __future__ import annotations
|
||||
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
from pydantic import Field
|
||||
from pydantic import Field, model_validator
|
||||
from pydantic_settings import BaseSettings, SettingsConfigDict
|
||||
|
||||
# ── 运行环境检测 ──────────────────────────────────────────
|
||||
# PyInstaller 打包后: __file__ 指向临时解压目录 _MEIPASS, 不能作为路径基准。
|
||||
# 此时:
|
||||
# - 只读资源 (tiers.yaml / 前端 dist) 放在 _MEIPASS 内
|
||||
# - 可写用户数据 (data_dir) 放在可执行文件旁的用户目录
|
||||
# 非 frozen 模式 (开发/Docker): 保持原有 __file__ 推导, 行为完全不变。
|
||||
_IS_FROZEN = getattr(sys, "frozen", False)
|
||||
|
||||
|
||||
def _user_data_root() -> Path:
|
||||
"""桌面版用户数据根目录。
|
||||
|
||||
定位策略 (按优先级):
|
||||
1. 环境变量 DATA_DIR (pydantic-settings 自动注入到 settings.data_dir, 不在此处理)
|
||||
2. 打包桌面版: exe 同级的 data/ 子目录 (<安装目录>/data/)
|
||||
—— 与程序同处一个总目录 (用户选择的安装目录), 视觉直观, 便于备份/迁移。
|
||||
3. 非 frozen (开发模式): 项目根 data/
|
||||
|
||||
为什么不用 platformdirs 默认 (%LOCALAPPDATA%) 作为主路径:
|
||||
- 落在 C 盘系统目录, 用户不易察觉, 占系统盘空间
|
||||
- 用户期望「数据跟随程序」(便于备份/迁移)
|
||||
为什么放 {app}/data (exe 旁的 data/) 而非 {app} 外的兄弟目录:
|
||||
- 用户体验: 用户选了安装目录, 自然期望「程序和数据都在这」, 单一总目录更直观。
|
||||
- 数据安全: Inno Setup 覆盖安装(升级)时只往 {app} 写新程序文件, 不会清空
|
||||
目录里不在安装清单上的运行时文件 (data/ 即此类), 故覆盖安装不丢数据。
|
||||
(注意: 卸载时需在 .iss 中豁免 data/, 见 packaging/tickflow.iss 的 [UninstallDelete]。)
|
||||
旧版本数据迁移: 见 DataStore._migrate_legacy_data_dir(), 老用户首次启动自动搬迁。
|
||||
"""
|
||||
# 打包桌面版: exe 同级的 data/ 子目录 (与程序同一总目录, 覆盖安装不丢数据)
|
||||
if _IS_FROZEN:
|
||||
exe_dir = Path(sys.executable).resolve().parent
|
||||
return exe_dir / "data"
|
||||
|
||||
# 开发模式: 项目根 data/
|
||||
return _PROJECT_ROOT / "data"
|
||||
|
||||
|
||||
def _resource_root() -> Path:
|
||||
"""只读资源根目录。
|
||||
|
||||
frozen: PyInstaller 解压目录 (_MEIPASS)
|
||||
非 frozen: 项目根目录 (源码树)
|
||||
"""
|
||||
if _IS_FROZEN:
|
||||
# sys._MEIPASS 是 PyInstaller 注入的解压根
|
||||
return Path(getattr(sys, "_MEIPASS", Path(sys.executable).resolve().parent))
|
||||
return Path(__file__).resolve().parent.parent.parent
|
||||
|
||||
|
||||
def _project_root() -> Path:
|
||||
"""项目根目录 (非 frozen 用)。"""
|
||||
return Path(__file__).resolve().parent.parent.parent
|
||||
|
||||
|
||||
_PROJECT_ROOT = _project_root()
|
||||
_RESOURCE_ROOT = _resource_root()
|
||||
|
||||
|
||||
class Settings(BaseSettings):
|
||||
model_config = SettingsConfigDict(
|
||||
env_file=None, # 不读取 .env
|
||||
env_file=str(_RESOURCE_ROOT / ".env") if not _IS_FROZEN else ".env",
|
||||
env_file_encoding="utf-8",
|
||||
extra="ignore",
|
||||
)
|
||||
|
||||
# 数据源 API Key(个人工具直接写死;如分享代码请改为空字符串或从环境变量注入)
|
||||
tickflow_api_key: str = "tk_94a20304993f45b5b0e376b9767597cc"
|
||||
# TickFlow
|
||||
tickflow_api_key: str = Field(default="", description="留空启用 free 模式")
|
||||
|
||||
# AI(可选,留空即关闭)
|
||||
# AI
|
||||
ai_provider: str = "openai_compat"
|
||||
ai_base_url: str = "https://api.deepseek.com/v1"
|
||||
ai_base_url: str = "https://api.alysc.top"
|
||||
ai_api_key: str = ""
|
||||
ai_model: str = "deepseek-chat"
|
||||
ai_daily_token_budget: int = 500_000
|
||||
ai_model: str = "gpt-5.5"
|
||||
ai_codex_command: str = "codex"
|
||||
# 默认浏览器风格 UA,绕过 Cloudflare 等 CDN/WAF 的 Bot 拦截(Issue #8)。
|
||||
# 用户可在 AI 设置页按需修改。
|
||||
ai_user_agent: str = (
|
||||
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
|
||||
"AppleWebKit/537.36 (KHTML, like Gecko) "
|
||||
"Chrome/131.0.0.0 Safari/537.36"
|
||||
)
|
||||
|
||||
# Server
|
||||
host: str = "0.0.0.0"
|
||||
@@ -29,16 +95,27 @@ class Settings(BaseSettings):
|
||||
log_level: str = "INFO"
|
||||
backtest_range_guard: bool = False
|
||||
|
||||
# 访问门控:留空则不启用,部署时通过 ACCESS_UUID 环境变量注入
|
||||
# 优先级:ADMIN_TOKEN > 动态 UUID > ACCESS_UUID
|
||||
access_uuid: str = ""
|
||||
# 管理员初始令牌,硬编码以便开箱即用;如需更安全可改为空字符串并从环境变量 ADMIN_TOKEN 注入
|
||||
admin_token: str = "admin7226132"
|
||||
# Auth — 首次启动时预置访问密码(明文, 仅用于初始化, 详见 services/auth.bootstrap_from_env)
|
||||
# 公网服务器部署时免去 SSH 端口转发设密码的麻烦。写入 auth.json(哈希)后即不再读取。
|
||||
auth_password: str = ""
|
||||
|
||||
# 路径 — 硬编码为 Docker 容器内路径,确保数据持久化
|
||||
data_dir: Path = Path("/app/data")
|
||||
tiers_yaml: Path = Path("/app/tiers.yaml")
|
||||
static_dir: Path = Path("/app/static")
|
||||
# Data — frozen: exe 同级 data/ 子目录; 非 frozen: 项目根 data/
|
||||
# (均可被环境变量 DATA_DIR 覆盖, pydantic-settings 自动注入)
|
||||
data_dir: Path = _user_data_root()
|
||||
|
||||
# tiers.yaml 路径 — frozen: 资源目录内; 非 frozen: 项目根目录
|
||||
tiers_yaml: Path = _RESOURCE_ROOT / "tiers.yaml" if _IS_FROZEN else _PROJECT_ROOT / "tiers.yaml"
|
||||
|
||||
# 静态文件(前端 dist) — frozen: 资源目录的 static/; 非 frozen: frontend/dist
|
||||
static_dir: Path = _RESOURCE_ROOT / "static" if _IS_FROZEN else (_PROJECT_ROOT / "frontend" / "dist")
|
||||
|
||||
@model_validator(mode="after")
|
||||
def _resolve_paths(self) -> Settings:
|
||||
"""确保 data_dir 是绝对路径（环境变量传入的相对路径基于项目根目录解析）。"""
|
||||
if not self.data_dir.is_absolute():
|
||||
# 相对路径基于项目根目录解析，而非 CWD
|
||||
self.data_dir = (_PROJECT_ROOT / self.data_dir).resolve()
|
||||
return self
|
||||
|
||||
@property
|
||||
def use_free_mode(self) -> bool:
|
||||
|
||||
@@ -0,0 +1,8 @@
|
||||
"""Market data provider abstraction.
|
||||
|
||||
Providers normalize external data sources into the internal parquet schema.
|
||||
"""
|
||||
from app.data_providers.base import AssetType, MarketDataProvider, ProviderCapabilities
|
||||
from app.data_providers.registry import get_provider
|
||||
|
||||
__all__ = ["AssetType", "MarketDataProvider", "ProviderCapabilities", "get_provider"]
|
||||
@@ -0,0 +1,68 @@
|
||||
"""Provider contracts for external market data sources.
|
||||
|
||||
The first implementation wraps TickFlow. Other providers (Tushare/AkShare/etc.)
|
||||
should return the same normalized Polars schemas so storage, indicators and
|
||||
backtests stay data-source agnostic.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass
|
||||
from datetime import datetime
|
||||
from typing import Literal, Protocol
|
||||
|
||||
import polars as pl
|
||||
|
||||
AssetType = Literal["stock", "index", "etf"]
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class ProviderCapabilities:
|
||||
instruments: bool = False
|
||||
daily: bool = False
|
||||
adj_factor: bool = False
|
||||
minute: bool = False
|
||||
realtime: bool = False
|
||||
financial: bool = False
|
||||
|
||||
|
||||
class MarketDataProvider(Protocol):
|
||||
name: str
|
||||
capabilities: ProviderCapabilities
|
||||
|
||||
def get_instruments(self, asset_type: AssetType) -> pl.DataFrame:
|
||||
"""Return normalized instruments: symbol/name/code/exchange/asset_type/source."""
|
||||
|
||||
def get_daily(
|
||||
self,
|
||||
symbols: list[str],
|
||||
start_time: datetime | None,
|
||||
end_time: datetime | None,
|
||||
asset_type: AssetType,
|
||||
) -> pl.DataFrame:
|
||||
"""Return normalized daily K rows."""
|
||||
|
||||
def get_adj_factors(
|
||||
self,
|
||||
symbols: list[str],
|
||||
start_time: datetime | None,
|
||||
end_time: datetime | None,
|
||||
asset_type: AssetType,
|
||||
) -> pl.DataFrame:
|
||||
"""Return normalized adjustment factors: symbol/trade_date/ex_factor."""
|
||||
|
||||
def get_minute(
|
||||
self,
|
||||
symbols: list[str],
|
||||
start_time: datetime | None,
|
||||
end_time: datetime | None,
|
||||
asset_type: AssetType,
|
||||
freq: str = "1m",
|
||||
) -> pl.DataFrame:
|
||||
"""Return normalized minute K rows. Implementations may return empty."""
|
||||
|
||||
def get_realtime(
|
||||
self,
|
||||
universes: list[str] | None = None,
|
||||
symbols: list[str] | None = None,
|
||||
) -> pl.DataFrame:
|
||||
"""Return normalized realtime quotes. Implementations may return empty."""
|
||||
@@ -0,0 +1,99 @@
|
||||
"""Normalize provider responses into internal Polars schemas."""
|
||||
from __future__ import annotations
|
||||
|
||||
import polars as pl
|
||||
|
||||
from app.indicators.pipeline import filter_halt_days
|
||||
|
||||
DAILY_COLS = ["symbol", "date", "open", "high", "low", "close", "volume", "amount"]
|
||||
ADJ_FACTOR_COLS = ["symbol", "trade_date", "ex_factor"]
|
||||
INSTRUMENT_COLS = ["symbol", "name", "code", "exchange", "asset_type", "source"]
|
||||
|
||||
|
||||
def to_polars(data) -> pl.DataFrame:
|
||||
if data is None:
|
||||
return pl.DataFrame()
|
||||
if isinstance(data, pl.DataFrame):
|
||||
return data
|
||||
if isinstance(data, dict):
|
||||
rows: list[dict] = []
|
||||
for sym, values in data.items():
|
||||
for item in values or []:
|
||||
row = dict(item or {})
|
||||
row.setdefault("symbol", sym)
|
||||
rows.append(row)
|
||||
return pl.DataFrame(rows) if rows else pl.DataFrame()
|
||||
if hasattr(data, "reset_index"):
|
||||
return pl.from_pandas(data.reset_index())
|
||||
try:
|
||||
return pl.DataFrame(data)
|
||||
except Exception: # noqa: BLE001
|
||||
return pl.DataFrame()
|
||||
|
||||
|
||||
def normalize_daily(data, default_symbol: str | None = None, source: str = "tickflow") -> pl.DataFrame: # noqa: ARG001
|
||||
df = to_polars(data)
|
||||
if df.is_empty():
|
||||
return df
|
||||
rename_map = {
|
||||
"ts_code": "symbol",
|
||||
"trade_date": "date",
|
||||
"datetime": "date",
|
||||
"vol": "volume",
|
||||
"amt": "amount",
|
||||
}
|
||||
df = df.rename({k: v for k, v in rename_map.items() if k in df.columns})
|
||||
if "symbol" not in df.columns and default_symbol:
|
||||
df = df.with_columns(pl.lit(default_symbol).alias("symbol"))
|
||||
if "date" in df.columns and df.schema["date"] != pl.Date:
|
||||
df = df.with_columns(pl.col("date").cast(pl.Date, strict=False))
|
||||
for col in ("open", "high", "low", "close", "volume", "amount"):
|
||||
if col in df.columns:
|
||||
df = df.with_columns(pl.col(col).cast(pl.Float64, strict=False))
|
||||
df = filter_halt_days(df)
|
||||
keep = [c for c in DAILY_COLS if c in df.columns]
|
||||
return df.select(keep) if keep else pl.DataFrame()
|
||||
|
||||
|
||||
def normalize_adj_factors(data, source: str = "tickflow") -> pl.DataFrame: # noqa: ARG001
|
||||
df = to_polars(data)
|
||||
if df.is_empty():
|
||||
return df
|
||||
rename_map = {
|
||||
"timestamp": "trade_date",
|
||||
"date": "trade_date",
|
||||
"adj_factor": "ex_factor",
|
||||
}
|
||||
df = df.rename({k: v for k, v in rename_map.items() if k in df.columns})
|
||||
if "trade_date" in df.columns:
|
||||
if df.schema["trade_date"] in {pl.Int64, pl.Int32, pl.UInt64, pl.UInt32, pl.Float64, pl.Float32}:
|
||||
df = df.with_columns(
|
||||
pl.from_epoch(pl.col("trade_date").cast(pl.Int64), time_unit="ms").dt.date().alias("trade_date")
|
||||
)
|
||||
else:
|
||||
df = df.with_columns(pl.col("trade_date").cast(pl.Date, strict=False))
|
||||
if "ex_factor" in df.columns:
|
||||
df = df.with_columns(pl.col("ex_factor").cast(pl.Float64, strict=False))
|
||||
keep = [c for c in ADJ_FACTOR_COLS if c in df.columns]
|
||||
return df.select(keep).drop_nulls() if len(keep) == len(ADJ_FACTOR_COLS) else pl.DataFrame()
|
||||
|
||||
|
||||
def normalize_instruments(rows: list[dict], asset_type: str, source: str = "tickflow") -> pl.DataFrame:
|
||||
if not rows:
|
||||
return pl.DataFrame()
|
||||
out: list[dict] = []
|
||||
for item in rows:
|
||||
symbol = item.get("symbol")
|
||||
if not symbol:
|
||||
continue
|
||||
out.append({
|
||||
"symbol": str(symbol),
|
||||
"name": item.get("name") or str(symbol),
|
||||
"code": item.get("code") or str(symbol).split(".")[0],
|
||||
"exchange": item.get("exchange"),
|
||||
"asset_type": asset_type,
|
||||
"source": source,
|
||||
})
|
||||
if not out:
|
||||
return pl.DataFrame()
|
||||
return pl.DataFrame(out).select(INSTRUMENT_COLS).unique(subset=["symbol"], keep="last").sort("symbol")
|
||||
@@ -0,0 +1,15 @@
|
||||
"""Provider registry."""
|
||||
from __future__ import annotations
|
||||
|
||||
from app.data_providers.tickflow_provider import TickFlowProvider
|
||||
|
||||
_PROVIDERS = {
|
||||
"tickflow": TickFlowProvider,
|
||||
}
|
||||
|
||||
|
||||
def get_provider(name: str = "tickflow"):
|
||||
provider_cls = _PROVIDERS.get((name or "tickflow").lower())
|
||||
if provider_cls is None:
|
||||
raise ValueError(f"Unsupported data provider: {name}")
|
||||
return provider_cls()
|
||||
@@ -0,0 +1,18 @@
|
||||
"""Internal provider schema column lists."""
|
||||
from __future__ import annotations
|
||||
|
||||
DAILY_COLUMNS = [
|
||||
"symbol", "asset_type", "source", "date", "open", "high", "low", "close",
|
||||
"volume", "amount", "pre_close", "change_pct",
|
||||
]
|
||||
|
||||
ADJ_FACTOR_COLUMNS = ["symbol", "asset_type", "source", "trade_date", "ex_factor"]
|
||||
|
||||
INSTRUMENT_COLUMNS = [
|
||||
"symbol", "name", "exchange", "asset_type", "source", "list_date", "status",
|
||||
]
|
||||
|
||||
MINUTE_COLUMNS = [
|
||||
"symbol", "asset_type", "source", "datetime", "open", "high", "low", "close",
|
||||
"volume", "amount", "freq",
|
||||
]
|
||||
@@ -0,0 +1,120 @@
|
||||
"""TickFlow provider implementation."""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from datetime import datetime
|
||||
|
||||
import polars as pl
|
||||
|
||||
from app.data_providers.base import AssetType, ProviderCapabilities
|
||||
from app.data_providers.normalizer import normalize_adj_factors, normalize_daily, normalize_instruments
|
||||
from app.tickflow.client import get_client
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
_EXCHANGES = ["SH", "SZ", "BJ"]
|
||||
|
||||
|
||||
class TickFlowProvider:
|
||||
name = "tickflow"
|
||||
capabilities = ProviderCapabilities(
|
||||
instruments=True,
|
||||
daily=True,
|
||||
adj_factor=True,
|
||||
minute=True,
|
||||
realtime=True,
|
||||
financial=True,
|
||||
)
|
||||
|
||||
def get_instruments(self, asset_type: AssetType) -> pl.DataFrame:
|
||||
tf = get_client()
|
||||
instrument_type = "stock" if asset_type == "stock" else asset_type
|
||||
rows: list[dict] = []
|
||||
for ex in _EXCHANGES:
|
||||
try:
|
||||
items = tf.exchanges.get_instruments(ex, instrument_type=instrument_type)
|
||||
rows.extend([it for it in (items or []) if isinstance(it, dict)])
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("TickFlow instruments %s/%s failed: %s", ex, instrument_type, e)
|
||||
return normalize_instruments(rows, asset_type=asset_type, source=self.name)
|
||||
|
||||
def get_daily(
|
||||
self,
|
||||
symbols: list[str],
|
||||
start_time: datetime | None,
|
||||
end_time: datetime | None,
|
||||
asset_type: AssetType, # noqa: ARG002
|
||||
) -> pl.DataFrame:
|
||||
if not symbols:
|
||||
return pl.DataFrame()
|
||||
tf = get_client()
|
||||
kwargs = {
|
||||
"period": "1d",
|
||||
"adjust": "none",
|
||||
"count": 10000 if start_time and end_time else 250,
|
||||
"as_dataframe": True,
|
||||
"show_progress": False,
|
||||
}
|
||||
if start_time and end_time:
|
||||
from app.services.kline_sync import _datetime_to_ms
|
||||
kwargs["start_time"] = _datetime_to_ms(start_time)
|
||||
kwargs["end_time"] = _datetime_to_ms(end_time)
|
||||
raw = tf.klines.batch(symbols, **kwargs)
|
||||
frames: list[pl.DataFrame] = []
|
||||
if isinstance(raw, dict):
|
||||
for sym, sub in raw.items():
|
||||
normalized = normalize_daily(sub, default_symbol=sym, source=self.name)
|
||||
if not normalized.is_empty():
|
||||
frames.append(normalized)
|
||||
else:
|
||||
normalized = normalize_daily(raw, source=self.name)
|
||||
if not normalized.is_empty():
|
||||
frames.append(normalized)
|
||||
return pl.concat(frames, how="diagonal_relaxed") if frames else pl.DataFrame()
|
||||
|
||||
def get_adj_factors(
|
||||
self,
|
||||
symbols: list[str],
|
||||
start_time: datetime | None,
|
||||
end_time: datetime | None,
|
||||
asset_type: AssetType, # noqa: ARG002
|
||||
) -> pl.DataFrame:
|
||||
if not symbols:
|
||||
return pl.DataFrame()
|
||||
tf = get_client()
|
||||
kwargs = {"as_dataframe": False}
|
||||
if start_time or end_time:
|
||||
from app.services.kline_sync import _datetime_to_ms
|
||||
if start_time:
|
||||
kwargs["start_time"] = _datetime_to_ms(start_time)
|
||||
if end_time:
|
||||
kwargs["end_time"] = _datetime_to_ms(end_time)
|
||||
raw = tf.klines.ex_factors(symbols, **kwargs)
|
||||
return normalize_adj_factors(raw, source=self.name)
|
||||
|
||||
def get_minute(
|
||||
self,
|
||||
symbols: list[str],
|
||||
start_time: datetime | None,
|
||||
end_time: datetime | None,
|
||||
asset_type: AssetType, # noqa: ARG002
|
||||
freq: str = "1m", # noqa: ARG002
|
||||
) -> pl.DataFrame:
|
||||
# Existing minute sync remains in app.services.kline_sync for now.
|
||||
return pl.DataFrame()
|
||||
|
||||
def get_realtime(
|
||||
self,
|
||||
universes: list[str] | None = None,
|
||||
symbols: list[str] | None = None,
|
||||
) -> pl.DataFrame:
|
||||
tf = get_client()
|
||||
if universes and symbols:
|
||||
raise ValueError("TickFlow realtime accepts either universes or symbols, not both")
|
||||
if universes:
|
||||
resp = tf.quotes.get_by_universes(universes=universes)
|
||||
elif symbols:
|
||||
resp = tf.quotes.get(symbols=symbols)
|
||||
else:
|
||||
return pl.DataFrame()
|
||||
return pl.DataFrame(resp or [])
|
||||
@@ -0,0 +1,241 @@
|
||||
"""桌面客户端入口 — uvicorn 后台服务 + pywebview 桌面窗口。
|
||||
|
||||
运行方式:
|
||||
开发模式: python -m app.desktop (需 pip install pywebview)
|
||||
打包后: 双击可执行文件即可
|
||||
|
||||
职责:
|
||||
1. 单实例锁 — 已运行则聚焦已有窗口并退出
|
||||
2. 选可用端口 — 从 settings.port 起, 被占则递增
|
||||
3. 后台线程起 uvicorn (仅监听 127.0.0.1, 不暴露外网)
|
||||
4. 主线程起 pywebview 窗口渲染前端
|
||||
5. 窗口关闭 → 优雅停止 uvicorn → 进程退出
|
||||
|
||||
不含: 业务逻辑、配置持久化、监控告警 (全在 app.main 里)。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import socket
|
||||
import sys
|
||||
import threading
|
||||
import time
|
||||
from pathlib import Path
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
_APP_NAME = "TickFlow 股票面板"
|
||||
_BASE_PORT = 3018
|
||||
_PORT_PROBE_RANGE = 50 # 从 3018 起最多试 50 个端口
|
||||
|
||||
|
||||
def _ensure_data_dir_writable() -> None:
|
||||
"""确保用户数据目录可写 (lifespan 会创建子目录, 这里只验证根目录)。
|
||||
|
||||
data_dir 在 frozen 模式下指向用户目录 (见 config.py), 非可写会导致
|
||||
DuckDB 视图 / parquet 落盘全失败。提前失败胜过启动后乱报错。
|
||||
"""
|
||||
from app.config import settings
|
||||
|
||||
data_root = settings.data_dir
|
||||
try:
|
||||
data_root.mkdir(parents=True, exist_ok=True)
|
||||
probe = data_root / ".write_probe"
|
||||
probe.write_text("ok", encoding="utf-8")
|
||||
probe.unlink(missing_ok=True)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.error("数据目录不可写, 桌面版无法运行: %s (%s)", data_root, e)
|
||||
raise
|
||||
|
||||
|
||||
def _acquire_single_instance() -> bool:
|
||||
"""单实例锁。已运行返回 False (本进程应退出), 否则 True。
|
||||
|
||||
用 data_dir/.desktop.lock 文件锁实现。跨进程, 文件存在即视为已运行
|
||||
(简单可靠; 不引入 msvcrt/fcntl 平台差异)。
|
||||
"""
|
||||
from app.config import settings
|
||||
|
||||
lock_path = settings.data_dir / ".desktop.lock"
|
||||
if lock_path.exists():
|
||||
# 软检测: 写入进程 PID, 若该 PID 已不存在则视为残留锁, 允许接管
|
||||
try:
|
||||
pid_str = lock_path.read_text(encoding="utf-8").strip()
|
||||
pid = int(pid_str) if pid_str.isdigit() else None
|
||||
except Exception: # noqa: BLE001
|
||||
pid = None
|
||||
|
||||
if pid is not None and _pid_alive(pid):
|
||||
logger.warning("检测到已有实例运行 (PID %d), 本进程退出", pid)
|
||||
return False
|
||||
# 残留锁: 清理后继续
|
||||
logger.info("清理残留单实例锁 (PID %s 已不存在)", pid)
|
||||
|
||||
lock_path.write_text(str(_current_pid()), encoding="utf-8")
|
||||
return True
|
||||
|
||||
|
||||
def _release_single_instance() -> None:
|
||||
from app.config import settings
|
||||
|
||||
lock_path = settings.data_dir / ".desktop.lock"
|
||||
try:
|
||||
lock_path.unlink(missing_ok=True)
|
||||
except Exception: # noqa: BLE001
|
||||
pass
|
||||
|
||||
|
||||
def _pid_alive(pid: int) -> bool:
|
||||
"""检查指定 PID 的进程是否存活。"""
|
||||
import os
|
||||
|
||||
if os.name == "nt":
|
||||
# Windows: 0 表示存在, 其它是异常
|
||||
try:
|
||||
os.kill(pid, 0)
|
||||
return True
|
||||
except OSError:
|
||||
return False
|
||||
else:
|
||||
try:
|
||||
os.kill(pid, 0) # signal 0 = 探测存活, 不实际发信号
|
||||
return True
|
||||
except OSError:
|
||||
return False
|
||||
|
||||
|
||||
def _current_pid() -> int:
|
||||
import os
|
||||
|
||||
return os.getpid()
|
||||
|
||||
|
||||
def _find_free_port(start: int, count: int = _PORT_PROBE_RANGE) -> int:
|
||||
"""从 start 起找第一个可用端口。全部被占则返回 start (交给 uvicorn 报错)。"""
|
||||
for port in range(start, start + count):
|
||||
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
|
||||
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
|
||||
try:
|
||||
s.bind(("127.0.0.1", port))
|
||||
return port
|
||||
except OSError:
|
||||
continue
|
||||
return start
|
||||
|
||||
|
||||
def _run_uvmicorn(port: int, ready_event: threading.Event) -> None:
|
||||
"""后台线程: 启动 uvicorn 服务。ready_event 在线程退出时置位 (通知主线程)。"""
|
||||
import uvicorn
|
||||
|
||||
# 延迟 import app, 确保配置层已就绪 (frozen 检测在 config.py 导入时完成)
|
||||
from app.main import app
|
||||
|
||||
config = uvicorn.Config(
|
||||
app,
|
||||
host="127.0.0.1", # 仅本机, 不暴露外网 (桌面版无需远程访问)
|
||||
port=port,
|
||||
log_level="info",
|
||||
access_log=False, # 桌面版不需要访问日志
|
||||
loop="auto",
|
||||
)
|
||||
server = uvicorn.Server(config)
|
||||
|
||||
# 线程结束时通知主线程 (无论正常退出还是异常)
|
||||
def _signal_done(*exc):
|
||||
ready_event.set()
|
||||
server.config.callback_notify = None # 不用 notify 机制
|
||||
|
||||
try:
|
||||
server.run()
|
||||
finally:
|
||||
ready_event.set()
|
||||
|
||||
|
||||
def _wait_for_server(port: int, timeout: float = 60.0) -> bool:
|
||||
"""轮询 health 接口直到后端就绪或超时。
|
||||
|
||||
比 monkey-patch uvicorn 内部方法更健壮, 不依赖版本内部实现。
|
||||
"""
|
||||
import urllib.request
|
||||
import urllib.error
|
||||
|
||||
url = f"http://127.0.0.1:{port}/health"
|
||||
deadline = time.monotonic() + timeout
|
||||
while time.monotonic() < deadline:
|
||||
try:
|
||||
with urllib.request.urlopen(url, timeout=2) as r:
|
||||
if r.status == 200:
|
||||
return True
|
||||
except (urllib.error.URLError, ConnectionError, OSError):
|
||||
pass
|
||||
time.sleep(0.5)
|
||||
return False
|
||||
|
||||
|
||||
def _open_window(url: str) -> None:
|
||||
"""主线程: 用 pywebview 打开桌面窗口。"""
|
||||
import webview # type: ignore[import-not-found]
|
||||
|
||||
window = webview.create_window(
|
||||
_APP_NAME,
|
||||
url,
|
||||
width=1440,
|
||||
height=900,
|
||||
min_size=(1024, 700),
|
||||
# 桌面版固定单窗口, 禁用外部浏览器跳转
|
||||
confirm_close=False,
|
||||
)
|
||||
# pywebview 会阻塞主线程直到窗口关闭
|
||||
webview.start(debug=False)
|
||||
|
||||
|
||||
def main() -> int:
|
||||
"""桌面客户端主入口。返回进程退出码。"""
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
|
||||
)
|
||||
|
||||
try:
|
||||
_ensure_data_dir_writable()
|
||||
except Exception:
|
||||
# 数据目录不可写是致命错误, 无法继续
|
||||
return 1
|
||||
|
||||
# 单实例: 已运行则退出
|
||||
if not _acquire_single_instance():
|
||||
return 0
|
||||
|
||||
try:
|
||||
port = _find_free_port(_BASE_PORT)
|
||||
logger.info("桌面版后端将监听 127.0.0.1:%d", port)
|
||||
|
||||
# 后台线程起 uvicorn
|
||||
ready = threading.Event()
|
||||
server_thread = threading.Thread(
|
||||
target=_run_uvmicorn, args=(port, ready), daemon=True,
|
||||
name="uvicorn",
|
||||
)
|
||||
server_thread.start()
|
||||
|
||||
# 轮询 health 接口等后端就绪 (含 lifespan 初始化, 最多 60s)
|
||||
if not _wait_for_server(port, timeout=60.0):
|
||||
logger.error("后端启动超时, 桌面版退出")
|
||||
_release_single_instance()
|
||||
return 1
|
||||
|
||||
url = f"http://127.0.0.1:{port}"
|
||||
logger.info("打开桌面窗口: %s", url)
|
||||
_open_window(url)
|
||||
|
||||
# 窗口关闭后, 进程退出 (daemon 线程会被回收)
|
||||
logger.info("窗口已关闭, 桌面版退出")
|
||||
return 0
|
||||
except KeyboardInterrupt:
|
||||
return 0
|
||||
finally:
|
||||
_release_single_instance()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,600 @@
|
||||
"""关键价位计算 —— 独立模块,纯函数,无 IO / 无存储。
|
||||
|
||||
输入: 已经包含 OHLCV 的 polars 日 K DataFrame(内存中,通常来自 KlineRepository 缓存)。
|
||||
输出: 4 类结构化价位点,供:
|
||||
- 图表 markLine 渲染(压力位 / 支撑位 / 成交密集区 / 枢轴点 / 前高前低)
|
||||
- AI 个股分析提示词(价位上下文)
|
||||
|
||||
设计:
|
||||
- 纯函数 + polars 向量化,毫秒级,无需落盘。
|
||||
- 每个点位带 {value, label, type, side, strength?},前端直接画水平价格线。
|
||||
- NaN/Inf 全部过滤,空数据返回空列表,不抛异常。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from typing import Any
|
||||
|
||||
import polars as pl
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 输出结构
|
||||
# ================================================================
|
||||
|
||||
class PriceLevel:
|
||||
"""单个价位点的数据结构(用 dict 表达,这里只作文档说明)。
|
||||
|
||||
{
|
||||
"value": 12.34, # 价格
|
||||
"label": "压力位 R1", # 显示标签
|
||||
"type": "pivot", # 类型分组(同类型用一个开关按钮控制显隐)
|
||||
"side": "resistance", # 方向:resistance(压力) / support(支撑) / neutral
|
||||
"strength": "medium", # 强度:strong / medium / weak(可选,影响线型)
|
||||
"rank": 1, # 档位(仅 pivot 有):0=P,1=R1/S1,2=R2/S2,3=R3/S3
|
||||
# 前端按"显示到第几档"过滤,非 pivot 点位无此字段
|
||||
}
|
||||
"""
|
||||
|
||||
|
||||
# 价位分组 → 开关 key。前端按这个 type 显隐。
|
||||
LEVEL_TYPES = {
|
||||
"sr": "压力支撑", # 成交密集区(价量:Volume Profile POC + 高成交密集区)
|
||||
"pivot": "枢轴点", # 经典 Pivot P/R/S
|
||||
"extreme": "前高前低", # 60/250 日极值 + 近期 swing 高低点
|
||||
"boll": "布林带", # MA20 ± 2σ,标准差波动带(参考性,非真实支撑压力)
|
||||
"keltner_s": "Keltner短期", # MA20 ± 2×ATR
|
||||
"keltner_m": "Keltner中期", # MA60 ± 2.5×ATR
|
||||
"keltner_l": "Keltner长期", # MA120 ± 3×ATR(牛熊趋势边界)
|
||||
"atr_stop": "ATR止损", # close±nATR 动态止盈止损
|
||||
"gap": "缺口位", # 未回补跳空缺口
|
||||
"fib": "斐波那契", # 回撤位 0.236~0.786
|
||||
"round": "整数关口", # 心理整数位
|
||||
}
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 1. 压力位 / 支撑位 —— 成交量分布 (Volume Profile)
|
||||
# ================================================================
|
||||
|
||||
def _support_resistance(df: pl.DataFrame, bins: int = 40) -> list[dict]:
|
||||
"""成交量分布 (Volume Profile) —— 真正基于价+量的支撑/压力位。
|
||||
|
||||
把每个价位层按价格分桶,统计落在该桶的累计成交量,取高成交密集区作为关键
|
||||
价位带。与 BOLL/Keltner 等"波动通道"不同,成交密集区反映的是真实换手堆积,
|
||||
是经典意义的支撑/压力。
|
||||
|
||||
密集区 = 成交量高于均值的桶,按成交量降序取前 3 个作为关键价位带:
|
||||
- POC(控制点):成交量最大的桶,标记为 strong
|
||||
- 其他高成交区:高于均值,标记为 medium
|
||||
"""
|
||||
if df.is_empty() or "volume" not in df.columns or df.height < 20:
|
||||
return []
|
||||
|
||||
hi = float(df["high"].max())
|
||||
lo = float(df["low"].min())
|
||||
if not (hi > lo > 0):
|
||||
return []
|
||||
|
||||
# 每根 K 的价格区间中点 × 成交量 ≈ 该价位层贡献的成交量(简化模型)
|
||||
df2 = df.select([
|
||||
((pl.col("high") + pl.col("low")) / 2).alias("mid"),
|
||||
pl.col("volume").alias("vol"),
|
||||
]).drop_nulls()
|
||||
|
||||
# 桶边界:bins 个桶需要 bins-1 个内部 break,cut 据此切成 bins 段
|
||||
step = (hi - lo) / bins
|
||||
edges = [lo + i * step for i in range(bins + 1)] # 含首尾,共 bins+1 个边界值
|
||||
breaks = edges[1:-1] # 内部 break,bins-1 个
|
||||
bin_labels = [f"{i}" for i in range(bins)] # 桶序号 0..bins-1
|
||||
# 至少要有 1 个不同的内部 break
|
||||
if len(set(f"{b:.6f}" for b in breaks)) < 1:
|
||||
return []
|
||||
|
||||
df2 = df2.with_columns(
|
||||
pl.col("mid").cut(breaks, labels=bin_labels).alias("bin")
|
||||
)
|
||||
prof = df2.group_by("bin").agg(pl.col("vol").sum())
|
||||
if prof.is_empty():
|
||||
return []
|
||||
|
||||
# 把桶序号字符串还原为 int,以便回查 edges;并按序号排序保证可索引
|
||||
prof = prof.with_columns(pl.col("bin").cast(pl.Int64).alias("bi")).sort("bi")
|
||||
bin_ids = prof["bi"].to_list()
|
||||
vols = prof["vol"].to_list()
|
||||
mean_vol = sum(vols) / len(vols) if vols else 0
|
||||
|
||||
def bin_mid(bin_id: int) -> float:
|
||||
return (edges[bin_id] + edges[bin_id + 1]) / 2
|
||||
|
||||
close = float(df.tail(1)["close"][0])
|
||||
|
||||
out: list[dict] = []
|
||||
# POC:成交量最大的桶
|
||||
poc_pos = max(range(len(vols)), key=lambda i: vols[i])
|
||||
poc_mid = bin_mid(bin_ids[poc_pos])
|
||||
out.append({"value": round(poc_mid, 2), "label": "成交密集区(POC)",
|
||||
"type": "sr", "side": _side(poc_mid, close), "strength": "strong"})
|
||||
|
||||
# 其他高成交区(高于均值,排除 POC),按成交量降序取 2 个
|
||||
candidates = [(i, v) for i, v in enumerate(vols) if v > mean_vol and i != poc_pos]
|
||||
candidates.sort(key=lambda x: x[1], reverse=True)
|
||||
for i, _v in candidates[:2]:
|
||||
mid = bin_mid(bin_ids[i])
|
||||
out.append({"value": round(mid, 2), "label": "成交密集区",
|
||||
"type": "sr", "side": _side(mid, close), "strength": "medium"})
|
||||
return out
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 2. 枢轴点 (Pivot Point) —— 经典公式,基于最近完整交易日
|
||||
# ================================================================
|
||||
|
||||
def _pivot_points(df: pl.DataFrame) -> list[dict]:
|
||||
"""经典 Pivot:P = (H+L+C)/3, R1/R2/R3, S1/S2/S3。
|
||||
|
||||
基准:最后 1 根 K(代表"上一交易日")。实务中常用前一日,这里取最后一根。
|
||||
"""
|
||||
if df.is_empty():
|
||||
return []
|
||||
last = df.tail(1)
|
||||
h = last["high"][0]
|
||||
l = last["low"][0]
|
||||
c = last["close"][0]
|
||||
if not _ok(h) or not _ok(l) or not _ok(c):
|
||||
return []
|
||||
|
||||
h, l, c = float(h), float(l), float(c)
|
||||
p = (h + l + c) / 3
|
||||
r1 = 2 * p - l
|
||||
s1 = 2 * p - h
|
||||
r2 = p + (h - l)
|
||||
s2 = p - (h - l)
|
||||
r3 = h + 2 * (p - l)
|
||||
s3 = l - 2 * (h - p)
|
||||
|
||||
def lv(v: float, label: str, side: str, strength: str, rank: int) -> dict:
|
||||
# rank:档位标记,前端据此按"显示到第几档"过滤
|
||||
# 0 = 枢轴位 P(始终显示)
|
||||
# 1 = R1/S1(第一档压力/支撑)
|
||||
# 2 = R2/S2(第二档)
|
||||
# 3 = R3/S3(第三档,极端,实际很少触及)
|
||||
return {"value": round(v, 2), "label": label, "type": "pivot",
|
||||
"side": side, "strength": strength, "rank": rank}
|
||||
|
||||
return [
|
||||
lv(p, "枢轴位 P", "neutral", "strong", 0),
|
||||
lv(r1, "压力位 R1", "resistance", "medium", 1),
|
||||
lv(r2, "压力位 R2", "resistance", "medium", 2),
|
||||
lv(r3, "压力位 R3", "resistance", "weak", 3),
|
||||
lv(s1, "支撑位 S1", "support", "medium", 1),
|
||||
lv(s2, "支撑位 S2", "support", "medium", 2),
|
||||
lv(s3, "支撑位 S3", "support", "weak", 3),
|
||||
]
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 3. 前高 / 前低 —— 60 / 120 / 250 日极值
|
||||
# ================================================================
|
||||
|
||||
def _extreme_levels(df: pl.DataFrame) -> list[dict]:
|
||||
"""关键前高 / 前低 —— 历史极值 + 近期 swing 高低点(收敛后)。
|
||||
|
||||
设计:把所有"前高前低"类点位集中在本组,与 sr(通道)区分:
|
||||
- 60 日极值:近一季度高低点(短期参照)
|
||||
- 250 日极值:年度高低点(牛熊分界参照);跳过 120 日(被 250 日包含,信息冗余)
|
||||
- swing 高低点:近期局部转折点,每侧只取距当前价最近的 2 个
|
||||
"""
|
||||
if df.is_empty():
|
||||
return []
|
||||
close = float(df.tail(1)["close"][0]) if "close" in df.columns else None
|
||||
out: list[dict] = []
|
||||
|
||||
# —— 历史极值(只取 60 / 250,避免中间档冗余)——
|
||||
for n in (60, 250):
|
||||
if df.height < n:
|
||||
continue
|
||||
sub = df.tail(n)
|
||||
hi = float(sub["high"].max())
|
||||
lo = float(sub["low"].min())
|
||||
if _ok(hi):
|
||||
out.append({"value": round(hi, 2), "label": f"{n}日新高",
|
||||
"type": "extreme", "side": "resistance", "strength": "strong"})
|
||||
if _ok(lo):
|
||||
out.append({"value": round(lo, 2), "label": f"{n}日新低",
|
||||
"type": "extreme", "side": "support", "strength": "strong"})
|
||||
|
||||
# —— 近期 swing 高低点(每侧只取距当前价最近的 2 个,避免点位爆炸)——
|
||||
win = 5
|
||||
if df.height > win * 2 and close:
|
||||
highs = df["high"].to_list()
|
||||
lows = df["low"].to_list()
|
||||
swing_highs: list[float] = []
|
||||
swing_lows: list[float] = []
|
||||
for i in range(win, len(highs) - win):
|
||||
if highs[i] == max(highs[i - win:i + win + 1]):
|
||||
swing_highs.append(float(highs[i]))
|
||||
if lows[i] == min(lows[i - win:i + win + 1]):
|
||||
swing_lows.append(float(lows[i]))
|
||||
|
||||
# 聚合 ±1% 相近价位,再按距当前价排序取最近 2 个
|
||||
agg_h = _aggregate_levels(swing_highs, 0.01)
|
||||
agg_h = [v for v in agg_h if v > close * 1.001]
|
||||
agg_h.sort(key=lambda v: abs(v - close))
|
||||
for v in agg_h[:2]:
|
||||
out.append({"value": round(v, 2), "label": "前高",
|
||||
"type": "extreme", "side": "resistance", "strength": "medium"})
|
||||
|
||||
agg_l = _aggregate_levels(swing_lows, 0.01)
|
||||
agg_l = [v for v in agg_l if v < close * 0.999]
|
||||
agg_l.sort(key=lambda v: abs(v - close))
|
||||
for v in agg_l[:2]:
|
||||
out.append({"value": round(v, 2), "label": "前低",
|
||||
"type": "extreme", "side": "support", "strength": "medium"})
|
||||
|
||||
return out
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 4. 波动通道 —— 布林带 + Keltner 三档,各自独立开关
|
||||
# ================================================================
|
||||
|
||||
def _ma_value(df: pl.DataFrame, ma_col: str | None, window: int) -> float | None:
|
||||
"""取某档均线值:优先用预计算列,缺失则现场 rolling_mean。"""
|
||||
last = df.tail(1)
|
||||
if ma_col and ma_col in df.columns:
|
||||
v = last[ma_col][0]
|
||||
return float(v) if _ok(v) else None
|
||||
if df.height >= window:
|
||||
v = df.select(pl.col("close").rolling_mean(window)).tail(1)["close"][0]
|
||||
return float(v) if _ok(v) else None
|
||||
return None
|
||||
|
||||
|
||||
def _keltner_band(
|
||||
df: pl.DataFrame, ma_col: str | None, window: int, n: float,
|
||||
label_short: str, type_key: str,
|
||||
) -> list[dict]:
|
||||
"""单档 Keltner 通道:均线 ± n×ATR。
|
||||
|
||||
ATR 自适应波动,通道宽度随行情自动收缩/扩张。type_key 决定归入哪一组
|
||||
(keltner_s / keltner_m / keltner_l),前端各自独立开关。
|
||||
"""
|
||||
if df.is_empty() or df.height < 20 or "atr_14" not in df.columns:
|
||||
return []
|
||||
last = df.tail(1)
|
||||
close = float(last["close"][0]) if "close" in df.columns else 0
|
||||
atr = float(last["atr_14"][0])
|
||||
if not close or not _ok(atr):
|
||||
return []
|
||||
|
||||
ma_val = _ma_value(df, ma_col, window)
|
||||
if ma_val is None:
|
||||
return []
|
||||
upper = ma_val + n * atr
|
||||
lower = ma_val - n * atr
|
||||
return [
|
||||
{"value": round(upper, 2), "label": f"{label_short}通道上轨",
|
||||
"type": type_key, "side": _side(upper, close), "strength": "medium"},
|
||||
{"value": round(lower, 2), "label": f"{label_short}通道下轨",
|
||||
"type": type_key, "side": _side(lower, close), "strength": "medium"},
|
||||
]
|
||||
|
||||
|
||||
def _boll_channel(df: pl.DataFrame) -> list[dict]:
|
||||
"""布林带上下轨(MA20 ± 2σ)。
|
||||
|
||||
基于标准差的波动带,反映价格相对均线的统计偏离;非真实支撑压力,
|
||||
仅作波动边界参考。数据直接取预计算列 boll_upper/boll_lower。
|
||||
"""
|
||||
if df.is_empty() or "boll_upper" not in df.columns or "boll_lower" not in df.columns:
|
||||
return []
|
||||
last = df.tail(1)
|
||||
close = float(last["close"][0]) if "close" in df.columns else 0
|
||||
if not close:
|
||||
return []
|
||||
bu = last["boll_upper"][0]
|
||||
bl = last["boll_lower"][0]
|
||||
if not _ok(bu) or not _ok(bl):
|
||||
return []
|
||||
bu, bl = float(bu), float(bl)
|
||||
out = [
|
||||
{"value": round(bu, 2), "label": "布林上轨",
|
||||
"type": "boll", "side": _side(bu, close), "strength": "medium"},
|
||||
{"value": round(bl, 2), "label": "布林下轨",
|
||||
"type": "boll", "side": _side(bl, close), "strength": "medium"},
|
||||
]
|
||||
# 布林中轨 = MA20(多空平衡线,价格在其上下分强弱);数据层已预计算 ma20
|
||||
if "ma20" in df.columns:
|
||||
mid = last["ma20"][0]
|
||||
if _ok(mid):
|
||||
mid = float(mid)
|
||||
out.append({"value": round(mid, 2), "label": "布林中轨",
|
||||
"type": "boll", "side": _side(mid, close), "strength": "medium"})
|
||||
return out
|
||||
|
||||
|
||||
def _keltner_short(df: pl.DataFrame) -> list[dict]:
|
||||
"""Keltner 短期:MA20 ± 2×ATR(近期波动带,约一个月)。"""
|
||||
return _keltner_band(df, "ma20", 20, 2.0, "短期", "keltner_s")
|
||||
|
||||
|
||||
def _keltner_mid(df: pl.DataFrame) -> list[dict]:
|
||||
"""Keltner 中期:MA60 ± 2.5×ATR(季度波动带)。"""
|
||||
return _keltner_band(df, "ma60", 60, 2.5, "中期", "keltner_m")
|
||||
|
||||
|
||||
def _keltner_long(df: pl.DataFrame) -> list[dict]:
|
||||
"""Keltner 长期:MA120 ± 3×ATR(半年波动带,牛熊趋势边界)。"""
|
||||
return _keltner_band(df, None, 120, 3.0, "长期", "keltner_l")
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 5. ATR 止损位 —— close ± n × ATR,动态止盈止损
|
||||
# ================================================================
|
||||
|
||||
def _atr_stops(df: pl.DataFrame) -> list[dict]:
|
||||
"""基于 ATR 的动态止损/止盈位。
|
||||
|
||||
ATR 衡量平均真实波幅,close ± n×ATR 是交易者最常用的止损位算法:
|
||||
- 止损位:close - 2×ATR (跌破即趋势破坏)
|
||||
- 止盈位:close + 2×ATR (突破即顺势扩展)
|
||||
- 近端波动带:close ± 1.5×ATR (中短期风控参考)
|
||||
"""
|
||||
if df.is_empty() or "atr_14" not in df.columns:
|
||||
return []
|
||||
last = df.tail(1)
|
||||
close = float(last["close"][0])
|
||||
atr = float(last["atr_14"][0])
|
||||
if not _ok(close) or not _ok(atr):
|
||||
return []
|
||||
|
||||
def lv(v: float, label: str, side: str, strength: str) -> dict:
|
||||
return {"value": round(v, 2), "label": label, "type": "atr_stop",
|
||||
"side": side, "strength": strength}
|
||||
|
||||
return [
|
||||
lv(close + 2 * atr, "ATR 止盈(+2)", "resistance", "medium"),
|
||||
lv(close + 1.5 * atr, "ATR 上轨(+1.5)", "resistance", "weak"),
|
||||
lv(close - 1.5 * atr, "ATR 下轨(-1.5)", "support", "weak"),
|
||||
lv(close - 2 * atr, "ATR 止损(-2)", "support", "medium"),
|
||||
]
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 6. 缺口位 (Gap) —— 未回补的跳空缺口
|
||||
# ================================================================
|
||||
|
||||
def _gap_levels(df: pl.DataFrame, lookback: int = 120) -> list[dict]:
|
||||
"""近期未回补的向上/向下跳空缺口。
|
||||
|
||||
向上缺口:当日 low > 前日 high(开盘跳空高开,全天未回补)
|
||||
向下缺口:当日 high < 前日 low(开盘跳空低开,全天未回补)
|
||||
|
||||
缺口是天然的支撑/阻力位。只保留"未回补"的(后续价格未回到缺口区间内),
|
||||
并按价格聚合相近缺口(±0.5%),每方向只取距当前价最近的 2~3 个。
|
||||
"""
|
||||
if df.is_empty() or df.height < 5:
|
||||
return []
|
||||
sub = df.tail(lookback) if df.height > lookback else df
|
||||
close = float(df.tail(1)["close"][0])
|
||||
highs = sub["high"].to_list()
|
||||
lows = sub["low"].to_list()
|
||||
|
||||
up_gaps: list[tuple[float, float]] = [] # (缺口低点, 缺口高点)
|
||||
dn_gaps: list[tuple[float, float]] = []
|
||||
for i in range(1, len(highs)):
|
||||
if _ok(highs[i]) and _ok(lows[i]) and _ok(highs[i - 1]) and _ok(lows[i - 1]):
|
||||
if lows[i] > highs[i - 1]: # 向上缺口
|
||||
up_gaps.append((highs[i - 1], lows[i]))
|
||||
elif highs[i] < lows[i - 1]: # 向下缺口
|
||||
dn_gaps.append((highs[i], lows[i - 1]))
|
||||
|
||||
def _filter_unfilled(gaps: list[tuple[float, float]], is_up: bool) -> list[float]:
|
||||
"""过滤掉已被后续价格回补的缺口,取缺口价位中点。"""
|
||||
mids: list[float] = []
|
||||
for g_lo, g_hi in gaps:
|
||||
# 未回补判定:当前价不在缺口区间内
|
||||
if is_up and close >= g_hi: # 向上缺口:价格已超过缺口上沿 = 未回补(站在缺口上方)
|
||||
mids.append((g_lo + g_hi) / 2)
|
||||
elif not is_up and close <= g_lo: # 向下缺口:价格已低于缺口下沿 = 未回补
|
||||
mids.append((g_lo + g_hi) / 2)
|
||||
# 聚合相近缺口 + 按距当前价排序取最近 3 个
|
||||
agg = _aggregate_levels(mids, 0.005)
|
||||
agg.sort(key=lambda v: abs(v - close))
|
||||
return agg[:3]
|
||||
|
||||
out: list[dict] = []
|
||||
for mid in _filter_unfilled(up_gaps, True):
|
||||
out.append({"value": round(mid, 2), "label": "向上缺口",
|
||||
"type": "gap", "side": _side(mid, close), "strength": "medium"})
|
||||
for mid in _filter_unfilled(dn_gaps, False):
|
||||
out.append({"value": round(mid, 2), "label": "向下缺口",
|
||||
"type": "gap", "side": _side(mid, close), "strength": "medium"})
|
||||
return out
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 7. 斐波那契回撤 —— 基于近期波段的回撤位
|
||||
# ================================================================
|
||||
|
||||
def _fibonacci_levels(df: pl.DataFrame, window: int = 120) -> list[dict]:
|
||||
"""基于近期一段明确趋势的斐波那契回撤位。
|
||||
|
||||
取近 window 个交易日的最高/最低点:
|
||||
- 若高点出现在低点之后(上涨波段):从低到高,回撤 = high - range × ratio
|
||||
- 若低点出现在高点之后(下跌波段):从高到低,回撤 = low + range × ratio
|
||||
比率:0.236 / 0.382 / 0.5 / 0.618 / 0.786
|
||||
"""
|
||||
if df.is_empty() or df.height < 10:
|
||||
return []
|
||||
sub = df.tail(window) if df.height > window else df
|
||||
close = float(df.tail(1)["close"][0])
|
||||
|
||||
highs = sub["high"].to_list()
|
||||
lows = sub["low"].to_list()
|
||||
hi_pos = highs.index(max(highs))
|
||||
lo_pos = lows.index(min(lows))
|
||||
hi_val = float(highs[hi_pos])
|
||||
lo_val = float(lows[lo_pos])
|
||||
if not _ok(hi_val) or not _ok(lo_val) or hi_val <= lo_val:
|
||||
return []
|
||||
|
||||
ratios = [0.236, 0.382, 0.5, 0.618, 0.786]
|
||||
rng = hi_val - lo_val
|
||||
|
||||
out: list[dict] = []
|
||||
# 判断波段方向:高点在低点之后 = 上涨波段(从低回撤)
|
||||
up_trend = hi_pos > lo_pos
|
||||
for r in ratios:
|
||||
if up_trend:
|
||||
val = hi_val - rng * r # 从高点向下回撤
|
||||
else:
|
||||
val = lo_val + rng * r # 从低点向上回撤
|
||||
out.append({"value": round(val, 2), "label": f"Fib {int(r * 1000) / 10:.1f}%",
|
||||
"type": "fib", "side": _side(val, close), "strength": "medium"})
|
||||
return out
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 8. 整数关口 —— 心理支撑/阻力位
|
||||
# ================================================================
|
||||
|
||||
def _round_numbers(df: pl.DataFrame, pct: float = 0.10, max_count: int = 8) -> list[dict]:
|
||||
"""当前价附近的心理整数关口。
|
||||
|
||||
整数位(如 10/11/12元,或 60/65/70元)是天然的心理支撑/阻力,
|
||||
低价股尤其明显。按价格量级自适应步长:
|
||||
- 价格 < 10: 步长 0.5 (如 6.5, 7.0, 7.5)
|
||||
- 价格 < 20: 步长 1 (如 11, 12, 13)
|
||||
- 价格 < 100: 步长 5 (如 60, 65, 70)
|
||||
- 价格 < 500: 步长 10 (如 110, 120, 130)
|
||||
- 价格 >= 500: 步长 50 (如 1100, 1150, 1200)
|
||||
过滤掉距当前价 <1% 的(太近,无分析价值),最多 max_count 个。
|
||||
"""
|
||||
if df.is_empty():
|
||||
return []
|
||||
close = float(df.tail(1)["close"][0])
|
||||
if not _ok(close):
|
||||
return []
|
||||
|
||||
if close < 10:
|
||||
step = 0.5
|
||||
elif close < 20:
|
||||
step = 1.0
|
||||
elif close < 100:
|
||||
step = 5.0
|
||||
elif close < 500:
|
||||
step = 10.0
|
||||
else:
|
||||
step = 50.0
|
||||
|
||||
lo = close * (1 - pct)
|
||||
hi = close * (1 + pct)
|
||||
# 找区间 [lo, hi] 内所有 step 的整数倍(严格限定在区间内)
|
||||
start = (int(lo / step) + (1 if lo % step > 0 else 0)) * step
|
||||
candidates: list[float] = []
|
||||
v = start
|
||||
while v <= hi:
|
||||
if v > 0:
|
||||
candidates.append(round(v, 2))
|
||||
v += step
|
||||
|
||||
# 按距当前价从近到远排序,取前 max_count 个
|
||||
candidates.sort(key=lambda x: abs(x - close))
|
||||
out: list[dict] = []
|
||||
for v in candidates[:max_count]:
|
||||
# 过滤距当前价 <1% 的(太近,无分析价值)
|
||||
if abs(v - close) / close < 0.01:
|
||||
continue
|
||||
out.append({"value": round(v, 2), "label": f"整数关口 {v:g}",
|
||||
"type": "round", "side": _side(v, close), "strength": "weak"})
|
||||
return out
|
||||
|
||||
def compute_levels(df: pl.DataFrame) -> dict[str, list[dict]]:
|
||||
"""计算 11 类价位点,返回 {分组key: [点位...]}。
|
||||
|
||||
分组 key 与 LEVEL_TYPES 一致(sr / pivot / extreme / boll /
|
||||
keltner_s / keltner_m / keltner_l / atr_stop / gap / fib / round),
|
||||
前端按 key 渲染开关按钮,逐组显隐。
|
||||
"""
|
||||
if df.is_empty():
|
||||
return {k: [] for k in LEVEL_TYPES}
|
||||
|
||||
try:
|
||||
return {
|
||||
"sr": _support_resistance(df),
|
||||
"pivot": _pivot_points(df),
|
||||
"extreme": _extreme_levels(df),
|
||||
"boll": _boll_channel(df),
|
||||
"keltner_s": _keltner_short(df),
|
||||
"keltner_m": _keltner_mid(df),
|
||||
"keltner_l": _keltner_long(df),
|
||||
"atr_stop": _atr_stops(df),
|
||||
"gap": _gap_levels(df),
|
||||
"fib": _fibonacci_levels(df),
|
||||
"round": _round_numbers(df),
|
||||
}
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("compute_levels failed: %s", e)
|
||||
return {k: [] for k in LEVEL_TYPES}
|
||||
|
||||
|
||||
def summarize_levels(levels: dict[str, list[dict]], close: float | None) -> str:
|
||||
"""生成给 AI 提示词的价位摘要文本(紧凑,供上下文)。"""
|
||||
if not close:
|
||||
return "无价位数据"
|
||||
parts: list[str] = []
|
||||
# 当前价
|
||||
parts.append(f"当前价 {close:.2f}")
|
||||
# 每组取前 2 个最相关的(距当前价近的优先)
|
||||
for key, label in LEVEL_TYPES.items():
|
||||
pts = levels.get(key, [])
|
||||
if not pts:
|
||||
continue
|
||||
# 按距当前价排序,取前 2
|
||||
ranked = sorted(pts, key=lambda p: abs(p["value"] - close))[:2]
|
||||
desc = "、".join(
|
||||
f"{p['label']}={p['value']}" for p in ranked
|
||||
)
|
||||
parts.append(f"{label}: {desc}")
|
||||
return " · ".join(parts)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 内部工具
|
||||
# ================================================================
|
||||
|
||||
def _ok(v: Any) -> bool:
|
||||
"""数值有效(非空/非 NaN/非 Inf/正数)。"""
|
||||
try:
|
||||
f = float(v)
|
||||
except (TypeError, ValueError):
|
||||
return False
|
||||
import math
|
||||
return math.isfinite(f) and f > 0
|
||||
|
||||
|
||||
def _side(level: float, close: float) -> str:
|
||||
"""价位相对当前价的方向。"""
|
||||
if level > close * 1.001:
|
||||
return "resistance"
|
||||
if level < close * 0.999:
|
||||
return "support"
|
||||
return "neutral"
|
||||
|
||||
|
||||
def _aggregate_levels(values: list[float], tol: float) -> list[float]:
|
||||
"""把相近的价位聚合(±tol),返回去重后的代表值(保留最新)。"""
|
||||
if not values:
|
||||
return []
|
||||
values = sorted(values)
|
||||
out: list[float] = [values[0]]
|
||||
for v in values[1:]:
|
||||
if abs(v - out[-1]) / out[-1] <= tol:
|
||||
out[-1] = v # 聚合到最新(更近期)
|
||||
else:
|
||||
out.append(v)
|
||||
return out
|
||||
@@ -1381,8 +1381,9 @@ def compute_enriched_today(
|
||||
def _compute_limit_signals_today(df: pl.DataFrame, instruments: pl.DataFrame) -> pl.DataFrame:
|
||||
"""盘中增量版的涨跌停/换手率/炸板/连板计算。"""
|
||||
inst_cols = ["symbol"]
|
||||
if "float_shares" in instruments.columns:
|
||||
inst_cols.append("float_shares")
|
||||
for c in ["float_shares", "limit_up", "limit_down"]:
|
||||
if c in instruments.columns:
|
||||
inst_cols.append(c)
|
||||
inst_subset = instruments.select(inst_cols).unique(subset=["symbol"])
|
||||
if "name" in instruments.columns:
|
||||
st_flag = (
|
||||
@@ -1431,14 +1432,31 @@ def _compute_limit_signals_today(df: pl.DataFrame, instruments: pl.DataFrame) ->
|
||||
limit_up_price = _limit_price(prev_raw, limit_pct, up=True)
|
||||
limit_down_price = _limit_price(prev_raw, limit_pct, up=False)
|
||||
|
||||
# 生效涨跌停价: 优先用维表权威值 (instruments.limit_up/down, 交易所级别精确价),
|
||||
# 维表缺失 (新股上市前 5 日: limit_up 为 null 或哨兵 100000) 回退自算理论价。
|
||||
# 哨兵阈值 10000 用于识别 "新股无涨跌停限制" 的占位值 (实际涨停价不可能上万)。
|
||||
_SENTINEL = 10000.0
|
||||
if "limit_up" in df.columns:
|
||||
effective_limit_up = pl.when(
|
||||
pl.col("limit_up").is_not_null() & (pl.col("limit_up") < _SENTINEL)
|
||||
).then(pl.col("limit_up")).otherwise(limit_up_price)
|
||||
else:
|
||||
effective_limit_up = limit_up_price
|
||||
if "limit_down" in df.columns:
|
||||
effective_limit_down = pl.when(
|
||||
pl.col("limit_down").is_not_null() & (pl.col("limit_down") < _SENTINEL)
|
||||
).then(pl.col("limit_down")).otherwise(limit_down_price)
|
||||
else:
|
||||
effective_limit_down = limit_down_price
|
||||
|
||||
is_limit_up = (
|
||||
pl.when((prev_raw > 0) & (pl.col("raw_close") > 0))
|
||||
.then((pl.col("raw_close") - limit_up_price).abs() < 0.005)
|
||||
.then(pl.col("raw_close") >= (effective_limit_up - 0.005))
|
||||
.otherwise(None).cast(pl.Boolean)
|
||||
)
|
||||
is_limit_down = (
|
||||
pl.when((prev_raw > 0) & (pl.col("raw_close") > 0))
|
||||
.then((pl.col("raw_close") - limit_down_price).abs() < 0.005)
|
||||
.then(pl.col("raw_close") <= (effective_limit_down + 0.005))
|
||||
.otherwise(None).cast(pl.Boolean)
|
||||
)
|
||||
|
||||
@@ -1449,7 +1467,7 @@ def _compute_limit_signals_today(df: pl.DataFrame, instruments: pl.DataFrame) ->
|
||||
pl.when(prev_raw > 0)
|
||||
.then(
|
||||
(~is_limit_down.fill_null(True))
|
||||
& (pl.col("low") <= limit_down_price + 0.005)
|
||||
& (pl.col("low") <= effective_limit_down + 0.005)
|
||||
& (pl.col("close") > pl.col("open"))
|
||||
).otherwise(None).cast(pl.Boolean)
|
||||
.alias("signal_limit_down_recovery"),
|
||||
@@ -1457,7 +1475,7 @@ def _compute_limit_signals_today(df: pl.DataFrame, instruments: pl.DataFrame) ->
|
||||
pl.when((prev_raw > 0) & (pl.col("raw_high") > 0))
|
||||
.then(
|
||||
(~is_limit_up.fill_null(True))
|
||||
& (pl.col("raw_high") >= limit_up_price - 0.005)
|
||||
& (pl.col("raw_high") >= effective_limit_up - 0.005)
|
||||
).otherwise(None).cast(pl.Boolean)
|
||||
.alias("signal_broken_limit_up"),
|
||||
])
|
||||
@@ -1482,7 +1500,7 @@ def _compute_limit_signals_today(df: pl.DataFrame, instruments: pl.DataFrame) ->
|
||||
])
|
||||
|
||||
# 清理
|
||||
cleanup = ["_limit_pct", "_is_st"]
|
||||
cleanup = ["_limit_pct", "_is_st", "limit_up", "limit_down"]
|
||||
for c in df.columns:
|
||||
if c.endswith("_inst"):
|
||||
cleanup.append(c)
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
"""盘后管道 + 盘前维表同步。
|
||||
|
||||
调度:
|
||||
09:10 盘前 — 同步标的维表 instruments (全量覆盖)
|
||||
09:10 盘前 — 同步个股维表 instruments (全量覆盖)
|
||||
15:30 盘后 — 日K同步 + 增量除权因子 + enriched 计算 + 刷新视图
|
||||
|
||||
盘后同步策略:
|
||||
@@ -20,7 +20,7 @@ from apscheduler.triggers.cron import CronTrigger
|
||||
|
||||
from app.indicators.pipeline import run_pipeline
|
||||
from app.config import settings
|
||||
from app.services import index_sync, instrument_sync, kline_sync
|
||||
from app.services import index_sync, instrument_sync, kline_sync, preferences as _prefs
|
||||
from app.tickflow.capabilities import Cap, CapabilitySet
|
||||
from app.tickflow.pools import DEMO_SYMBOLS, get_pool
|
||||
from app.tickflow.repository import KlineRepository
|
||||
@@ -69,7 +69,7 @@ def _resolve_universe(capset: CapabilitySet) -> list[str]:
|
||||
|
||||
|
||||
def run_instruments_sync(repo: KlineRepository) -> dict:
|
||||
"""盘前同步标的维表。"""
|
||||
"""盘前同步个股维表。"""
|
||||
rows = instrument_sync.sync_instruments(repo.store.data_dir)
|
||||
_refresh_instruments_view(repo)
|
||||
_invalidate("instruments")
|
||||
@@ -89,12 +89,12 @@ def run_now(
|
||||
emit = on_progress or _noop
|
||||
skipped: list[str] = []
|
||||
|
||||
# Step 0: 先同步标的维表, 再解析标的池 — 确保标的池基于最新 instruments
|
||||
emit("sync_instruments", 2, "同步标的维表…")
|
||||
# Step 0: 先同步个股维表, 再解析标的池 — 确保标的池基于最新 instruments
|
||||
emit("sync_instruments", 2, "同步个股维表…")
|
||||
inst_rows = instrument_sync.sync_instruments(repo.store.data_dir)
|
||||
if inst_rows > 0:
|
||||
_refresh_instruments_view(repo)
|
||||
emit("sync_instruments", 8, f"标的维表同步完成,{inst_rows} 只标的")
|
||||
emit("sync_instruments", 8, f"个股维表同步完成,{inst_rows} 只标的")
|
||||
_invalidate("instruments")
|
||||
|
||||
emit("resolve_universe", 9, "解析标的池…")
|
||||
@@ -102,27 +102,41 @@ def run_now(
|
||||
emit("resolve_universe", 10, f"标的池规模:{len(universe)} 只")
|
||||
|
||||
# Step 1: 日 K 同步
|
||||
# 今天有数据 → 实时行情接口拉一次覆写（1请求全市场）
|
||||
# 今天没数据 → batch K-line API 补齐
|
||||
# 付费档 + 今天有数据 → 实时行情接口拉一次覆写（1请求全市场）
|
||||
# 有历史数据 → batch K-line API 补齐缺口
|
||||
# 无任何数据 → batch K-line API 拉首次 1 年
|
||||
from datetime import date as _date, timedelta as _td, datetime as _dt
|
||||
latest_daily = repo.latest_daily_date()
|
||||
today = _date.today()
|
||||
today_exists = latest_daily and latest_daily >= today
|
||||
new_daily_days = 0
|
||||
# 日K范围拉取的起点(分支3补缺口/分支4首次); 实时增量/跳过时为 None。
|
||||
# 供 Step 1.5 除权因子回溯范围对齐: 范围拉取→用日K范围, 非范围→最近N天兜底。
|
||||
daily_range_start: _date | None = None
|
||||
|
||||
if today_exists:
|
||||
# 今天有数据（QuoteService 已落盘）→ 实时行情覆写，确保最新
|
||||
# A 股日K拉取开关(默认开);关闭时跳过日K同步,保留已有数据
|
||||
pull_a_share = _prefs.get_pipeline_pull_a_share()
|
||||
if not pull_a_share:
|
||||
emit("sync_daily", 45, "已跳过 A 股日K同步(拉取内容未勾选)")
|
||||
logger.info("sync_daily: skipped (pipeline_pull_a_share=False)")
|
||||
elif today_exists and capset.has(Cap.QUOTE_POOL):
|
||||
# 付费档:今天有数据(QuoteService 已落盘)→ 实时行情覆写,确保最新。
|
||||
# free/none 档无 quote.pool 能力,即便今天已有数据(如从 expert 降级),
|
||||
# 也降级到下方 batch 路径刷新,避免调用无权限的实时行情接口。
|
||||
emit("sync_daily", 12, f"获取日K [{today} ~ {today}] 实时行情…")
|
||||
written_daily = kline_sync.sync_daily_by_quotes(repo)
|
||||
new_daily_days = 1
|
||||
emit("sync_daily", 45, f"日K 完成,{written_daily} 只标的")
|
||||
logger.info("sync_daily: [%s ~ %s] live quotes, %d symbols", today, today, written_daily)
|
||||
elif latest_daily:
|
||||
# 有历史但今天没数据 → batch 补齐缺口
|
||||
# 有历史 → batch 补齐缺口。
|
||||
# 也覆盖"今天已有数据但无实时行情权限(free/none)"的降级场景:
|
||||
# 此时 start_date = latest_daily = today,batch 刷新当天日K。
|
||||
start_date = latest_daily
|
||||
daily_range_start = start_date
|
||||
emit("sync_daily", 12, f"获取日K [{start_date} ~ {today}]…")
|
||||
logger.info("sync_daily: [%s ~ %s] gap fill", start_date, today)
|
||||
logger.info("sync_daily: [%s ~ %s] %s", start_date, today,
|
||||
"refresh today" if today_exists else "gap fill")
|
||||
|
||||
def _daily_chunk_progress(cur: int, tot: int) -> None:
|
||||
emit("sync_daily", 12 + int(33 * cur / tot),
|
||||
@@ -140,6 +154,7 @@ def run_now(
|
||||
else:
|
||||
# 首次：无任何数据 → batch 拉 1 年
|
||||
start_date = today - _td(days=365)
|
||||
daily_range_start = start_date
|
||||
emit("sync_daily", 12, f"获取日K [{start_date} ~ {today}]…")
|
||||
logger.info("sync_daily: [%s ~ %s] initial fetch", start_date, today)
|
||||
|
||||
@@ -157,36 +172,22 @@ def run_now(
|
||||
logger.info("sync_daily: [%s ~ %s] done", start_date, today)
|
||||
_invalidate("daily")
|
||||
|
||||
# Step 1.5: 增量同步除权因子 — 从已有数据最新日期的下一天开始获取
|
||||
# Step 1.5: 同步除权因子 — 范围与日K拉取方式对齐
|
||||
# 日K范围拉取(补缺口/首次) → 除权用日K范围 [daily_range_start, now]
|
||||
# 首次会覆盖整个日K区间内的历史除权事件; 补缺口天然只增量(起点=latest_daily≈昨天)
|
||||
# 日K实时增量/跳过(分支2/分支1) → 除权兜底拉最近 30 天, 补可能遗漏的新除权
|
||||
# (这两类分支不拉历史日K, 除权不能用日K范围, 只能兜底最近几日)
|
||||
written_adj = 0
|
||||
affected_symbols: list[str] = []
|
||||
if capset.has(Cap.ADJ_FACTOR):
|
||||
from datetime import datetime, timedelta
|
||||
adj_end = datetime.now()
|
||||
# 从已有除权因子数据的最新日期开始获取，避免重复拉取
|
||||
adj_factor_path = repo.store.data_dir / "adj_factor" / "all.parquet"
|
||||
fallback_start = adj_end - timedelta(days=30)
|
||||
if adj_factor_path.exists():
|
||||
try:
|
||||
from datetime import date as date_cls
|
||||
max_date = pl.scan_parquet(adj_factor_path).select(
|
||||
pl.col("trade_date").max()
|
||||
).collect().item()
|
||||
if max_date is not None:
|
||||
# trade_date 可能是 date / datetime / string 类型
|
||||
if isinstance(max_date, str):
|
||||
td = date_cls.fromisoformat(max_date)
|
||||
elif isinstance(max_date, datetime):
|
||||
td = max_date.date()
|
||||
if daily_range_start is not None:
|
||||
adj_start = datetime.combine(daily_range_start, datetime.min.time())
|
||||
else:
|
||||
td = max_date
|
||||
adj_start = datetime.combine(td, datetime.min.time())
|
||||
else:
|
||||
adj_start = fallback_start
|
||||
except Exception:
|
||||
adj_start = fallback_start
|
||||
else:
|
||||
adj_start = fallback_start
|
||||
# 日K实时增量/跳过时, 除权兜底拉最近 N 天, 覆盖周末/长假/停机期间的新除权事件。
|
||||
# 15 天: 覆盖春节/国庆最长约10天长假 + 故障恢复缓冲; sync_adj_factor 内部 merge+unique 幂等, 多拉无副作用。
|
||||
adj_start = adj_end - timedelta(days=15)
|
||||
adj_start_str = adj_start.strftime("%Y-%m-%d")
|
||||
adj_end_str = adj_end.strftime("%Y-%m-%d")
|
||||
emit("sync_adj", 50, f"获取除权因子 [{adj_start_str} ~ {adj_end_str}]…")
|
||||
@@ -286,33 +287,119 @@ def run_now(
|
||||
_refresh_single_view(repo, "kline_enriched")
|
||||
_invalidate("enriched")
|
||||
|
||||
# Step 2.3: 指数同步 — 独立 kline_index_* 存储，不进入股票选股/策略链路。
|
||||
# Step 2.3: 指数 / ETF 同步 — 物理分开存储；ETF 可复权，指数不复权。
|
||||
written_index_daily = 0
|
||||
written_etf_daily = 0
|
||||
index_count = 0
|
||||
if capset.has(Cap.KLINE_DAILY_BATCH):
|
||||
emit("sync_index", 88, "同步指数列表与日K…")
|
||||
etf_count = 0
|
||||
etf_adj_symbols = 0
|
||||
pull_index = _prefs.get_pipeline_pull_index()
|
||||
pull_etf = _prefs.get_pipeline_pull_etf()
|
||||
|
||||
if capset.has(Cap.KLINE_DAILY_BATCH) and (pull_index or pull_etf):
|
||||
_types = []
|
||||
if pull_index:
|
||||
_types.append("指数")
|
||||
if pull_etf:
|
||||
_types.append("ETF")
|
||||
emit("sync_index", 88, f"同步{'+'.join(_types)}日K…")
|
||||
# 子阶段进度分配: 88.0(开始) → 89.0(完成), 指数占前半, ETF 占后半
|
||||
try:
|
||||
index_count = index_sync.sync_index_instruments(repo)
|
||||
if pull_index:
|
||||
emit("sync_index", 88, "同步指数维表…")
|
||||
index_count = index_sync.sync_index_instruments(repo, pull_index=True, pull_etf=False)
|
||||
emit("sync_index", 88, f"指数维表完成,{index_count} 只")
|
||||
index_dir = repo.store.data_dir / "kline_index_enriched"
|
||||
index_dates = sorted(
|
||||
d.name[5:] for d in index_dir.glob("date=*")
|
||||
if d.is_dir() and d.name.startswith("date=")
|
||||
) if index_dir.exists() else []
|
||||
index_start = _date.fromisoformat(index_dates[-1]) if index_dates else today - _td(days=365)
|
||||
|
||||
def _index_chunk(cur: int, tot: int) -> None:
|
||||
emit("sync_index", 88, f"指数日K批次 {cur}/{tot}",
|
||||
stage_pct=int(100 * cur / tot) if tot else 100, skip_log=cur < tot)
|
||||
|
||||
written_index_daily = index_sync.sync_and_persist_index_daily(
|
||||
repo,
|
||||
capset,
|
||||
start_date=_dt.combine(index_start, _dt.min.time()),
|
||||
end_date=_dt.combine(today, _dt.min.time()),
|
||||
on_chunk_done=_index_chunk,
|
||||
)
|
||||
repo.refresh_index_views()
|
||||
emit("sync_index", 88, f"指数日K完成,{written_index_daily} 行")
|
||||
_invalidate("index_instruments")
|
||||
_invalidate("index_daily")
|
||||
_invalidate("index_enriched")
|
||||
emit("sync_index", 89, f"指数完成,{index_count} 只指数,{written_index_daily} 行日K")
|
||||
|
||||
if pull_etf:
|
||||
emit("sync_index", 88, "同步 ETF 维表…")
|
||||
etf_count = index_sync.sync_etf_instruments(repo)
|
||||
emit("sync_index", 88, f"ETF 维表完成,{etf_count} 只")
|
||||
etf_symbols: list[str] = []
|
||||
etf_inst = repo.get_etf_instruments()
|
||||
if not etf_inst.is_empty() and "symbol" in etf_inst.columns:
|
||||
etf_symbols = sorted(set(etf_inst["symbol"].to_list()))
|
||||
if etf_symbols and capset.has(Cap.ADJ_FACTOR):
|
||||
try:
|
||||
emit("sync_index", 88, "同步 ETF 除权因子…")
|
||||
from datetime import datetime, timedelta
|
||||
adj_end = datetime.now()
|
||||
adj_path = repo.store.data_dir / "adj_factor_etf" / "all.parquet"
|
||||
fallback_start = adj_end - timedelta(days=30)
|
||||
adj_start = fallback_start
|
||||
if adj_path.exists():
|
||||
max_date = pl.scan_parquet(adj_path).select(pl.col("trade_date").max()).collect().item()
|
||||
if max_date is not None:
|
||||
if isinstance(max_date, str):
|
||||
adj_start = datetime.combine(_date.fromisoformat(max_date), datetime.min.time())
|
||||
elif isinstance(max_date, datetime):
|
||||
adj_start = datetime.combine(max_date.date(), datetime.min.time())
|
||||
else:
|
||||
adj_start = datetime.combine(max_date, datetime.min.time())
|
||||
_, affected_etfs = index_sync.sync_etf_adj_factor(
|
||||
etf_symbols,
|
||||
repo,
|
||||
capset,
|
||||
start_time=adj_start,
|
||||
end_time=adj_end,
|
||||
)
|
||||
etf_adj_symbols = len(affected_etfs)
|
||||
emit("sync_index", 88, f"ETF 除权因子完成,{etf_adj_symbols} 只")
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("sync_index failed: %s", e)
|
||||
emit("sync_index", 89, f"指数同步失败:{e}")
|
||||
logger.warning("ETF adj_factor skipped: %s", e)
|
||||
etf_dir = repo.store.data_dir / "kline_etf_enriched"
|
||||
etf_dates = sorted(
|
||||
d.name[5:] for d in etf_dir.glob("date=*")
|
||||
if d.is_dir() and d.name.startswith("date=")
|
||||
) if etf_dir.exists() else []
|
||||
etf_start = _date.fromisoformat(etf_dates[-1]) if etf_dates else today - _td(days=365)
|
||||
|
||||
def _etf_chunk(cur: int, tot: int) -> None:
|
||||
emit("sync_index", 88, f"ETF 日K批次 {cur}/{tot}",
|
||||
stage_pct=int(100 * cur / tot) if tot else 100, skip_log=cur < tot)
|
||||
|
||||
written_etf_daily = index_sync.sync_and_persist_etf_daily(
|
||||
repo,
|
||||
capset,
|
||||
start_date=_dt.combine(etf_start, _dt.min.time()),
|
||||
end_date=_dt.combine(today, _dt.min.time()),
|
||||
on_chunk_done=_etf_chunk,
|
||||
)
|
||||
emit("sync_index", 88, f"ETF 日K完成,{written_etf_daily} 行")
|
||||
_invalidate("etf_instruments")
|
||||
_invalidate("etf_daily")
|
||||
|
||||
repo.refresh_index_views()
|
||||
emit(
|
||||
"sync_index",
|
||||
89,
|
||||
f"同步完成,指数 {index_count} 只/{written_index_daily} 行, ETF {etf_count} 只/{written_etf_daily} 行"
|
||||
+ (f", ETF复权 {etf_adj_symbols} 只" if etf_adj_symbols else ""),
|
||||
)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("sync_index/etf failed: %s", e)
|
||||
emit("sync_index", 89, f"指数/ETF同步失败:{e}")
|
||||
else:
|
||||
skipped.append("sync_index")
|
||||
|
||||
@@ -359,6 +446,9 @@ def run_now(
|
||||
"enriched_days": written_enriched,
|
||||
"index_count": index_count,
|
||||
"index_daily_rows": written_index_daily,
|
||||
"etf_count": etf_count,
|
||||
"etf_daily_rows": written_etf_daily,
|
||||
"etf_adj_factor_symbols": etf_adj_symbols,
|
||||
"minute_rows": written_minute,
|
||||
"skipped_stages": skipped,
|
||||
}
|
||||
@@ -372,10 +462,15 @@ def _refresh_views(repo: KlineRepository) -> None:
|
||||
"kline_enriched": f"{d}/kline_daily_enriched/**/*.parquet",
|
||||
"kline_index_daily": f"{d}/kline_index_daily/**/*.parquet",
|
||||
"kline_index_enriched": f"{d}/kline_index_enriched/**/*.parquet",
|
||||
"kline_etf_daily": f"{d}/kline_etf_daily/**/*.parquet",
|
||||
"kline_etf_enriched": f"{d}/kline_etf_enriched/**/*.parquet",
|
||||
"kline_etf_minute": f"{d}/kline_etf_minute/**/*.parquet",
|
||||
"kline_minute": f"{d}/kline_minute/**/*.parquet",
|
||||
"adj_factor": f"{d}/adj_factor/**/*.parquet",
|
||||
"adj_factor_etf": f"{d}/adj_factor_etf/**/*.parquet",
|
||||
"instruments": f"{d}/instruments/**/*.parquet",
|
||||
"instruments_index": f"{d}/instruments_index/**/*.parquet",
|
||||
"instruments_etf": f"{d}/instruments_etf/**/*.parquet",
|
||||
}
|
||||
for name, path in views.items():
|
||||
try:
|
||||
@@ -385,6 +480,7 @@ def _refresh_views(repo: KlineRepository) -> None:
|
||||
)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("refresh view %s failed: %s", name, e)
|
||||
repo.store._register_unified_views()
|
||||
|
||||
|
||||
def _refresh_single_view(repo: KlineRepository, name: str) -> None:
|
||||
@@ -395,10 +491,15 @@ def _refresh_single_view(repo: KlineRepository, name: str) -> None:
|
||||
"kline_enriched": f"{d}/kline_daily_enriched/**/*.parquet",
|
||||
"kline_index_daily": f"{d}/kline_index_daily/**/*.parquet",
|
||||
"kline_index_enriched": f"{d}/kline_index_enriched/**/*.parquet",
|
||||
"kline_etf_daily": f"{d}/kline_etf_daily/**/*.parquet",
|
||||
"kline_etf_enriched": f"{d}/kline_etf_enriched/**/*.parquet",
|
||||
"kline_etf_minute": f"{d}/kline_etf_minute/**/*.parquet",
|
||||
"kline_minute": f"{d}/kline_minute/**/*.parquet",
|
||||
"adj_factor": f"{d}/adj_factor/**/*.parquet",
|
||||
"adj_factor_etf": f"{d}/adj_factor_etf/**/*.parquet",
|
||||
"instruments": f"{d}/instruments/**/*.parquet",
|
||||
"instruments_index": f"{d}/instruments_index/**/*.parquet",
|
||||
"instruments_etf": f"{d}/instruments_etf/**/*.parquet",
|
||||
}
|
||||
path = paths.get(name)
|
||||
if not path:
|
||||
@@ -449,10 +550,201 @@ def _run_tracked(fn, job_label: str) -> None:
|
||||
job_store.fail(job_id, f"scheduled {job_label} failed")
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 定时复盘 (AI 大盘复盘报告)
|
||||
# ================================================================
|
||||
|
||||
REVIEW_JOB_ID = "scheduled_review"
|
||||
|
||||
|
||||
async def _run_scheduled_review(repo) -> None:
|
||||
"""定时复盘 job: 流式生成复盘 → 实时推 SSE(开着页面可见) → 落盘归档 → 推飞书。
|
||||
|
||||
与手动「生成复盘」体验一致: 流式事件经 quote_service.push_review_event →
|
||||
/api/intraday/stream 的 review_progress 事件 → 前端 reviewStore, 用户开着复盘页
|
||||
即可看到报告边生成边显示, 切走再回来也能看到生成中/已生成。
|
||||
LLM 偶发断流(peer closed connection)时自动重试最多 2 次。
|
||||
任何异常都吞掉只记日志, 绝不影响调度器主循环。
|
||||
"""
|
||||
import json
|
||||
|
||||
try:
|
||||
from app.services import market_recap_reports
|
||||
from app import secrets_store as ss
|
||||
|
||||
# AI Key 未配置时跳过(避免每日报错刷日志)
|
||||
if not ss.get_ai_key():
|
||||
logger.info("scheduled review skipped: AI key not configured")
|
||||
return
|
||||
|
||||
app_state = _get_app_state()
|
||||
quote_service = getattr(app_state, "quote_service", None) if app_state else None
|
||||
depth_service = getattr(app_state, "depth_service", None) if app_state else None
|
||||
|
||||
content, meta = await _stream_review_with_retry(repo, quote_service, depth_service)
|
||||
if not content:
|
||||
logger.warning("scheduled review produced no content (meta=%s)", meta)
|
||||
# 通知前端进入 error 态(若有页面在听)
|
||||
if quote_service:
|
||||
quote_service.push_review_event(json.dumps(
|
||||
{"type": "error", "message": "复盘生成失败,请稍后手动重试"},
|
||||
ensure_ascii=False))
|
||||
return
|
||||
|
||||
# 落盘: 与手动生成完全相同的归档格式
|
||||
market_recap_reports.save_report({
|
||||
"as_of": meta.get("as_of"),
|
||||
"focus": "",
|
||||
"content": content,
|
||||
"summary": meta.get("summary", ""),
|
||||
"emotion_score": meta.get("emotion_score"),
|
||||
"emotion_label": meta.get("emotion_label", ""),
|
||||
})
|
||||
logger.info("scheduled review saved: as_of=%s", meta.get("as_of"))
|
||||
|
||||
# 通知前端: 生成完成且已归档(archived=true 让前端只刷新列表, 不重复归档)
|
||||
if quote_service:
|
||||
quote_service.push_review_event(json.dumps(
|
||||
{"type": "done", "archived": True}, ensure_ascii=False))
|
||||
|
||||
# 推送到飞书(可选): 运行时读取配置, 用户改设置下次触发即生效。
|
||||
# 失败静默降级, 不影响已归档的报告。
|
||||
_maybe_push_review(content, meta)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.exception("scheduled review failed: %s", e)
|
||||
# 兜底: 异常时通知前端停止「生成中」状态, 避免页面卡在 streaming
|
||||
try:
|
||||
app_state = _get_app_state()
|
||||
qs = getattr(app_state, "quote_service", None) if app_state else None
|
||||
if qs:
|
||||
import json as _json
|
||||
qs.push_review_event(_json.dumps(
|
||||
{"type": "error", "message": "复盘生成异常,请稍后手动重试"},
|
||||
ensure_ascii=False))
|
||||
except Exception: # noqa: BLE001
|
||||
pass
|
||||
|
||||
|
||||
async def _stream_review_with_retry(repo, quote_service, depth_service) -> tuple[str, dict]:
|
||||
"""流式生成复盘, 每个事件推 SSE + 累积内容。LLM 断流时最多重试 2 次。
|
||||
|
||||
返回 (content, meta)。重试时推一个 retry 事件让前端清空已累积内容重新开始。
|
||||
成功(收到 done/无 error)或耗尽重试后返回。
|
||||
"""
|
||||
import asyncio
|
||||
import json
|
||||
from app.services.market_recap import recap_market_stream
|
||||
|
||||
max_attempts = 3 # 初次 + 2 次重试
|
||||
last_meta: dict = {}
|
||||
content_parts: list[str] = []
|
||||
|
||||
for attempt in range(1, max_attempts + 1):
|
||||
content_parts = [] # 每次重试重新累积
|
||||
failed = False
|
||||
try:
|
||||
async for evt_json in recap_market_stream(repo, quote_service, depth_service):
|
||||
evt = json.loads(evt_json)
|
||||
t = evt.get("type")
|
||||
|
||||
# 推给前端(让开着页面的用户实时看到, 与手动一致)
|
||||
if quote_service:
|
||||
quote_service.push_review_event(evt_json)
|
||||
|
||||
if t == "meta":
|
||||
last_meta = evt
|
||||
elif t == "delta" and evt.get("content"):
|
||||
content_parts.append(evt["content"])
|
||||
elif t == "error":
|
||||
failed = True
|
||||
logger.warning("scheduled review stream error (attempt %d/%d): %s",
|
||||
attempt, max_attempts, evt.get("message"))
|
||||
break # 触发重试
|
||||
elif t == "done":
|
||||
# 正常完成
|
||||
return "".join(content_parts), last_meta
|
||||
# 流自然结束(无 done 事件)且有内容, 视为成功
|
||||
if content_parts and not failed:
|
||||
return "".join(content_parts), last_meta
|
||||
except Exception as e: # noqa: BLE001
|
||||
# LLM 断流等异常(httpx.RemoteProtocolError)落到这里
|
||||
failed = True
|
||||
logger.warning("scheduled review stream exception (attempt %d/%d): %s",
|
||||
attempt, max_attempts, e)
|
||||
|
||||
# 失败: 决定是否重试
|
||||
if attempt < max_attempts:
|
||||
logger.info("scheduled review retrying in 3s (attempt %d → %d)", attempt, attempt + 1)
|
||||
# 通知前端: 即将重试, 清空已累积内容重新开始
|
||||
if quote_service:
|
||||
quote_service.push_review_event(json.dumps(
|
||||
{"type": "retry", "attempt": attempt + 1}, ensure_ascii=False))
|
||||
await asyncio.sleep(3)
|
||||
|
||||
# 耗尽重试, 返回已累积内容(可能为空)和最后 meta
|
||||
return "".join(content_parts), last_meta
|
||||
|
||||
|
||||
def _maybe_push_review(content: str, meta: dict) -> None:
|
||||
"""复盘报告归档后, 按 review_push_channels 选定的外部工具逐个推送完整报告。
|
||||
|
||||
定时生成与手动生成共用本函数 (手动归档端点 POST /api/market-recap/reports 也会调用)。
|
||||
channels 为空则不推送; 'feishu' 复用监控中心的全局飞书 Webhook 通道。
|
||||
推送失败静默降级 (Webhook 是辅助通道), 不影响已归档的报告。
|
||||
"""
|
||||
try:
|
||||
from app.services import preferences, webhook_adapter
|
||||
|
||||
channels = preferences.get_review_push_channels()
|
||||
if not channels:
|
||||
return
|
||||
|
||||
emotion = f"{meta.get('emotion_label') or ''}".strip()
|
||||
as_of = meta.get("as_of") or ""
|
||||
subtitle = as_of + (f" · 情绪 {emotion}" if emotion else "")
|
||||
|
||||
for ch in channels:
|
||||
if ch == "feishu":
|
||||
url = preferences.get_feishu_webhook_url()
|
||||
if not url:
|
||||
logger.info("review push(feishu) skipped: webhook not configured")
|
||||
continue
|
||||
secret = preferences.get_feishu_webhook_secret()
|
||||
ok = webhook_adapter.send_feishu_card(
|
||||
url, "TickFlow · 每日复盘", subtitle, content, secret
|
||||
)
|
||||
logger.info("review push(feishu) %s", "sent" if ok else "failed")
|
||||
# 未来更多渠道在此追加分支
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("review push error: %s", e)
|
||||
|
||||
|
||||
def _register_review_job(scheduler, repo, hour: int, minute: int) -> None:
|
||||
"""注册/更新定时复盘 job(工作日 mon-fri, Asia/Shanghai)。
|
||||
|
||||
供 start_scheduler(启动时) 和 settings API(改时间时) 共用。
|
||||
用 replace_existing=True, 重复注册只更新 trigger。
|
||||
|
||||
注意: _run_scheduled_review 是协程函数, 必须把函数对象本身(配合 args)传给
|
||||
add_job, 而非用 lambda 包裹 —— 否则 APScheduler 会把 lambda 当同步函数在线程池
|
||||
执行, 仅得到一个未 await 的协程对象, 复盘实际不会运行。
|
||||
"""
|
||||
scheduler.add_job(
|
||||
_run_scheduled_review,
|
||||
args=[repo],
|
||||
trigger=CronTrigger(day_of_week="mon-fri",
|
||||
hour=hour, minute=minute,
|
||||
timezone="Asia/Shanghai"),
|
||||
id=REVIEW_JOB_ID,
|
||||
misfire_grace_time=7200, # 复盘非关键, 允许 2 小时内补跑
|
||||
replace_existing=True,
|
||||
)
|
||||
|
||||
|
||||
def start_scheduler(repo: KlineRepository, capset: CapabilitySet) -> AsyncIOScheduler:
|
||||
"""启动调度器。
|
||||
|
||||
工作日 09:10 — 同步标的维表
|
||||
工作日 09:10 — 同步个股维表
|
||||
工作日 HH:MM — 盘后管道（时间由用户偏好决定，默认 15:30）
|
||||
"""
|
||||
from app.services import preferences
|
||||
@@ -464,9 +756,9 @@ def start_scheduler(repo: KlineRepository, capset: CapabilitySet) -> AsyncIOSche
|
||||
# 盘前: 同步 instruments（时间由偏好决定）
|
||||
def _instruments_task(on_progress=None):
|
||||
emit = on_progress or _noop
|
||||
emit("sync_instruments", 0, "同步标的维表…")
|
||||
emit("sync_instruments", 0, "同步个股维表…")
|
||||
result = run_instruments_sync(repo)
|
||||
emit("done", 100, f"标的维表同步完成,{result.get('instruments_rows', 0)} 只标的")
|
||||
emit("done", 100, f"个股维表同步完成,{result.get('instruments_rows', 0)} 只标的")
|
||||
return result
|
||||
|
||||
scheduler.add_job(
|
||||
@@ -480,11 +772,16 @@ def start_scheduler(repo: KlineRepository, capset: CapabilitySet) -> AsyncIOSche
|
||||
)
|
||||
|
||||
# 盘后: 日 K + enriched（时间由偏好决定）
|
||||
def _pipeline_then_refresh(on_progress=None):
|
||||
# 与手动触发 (/api/pipeline/run) 对齐: 管道落盘后重建 Polars 内存缓存,
|
||||
# 否则 live_agg 的昨日连板数等基准列会停留在旧交易日, 次日开盘连板梯队
|
||||
# 整体少算一档 (仅手动触发或重启才会刷缓存, cron 调度路径此前漏了这步)。
|
||||
result = run_now(repo, capset, on_progress=on_progress)
|
||||
repo.refresh_cache()
|
||||
return result
|
||||
|
||||
scheduler.add_job(
|
||||
lambda: _run_tracked(
|
||||
lambda on_progress=None: run_now(repo, capset, on_progress=on_progress),
|
||||
"daily_pipeline",
|
||||
),
|
||||
lambda: _run_tracked(_pipeline_then_refresh, "daily_pipeline"),
|
||||
trigger=CronTrigger(day_of_week="mon-fri",
|
||||
hour=sched["hour"], minute=sched["minute"],
|
||||
timezone="Asia/Shanghai"),
|
||||
@@ -511,6 +808,16 @@ def start_scheduler(repo: KlineRepository, capset: CapabilitySet) -> AsyncIOSche
|
||||
replace_existing=True,
|
||||
)
|
||||
|
||||
# 定时复盘 (AI 大盘复盘报告): 工作日到点自动生成并归档。
|
||||
# 默认关闭 —— 仅当用户在复盘页开启时才注册 job。
|
||||
# 复用 recap_market_once(非流式) + market_recap_reports.save_report(落盘)。
|
||||
# quote_service / depth_service 通过 _get_app_state() 延迟取用。
|
||||
review_sched = preferences.get_review_schedule()
|
||||
if review_sched["enabled"]:
|
||||
_register_review_job(scheduler, repo, review_sched["hour"], review_sched["minute"])
|
||||
logger.info("scheduled_review enabled @%02d:%02d mon-fri",
|
||||
review_sched["hour"], review_sched["minute"])
|
||||
|
||||
scheduler.start()
|
||||
logger.info("scheduler started; instruments@%02d:%02d, pipeline@%02d:%02d, depth@%02d:%02d mon-fri",
|
||||
inst_sched["hour"], inst_sched["minute"], sched["hour"], sched["minute"],
|
||||
|
||||
+71
-30
@@ -11,8 +11,7 @@ from fastapi.responses import FileResponse, JSONResponse
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
|
||||
from app import __version__
|
||||
from app import auth as auth_module
|
||||
from app.api import analysis, auth, backtest, data, ext_data, financials, indices, intraday, kline, monitor_rules, alerts, overview, pipeline, screener, settings as settings_api, signals, strategy, watchlist
|
||||
from app.api import analysis, auth as auth_api, backtest, data, ext_data, financials, indices, intraday, kline, market_recap, monitor_rules, alerts, overview, pipeline, rps, screener, settings as settings_api, signals, stock_analysis, strategy, watchlist
|
||||
from app.api.routes import router as core_router
|
||||
from app.config import settings
|
||||
from app.jobs import daily_pipeline
|
||||
@@ -31,10 +30,18 @@ logger = logging.getLogger(__name__)
|
||||
@asynccontextmanager
|
||||
async def lifespan(app: FastAPI):
|
||||
logger.info(
|
||||
"Stock Panel v%s starting (mode=%s)",
|
||||
"TickFlow Stock Panel v%s starting (mode=%s)",
|
||||
__version__, tf_client.current_mode(),
|
||||
)
|
||||
|
||||
# 首次启动: 若配置了 AUTH_PASSWORD 环境变量且未设过密码, 用它初始化。
|
||||
# 公网部署免 SSH 端口转发; 已设过密码则不覆盖 (改密码走 UI)。
|
||||
try:
|
||||
from app.services import auth as auth_service
|
||||
auth_service.bootstrap_from_env()
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("auth bootstrap failed: %s", e)
|
||||
|
||||
# 数据层
|
||||
store = DataStore()
|
||||
repo = KlineRepository(store)
|
||||
@@ -91,7 +98,16 @@ async def lifespan(app: FastAPI):
|
||||
pull_scheduler.refresh(store.data_dir)
|
||||
app.state.pull_scheduler = pull_scheduler
|
||||
|
||||
# 财务数据独立调度 (需 Expert 套餐)
|
||||
# 内置扩展表 (概念/行业): 只创建 config (含拉取配置), 不自动拉数据
|
||||
# 数据获取由用户在概念/行业页点「获取数据」手动触发 (POST /api/ext-data/presets/{id}/fetch)
|
||||
try:
|
||||
from app.services.ext_presets import ensure_builtin_presets
|
||||
await ensure_builtin_presets(store.data_dir)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("内置扩展表初始化失败 (不影响启动): %s", e)
|
||||
|
||||
# 财务数据 (需 Expert 套餐): 仅初始化调度器供 /api/financials/sync/* 手动同步,
|
||||
# 不启动自动调度——用户在「财务分析」页点「同步」手动拉取。
|
||||
from app.services.financial_sync import financial_scheduler
|
||||
financial_scheduler.start(store.data_dir, capset)
|
||||
app.state.financial_scheduler = financial_scheduler
|
||||
@@ -122,6 +138,9 @@ async def lifespan(app: FastAPI):
|
||||
monitor_engine = MonitorRuleEngine()
|
||||
monitor_engine.set_strategy_engine(strategy_engine)
|
||||
monitor_engine.set_data_dir(store.data_dir)
|
||||
# 复用 ScreenerService 的历史窗口加载器 (三级缓存, 启动预计算命中 ~0ms),
|
||||
# 让声明 filter_history 的策略 (如反包) 也能在实时监控里跑选股 → 盘中触发通知。
|
||||
monitor_engine.set_history_loader(_screener_svc._load_enriched_history)
|
||||
|
||||
# 自动迁移: 把旧 strategy_monitor_ids 同步为 type=strategy 规则 (统一到监控页)
|
||||
try:
|
||||
@@ -162,9 +181,9 @@ async def lifespan(app: FastAPI):
|
||||
|
||||
|
||||
app = FastAPI(
|
||||
title="Stock Panel",
|
||||
title="TickFlow Stock Panel",
|
||||
version=__version__,
|
||||
description="A 股选股 + 监控 + 回测面板",
|
||||
description="A 股选股 + 回测面板 — TickFlow 适配",
|
||||
lifespan=lifespan,
|
||||
)
|
||||
|
||||
@@ -180,37 +199,54 @@ app.add_middleware(
|
||||
)
|
||||
|
||||
|
||||
# 访问门控中间件:仅对 /api/* 路径校验,静态资源和前端路由放行,
|
||||
# 由前端 AccessGuard 控制 UI 展示。
|
||||
# ================================================================
|
||||
# 访问认证中间件
|
||||
# ================================================================
|
||||
# 拦截所有 /api/ 请求, 三种状态:
|
||||
# 1. 未设密码 + 本机/内网 → 放行(让本机用户访问面板 + 调 /api/auth/setup 设密码)
|
||||
# 2. 未设密码 + 公网 → 拒绝(403, 防裸奔也防抢占; 引导本机设密码)
|
||||
# 3. 已设密码 → 检查 session, 无效则 401(前端跳登录)
|
||||
# 白名单: /api/auth/* (设密码/登录本身)、/health 等探活。
|
||||
_AUTH_WHITELIST_PREFIX = ("/api/auth/",)
|
||||
_AUTH_WHITELIST_EXACT = ("/health", "/api/health", "/openapi.json", "/docs", "/redoc")
|
||||
|
||||
|
||||
@app.middleware("http")
|
||||
async def access_uuid_middleware(request: Request, call_next):
|
||||
if auth_module.access_control_enabled():
|
||||
async def auth_middleware(request: Request, call_next):
|
||||
path = request.url.path
|
||||
# 白名单直接放行
|
||||
if not auth_module.is_public_path(path):
|
||||
token = auth_module.get_access_token_from_request(request)
|
||||
role = auth_module.validate_access_token(token)
|
||||
# 管理员接口需 admin 角色
|
||||
if auth_module.is_admin_path(path):
|
||||
if role != auth_module.AuthRole.ADMIN:
|
||||
return JSONResponse(
|
||||
status_code=403 if role else 401,
|
||||
content={"detail": "需要管理员权限"},
|
||||
)
|
||||
# 其它 API 调用需任意有效角色
|
||||
elif path.startswith("/api/"):
|
||||
if role is None:
|
||||
return JSONResponse(
|
||||
status_code=401,
|
||||
content={"detail": "访问令牌无效或已过期,请先验证"},
|
||||
)
|
||||
# 仅 /api/ 走认证; 静态资源(前端页面/assets)放行, 由前端处理跳转
|
||||
if not path.startswith("/api/"):
|
||||
return await call_next(request)
|
||||
# 白名单放行(设密码/登录/探活本身不拦)
|
||||
if path.startswith(_AUTH_WHITELIST_PREFIX) or path in _AUTH_WHITELIST_EXACT:
|
||||
return await call_next(request)
|
||||
|
||||
from app.services import auth as auth_service
|
||||
# 情况 1+2: 未设密码
|
||||
if not auth_service.is_configured():
|
||||
# 本机/内网 → 放行(服务器主人可访问, 并去 /login 设密码)
|
||||
if auth_api._is_local_network(auth_api._client_ip(request)):
|
||||
return await call_next(request)
|
||||
# 公网 → 拒绝。不裸奔, 也不给公网设密码的机会(防抢占)
|
||||
return JSONResponse(
|
||||
status_code=403,
|
||||
content={
|
||||
"detail": "面板尚未初始化访问密码,请通过 SSH/本机浏览器访问以设置密码",
|
||||
"code": "NOT_INITIALIZED",
|
||||
},
|
||||
)
|
||||
|
||||
# 情况 3: 已设密码, 检查会话
|
||||
token = request.cookies.get(auth_api.COOKIE_NAME)
|
||||
if token and auth_service.is_valid_session(token):
|
||||
return await call_next(request)
|
||||
# 未登录: 401(前端跳登录页)
|
||||
return JSONResponse(status_code=401, content={"detail": "未登录或会话已过期"})
|
||||
|
||||
|
||||
# 路由
|
||||
app.include_router(core_router)
|
||||
app.include_router(auth.router)
|
||||
app.include_router(auth.admin_router)
|
||||
app.include_router(auth_api.router)
|
||||
app.include_router(kline.router)
|
||||
app.include_router(watchlist.router)
|
||||
app.include_router(screener.router)
|
||||
@@ -223,16 +259,21 @@ app.include_router(pipeline.router)
|
||||
app.include_router(data.router)
|
||||
app.include_router(ext_data.router)
|
||||
app.include_router(financials.router)
|
||||
app.include_router(stock_analysis.router)
|
||||
app.include_router(market_recap.router)
|
||||
app.include_router(settings_api.router)
|
||||
app.include_router(strategy.router)
|
||||
app.include_router(signals.router)
|
||||
app.include_router(monitor_rules.router)
|
||||
app.include_router(alerts.router)
|
||||
app.include_router(rps.router)
|
||||
|
||||
|
||||
# 能力门控异常 → 403(而非默认 500)
|
||||
# 业务代码用 capset.require(Cap.X) 断言能力,缺失时抛 CapabilityDenied;
|
||||
# 若不注册 handler 会冒泡成 500 Internal Server Error,对前端不友好且语义错误。
|
||||
from fastapi import Request
|
||||
from fastapi.responses import JSONResponse
|
||||
from app.tickflow.capabilities import CapabilityDenied
|
||||
|
||||
|
||||
|
||||
@@ -61,7 +61,7 @@ def clear(*keys: str) -> dict:
|
||||
|
||||
|
||||
def get_tickflow_key() -> str:
|
||||
"""取当前数据源 Key:secrets.json 优先,否则 .env。"""
|
||||
"""取当前 TickFlow Key:secrets.json 优先,否则 .env。"""
|
||||
val = load().get("tickflow_api_key")
|
||||
if val:
|
||||
return val
|
||||
|
||||
@@ -0,0 +1,429 @@
|
||||
"""AI provider adapter for OpenAI-compatible APIs and local Codex CLI."""
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import re
|
||||
import shutil
|
||||
import sys
|
||||
import tempfile
|
||||
import tomllib
|
||||
from collections.abc import AsyncIterator, Sequence
|
||||
from pathlib import Path
|
||||
|
||||
from app import secrets_store
|
||||
from app.config import settings
|
||||
|
||||
OPENAI_COMPAT_PROVIDER = "openai_compat"
|
||||
CODEX_CLI_PROVIDER = "codex_cli"
|
||||
CODEX_DEFAULT_COMMAND = "codex"
|
||||
CODEX_SERVICE_TIER_FALLBACK = "fast"
|
||||
CODEX_SUPPORTED_SERVICE_TIERS = {"fast", "flex"}
|
||||
|
||||
Message = dict[str, str]
|
||||
|
||||
_ANSI_RE = re.compile(r"\x1b\[[0-9;?]*[ -/]*[@-~]")
|
||||
|
||||
|
||||
def current_ai_provider() -> str:
|
||||
return secrets_store.get_ai_config("ai_provider", settings.ai_provider) or OPENAI_COMPAT_PROVIDER
|
||||
|
||||
|
||||
def current_ai_model() -> str:
|
||||
if current_ai_provider() == CODEX_CLI_PROVIDER:
|
||||
return normalize_codex_model(str(secrets_store.load().get("ai_model") or ""))
|
||||
return secrets_store.get_ai_config("ai_model", settings.ai_model)
|
||||
|
||||
|
||||
def current_codex_command() -> str:
|
||||
return normalize_codex_command(
|
||||
secrets_store.get_ai_config("ai_codex_command", settings.ai_codex_command),
|
||||
strict=False,
|
||||
)
|
||||
|
||||
|
||||
def is_codex_cli_provider(provider: str | None = None) -> bool:
|
||||
return (provider or current_ai_provider()) == CODEX_CLI_PROVIDER
|
||||
|
||||
|
||||
def normalize_codex_model(model: str) -> str:
|
||||
value = model.strip()
|
||||
aliases = {
|
||||
"gpt5": "gpt-5",
|
||||
"gpt5.5": "gpt-5.5",
|
||||
}
|
||||
return aliases.get(value.lower(), value)
|
||||
|
||||
|
||||
def normalize_codex_command(command: str | None, *, strict: bool = True) -> str:
|
||||
value = (command or "").strip()
|
||||
if not value or value.lower() == CODEX_DEFAULT_COMMAND:
|
||||
return CODEX_DEFAULT_COMMAND
|
||||
if strict:
|
||||
raise ValueError("Codex CLI 仅支持使用默认 codex 命令自动解析, 不支持自定义可执行路径")
|
||||
return CODEX_DEFAULT_COMMAND
|
||||
|
||||
|
||||
def normalize_openai_base_url(url: str) -> str:
|
||||
"""Return the OpenAI-compatible base URL expected by the OpenAI SDK."""
|
||||
base = (url or "").strip().rstrip("/")
|
||||
if base.endswith("/chat/completions"):
|
||||
base = base[: -len("/chat/completions")].rstrip("/")
|
||||
if not base.endswith("/v1"):
|
||||
base = f"{base}/v1"
|
||||
return base
|
||||
|
||||
|
||||
def codex_cli_available() -> bool:
|
||||
try:
|
||||
_codex_base_command()
|
||||
return True
|
||||
except RuntimeError:
|
||||
return False
|
||||
|
||||
|
||||
def ai_configured(provider: str | None = None) -> bool:
|
||||
provider = provider or current_ai_provider()
|
||||
if is_codex_cli_provider(provider):
|
||||
return codex_cli_available()
|
||||
return bool(secrets_store.get_ai_key())
|
||||
|
||||
|
||||
async def generate_ai_text(
|
||||
messages: Sequence[Message],
|
||||
*,
|
||||
temperature: float = 0.3,
|
||||
max_tokens: int = 3000,
|
||||
timeout: float = 180.0,
|
||||
) -> str:
|
||||
"""Return a complete AI response from the currently configured provider."""
|
||||
if is_codex_cli_provider():
|
||||
return await _run_codex_cli(messages, max_tokens=max_tokens, timeout=max(timeout, 600.0))
|
||||
return await _run_openai_once(
|
||||
messages,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
timeout=timeout,
|
||||
)
|
||||
|
||||
|
||||
async def stream_ai_text(
|
||||
messages: Sequence[Message],
|
||||
*,
|
||||
temperature: float = 0.5,
|
||||
max_tokens: int = 4000,
|
||||
timeout: float = 180.0,
|
||||
) -> AsyncIterator[str]:
|
||||
"""Yield text deltas from the configured provider.
|
||||
|
||||
Codex CLI only exposes the final assistant message for this use case, so it
|
||||
yields one complete chunk after the command exits.
|
||||
"""
|
||||
if is_codex_cli_provider():
|
||||
yield await _run_codex_cli(messages, max_tokens=max_tokens, timeout=max(timeout, 600.0))
|
||||
return
|
||||
|
||||
async for chunk in _stream_openai(
|
||||
messages,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
timeout=timeout,
|
||||
):
|
||||
yield chunk
|
||||
|
||||
|
||||
async def _run_openai_once(
|
||||
messages: Sequence[Message],
|
||||
*,
|
||||
temperature: float,
|
||||
max_tokens: int,
|
||||
timeout: float,
|
||||
) -> str:
|
||||
ai_key = secrets_store.get_ai_key()
|
||||
if not ai_key:
|
||||
raise RuntimeError("AI API Key 未配置, 请在设置页配置")
|
||||
|
||||
client = _openai_client(ai_key, timeout)
|
||||
resp = await client.chat.completions.create(
|
||||
model=current_ai_model(),
|
||||
messages=list(messages),
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
)
|
||||
if not resp.choices:
|
||||
return ""
|
||||
return (resp.choices[0].message.content or "").strip()
|
||||
|
||||
|
||||
async def _stream_openai(
|
||||
messages: Sequence[Message],
|
||||
*,
|
||||
temperature: float,
|
||||
max_tokens: int,
|
||||
timeout: float,
|
||||
) -> AsyncIterator[str]:
|
||||
ai_key = secrets_store.get_ai_key()
|
||||
if not ai_key:
|
||||
raise RuntimeError("AI API Key 未配置, 请在设置页配置")
|
||||
|
||||
client = _openai_client(ai_key, timeout)
|
||||
stream = await client.chat.completions.create(
|
||||
model=current_ai_model(),
|
||||
messages=list(messages),
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
stream=True,
|
||||
)
|
||||
|
||||
async for chunk in stream:
|
||||
delta = chunk.choices[0].delta if chunk.choices else None
|
||||
if delta and delta.content:
|
||||
yield delta.content
|
||||
|
||||
|
||||
def _openai_client(api_key: str, timeout: float):
|
||||
from openai import AsyncOpenAI
|
||||
|
||||
user_agent = secrets_store.get_ai_config("ai_user_agent", "") or settings.ai_user_agent
|
||||
return AsyncOpenAI(
|
||||
api_key=api_key,
|
||||
base_url=normalize_openai_base_url(secrets_store.get_ai_config("ai_base_url", settings.ai_base_url)),
|
||||
timeout=timeout,
|
||||
max_retries=2,
|
||||
default_headers={"User-Agent": user_agent},
|
||||
)
|
||||
|
||||
|
||||
async def _run_codex_cli(
|
||||
messages: Sequence[Message],
|
||||
*,
|
||||
max_tokens: int,
|
||||
timeout: float,
|
||||
) -> str:
|
||||
prompt = _codex_prompt(messages, max_tokens=max_tokens)
|
||||
with tempfile.TemporaryDirectory(prefix="tickflow-codex-run-") as run_dir:
|
||||
run_path = Path(run_dir)
|
||||
codex_home_path = run_path / "codex-home"
|
||||
workspace_path = run_path / "workspace"
|
||||
codex_home_path.mkdir()
|
||||
workspace_path.mkdir()
|
||||
output_path = codex_home_path / "last-message.txt"
|
||||
_prepare_codex_home(codex_home_path)
|
||||
|
||||
args = [
|
||||
*_codex_base_command(),
|
||||
"exec",
|
||||
"--ephemeral",
|
||||
"--sandbox",
|
||||
"read-only",
|
||||
"--skip-git-repo-check",
|
||||
"--color",
|
||||
"never",
|
||||
"--output-last-message",
|
||||
str(output_path),
|
||||
]
|
||||
model = current_ai_model().strip()
|
||||
if model:
|
||||
args.extend(["--model", model])
|
||||
args.extend(["--cd", str(workspace_path), "-"])
|
||||
|
||||
env = os.environ.copy()
|
||||
env.setdefault("NO_COLOR", "1")
|
||||
env["CODEX_HOME"] = str(codex_home_path)
|
||||
|
||||
proc = await asyncio.create_subprocess_exec(
|
||||
*args,
|
||||
stdin=asyncio.subprocess.PIPE,
|
||||
stdout=asyncio.subprocess.PIPE,
|
||||
stderr=asyncio.subprocess.PIPE,
|
||||
env=env,
|
||||
)
|
||||
try:
|
||||
stdout, stderr = await asyncio.wait_for(
|
||||
proc.communicate(prompt.encode("utf-8")),
|
||||
timeout=timeout,
|
||||
)
|
||||
except TimeoutError as exc:
|
||||
proc.kill()
|
||||
await proc.wait()
|
||||
raise RuntimeError("Codex CLI 调用超时, 请稍后重试或检查本机 Codex 登录状态") from exc
|
||||
|
||||
out = _clean_process_text(stdout)
|
||||
err = _clean_process_text(stderr)
|
||||
final_message = _read_output_file(output_path)
|
||||
if proc.returncode != 0:
|
||||
detail = err or out or f"exit code {proc.returncode}"
|
||||
raise RuntimeError(f"Codex CLI 调用失败: {detail[-1200:]}")
|
||||
result = final_message or out
|
||||
if not result:
|
||||
raise RuntimeError("Codex CLI 未返回内容")
|
||||
return result
|
||||
|
||||
|
||||
def _codex_prompt(messages: Sequence[Message], *, max_tokens: int) -> str:
|
||||
parts = [
|
||||
"You are TickFlow Stock Panel's local AI provider.",
|
||||
"This is a text-generation task. The working directory is intentionally empty.",
|
||||
"Use only the user-provided prompt content below; do not inspect or modify local files.",
|
||||
"Return only the final requested content; do not include execution logs.",
|
||||
]
|
||||
if max_tokens > 0:
|
||||
parts.append(f"Keep the final answer within about {max_tokens} output tokens.")
|
||||
for message in messages:
|
||||
role = message.get("role", "user")
|
||||
content = message.get("content", "")
|
||||
parts.append(f"\n<{role}>\n{content}\n</{role}>")
|
||||
return "\n".join(parts)
|
||||
|
||||
|
||||
def _codex_base_command() -> list[str]:
|
||||
command = current_codex_command()
|
||||
resolved = _resolve_command(command)
|
||||
if not resolved:
|
||||
raise RuntimeError(f"未找到 Codex CLI 命令: {command}")
|
||||
|
||||
if sys.platform == "win32" and resolved.lower().endswith(".ps1"):
|
||||
return ["powershell.exe", "-NoProfile", "-ExecutionPolicy", "Bypass", "-File", resolved]
|
||||
return [resolved]
|
||||
|
||||
|
||||
def _resolve_command(command: str) -> str | None:
|
||||
if command.lower() != CODEX_DEFAULT_COMMAND:
|
||||
return None
|
||||
|
||||
if sys.platform == "win32":
|
||||
desktop_codex = _resolve_windows_desktop_codex()
|
||||
if desktop_codex:
|
||||
return desktop_codex
|
||||
|
||||
resolved = shutil.which(command)
|
||||
if sys.platform == "win32" and resolved:
|
||||
resolved_path = Path(resolved)
|
||||
if not resolved_path.suffix:
|
||||
cmd_path = resolved_path.with_suffix(".cmd")
|
||||
if cmd_path.exists():
|
||||
return str(cmd_path)
|
||||
if not resolved and sys.platform == "win32" and not command.lower().endswith(".cmd"):
|
||||
resolved = shutil.which(f"{command}.cmd")
|
||||
if not resolved and sys.platform == "win32":
|
||||
resolved = _resolve_windows_codex_command(command)
|
||||
return resolved
|
||||
|
||||
|
||||
def _resolve_windows_codex_command(command: str) -> str | None:
|
||||
"""Find npm-installed Codex when the backend process has a minimal PATH."""
|
||||
raw = Path(command)
|
||||
if raw.parent != Path("."):
|
||||
return None
|
||||
|
||||
names = [command]
|
||||
if not raw.suffix:
|
||||
names = [f"{command}.cmd", f"{command}.exe", f"{command}.bat", f"{command}.ps1", command]
|
||||
|
||||
dirs: list[Path] = []
|
||||
appdata = os.environ.get("APPDATA")
|
||||
if appdata:
|
||||
dirs.append(Path(appdata) / "npm")
|
||||
dirs.append(Path.home() / "AppData" / "Roaming" / "npm")
|
||||
|
||||
for env_name in ("ProgramFiles", "ProgramFiles(x86)", "LOCALAPPDATA"):
|
||||
value = os.environ.get(env_name)
|
||||
if value:
|
||||
dirs.append(Path(value) / "nodejs")
|
||||
|
||||
for directory in dirs:
|
||||
for name in names:
|
||||
candidate = directory / name
|
||||
if candidate.exists():
|
||||
return str(candidate)
|
||||
return None
|
||||
|
||||
|
||||
def _resolve_windows_desktop_codex() -> str | None:
|
||||
"""Prefer the Codex Desktop bundled CLI over an older npm shim."""
|
||||
local_appdata = os.environ.get("LOCALAPPDATA")
|
||||
if not local_appdata:
|
||||
return None
|
||||
|
||||
root = Path(local_appdata) / "OpenAI" / "Codex" / "bin"
|
||||
if not root.exists():
|
||||
return None
|
||||
|
||||
candidates = list(root.glob("*/codex.exe"))
|
||||
direct = root / "codex.exe"
|
||||
if direct.exists():
|
||||
candidates.append(direct)
|
||||
if not candidates:
|
||||
return None
|
||||
|
||||
newest = max(candidates, key=lambda p: p.stat().st_mtime)
|
||||
return str(newest)
|
||||
|
||||
|
||||
def _prepare_codex_home(target: Path) -> None:
|
||||
"""Create an isolated CODEX_HOME that reuses auth but not fragile config."""
|
||||
source = _codex_home()
|
||||
auth_file = source / "auth.json"
|
||||
if auth_file.exists():
|
||||
shutil.copy2(auth_file, target / "auth.json")
|
||||
_write_compatible_codex_config(target / "config.toml")
|
||||
|
||||
|
||||
def _codex_home() -> Path:
|
||||
return Path(os.environ.get("CODEX_HOME") or Path.home() / ".codex")
|
||||
|
||||
|
||||
def _write_compatible_codex_config(path: Path) -> None:
|
||||
config = _read_codex_config()
|
||||
lines: list[str] = []
|
||||
|
||||
tier = str(config.get("service_tier") or "").strip()
|
||||
if tier not in CODEX_SUPPORTED_SERVICE_TIERS:
|
||||
tier = CODEX_SERVICE_TIER_FALLBACK
|
||||
lines.append(_toml_string("service_tier", tier))
|
||||
lines.append(_toml_string("approval_policy", "never"))
|
||||
lines.append(_toml_string("sandbox_mode", "read-only"))
|
||||
|
||||
path.write_text("\n".join(lines) + "\n", encoding="utf-8")
|
||||
|
||||
|
||||
def _read_codex_config() -> dict:
|
||||
path = _codex_home() / "config.toml"
|
||||
if not path.exists():
|
||||
return {}
|
||||
try:
|
||||
with path.open("rb") as f:
|
||||
return tomllib.load(f)
|
||||
except tomllib.TOMLDecodeError:
|
||||
return _read_codex_config_lenient(path)
|
||||
except OSError:
|
||||
return {}
|
||||
|
||||
|
||||
def _read_codex_config_lenient(path: Path) -> dict:
|
||||
config: dict[str, str] = {}
|
||||
pattern = re.compile(r'^\s*([A-Za-z0-9_-]+)\s*=\s*"([^"]*)"\s*$')
|
||||
try:
|
||||
for line in path.read_text(encoding="utf-8", errors="replace").splitlines():
|
||||
match = pattern.match(line)
|
||||
if match:
|
||||
config[match.group(1)] = match.group(2)
|
||||
except OSError:
|
||||
pass
|
||||
return config
|
||||
|
||||
|
||||
def _toml_string(key: str, value: str) -> str:
|
||||
escaped = value.replace("\\", "\\\\").replace('"', '\\"')
|
||||
return f'{key} = "{escaped}"'
|
||||
|
||||
|
||||
def _clean_process_text(raw: bytes) -> str:
|
||||
text = raw.decode("utf-8", errors="replace")
|
||||
return _ANSI_RE.sub("", text).strip()
|
||||
|
||||
|
||||
def _read_output_file(path: Path) -> str:
|
||||
if path.exists():
|
||||
return _ANSI_RE.sub("", path.read_text(encoding="utf-8", errors="replace")).strip()
|
||||
return ""
|
||||
@@ -0,0 +1,101 @@
|
||||
"""AI 财务分析报告持久化存储。
|
||||
|
||||
存储位置: data/user_data/ai_reports.json (数组,按 created_at 降序)
|
||||
保留最近 MAX_REPORTS 条;超出自动裁剪最旧的。
|
||||
|
||||
每条报告结构:
|
||||
{
|
||||
"id": "rpt_xxx", # 唯一 id
|
||||
"symbol": "600519.SH",
|
||||
"name": "贵州茅台",
|
||||
"focus": "", # 用户追加的关心点(可为空)
|
||||
"content": "# ...markdown", # 报告正文
|
||||
"periods": 4, # 基于几期数据生成
|
||||
"summary": "metrics: 1期...", # 数据摘要
|
||||
"created_at": "2026-06-25T10:00:00"
|
||||
}
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import time
|
||||
from pathlib import Path
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
MAX_REPORTS = 20
|
||||
|
||||
|
||||
def _path() -> Path:
|
||||
from app.config import settings
|
||||
p = settings.data_dir / "user_data" / "ai_reports.json"
|
||||
p.parent.mkdir(parents=True, exist_ok=True)
|
||||
return p
|
||||
|
||||
|
||||
def list_reports() -> list[dict]:
|
||||
"""返回全部报告(按 created_at 降序)。"""
|
||||
p = _path()
|
||||
if not p.exists():
|
||||
return []
|
||||
try:
|
||||
data = json.loads(p.read_text(encoding="utf-8"))
|
||||
if isinstance(data, list):
|
||||
return sorted(data, key=lambda r: r.get("created_at", ""), reverse=True)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("ai_reports.json malformed: %s", e)
|
||||
return []
|
||||
|
||||
|
||||
def _save_all(reports: list[dict]) -> None:
|
||||
"""全量写入(裁剪到 MAX_REPORTS)。"""
|
||||
# 保持降序
|
||||
reports.sort(key=lambda r: r.get("created_at", ""), reverse=True)
|
||||
if len(reports) > MAX_REPORTS:
|
||||
reports = reports[:MAX_REPORTS]
|
||||
_path().write_text(
|
||||
json.dumps(reports, indent=2, ensure_ascii=False), encoding="utf-8",
|
||||
)
|
||||
|
||||
|
||||
def save_report(report: dict) -> dict:
|
||||
"""新增一条报告并持久化。返回保存后的报告(含 id / created_at)。
|
||||
|
||||
自动补全 id 与 created_at(若缺),并裁剪到上限。
|
||||
"""
|
||||
reports = list_reports()
|
||||
if not report.get("id"):
|
||||
report["id"] = f"rpt_{int(time.time() * 1000)}_{report.get('symbol', 'x')}"
|
||||
if not report.get("created_at"):
|
||||
report["created_at"] = _now_iso()
|
||||
reports.append(report)
|
||||
_save_all(reports)
|
||||
logger.info("AI report saved: %s (%s), total %d", report.get("symbol"), report.get("id"), len(reports))
|
||||
return report
|
||||
|
||||
|
||||
def delete_report(report_id: str) -> bool:
|
||||
"""删除指定报告。返回是否删除成功。"""
|
||||
reports = list_reports()
|
||||
before = len(reports)
|
||||
reports = [r for r in reports if r.get("id") != report_id]
|
||||
if len(reports) < before:
|
||||
_save_all(reports)
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def clear_reports() -> int:
|
||||
"""清空全部报告。返回删除数量。"""
|
||||
reports = list_reports()
|
||||
n = len(reports)
|
||||
if n > 0:
|
||||
_save_all([])
|
||||
return n
|
||||
|
||||
|
||||
def _now_iso() -> str:
|
||||
"""当前本地时间 ISO 字符串(带秒精度,前端 toLocaleString 友好)。"""
|
||||
from datetime import datetime
|
||||
return datetime.now().isoformat(timespec="seconds")
|
||||
@@ -0,0 +1,201 @@
|
||||
"""访问密码认证 — 单用户, 自托管场景。
|
||||
|
||||
设计:
|
||||
- 密码用 PBKDF2-HMAC-SHA256 哈希(标准库 hashlib, 无新依赖), 加随机 salt。
|
||||
即使 auth.json 泄露, 也无法逆向出明文密码。
|
||||
- 会话用随机 token(token_urlsafe), 内存 + 文件双存(支持多进程/重启不丢失)。
|
||||
- 存储: data/user_data/auth.json (chmod 0600), 仿 secrets_store 模式。
|
||||
|
||||
安全要点:
|
||||
- 设密码接口必须限制本机/内网(见 auth router), 防黑客抢占域名抢先设密码。
|
||||
- 登录限流: 错5次锁5分钟(见 auth router 内存计数)。
|
||||
- 单密码, 不做多用户(避免重构全项目数据层)。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import hashlib
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import secrets as _secrets
|
||||
import threading
|
||||
import time
|
||||
from pathlib import Path
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# PBKDF2 参数(NIST 推荐, 单次校验 ~100ms, 兼顾安全与响应)
|
||||
_PBKDF2_ITER = 200_000
|
||||
_SALT_LEN = 16
|
||||
_TOKEN_BYTES = 32
|
||||
|
||||
# 会话有效期: 30 天(自托管单用户, 长一点减少重登频率)
|
||||
SESSION_TTL = 30 * 24 * 3600
|
||||
|
||||
_lock = threading.Lock()
|
||||
# 内存中的有效会话: { token: expire_ts }。进程重启后从磁盘恢复。
|
||||
_sessions: dict[str, float] = {}
|
||||
|
||||
|
||||
def _path() -> Path:
|
||||
from app.config import settings
|
||||
p = settings.data_dir / "user_data" / "auth.json"
|
||||
p.parent.mkdir(parents=True, exist_ok=True)
|
||||
return p
|
||||
|
||||
|
||||
def _load() -> dict:
|
||||
p = _path()
|
||||
if p.exists():
|
||||
try:
|
||||
return json.loads(p.read_text(encoding="utf-8"))
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("auth.json malformed: %s", e)
|
||||
return {}
|
||||
|
||||
|
||||
def _save(data: dict) -> None:
|
||||
p = _path()
|
||||
p.write_text(json.dumps(data, indent=2, ensure_ascii=False), encoding="utf-8")
|
||||
try:
|
||||
os.chmod(p, 0o600)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
|
||||
def _hash_password(password: str, salt: bytes | None = None) -> tuple[str, str]:
|
||||
"""返回 (salt_hex, hash_hex)。salt 为 None 时生成新 salt。"""
|
||||
if salt is None:
|
||||
salt = os.urandom(_SALT_LEN)
|
||||
dk = hashlib.pbkdf2_hmac("sha256", password.encode("utf-8"), salt, _PBKDF2_ITER)
|
||||
return salt.hex(), dk.hex()
|
||||
|
||||
|
||||
def _verify_password(password: str, salt_hex: str, hash_hex: str) -> bool:
|
||||
"""恒定时间比较, 防时序攻击。"""
|
||||
try:
|
||||
salt = bytes.fromhex(salt_hex)
|
||||
expected = bytes.fromhex(hash_hex)
|
||||
except ValueError:
|
||||
return False
|
||||
actual = hashlib.pbkdf2_hmac("sha256", password.encode("utf-8"), salt, _PBKDF2_ITER)
|
||||
return _secrets.compare_digest(actual, expected)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 密码管理
|
||||
# ================================================================
|
||||
|
||||
def is_configured() -> bool:
|
||||
"""是否已设置访问密码。"""
|
||||
d = _load()
|
||||
return bool(d.get("password_hash"))
|
||||
|
||||
|
||||
def set_password(password: str) -> None:
|
||||
"""设置/修改访问密码。清空所有现有会话(强制重新登录)。"""
|
||||
if len(password) < 6:
|
||||
raise ValueError("密码至少 6 位")
|
||||
salt_hex, hash_hex = _hash_password(password)
|
||||
with _lock:
|
||||
_sessions.clear() # 改密码 = 旧会话全部失效
|
||||
_save({
|
||||
"password_hash": hash_hex,
|
||||
"password_salt": salt_hex,
|
||||
"updated_at": int(time.time()),
|
||||
"sessions": {}, # 清空持久化会话
|
||||
})
|
||||
logger.info("access password set")
|
||||
|
||||
|
||||
def bootstrap_from_env() -> bool:
|
||||
"""首次初始化: 若环境变量 AUTH_PASSWORD 已配置且尚未设过密码, 则用它设密码。
|
||||
|
||||
公网服务器部署场景: 避免每次都要 SSH 端口转发才能设首个密码。
|
||||
明文密码只在内存/配置中, 经 set_password() 哈希后写入 auth.json (chmod 0600)。
|
||||
一旦设置成功, 后续重启不再覆盖 (用户改密码走 UI, 不受环境变量影响)。
|
||||
|
||||
Returns:
|
||||
True 表示本次用环境变量初始化了密码; False 表示无需初始化。
|
||||
"""
|
||||
from app.config import settings
|
||||
|
||||
pwd = (settings.auth_password or "").strip()
|
||||
if not pwd:
|
||||
return False
|
||||
if is_configured():
|
||||
# 已设过密码, 不覆盖 (避免环境变量反复重置用户在 UI 改的密码)
|
||||
return False
|
||||
try:
|
||||
set_password(pwd)
|
||||
logger.info("access password bootstrapped from AUTH_PASSWORD env (one-time)")
|
||||
return True
|
||||
except ValueError as e:
|
||||
# 密码不合规 (< 6 位), 记日志但不阻断启动
|
||||
logger.warning("AUTH_PASSWORD bootstrap skipped: %s", e)
|
||||
return False
|
||||
|
||||
|
||||
def verify_and_create_session(password: str) -> str | None:
|
||||
"""验证密码, 成功则创建会话并返回 token, 失败返回 None。"""
|
||||
d = _load()
|
||||
if not d.get("password_hash"):
|
||||
return None
|
||||
if not _verify_password(password, d.get("password_salt", ""), d["password_hash"]):
|
||||
return None
|
||||
token = _secrets.token_urlsafe(_TOKEN_BYTES)
|
||||
expire = time.time() + SESSION_TTL
|
||||
with _lock:
|
||||
_sessions[token] = expire
|
||||
_persist_sessions_locked()
|
||||
return token
|
||||
|
||||
|
||||
def revoke_session(token: str) -> None:
|
||||
"""注销会话(登出)。"""
|
||||
with _lock:
|
||||
_sessions.pop(token, None)
|
||||
_persist_sessions_locked()
|
||||
|
||||
|
||||
def is_valid_session(token: str) -> bool:
|
||||
"""检查会话是否有效(存在且未过期)。过期则清理。"""
|
||||
if not token:
|
||||
return False
|
||||
with _lock:
|
||||
expire = _sessions.get(token)
|
||||
if expire is None:
|
||||
return False
|
||||
if time.time() > expire:
|
||||
_sessions.pop(token, None)
|
||||
_persist_sessions_locked()
|
||||
return False
|
||||
return True
|
||||
|
||||
|
||||
def _persist_sessions_locked() -> None:
|
||||
"""把当前内存会话写回 auth.json(需持锁调用)。"""
|
||||
d = _load()
|
||||
d["sessions"] = {t: exp for t, exp in _sessions.items()}
|
||||
_save(d)
|
||||
|
||||
|
||||
def _restore_sessions() -> None:
|
||||
"""启动时从 auth.json 恢复未过期会话(支持进程重启不丢登录态)。"""
|
||||
with _lock:
|
||||
d = _load()
|
||||
now = time.time()
|
||||
saved = d.get("sessions") or {}
|
||||
for token, expire in saved.items():
|
||||
if isinstance(expire, (int, float)) and expire > now:
|
||||
_sessions[token] = expire
|
||||
if len(_sessions) != len(saved):
|
||||
# 有过期会话被清理, 落盘一次
|
||||
_persist_sessions_locked()
|
||||
|
||||
|
||||
# 模块加载时恢复会话
|
||||
try:
|
||||
_restore_sessions()
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("restore sessions failed: %s", e)
|
||||
@@ -0,0 +1,357 @@
|
||||
"""AI 概念轮动分析 — 从概念涨幅排名矩阵提炼主线/新晋/退潮信号。
|
||||
|
||||
数据来源:
|
||||
- rps_rotation.build_rps_rotation: 概念涨幅排名矩阵 (N 日 × ~387 概念)
|
||||
- market_overview_builder.build_market_overview: 大盘背景 (指数/情绪/涨停)
|
||||
|
||||
架构 (复刻 market_recap):
|
||||
预计算轮动信号 → 拼装 prompt → stream_ai_text 流式调用 → NDJSON 协议输出
|
||||
协议事件: meta(摘要) / delta(文本片段) / error / done
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import math
|
||||
from collections.abc import AsyncIterator
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# System Prompt — 轮动策略师人格 + 固定章节模板
|
||||
# ================================================================
|
||||
|
||||
_SYSTEM_PROMPT = """你是一位专注 A 股题材轮动的资深策略师,拥有 12 年一线实战经验,擅长从概念板块的**涨幅排名矩阵**中识别主力资金脉络,区分机构主导的持续性主线与游资驱动的脉冲式轮动,产出可直接指导题材跟踪与节奏把握的轮动分析。
|
||||
|
||||
## 输出规范
|
||||
|
||||
用 **Markdown** 格式输出,严格遵循以下结构。不要输出任何 JSON 或代码块,直接输出 Markdown 正文。
|
||||
|
||||
### 1. 🎯 主线研判(2-3 句)
|
||||
点名当前最核心的 1-2 条主线题材(连续多日霸榜的强势概念),用一句话概括其逻辑(政策/产业/业绩/事件驱动),并判断是**主升期/加速期/扩散期/见顶期**。结尾用【主线强度:强 / 中 / 弱】定性。
|
||||
|
||||
### 2. 🆕 新晋强势
|
||||
列出排名快速跃升的概念(从榜单中后段冲进前列的),逐个给出:
|
||||
- 概念名 + 近 N 日排名变化(如 `45→20→8`)
|
||||
- 涨幅加速度(连日递增 = 趋势加强)
|
||||
- 可能的驱动逻辑(从板块属性推断,不要编造具体消息)
|
||||
- 判断是**主力切入**还是**消息脉冲**
|
||||
|
||||
### 3. 📉 退潮预警
|
||||
列出从高位明显滑落的概念(连续排名下滑或涨幅骤降),逐个给出:
|
||||
- 概念名 + 排名下滑轨迹
|
||||
- 退潮性质(高位分歧/资金撤离/补跌)
|
||||
- 是否扩散风险
|
||||
|
||||
### 4. 🏛️ 机构主线 vs 🎰 游资轮动
|
||||
基于排名稳定性区分两类资金行为:
|
||||
- **机构主线**:排名标准差小、长期稳居前列的概念 → 持续性判断、是否可作底仓方向
|
||||
- **游资轮动**:排名剧烈波动、脉冲式冲高的概念 → 短线节奏提示、追高风险
|
||||
给出当前市场**整体轮动节奏**(快轮动/慢轮动/主线聚焦)的判断。
|
||||
|
||||
### 5. 🌐 结合大盘
|
||||
结合提供的大盘数据(指数涨跌/情绪/涨停数),判断:
|
||||
- 当前大盘环境对题材轮动是助力还是阻力
|
||||
- 情绪温度与轮动节奏的匹配度(如情绪冰点但题材活跃 = 抱团;情绪火热但轮动快 = 末段)
|
||||
|
||||
### 6. 🎯 操作建议
|
||||
- **跟踪方向**:主线延续 + 新晋确认的概念
|
||||
- **规避方向**:明确退潮 + 高位脉冲的概念
|
||||
- **节奏提示**:当前适合追高 / 低吸 / 观望,及切换信号(如"主线概念连续 2 日跌出前 10 则确认退潮")
|
||||
|
||||
### 7. ⚠️ 风险提示
|
||||
列出需要盯的风险(如主线断层、情绪与轮动背离、成交萎缩)。末尾附一行:
|
||||
"> ⚠️ 本报告由 AI 基于公开行情数据生成,仅供参考,不构成任何投资建议。交易有风险,入市需谨慎。"
|
||||
|
||||
## 分析准则(务必遵守)
|
||||
|
||||
0. **只输出结论,不输出思考过程**:禁止复述你的分析步骤。不要写"我先看...""基于上述数据我认为"——直接给结论。
|
||||
1. **数据说话**:每个判断引用具体排名/涨幅数值,严禁空泛套话("强势"必须改成"连续 4 日稳居前 5,均涨 +4.2%")。
|
||||
2. **诚实中立**:数据不支持的结论就直言"信号不足,暂无法判断",不要硬凑。
|
||||
3. **区分资金性质**:这是本分析的核心价值——机构 vs 游资的判断必须基于排名稳定性(标准差),不要凭感觉。
|
||||
4. **不重复数字**:正文负责解读信号含义,不要照抄罗列已提供的全部原始数据。
|
||||
5. **简明实战**:总字数 1000-1800 字,重在可执行。
|
||||
6. **客观推断**:若无明确消息,从量价异动推断可能逻辑并给结论,不要标注"[推断]"或编造具体新闻。
|
||||
|
||||
现在请基于下方概念轮动数据进行分析。"""
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 预计算: 把排名矩阵转成结构化轮动信号
|
||||
# ================================================================
|
||||
|
||||
# 每类信号最多取多少个概念喂给 AI (控制 token)
|
||||
_TOP_N = 8
|
||||
|
||||
|
||||
def _compute_rotation_signals(dates: list[str], columns: dict) -> dict:
|
||||
"""从概念涨幅排名矩阵计算轮动信号。
|
||||
|
||||
Args:
|
||||
dates: 日期列表 (最新在最前, 与 columns key 一致)
|
||||
columns: {日期: [[概念, 涨幅], ...]} 每列各自降序
|
||||
|
||||
Returns:
|
||||
{
|
||||
"persistent_leaders": [...], # 连续多日稳居前列 (主线)
|
||||
"rising": [...], # 排名快速跃升 (新晋)
|
||||
"fading": [...], # 从高位滑落 (退潮)
|
||||
"institutional": [...], # 排名稳定 (机构特征)
|
||||
"hot_money": [...], # 排名波动大 (游资特征)
|
||||
}
|
||||
每项含: concept, ranks (按 dates 顺序), pcts, avg_rank, rank_std
|
||||
ranks 时间方向: ranks[0] = 最早日, ranks[-1] = 最新日 (已反转, 左老右新)
|
||||
"""
|
||||
if not dates or not columns:
|
||||
return {}
|
||||
|
||||
# 按时间正序 (左老右新) 处理
|
||||
dates_asc = list(reversed(dates))
|
||||
|
||||
# 收集每个概念在各日期的 (排名, 涨幅)。排名 = 该日在列中的索引 + 1。
|
||||
concept_data: dict[str, list[tuple[int, float]]] = {}
|
||||
for d in dates_asc:
|
||||
col = columns.get(d) or []
|
||||
for idx, (name, pct) in enumerate(col):
|
||||
concept_data.setdefault(name, []).append((idx + 1, pct))
|
||||
|
||||
n_dates = len(dates_asc)
|
||||
|
||||
def _stats(ranks_pcts: list[tuple[int, float]]) -> dict:
|
||||
ranks = [r for r, _ in ranks_pcts]
|
||||
pcts = [p for _, p in ranks_pcts]
|
||||
avg = sum(ranks) / len(ranks) if ranks else 0
|
||||
var = sum((r - avg) ** 2 for r in ranks) / len(ranks) if ranks else 0
|
||||
return {
|
||||
"ranks": ranks,
|
||||
"pcts": [round(p, 4) for p in pcts],
|
||||
"avg_rank": round(avg, 1),
|
||||
"rank_std": round(math.sqrt(var), 1),
|
||||
}
|
||||
|
||||
persistent: list[dict] = []
|
||||
rising: list[dict] = []
|
||||
fading: list[dict] = []
|
||||
institutional: list[dict] = []
|
||||
hot_money: list[dict] = []
|
||||
|
||||
for concept, rp in concept_data.items():
|
||||
# 缺失日补 (大排名, 0 涨幅) 保持时间轴对齐
|
||||
if len(rp) < n_dates:
|
||||
rp = rp + [(999, 0.0)] * (n_dates - len(rp))
|
||||
s = _stats(rp)
|
||||
s["concept"] = concept
|
||||
|
||||
ranks = s["ranks"]
|
||||
latest_rank = ranks[-1]
|
||||
earliest_rank = ranks[0]
|
||||
# 最近 3 日 (不足则全部) 均排名, 判断近期强度
|
||||
recent = ranks[-min(3, len(ranks)):]
|
||||
recent_avg = sum(recent) / len(recent)
|
||||
|
||||
# 主线: 近期稳居前 10
|
||||
if recent_avg <= 10 and latest_rank <= 10:
|
||||
persistent.append(s)
|
||||
|
||||
# 新晋: 早期排名靠后(>30), 最新冲进前 20, 跃升幅度大
|
||||
jump = earliest_rank - latest_rank
|
||||
if earliest_rank > 30 and latest_rank <= 20 and jump >= 20:
|
||||
rising.append(s)
|
||||
|
||||
# 退潮: 早期排名靠前(<=10), 最新滑落到 30 外
|
||||
drop = latest_rank - earliest_rank
|
||||
if earliest_rank <= 10 and latest_rank > 30 and drop >= 20:
|
||||
fading.append(s)
|
||||
|
||||
# 机构: 排名标准差小且平均排名靠前 (稳定强势)
|
||||
if s["rank_std"] <= 5 and s["avg_rank"] <= 20:
|
||||
institutional.append(s)
|
||||
|
||||
# 游资: 排名标准差大 (波动剧烈)
|
||||
if s["rank_std"] >= 20:
|
||||
hot_money.append(s)
|
||||
|
||||
# 排序: 主线按近期排名升序; 新晋按跃升幅度降序; 退潮按跌幅降序
|
||||
persistent.sort(key=lambda x: x["avg_rank"])
|
||||
rising.sort(key=lambda x: x["ranks"][0] - x["ranks"][-1], reverse=True)
|
||||
fading.sort(key=lambda x: x["ranks"][-1] - x["ranks"][0], reverse=True)
|
||||
institutional.sort(key=lambda x: (x["rank_std"], x["avg_rank"]))
|
||||
hot_money.sort(key=lambda x: x["rank_std"], reverse=True)
|
||||
|
||||
return {
|
||||
"persistent_leaders": persistent[:_TOP_N],
|
||||
"rising": rising[:_TOP_N],
|
||||
"fading": fading[:_TOP_N],
|
||||
"institutional": institutional[:_TOP_N],
|
||||
"hot_money": hot_money[:_TOP_N],
|
||||
}
|
||||
|
||||
|
||||
# ================================================================
|
||||
# Prompt 构建
|
||||
# ================================================================
|
||||
|
||||
def _fmt_pct(v) -> str:
|
||||
if v is None:
|
||||
return "—"
|
||||
return f"{v*100:+.2f}%"
|
||||
|
||||
|
||||
def _build_market_block(overview: dict) -> str:
|
||||
"""大盘背景精简块 (复用 market_overview 已算好的字段)。"""
|
||||
indices = overview.get("indices") or []
|
||||
emo = overview.get("emotion") or {}
|
||||
lim = overview.get("limit") or {}
|
||||
amt = overview.get("amount") or {}
|
||||
|
||||
idx_lines = []
|
||||
for idx in indices[:4]:
|
||||
name = idx.get("name") or idx.get("symbol") or "?"
|
||||
chg = idx.get("change_pct")
|
||||
idx_lines.append(f"{name} {_fmt_pct(chg)}")
|
||||
idx_str = " / ".join(idx_lines) or "指数缺失"
|
||||
|
||||
total_amount = (amt.get("total") or 0) / 1e8 # 元 → 亿
|
||||
|
||||
return (
|
||||
f"- 指数: {idx_str}\n"
|
||||
f"- 情绪: {emo.get('score', 50)} ({emo.get('label', '—')})\n"
|
||||
f"- 涨停/炸板/跌停: {lim.get('limit_up', 0)} / {lim.get('broken', 0)} / {lim.get('limit_down', 0)}"
|
||||
f" (最高连板 {lim.get('max_boards', 0)})\n"
|
||||
f"- 两市成交额: {total_amount:.0f} 亿元"
|
||||
)
|
||||
|
||||
|
||||
def _build_signal_block(title: str, items: list[dict]) -> str:
|
||||
"""轮动信号块: 把预计算的概念信号转成紧凑文本。"""
|
||||
if not items:
|
||||
return f"### {title}\n(本类无明显信号)"
|
||||
lines = [f"### {title}"]
|
||||
for it in items:
|
||||
ranks_str = "→".join(str(r) if r < 999 else "—" for r in it["ranks"])
|
||||
avg_pct = sum(it["pcts"]) / len(it["pcts"]) if it["pcts"] else 0
|
||||
lines.append(
|
||||
f"- {it['concept']}: 排名 {ranks_str} | 均排名 {it['avg_rank']} "
|
||||
f"| 排名波动σ {it['rank_std']} | 区间均涨 {_fmt_pct(avg_pct)}"
|
||||
)
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def _build_user_prompt(signals: dict, overview: dict, days: int, dates: list[str], focus: str) -> str:
|
||||
"""组装 user 消息: 大盘背景 + 轮动信号 + focus。"""
|
||||
dates_asc = list(reversed(dates))
|
||||
date_range = f"{dates_asc[0]} ~ {dates_asc[-1]}" if dates_asc else "—"
|
||||
|
||||
parts = [
|
||||
f"# 概念涨幅轮动数据 (最近 {days} 个交易日: {date_range})",
|
||||
"",
|
||||
"## 大盘背景",
|
||||
_build_market_block(overview),
|
||||
"",
|
||||
"## 轮动信号 (排名时间方向: 左→右 = 旧→新, 排名越小越强)",
|
||||
"",
|
||||
_build_signal_block("🎯 主线 (连续霸榜)", signals.get("persistent_leaders", [])),
|
||||
"",
|
||||
_build_signal_block("🆕 新晋强势 (排名跃升)", signals.get("rising", [])),
|
||||
"",
|
||||
_build_signal_block("📉 退潮预警 (高位滑落)", signals.get("fading", [])),
|
||||
"",
|
||||
_build_signal_block("🏛️ 机构特征 (排名稳定)", signals.get("institutional", [])),
|
||||
"",
|
||||
_build_signal_block("🎰 游资特征 (排名波动大)", signals.get("hot_money", [])),
|
||||
]
|
||||
|
||||
if focus.strip():
|
||||
parts.extend(["", f"## 用户关注点\n{focus.strip()}"])
|
||||
|
||||
return "\n".join(parts)
|
||||
|
||||
|
||||
def _build_summary(signals: dict) -> str:
|
||||
"""meta 事件的摘要 (前端可立即展示)。"""
|
||||
leaders = signals.get("persistent_leaders", [])
|
||||
rising = signals.get("rising", [])
|
||||
fading = signals.get("fading", [])
|
||||
leader_names = "、".join(it["concept"] for it in leaders[:3]) or "暂无明确主线"
|
||||
return f"主线: {leader_names} | 新晋 {len(rising)} | 退潮 {len(fading)}"
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 流式主入口
|
||||
# ================================================================
|
||||
|
||||
async def analyze_rotation_stream(
|
||||
repo,
|
||||
days: int = 12,
|
||||
focus: str = "",
|
||||
quote_service=None,
|
||||
depth_service=None,
|
||||
) -> AsyncIterator[str]:
|
||||
"""流式概念轮动分析: yield 出每个 NDJSON 事件。
|
||||
|
||||
Args:
|
||||
repo: KlineRepository (必填)。
|
||||
days: 分析最近 N 个交易日 (7-30)。
|
||||
focus: 用户追加的关注点。
|
||||
quote_service / depth_service: 可选, 大盘背景装配依赖。
|
||||
"""
|
||||
from app.services.rps_rotation import build_rps_rotation
|
||||
from app.services.market_overview_builder import build_market_overview
|
||||
|
||||
# 1. 取轮动矩阵
|
||||
rotation = build_rps_rotation(repo, days)
|
||||
dates = rotation.get("dates") or []
|
||||
columns = rotation.get("columns") or {}
|
||||
|
||||
if not dates or not columns:
|
||||
yield json.dumps({
|
||||
"type": "error",
|
||||
"message": "暂无概念轮动数据,请先在「概念分析」页获取概念数据源",
|
||||
}, ensure_ascii=False)
|
||||
return
|
||||
|
||||
# 2. 预计算轮动信号
|
||||
signals = _compute_rotation_signals(dates, columns)
|
||||
|
||||
# 3. 大盘背景 (失败不阻断, 降级为空)
|
||||
try:
|
||||
overview = build_market_overview(repo, quote_service, depth_service)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("rotation analyze: 大盘背景获取失败, 降级为空: %s", e)
|
||||
overview = {}
|
||||
|
||||
# 4. meta 事件
|
||||
yield json.dumps({
|
||||
"type": "meta",
|
||||
"days": days,
|
||||
"summary": _build_summary(signals),
|
||||
}, ensure_ascii=False)
|
||||
|
||||
# 5. 构建 prompt + 流式调用 LLM
|
||||
try:
|
||||
from app.services.ai_provider import stream_ai_text, ai_configured
|
||||
|
||||
if not ai_configured():
|
||||
yield json.dumps({
|
||||
"type": "error",
|
||||
"message": "AI 未配置,请在「设置」页填写 API Key 与接口地址",
|
||||
}, ensure_ascii=False)
|
||||
return
|
||||
|
||||
user_prompt = _build_user_prompt(signals, overview, days, dates, focus)
|
||||
async for delta in stream_ai_text(
|
||||
[
|
||||
{"role": "system", "content": _SYSTEM_PROMPT},
|
||||
{"role": "user", "content": user_prompt},
|
||||
],
|
||||
temperature=0.5,
|
||||
max_tokens=4000,
|
||||
):
|
||||
yield json.dumps({"type": "delta", "content": delta}, ensure_ascii=False)
|
||||
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.exception("AI concept rotation analyze failed: %s", e)
|
||||
yield json.dumps({"type": "error", "message": f"AI 轮动分析失败: {e}"}, ensure_ascii=False)
|
||||
|
||||
yield json.dumps({"type": "done"}, ensure_ascii=False)
|
||||
@@ -316,7 +316,18 @@ class DepthService:
|
||||
"status": e.get("status"),
|
||||
"fetched_at": e.get("fetched_ts"),
|
||||
})
|
||||
df = pl.DataFrame(rows)
|
||||
# 显式 schema: sealed_up/sealed_down 是 bool 与 None 混合, 不指定 schema
|
||||
# polars 会按首行推断类型, 后续遇到不一致 (bool vs null) 报
|
||||
# "could not append value: false of type: bool to the builder"。
|
||||
df = pl.DataFrame(rows, schema={
|
||||
"symbol": pl.Utf8,
|
||||
"sealed_up": pl.Boolean,
|
||||
"sealed_down": pl.Boolean,
|
||||
"ask1_vol": pl.Int64,
|
||||
"bid1_vol": pl.Int64,
|
||||
"status": pl.Utf8,
|
||||
"fetched_at": pl.Float64,
|
||||
})
|
||||
ds = today.isoformat()
|
||||
out = self._repo.store.data_dir / "depth5" / f"date={ds}" / "part.parquet"
|
||||
out.parent.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
@@ -38,6 +38,7 @@ class PullConfig:
|
||||
"url", "method", "headers", "body", "response_path",
|
||||
"field_map", "schedule_minutes", "enabled",
|
||||
"last_run", "last_status", "last_message", "last_rows",
|
||||
"next_run",
|
||||
)
|
||||
|
||||
def __init__(
|
||||
@@ -54,6 +55,7 @@ class PullConfig:
|
||||
last_status: str | None = None,
|
||||
last_message: str | None = None,
|
||||
last_rows: int | None = None,
|
||||
next_run: str | None = None,
|
||||
) -> None:
|
||||
self.url = url
|
||||
self.method = method # GET | POST
|
||||
@@ -67,6 +69,7 @@ class PullConfig:
|
||||
self.last_status = last_status # "success" | "error"
|
||||
self.last_message = last_message
|
||||
self.last_rows = last_rows
|
||||
self.next_run = next_run # 下次预计运行 (ISO, 调度器写入)
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
return {
|
||||
@@ -82,6 +85,7 @@ class PullConfig:
|
||||
"last_status": self.last_status,
|
||||
"last_message": self.last_message,
|
||||
"last_rows": self.last_rows,
|
||||
"next_run": self.next_run,
|
||||
}
|
||||
|
||||
@classmethod
|
||||
@@ -101,6 +105,7 @@ class PullConfig:
|
||||
last_status=d.get("last_status"),
|
||||
last_message=d.get("last_message"),
|
||||
last_rows=d.get("last_rows"),
|
||||
next_run=d.get("next_run"),
|
||||
)
|
||||
|
||||
|
||||
@@ -407,8 +412,10 @@ def write_ext_parquet(
|
||||
existing = pl.read_parquet(out_path)
|
||||
key = "symbol" if "symbol" in df.columns else df.columns[0]
|
||||
df = pl.concat([existing, df]).unique(subset=[key], keep="last")
|
||||
except Exception:
|
||||
pass
|
||||
except Exception as e:
|
||||
# schema 不一致 (列不同) 时 concat 失败 → 直接用新 df 覆盖。
|
||||
# 记日志而非静默吞掉, 便于排查"数据结构错乱"类问题。
|
||||
logger.warning("扩展表 %s 合并去重失败, 将覆盖写入: %s", config.id, e)
|
||||
else:
|
||||
# 时序: timeseries/ 下按日期分区
|
||||
out_dir = cfg_dir / "timeseries" / f"date={snap}"
|
||||
@@ -421,8 +428,8 @@ def write_ext_parquet(
|
||||
existing = pl.read_parquet(out_path)
|
||||
key = "symbol" if "symbol" in df.columns else df.columns[0]
|
||||
df = pl.concat([existing, df]).unique(subset=[key], keep="last")
|
||||
except Exception:
|
||||
pass
|
||||
except Exception as e:
|
||||
logger.warning("扩展表 %s 合并去重失败, 将覆盖写入: %s", config.id, e)
|
||||
|
||||
df = cast_df_to_schema(df, config.fields)
|
||||
df.write_parquet(out_path)
|
||||
|
||||
@@ -0,0 +1,236 @@
|
||||
"""内置扩展数据预设 — 概念/行业首次启动自动拉取。
|
||||
|
||||
设计原则:
|
||||
- 扩展数据通用逻辑零改动 (ExtConfig / fetch_and_ingest / API / 前端均不动)
|
||||
- 仅在本模块做「接口结构 → 本地 schema」的转换
|
||||
- 「已存在则跳过」: 绝不覆盖用户已有数据, 老用户零影响
|
||||
- 拉取失败只记 warning, 不阻断启动 (保持「没数据也能跑」)
|
||||
|
||||
种子数据来源: https://files.688798.xyz/ths/{concepts,industries}.json
|
||||
作者更新数据只需改接口上的 JSON, 用户下次拉取自动同步, 无需发版。
|
||||
|
||||
接入点: app.main.lifespan → ensure_builtin_presets(store.data_dir)
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from pathlib import Path
|
||||
|
||||
from app.services.ext_data import (
|
||||
ExtConfig,
|
||||
ExtConfigStore,
|
||||
ExtField,
|
||||
PullConfig,
|
||||
rows_to_parquet,
|
||||
)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 种子数据源 (作者维护, 改这里即对所有用户生效)
|
||||
_THS_BASE = "https://files.688798.xyz/ths"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 预设定义: 字段结构 + 拉取配方
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _concept_preset() -> ExtConfig:
|
||||
"""扩展概念 (ext_gn_ths)。
|
||||
|
||||
接口结构: [{symbol, name, concepts: [概念1, 概念2, ...]}]
|
||||
本地 schema: 股票代码 / 股票简称 / 所属概念(分号拼接) / symbol / code
|
||||
"""
|
||||
return ExtConfig(
|
||||
id="ext_gn_ths",
|
||||
label="扩展概念",
|
||||
mode="snapshot",
|
||||
fields=[
|
||||
ExtField("symbol", "string", "标的代码"),
|
||||
ExtField("code", "string", "代码"),
|
||||
ExtField("股票代码", "string", "股票代码"),
|
||||
ExtField("股票简称", "string", "股票简称"),
|
||||
ExtField("所属概念", "string", "所属概念"),
|
||||
],
|
||||
description="同花顺概念分类 (首次启动自动拉取, 可在扩展数据页手动更新)",
|
||||
symbol_map={"type": "mapped", "col": "股票代码"},
|
||||
code_map={"type": "computed", "from": "symbol", "method": "strip_exchange"},
|
||||
pull=PullConfig(
|
||||
url=f"{_THS_BASE}/concepts.json",
|
||||
method="GET",
|
||||
schedule_minutes=1440,
|
||||
enabled=False,
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
def _industry_preset() -> ExtConfig:
|
||||
"""扩展行业 (ext_hy_ths)。
|
||||
|
||||
接口结构: [{symbol, name, industries: [一级行业, 二级行业, 三级行业]}]
|
||||
本地 schema: 股票代码 / 股票简称 / 所属同花顺行业(横杠拼接) / symbol / code
|
||||
"""
|
||||
return ExtConfig(
|
||||
id="ext_hy_ths",
|
||||
label="扩展行业",
|
||||
mode="snapshot",
|
||||
fields=[
|
||||
ExtField("symbol", "string", "标的代码"),
|
||||
ExtField("code", "string", "代码"),
|
||||
ExtField("股票代码", "string", "股票代码"),
|
||||
ExtField("股票简称", "string", "股票简称"),
|
||||
ExtField("所属同花顺行业", "string", "所属同花顺行业"),
|
||||
],
|
||||
description="同花顺行业分类 (首次启动自动拉取, 可在扩展数据页手动更新)",
|
||||
symbol_map={"type": "mapped", "col": "股票代码"},
|
||||
code_map={"type": "computed", "from": "symbol", "method": "strip_exchange"},
|
||||
pull=PullConfig(
|
||||
url=f"{_THS_BASE}/industries.json",
|
||||
method="GET",
|
||||
schedule_minutes=1440,
|
||||
enabled=False,
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
def _presets() -> list[ExtConfig]:
|
||||
return [_concept_preset(), _industry_preset()]
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 接口结构 → 本地 schema 转换 (仅预设使用)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _symbol_to_code(symbol: str) -> str:
|
||||
"""symbol (000001.SZ) → code (000001)。"""
|
||||
return symbol.split(".", 1)[0] if "." in symbol else symbol
|
||||
|
||||
|
||||
def _flatten_concept_rows(raw_rows: list[dict]) -> list[dict]:
|
||||
"""概念: concepts 数组 → 分号拼接成「所属概念」字符串。
|
||||
|
||||
[{symbol, name, concepts:[...]}] → [{股票代码, 股票简称, 所属概念, symbol, code}]
|
||||
注: code 由 symbol 派生 (000001.SZ → 000001), 因 rows_to_parquet 不执行 code_map。
|
||||
"""
|
||||
out: list[dict] = []
|
||||
for r in raw_rows:
|
||||
sym = (r.get("symbol") or "").strip()
|
||||
if not sym:
|
||||
continue
|
||||
concepts = r.get("concepts") or []
|
||||
out.append({
|
||||
"股票代码": sym,
|
||||
"股票简称": r.get("name") or "",
|
||||
"所属概念": ";".join(str(c) for c in concepts if c),
|
||||
"symbol": sym,
|
||||
"code": _symbol_to_code(sym),
|
||||
})
|
||||
return out
|
||||
|
||||
|
||||
def _flatten_industry_rows(raw_rows: list[dict]) -> list[dict]:
|
||||
"""行业: industries 数组 → 横杠拼接成「所属同花顺行业」字符串。
|
||||
|
||||
[{symbol, name, industries:[...]}] → [{股票代码, 股票简称, 所属同花顺行业, symbol, code}]
|
||||
"""
|
||||
out: list[dict] = []
|
||||
for r in raw_rows:
|
||||
sym = (r.get("symbol") or "").strip()
|
||||
if not sym:
|
||||
continue
|
||||
inds = r.get("industries") or []
|
||||
out.append({
|
||||
"股票代码": sym,
|
||||
"股票简称": r.get("name") or "",
|
||||
"所属同花顺行业": "-".join(str(i) for i in inds if i),
|
||||
"symbol": sym,
|
||||
"code": _symbol_to_code(sym),
|
||||
})
|
||||
return out
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 拉取执行 (复用 httpx, 不依赖 fetch_and_ingest 的 PullConfig 路径)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
async def _fetch_json(url: str) -> list[dict]:
|
||||
"""请求 JSON 接口, 返回行数组。超时 30s, 失败抛异常由调用方兜底。"""
|
||||
import httpx
|
||||
|
||||
async with httpx.AsyncClient(timeout=30) as client:
|
||||
resp = await client.get(url)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
if not isinstance(data, list):
|
||||
raise ValueError(f"接口返回不是数组: {type(data)}")
|
||||
return data
|
||||
|
||||
|
||||
async def _seed_one(config: ExtConfig, flatten, data_dir: Path) -> int:
|
||||
"""拉取 + 转换 + 写入单个预设。返回写入行数。"""
|
||||
from datetime import date
|
||||
|
||||
raw = await _fetch_json(config.pull.url)
|
||||
rows = flatten(raw)
|
||||
if not rows:
|
||||
raise ValueError(f"接口返回 0 行: {config.pull.url}")
|
||||
n = rows_to_parquet(rows, config, data_dir, snapshot_date=date.today())
|
||||
return n
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 对外入口
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def get_preset(config_id: str) -> ExtConfig | None:
|
||||
"""按 id 取预设定义 (供 API 层校验 id 合法性)。"""
|
||||
for c in _presets():
|
||||
if c.id == config_id:
|
||||
return c
|
||||
return None
|
||||
|
||||
|
||||
async def ensure_builtin_presets(data_dir: Path) -> None:
|
||||
"""启动时: 为缺失的预设创建 config.json (含 pull 配置), 但【不拉取数据】。
|
||||
|
||||
设计: 数据获取改为用户在概念/行业页手动点「获取数据」触发, 避免启动时
|
||||
网络请求阻塞, 也避免「自动拉取」与「用户自主控制」的预期冲突。
|
||||
|
||||
安全保证:
|
||||
- 已存在则完全跳过 (绝不覆盖用户数据)
|
||||
- 只写 config.json, 失败只记 warning 不阻断启动
|
||||
"""
|
||||
store = ExtConfigStore(data_dir)
|
||||
|
||||
for config in _presets():
|
||||
existing = store.get(config.id)
|
||||
if existing is not None:
|
||||
# 用户已有此表 (老用户 / 自己重建过) → 一律不动
|
||||
continue
|
||||
try:
|
||||
store.upsert(config)
|
||||
logger.info("内置扩展表 %s 配置已就绪 (待用户手动获取数据)", config.id)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("内置扩展表 %s 配置写入失败 (不影响启动): %s", config.id, e)
|
||||
|
||||
|
||||
async def fetch_preset(config_id: str, data_dir: Path) -> int:
|
||||
"""手动触发某个预设的数据拉取 (供 API 调用)。
|
||||
|
||||
Raises:
|
||||
ValueError: config_id 不是内置预设
|
||||
Exception: 网络请求/解析/写入失败 (由 API 层转 HTTP 错误)
|
||||
"""
|
||||
config = get_preset(config_id)
|
||||
if config is None:
|
||||
raise ValueError(f"未知的内置预设: {config_id}")
|
||||
|
||||
flatten = _flatten_concept_rows if config_id == "ext_gn_ths" else _flatten_industry_rows
|
||||
|
||||
# 确保 config.json 存在 (用户可能从未启动过 ensure_builtin_presets)
|
||||
store = ExtConfigStore(data_dir)
|
||||
if store.get(config_id) is None:
|
||||
store.upsert(config)
|
||||
|
||||
n = await _seed_one(config, flatten, data_dir)
|
||||
logger.info("内置扩展表 %s 手动拉取成功: %d 行", config_id, n)
|
||||
return n
|
||||
@@ -75,6 +75,19 @@ def _apply_field_map(rows: list[dict], field_map: dict[str, str]) -> list[dict]:
|
||||
# 拉取执行
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _apply_preset_flatten(config_id: str, rows: list[dict]) -> list[dict]:
|
||||
"""对内置预设 (概念/行业) 应用结构转换, 与 fetch_preset 保持一致。
|
||||
|
||||
延迟导入避免与 ext_presets 形成循环依赖。
|
||||
非预设 id 原样返回。
|
||||
"""
|
||||
if config_id not in ("ext_gn_ths", "ext_hy_ths"):
|
||||
return rows
|
||||
from app.services.ext_presets import _flatten_concept_rows, _flatten_industry_rows
|
||||
flatten = _flatten_concept_rows if config_id == "ext_gn_ths" else _flatten_industry_rows
|
||||
return flatten(rows)
|
||||
|
||||
|
||||
async def fetch_and_ingest(
|
||||
config: ExtConfig,
|
||||
data_dir,
|
||||
@@ -111,6 +124,12 @@ async def fetch_and_ingest(
|
||||
if not rows:
|
||||
raise ValueError("提取到的行数为 0")
|
||||
|
||||
# 内置预设 (概念/行业): 应用结构转换, 让产出 schema 与分析页一致。
|
||||
# 否则 raw 接口列 (concepts/industries 数组、name) 会直接覆盖正确的 part.parquet,
|
||||
# 导致分析页因找不到维度字段 (所属概念/所属同花顺行业) 而"数据消失"。
|
||||
# 见 ext_presets._flatten_* —— 手动拉取 / 定时拉取都必须走同一套转换。
|
||||
rows = _apply_preset_flatten(config.id, rows)
|
||||
|
||||
# 字段映射
|
||||
rows = _apply_field_map(rows, pull.field_map)
|
||||
|
||||
@@ -129,21 +148,46 @@ async def fetch_and_ingest(
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class PullScheduler:
|
||||
"""后台调度器：为每个启用了 pull 的 ExtConfig 维护定时任务。"""
|
||||
"""后台调度器：为每个启用了 pull 的 ExtConfig 维护定时任务。
|
||||
|
||||
线程安全说明:
|
||||
refresh()/stop() 可能从主事件循环 (lifespan startup) 或同步路由的
|
||||
worker 线程 (configure_pull 是 def 而非 async def, FastAPI 丢进线程池)
|
||||
调用。worker 线程里没有 running loop, 直接 asyncio.create_task 会抛
|
||||
"no running event loop"。因此对 task 的增删一律通过
|
||||
call_soon_threadsafe 提交到主循环执行 —— 同一套代码两种调用场景都安全。
|
||||
"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self._tasks: dict[str, asyncio.Task] = {}
|
||||
self._running = False
|
||||
self._lock = threading.Lock()
|
||||
self._loop: asyncio.AbstractEventLoop | None = None
|
||||
|
||||
def start(self, data_dir) -> None:
|
||||
"""启动调度（在 lifespan startup 调用）。"""
|
||||
"""启动调度（在 lifespan startup 调用，主事件循环内）。"""
|
||||
self._running = True
|
||||
self._data_dir = data_dir
|
||||
try:
|
||||
self._loop = asyncio.get_running_loop()
|
||||
except RuntimeError:
|
||||
self._loop = None
|
||||
logger.info("PullScheduler started")
|
||||
|
||||
def _submit(self, fn, *args) -> None:
|
||||
"""把一个 callable 提交到主事件循环执行 (线程安全)。
|
||||
|
||||
startup 在主循环内调用时 fn 立即排队; worker 线程调用时跨线程排队。
|
||||
两者都通过 call_soon_threadsafe, 保证 _tasks 字典的读写只在主循环里发生。
|
||||
"""
|
||||
loop = self._loop
|
||||
if loop is None or loop.is_closed():
|
||||
raise RuntimeError(
|
||||
"PullScheduler: 事件循环不可用 (start() 未在事件循环中调用?)"
|
||||
)
|
||||
loop.call_soon_threadsafe(fn, *args)
|
||||
|
||||
def stop(self) -> None:
|
||||
"""停止所有任务。"""
|
||||
"""停止所有任务 (从 shutdown 调用)。"""
|
||||
self._running = False
|
||||
for task in self._tasks.values():
|
||||
task.cancel()
|
||||
@@ -151,47 +195,61 @@ class PullScheduler:
|
||||
logger.info("PullScheduler stopped")
|
||||
|
||||
def refresh(self, data_dir) -> None:
|
||||
"""重新加载配置，更新调度任务（增/删/改）。"""
|
||||
"""重新加载配置，更新调度任务（增/删/改）。线程安全。"""
|
||||
self._data_dir = data_dir
|
||||
store = ExtConfigStore(data_dir)
|
||||
configs = store.load_all()
|
||||
|
||||
active_ids: set[str] = set()
|
||||
new_configs: list[ExtConfig] = []
|
||||
|
||||
for config in configs:
|
||||
if not config.pull or not config.pull.enabled or not config.pull.url:
|
||||
continue
|
||||
active_ids.add(config.id)
|
||||
if config.id not in self._tasks:
|
||||
# 新增调度
|
||||
task = asyncio.create_task(self._run_loop(config))
|
||||
self._tasks[config.id] = task
|
||||
logger.info("PullScheduler: scheduled %s (every %d min)", config.id, config.pull.schedule_minutes)
|
||||
new_configs.append(config)
|
||||
|
||||
# 移除不再活跃的
|
||||
for cid in list(self._tasks):
|
||||
if cid not in active_ids:
|
||||
self._tasks[cid].cancel()
|
||||
del self._tasks[cid]
|
||||
# 需要移除的 id (快照当前 task 字典的键, 避免遍历时改字典)
|
||||
remove_ids = [cid for cid in list(self._tasks) if cid not in active_ids]
|
||||
|
||||
# 所有对 _tasks 的修改都提交到主循环里执行, 保证线程安全
|
||||
def _apply() -> None:
|
||||
for config in new_configs:
|
||||
if config.id not in self._tasks: # 二次校验, 防重复
|
||||
self._tasks[config.id] = self._loop.create_task(
|
||||
self._run_loop(config)
|
||||
)
|
||||
logger.info(
|
||||
"PullScheduler: scheduled %s (every %d min)",
|
||||
config.id, config.pull.schedule_minutes,
|
||||
)
|
||||
for cid in remove_ids:
|
||||
task = self._tasks.pop(cid, None)
|
||||
if task is not None:
|
||||
task.cancel()
|
||||
logger.info("PullScheduler: removed %s", cid)
|
||||
|
||||
self._submit(_apply)
|
||||
|
||||
async def _run_loop(self, config: ExtConfig) -> None:
|
||||
"""单个配置的定时拉取循环。"""
|
||||
"""单个配置的定时拉取循环。
|
||||
|
||||
策略: 启用后立即执行一次, 之后按 interval 循环。
|
||||
每次循环重读最新配置 (fresh), interval 取自 fresh.pull.schedule_minutes,
|
||||
这样用户中途修改间隔也能立即生效 (无需重启)。
|
||||
"""
|
||||
try:
|
||||
while self._running:
|
||||
pull = config.pull
|
||||
if not pull:
|
||||
break
|
||||
interval = max(pull.schedule_minutes * 60, 60) # 至少 60s
|
||||
await asyncio.sleep(interval)
|
||||
if not self._running:
|
||||
break
|
||||
try:
|
||||
# 重新加载最新配置（用户可能中途修改）
|
||||
# 每轮重读最新配置 — 用户可能修改了 url / interval / enabled
|
||||
store = ExtConfigStore(self._data_dir)
|
||||
fresh = store.get(config.id)
|
||||
if not fresh or not fresh.pull or not fresh.pull.enabled:
|
||||
break
|
||||
pull = fresh.pull
|
||||
|
||||
# 先执行一次 (启用即拉取, 让用户立刻看到生效)
|
||||
try:
|
||||
n, d = await fetch_and_ingest(fresh, self._data_dir)
|
||||
fresh.pull.last_run = datetime.now(timezone.utc).isoformat()
|
||||
fresh.pull.last_status = "success"
|
||||
@@ -200,14 +258,79 @@ class PullScheduler:
|
||||
store.upsert(fresh)
|
||||
logger.info("PullScheduler: %s success, %d rows", config.id, n)
|
||||
except Exception as e:
|
||||
fresh2 = store.get(config.id)
|
||||
if fresh2 and fresh2.pull:
|
||||
fresh2.pull.last_run = datetime.now(timezone.utc).isoformat()
|
||||
fresh2.pull.last_status = "error"
|
||||
fresh2.pull.last_message = str(e)[:200]
|
||||
store.upsert(fresh2)
|
||||
logger.warning("PullScheduler: %s error: %s", config.id, e)
|
||||
|
||||
# 间隔取自最新配置 (每次重新读取, 修复改间隔不生效)
|
||||
interval = max(pull.schedule_minutes * 60, 60) # 至少 60s
|
||||
# 预告下次运行时间, 供前端展示
|
||||
next_dt = datetime.now(timezone.utc).timestamp() + interval
|
||||
latest = store.get(config.id)
|
||||
if latest and latest.pull:
|
||||
latest.pull.next_run = datetime.fromtimestamp(
|
||||
next_dt, tz=timezone.utc
|
||||
).isoformat()
|
||||
store.upsert(latest)
|
||||
|
||||
await asyncio.sleep(interval)
|
||||
if not self._running:
|
||||
break
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
|
||||
async def _run_loop(self, config: ExtConfig) -> None:
|
||||
"""单个配置的定时拉取循环。
|
||||
|
||||
策略: 启用后立即执行一次, 之后按 interval 循环。
|
||||
每次循环重读最新配置 (fresh), interval 取自 fresh.pull.schedule_minutes,
|
||||
这样用户中途修改间隔也能立即生效 (无需重启)。
|
||||
"""
|
||||
try:
|
||||
while self._running:
|
||||
# 每轮重读最新配置 — 用户可能修改了 url / interval / enabled
|
||||
store = ExtConfigStore(self._data_dir)
|
||||
fresh = store.get(config.id)
|
||||
if fresh and fresh.pull:
|
||||
if not fresh or not fresh.pull or not fresh.pull.enabled:
|
||||
break
|
||||
pull = fresh.pull
|
||||
|
||||
# 先执行一次 (启用即拉取, 让用户立刻看到生效)
|
||||
try:
|
||||
n, d = await fetch_and_ingest(fresh, self._data_dir)
|
||||
fresh.pull.last_run = datetime.now(timezone.utc).isoformat()
|
||||
fresh.pull.last_status = "error"
|
||||
fresh.pull.last_message = str(e)[:200]
|
||||
fresh.pull.last_status = "success"
|
||||
fresh.pull.last_message = f"{n} rows @ {d}"
|
||||
fresh.pull.last_rows = n
|
||||
store.upsert(fresh)
|
||||
logger.info("PullScheduler: %s success, %d rows", config.id, n)
|
||||
except Exception as e:
|
||||
fresh2 = store.get(config.id)
|
||||
if fresh2 and fresh2.pull:
|
||||
fresh2.pull.last_run = datetime.now(timezone.utc).isoformat()
|
||||
fresh2.pull.last_status = "error"
|
||||
fresh2.pull.last_message = str(e)[:200]
|
||||
store.upsert(fresh2)
|
||||
logger.warning("PullScheduler: %s error: %s", config.id, e)
|
||||
|
||||
# 间隔取自最新配置 (每次重新读取, 修复改间隔不生效)
|
||||
interval = max(pull.schedule_minutes * 60, 60) # 至少 60s
|
||||
# 预告下次运行时间, 供前端展示
|
||||
next_dt = datetime.now(timezone.utc).timestamp() + interval
|
||||
latest = store.get(config.id)
|
||||
if latest and latest.pull:
|
||||
latest.pull.next_run = datetime.fromtimestamp(
|
||||
next_dt, tz=timezone.utc
|
||||
).isoformat()
|
||||
store.upsert(latest)
|
||||
|
||||
await asyncio.sleep(interval)
|
||||
if not self._running:
|
||||
break
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
|
||||
|
||||
@@ -0,0 +1,187 @@
|
||||
"""AI 财务分析服务 — 读取个股财务数据 → 构建专业提示词 → 流式调用 LLM。
|
||||
|
||||
职责: 拉取单只标的的 4 张财务表 → 转成紧凑 JSON → 拼装 CFA 分析师级系统提示词
|
||||
→ 流式调用 OpenAI 兼容 API → 逐 chunk 吐给前端。
|
||||
|
||||
不知道: HTTP、前端、配置持久化。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
from pathlib import Path
|
||||
from typing import AsyncIterator
|
||||
|
||||
import polars as pl
|
||||
|
||||
from app.services.financial_sync import get_financial_df
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 最多注入的报告期数(最新 N 期),避免上下文爆炸 / token 浪费
|
||||
_MAX_PERIODS = 4
|
||||
|
||||
|
||||
def _load_stock_financials(data_dir: Path, symbol: str) -> dict[str, list[dict]]:
|
||||
"""读取该标的的 4 张财务表,返回 {table: [records...]}(按 period_end 降序,截取最新 N 期)。
|
||||
|
||||
数值统一做 NaN/Inf → null 清洗,保证 JSON 序列化不报错。
|
||||
"""
|
||||
result: dict[str, list[dict]] = {}
|
||||
for table in ("metrics", "income", "balance_sheet", "cash_flow"):
|
||||
df = get_financial_df(data_dir, table)
|
||||
if df.is_empty():
|
||||
result[table] = []
|
||||
continue
|
||||
df = df.filter(pl.col("symbol") == symbol)
|
||||
if df.is_empty():
|
||||
result[table] = []
|
||||
continue
|
||||
# 按 period_end 降序,截取最新 N 期
|
||||
if "period_end" in df.columns:
|
||||
df = df.sort("period_end", descending=True).head(_MAX_PERIODS)
|
||||
# 清洗 NaN/Inf,转成 JSON 安全的 dict 列表
|
||||
rows = []
|
||||
for rec in df.to_dicts():
|
||||
clean = {}
|
||||
for k, v in rec.items():
|
||||
if k == "symbol":
|
||||
continue # 不需要重复回传 symbol
|
||||
if isinstance(v, float):
|
||||
import math
|
||||
clean[k] = None if not math.isfinite(v) else v
|
||||
else:
|
||||
clean[k] = v
|
||||
rows.append(clean)
|
||||
result[table] = rows
|
||||
return result
|
||||
|
||||
|
||||
def _summarize(fins: dict[str, list[dict]]) -> str:
|
||||
"""生成一行业务摘要,便于 LLM 快速把握数据全貌(行数/期数)。"""
|
||||
parts = []
|
||||
for table in ("metrics", "income", "balance_sheet", "cash_flow"):
|
||||
rows = fins.get(table, [])
|
||||
if rows:
|
||||
periods = [r.get("period_end") for r in rows if r.get("period_end")]
|
||||
parts.append(f"{table}: {len(rows)}期 ({', '.join(str(p) for p in periods[:3])})")
|
||||
else:
|
||||
parts.append(f"{table}: 无数据")
|
||||
return " · ".join(parts)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 系统提示词 —— CFA 分析师级,九维分析框架
|
||||
# ================================================================
|
||||
|
||||
_SYSTEM_PROMPT = """你是一位拥有 15 年 A 股投研经验的资深财务分析师(CFA + CPA),服务于专业机构投资者。你的任务是:基于提供的上市公司财务数据,产出一份**严谨、专业、可直接用于投资决策**的财务分析报告。
|
||||
|
||||
## 输出规范
|
||||
|
||||
用 **Markdown** 格式输出,严格遵循以下结构。不要输出任何 JSON 或代码块,直接输出 Markdown 正文。
|
||||
|
||||
### 1. 📌 核心摘要(1-2 句)
|
||||
用一句话概括该公司的财务画像:盈利质量、成长动能、财务健康度的最关键判断。结尾用【综合评级:★★★☆☆】给出 1-5 星评级。
|
||||
|
||||
### 2. ✅ 亮点(2-3 条)
|
||||
列出最值得关注的**积极信号**,每条用加粗短语领起,配数据支撑。例如盈利高增、ROE 持续提升、现金流充沛等。
|
||||
|
||||
### 3. ⚠️ 风险提示(2-3 条)
|
||||
客观指出**潜在风险或值得警惕的信号**,例如应收激增、存货堆积、经营现金流与净利润背离、债务攀升等。宁可保守,不要回避。
|
||||
|
||||
### 4. 📊 分项诊断
|
||||
用**表格**呈现各维度的诊断结论,列为「维度 / 关键指标 / 判断」。维度包括:
|
||||
- **盈利能力**:ROE / ROA / 毛利率 / 净利率
|
||||
- **成长性**:营收同比 / 净利润同比
|
||||
- **偿债能力**:资产负债率 / 流动比率(用资产/负债估算)
|
||||
- **现金流**:经营现金流净额 / 与净利润的匹配度
|
||||
- **营运效率**:存货周转率等(有数据时)
|
||||
|
||||
每个判断给「优秀 / 良好 / 一般 / 偏弱 / 警惕」之一,并一句话说明依据。
|
||||
|
||||
### 5. 🎯 综合评估与展望
|
||||
2-3 段总结:该公司当前的财务状态(优秀/稳健/承压/恶化)、核心驱动力、未来需重点跟踪的指标。**结尾给出"投资参考"**:从纯财务质量角度,该股属于(高质量蓝筹 / 稳健成长 / 周期波动 / 财务承压 / 高风险)中的哪一类。
|
||||
|
||||
## 分析准则(务必遵守)
|
||||
|
||||
1. **数据说话**:每个判断必须引用具体数值(如"营收同比 +28.5%"),严禁空泛套话
|
||||
2. **纵向对比**:利用多期数据看趋势(改善/恶化),而非只看单期
|
||||
3. **交叉验证**:经营现金流 vs 净利润(是否造血)、毛利率 vs 费用率(盈利结构)、负债 vs 资产(杠杆)
|
||||
4. **行业常识**:对照 A 股常识判断水平(如 ROE>15% 优秀,资产负债率>70% 偏高,毛利率<20% 偏低)
|
||||
5. **诚实中立**:数据不支持时直言"数据不足,无法判断",绝不编造或过度演绎
|
||||
6. **简明有力**:避免冗长,用专业投资者能扫读的密度输出,总字数 800-1500 字
|
||||
|
||||
## 重要免责
|
||||
报告末尾附一行:"> ⚠️ 本报告由 AI 基于公开财务数据生成,仅供参考,不构成任何投资建议。"
|
||||
|
||||
现在请基于下方数据进行分析。"""
|
||||
|
||||
|
||||
def _build_user_prompt(fins: dict[str, list[dict]], symbol: str, focus: str) -> str:
|
||||
"""构建用户消息:标的代码 + 数据 JSON + 可选关注点。"""
|
||||
data_json = json.dumps(fins, ensure_ascii=False, indent=2)
|
||||
lines = [
|
||||
f"标的标准代码: {symbol}",
|
||||
f"数据概览: {_summarize(fins)}",
|
||||
"",
|
||||
"以下是该标的最新财务数据(JSON 格式,金额单位为元,比率类指标为百分点):",
|
||||
"```json",
|
||||
data_json,
|
||||
"```",
|
||||
]
|
||||
if focus.strip():
|
||||
lines.extend([
|
||||
"",
|
||||
f"本次分析请特别关注: {focus.strip()}",
|
||||
])
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
async def analyze_financials_stream(
|
||||
data_dir: Path,
|
||||
symbol: str,
|
||||
focus: str = "",
|
||||
) -> AsyncIterator[str]:
|
||||
"""流式分析:yield 出每个文本 chunk。
|
||||
|
||||
- 启动时先 yield 一条 {"type":"meta",...} 让前端显示数据摘要
|
||||
- 之后逐 chunk yield {"type":"delta","content":"..."}
|
||||
- 出错时 yield {"type":"error","message":"..."}
|
||||
- 结束 yield {"type":"done"}
|
||||
"""
|
||||
# 1. 加载数据
|
||||
fins = _load_stock_financials(data_dir, symbol)
|
||||
total_rows = sum(len(v) for v in fins.values())
|
||||
if total_rows == 0:
|
||||
yield json.dumps({"type": "error", "message": f"标的 {symbol} 暂无任何财务数据,请先同步财务表"}, ensure_ascii=False)
|
||||
return
|
||||
|
||||
# 2. meta
|
||||
yield json.dumps({
|
||||
"type": "meta",
|
||||
"symbol": symbol,
|
||||
"summary": _summarize(fins),
|
||||
"periods": total_rows,
|
||||
}, ensure_ascii=False)
|
||||
|
||||
# 3. 调用 LLM 流式
|
||||
try:
|
||||
from app.services.ai_provider import stream_ai_text
|
||||
|
||||
user_prompt = _build_user_prompt(fins, symbol, focus)
|
||||
async for delta in stream_ai_text(
|
||||
[
|
||||
{"role": "system", "content": _SYSTEM_PROMPT},
|
||||
{"role": "user", "content": user_prompt},
|
||||
],
|
||||
temperature=0.4,
|
||||
max_tokens=4000,
|
||||
):
|
||||
yield json.dumps({"type": "delta", "content": delta}, ensure_ascii=False)
|
||||
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.exception("AI financial analysis failed for %s: %s", symbol, e)
|
||||
yield json.dumps({"type": "error", "message": f"AI 分析失败: {e}"}, ensure_ascii=False)
|
||||
return
|
||||
|
||||
yield json.dumps({"type": "done"}, ensure_ascii=False)
|
||||
@@ -8,7 +8,7 @@ from __future__ import annotations
|
||||
import asyncio
|
||||
import logging
|
||||
import threading
|
||||
from datetime import date, datetime, timezone
|
||||
from datetime import datetime, timezone
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
@@ -200,15 +200,82 @@ class FinancialScheduler:
|
||||
# 手动同步(run_now)是否正在进行。前端据此显示"同步中"并防重复点击。
|
||||
self._is_syncing = False
|
||||
|
||||
def start(self, data_dir: Path, capset: CapabilitySet) -> None:
|
||||
def start(self, data_dir: Path, capset: CapabilitySet, *, auto_schedule: bool = False) -> None:
|
||||
"""初始化调度器，并按需启动周期同步后台任务。
|
||||
|
||||
auto_schedule=False (默认): 仅初始化 (设置数据目录/能力 + 恢复 last_sync),
|
||||
供 /api/financials/sync/* 手动同步使用, 不启动自动调度。
|
||||
auto_schedule=True: 额外启动每周一次的 metrics 自动同步 (启动后 60s 首跑)。
|
||||
"""
|
||||
# 先记录 data_dir/capset, 即使当前无 FINANCIAL 也保留引用:
|
||||
# 用户稍后在「设置」页升级到 Expert Key 时, update_capabilities() 会把新 capset
|
||||
# 推进来,trigger()/run_now() 才能用上 FINANCIAL。否则 _capset 永远是 None,
|
||||
# 即便 app.state.capabilities 已更新, 调度器仍报 "no FINANCIAL capability"。
|
||||
self._data_dir = data_dir
|
||||
self._capset = capset
|
||||
if not capset.has(Cap.FINANCIAL):
|
||||
logger.info("FinancialScheduler skipped: no FINANCIAL capability")
|
||||
return
|
||||
self._data_dir = data_dir
|
||||
self._capset = capset
|
||||
# 从持久化恢复上次同步时间: 重启后前端仍能显示真实最后同步时间,而非"尚未同步"
|
||||
try:
|
||||
from app.services import preferences
|
||||
restored = dict(preferences.get_financial_sync_times())
|
||||
# 老用户迁移兜底: 若某表在 preferences 无记录但 parquet 已存在(升级前同步过),
|
||||
# 用 parquet 文件的修改时间作为同步时间并补写持久化。
|
||||
for table in FINANCIAL_TABLES:
|
||||
if table in restored:
|
||||
continue
|
||||
parquet = data_dir / "financials" / table / "part.parquet"
|
||||
if parquet.exists():
|
||||
mtime = datetime.fromtimestamp(parquet.stat().st_mtime, tz=timezone.utc).isoformat()
|
||||
restored[table] = mtime
|
||||
preferences.set_financial_sync_time(table, mtime)
|
||||
logger.info("FinancialScheduler backfilled last_sync for %s from parquet mtime", table)
|
||||
self._last_sync = restored
|
||||
if self._last_sync:
|
||||
logger.info("FinancialScheduler restored last_sync: %s", list(self._last_sync.keys()))
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("restore financial_sync_times failed: %s", e)
|
||||
|
||||
if not auto_schedule:
|
||||
# 仅初始化 (手动同步用), 不启动周期任务。
|
||||
logger.info("FinancialScheduler initialized (auto-schedule disabled; manual sync only)")
|
||||
return
|
||||
|
||||
self._running = True
|
||||
self._task = asyncio.create_task(self._run_loop())
|
||||
logger.info("FinancialScheduler started")
|
||||
logger.info("FinancialScheduler started (auto-schedule enabled)")
|
||||
|
||||
def _record_sync(self, table: str) -> None:
|
||||
"""记录一张表的同步完成时间: 更新内存 + 持久化到 preferences.json。
|
||||
|
||||
持久化确保即使重启,前端 /status 仍返回真实的最后同步时间,
|
||||
不会错误地显示"尚未同步"。
|
||||
"""
|
||||
ts = datetime.now(timezone.utc).isoformat()
|
||||
self._last_sync[table] = ts
|
||||
try:
|
||||
from app.services import preferences
|
||||
preferences.set_financial_sync_time(table, ts)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("persist financial_sync_time(%s) failed: %s", e)
|
||||
|
||||
def update_capabilities(self, capset: CapabilitySet) -> None:
|
||||
"""刷新调度器持有的能力集。
|
||||
|
||||
用户在「设置」页新增/清除 API Key 后, settings API 会重新探测能力并更新
|
||||
app.state.capabilities; 必须同步推给本调度器, 否则 trigger()/run_now() 仍读
|
||||
启动时的旧 capset, 即便 app.state 已含 FINANCIAL, 调度器仍报
|
||||
"no FINANCIAL capability" 而拒绝同步 (表现为前端「全部同步」按钮闪一下无动作)。
|
||||
"""
|
||||
prev = self._capset
|
||||
self._capset = capset
|
||||
had = bool(prev) and prev.has(Cap.FINANCIAL)
|
||||
now = capset.has(Cap.FINANCIAL)
|
||||
if had != now:
|
||||
logger.info(
|
||||
"FinancialScheduler capabilities updated: FINANCIAL %s -> %s", had, now
|
||||
)
|
||||
|
||||
def stop(self) -> None:
|
||||
self._running = False
|
||||
@@ -217,22 +284,6 @@ class FinancialScheduler:
|
||||
self._task = None
|
||||
logger.info("FinancialScheduler stopped")
|
||||
|
||||
def update(self, data_dir: Path, capset: CapabilitySet) -> None:
|
||||
"""运行时更新数据目录和能力集。
|
||||
|
||||
用户在设置页更换/清除 Key 后,能力集可能变化,无需重启服务即可让
|
||||
财务调度器生效或失效。
|
||||
"""
|
||||
had_financial = self._capset is not None and self._capset.has(Cap.FINANCIAL)
|
||||
has_financial = capset.has(Cap.FINANCIAL)
|
||||
self._data_dir = data_dir
|
||||
self._capset = capset
|
||||
|
||||
if has_financial and not self._running:
|
||||
self.start(data_dir, capset)
|
||||
elif had_financial and not has_financial and self._running:
|
||||
self.stop()
|
||||
|
||||
async def _run_loop(self) -> None:
|
||||
"""每周执行一次 metrics 同步。"""
|
||||
try:
|
||||
@@ -245,7 +296,7 @@ class FinancialScheduler:
|
||||
# 每周: 只同步 metrics
|
||||
try:
|
||||
rows = sync_metrics(self._data_dir, self._capset)
|
||||
self._last_sync["metrics"] = datetime.now(timezone.utc).isoformat()
|
||||
self._record_sync("metrics")
|
||||
logger.info("FinancialScheduler: metrics synced, %d rows", rows)
|
||||
except Exception as e:
|
||||
logger.warning("FinancialScheduler: metrics sync failed: %s", e)
|
||||
@@ -259,8 +310,39 @@ class FinancialScheduler:
|
||||
except asyncio.CancelledError:
|
||||
pass
|
||||
|
||||
def _run_body(self, table: str | None) -> dict[str, int]:
|
||||
"""同步逻辑本体(不加锁,假设调用方已持有 _is_syncing)。
|
||||
|
||||
table=None 同步全部 4 张表;否则只同步指定表。
|
||||
每张表完成立即更新 last_sync,让前端轮询 /status 能看到进度递增。
|
||||
"""
|
||||
if table:
|
||||
fn = {
|
||||
"metrics": sync_metrics,
|
||||
"income": sync_income,
|
||||
"balance_sheet": sync_balance_sheet,
|
||||
"cash_flow": sync_cash_flow,
|
||||
}.get(table)
|
||||
if not fn:
|
||||
return {}
|
||||
rows = fn(self._data_dir, self._capset)
|
||||
self._record_sync(table)
|
||||
return {table: rows}
|
||||
# 全部同步
|
||||
symbols = _get_symbols(self._data_dir)
|
||||
result: dict[str, int] = {}
|
||||
for t in FINANCIAL_TABLES:
|
||||
result[t] = _sync_table(t, symbols, self._data_dir, self._capset, latest_only=True)
|
||||
self._record_sync(t)
|
||||
_refresh_financials_views(self._data_dir)
|
||||
return result
|
||||
|
||||
def run_now(self, table: str | None = None) -> dict[str, int]:
|
||||
"""手动触发同步。table=None 同步全部。
|
||||
"""同步执行一次同步(阻塞调用线程)。
|
||||
|
||||
⚠ 全量同步需数分钟,务必在后台线程调用,不要直接在 HTTP 请求线程里阻塞,
|
||||
否则请求会长时间 pending 直至被浏览器/代理超时掐断(表现为"点击无反应")。
|
||||
HTTP 接口应调用 trigger() 立即返回,再让前端轮询 /status.syncing 看进度。
|
||||
|
||||
用 _is_syncing 标志防并发:若已有同步在进行,本次直接跳过,
|
||||
避免重复请求拖慢服务端 / 触发上游限流。
|
||||
@@ -273,32 +355,46 @@ class FinancialScheduler:
|
||||
return {"_skipped": 1}
|
||||
self._is_syncing = True
|
||||
try:
|
||||
if table:
|
||||
fn = {
|
||||
"metrics": sync_metrics,
|
||||
"income": sync_income,
|
||||
"balance_sheet": sync_balance_sheet,
|
||||
"cash_flow": sync_cash_flow,
|
||||
}.get(table)
|
||||
if not fn:
|
||||
return {}
|
||||
rows = fn(self._data_dir, self._capset)
|
||||
self._last_sync[table] = datetime.now(timezone.utc).isoformat()
|
||||
return {table: rows}
|
||||
else:
|
||||
# 全部同步: 逐表执行, 每张完成立即更新 last_sync,
|
||||
# 让前端轮询 /status 能看到进度递增 (而非等全部完成才一次性更新)。
|
||||
symbols = _get_symbols(self._data_dir)
|
||||
result: dict[str, int] = {}
|
||||
for t in FINANCIAL_TABLES:
|
||||
result[t] = _sync_table(t, symbols, self._data_dir, self._capset, latest_only=True)
|
||||
self._last_sync[t] = datetime.now(timezone.utc).isoformat()
|
||||
_refresh_financials_views(self._data_dir)
|
||||
return result
|
||||
return self._run_body(table)
|
||||
finally:
|
||||
with self._lock:
|
||||
self._is_syncing = False
|
||||
|
||||
def trigger(self, table: str | None = None) -> dict[str, int]:
|
||||
"""触发一次同步(非阻塞,立即返回)。
|
||||
|
||||
在后台线程执行同步体,HTTP 请求无需等待。
|
||||
返回 {"started": True/False}:
|
||||
- False = 能力不足或已有同步在进行(被防并发跳过)
|
||||
- True = 已在后台开始,前端应轮询 /status.syncing 观察进度
|
||||
|
||||
⚠ _is_syncing 在此处置 True(持锁),确保 trigger 返回时前端轮询
|
||||
/status 已能看到 syncing=True,无竞态窗口;同时防止快速重复点击
|
||||
启动多个后台线程。后台线程复用 _run_body 执行真正的同步逻辑。
|
||||
"""
|
||||
if not self._capset or not self._capset.has(Cap.FINANCIAL):
|
||||
return {"started": False, "reason": "no FINANCIAL capability"}
|
||||
with self._lock:
|
||||
if self._is_syncing:
|
||||
logger.info("financial sync trigger skipped: already running")
|
||||
return {"started": False, "reason": "already running"}
|
||||
# 持锁置位:保证 trigger 返回前 syncing 已为 True
|
||||
self._is_syncing = True
|
||||
|
||||
def _bg() -> None:
|
||||
try:
|
||||
self._run_body(table)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.exception("background financial sync failed: %s", e)
|
||||
finally:
|
||||
with self._lock:
|
||||
self._is_syncing = False
|
||||
|
||||
t = threading.Thread(target=_bg, name="financial-sync", daemon=True)
|
||||
t.start()
|
||||
logger.info("financial sync triggered in background: table=%s", table or "all")
|
||||
return {"started": True}
|
||||
|
||||
@property
|
||||
def is_syncing(self) -> bool:
|
||||
"""手动同步是否正在进行(供 /status 返回,前端据此显示"同步中")。"""
|
||||
|
||||
@@ -1,8 +1,14 @@
|
||||
"""指数数据同步服务。"""
|
||||
"""指数 / ETF 数据同步服务。
|
||||
|
||||
标的列表优先用免费的 exchanges.get_instruments(type=index/etf) 拉取
|
||||
(None/Free 档均可用,无需 quote.pool 权限);付费档可额外用
|
||||
quotes.get_by_universes 作为补充来源。日K统一走 klines.batch。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import gc
|
||||
from collections.abc import Callable
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
import polars as pl
|
||||
@@ -15,9 +21,15 @@ from app.tickflow.repository import KlineRepository
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# exchanges.get_instruments 查询的交易所(沪深京)
|
||||
_EXCHANGES = ["SH", "SZ", "BJ"]
|
||||
|
||||
|
||||
def _quotes_to_index_instruments(resp) -> pl.DataFrame:
|
||||
"""将数据源 quotes 响应规范为指数 instruments。"""
|
||||
"""将 TickFlow quotes 响应(get_by_universes)规范为指数 instruments。
|
||||
|
||||
付费档(Starter+)的补充来源,免费档用不到。
|
||||
"""
|
||||
if resp is None:
|
||||
return pl.DataFrame()
|
||||
|
||||
@@ -61,11 +73,77 @@ def _quotes_to_index_instruments(resp) -> pl.DataFrame:
|
||||
return result.unique(subset=["symbol"], keep="last").sort("symbol")
|
||||
|
||||
|
||||
def sync_index_instruments(repo: KlineRepository) -> int:
|
||||
"""同步 CN_Index 指数标的维表，返回指数数量。"""
|
||||
def _fetch_instruments_by_type(instrument_type: str, asset_type_label: str) -> pl.DataFrame:
|
||||
"""用免费的 exchanges.get_instruments 拉取指定类型的标的列表。
|
||||
|
||||
None/Free 档均可使用(标的信息查询免费开放)。
|
||||
instrument_type: 'index' / 'etf'
|
||||
asset_type_label: 写入 instruments 表的 asset_type 标记('index' / 'etf')
|
||||
"""
|
||||
tf = get_client()
|
||||
rows: list[dict] = []
|
||||
for ex in _EXCHANGES:
|
||||
try:
|
||||
items = tf.exchanges.get_instruments(ex, instrument_type=instrument_type)
|
||||
for it in items or []:
|
||||
item = it if isinstance(it, dict) else {}
|
||||
symbol = item.get("symbol")
|
||||
if not symbol:
|
||||
continue
|
||||
rows.append({
|
||||
"symbol": str(symbol),
|
||||
"name": item.get("name") or str(symbol),
|
||||
})
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("get_instruments(%s, type=%s) failed: %s", ex, instrument_type, e)
|
||||
|
||||
if not rows:
|
||||
return pl.DataFrame()
|
||||
|
||||
return (
|
||||
pl.DataFrame(rows)
|
||||
.with_columns([
|
||||
pl.col("symbol").str.split(".").list.first().alias("code"),
|
||||
pl.lit(asset_type_label).alias("asset_type"),
|
||||
])
|
||||
.unique(subset=["symbol"], keep="last")
|
||||
.sort("symbol")
|
||||
)
|
||||
|
||||
|
||||
def sync_index_instruments(
|
||||
repo: KlineRepository,
|
||||
pull_index: bool = True,
|
||||
pull_etf: bool = True,
|
||||
) -> int:
|
||||
"""同步指数 / ETF 标的维表,返回标的总数。
|
||||
|
||||
新版物理分开保存: 指数写 instruments_index, ETF 写 instruments_etf。
|
||||
读取层仍兼容旧版 instruments_index 中 asset_type='etf' 的历史数据。
|
||||
"""
|
||||
index_parts: list[pl.DataFrame] = []
|
||||
etf_parts: list[pl.DataFrame] = []
|
||||
|
||||
# 1) 免费通道:按开关分别拉 index / etf
|
||||
if pull_index:
|
||||
index_df = _fetch_instruments_by_type("index", "index")
|
||||
if not index_df.is_empty():
|
||||
index_parts.append(index_df)
|
||||
if pull_etf:
|
||||
etf_df = _fetch_instruments_by_type("etf", "etf")
|
||||
if not etf_df.is_empty():
|
||||
etf_parts.append(etf_df)
|
||||
|
||||
# 2) 付费补充:Starter+ 用 get_by_universes 补指数(仅当开启指数拉取)
|
||||
if pull_index:
|
||||
capset = None
|
||||
try:
|
||||
from app.tickflow import policy
|
||||
capset = policy.detect_capabilities(force=False)
|
||||
except Exception: # noqa: BLE001
|
||||
pass
|
||||
if capset is not None and capset.has(Cap.QUOTE_POOL):
|
||||
tf = get_client()
|
||||
resp = None
|
||||
errors: list[str] = []
|
||||
for kwargs in (
|
||||
{"universes": ["CN_Index"]},
|
||||
{"universes": ["CN_Index"], "as_dataframe": False},
|
||||
@@ -73,21 +151,41 @@ def sync_index_instruments(repo: KlineRepository) -> int:
|
||||
try:
|
||||
resp = tf.quotes.get_by_universes(**kwargs)
|
||||
if resp is not None and len(resp) > 0:
|
||||
sup = _quotes_to_index_instruments(resp)
|
||||
if not sup.is_empty():
|
||||
index_parts.append(sup)
|
||||
break
|
||||
except Exception as e: # noqa: BLE001
|
||||
errors.append(str(e))
|
||||
resp = None
|
||||
logger.debug("CN_Index universe supplement failed: %s", e)
|
||||
|
||||
if resp is None or len(resp) == 0:
|
||||
logger.warning("CN_Index universe returned empty: %s", "; ".join(errors))
|
||||
return 0
|
||||
total = 0
|
||||
if index_parts:
|
||||
index_inst = pl.concat(index_parts, how="diagonal_relaxed").unique(subset=["symbol"], keep="last").sort("symbol")
|
||||
if not index_inst.is_empty():
|
||||
repo.save_index_instruments(index_inst)
|
||||
total += index_inst.height
|
||||
if etf_parts:
|
||||
etf_inst = pl.concat(etf_parts, how="diagonal_relaxed").unique(subset=["symbol"], keep="last").sort("symbol")
|
||||
if not etf_inst.is_empty():
|
||||
repo.save_etf_instruments(etf_inst)
|
||||
total += etf_inst.height
|
||||
|
||||
instruments = _quotes_to_index_instruments(resp)
|
||||
if instruments.is_empty():
|
||||
if total == 0:
|
||||
logger.warning("指数/ETF 标的列表为空(pull_index=%s, pull_etf=%s)", pull_index, pull_etf)
|
||||
return 0
|
||||
repo.save_index_instruments(instruments)
|
||||
repo.refresh_index_views()
|
||||
return instruments.height
|
||||
logger.info("指数/ETF 标的同步完成: %d 只", total)
|
||||
return total
|
||||
|
||||
|
||||
def sync_etf_instruments(repo: KlineRepository) -> int:
|
||||
"""单独同步 ETF 标的维表(返回 ETF 数量)。"""
|
||||
etf_df = _fetch_instruments_by_type("etf", "etf")
|
||||
if etf_df.is_empty():
|
||||
return 0
|
||||
repo.save_etf_instruments(etf_df)
|
||||
repo.refresh_index_views()
|
||||
return etf_df.height
|
||||
|
||||
|
||||
def sync_and_persist_index_daily(
|
||||
@@ -96,18 +194,31 @@ def sync_and_persist_index_daily(
|
||||
count: int | None = None,
|
||||
start_date: datetime | None = None,
|
||||
end_date: datetime | None = None,
|
||||
symbols_override: list[str] | None = None,
|
||||
on_chunk_done: Callable[[int, int], None] | None = None,
|
||||
) -> int:
|
||||
"""同步指数日K到独立 parquet，并计算指数 enriched。"""
|
||||
"""同步指数/ETF 日K到独立 parquet,并计算 enriched。
|
||||
|
||||
symbols_override 非空时,只拉这些代码(跳过 instruments 表),用于自定义范围。
|
||||
否则取 index_instruments 表全量(指数+ETF 合并存储)。
|
||||
on_chunk_done(current, total) 每个批次完成后回调。
|
||||
"""
|
||||
if not capset.has(Cap.KLINE_DAILY_BATCH):
|
||||
return 0
|
||||
|
||||
if symbols_override:
|
||||
symbols = sorted(set(s for s in symbols_override if s))
|
||||
if not symbols:
|
||||
return 0
|
||||
else:
|
||||
instruments = repo.get_index_instruments()
|
||||
if instruments.is_empty():
|
||||
sync_index_instruments(repo)
|
||||
sync_index_instruments(repo, pull_index=True, pull_etf=False)
|
||||
instruments = repo.get_index_instruments()
|
||||
if not instruments.is_empty() and "asset_type" in instruments.columns:
|
||||
instruments = instruments.filter(pl.col("asset_type") != "etf")
|
||||
if instruments.is_empty() or "symbol" not in instruments.columns:
|
||||
return 0
|
||||
|
||||
symbols = sorted(set(instruments["symbol"].to_list()))
|
||||
lim = capset.limits(Cap.KLINE_DAILY_BATCH)
|
||||
batch_size = preferences.get_index_daily_batch_size()
|
||||
@@ -139,7 +250,110 @@ def sync_and_persist_index_daily(
|
||||
enriched = compute_enriched(raw, factors=None, instruments=None)
|
||||
repo.append_index_enriched(enriched)
|
||||
total_rows += raw.height
|
||||
logger.info("index daily synced: %d/%d chunks, +%d rows", i + 1, len(chunks), raw.height)
|
||||
logger.info("index/etf daily synced: %d/%d chunks, +%d rows", i + 1, len(chunks), raw.height)
|
||||
if on_chunk_done:
|
||||
on_chunk_done(i + 1, len(chunks))
|
||||
del raw, enriched
|
||||
gc.collect()
|
||||
repo.refresh_index_views()
|
||||
return total_rows
|
||||
|
||||
|
||||
def _load_etf_factors(repo: KlineRepository) -> pl.DataFrame:
|
||||
factor_path = repo.store.data_dir / "adj_factor_etf" / "all.parquet"
|
||||
if not factor_path.exists():
|
||||
return pl.DataFrame()
|
||||
try:
|
||||
return pl.read_parquet(factor_path)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("ETF 复权因子读取失败: %s", e)
|
||||
return pl.DataFrame()
|
||||
|
||||
|
||||
def sync_etf_adj_factor(
|
||||
symbols: list[str],
|
||||
repo: KlineRepository,
|
||||
capset: CapabilitySet,
|
||||
start_time: datetime | None = None,
|
||||
end_time: datetime | None = None,
|
||||
on_chunk_done=None,
|
||||
) -> tuple[int, list[str]]:
|
||||
"""同步 ETF 复权因子；失败由调用方降级为 warning。"""
|
||||
return kline_sync.sync_adj_factor(
|
||||
symbols,
|
||||
repo,
|
||||
capset,
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
on_chunk_done=on_chunk_done,
|
||||
asset_type="etf",
|
||||
)
|
||||
|
||||
|
||||
def sync_and_persist_etf_daily(
|
||||
repo: KlineRepository,
|
||||
capset: CapabilitySet,
|
||||
count: int | None = None,
|
||||
start_date: datetime | None = None,
|
||||
end_date: datetime | None = None,
|
||||
symbols_override: list[str] | None = None,
|
||||
on_chunk_done: Callable[[int, int], None] | None = None,
|
||||
) -> int:
|
||||
"""同步 ETF 日K到独立 kline_etf_* parquet,并计算 ETF enriched。
|
||||
on_chunk_done(current, total) 每个批次完成后回调。
|
||||
"""
|
||||
if not capset.has(Cap.KLINE_DAILY_BATCH):
|
||||
return 0
|
||||
|
||||
if symbols_override:
|
||||
symbols = sorted(set(s for s in symbols_override if s))
|
||||
else:
|
||||
instruments = repo.get_etf_instruments()
|
||||
if instruments.is_empty():
|
||||
sync_etf_instruments(repo)
|
||||
instruments = repo.get_etf_instruments()
|
||||
if instruments.is_empty() or "symbol" not in instruments.columns:
|
||||
return 0
|
||||
symbols = sorted(set(instruments["symbol"].to_list()))
|
||||
if not symbols:
|
||||
return 0
|
||||
|
||||
lim = capset.limits(Cap.KLINE_DAILY_BATCH)
|
||||
batch_size = preferences.get_index_daily_batch_size()
|
||||
if lim and lim.batch:
|
||||
batch_size = min(batch_size, lim.batch)
|
||||
rpm = lim.rpm if lim else None
|
||||
|
||||
end_time = end_date or datetime.now()
|
||||
start_time = start_date or (end_time - timedelta(days=365))
|
||||
|
||||
total_rows = 0
|
||||
interval = (60.0 / rpm) if rpm else 0
|
||||
chunks = [symbols[i:i + batch_size] for i in range(0, len(symbols), batch_size)]
|
||||
factors = _load_etf_factors(repo)
|
||||
for i, chunk in enumerate(chunks):
|
||||
if i > 0 and interval > 0 and len(chunks) > rpm:
|
||||
import time
|
||||
time.sleep(interval)
|
||||
raw = kline_sync.sync_daily_batch(
|
||||
chunk,
|
||||
count=count,
|
||||
batch_size=None,
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
)
|
||||
if raw.is_empty():
|
||||
continue
|
||||
|
||||
repo.append_etf_daily(raw)
|
||||
batch_factors = factors.filter(pl.col("symbol").is_in(chunk)) if not factors.is_empty() else factors
|
||||
# ETF 使用复权和通用技术指标；不传 instruments，避免套用 A股涨跌停/连板逻辑。
|
||||
enriched = compute_enriched(raw, factors=batch_factors, instruments=None)
|
||||
repo.append_etf_enriched(enriched)
|
||||
total_rows += raw.height
|
||||
logger.info("etf daily synced: %d/%d chunks, +%d rows", i + 1, len(chunks), raw.height)
|
||||
if on_chunk_done:
|
||||
on_chunk_done(i + 1, len(chunks))
|
||||
del raw, enriched
|
||||
gc.collect()
|
||||
repo.refresh_index_views()
|
||||
|
||||
@@ -223,11 +223,53 @@ def sync_daily_by_quotes(repo: KlineRepository) -> int:
|
||||
return daily_df.height
|
||||
|
||||
|
||||
def _normalize_adj_factor(raw) -> pl.DataFrame:
|
||||
"""Normalize SDK ex_factors response to symbol/trade_date/ex_factor."""
|
||||
if raw is None or len(raw) == 0:
|
||||
return pl.DataFrame()
|
||||
if isinstance(raw, dict):
|
||||
rows: list[dict] = []
|
||||
for sym, values in raw.items():
|
||||
for item in values or []:
|
||||
row = dict(item or {})
|
||||
row.setdefault("symbol", sym)
|
||||
rows.append(row)
|
||||
df = pl.DataFrame(rows) if rows else pl.DataFrame()
|
||||
elif isinstance(raw, pl.DataFrame):
|
||||
df = raw
|
||||
else:
|
||||
df = pl.from_pandas(raw.reset_index() if hasattr(raw, "reset_index") else raw)
|
||||
if df.is_empty():
|
||||
return df
|
||||
# rename: timestamp/date → trade_date, adj_factor → ex_factor
|
||||
# 注意: 新版 SDK 可能同时返回 timestamp 和 trade_date (或 adj_factor 和 ex_factor),
|
||||
# 直接 rename 会产生重复列报错。仅当目标列不存在时才 rename。
|
||||
rename_map: dict[str, str] = {}
|
||||
for src, dst in (("timestamp", "trade_date"), ("date", "trade_date"), ("adj_factor", "ex_factor")):
|
||||
if src in df.columns and dst not in df.columns:
|
||||
rename_map[src] = dst
|
||||
df = df.rename(rename_map)
|
||||
if "trade_date" in df.columns:
|
||||
if df.schema["trade_date"] in {pl.Int64, pl.Int32, pl.UInt64, pl.UInt32, pl.Float64, pl.Float32}:
|
||||
df = df.with_columns(
|
||||
pl.from_epoch(pl.col("trade_date").cast(pl.Int64), time_unit="ms").dt.date().alias("trade_date")
|
||||
)
|
||||
else:
|
||||
df = df.with_columns(pl.col("trade_date").cast(pl.Date, strict=False))
|
||||
if "ex_factor" in df.columns:
|
||||
df = df.with_columns(pl.col("ex_factor").cast(pl.Float64, strict=False))
|
||||
cols = [c for c in ["symbol", "trade_date", "ex_factor"] if c in df.columns]
|
||||
if len(cols) < 3:
|
||||
return pl.DataFrame()
|
||||
return df.select(cols).drop_nulls()
|
||||
|
||||
|
||||
def sync_adj_factor(symbols: list[str], repo: KlineRepository,
|
||||
capset: CapabilitySet,
|
||||
start_time: datetime | None = None,
|
||||
end_time: datetime | None = None,
|
||||
on_chunk_done: Callable[[int, int], None] | None = None) -> tuple[int, list[str]]:
|
||||
on_chunk_done: Callable[[int, int], None] | None = None,
|
||||
asset_type: str = "stock") -> tuple[int, list[str]]:
|
||||
"""同步除权因子(Starter+)。SDK 接口:`tf.klines.ex_factors(symbols=...)`。
|
||||
|
||||
支持增量: 传 start_time/end_time 只拉取该时间范围内的新除权事件。
|
||||
@@ -257,10 +299,9 @@ def sync_adj_factor(symbols: list[str], repo: KlineRepository,
|
||||
time.sleep(interval)
|
||||
try:
|
||||
raw = tf.klines.ex_factors(chunk, **sdk_kwargs)
|
||||
if raw is not None and len(raw) > 0:
|
||||
all_dfs.append(pl.from_pandas(
|
||||
raw.reset_index() if hasattr(raw, "reset_index") else raw
|
||||
))
|
||||
normalized = _normalize_adj_factor(raw)
|
||||
if not normalized.is_empty():
|
||||
all_dfs.append(normalized)
|
||||
logger.debug("adj_factor chunk %d/%d: %d symbols", i + 1, len(chunks), len(chunk))
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("adj_factor chunk %d failed: %s", i + 1, e)
|
||||
@@ -276,7 +317,8 @@ def sync_adj_factor(symbols: list[str], repo: KlineRepository,
|
||||
# 提取受影响的 symbol 列表(合并前)
|
||||
affected = new_data["symbol"].unique().to_list()
|
||||
|
||||
out = repo.store.data_dir / "adj_factor" / "all.parquet"
|
||||
factor_dir = "adj_factor_etf" if asset_type == "etf" else "adj_factor"
|
||||
out = repo.store.data_dir / factor_dir / "all.parquet"
|
||||
out.parent.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
if out.exists():
|
||||
@@ -420,7 +462,7 @@ def sync_minute_batch(
|
||||
|
||||
|
||||
def fetch_minute_single(symbol: str, trade_date: date) -> pl.DataFrame:
|
||||
"""从数据源实时拉取单股单日分钟 K（不写入本地）。"""
|
||||
"""从 TickFlow 实时拉取单股单日分钟 K（不写入本地）。"""
|
||||
from datetime import datetime
|
||||
start_time = datetime(trade_date.year, trade_date.month, trade_date.day, 9, 25, 0)
|
||||
end_time = datetime(trade_date.year, trade_date.month, trade_date.day, 15, 5, 0)
|
||||
@@ -445,6 +487,21 @@ def fetch_minute_single(symbol: str, trade_date: date) -> pl.DataFrame:
|
||||
return pl.DataFrame()
|
||||
|
||||
|
||||
def fetch_adj_factor_single(symbol: str) -> pl.DataFrame:
|
||||
"""从 TickFlow 实时拉取单股除权因子(不写入本地), 用于单股 K 线即时前复权。
|
||||
|
||||
返回结构: symbol, trade_date, ex_factor (空 DataFrame 表示无除权事件或拉取失败)。
|
||||
与 _apply_adj_factor / compute_enriched 的 factors 参数格式一致。
|
||||
"""
|
||||
tf = get_client()
|
||||
try:
|
||||
raw = tf.klines.ex_factors([symbol], as_dataframe=True, show_progress=False)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("fetch_adj_factor_single(%s) failed: %s", symbol, e)
|
||||
return pl.DataFrame()
|
||||
return _normalize_adj_factor(raw)
|
||||
|
||||
|
||||
def _latest_minute_datetime(repo: KlineRepository) -> datetime | None:
|
||||
"""本地分钟 K 数据的最新时间。"""
|
||||
try:
|
||||
|
||||
@@ -0,0 +1,576 @@
|
||||
"""市场总览数据装配(与 HTTP Request 解耦)。
|
||||
|
||||
本模块由 `app.api.overview._build_overview` 抽离而来,目的是让「大盘复盘」
|
||||
等无 Request 的调用方(定时任务、复盘服务)也能复用同一套聚合逻辑。
|
||||
|
||||
行为与原 `_build_overview` 完全一致,仅把对 `request.app.state.{repo,
|
||||
quote_service,depth_service}` 的依赖改为显式参数。
|
||||
|
||||
公共入口:
|
||||
build_market_overview(repo, quote_service, depth_service, as_of)
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
import re
|
||||
from datetime import date
|
||||
from typing import Any
|
||||
|
||||
import polars as pl
|
||||
|
||||
from app.services.ext_data import ExtConfig, ExtConfigStore
|
||||
from app.services.screener import ScreenerService
|
||||
|
||||
# ================================================================
|
||||
# 常量(与 overview.py 保持同步;复盘复盘仅 A 股核心指数)
|
||||
# ================================================================
|
||||
|
||||
CORE_INDEX_NAMES = {
|
||||
"000001.SH": "上证指数",
|
||||
"399001.SZ": "深证成指",
|
||||
"399006.SZ": "创业板指",
|
||||
"000680.SH": "科创综指",
|
||||
}
|
||||
CORE_INDEX_SYMBOLS = tuple(CORE_INDEX_NAMES.keys())
|
||||
|
||||
_DIMENSION_SEP = re.compile(r"[、,，;；|/\s]+")
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 通用工具
|
||||
# ================================================================
|
||||
|
||||
def _finite(v: Any) -> float | None:
|
||||
if v is None:
|
||||
return None
|
||||
try:
|
||||
f = float(v)
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
return f if math.isfinite(f) else None
|
||||
|
||||
|
||||
def _json_safe(value: Any) -> Any:
|
||||
if isinstance(value, dict):
|
||||
return {k: _json_safe(v) for k, v in value.items()}
|
||||
if isinstance(value, list):
|
||||
return [_json_safe(v) for v in value]
|
||||
if isinstance(value, float) and not math.isfinite(value):
|
||||
return None
|
||||
return value
|
||||
|
||||
|
||||
def _board(symbol: str) -> str:
|
||||
if symbol.endswith(".BJ"):
|
||||
return "北交所"
|
||||
if symbol.startswith(("300", "301")):
|
||||
return "创业板"
|
||||
if symbol.startswith(("688", "689")):
|
||||
return "科创板"
|
||||
if symbol.endswith(".SH"):
|
||||
return "沪主板"
|
||||
if symbol.endswith(".SZ"):
|
||||
return "深主板"
|
||||
return "其他"
|
||||
|
||||
|
||||
def _score(value: float, low: float, high: float) -> int:
|
||||
if high <= low:
|
||||
return 50
|
||||
return max(0, min(100, round((value - low) / (high - low) * 100)))
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 指数行情(实时 quote_service 优先,回退 kline_index_daily SQL)
|
||||
# ================================================================
|
||||
|
||||
def _quote_status(quote_service) -> dict:
|
||||
qs = quote_service
|
||||
if not qs:
|
||||
return {"enabled": False, "running": False, "quote_age_ms": None, "is_trading_hours": False}
|
||||
return qs.status()
|
||||
|
||||
|
||||
def _index_quotes(repo, quote_service, as_of: date | None = None) -> list[dict]:
|
||||
rows: list[dict] = []
|
||||
if quote_service and as_of is None:
|
||||
df = quote_service.get_index_quotes(list(CORE_INDEX_SYMBOLS))
|
||||
if not df.is_empty():
|
||||
rows = df.to_dicts()
|
||||
|
||||
if not rows and repo:
|
||||
placeholders = ", ".join("?" for _ in CORE_INDEX_SYMBOLS)
|
||||
try:
|
||||
db_rows = repo.execute_all(
|
||||
f"""
|
||||
WITH ranked AS (
|
||||
SELECT symbol, date, close,
|
||||
row_number() OVER (PARTITION BY symbol ORDER BY date DESC) AS rn
|
||||
FROM kline_index_daily
|
||||
WHERE symbol IN ({placeholders})
|
||||
AND (? IS NULL OR date <= ?)
|
||||
), latest AS (
|
||||
SELECT symbol,
|
||||
max(CASE WHEN rn = 1 THEN date END) AS date,
|
||||
max(CASE WHEN rn = 1 THEN close END) AS last_price,
|
||||
max(CASE WHEN rn = 2 THEN close END) AS prev_close
|
||||
FROM ranked
|
||||
WHERE rn <= 2
|
||||
GROUP BY symbol
|
||||
)
|
||||
SELECT symbol, date, last_price, prev_close
|
||||
FROM latest
|
||||
""",
|
||||
[*CORE_INDEX_SYMBOLS, as_of, as_of],
|
||||
)
|
||||
except Exception: # noqa: BLE001
|
||||
db_rows = []
|
||||
for symbol, dt, last_price, prev_close in db_rows:
|
||||
change_amount = None
|
||||
change_pct = None
|
||||
lp = _finite(last_price)
|
||||
pc = _finite(prev_close)
|
||||
if lp is not None and pc not in (None, 0):
|
||||
change_amount = lp - pc
|
||||
change_pct = change_amount / pc * 100
|
||||
rows.append({
|
||||
"symbol": symbol,
|
||||
"name": CORE_INDEX_NAMES.get(symbol),
|
||||
"date": str(dt) if dt else None,
|
||||
"last_price": lp,
|
||||
"close": lp,
|
||||
"prev_close": pc,
|
||||
"change_amount": change_amount,
|
||||
"change_pct": change_pct,
|
||||
})
|
||||
|
||||
by_symbol = {r.get("symbol"): r for r in rows}
|
||||
out = []
|
||||
for symbol in CORE_INDEX_SYMBOLS:
|
||||
r = by_symbol.get(symbol, {"symbol": symbol})
|
||||
out.append({
|
||||
"symbol": symbol,
|
||||
"name": r.get("name") or CORE_INDEX_NAMES[symbol],
|
||||
"last_price": _finite(r.get("last_price") if r.get("last_price") is not None else r.get("close")),
|
||||
"change_pct": _finite(r.get("change_pct")),
|
||||
"change_amount": _finite(r.get("change_amount")),
|
||||
})
|
||||
return out
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 扩展数据(行业 / 概念)维度聚合
|
||||
# ================================================================
|
||||
|
||||
def _dimension_field(config: ExtConfig, kind: str) -> str | None:
|
||||
candidates = ["概念", "concept", "theme"] if kind == "concept" else ["行业", "industry", "sector"]
|
||||
for candidate in candidates:
|
||||
needle = candidate.lower()
|
||||
for field in config.fields:
|
||||
haystack = f"{field.name} {field.label}".lower()
|
||||
if needle in haystack:
|
||||
return field.name
|
||||
return None
|
||||
|
||||
|
||||
def _ext_files(data_dir, config: ExtConfig) -> list[str]:
|
||||
base = data_dir / "ext_data" / config.id
|
||||
if config.mode == "timeseries":
|
||||
root = base / "timeseries"
|
||||
return [str(p) for p in sorted(root.rglob("*.parquet")) if p.is_file()]
|
||||
return [str(p) for p in sorted(base.glob("*.parquet")) if p.is_file()]
|
||||
|
||||
|
||||
def _read_ext_rows(data_dir, config: ExtConfig, dimension_field: str) -> list[dict]:
|
||||
files = _ext_files(data_dir, config)
|
||||
if not files:
|
||||
return []
|
||||
try:
|
||||
df = pl.read_parquet(files, hive_partitioning=True)
|
||||
except TypeError:
|
||||
try:
|
||||
df = pl.read_parquet(files)
|
||||
except Exception: # noqa: BLE001
|
||||
return []
|
||||
except Exception: # noqa: BLE001
|
||||
return []
|
||||
if df.is_empty() or dimension_field not in df.columns:
|
||||
return []
|
||||
|
||||
if config.mode == "timeseries" and "date" in df.columns:
|
||||
latest = df.get_column("date").max()
|
||||
if latest is not None:
|
||||
df = df.filter(pl.col("date") == latest)
|
||||
|
||||
symbol_cols = ["symbol", "code", "股票代码", "代码"]
|
||||
for mapping in (config.symbol_map, config.code_map):
|
||||
if isinstance(mapping, dict) and mapping.get("type") == "mapped" and mapping.get("col"):
|
||||
symbol_cols.append(str(mapping["col"]))
|
||||
cols = []
|
||||
for col in [dimension_field, *symbol_cols]:
|
||||
if col in df.columns and col not in cols:
|
||||
cols.append(col)
|
||||
return df.select(cols).to_dicts()
|
||||
|
||||
|
||||
def _dimension_values(raw: Any) -> list[str]:
|
||||
if raw is None:
|
||||
return []
|
||||
values = [v.strip() for v in _DIMENSION_SEP.split(str(raw).strip()) if v.strip()]
|
||||
return values
|
||||
|
||||
|
||||
def _symbol_keys(row: dict, config: ExtConfig) -> list[str]:
|
||||
fields = ["symbol", "code", "股票代码", "代码"]
|
||||
for mapping in (config.symbol_map, config.code_map):
|
||||
if isinstance(mapping, dict) and mapping.get("type") == "mapped" and mapping.get("col"):
|
||||
fields.append(str(mapping["col"]))
|
||||
|
||||
keys: list[str] = []
|
||||
for field in fields:
|
||||
raw = row.get(field)
|
||||
if raw is None:
|
||||
continue
|
||||
text = str(raw).strip().upper()
|
||||
if not text:
|
||||
continue
|
||||
keys.append(text)
|
||||
if "." in text:
|
||||
keys.append(text.split(".", 1)[0])
|
||||
return keys
|
||||
|
||||
|
||||
def _dimension_rank(rows: list[dict], repo, kind: str, limit: int = 5, level: int | None = None) -> dict:
|
||||
if not rows:
|
||||
return {"leading": [], "lagging": []}
|
||||
|
||||
quote_map: dict[str, dict] = {}
|
||||
for row in rows:
|
||||
symbol = str(row.get("symbol") or "").strip().upper()
|
||||
if not symbol:
|
||||
continue
|
||||
quote_map[symbol] = row
|
||||
quote_map[symbol.split(".", 1)[0]] = row
|
||||
|
||||
store = ExtConfigStore(repo.store.data_dir)
|
||||
groups: dict[str, dict[str, dict]] = {}
|
||||
for config in store.load_all():
|
||||
field = _dimension_field(config, kind)
|
||||
if not field:
|
||||
continue
|
||||
for ext_row in _read_ext_rows(repo.store.data_dir, config, field):
|
||||
quote = None
|
||||
for key in _symbol_keys(ext_row, config):
|
||||
quote = quote_map.get(key)
|
||||
if quote:
|
||||
break
|
||||
if not quote:
|
||||
continue
|
||||
symbol = str(quote.get("symbol") or "")
|
||||
for value in _dimension_values(ext_row.get(field)):
|
||||
# 行业按 "-" 拆分级: "银行-银行-股份制银行" → level=2 取"银行"(二级)
|
||||
if level is not None and "-" in value:
|
||||
parts = value.split("-")
|
||||
value = parts[level - 1] if level <= len(parts) else parts[-1]
|
||||
groups.setdefault(value, {})[symbol] = quote
|
||||
|
||||
items = []
|
||||
for name, by_symbol in groups.items():
|
||||
stocks = list(by_symbol.values())
|
||||
changes = [_finite(s.get("change_pct")) for s in stocks]
|
||||
changes = [v for v in changes if v is not None]
|
||||
if not changes:
|
||||
continue
|
||||
leader = max(stocks, key=lambda s: _finite(s.get("change_pct")) or -999)
|
||||
items.append({
|
||||
"name": name,
|
||||
"count": len(stocks),
|
||||
"avg_pct": sum(changes) / len(changes),
|
||||
"up_count": sum(1 for v in changes if v > 0),
|
||||
"down_count": sum(1 for v in changes if v < 0),
|
||||
"amount": sum(_finite(s.get("amount")) or 0 for s in stocks),
|
||||
"leader": {
|
||||
"symbol": leader.get("symbol"),
|
||||
"name": leader.get("name"),
|
||||
"change_pct": _finite(leader.get("change_pct")),
|
||||
},
|
||||
})
|
||||
|
||||
leading = sorted(items, key=lambda x: x["avg_pct"], reverse=True)[:limit]
|
||||
lagging = sorted(items, key=lambda x: x["avg_pct"])[:limit]
|
||||
return {"leading": leading, "lagging": lagging}
|
||||
|
||||
|
||||
# ================================================================
|
||||
# Top 行 / 涨跌幅分桶
|
||||
# ================================================================
|
||||
|
||||
def _top_rows(rows: list[dict], key: str, descending: bool, limit: int = 8) -> list[dict]:
|
||||
filtered = [r for r in rows if _finite(r.get(key)) is not None]
|
||||
filtered.sort(key=lambda r: _finite(r.get(key)) or 0, reverse=descending)
|
||||
return [
|
||||
{
|
||||
"symbol": r.get("symbol"),
|
||||
"name": r.get("name"),
|
||||
"close": _finite(r.get("close")),
|
||||
"change_pct": _finite(r.get("change_pct")),
|
||||
"amount": _finite(r.get("amount")),
|
||||
"turnover_rate": _finite(r.get("turnover_rate")),
|
||||
"board": _board(str(r.get("symbol") or "")),
|
||||
}
|
||||
for r in filtered[:limit]
|
||||
]
|
||||
|
||||
|
||||
def _pct_band_rows(values: list[float]) -> list[dict]:
|
||||
bands = [
|
||||
("<-5%", None, -0.05),
|
||||
("-5~-3%", -0.05, -0.03),
|
||||
("-3~-1%", -0.03, -0.01),
|
||||
("-1~0%", -0.01, 0),
|
||||
("0~1%", 0, 0.01),
|
||||
("1~3%", 0.01, 0.03),
|
||||
("3~5%", 0.03, 0.05),
|
||||
(">5%", 0.05, None),
|
||||
]
|
||||
total = len(values) or 1
|
||||
out = []
|
||||
for label, low, high in bands:
|
||||
count = 0
|
||||
for v in values:
|
||||
if low is None and v < high:
|
||||
count += 1
|
||||
elif high is None and v >= low:
|
||||
count += 1
|
||||
elif low is not None and high is not None and low <= v < high:
|
||||
count += 1
|
||||
out.append({"label": label, "count": count, "pct": count / total * 100})
|
||||
return out
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 主装配入口
|
||||
# ================================================================
|
||||
|
||||
def build_market_overview(
|
||||
repo,
|
||||
quote_service=None,
|
||||
depth_service=None,
|
||||
as_of: date | None = None,
|
||||
) -> dict:
|
||||
"""装配市场总览(与原 overview._build_overview 行为一致)。
|
||||
|
||||
Args:
|
||||
repo: KlineRepository(必填)。
|
||||
quote_service: QuoteService(可选;实时指数行情来源)。
|
||||
depth_service: DepthService(可选;五档封板修正)。
|
||||
as_of: 指定日期,None 则取最新有数据日。
|
||||
"""
|
||||
svc = ScreenerService(repo)
|
||||
as_of = as_of or svc.latest_date()
|
||||
status = _quote_status(quote_service)
|
||||
indices = _index_quotes(repo, quote_service, as_of)
|
||||
|
||||
if not as_of:
|
||||
return {
|
||||
"as_of": None,
|
||||
"quote_status": status,
|
||||
"indices": indices,
|
||||
"breadth": {"total": 0, "up": 0, "down": 0, "flat": 0, "up_pct": 0, "down_pct": 0},
|
||||
"amount": {"total": 0, "avg": 0},
|
||||
"boards": [],
|
||||
"limit": {"limit_up": 0, "broken": 0, "failed": 0, "limit_down": 0, "max_boards": 0, "tiers": []},
|
||||
"distribution": [],
|
||||
"trend": {"above_ma5": 0, "above_ma20": 0, "above_ma60": 0, "above_ma5_pct": 0, "above_ma20_pct": 0, "above_ma60_pct": 0, "new_high": 0, "new_low": 0},
|
||||
"activity": {"avg_turnover": 0, "high_turnover": 0, "high_vol_ratio": 0, "vol_ratio": 1},
|
||||
"radar": [],
|
||||
"emotion": {"score": 50, "label": "暂无"},
|
||||
"top_gainers": [],
|
||||
"top_losers": [],
|
||||
"turnover_leaders": [],
|
||||
"active_leaders": [],
|
||||
"concept_rank": {"leading": [], "lagging": []},
|
||||
"industry_rank": {"leading": [], "lagging": []},
|
||||
}
|
||||
|
||||
df = svc._load_enriched_for_date(as_of)
|
||||
if df.is_empty():
|
||||
rows: list[dict] = []
|
||||
else:
|
||||
cols = [
|
||||
"symbol", "name", "close", "change_pct", "amount", "turnover_rate", "volume",
|
||||
"vol_ratio_5d", "consecutive_limit_ups", "signal_limit_up", "signal_broken_limit_up", "signal_limit_down",
|
||||
"ma5", "ma20", "ma60", "high_60d", "low_60d", "signal_n_day_high", "signal_n_day_low",
|
||||
]
|
||||
df = df.select([c for c in cols if c in df.columns])
|
||||
rows = df.to_dicts()
|
||||
|
||||
# 过滤真停牌（volume=0 且 change_pct=0），保留有涨跌幅的浮点误差股以对齐同花顺口径
|
||||
if rows and "volume" in rows[0]:
|
||||
rows = [r for r in rows
|
||||
if (_finite(r.get("volume")) or 0) > 0
|
||||
or (_finite(r.get("change_pct")) or 0) != 0]
|
||||
|
||||
total = len(rows)
|
||||
up = sum(1 for r in rows if (_finite(r.get("change_pct")) or 0) > 0)
|
||||
down = sum(1 for r in rows if (_finite(r.get("change_pct")) or 0) < 0)
|
||||
flat = max(0, total - up - down)
|
||||
up_pct = up / total * 100 if total else 0
|
||||
down_pct = down / total * 100 if total else 0
|
||||
|
||||
amounts = [_finite(r.get("amount")) or 0 for r in rows]
|
||||
total_amount = sum(amounts)
|
||||
avg_amount = total_amount / total if total else 0
|
||||
|
||||
pct_values = [_finite(r.get("change_pct")) for r in rows]
|
||||
pct_values = [v for v in pct_values if v is not None]
|
||||
avg_pct = sum(pct_values) / len(pct_values) if pct_values else 0
|
||||
median_pct = sorted(pct_values)[len(pct_values) // 2] if pct_values else 0
|
||||
strong_up = sum(1 for v in pct_values if v >= 0.03)
|
||||
strong_down = sum(1 for v in pct_values if v <= -0.03)
|
||||
|
||||
limit_up = sum(1 for r in rows if bool(r.get("signal_limit_up")) or (_finite(r.get("consecutive_limit_ups")) or 0) > 0)
|
||||
broken = sum(1 for r in rows if bool(r.get("signal_broken_limit_up")))
|
||||
limit_down = sum(1 for r in rows if bool(r.get("signal_limit_down")))
|
||||
max_boards = max([int(_finite(r.get("consecutive_limit_ups")) or 0) for r in rows], default=0)
|
||||
|
||||
# 五档 sealed 修正: 假涨停/假跌停不计入(需 Pro+ depth5.batch 能力)
|
||||
sealed_ready = False
|
||||
fake_up = 0
|
||||
fake_down = 0
|
||||
if depth_service:
|
||||
up_map = depth_service.get_sealed_map(as_of, is_down=False)
|
||||
down_map = depth_service.get_sealed_map(as_of, is_down=True)
|
||||
sealed_ready = bool(up_map or down_map) and depth_service.is_sealed_ready(as_of)
|
||||
if up_map:
|
||||
fake_up = sum(1 for v in up_map.values() if v.get("sealed") is False)
|
||||
if down_map:
|
||||
fake_down = sum(1 for v in down_map.values() if v.get("sealed") is False)
|
||||
if sealed_ready:
|
||||
limit_up = max(0, limit_up - fake_up)
|
||||
limit_down = max(0, limit_down - fake_down)
|
||||
|
||||
seal_rate = limit_up / (limit_up + broken) * 100 if (limit_up + broken) > 0 else 0
|
||||
|
||||
def above_ma_count(ma_key: str) -> int:
|
||||
return sum(1 for r in rows if (_finite(r.get("close")) is not None and _finite(r.get(ma_key)) is not None and (_finite(r.get("close")) or 0) >= (_finite(r.get(ma_key)) or 0)))
|
||||
|
||||
above_ma5 = above_ma_count("ma5")
|
||||
above_ma20 = above_ma_count("ma20")
|
||||
above_ma60 = above_ma_count("ma60")
|
||||
new_high = sum(1 for r in rows if bool(r.get("signal_n_day_high")) or (_finite(r.get("close")) is not None and _finite(r.get("high_60d")) is not None and (_finite(r.get("close")) or 0) >= (_finite(r.get("high_60d")) or 0)))
|
||||
new_low = sum(1 for r in rows if bool(r.get("signal_n_day_low")) or (_finite(r.get("close")) is not None and _finite(r.get("low_60d")) is not None and (_finite(r.get("close")) or 0) <= (_finite(r.get("low_60d")) or 0)))
|
||||
|
||||
turnovers = [_finite(r.get("turnover_rate")) for r in rows]
|
||||
turnovers = [v for v in turnovers if v is not None]
|
||||
avg_turnover = sum(turnovers) / len(turnovers) if turnovers else 0
|
||||
high_turnover = sum(1 for v in turnovers if v >= 5)
|
||||
|
||||
boards_map: dict[str, dict] = {}
|
||||
for r in rows:
|
||||
b = _board(str(r.get("symbol") or ""))
|
||||
item = boards_map.setdefault(b, {"board": b, "count": 0, "up": 0, "down": 0, "amount": 0.0})
|
||||
item["count"] += 1
|
||||
change = _finite(r.get("change_pct")) or 0
|
||||
if change > 0:
|
||||
item["up"] += 1
|
||||
elif change < 0:
|
||||
item["down"] += 1
|
||||
item["amount"] += _finite(r.get("amount")) or 0
|
||||
boards = sorted(boards_map.values(), key=lambda x: x["amount"], reverse=True)
|
||||
for b in boards:
|
||||
count = b["count"] or 1
|
||||
b["up_pct"] = b["up"] / count * 100
|
||||
|
||||
tiers_map: dict[int, int] = {}
|
||||
for r in rows:
|
||||
n = int(_finite(r.get("consecutive_limit_ups")) or 0)
|
||||
if n > 0:
|
||||
tiers_map[n] = tiers_map.get(n, 0) + 1
|
||||
tiers = [{"boards": k, "count": v} for k, v in sorted(tiers_map.items(), key=lambda item: -item[0])]
|
||||
|
||||
index_changes = [_finite(r.get("change_pct")) for r in indices]
|
||||
index_changes = [v for v in index_changes if v is not None]
|
||||
avg_index_pct = sum(index_changes) / len(index_changes) if index_changes else 0
|
||||
vol_ratios = [_finite(r.get("vol_ratio_5d")) for r in rows]
|
||||
vol_ratios = [v for v in vol_ratios if v is not None]
|
||||
avg_vol_ratio = sum(vol_ratios) / len(vol_ratios) if vol_ratios else 1
|
||||
high_vol_ratio = sum(1 for v in vol_ratios if v >= 1.5)
|
||||
|
||||
concept_rank = _dimension_rank(rows, repo, "concept")
|
||||
industry_rank = _dimension_rank(rows, repo, "industry", level=2)
|
||||
|
||||
strong_diff_pct = (strong_up - strong_down) / total * 100 if total else 0
|
||||
high_vol_pct = high_vol_ratio / total * 100 if total else 0
|
||||
strong_down_pct = strong_down / total * 100 if total else 0
|
||||
tier2_count = sum(t["count"] for t in tiers if t["boards"] >= 2)
|
||||
mainline_items = [*concept_rank["leading"][:3], *industry_rank["leading"][:3]]
|
||||
mainline_avg = max([_finite(item.get("avg_pct")) or 0 for item in mainline_items], default=0)
|
||||
mainline_cover_pct = max([(_finite(item.get("count")) or 0) / total * 100 for item in mainline_items], default=0) if total else 0
|
||||
mainline_score = round(_score(mainline_avg, -0.005, 0.03) * 0.65 + _score(mainline_cover_pct, 1, 12) * 0.35) if mainline_items else 50
|
||||
|
||||
radar = [
|
||||
{"key": "index", "label": "指数", "value": _score(avg_index_pct, -2.5, 2.5)},
|
||||
{"key": "profit", "label": "赚钱", "value": round(_score(up_pct, 20, 80) * 0.45 + _score(avg_pct, -0.02, 0.02) * 0.25 + _score(median_pct, -0.02, 0.02) * 0.20 + _score(strong_diff_pct, -8, 8) * 0.10)},
|
||||
{"key": "money", "label": "量能", "value": round(_score(avg_vol_ratio, 0.6, 1.8) * 0.70 + _score(high_vol_pct, 2, 12) * 0.30)},
|
||||
{"key": "speculation", "label": "投机", "value": round(_score(limit_up, 5, 90) * 0.25 + _score(seal_rate, 30, 85) * 0.35 + _score(max_boards, 1, 8) * 0.25 + _score(tier2_count, 0, 30) * 0.15)},
|
||||
{"key": "resilience", "label": "抗跌", "value": 100 - round(_score(down_pct, 20, 80) * 0.55 + _score(strong_down_pct, 1, 12) * 0.45)},
|
||||
{"key": "mainline", "label": "主线", "value": mainline_score},
|
||||
]
|
||||
emotion_score = round(sum(r["value"] for r in radar) / len(radar)) if radar else 50
|
||||
if emotion_score >= 70:
|
||||
emotion_label = "强势"
|
||||
elif emotion_score >= 55:
|
||||
emotion_label = "偏暖"
|
||||
elif emotion_score >= 45:
|
||||
emotion_label = "震荡"
|
||||
elif emotion_score >= 30:
|
||||
emotion_label = "偏冷"
|
||||
else:
|
||||
emotion_label = "冰点"
|
||||
|
||||
return _json_safe({
|
||||
"as_of": str(as_of),
|
||||
"quote_status": status,
|
||||
"indices": indices,
|
||||
"breadth": {
|
||||
"total": total,
|
||||
"up": up,
|
||||
"down": down,
|
||||
"flat": flat,
|
||||
"up_pct": up_pct,
|
||||
"down_pct": down_pct,
|
||||
"avg_pct": avg_pct,
|
||||
"median_pct": median_pct,
|
||||
"strong_up": strong_up,
|
||||
"strong_down": strong_down,
|
||||
},
|
||||
"amount": {"total": total_amount, "avg": avg_amount},
|
||||
"boards": boards,
|
||||
"limit": {"limit_up": limit_up, "broken": broken, "failed": 0, "limit_down": limit_down, "max_boards": max_boards, "seal_rate": seal_rate, "tiers": tiers, "sealed_ready": sealed_ready, "fake_up": fake_up, "fake_down": fake_down},
|
||||
"distribution": _pct_band_rows(pct_values),
|
||||
"trend": {
|
||||
"above_ma5": above_ma5,
|
||||
"above_ma20": above_ma20,
|
||||
"above_ma60": above_ma60,
|
||||
"above_ma5_pct": above_ma5 / total * 100 if total else 0,
|
||||
"above_ma20_pct": above_ma20 / total * 100 if total else 0,
|
||||
"above_ma60_pct": above_ma60 / total * 100 if total else 0,
|
||||
"new_high": new_high,
|
||||
"new_low": new_low,
|
||||
},
|
||||
"activity": {
|
||||
"avg_turnover": avg_turnover,
|
||||
"high_turnover": high_turnover,
|
||||
"high_vol_ratio": high_vol_pct,
|
||||
"vol_ratio": avg_vol_ratio,
|
||||
},
|
||||
"radar": radar,
|
||||
"emotion": {"score": emotion_score, "label": emotion_label},
|
||||
"top_gainers": _top_rows(rows, "change_pct", True),
|
||||
"top_losers": _top_rows(rows, "change_pct", False),
|
||||
"turnover_leaders": _top_rows(rows, "amount", True),
|
||||
"active_leaders": _top_rows(rows, "turnover_rate", True),
|
||||
"concept_rank": concept_rank,
|
||||
"industry_rank": industry_rank,
|
||||
})
|
||||
@@ -0,0 +1,343 @@
|
||||
"""AI 大盘复盘 —— 流式 LLM 复盘生成。
|
||||
|
||||
复刻 stock_analyzer.py 的 NDJSON 流式协议(meta/delta/error/done),
|
||||
将「市场总览」聚合数据交给 LLM 生成结构化复盘报告。
|
||||
|
||||
数据来源:services.market_overview_builder.build_market_overview
|
||||
(与 GET /api/overview/market 同源,保证复盘与看板数据口径一致)。
|
||||
|
||||
流式协议(与 stock_analyzer / financial_analyzer 一致,前端解析无差异):
|
||||
{"type":"meta", "as_of", "emotion_score", "emotion_label", "summary"}
|
||||
{"type":"delta","content":"..."} 逐 chunk 文本
|
||||
{"type":"error","message":"..."}
|
||||
{"type":"done"}
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
from datetime import date
|
||||
from typing import AsyncIterator
|
||||
|
||||
from app.services.market_overview_builder import build_market_overview
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
# 指数简称映射:摘要里用简称(上/深/创/科),全称太长列表放不下。与前端 INDEX_SHORT 对齐。
|
||||
_INDEX_SHORT = {
|
||||
"上证指数": "上",
|
||||
"深证成指": "深",
|
||||
"创业板指": "创",
|
||||
"科创综指": "科",
|
||||
"科创50": "科",
|
||||
}
|
||||
|
||||
# ================================================================
|
||||
# 系统提示词(市场策略师人格 + 固定七节模板)
|
||||
# ================================================================
|
||||
|
||||
_SYSTEM_PROMPT = """你是一位拥有 15 年 A 股一线实战经验的资深市场策略师,擅长从指数结构、涨跌家数、连板梯队、板块轮动与资金情绪中提炼交易主线,产出可直接指导次日仓位与节奏的盘后复盘报告。
|
||||
|
||||
## 输出规范
|
||||
|
||||
用 **Markdown** 格式输出,严格遵循以下结构。不要输出任何 JSON 或代码块,直接输出 Markdown 正文。
|
||||
|
||||
### 1. 🎯 一句话定调(1-2 句)
|
||||
用一句话概括今日市场的**核心矛盾与状态**(如"放量普涨、情绪修复,主线围绕科技扩散"/"指数虚高、个股杀跌,赚钱效应冰点")。结尾用【明日基调:进攻 / 均衡 / 防守】给出明确倾向。
|
||||
|
||||
### 2. 📊 盘面总览
|
||||
- 三大指数(上证/深证/创业板)表现:谁强谁弱、量能配合
|
||||
- 涨跌家数、涨停/跌停/炸板结构、两市成交额(放量/缩量判断)
|
||||
- 情绪温度(强势/偏暖/震荡/偏冷/冰点)及一句话依据
|
||||
|
||||
### 3. 📈 指数结构
|
||||
谁在护盘、谁在拖累;指数是否同步;关键支撑/压力位(基于当日点位推断);是否存在量价背离。
|
||||
|
||||
### 4. 🔥 板块主线
|
||||
- 领涨板块:背后的逻辑(消息/业绩/资金/技术)、持续性判断、是否形成可交易主线
|
||||
- 领跌板块:风险信号、是否扩散
|
||||
- 连板梯队与投机情绪:最高连板、封板率、炸板率反映的资金激进程度
|
||||
|
||||
### 5. 💰 资金与情绪
|
||||
成交额结构(增量/存量)、市场宽度(上涨占比、站上均线占比)、量能指标(量比)解读;风险偏好是修复还是转弱。
|
||||
|
||||
### 6. 📰 消息催化
|
||||
结合提供的近期新闻,提炼真正影响明日交易节奏的催化或扰动,明确区分"已兑现"与"待发酵"。**若无新闻数据,则直接从量价异动推断可能的催化逻辑并给出结论,不要标注"[推断]"之类的过程标签,更不要编造具体消息。**
|
||||
|
||||
### 7. 🎯 明日交易计划
|
||||
- 进攻 / 均衡 / 防守:基于今日盘面给出次日基调
|
||||
- 仓位区间建议(轻仓/半仓/重仓的粗略指引)
|
||||
- 关注方向(领涨延续 / 低吸 / 反包)与回避方向(高位滞涨 / 杀跌扩散)
|
||||
- 一个明确的触发失效条件(如"若上证跌破 X 点则转为防守")
|
||||
|
||||
### 8. ⚠️ 风险提示
|
||||
列出需要重点盯的风险点(如量能跟不上、外资流出、连板断层等)。末尾附一行:
|
||||
"> ⚠️ 本报告由 AI 基于公开行情数据生成,仅供参考,不构成任何投资建议。交易有风险,入市需谨慎。"
|
||||
|
||||
## 分析准则(务必遵守)
|
||||
|
||||
0. **只输出结论,不输出思考过程**:禁止复述你的分析步骤或方法论。不要写"我先按...做结构化复盘""接下来看...""基于上述数据我认为"这类元话语——直接给结论。读者要的是复盘结果,不是你怎么推导出来的。
|
||||
1. **数据说话**:每个判断引用具体数值,严禁空泛套话("情绪回暖"必须改成"涨停 68 家较前日 +22,封板率 75%")
|
||||
2. **诚实中立**:看多就写多,看空就写空,不要骑墙;数据不支持时直言无法判断
|
||||
3. **结构优先**:先看指数同步性与量能结构,再看板块与情绪,最后才是消息
|
||||
4. **不重复数字**:正文负责解读表格数据背后的含义,不要照抄罗列已提供的大段原始数字
|
||||
5. **风险前置**:任何进攻建议都要配触发失效条件
|
||||
6. **简明实战**:用交易员能扫读的密度输出,总字数 1200-2000 字,重在可执行
|
||||
|
||||
现在请基于下方数据进行复盘。"""
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 用户消息构建(精简切片,控制 token)
|
||||
# ================================================================
|
||||
|
||||
def _fmt_pct(v, suffix="%") -> str:
|
||||
if v is None:
|
||||
return "—"
|
||||
return f"{v:+.2f}{suffix}" if suffix else f"{v:.2f}"
|
||||
|
||||
|
||||
def _build_indices_block(overview: dict) -> str:
|
||||
"""指数行情精简块。"""
|
||||
indices = overview.get("indices") or []
|
||||
if not indices:
|
||||
return "(暂无指数)"
|
||||
lines = []
|
||||
for idx in indices:
|
||||
name = idx.get("name") or idx.get("symbol")
|
||||
price = idx.get("last_price")
|
||||
chg = idx.get("change_pct")
|
||||
price_s = f"{price:.2f}" if price is not None else "—"
|
||||
lines.append(f"- {name}: {price_s} {_fmt_pct(chg)}")
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def _build_breadth_block(overview: dict) -> str:
|
||||
b = overview.get("breadth") or {}
|
||||
amt = overview.get("amount") or {}
|
||||
lim = overview.get("limit") or {}
|
||||
tr = overview.get("trend") or {}
|
||||
act = overview.get("activity") or {}
|
||||
|
||||
total_amount = amt.get("total") or 0
|
||||
# 成交额单位换算为亿元(原始为元)
|
||||
amount_yi = total_amount / 1e8 if total_amount else 0
|
||||
|
||||
lines = [
|
||||
f"- 上涨/下跌/平盘: {b.get('up',0)} / {b.get('down',0)} / {b.get('flat',0)}"
|
||||
f" (上涨占比 {b.get('up_pct',0):.1f}%)",
|
||||
f"- 涨停/炸板/跌停: {lim.get('limit_up',0)} / {lim.get('broken',0)} / {lim.get('limit_down',0)}"
|
||||
f" (封板率 {lim.get('seal_rate',0):.0f}%, 最高连板 {lim.get('max_boards',0)})",
|
||||
]
|
||||
if lim.get("tiers"):
|
||||
tiers_str = "、".join(f"{t['boards']}板×{t['count']}" for t in lim["tiers"][:5])
|
||||
lines.append(f"- 连板梯队: {tiers_str}")
|
||||
lines.append(f"- 两市成交额: {amount_yi:.0f} 亿元")
|
||||
lines.append(
|
||||
f"- 均线站位: MA5 {tr.get('above_ma5_pct',0):.0f}% / "
|
||||
f"MA20 {tr.get('above_ma20_pct',0):.0f}% / MA60 {tr.get('above_ma60_pct',0):.0f}%"
|
||||
)
|
||||
lines.append(
|
||||
f"- 量能: 平均换手 {act.get('avg_turnover',0):.2f}%, "
|
||||
f"量比5日均 {act.get('vol_ratio',1):.2f}"
|
||||
)
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def _build_sector_block(rank: dict, label: str) -> str:
|
||||
"""板块排名精简块(领涨/领跌 top5)。"""
|
||||
if not rank:
|
||||
return f"### {label}\n(暂无数据)"
|
||||
def _fmt(items):
|
||||
if not items:
|
||||
return "—"
|
||||
return "、".join(
|
||||
f"{it.get('name')}({(it.get('avg_pct') or 0)*100:+.2f}%,领涨:{it.get('leader',{}).get('name','—')})"
|
||||
for it in items[:5]
|
||||
)
|
||||
return (
|
||||
f"- 领涨{label}: {_fmt(rank.get('leading'))}\n"
|
||||
f"- 领跌{label}: {_fmt(rank.get('lagging'))}"
|
||||
)
|
||||
|
||||
|
||||
def _build_emotion_block(overview: dict) -> str:
|
||||
emo = overview.get("emotion") or {}
|
||||
radar = overview.get("radar") or []
|
||||
score = emo.get("score", 50)
|
||||
label = emo.get("label", "—")
|
||||
lines = [f"- 情绪温度: {score} ({label})"]
|
||||
if radar:
|
||||
dims = "、".join(f"{r.get('label')}{r.get('value',0)}" for r in radar)
|
||||
lines.append(f"- 六维雷达: {dims}")
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def _build_user_prompt(overview: dict, news: list[dict], focus: str) -> str:
|
||||
"""构建用户消息:复盘日期 + 市场数据精简切片 + 新闻 + 关注点。"""
|
||||
as_of = overview.get("as_of") or "今日"
|
||||
|
||||
parts: list[str] = [
|
||||
f"复盘日期: {as_of}",
|
||||
"",
|
||||
"## 主要指数",
|
||||
_build_indices_block(overview),
|
||||
"",
|
||||
"## 盘面数据",
|
||||
_build_breadth_block(overview),
|
||||
"",
|
||||
"## 市场情绪",
|
||||
_build_emotion_block(overview),
|
||||
"",
|
||||
"## 概念板块排名",
|
||||
_build_sector_block(overview.get("concept_rank"), "概念"),
|
||||
"",
|
||||
"## 行业板块排名",
|
||||
_build_sector_block(overview.get("industry_rank"), "行业"),
|
||||
]
|
||||
|
||||
if news:
|
||||
news_lines = []
|
||||
for i, n in enumerate(news[:8], 1):
|
||||
title = (n.get("title") or "").strip()
|
||||
snippet = (n.get("snippet") or "").strip()
|
||||
source = (n.get("source") or "").strip()
|
||||
pub = (n.get("published_date") or "").strip()
|
||||
meta = " / ".join(p for p in (source, pub) if p)
|
||||
news_lines.append(f"{i}. {title} ({meta})\n {snippet}" if meta else f"{i}. {title}\n {snippet}")
|
||||
parts.extend(["", "## 近期市场新闻", "\n".join(news_lines)])
|
||||
else:
|
||||
parts.extend([
|
||||
"",
|
||||
"## 近期市场新闻",
|
||||
"(暂无新闻数据:本功能新闻检索能力将在后续版本接入。"
|
||||
"消息催化一节请直接从量价异动给出可能的催化逻辑结论,不要编造具体消息,也不要复述本说明。)",
|
||||
])
|
||||
|
||||
if focus.strip():
|
||||
parts.extend(["", f"本次复盘请特别关注: {focus.strip()}"])
|
||||
|
||||
return "\n".join(parts)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 摘要生成(供 meta 事件 / 历史报告 summary)
|
||||
# ================================================================
|
||||
|
||||
def _recap_summary(overview: dict) -> str:
|
||||
"""一句话摘要(供 meta 事件与历史列表展示)。
|
||||
|
||||
指数用简称(上/深/创/科),与前端摘要条一致,避免列表里全称放不下。
|
||||
"""
|
||||
indices = overview.get("indices") or []
|
||||
emo = overview.get("emotion") or {}
|
||||
lim = overview.get("limit") or {}
|
||||
amt = overview.get("amount") or {}
|
||||
total_amount = (amt.get("total") or 0) / 1e8
|
||||
|
||||
idx_str = "、".join(
|
||||
f"{_INDEX_SHORT.get(i.get('name') or '', i.get('name') or '')}{(i.get('change_pct') or 0):+.2f}%"
|
||||
for i in indices[:4]
|
||||
) or "指数缺失"
|
||||
return (
|
||||
f"{idx_str} | 情绪{emo.get('score',50)}({emo.get('label','—')}) | "
|
||||
f"涨停{lim.get('limit_up',0)} | 成交{total_amount:.0f}亿"
|
||||
)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# 流式主入口
|
||||
# ================================================================
|
||||
|
||||
async def recap_market_stream(
|
||||
repo,
|
||||
quote_service=None,
|
||||
depth_service=None,
|
||||
as_of: date | None = None,
|
||||
focus: str = "",
|
||||
news: list[dict] | None = None,
|
||||
) -> AsyncIterator[str]:
|
||||
"""流式大盘复盘:yield 出每个 NDJSON 事件。
|
||||
|
||||
Args:
|
||||
repo: KlineRepository(必填)。
|
||||
quote_service / depth_service: 可选,数据装配依赖。
|
||||
as_of: 复盘日期,None 取最新有数据日。
|
||||
focus: 用户追加的复盘关注点。
|
||||
news: 预检索的新闻列表(P1 不传,留 None 走降级说明;P3 由 news_search 注入)。
|
||||
"""
|
||||
# 1. 装配市场总览
|
||||
overview = build_market_overview(repo, quote_service, depth_service, as_of)
|
||||
as_of_str = overview.get("as_of")
|
||||
|
||||
if not as_of_str:
|
||||
yield json.dumps({
|
||||
"type": "error",
|
||||
"message": "暂无市场数据,请先在「数据」页同步日 K 与指数后再复盘",
|
||||
}, ensure_ascii=False)
|
||||
return
|
||||
|
||||
emo = overview.get("emotion") or {}
|
||||
|
||||
# 2. meta 事件(前端据此先渲染信号灯/看板)
|
||||
yield json.dumps({
|
||||
"type": "meta",
|
||||
"as_of": as_of_str,
|
||||
"emotion_score": emo.get("score", 50),
|
||||
"emotion_label": emo.get("label", "—"),
|
||||
"summary": _recap_summary(overview),
|
||||
}, ensure_ascii=False)
|
||||
|
||||
# 3+4. 构建 prompt + 流式调用 LLM(整体 try-except,任何异常 yield error,避免前端卡死)
|
||||
try:
|
||||
from app.services.ai_provider import stream_ai_text
|
||||
|
||||
user_prompt = _build_user_prompt(overview, news or [], focus)
|
||||
async for delta in stream_ai_text(
|
||||
[
|
||||
{"role": "system", "content": _SYSTEM_PROMPT},
|
||||
{"role": "user", "content": user_prompt},
|
||||
],
|
||||
temperature=0.5,
|
||||
max_tokens=4500,
|
||||
):
|
||||
yield json.dumps({"type": "delta", "content": delta}, ensure_ascii=False)
|
||||
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.exception("AI market recap failed for %s: %s", as_of_str, e)
|
||||
yield json.dumps({"type": "error", "message": f"AI 复盘失败: {e}"}, ensure_ascii=False)
|
||||
return
|
||||
|
||||
yield json.dumps({"type": "done"}, ensure_ascii=False)
|
||||
|
||||
|
||||
async def recap_market_once(
|
||||
repo,
|
||||
quote_service=None,
|
||||
depth_service=None,
|
||||
as_of: date | None = None,
|
||||
focus: str = "",
|
||||
news: list[dict] | None = None,
|
||||
) -> tuple[str | None, dict]:
|
||||
"""非流式版本(供定时任务调用):累积全部 delta,返回 (content, meta)。
|
||||
|
||||
content 为完整 Markdown 文本;失败时为 None。
|
||||
meta 含 as_of / emotion_score / emotion_label / summary(即使失败也尽量回填)。
|
||||
"""
|
||||
content_parts: list[str] = []
|
||||
meta: dict = {"as_of": as_of.isoformat() if as_of else None}
|
||||
async for evt in recap_market_stream(repo, quote_service, depth_service, as_of, focus, news):
|
||||
try:
|
||||
obj = json.loads(evt)
|
||||
except Exception: # noqa: BLE001
|
||||
continue
|
||||
t = obj.get("type")
|
||||
if t == "meta":
|
||||
meta = obj
|
||||
elif t == "delta":
|
||||
content_parts.append(obj.get("content", ""))
|
||||
elif t == "error":
|
||||
logger.warning("market recap error event: %s", obj.get("message"))
|
||||
return None, meta
|
||||
return "".join(content_parts), meta
|
||||
@@ -0,0 +1,92 @@
|
||||
"""AI 大盘复盘报告持久化存储。
|
||||
|
||||
与 stock_reports.py(个股分析报告)/ ai_reports.py(财务分析报告)完全独立 ——
|
||||
单独的文件、字段、上限,互不影响。刻意不复用,避免引入 kind 判别字段与分支
|
||||
(解耦 > 抽象)。
|
||||
|
||||
存储位置: data/user_data/ai_market_recaps.json (数组,按 created_at 降序)
|
||||
保留最近 MAX_REPORTS 条;超出自动裁剪最旧的。
|
||||
|
||||
每条报告结构:
|
||||
{
|
||||
"id": "mkr_xxx", # 唯一 id(market-recap-report)
|
||||
"as_of": "2026-06-27", # 复盘日期
|
||||
"focus": "", # 用户追加的关心点(可为空)
|
||||
"content": "# ...markdown", # 报告正文
|
||||
"summary": "三大指数齐涨...", # 一句话摘要
|
||||
"emotion_score": 68, # 情绪分(0-100, 复盘生成时的市场情绪雷达均分)
|
||||
"emotion_label": "偏暖", # 情绪标签(强势/偏暖/震荡/偏冷/冰点)
|
||||
"created_at": "2026-06-27T15:35:00"
|
||||
}
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import time
|
||||
from pathlib import Path
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
MAX_REPORTS = 20
|
||||
|
||||
|
||||
def _path() -> Path:
|
||||
from app.config import settings
|
||||
p = settings.data_dir / "user_data" / "ai_market_recaps.json"
|
||||
p.parent.mkdir(parents=True, exist_ok=True)
|
||||
return p
|
||||
|
||||
|
||||
def list_reports() -> list[dict]:
|
||||
"""返回全部报告(按 created_at 降序)。"""
|
||||
p = _path()
|
||||
if not p.exists():
|
||||
return []
|
||||
try:
|
||||
data = json.loads(p.read_text(encoding="utf-8"))
|
||||
if isinstance(data, list):
|
||||
return sorted(data, key=lambda r: r.get("created_at", ""), reverse=True)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("ai_market_recaps.json malformed: %s", e)
|
||||
return []
|
||||
|
||||
|
||||
def _save_all(reports: list[dict]) -> None:
|
||||
"""全量写入(裁剪到 MAX_REPORTS)。"""
|
||||
reports.sort(key=lambda r: r.get("created_at", ""), reverse=True)
|
||||
if len(reports) > MAX_REPORTS:
|
||||
reports = reports[:MAX_REPORTS]
|
||||
_path().write_text(
|
||||
json.dumps(reports, indent=2, ensure_ascii=False), encoding="utf-8",
|
||||
)
|
||||
|
||||
|
||||
def save_report(report: dict) -> dict:
|
||||
"""新增一条报告并持久化。返回保存后的报告(含 id / created_at)。"""
|
||||
reports = list_reports()
|
||||
if not report.get("id"):
|
||||
report["id"] = f"mkr_{int(time.time() * 1000)}"
|
||||
if not report.get("created_at"):
|
||||
report["created_at"] = _now_iso()
|
||||
reports.append(report)
|
||||
_save_all(reports)
|
||||
logger.info("Market recap saved: %s (as_of=%s), total %d",
|
||||
report.get("id"), report.get("as_of"), len(reports))
|
||||
return report
|
||||
|
||||
|
||||
def delete_report(report_id: str) -> bool:
|
||||
"""删除指定报告。返回是否删除成功。"""
|
||||
reports = list_reports()
|
||||
before = len(reports)
|
||||
reports = [r for r in reports if r.get("id") != report_id]
|
||||
if len(reports) < before:
|
||||
_save_all(reports)
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def _now_iso() -> str:
|
||||
from datetime import datetime
|
||||
return datetime.now().isoformat(timespec="seconds")
|
||||
@@ -1,12 +1,12 @@
|
||||
"""系统通知适配器 — 调用操作系统原生通知命令。
|
||||
"""系统通知适配器 — 三平台原生通知中心。
|
||||
|
||||
职责: 把后端产生的告警事件推送到操作系统通知中心。
|
||||
窗口最小化 / 被遮挡 / 后台运行时都能弹通知。
|
||||
窗口最小化 / 被遮挡 / 后台运行时都能弹通知 (不依赖前端 WebView)。
|
||||
|
||||
平台实现:
|
||||
- macOS: osascript (系统已内置)
|
||||
- Linux: notify-send (系统已内置)
|
||||
- Windows: 暂不支持原生通知中心 (无额外依赖实现)
|
||||
- Windows: winotify (进现代操作中心, 支持图标)
|
||||
- macOS: osascript (系统已内置, 无需额外依赖)
|
||||
- Linux: notify-send (系统已内置) / plyer 兜底
|
||||
|
||||
设计: 失败静默降级, 绝不因通知失败阻断告警主流程 (落盘 / SSE 推送)。
|
||||
通知去重不在本层做, 复用 MonitorRuleEngine 的 cooldown 逻辑。
|
||||
@@ -34,7 +34,15 @@ def _detect_backend() -> str | None:
|
||||
return _backend_cache if _backend_cache != "none" else None
|
||||
|
||||
backend = None
|
||||
if sys.platform == "darwin":
|
||||
if sys.platform == "win32":
|
||||
try:
|
||||
import winotify # type: ignore[import-not-found] # noqa: F401
|
||||
|
||||
backend = "winotify"
|
||||
except ImportError:
|
||||
logger.debug("winotify 不可用, Windows 通知降级")
|
||||
backend = None
|
||||
elif sys.platform == "darwin":
|
||||
backend = "osascript"
|
||||
elif sys.platform.startswith("linux"):
|
||||
backend = "notify-send"
|
||||
@@ -71,6 +79,8 @@ def notify(title: str, message: str, icon: Path | None = None) -> bool:
|
||||
return False
|
||||
|
||||
try:
|
||||
if backend == "winotify":
|
||||
return _notify_winotify(title, message)
|
||||
if backend == "osascript":
|
||||
return _notify_osascript(title, message)
|
||||
if backend == "notify-send":
|
||||
@@ -82,6 +92,20 @@ def notify(title: str, message: str, icon: Path | None = None) -> bool:
|
||||
return False
|
||||
|
||||
|
||||
def _notify_winotify(title: str, message: str) -> bool:
|
||||
"""Windows 通知 (winotify) — 进现代操作中心。"""
|
||||
from winotify import Notifier # type: ignore[import-not-found]
|
||||
|
||||
Notifier().create_notification(
|
||||
title=title,
|
||||
msg=message,
|
||||
# winotify 要求 duration 为 "short" 或 "long"
|
||||
duration="short",
|
||||
# 无可点击动作 (桌面版不实现"点击回到窗口"的复杂交互)
|
||||
).show()
|
||||
return True
|
||||
|
||||
|
||||
def _notify_osascript(title: str, message: str) -> bool:
|
||||
"""macOS 通知 (osascript) — 调用系统 AppleScript。"""
|
||||
# 转义双引号, 避免 AppleScript 注入
|
||||
|
||||
@@ -53,6 +53,29 @@ def get_realtime_quote_interval() -> float:
|
||||
return load().get("realtime_quote_interval", 10.0)
|
||||
|
||||
|
||||
def get_realtime_watchlist_symbols() -> list[str]:
|
||||
"""Free 档自选实时监控标的:直接取自选页前 5 个。"""
|
||||
try:
|
||||
from app.services import watchlist
|
||||
rows = watchlist.list_symbols()
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("load watchlist for realtime failed: %s", e)
|
||||
return []
|
||||
out: list[str] = []
|
||||
for row in rows:
|
||||
symbol = str((row or {}).get("symbol") or "").strip().upper()
|
||||
if symbol and symbol not in out:
|
||||
out.append(symbol)
|
||||
if len(out) >= 5:
|
||||
break
|
||||
return out
|
||||
|
||||
|
||||
def set_realtime_watchlist_symbols(symbols: list[str]) -> list[str]: # noqa: ARG001
|
||||
"""兼容旧接口: Free 实时标的现在由自选页前 5 个决定。"""
|
||||
return get_realtime_watchlist_symbols()
|
||||
|
||||
|
||||
def set_realtime_quote_interval(interval: float) -> float:
|
||||
"""保存行情轮询间隔（不在此做 min/max 校验，由调用方按档位限制）。"""
|
||||
current = load()
|
||||
@@ -71,6 +94,83 @@ def get_minute_sync_days() -> int:
|
||||
return max(1, min(30, load().get("minute_sync_days", 5)))
|
||||
|
||||
|
||||
# ===== 数据源选择 (默认 TickFlow；第一阶段仅日K切换入口) =====
|
||||
|
||||
_ALLOWED_DATA_PROVIDERS = {"tickflow"}
|
||||
|
||||
|
||||
def get_daily_data_provider() -> str:
|
||||
provider = str(load().get("daily_data_provider", "tickflow") or "tickflow").lower()
|
||||
return provider if provider in _ALLOWED_DATA_PROVIDERS else "tickflow"
|
||||
|
||||
|
||||
def get_adj_factor_provider() -> str:
|
||||
provider = str(load().get("adj_factor_provider", "same_as_daily") or "same_as_daily").lower()
|
||||
if provider == "same_as_daily":
|
||||
return provider
|
||||
return provider if provider in _ALLOWED_DATA_PROVIDERS else "same_as_daily"
|
||||
|
||||
|
||||
def get_minute_data_provider() -> str:
|
||||
provider = str(load().get("minute_data_provider", "tickflow") or "tickflow").lower()
|
||||
return provider if provider in _ALLOWED_DATA_PROVIDERS else "tickflow"
|
||||
|
||||
|
||||
def get_realtime_data_provider() -> str:
|
||||
# 盘中实时现阶段仅支持 TickFlow。
|
||||
return "tickflow"
|
||||
|
||||
|
||||
# ===== 盘后管道拉取内容开关 (A股 / ETF / 指数 独立控制) =====
|
||||
|
||||
def get_pipeline_pull_a_share() -> bool:
|
||||
"""A 股日K固定拉取。"""
|
||||
return True
|
||||
|
||||
|
||||
def get_pipeline_pull_etf() -> bool:
|
||||
"""是否拉取 ETF 日K。默认 False(标的多,首次较慢)。"""
|
||||
return load().get("pipeline_pull_etf", False)
|
||||
|
||||
|
||||
def get_pipeline_pull_index() -> bool:
|
||||
"""是否拉取指数日K。默认 True。"""
|
||||
return load().get("pipeline_pull_index", True)
|
||||
|
||||
|
||||
_PIPELINE_PULL_KEYS = ("pipeline_pull_etf", "pipeline_pull_index")
|
||||
|
||||
|
||||
def get_pipeline_pull_types() -> dict:
|
||||
"""返回三个拉取开关的当前值。"""
|
||||
return {
|
||||
"pipeline_pull_a_share": get_pipeline_pull_a_share(),
|
||||
"pipeline_pull_etf": get_pipeline_pull_etf(),
|
||||
"pipeline_pull_index": get_pipeline_pull_index(),
|
||||
}
|
||||
|
||||
|
||||
def set_pipeline_pull_types(cfg: dict) -> dict:
|
||||
"""批量保存拉取开关。只接受白名单内的布尔字段。"""
|
||||
updates = {
|
||||
k: bool(v) for k, v in cfg.items()
|
||||
if k in _PIPELINE_PULL_KEYS and v is not None
|
||||
}
|
||||
save(updates)
|
||||
return get_pipeline_pull_types()
|
||||
|
||||
|
||||
def get_pipeline_index_symbols() -> str:
|
||||
"""指数自定义拉取代码(逗号/换行/空格分隔)。空串表示全量。"""
|
||||
return str(load().get("pipeline_index_symbols", "") or "").strip()
|
||||
|
||||
|
||||
def set_pipeline_index_symbols(symbols: str) -> str:
|
||||
"""保存指数自定义代码,返回规范化后的字符串。"""
|
||||
save({"pipeline_index_symbols": symbols})
|
||||
return get_pipeline_index_symbols()
|
||||
|
||||
|
||||
def get_pipeline_schedule() -> dict:
|
||||
"""返回盘后管道调度时间 {"hour": 15, "minute": 30}。"""
|
||||
d = load().get("pipeline_schedule", {"hour": 15, "minute": 30})
|
||||
@@ -165,6 +265,73 @@ def set_depth_finalize_time(hour: int, minute: int) -> dict:
|
||||
return {"hour": h, "minute": m}
|
||||
|
||||
|
||||
# 复盘推送可选渠道白名单 (微信等暂未实现, 不在白名单内, 前端仅作占位)
|
||||
# 多选: 不推送 = 空数组, 而非 'none'
|
||||
REVIEW_PUSH_CHANNELS = {"feishu"}
|
||||
|
||||
|
||||
def get_review_schedule() -> dict:
|
||||
"""定时复盘调度 {"enabled": False, "hour": 15, "minute": 10}。默认关闭。
|
||||
|
||||
A股 15:00 收盘, 默认时间设为 15:10(收盘后即时复盘), 强制下限 15:00。
|
||||
"""
|
||||
d = load().get("review_schedule", {"enabled": False, "hour": 15, "minute": 10})
|
||||
return {
|
||||
"enabled": bool(d.get("enabled", False)),
|
||||
"hour": d.get("hour", 15),
|
||||
"minute": d.get("minute", 10),
|
||||
}
|
||||
|
||||
|
||||
def set_review_schedule(enabled: bool, hour: int, minute: int) -> dict:
|
||||
"""保存定时复盘调度。强制时间下限 15:00(A股收盘)。
|
||||
|
||||
enabled=False 时时间仍保存(下次开启可沿用), 但调度器不会注册 job。
|
||||
"""
|
||||
h = max(0, min(23, hour))
|
||||
m = max(0, min(59, minute))
|
||||
# 下限 15:00: A股 15:00 收盘, 收盘后才有当日完整数据复盘
|
||||
if h * 60 + m < 15 * 60:
|
||||
h, m = 15, 0
|
||||
save({"review_schedule": {"enabled": bool(enabled), "hour": h, "minute": m}})
|
||||
return {"enabled": bool(enabled), "hour": h, "minute": m}
|
||||
|
||||
|
||||
def get_review_push_channels() -> list[str]:
|
||||
"""复盘推送渠道(多选) — 选定的外部工具列表, 复盘归档后逐个推送。
|
||||
|
||||
与 review_schedule / 实时行情完全独立, 常驻可单独设置。
|
||||
空列表 = 不推送; ['feishu'] = 推送到飞书(复用监控中心全局 feishu_webhook_url/secret)。
|
||||
|
||||
向后兼容:
|
||||
- 老多版本单选 review_push_channel=='feishu' → ['feishu']
|
||||
- 更老布尔 review_push_enabled==True → ['feishu']
|
||||
"""
|
||||
d = load()
|
||||
raw = d.get("review_push_channels")
|
||||
if isinstance(raw, list):
|
||||
return [c for c in raw if c in REVIEW_PUSH_CHANNELS]
|
||||
# 兼容老单选字符串
|
||||
if d.get("review_push_channel") == "feishu":
|
||||
return ["feishu"]
|
||||
# 兼容更老布尔开关
|
||||
if d.get("review_push_enabled") is True:
|
||||
return ["feishu"]
|
||||
return []
|
||||
|
||||
|
||||
def set_review_push_channels(channels: list[str]) -> list[str]:
|
||||
"""保存复盘推送渠道(多选)。过滤白名单外的值、去重、保序。空列表 = 不推送。"""
|
||||
seen: set[str] = set()
|
||||
cleaned: list[str] = []
|
||||
for c in channels or []:
|
||||
if c in REVIEW_PUSH_CHANNELS and c not in seen:
|
||||
seen.add(c)
|
||||
cleaned.append(c)
|
||||
save({"review_push_channels": cleaned})
|
||||
return cleaned
|
||||
|
||||
|
||||
|
||||
# ===== 实时监控 =====
|
||||
|
||||
@@ -178,6 +345,59 @@ SSE_REFRESH_PAGES_DEFAULT = {
|
||||
SIDEBAR_INDEX_SYMBOLS_DEFAULT = ["000001.SH", "399001.SZ", "399006.SZ", "000680.SH"]
|
||||
|
||||
|
||||
# ===== 盘中实时行情范围 (独立于盘后管道范围) =====
|
||||
|
||||
|
||||
def get_realtime_pull_stock() -> bool:
|
||||
return load().get("realtime_pull_stock", True)
|
||||
|
||||
|
||||
def get_realtime_pull_etf() -> bool:
|
||||
# 老用户兼容: ETF 实时默认关闭，避免升级后请求量/写盘量突然增加。
|
||||
return load().get("realtime_pull_etf", False)
|
||||
|
||||
|
||||
def get_realtime_pull_index() -> bool:
|
||||
return load().get("realtime_pull_index", True)
|
||||
|
||||
|
||||
def get_realtime_index_mode() -> str:
|
||||
mode = str(load().get("realtime_index_mode", "core") or "core").lower()
|
||||
return mode if mode in {"core", "all"} else "core"
|
||||
|
||||
|
||||
def get_realtime_index_symbols() -> list[str]:
|
||||
stored = load().get("realtime_index_symbols", SIDEBAR_INDEX_SYMBOLS_DEFAULT)
|
||||
if isinstance(stored, str):
|
||||
import re
|
||||
stored = [s.strip() for s in re.split(r"[,\s]+", stored) if s.strip()]
|
||||
return [str(s) for s in stored if str(s).strip()]
|
||||
|
||||
|
||||
def set_realtime_quote_scope(cfg: dict) -> dict:
|
||||
updates = {}
|
||||
for key in ("realtime_pull_stock", "realtime_pull_etf", "realtime_pull_index"):
|
||||
if key in cfg and cfg[key] is not None:
|
||||
updates[key] = bool(cfg[key])
|
||||
if "realtime_index_mode" in cfg and cfg["realtime_index_mode"] in {"core", "all"}:
|
||||
updates["realtime_index_mode"] = cfg["realtime_index_mode"]
|
||||
if "realtime_index_symbols" in cfg and cfg["realtime_index_symbols"] is not None:
|
||||
updates["realtime_index_symbols"] = cfg["realtime_index_symbols"]
|
||||
if updates:
|
||||
save(updates)
|
||||
return get_realtime_quote_scope()
|
||||
|
||||
|
||||
def get_realtime_quote_scope() -> dict:
|
||||
return {
|
||||
"realtime_pull_stock": get_realtime_pull_stock(),
|
||||
"realtime_pull_etf": get_realtime_pull_etf(),
|
||||
"realtime_pull_index": get_realtime_pull_index(),
|
||||
"realtime_index_mode": get_realtime_index_mode(),
|
||||
"realtime_index_symbols": get_realtime_index_symbols(),
|
||||
}
|
||||
|
||||
|
||||
def get_sse_refresh_pages() -> dict[str, bool]:
|
||||
"""返回每个页面的 SSE 刷新开关。"""
|
||||
stored = load().get("sse_refresh_pages", {})
|
||||
@@ -216,6 +436,43 @@ def set_system_notify_enabled(enabled: bool) -> bool:
|
||||
return bool(enabled)
|
||||
|
||||
|
||||
def get_feishu_webhook_url() -> str:
|
||||
"""飞书自定义机器人 Webhook 地址 — 全局共用一处, 所有启用推送的规则都推到这一个群。"""
|
||||
return load().get("feishu_webhook_url", "")
|
||||
|
||||
|
||||
def get_feishu_webhook_secret() -> str:
|
||||
"""飞书自定义机器人签名密钥 — 机器人启用「签名校验」时必填, 留空表示不验签。"""
|
||||
return load().get("feishu_webhook_secret", "")
|
||||
|
||||
|
||||
def set_feishu_webhook_url(url: str) -> str:
|
||||
"""保存飞书 Webhook 地址。传入空串表示清空配置。"""
|
||||
save({"feishu_webhook_url": str(url or "").strip()})
|
||||
return get_feishu_webhook_url()
|
||||
|
||||
|
||||
def set_feishu_webhook_secret(secret: str) -> str:
|
||||
"""保存飞书签名密钥。传入空串表示不验签。"""
|
||||
save({"feishu_webhook_secret": str(secret or "").strip()})
|
||||
return get_feishu_webhook_secret()
|
||||
|
||||
|
||||
def get_webhook_enabled_default() -> bool:
|
||||
"""新建监控规则时是否默认勾选「飞书推送」。
|
||||
|
||||
数据模型当前只有一个 webhook_enabled 布尔 (即飞书), QMT/ptrade 待定。
|
||||
此默认值供规则编辑器新建规则时预填, 单条规则仍可独立修改。
|
||||
"""
|
||||
return load().get("webhook_enabled_default", False)
|
||||
|
||||
|
||||
def set_webhook_enabled_default(enabled: bool) -> bool:
|
||||
"""保存飞书推送默认勾选态。"""
|
||||
save({"webhook_enabled_default": bool(enabled)})
|
||||
return get_webhook_enabled_default()
|
||||
|
||||
|
||||
def get_screener_auto_run() -> bool:
|
||||
"""选股页进入时是否自动运行所有策略 (获取命中数)。默认开。"""
|
||||
return load().get("screener_auto_run", True)
|
||||
@@ -311,3 +568,18 @@ def set_onboarding_completed(done: bool = True) -> bool:
|
||||
"""标记首次使用向导完成状态。"""
|
||||
save({"onboarding_completed": bool(done)})
|
||||
return bool(done)
|
||||
|
||||
|
||||
# ===== 财务数据同步时间(持久化,重启不丢失) =====
|
||||
# 结构: { "metrics": "2026-06-25T10:00:00+08:00", "income": ..., ... }
|
||||
|
||||
def get_financial_sync_times() -> dict[str, str]:
|
||||
"""返回各财务表的最后同步时间(ISO 字符串)。未同步过的表不在返回值中。"""
|
||||
return load().get("financial_sync_times", {}) or {}
|
||||
|
||||
|
||||
def set_financial_sync_time(table: str, iso_ts: str) -> None:
|
||||
"""更新单张财务表的最后同步时间(合并写入,不清除其他表)。"""
|
||||
times = get_financial_sync_times()
|
||||
times[table] = iso_ts
|
||||
save({"financial_sync_times": times})
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
集中管理全市场行情拉取 + enriched 缓存，供盘中选股、自选股等所有模块复用。
|
||||
|
||||
架构:
|
||||
- 后台线程轮询数据源 get_by_universes(["CN_Equity_A", "CN_Index"])
|
||||
- 后台线程轮询 TickFlow get_by_universes(["CN_Equity_A", "CN_Index"])
|
||||
- 拉取行情 → 写 kline_daily (不复权) + 增量计算 enriched → 写盘 + 更新缓存
|
||||
- _enriched_cache 是唯一的盘中数据源 (OHLCV + 全套技术指标)
|
||||
- _live_agg_cache 是递推状态 (只加载一次, 盘中不变)
|
||||
@@ -43,6 +43,7 @@ class QuoteService:
|
||||
"expert": 1.0,
|
||||
"pro": 2.0,
|
||||
"starter": 3.0,
|
||||
"free": 6.0,
|
||||
}
|
||||
DEFAULT_INTERVAL = 10.0
|
||||
MAX_INTERVAL = 60.0
|
||||
@@ -59,6 +60,10 @@ class QuoteService:
|
||||
self._depth_update_event = threading.Event() # SSE 通知: depth 五档修正后 set (刷新连板梯队)
|
||||
self._pending_alerts: list[dict] = [] # 待推送的告警
|
||||
self._max_pending_alerts: int = 1000 # 背压上限: 超出丢弃最旧
|
||||
# 复盘进度 SSE 通道: 定时复盘流式生成时, 把 meta/delta/done 事件推给开着页面的前端
|
||||
self._review_event = threading.Event() # SSE 通知: 有复盘进度事件时 set
|
||||
self._pending_review: list[str] = [] # 待推送的复盘事件(JSON 字符串)
|
||||
self._max_pending_review: int = 200 # 背压上限: 超出丢弃最旧
|
||||
self._strategy_monitor = None # 延迟注入
|
||||
self._app_state = None # 延迟注入 (FastAPI app.state)
|
||||
|
||||
@@ -68,6 +73,7 @@ class QuoteService:
|
||||
self._fetched_at: float = 0.0 # 拉取完成的 Unix 时间戳 (毫秒)
|
||||
self._symbol_count: int = 0
|
||||
self._index_symbol_count: int = 0
|
||||
self._etf_symbol_count: int = 0
|
||||
self._index_quotes_cache: pl.DataFrame | None = None
|
||||
|
||||
# ================================================================
|
||||
@@ -102,11 +108,11 @@ class QuoteService:
|
||||
def enable(self) -> bool:
|
||||
"""开启自动行情 (不立即启动线程，等下一个交易时段)。
|
||||
|
||||
none/free 档无实时行情权限,拒绝开启并返回 False;
|
||||
starter+ 正常启动。返回值表示是否真正开启。
|
||||
none 档无实时行情权限,拒绝开启并返回 False;
|
||||
free 档开启自选股实时,starter+ 开启全市场实时。返回值表示是否真正开启。
|
||||
"""
|
||||
if not self.is_realtime_allowed():
|
||||
logger.warning("实时行情开启被拒:当前档位(none/free)无实时行情权限")
|
||||
logger.warning("实时行情开启被拒:当前档位(none)无实时行情权限")
|
||||
return False
|
||||
self._enabled = True
|
||||
self._save_enabled(True)
|
||||
@@ -126,14 +132,14 @@ class QuoteService:
|
||||
def boot_check(self) -> None:
|
||||
"""启动时检查 preferences，若 enabled 则自动启动。
|
||||
|
||||
none/free 档无实时行情权限:即使 preferences 标记为 enabled,
|
||||
none 档无实时行情权限:即使 preferences 标记为 enabled,
|
||||
也不启动,并同步 preferences 为关闭(避免 UI 误显示已开启)。
|
||||
"""
|
||||
from app.services import preferences
|
||||
if not self.is_realtime_allowed():
|
||||
if preferences.get_realtime_quotes_enabled():
|
||||
self._save_enabled(False)
|
||||
logger.info("实时行情未启动:当前档位(none/free)无实时行情权限")
|
||||
logger.info("实时行情未启动:当前档位(none)无实时行情权限")
|
||||
return
|
||||
if preferences.get_realtime_quotes_enabled():
|
||||
self.start()
|
||||
@@ -188,6 +194,34 @@ class QuoteService:
|
||||
self._pending_alerts = []
|
||||
return alerts
|
||||
|
||||
# ================================================================
|
||||
# 复盘进度 SSE 通道 — 定时复盘流式生成时, 把事件实时推给前端
|
||||
# ================================================================
|
||||
def push_review_event(self, event_json: str) -> None:
|
||||
"""追加一条复盘进度事件(JSON 字符串), 并唤醒 SSE generator。
|
||||
|
||||
事件格式与 recap_market_stream 的产出一致(meta/delta/error/done),
|
||||
前端 reviewStore 直接消费。背压: 超过上限丢弃最旧(复盘流几百条 delta, 200 够用)。
|
||||
"""
|
||||
with self._lock:
|
||||
self._pending_review.append(event_json)
|
||||
if len(self._pending_review) > self._max_pending_review:
|
||||
overflow = len(self._pending_review) - self._max_pending_review
|
||||
self._pending_review = self._pending_review[overflow:]
|
||||
self._review_event.set()
|
||||
|
||||
def wait_for_review(self, timeout: float = 30.0) -> bool:
|
||||
"""阻塞等待复盘进度事件 (供 SSE 线程使用)。"""
|
||||
self._review_event.clear()
|
||||
return self._review_event.wait(timeout=timeout)
|
||||
|
||||
def pop_review_events(self) -> list[str]:
|
||||
"""取走所有待推送的复盘事件 (线程安全)。"""
|
||||
with self._lock:
|
||||
events = self._pending_review
|
||||
self._pending_review = []
|
||||
return events
|
||||
|
||||
# ================================================================
|
||||
# 档位感知间隔限制
|
||||
# ================================================================
|
||||
@@ -199,13 +233,19 @@ class QuoteService:
|
||||
return tier_label().split()[0].split("+")[0].strip().lower()
|
||||
|
||||
@classmethod
|
||||
def is_realtime_allowed(cls) -> bool:
|
||||
"""当前档位是否允许使用实时行情。
|
||||
def realtime_mode(cls) -> str:
|
||||
"""当前实时行情模式: none / watchlist / full_market。"""
|
||||
tier = cls._current_tier()
|
||||
if tier == "none":
|
||||
return "none"
|
||||
if tier == "free":
|
||||
return "watchlist"
|
||||
return "full_market"
|
||||
|
||||
none/free 档走 free-api 服务器,无实时行情权限 → 不允许;
|
||||
starter+ 付费档走付费端点,有实时行情 → 允许。
|
||||
"""
|
||||
return cls._current_tier() not in ("none", "free")
|
||||
@classmethod
|
||||
def is_realtime_allowed(cls) -> bool:
|
||||
"""当前档位是否允许使用实时行情。"""
|
||||
return cls.realtime_mode() != "none"
|
||||
|
||||
@classmethod
|
||||
def _tier_min_interval(cls) -> float:
|
||||
@@ -251,7 +291,7 @@ class QuoteService:
|
||||
return df
|
||||
|
||||
def get_index_quotes(self, symbols: list[str] | None = None) -> pl.DataFrame:
|
||||
"""返回实时指数行情缓存。不会触发数据源请求。"""
|
||||
"""返回实时指数行情缓存。不会触发 TickFlow 请求。"""
|
||||
with self._lock:
|
||||
df = self._index_quotes_cache.clone() if self._index_quotes_cache is not None else pl.DataFrame()
|
||||
if df.is_empty():
|
||||
@@ -262,13 +302,19 @@ class QuoteService:
|
||||
|
||||
def status(self) -> dict:
|
||||
"""返回行情服务状态。"""
|
||||
from app.services import preferences
|
||||
age = (time.perf_counter() - self._fetch_time) * 1000 if self._fetch_time else -1
|
||||
mode = self.realtime_mode()
|
||||
return {
|
||||
"enabled": self._enabled,
|
||||
"running": self._running,
|
||||
"mode": mode,
|
||||
"realtime_allowed": mode != "none",
|
||||
"watchlist_symbol_count": len(preferences.get_realtime_watchlist_symbols()),
|
||||
"interval_s": self._interval,
|
||||
"symbol_count": self._symbol_count,
|
||||
"index_symbol_count": self._index_symbol_count,
|
||||
"etf_symbol_count": self._etf_symbol_count,
|
||||
"quote_age_ms": round(age, 0) if age >= 0 else None,
|
||||
"is_trading_hours": self._is_trading_hours(),
|
||||
"last_fetch_ms": round(self._fetched_at, 0) if self._fetched_at else None,
|
||||
@@ -299,17 +345,47 @@ class QuoteService:
|
||||
waited += 0.5
|
||||
|
||||
def _fetch_quotes(self) -> None:
|
||||
"""拉取全市场行情 → 写 daily + 计算 enriched + 更新缓存。"""
|
||||
from app.tickflow.client import get_client
|
||||
"""按当前档位拉取行情。"""
|
||||
if self.realtime_mode() == "watchlist":
|
||||
self._fetch_watchlist_quotes()
|
||||
return
|
||||
self._fetch_full_market_quotes()
|
||||
|
||||
tf = get_client()
|
||||
def _fetch_full_market_quotes(self) -> None:
|
||||
"""拉取全市场行情 → 写 daily + 计算 enriched + 更新缓存。"""
|
||||
from app.tickflow.client import get_paid_realtime_client
|
||||
|
||||
tf = get_paid_realtime_client()
|
||||
if tf is None:
|
||||
logger.warning("实时行情拉取失败:未配置付费服务器 API Key")
|
||||
return
|
||||
t0 = time.perf_counter()
|
||||
now_ts = time.perf_counter()
|
||||
|
||||
try:
|
||||
from app.services import preferences
|
||||
all_index_symbols = set(self._repo.get_index_symbol_set()) if self._repo else set()
|
||||
all_index_symbols.update(self.CORE_INDEX_SYMBOLS)
|
||||
resp = tf.quotes.get_by_universes(universes=["CN_Equity_A", "CN_Index"])
|
||||
core_index_symbols = set(preferences.get_realtime_index_symbols() or self.CORE_INDEX_SYMBOLS)
|
||||
all_index_symbols.update(core_index_symbols)
|
||||
all_etf_symbols = set()
|
||||
if self._repo:
|
||||
etf_inst = self._repo.get_etf_instruments()
|
||||
if not etf_inst.is_empty() and "symbol" in etf_inst.columns:
|
||||
all_etf_symbols = set(etf_inst["symbol"].cast(pl.Utf8).to_list())
|
||||
|
||||
universes: list[str] = []
|
||||
if preferences.get_realtime_pull_stock():
|
||||
universes.append("CN_Equity_A")
|
||||
if preferences.get_realtime_pull_etf() and all_etf_symbols:
|
||||
universes.append("CN_ETF")
|
||||
if preferences.get_realtime_pull_index() and preferences.get_realtime_index_mode() == "all":
|
||||
universes.append("CN_Index")
|
||||
|
||||
resp = []
|
||||
if universes:
|
||||
resp.extend(tf.quotes.get_by_universes(universes=universes) or [])
|
||||
if preferences.get_realtime_pull_index() and preferences.get_realtime_index_mode() == "core":
|
||||
resp.extend(tf.quotes.get(symbols=sorted(core_index_symbols)) or [])
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("行情拉取失败: %s", e)
|
||||
return
|
||||
@@ -349,7 +425,11 @@ class QuoteService:
|
||||
})
|
||||
|
||||
index_records = [r for r in records if r.get("symbol") in all_index_symbols]
|
||||
stock_records = [r for r in records if r.get("symbol") not in all_index_symbols]
|
||||
etf_records = [r for r in records if r.get("symbol") in all_etf_symbols]
|
||||
stock_records = [
|
||||
r for r in records
|
||||
if r.get("symbol") not in all_index_symbols and r.get("symbol") not in all_etf_symbols
|
||||
]
|
||||
|
||||
fetch_ms = (time.perf_counter() - t0) * 1000
|
||||
fetched_at = time.time() * 1000
|
||||
@@ -361,9 +441,10 @@ class QuoteService:
|
||||
self._fetched_at = fetched_at
|
||||
self._symbol_count = len(stock_records)
|
||||
self._index_symbol_count = len(index_records)
|
||||
self._etf_symbol_count = len(etf_records)
|
||||
self._index_quotes_cache = self._build_index_quotes(index_records)
|
||||
|
||||
logger.info("行情刷新: %d 只股票, %d 只指数, 耗时 %.0fms", len(stock_records), len(index_records), fetch_ms)
|
||||
logger.info("行情刷新: %d 只股票, %d 只ETF, %d 只指数, 耗时 %.0fms", len(stock_records), len(etf_records), len(index_records), fetch_ms)
|
||||
|
||||
# ---- 写 kline_daily (不复权原始价格, 只有 OHLCV) ----
|
||||
daily_df = self._build_daily(stock_records)
|
||||
@@ -373,12 +454,22 @@ class QuoteService:
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("日K写盘失败: %s", e)
|
||||
|
||||
etf_daily_df = self._build_daily(etf_records)
|
||||
if not etf_daily_df.is_empty() and self._repo:
|
||||
try:
|
||||
self._repo.flush_live_daily_asset("etf", etf_daily_df)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("ETF 日K写盘失败: %s", e)
|
||||
|
||||
# ---- 构建 API 直接值的补充表 (不写 daily, 只用于 enriched 计算) ----
|
||||
quote_extra = self._build_quote_extra(stock_records)
|
||||
etf_quote_extra = self._build_quote_extra(etf_records)
|
||||
|
||||
# ---- 增量计算 enriched + 写盘 + 更新缓存 ----
|
||||
if not daily_df.is_empty() and self._repo:
|
||||
self._flush_live_enriched(daily_df, quote_extra)
|
||||
self._flush_live_enriched(daily_df, quote_extra, asset_type="stock")
|
||||
if not etf_daily_df.is_empty() and self._repo:
|
||||
self._flush_live_enriched(etf_daily_df, etf_quote_extra, asset_type="etf")
|
||||
|
||||
# ---- 通知 SSE ----
|
||||
self._update_event.set()
|
||||
@@ -386,6 +477,87 @@ class QuoteService:
|
||||
# ---- 策略监控 + 告警评估 ----
|
||||
self._evaluate_monitors(daily_df, quote_extra)
|
||||
|
||||
def _fetch_watchlist_quotes(self) -> None:
|
||||
"""Free 档自选股实时: 只拉取最多 5 个 symbols。"""
|
||||
from app.services import preferences
|
||||
from app.tickflow.client import get_paid_realtime_client
|
||||
|
||||
symbols = preferences.get_realtime_watchlist_symbols()
|
||||
if not symbols:
|
||||
logger.info("自选实时未配置标的, 跳过行情拉取")
|
||||
return
|
||||
|
||||
tf = get_paid_realtime_client()
|
||||
if tf is None:
|
||||
logger.warning("自选实时拉取失败:未配置付费服务器 API Key")
|
||||
return
|
||||
|
||||
t0 = time.perf_counter()
|
||||
now_ts = time.perf_counter()
|
||||
try:
|
||||
resp = tf.quotes.get(symbols=symbols) or []
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("自选实时拉取失败: %s", e)
|
||||
return
|
||||
|
||||
if not resp:
|
||||
logger.warning("自选实时行情数据为空")
|
||||
return
|
||||
|
||||
records = []
|
||||
for q in resp:
|
||||
ext = q.get("ext") or {}
|
||||
last_price = q.get("last_price")
|
||||
prev_close = q.get("prev_close")
|
||||
change_amount = ext.get("change_amount")
|
||||
change_pct = ext.get("change_pct")
|
||||
if change_amount is None and last_price is not None and prev_close is not None:
|
||||
change_amount = float(last_price) - float(prev_close)
|
||||
if change_pct is None and change_amount is not None and prev_close not in (None, 0):
|
||||
change_pct = float(change_amount) / float(prev_close) * 100
|
||||
records.append({
|
||||
"symbol": q.get("symbol"),
|
||||
"name": q.get("name") or ext.get("name"),
|
||||
"last_price": last_price,
|
||||
"prev_close": prev_close,
|
||||
"open": q.get("open"),
|
||||
"high": q.get("high"),
|
||||
"low": q.get("low"),
|
||||
"volume": q.get("volume"),
|
||||
"amount": q.get("amount"),
|
||||
"change_pct": change_pct,
|
||||
"change_amount": change_amount,
|
||||
"amplitude": ext.get("amplitude"),
|
||||
"turnover_rate": ext.get("turnover_rate"),
|
||||
"timestamp": q.get("timestamp"),
|
||||
"session": q.get("session"),
|
||||
})
|
||||
|
||||
fetch_ms = (time.perf_counter() - t0) * 1000
|
||||
fetched_at = time.time() * 1000
|
||||
with self._lock:
|
||||
self._fetch_time = now_ts
|
||||
self._fetch_ms = fetch_ms
|
||||
self._fetched_at = fetched_at
|
||||
self._symbol_count = len(records)
|
||||
self._index_symbol_count = 0
|
||||
self._etf_symbol_count = 0
|
||||
self._index_quotes_cache = None
|
||||
|
||||
logger.info("自选实时刷新: %d 只股票, 耗时 %.0fms", len(records), fetch_ms)
|
||||
|
||||
daily_df = self._build_daily(records)
|
||||
quote_extra = self._build_quote_extra(records)
|
||||
if not daily_df.is_empty() and self._repo:
|
||||
try:
|
||||
self._repo.merge_live_daily_asset("stock", daily_df)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("自选实时日K写盘失败: %s", e)
|
||||
self._flush_live_enriched(daily_df, quote_extra, asset_type="stock", merge=True)
|
||||
|
||||
self._update_event.set()
|
||||
self._evaluate_monitors(daily_df, quote_extra)
|
||||
|
||||
# ================================================================
|
||||
# 工具
|
||||
# ================================================================
|
||||
@@ -495,6 +667,8 @@ class QuoteService:
|
||||
return
|
||||
|
||||
all_alerts: list[dict] = []
|
||||
rule_events: list[dict] = []
|
||||
engine = None
|
||||
|
||||
# 通用监控规则评估 (统一引擎: signal/price/market/strategy)
|
||||
if self._app_state:
|
||||
@@ -511,7 +685,11 @@ class QuoteService:
|
||||
})
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.debug("name_map 构建失败 (不影响监控): %s", e)
|
||||
rule_events = engine.evaluate(enriched_today)
|
||||
# 连板梯队封单监控: 有 ladder 规则时, 从 depth_service 注入封单量到 enriched
|
||||
eval_df = enriched_today
|
||||
if engine.has_rule_type("ladder"):
|
||||
eval_df = self._inject_sealed_vol(enriched_today, enriched_date)
|
||||
rule_events = engine.evaluate(eval_df)
|
||||
if rule_events:
|
||||
# 落盘到 alerts.jsonl
|
||||
try:
|
||||
@@ -535,11 +713,13 @@ class QuoteService:
|
||||
"change_pct": ev["change_pct"],
|
||||
"signals": ev["signals"],
|
||||
"severity": ev.get("severity", "info"),
|
||||
"conditions": ev.get("conditions") or [],
|
||||
"logic": ev.get("logic") or "and",
|
||||
})
|
||||
|
||||
# 刷新策略结果缓存 (实时行情开启时，每轮行情更新后自动重算)
|
||||
if self._enabled and self._app_state:
|
||||
self._refresh_strategy_cache(enriched_today, enriched_date)
|
||||
# 策略页实时回显: 不写文件 (实时行情每轮更新 enriched, 写文件会被 read_cache
|
||||
# 的 mtime 校验判过期, 反复读不到)。监控引擎本轮已算出的结果存在内存
|
||||
# (latest_strategy_results), 由 /api/screener/cached 端点直接叠加读取。
|
||||
|
||||
# 推入待推送队列 + 通知 SSE (含背压保护)
|
||||
if all_alerts:
|
||||
@@ -556,9 +736,95 @@ class QuoteService:
|
||||
# cooldown 去重已在 MonitorRuleEngine 做过, 这里只负责转发。
|
||||
self._maybe_send_system_notifications(all_alerts)
|
||||
|
||||
# Webhook 推送 (飞书等外部 IM, 由规则 webhook_enabled 开关控制)。
|
||||
# 紧随系统通知, 同样静默降级不阻断主流程。
|
||||
if rule_events:
|
||||
self._maybe_send_webhook(rule_events, engine)
|
||||
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("监控评估失败: %s", e)
|
||||
|
||||
def _inject_sealed_vol(self, enriched_today: pl.DataFrame, enriched_date) -> pl.DataFrame:
|
||||
"""从 depth_service 取封单量, 作为临时列 _sealed_vol 注入 enriched 副本。
|
||||
|
||||
涨停封单(买一量) + 跌停封单(卖一量)合并, 供 ladder 规则评估。
|
||||
depth 未就绪时返回原 df (不注入, ladder 规则安全降级不触发)。
|
||||
"""
|
||||
try:
|
||||
depth_svc = getattr(self._app_state, "depth_service", None)
|
||||
if not depth_svc:
|
||||
return enriched_today
|
||||
# enriched_date 可能是 date 或字符串, 统一为 date
|
||||
from datetime import date as date_cls
|
||||
target_date = enriched_date if isinstance(enriched_date, date_cls) else date_cls.fromisoformat(str(enriched_date))
|
||||
# 取涨停 + 跌停封单, 合并 {symbol: vol}
|
||||
up_map = depth_svc.get_sealed_map(target_date, is_down=False)
|
||||
down_map = depth_svc.get_sealed_map(target_date, is_down=True)
|
||||
sealed: dict[str, int] = {}
|
||||
for m in (up_map, down_map):
|
||||
for sym, info in m.items():
|
||||
vol = (info or {}).get("vol")
|
||||
if vol and vol > 0:
|
||||
sealed[sym] = vol # 后者覆盖前者 (同 symbol 不可能在涨跌停都封单)
|
||||
if not sealed:
|
||||
return enriched_today
|
||||
# 构造 (symbol, _sealed_vol) DataFrame, join 到 enriched 副本
|
||||
sealed_df = pl.DataFrame({
|
||||
"symbol": list(sealed.keys()),
|
||||
"_sealed_vol": list(sealed.values()),
|
||||
})
|
||||
# 若已有残留列先移除 (避免重复 join 报错)
|
||||
df = enriched_today.drop("_sealed_vol") if "_sealed_vol" in enriched_today.columns else enriched_today
|
||||
return df.join(sealed_df, on="symbol", how="left")
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.debug("封单注入失败 (ladder 规则将不触发): %s", e)
|
||||
return enriched_today
|
||||
|
||||
def _maybe_send_webhook(self, rule_events: list[dict], engine) -> None:
|
||||
"""把告警通过 Webhook 推送到外部 IM (由规则 webhook_enabled 开关控制)。
|
||||
|
||||
- 全局飞书 URL 未配置: 直接返回
|
||||
- 仅推送 webhook_enabled=True 的规则触发的告警
|
||||
- 失败静默, 不阻断主流程
|
||||
- 去重: 复用 MonitorRuleEngine 的 cooldown, 此处不重复去重
|
||||
|
||||
注意: 用 rule_events (含 rule_id) 而非重建后的 all_alerts,
|
||||
以便反查引擎规则判断是否启用推送。
|
||||
"""
|
||||
try:
|
||||
from app.services import preferences
|
||||
from app.services import webhook_adapter
|
||||
|
||||
url = preferences.get_feishu_webhook_url()
|
||||
if not url:
|
||||
return
|
||||
secret = preferences.get_feishu_webhook_secret()
|
||||
|
||||
# 反查规则, 过滤出启用推送的事件
|
||||
source_labels = {
|
||||
"strategy": "策略", "signal": "信号",
|
||||
"price": "价格", "market": "异动",
|
||||
}
|
||||
rules = engine.rules if engine is not None else {}
|
||||
pushed = 0
|
||||
for ev in rule_events:
|
||||
rule = rules.get(ev.get("rule_id"))
|
||||
if not rule or not rule.get("webhook_enabled"):
|
||||
continue
|
||||
source = ev.get("source", "")
|
||||
source_label = source_labels.get(source, source or "通知")
|
||||
symbol = ev.get("symbol") or ""
|
||||
name = ev.get("name") or ""
|
||||
message = ev.get("message") or ""
|
||||
title = f"TickFlow · {source_label}"
|
||||
body = f"{symbol} {name} {message}".strip() if symbol else (message or name)
|
||||
if webhook_adapter.send_feishu(url, title, body, secret):
|
||||
pushed += 1
|
||||
if pushed:
|
||||
logger.info("飞书 Webhook 推送: %d 条", pushed)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.debug("Webhook 推送异常 (不影响告警主流程): %s", e)
|
||||
|
||||
def _maybe_send_system_notifications(self, all_alerts: list[dict]) -> None:
|
||||
"""把告警转发到操作系统通知中心 (由 preferences 开关控制)。
|
||||
|
||||
@@ -592,95 +858,11 @@ class QuoteService:
|
||||
else:
|
||||
body = message or name
|
||||
|
||||
title = f"Stock Panel · {source_label}"
|
||||
title = f"TickFlow · {source_label}"
|
||||
notify_adapter.notify(title, body)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.debug("系统通知发送异常 (不影响告警主流程): %s", e)
|
||||
|
||||
def _refresh_strategy_cache(self, enriched_today: pl.DataFrame, enriched_date: date | None) -> None:
|
||||
"""利用已计算好的 enriched 数据，运行策略池并写入缓存。"""
|
||||
import math
|
||||
from dataclasses import asdict
|
||||
from app.services import strategy_cache
|
||||
from app.services.screener import PRESET_STRATEGIES, ScreenerService
|
||||
from app.strategy import config as strategy_config
|
||||
|
||||
try:
|
||||
if enriched_date is None:
|
||||
return
|
||||
as_of = enriched_date
|
||||
data_dir = self._repo.store.data_dir
|
||||
svc = ScreenerService(self._repo)
|
||||
engine = getattr(self._app_state, "strategy_engine", None)
|
||||
|
||||
# 确定要运行的策略: 策略监控池中的策略
|
||||
monitor_ids = self._get_monitor_pool_ids()
|
||||
if not monitor_ids:
|
||||
return
|
||||
|
||||
# 一次加载所有 override
|
||||
all_overrides = strategy_config.list_overrides(data_dir)
|
||||
|
||||
# 历史策略: 只在需要时加载
|
||||
shared_history = None
|
||||
history_strats = []
|
||||
if engine:
|
||||
id_set = set(monitor_ids)
|
||||
history_strats = [
|
||||
(sid, s) for sid, s in engine._strategies.items()
|
||||
if s.filter_history_fn and sid in id_set
|
||||
]
|
||||
if history_strats:
|
||||
max_lb = max(s.lookback_days for _, s in history_strats)
|
||||
shared_history = svc._load_enriched_history(as_of, max(1, max_lb))
|
||||
|
||||
results: dict[str, dict] = {}
|
||||
for sid in monitor_ids:
|
||||
try:
|
||||
overrides = all_overrides.get(sid, {})
|
||||
bf = overrides.get("basic_filter") if overrides else None
|
||||
dl = overrides.get("display_limit") if overrides else None
|
||||
if dl is None and overrides and "display_limit" in overrides:
|
||||
dl = 0
|
||||
|
||||
if sid in PRESET_STRATEGIES:
|
||||
r = svc.run_preset(sid, as_of=as_of, precomputed=enriched_today, basic_filter=bf, display_limit=dl)
|
||||
elif engine:
|
||||
r = engine.run(
|
||||
sid, as_of, overrides=overrides or None,
|
||||
precomputed=enriched_today, precomputed_history=shared_history,
|
||||
)
|
||||
if dl is not None and dl > 0:
|
||||
r.rows = r.rows[:dl]
|
||||
r.total = min(r.total, dl)
|
||||
else:
|
||||
continue
|
||||
|
||||
# sanitize NaN/Inf
|
||||
rows = []
|
||||
for row_dict in asdict(r).get("rows", []):
|
||||
for k, v in list(row_dict.items()):
|
||||
if isinstance(v, float) and not math.isfinite(v):
|
||||
row_dict[k] = None
|
||||
rows.append(row_dict)
|
||||
results[sid] = {"total": r.total, "as_of": str(as_of), "rows": rows}
|
||||
except Exception: # noqa: BLE001
|
||||
continue
|
||||
|
||||
if results:
|
||||
strategy_cache.write_cache(data_dir, str(as_of), results)
|
||||
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("策略缓存刷新失败: %s", e)
|
||||
|
||||
def _get_monitor_pool_ids(self) -> list[str]:
|
||||
"""获取策略监控池中的策略 ID 列表。"""
|
||||
from app.services import preferences
|
||||
ids = preferences.get_strategy_monitor_ids()
|
||||
if not ids:
|
||||
return []
|
||||
return [sid for sid in ids if sid]
|
||||
|
||||
@staticmethod
|
||||
def _get_strategy_monitor():
|
||||
"""获取 StrategyMonitorService — 不再使用, 改用 _app_state 注入。"""
|
||||
@@ -690,7 +872,7 @@ class QuoteService:
|
||||
# enriched 增量计算
|
||||
# ================================================================
|
||||
|
||||
def _flush_live_enriched(self, daily_df: pl.DataFrame, quote_extra: pl.DataFrame = None) -> None:
|
||||
def _flush_live_enriched(self, daily_df: pl.DataFrame, quote_extra: pl.DataFrame = None, asset_type: str = "stock", merge: bool = False) -> None:
|
||||
"""增量计算今天的 enriched: 用昨天的递推状态 + 今天 OHLCV → 只算今天 5500 行。
|
||||
|
||||
quote_extra: API 直接提供的补充字段 (prev_close, change_pct 等),
|
||||
@@ -701,11 +883,16 @@ class QuoteService:
|
||||
t0 = time.perf_counter()
|
||||
|
||||
# ---- 尝试增量路径 ----
|
||||
live_agg = self._repo.get_live_agg()
|
||||
prev_enriched, prev_date = self._repo.get_enriched_latest()
|
||||
live_agg = self._repo.get_live_agg() if asset_type == "stock" else pl.DataFrame()
|
||||
prev_enriched, prev_date = (
|
||||
self._repo.get_enriched_latest()
|
||||
if asset_type == "stock"
|
||||
else self._repo.get_enriched_latest_asset(asset_type)
|
||||
)
|
||||
|
||||
use_incremental = (
|
||||
not live_agg.is_empty()
|
||||
asset_type == "stock"
|
||||
and not live_agg.is_empty()
|
||||
and not prev_enriched.is_empty()
|
||||
and prev_date is not None
|
||||
)
|
||||
@@ -736,7 +923,8 @@ class QuoteService:
|
||||
"ok" if not live_agg.is_empty() else "空", prev_date)
|
||||
|
||||
cutoff = today - timedelta(days=90)
|
||||
daily_glob = str(self._repo.store.data_dir / "kline_daily" / "**" / "*.parquet")
|
||||
table = "kline_etf_daily" if asset_type == "etf" else "kline_daily"
|
||||
daily_glob = str(self._repo.store.data_dir / table / "**" / "*.parquet")
|
||||
ohlcv_cols = ["symbol", "date", "open", "high", "low", "close", "volume", "amount"]
|
||||
hist_df = (
|
||||
pl.scan_parquet(daily_glob)
|
||||
@@ -753,14 +941,15 @@ class QuoteService:
|
||||
full_df = pl.concat([hist_df, daily_ohlcv], how="diagonal_relaxed")
|
||||
full_df = full_df.sort(["symbol", "date"])
|
||||
|
||||
factor_path = self._repo.store.data_dir / "adj_factor" / "all.parquet"
|
||||
factor_dir = "adj_factor_etf" if asset_type == "etf" else "adj_factor"
|
||||
factor_path = self._repo.store.data_dir / factor_dir / "all.parquet"
|
||||
factors = pl.DataFrame()
|
||||
if factor_path.exists():
|
||||
try:
|
||||
factors = pl.read_parquet(factor_path)
|
||||
except Exception:
|
||||
pass
|
||||
instruments = self._repo.get_instruments()
|
||||
instruments = self._repo.get_instruments() if asset_type == "stock" else None
|
||||
|
||||
enriched_full = compute_enriched(full_df, factors=factors, instruments=instruments)
|
||||
enriched_today = enriched_full.filter(pl.col("date") == today)
|
||||
@@ -769,7 +958,10 @@ class QuoteService:
|
||||
return
|
||||
|
||||
# ---- 写盘 + 更新缓存 ----
|
||||
self._repo.flush_live_enriched(enriched_today)
|
||||
if merge:
|
||||
self._repo.merge_live_enriched_asset(asset_type, enriched_today)
|
||||
else:
|
||||
self._repo.flush_live_enriched_asset(asset_type, enriched_today)
|
||||
|
||||
elapsed = time.perf_counter() - t0
|
||||
mode_label = "增量" if use_incremental else "全量"
|
||||
|
||||
@@ -0,0 +1,214 @@
|
||||
"""概念涨幅轮动矩阵 service。
|
||||
|
||||
输出「每列(日期)各自把所有概念按当天涨幅从高到低排序」的矩阵,供前端
|
||||
「概念分析 → 涨幅RPS轮动」对话框渲染。
|
||||
|
||||
数据来源全部复用现有资产, 不引入新数据源:
|
||||
- 个股历史涨跌幅: repo.get_enriched_range(..., columns=["symbol","date","change_pct"])
|
||||
命中启动时构建的 _enriched_history_cache (0ms, 含 change_pct 小数列)
|
||||
- 概念成分股映射: 复用 market_overview_builder 的 _dimension_field / _read_ext_rows /
|
||||
_symbol_keys / _dimension_values, 与看板/复盘的概念聚合口径完全一致
|
||||
|
||||
性能: 387 概念 × 30 天的 group_by + sort 是 polars 内存操作, 实测 <50ms;
|
||||
另加进程级结果缓存 (_CACHE_TTL=120s), 重复请求 <1ms。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import time
|
||||
from datetime import date, timedelta
|
||||
|
||||
import polars as pl
|
||||
|
||||
from app.services.market_overview_builder import (
|
||||
_dimension_field,
|
||||
_dimension_values,
|
||||
_read_ext_rows,
|
||||
_symbol_keys,
|
||||
)
|
||||
from app.services.ext_data import ExtConfigStore
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 进程级结果缓存 (照搬 overview.py:18 的模式, TTL 拉长到 120s —— 轮动矩阵
|
||||
# 不像看板那样需要近实时, 盘后数据稳定, 缓存久一点无妨)
|
||||
_CACHE_TTL = 120.0
|
||||
_cache: dict[str, dict] = {}
|
||||
_cache_ts: dict[str, float] = {}
|
||||
|
||||
|
||||
def invalidate_cache() -> None:
|
||||
"""清空轮动矩阵结果缓存(数据管道完成后调用, 避免返回旧数据)。"""
|
||||
_cache.clear()
|
||||
_cache_ts.clear()
|
||||
|
||||
|
||||
def _latest_enriched_date(repo) -> date | None:
|
||||
"""取 enriched 缓存里的最新交易日(矩阵的右端=最新日期)。"""
|
||||
cache = repo._enriched_history_cache # noqa: SLF001 —— 缓存字段无公开 getter
|
||||
if cache is None or cache.is_empty() or "date" not in cache.columns:
|
||||
return None
|
||||
return cache["date"].max()
|
||||
|
||||
|
||||
def _load_concept_map_df(repo) -> tuple[pl.DataFrame, int]:
|
||||
"""构建并缓存 {symbol_upper → 概念} 的已展开 polars 映射表。
|
||||
|
||||
复用 market_overview_builder 的概念识别 + 成分股读取逻辑(_dimension_field /
|
||||
_read_ext_rows / _symbol_keys / _dimension_values), 但要的是「反向映射」
|
||||
(symbol → 概念), 且直接产出 polars DataFrame 供 join 使用。
|
||||
|
||||
返回 (map_df, concept_count):
|
||||
- map_df: 两列 (_sym_up: 大写 symbol, concept: 概念名), 已 explode, 一个
|
||||
symbol 属多概念时有多行。无概念数据时返回空 DataFrame。
|
||||
- concept_count: 去重概念总数。
|
||||
|
||||
缓存: 概念成分股是 snapshot, 进程内不变, 缓存 600s。
|
||||
直接缓存 DataFrame 而非 Python dict —— 后续 join 时省掉每次 ~1s 的 dict→DataFrame
|
||||
重建开销(这是结果缓存失效后重算的主要瓶颈)。
|
||||
"""
|
||||
global _concept_map_cache, _concept_map_count, _concept_map_ts
|
||||
now = time.time()
|
||||
if _concept_map_cache is not None and (now - _concept_map_ts) < 600:
|
||||
return _concept_map_cache, _concept_map_count
|
||||
|
||||
data_dir = repo.store.data_dir
|
||||
store = ExtConfigStore(data_dir)
|
||||
# 先收集成扁平的 (sym, concept) 行, 再一次性构造 DataFrame(比 list 列快得多)
|
||||
pairs: list[tuple[str, str]] = []
|
||||
concepts_seen: set[str] = set()
|
||||
|
||||
for config in store.load_all():
|
||||
field = _dimension_field(config, "concept")
|
||||
if not field:
|
||||
continue
|
||||
for ext_row in _read_ext_rows(data_dir, config, field):
|
||||
concepts = _dimension_values(ext_row.get(field))
|
||||
if not concepts:
|
||||
continue
|
||||
keys = _symbol_keys(ext_row, config)
|
||||
for key in keys:
|
||||
for c in concepts:
|
||||
pairs.append((key, c))
|
||||
concepts_seen.add(c)
|
||||
|
||||
if pairs:
|
||||
# 去重: 同一 (symbol, concept) 对会因多 key 形式(SZ/000001)和
|
||||
# 多 config 重复出现, 去重后从 ~48万 行降到 ~14万, join 快 3x+
|
||||
_concept_map_cache = pl.DataFrame(
|
||||
{"_sym_up": [p[0] for p in pairs], "concept": [p[1] for p in pairs]},
|
||||
schema={"_sym_up": pl.Utf8, "concept": pl.Utf8},
|
||||
).unique()
|
||||
_concept_map_count = len(concepts_seen)
|
||||
else:
|
||||
_concept_map_cache = pl.DataFrame(
|
||||
schema={"_sym_up": pl.Utf8, "concept": pl.Utf8}
|
||||
)
|
||||
_concept_map_count = 0
|
||||
_concept_map_ts = now
|
||||
return _concept_map_cache, _concept_map_count
|
||||
|
||||
|
||||
_concept_map_cache: pl.DataFrame | None = None
|
||||
_concept_map_count: int = 0
|
||||
_concept_map_ts: float = 0.0
|
||||
|
||||
|
||||
def build_rps_rotation(repo, days: int = 12) -> dict:
|
||||
"""构建概念涨幅轮动矩阵。
|
||||
|
||||
Args:
|
||||
repo: KlineRepository(含 _enriched_history_cache 内存历史)。
|
||||
days: 取最近 N 个交易日, 范围 [7, 30], 默认 12。
|
||||
|
||||
Returns:
|
||||
{
|
||||
"dates": ["2026-06-30", ...], # 最新在最前, 长度 ≤ days
|
||||
"columns": {"2026-06-30": [[概念, 涨幅], ...], ...}, # 每列各自排序(高→低)
|
||||
"concept_count": 387, # 去重概念总数(0 表示无概念数据)
|
||||
}
|
||||
涨幅是小数(0.0522 = +5.22%)。无数据时返回空 columns。
|
||||
"""
|
||||
days = max(7, min(30, days))
|
||||
|
||||
# 结果缓存: 同 days(→ 同 start/end)的请求在 TTL 内直接返回
|
||||
latest = _latest_enriched_date(repo)
|
||||
if latest is None:
|
||||
return {"dates": [], "columns": {}, "concept_count": 0}
|
||||
|
||||
cache_key = latest.isoformat()
|
||||
now = time.time()
|
||||
cached = _cache.get(cache_key)
|
||||
if cached and (now - _cache_ts.get(cache_key, 0)) < _CACHE_TTL:
|
||||
# 缓存的是所有日期, 按需要的 days 截取(避免不同 days 各存一份)
|
||||
return _slice_cached(cached, days)
|
||||
|
||||
# 1. 概念映射(symbol → 概念), 已缓存为 polars DataFrame
|
||||
map_df, concept_count = _load_concept_map_df(repo)
|
||||
if map_df.is_empty():
|
||||
logger.info("rps_rotation: no concept data (ext_gn_ths not fetched yet)")
|
||||
return {"dates": [], "columns": {}, "concept_count": 0}
|
||||
|
||||
# 2. 取最近 N 交易日的个股 change_pct(命中内存缓存)
|
||||
start = latest - timedelta(days=days * 2 + 10) # 日历天 ≈ 2/3 交易日, 多取余量
|
||||
df = repo.get_enriched_range(
|
||||
start, latest, columns=["symbol", "date", "change_pct"]
|
||||
)
|
||||
if df is None or df.is_empty():
|
||||
return {"dates": [], "columns": {}, "concept_count": 0}
|
||||
|
||||
# 3. 把个股 symbol 映射到概念, 一只股票拆成多行(每个概念一行)
|
||||
# symbol 大写匹配(map_df 的 _sym_up 已大写)
|
||||
df = df.with_columns(pl.col("symbol").str.to_uppercase().alias("_sym_up"))
|
||||
joined = df.join(map_df, on="_sym_up", how="inner").drop("_sym_up")
|
||||
|
||||
if joined.is_empty():
|
||||
return {"dates": [], "columns": {}, "concept_count": 0}
|
||||
|
||||
# 4. 按 (date, concept) 聚合 avg change_pct —— 与 _dimension_rank:288 的简单平均口径一致
|
||||
agg = joined.group_by(["date", "concept"]).agg(
|
||||
pl.col("change_pct").mean().alias("avg_pct")
|
||||
)
|
||||
# 去掉 NaN/Null(停牌等无行情的概念日)
|
||||
agg = agg.filter(pl.col("avg_pct").is_not_null() & pl.col("avg_pct").is_not_nan())
|
||||
|
||||
# 5. 每个日期内按 avg_pct 降序排, 再 group_by 把每组的 (concept, avg_pct)
|
||||
# 收集成并行 list —— 一次 polars 操作拿到全部列, 避免 partition_by 的 tuple key 歧义
|
||||
agg = agg.sort(["date", "avg_pct"], descending=[False, True])
|
||||
grouped = agg.group_by("date", maintain_order=True).agg(
|
||||
pl.col("concept"), pl.col("avg_pct")
|
||||
)
|
||||
# 最新日期排最前
|
||||
grouped = grouped.sort("date", descending=True)
|
||||
|
||||
columns: dict[str, list[list]] = {}
|
||||
all_dates_sorted: list[str] = []
|
||||
for row in grouped.iter_rows(named=True):
|
||||
d_str = str(row["date"])
|
||||
all_dates_sorted.append(d_str)
|
||||
columns[d_str] = list(zip(row["concept"], row["avg_pct"]))
|
||||
|
||||
full = {
|
||||
"dates": [str(d) for d in all_dates_sorted],
|
||||
"columns": columns,
|
||||
"concept_count": concept_count,
|
||||
}
|
||||
|
||||
# 写缓存(存全量, 按需 slice)
|
||||
_cache[cache_key] = full
|
||||
_cache_ts[cache_key] = now
|
||||
|
||||
return _slice_cached(full, days)
|
||||
|
||||
|
||||
def _slice_cached(full: dict, days: int) -> dict:
|
||||
"""从全量缓存截取最近 N 天(days)。"""
|
||||
dates_all = full["dates"]
|
||||
if len(dates_all) <= days:
|
||||
return full
|
||||
keep_dates = dates_all[:days]
|
||||
return {
|
||||
"dates": keep_dates,
|
||||
"columns": {d: full["columns"][d] for d in keep_dates},
|
||||
"concept_count": full["concept_count"],
|
||||
}
|
||||
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Reference in New Issue
Block a user