From 4393bf68cd21fab03549df458f345f10aadb0386 Mon Sep 17 00:00:00 2001 From: Cassianvale Date: Wed, 5 Mar 2025 17:45:09 +0800 Subject: [PATCH 01/17] =?UTF-8?q?feat:=20=20vue=E9=87=8D=E6=9E=84?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .gitignore | 17 + frontend/README.md | 5 + frontend/index.html | 14 + frontend/package-lock.json | 1256 +++++++++++++++++ frontend/package.json | 28 + frontend/public/vite.svg | 1 + frontend/src/App.vue | 41 + frontend/src/assets/vue.svg | 1 + .../src/components/AnnouncementBanner.vue | 128 ++ frontend/src/components/ApiConfigPanel.vue | 339 +++++ frontend/src/components/MarketTimeDisplay.vue | 133 ++ frontend/src/components/StockAnalysisApp.vue | 489 +++++++ frontend/src/components/StockCard.vue | 207 +++ frontend/src/components/StockSearch.vue | 220 +++ frontend/src/main.ts | 6 + frontend/src/services/api.ts | 59 + frontend/src/style.css | 79 ++ frontend/src/types/index.ts | 80 ++ frontend/src/utils/index.ts | 201 +++ frontend/src/vite-env.d.ts | 1 + frontend/tsconfig.app.json | 18 + frontend/tsconfig.json | 7 + frontend/tsconfig.node.json | 25 + frontend/vite.config.ts | 43 + frontend/yarn.lock | 731 ++++++++++ stock_analyzer.py | 2 +- web_server.py | 48 +- 27 files changed, 4164 insertions(+), 15 deletions(-) create mode 100644 frontend/README.md create mode 100644 frontend/index.html create mode 100644 frontend/package-lock.json create mode 100644 frontend/package.json create mode 100644 frontend/public/vite.svg create mode 100644 frontend/src/App.vue create mode 100644 frontend/src/assets/vue.svg create mode 100644 frontend/src/components/AnnouncementBanner.vue create mode 100644 frontend/src/components/ApiConfigPanel.vue create mode 100644 frontend/src/components/MarketTimeDisplay.vue create mode 100644 frontend/src/components/StockAnalysisApp.vue create mode 100644 frontend/src/components/StockCard.vue create mode 100644 frontend/src/components/StockSearch.vue create mode 100644 frontend/src/main.ts create mode 100644 frontend/src/services/api.ts create mode 100644 frontend/src/style.css create mode 100644 frontend/src/types/index.ts create mode 100644 frontend/src/utils/index.ts create mode 100644 frontend/src/vite-env.d.ts create mode 100644 frontend/tsconfig.app.json create mode 100644 frontend/tsconfig.json create mode 100644 frontend/tsconfig.node.json create mode 100644 frontend/vite.config.ts create mode 100644 frontend/yarn.lock diff --git a/.gitignore b/.gitignore index db3d017..9759f13 100644 --- a/.gitignore +++ b/.gitignore @@ -21,6 +21,23 @@ build_upload.log *.spec *.zip +# frontend +node_modules/ +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* +lerna-debug.log* +dist/ +dist-ssr +*.local +.DS_Store +*.suo +*.ntvs* +*.njsproj +*.sln +*.sw? + # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] diff --git a/frontend/README.md b/frontend/README.md new file mode 100644 index 0000000..33895ab --- /dev/null +++ b/frontend/README.md @@ -0,0 +1,5 @@ +# Vue 3 + TypeScript + Vite + +This template should help get you started developing with Vue 3 and TypeScript in Vite. The template uses Vue 3 ` + + \ No newline at end of file diff --git a/frontend/package-lock.json b/frontend/package-lock.json new file mode 100644 index 0000000..96ad038 --- /dev/null +++ b/frontend/package-lock.json @@ -0,0 +1,1256 @@ +{ + "name": "frontend", + "version": "0.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "frontend", + "version": "0.0.0", + "dependencies": { + "@types/node": "^22.13.9", + "@vicons/ionicons5": "^0.13.0", + "@vueuse/core": "^12.7.0", + "axios": "^1.8.1", + "marked": "^15.0.7", + "naive-ui": "^2.41.0", + "vue": "^3.5.13" + }, + "devDependencies": { + "@types/marked": "^5.0.2", + "@vitejs/plugin-vue": "^5.2.1", + "@vue/tsconfig": "^0.7.0", + "typescript": "~5.7.2", + "vite": "^6.2.0", + "vue-tsc": "^2.2.4" + } + }, + "node_modules/@babel/helper-string-parser": { + "version": "7.25.9", + "resolved": "https://registry.npmmirror.com/@babel/helper-string-parser/-/helper-string-parser-7.25.9.tgz", + "integrity": 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--- /dev/null +++ b/frontend/public/vite.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/frontend/src/App.vue b/frontend/src/App.vue new file mode 100644 index 0000000..84095a0 --- /dev/null +++ b/frontend/src/App.vue @@ -0,0 +1,41 @@ + + + + + diff --git a/frontend/src/assets/vue.svg b/frontend/src/assets/vue.svg new file mode 100644 index 0000000..770e9d3 --- /dev/null +++ b/frontend/src/assets/vue.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/frontend/src/components/AnnouncementBanner.vue b/frontend/src/components/AnnouncementBanner.vue new file mode 100644 index 0000000..ab872cb --- /dev/null +++ b/frontend/src/components/AnnouncementBanner.vue @@ -0,0 +1,128 @@ + + + + + diff --git a/frontend/src/components/ApiConfigPanel.vue b/frontend/src/components/ApiConfigPanel.vue new file mode 100644 index 0000000..f840b70 --- /dev/null +++ b/frontend/src/components/ApiConfigPanel.vue @@ -0,0 +1,339 @@ + + + + + diff --git a/frontend/src/components/MarketTimeDisplay.vue b/frontend/src/components/MarketTimeDisplay.vue new file mode 100644 index 0000000..2b9e48a --- /dev/null +++ b/frontend/src/components/MarketTimeDisplay.vue @@ -0,0 +1,133 @@ + + + + + diff --git a/frontend/src/components/StockAnalysisApp.vue b/frontend/src/components/StockAnalysisApp.vue new file mode 100644 index 0000000..a6ac6bb --- /dev/null +++ b/frontend/src/components/StockAnalysisApp.vue @@ -0,0 +1,489 @@ + + + + + diff --git a/frontend/src/components/StockCard.vue b/frontend/src/components/StockCard.vue new file mode 100644 index 0000000..211a512 --- /dev/null +++ b/frontend/src/components/StockCard.vue @@ -0,0 +1,207 @@ + + + + + diff --git a/frontend/src/components/StockSearch.vue b/frontend/src/components/StockSearch.vue new file mode 100644 index 0000000..ed7eed7 --- /dev/null +++ b/frontend/src/components/StockSearch.vue @@ -0,0 +1,220 @@ + + + + + diff --git a/frontend/src/main.ts b/frontend/src/main.ts new file mode 100644 index 0000000..e03fc18 --- /dev/null +++ b/frontend/src/main.ts @@ -0,0 +1,6 @@ +import { createApp } from 'vue' +import './style.css' +import App from './App.vue' + +const app = createApp(App) +app.mount('#app') diff --git a/frontend/src/services/api.ts b/frontend/src/services/api.ts new file mode 100644 index 0000000..6c38f9a --- /dev/null +++ b/frontend/src/services/api.ts @@ -0,0 +1,59 @@ +import axios from 'axios'; +import type { AnalyzeRequest, TestApiRequest, TestApiResponse, SearchResult } from '@/types'; + +// 在开发环境中前缀为空，因为已经在vite.config.ts中配置了代理 +const API_PREFIX = ''; + +export const apiService = { + // 分析股票 + analyzeStocks: async (request: AnalyzeRequest) => { + return axios.post(`${API_PREFIX}/analyze`, request, { + responseType: 'stream' + }); + }, + + // 测试API连接 + testApiConnection: async (request: TestApiRequest): Promise => { + try { + const response = await axios.post(`${API_PREFIX}/test_api_connection`, request); + return response.data; + } catch (error: any) { + if (error.response) { + return error.response.data; + } + return { + success: false, + message: error.message || '连接失败' + }; + } + }, + + // 搜索美股 + searchUsStocks: async (keyword: string): Promise => { + try { + const response = await axios.get(`${API_PREFIX}/search_us_stocks`, { + params: { keyword } + }); + return response.data.results || []; + } catch (error) { + console.error('搜索美股时出错:', error); + return []; + } + }, + + // 获取配置 + getConfig: async () => { + try { + const response = await axios.get(`${API_PREFIX}/config`); + return response.data; + } catch (error) { + console.error('获取配置时出错:', error); + return { + announcement: '', + default_api_url: '', + default_api_model: 'gpt-3.5-turbo', + default_api_timeout: '60' + }; + } + } +}; diff --git a/frontend/src/style.css b/frontend/src/style.css new file mode 100644 index 0000000..f691315 --- /dev/null +++ b/frontend/src/style.css @@ -0,0 +1,79 @@ +:root { + font-family: system-ui, Avenir, Helvetica, Arial, sans-serif; + line-height: 1.5; + font-weight: 400; + + color-scheme: light dark; + color: rgba(255, 255, 255, 0.87); + background-color: #242424; + + font-synthesis: none; + text-rendering: optimizeLegibility; + -webkit-font-smoothing: antialiased; + -moz-osx-font-smoothing: grayscale; +} + +a { + font-weight: 500; + color: #646cff; + text-decoration: inherit; +} +a:hover { + color: #535bf2; +} + +body { + margin: 0; + display: flex; + place-items: center; + min-width: 320px; + min-height: 100vh; +} + +h1 { + font-size: 3.2em; + line-height: 1.1; +} + +button { + border-radius: 8px; + border: 1px solid transparent; + padding: 0.6em 1.2em; + font-size: 1em; + font-weight: 500; + font-family: inherit; + background-color: #1a1a1a; + cursor: pointer; + transition: border-color 0.25s; +} +button:hover { + border-color: #646cff; +} +button:focus, +button:focus-visible { + outline: 4px auto -webkit-focus-ring-color; +} + +.card { + padding: 2em; +} + +#app { + max-width: 1280px; + margin: 0 auto; + padding: 2rem; + text-align: center; +} + +@media (prefers-color-scheme: light) { + :root { + color: #213547; + background-color: #ffffff; + } + a:hover { + color: #747bff; + } + button { + background-color: #f9f9f9; + } +} diff --git a/frontend/src/types/index.ts b/frontend/src/types/index.ts new file mode 100644 index 0000000..10d1e83 --- /dev/null +++ b/frontend/src/types/index.ts @@ -0,0 +1,80 @@ +// API接口相关类型 +export interface ApiConfig { + apiUrl: string; + apiKey: string; + apiModel: string; + apiTimeout: string; + saveApiConfig: boolean; +} + +export interface StockInfo { + code: string; + name: string; + marketType: string; + price?: number; + changePercent?: number; + marketValue?: number; + analysis?: string; + analysisStatus: 'waiting' | 'analyzing' | 'completed' | 'error'; + error?: string; +} + +export interface SearchResult { + symbol: string; + name: string; + market: string; + marketValue?: number; +} + +export interface MarketStatus { + isOpen: boolean; + nextTime: string; +} + +export interface MarketTimeInfo { + currentTime: string; + cnMarket: MarketStatus; + hkMarket: MarketStatus; + usMarket: MarketStatus; +} + +// 分析请求和响应 +export interface AnalyzeRequest { + stock_codes: string[]; + market_type: string; + api_url?: string; + api_key?: string; + api_model?: string; + api_timeout?: string; +} + +export interface TestApiRequest { + api_url: string; + api_key: string; + api_model: string; + api_timeout: string; +} + +export interface TestApiResponse { + success: boolean; + message: string; + status_code?: number; +} + +// 流式响应类型 +export interface StreamInitMessage { + stream_type: 'single' | 'batch'; + stock_code?: string; + stock_codes?: string[]; +} + +export interface StreamAnalysisUpdate { + stock_code: string; + analysis?: string; + status: 'analyzing' | 'completed' | 'error'; + error?: string; + name?: string; + price?: number; + change_percent?: number; + market_value?: number; +} diff --git a/frontend/src/utils/index.ts b/frontend/src/utils/index.ts new file mode 100644 index 0000000..9877d89 --- /dev/null +++ b/frontend/src/utils/index.ts @@ -0,0 +1,201 @@ +import type { MarketTimeInfo } from '@/types'; +import { marked } from 'marked'; + +// 防抖函数 +export function debounce any>( + func: T, + wait: number +): (...args: Parameters) => void { + let timeout: number | null = null; + + return function(...args: Parameters): void { + const later = () => { + timeout = null; + func(...args); + }; + + if (timeout !== null) { + clearTimeout(timeout); + } + timeout = window.setTimeout(later, wait); + }; +} + +// 格式化市值 +export function formatMarketValue(value: number): string { + if (!value) return '未知'; + + if (value >= 1000000000000) { + return (value / 1000000000000).toFixed(2) + '万亿'; + } else if (value >= 100000000) { + return (value / 100000000).toFixed(2) + '亿'; + } else if (value >= 10000) { + return (value / 10000).toFixed(2) + '万'; + } else { + return value.toFixed(2); + } +} + +// 解析Markdown +export function parseMarkdown(text: string): string { + try { + const result = marked(text); + if (typeof result === 'string') { + return result; + } + return ''; + } catch (e) { + console.error('解析Markdown出错:', e); + return text; + } +} + +// 更新市场时间信息 +export function updateMarketTimeInfo(): MarketTimeInfo { + const now = new Date(); + + // 当前时间 + const currentTime = now.toLocaleTimeString('zh-CN', { hour12: false }); + + // 中国时间 + const cnOptions = { timeZone: 'Asia/Shanghai', hour12: false } as Intl.DateTimeFormatOptions; + const cnTime = now.toLocaleString('zh-CN', cnOptions); + const cnHour = new Date(cnTime).getHours(); + const cnMinute = new Date(cnTime).getMinutes(); + + // A股市场状态 + const cnMarketOpen = (cnHour === 9 && cnMinute >= 30) || (cnHour === 10) || + (cnHour === 11 && cnMinute <= 30) || + (cnHour >= 13 && cnHour < 15); + + const cnNextTime = getNextTimeText(cnMarketOpen, cnHour, cnMinute, 9, 30, 15, 0); + + // 港股市场状态（与A股相同时区） + const hkMarketOpen = (cnHour === 9 && cnMinute >= 30) || + (cnHour === 10) || (cnHour === 11) || + (cnHour >= 13 && cnHour < 16); + + const hkNextTime = getNextTimeText(hkMarketOpen, cnHour, cnMinute, 9, 30, 16, 0); + + // 获取美国东部时间 + const usOptions = { timeZone: 'America/New_York', hour12: false } as Intl.DateTimeFormatOptions; + const usTime = now.toLocaleString('zh-CN', usOptions); + const usHour = new Date(usTime).getHours(); + const usMinute = new Date(usTime).getMinutes(); + + // 美股市场状态 + const usMarketOpen = (usHour >= 9 && usHour < 16) || + (usHour === 16 && usMinute === 0); + + const usNextTime = getNextTimeText(usMarketOpen, usHour, usMinute, 9, 30, 16, 0); + + return { + currentTime, + cnMarket: { isOpen: cnMarketOpen, nextTime: cnNextTime }, + hkMarket: { isOpen: hkMarketOpen, nextTime: hkNextTime }, + usMarket: { isOpen: usMarketOpen, nextTime: usNextTime } + }; +} + +// 辅助函数：获取距离下一次开/闭市的时间文本 +function getNextTimeText( + isOpen: boolean, + currentHour: number, + currentMinute: number, + openHour: number, + openMinute: number, + closeHour: number, + closeMinute: number +): string { + if (isOpen) { + // 计算距离收盘时间 + let timeToCloseMinutes = (closeHour - currentHour) * 60 + (closeMinute - currentMinute); + + if (timeToCloseMinutes <= 0) { + return '即将收盘'; + } + + const hours = Math.floor(timeToCloseMinutes / 60); + const minutes = timeToCloseMinutes % 60; + + return `距离收盘还有 ${hours}小时${minutes}分钟`; + } else { + // 计算距离开盘时间 + let nextOpenHour = openHour; + let nextOpenMinute = openMinute; + let isNextDay = false; + + if (currentHour >= closeHour) { + // 已经过了今天的收盘时间，下一个开盘是明天 + isNextDay = true; + } else if (currentHour < openHour || (currentHour === openHour && currentMinute < openMinute)) { + // 还没到今天的开盘时间 + isNextDay = false; + } else { + // 当前处于盘中休息时间，下一个开盘时间是当天下午 + nextOpenHour = 13; + nextOpenMinute = 0; + } + + let timeToOpenMinutes; + + if (isNextDay) { + timeToOpenMinutes = (24 - currentHour + nextOpenHour) * 60 + (nextOpenMinute - currentMinute); + } else { + timeToOpenMinutes = (nextOpenHour - currentHour) * 60 + (nextOpenMinute - currentMinute); + } + + if (timeToOpenMinutes <= 0) { + return '即将开盘'; + } + + const hours = Math.floor(timeToOpenMinutes / 60); + const minutes = timeToOpenMinutes % 60; + + return `距离开盘还有 ${hours}小时${minutes}分钟`; + } +} + +// 保存API配置到localStorage +export function saveApiConfigToLocalStorage(config: Partial>): void { + if (window.localStorage) { + localStorage.setItem('apiConfig', JSON.stringify(config)); + } +} + +// 从localStorage加载API配置 +export function loadApiConfig(): Partial<{ + apiUrl: string, + apiKey: string, + apiModel: string, + apiTimeout: string, + saveApiConfig: boolean +}> { + if (window.localStorage) { + const saved = localStorage.getItem('apiConfig'); + if (saved) { + try { + return JSON.parse(saved); + } catch (e) { + console.error('解析保存的API配置出错:', e); + } + } + } + return { + apiUrl: '', + apiKey: '', + apiModel: '', + apiTimeout: '', + saveApiConfig: false + }; +} + +// 清除API配置 +export function clearApiConfig(): void { + if (window.localStorage) { + localStorage.removeItem('apiConfig'); + } +} diff --git a/frontend/src/vite-env.d.ts b/frontend/src/vite-env.d.ts new file mode 100644 index 0000000..11f02fe --- /dev/null +++ b/frontend/src/vite-env.d.ts @@ -0,0 +1 @@ +/// diff --git a/frontend/tsconfig.app.json b/frontend/tsconfig.app.json new file mode 100644 index 0000000..c86af31 --- /dev/null +++ b/frontend/tsconfig.app.json @@ -0,0 +1,18 @@ +{ + "extends": "@vue/tsconfig/tsconfig.dom.json", + "compilerOptions": { + "incremental": true, // 启用增量编译 + "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo", + /* Linting */ + "strict": true, + "noUnusedLocals": true, + "noUnusedParameters": true, + "noFallthroughCasesInSwitch": true, + "noUncheckedSideEffectImports": true, + "baseUrl": ".", + "paths": { + "@/*": ["src/*"] + } + }, + "include": ["src/**/*.ts", "src/**/*.tsx", "src/**/*.vue"] +} diff --git a/frontend/tsconfig.json b/frontend/tsconfig.json new file mode 100644 index 0000000..1ffef60 --- /dev/null +++ b/frontend/tsconfig.json @@ -0,0 +1,7 @@ +{ + "files": [], + "references": [ + { "path": "./tsconfig.app.json" }, + { "path": "./tsconfig.node.json" } + ] +} diff --git a/frontend/tsconfig.node.json b/frontend/tsconfig.node.json new file mode 100644 index 0000000..69fc25c --- /dev/null +++ b/frontend/tsconfig.node.json @@ -0,0 +1,25 @@ +{ + "compilerOptions": { + "incremental": true, // 启用增量编译 + "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo", + "target": "ES2022", + "lib": ["ES2023"], + "module": "ESNext", + "skipLibCheck": true, + + /* Bundler mode */ + "moduleResolution": "bundler", + "allowImportingTsExtensions": true, + "isolatedModules": true, + "moduleDetection": "force", + "noEmit": true, + + /* Linting */ + "strict": true, + "noUnusedLocals": true, + "noUnusedParameters": true, + "noFallthroughCasesInSwitch": true, + "noUncheckedSideEffectImports": true + }, + "include": ["vite.config.ts"] +} diff --git a/frontend/vite.config.ts b/frontend/vite.config.ts new file mode 100644 index 0000000..181d624 --- /dev/null +++ b/frontend/vite.config.ts @@ -0,0 +1,43 @@ +import { defineConfig } from 'vite' +import vue from '@vitejs/plugin-vue' +import { fileURLToPath } from 'url' +import { dirname, resolve } from 'path' + +// 获取当前文件的目录路径（在ESM中替代__dirname） +const __filename = fileURLToPath(import.meta.url) +const __dirname = dirname(__filename) + +// https://vitejs.dev/config/ +export default defineConfig({ + plugins: [vue()], + resolve: { + alias: { + '@': resolve(__dirname, 'src'), + }, + }, + server: { + proxy: { + '/api': { + target: 'http://127.0.0.1:8888', + changeOrigin: true, + rewrite: (path) => path.replace(/^\/api/, ''), + }, + '/analyze': { + target: 'http://127.0.0.1:8888', + changeOrigin: true, + }, + '/test_api_connection': { + target: 'http://127.0.0.1:8888', + changeOrigin: true, + }, + '/search_us_stocks': { + target: 'http://127.0.0.1:8888', + changeOrigin: true, + }, + '/config': { + target: 'http://127.0.0.1:8888', + changeOrigin: true, + }, + }, + }, +}) diff --git a/frontend/yarn.lock b/frontend/yarn.lock new file mode 100644 index 0000000..81a0230 --- /dev/null +++ b/frontend/yarn.lock @@ -0,0 +1,731 @@ +# THIS IS AN AUTOGENERATED FILE. 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def _process_ai_stream(self, response, stock_code) -> Generator[str, None, None]: """处理AI流式响应""" - logger.info(f"开始处理 {stock_code} 的AI流式响应") + logger.info(f"开始处理股票 {stock_code} 的AI流式响应\n") buffer = "" chunk_count = 0 diff --git a/web_server.py b/web_server.py index 2e13be7..a14ef1d 100644 --- a/web_server.py +++ b/web_server.py @@ -1,4 +1,4 @@ -from flask import Flask, render_template, request, jsonify, Response, stream_with_context +from flask import Flask, render_template, request, jsonify, Response, stream_with_context, send_from_directory from stock_analyzer import StockAnalyzer from us_stock_service import USStockService from fund_service import FundService # 新增导入 @@ -16,24 +16,44 @@ load_dotenv() # 获取日志器 logger = get_logger() -app = Flask(__name__) +app = Flask(__name__, + static_folder='frontend/dist', + static_url_path='/') + analyzer = StockAnalyzer() us_stock_service = USStockService() fund_service = FundService() # 新增服务实例 @app.route('/') def index(): - announcement = os.getenv('ANNOUNCEMENT_TEXT') or None - # 获取默认API配置信息 - default_api_url = os.getenv('API_URL', '') - default_api_model = os.getenv('API_MODEL', 'gpt-3.5-turbo') - default_api_timeout = os.getenv('API_TIMEOUT', '60') - # 不传递API_KEY到前端，出于安全考虑 - return render_template('index.html', - announcement=announcement, - default_api_url=default_api_url, - default_api_model=default_api_model, - default_api_timeout=default_api_timeout) + # 检查是否使用前端构建版本 + frontend_dist = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'frontend', 'dist') + if os.path.exists(frontend_dist): + return send_from_directory(frontend_dist, 'index.html') + else: + # 传统模板渲染，用于兼容旧版本 + announcement = os.getenv('ANNOUNCEMENT_TEXT') or None + # 获取默认API配置信息 + default_api_url = os.getenv('API_URL', '') + default_api_model = os.getenv('API_MODEL', 'gpt-3.5-turbo') + default_api_timeout = os.getenv('API_TIMEOUT', '60') + # 不传递API_KEY到前端，出于安全考虑 + return render_template('index.html', + announcement=announcement, + default_api_url=default_api_url, + default_api_model=default_api_model, + default_api_timeout=default_api_timeout) + +@app.route('/config') +def get_config(): + """返回系统配置信息""" + config = { + 'announcement': os.getenv('ANNOUNCEMENT_TEXT') or '', + 'default_api_url': os.getenv('API_URL', ''), + 'default_api_model': os.getenv('API_MODEL', 'gpt-3.5-turbo'), + 'default_api_timeout': os.getenv('API_TIMEOUT', '60') + } + return jsonify(config) @app.route('/analyze', methods=['POST']) def analyze(): @@ -200,4 +220,4 @@ def test_api_connection(): if __name__ == '__main__': logger.info("股票分析系统启动") - app.run(host='0.0.0.0', port=8888, debug=True) \ No newline at end of file + app.run(host='127.0.0.1', port=8888, debug=True) \ No newline at end of file From 8781eebdfa27e5662e59f578cdda4a8320493cc9 Mon Sep 17 00:00:00 2001 From: Cassianvale Date: Thu, 6 Mar 2025 14:46:59 +0800 Subject: [PATCH 02/17] =?UTF-8?q?feat:=20=E4=BC=98=E5=8C=96=E5=8D=A1?= =?UTF-8?q?=E7=89=87=E5=86=85=E5=AE=B9=E6=98=BE=E7=A4=BA?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- frontend/src/components/StockAnalysisApp.vue | 141 ++++- frontend/src/components/StockCard.vue | 598 +++++++++++++++++-- frontend/src/types/index.ts | 17 + frontend/yarn.lock | 233 +++++++- stock_analyzer.py | 3 +- 5 files changed, 939 insertions(+), 53 deletions(-) diff --git a/frontend/src/components/StockAnalysisApp.vue b/frontend/src/components/StockAnalysisApp.vue index a6ac6bb..385523b 100644 --- a/frontend/src/components/StockAnalysisApp.vue +++ b/frontend/src/components/StockAnalysisApp.vue @@ -227,22 +227,37 @@ function handleStreamInit(data: StreamInitMessage) { // 处理流式更新消息 function handleStreamUpdate(data: StreamAnalysisUpdate) { - const stockIndex = analyzedStocks.value.findIndex(s => s.code === data.stock_code); + const stockIndex = analyzedStocks.value.findIndex((s: StockInfo) => s.code === data.stock_code); if (stockIndex >= 0) { const stock = { ...analyzedStocks.value[stockIndex] }; // 更新分析状态 - stock.analysisStatus = data.status; + if (data.status) { + stock.analysisStatus = data.status; + } // 如果有分析结果，则更新 if (data.analysis !== undefined) { stock.analysis = data.analysis; } + // 处理AI分析片段 + if (data.ai_analysis_chunk !== undefined) { + // 如果之前没有分析内容，则初始化 + if (!stock.analysis) { + stock.analysis = ''; + } + // 追加新的分析片段 + stock.analysis += data.ai_analysis_chunk; + // 确保分析状态为正在分析 + stock.analysisStatus = 'analyzing'; + } + // 如果有错误，则更新 if (data.error !== undefined) { stock.error = data.error; + stock.analysisStatus = 'error'; } // 更新股票名称、价格等信息 @@ -262,6 +277,41 @@ function handleStreamUpdate(data: StreamAnalysisUpdate) { stock.marketValue = data.market_value; } + // 添加新字段的处理 + if (data.score !== undefined) { + stock.score = data.score; + } + + if (data.recommendation !== undefined) { + stock.recommendation = data.recommendation; + } + + if (data.price_change !== undefined) { + stock.price_change = data.price_change; + } + + if (data.rsi !== undefined) { + stock.rsi = data.rsi; + } + + // 添加技术指标字段的处理 + if (data.ma_trend !== undefined) { + stock.ma_trend = data.ma_trend; + } + + if (data.macd_signal !== undefined) { + stock.macd_signal = data.macd_signal; + } + + if (data.volume_status !== undefined) { + stock.volume_status = data.volume_status; + } + + // 添加分析日期字段的处理 + if (data.analysis_date !== undefined) { + stock.analysis_date = data.analysis_date; + } + // 更新数组中的股票信息 analyzedStocks.value[stockIndex] = stock; } @@ -280,8 +330,8 @@ async function analyzeStocks() { // 解析股票代码 const codes = stockCodes.value .split(/[,\s\n]+/) - .map(code => code.trim()) - .filter(code => code); + .map((code: string) => code.trim()) + .filter((code: string) => code); if (codes.length === 0) { message.warning('未找到有效的股票代码'); @@ -362,6 +412,14 @@ async function analyzeStocks() { processStreamData(buffer); } + // 将所有分析中的股票状态更新为已完成 + analyzedStocks.value.forEach((stock, index) => { + if (stock.analysisStatus === 'analyzing') { + const updatedStock = { ...stock, analysisStatus: 'completed' }; + analyzedStocks.value[index] = updatedStock; + } + }); + message.success('分析完成'); } catch (error: any) { message.error(`分析出错: ${error.message || '未知错误'}`); @@ -381,9 +439,78 @@ async function copyAnalysisResults() { try { // 格式化分析结果 const formattedResults = analyzedStocks.value - .filter(stock => stock.analysisStatus === 'completed') - .map(stock => { - return `【${stock.code} ${stock.name || ''}】\n${stock.analysis || '无分析结果'}\n`; + .filter((stock: StockInfo) => stock.analysisStatus === 'completed') + .map((stock: StockInfo) => { + let result = `【${stock.code} ${stock.name || ''}】\n`; + + // 添加分析日期 + if (stock.analysis_date) { + try { + const date = new Date(stock.analysis_date); + if (!isNaN(date.getTime())) { + result += `分析日期: ${date.toISOString().split('T')[0]}\n`; + } else { + result += `分析日期: ${stock.analysis_date}\n`; + } + } catch (e) { + result += `分析日期: ${stock.analysis_date}\n`; + } + } + + // 添加评分和推荐信息 + if (stock.score !== undefined) { + result += `评分: ${stock.score}\n`; + } + + if (stock.recommendation) { + result += `推荐: ${stock.recommendation}\n`; + } + + // 添加技术指标信息 + if (stock.rsi !== undefined) { + result += `RSI: ${stock.rsi.toFixed(2)}\n`; + } + + if (stock.price_change !== undefined) { + const sign = stock.price_change > 0 ? '+' : ''; + result += `价格变动: ${sign}${stock.price_change.toFixed(2)}\n`; + } + + if (stock.ma_trend) { + const trendMap: Record = { + 'UP': '上升', + 'DOWN': '下降', + 'NEUTRAL': '平稳' + }; + const trend = trendMap[stock.ma_trend] || stock.ma_trend; + result += `均线趋势: ${trend}\n`; + } + + if (stock.macd_signal) { + const signalMap: Record = { + 'BUY': '买入', + 'SELL': '卖出', + 'HOLD': '持有', + 'NEUTRAL': '中性' + }; + const signal = signalMap[stock.macd_signal] || stock.macd_signal; + result += `MACD信号: ${signal}\n`; + } + + if (stock.volume_status) { + const statusMap: Record = { + 'HIGH': '放量', + 'LOW': '缩量', + 'NORMAL': '正常' + }; + const status = statusMap[stock.volume_status] || stock.volume_status; + result += `成交量: ${status}\n`; + } + + // 添加分析结果 + result += `\n${stock.analysis || '无分析结果'}\n`; + + return result; }) .join('\n'); diff --git a/frontend/src/components/StockCard.vue b/frontend/src/components/StockCard.vue index 211a512..52673b7 100644 --- a/frontend/src/components/StockCard.vue +++ b/frontend/src/components/StockCard.vue @@ -3,15 +3,74 @@
{{ stock.code }}
-
{{ stock.name || '加载中...' }}
-
{{ stock.price.toFixed(2) }}
+
当前价格: {{ stock.price.toFixed(2) }}
- {{ formatChangePercent(stock.changePercent) }} + 涨跌幅: {{ formatChangePercent(calculatedChangePercent) }} +
+
+
+ +
+
+
{{ stock.score }}
+
评分
+
+
+
{{ stock.recommendation }}
+
推荐
+
+
+ +
+ + + 分析日期: {{ formatDate(stock.analysis_date) }} + +
+ +
+ 技术指标 + +
+
+
{{ stock.rsi.toFixed(2) }}
+
RSI
+
+ +
+
{{ formatPriceChange(stock.price_change) }}
+
价格变动
+
+ +
+
+ {{ getChineseTrend(stock.ma_trend) }} +
+
均线趋势
+
+ +
+
+ {{ getChineseSignal(stock.macd_signal) }} +
+
MACD信号
+
+ +
+
+ {{ getChineseVolumeStatus(stock.volume_status) }} +
+
成交量
@@ -31,6 +90,7 @@ 正在分析... +
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"https://registry.npmmirror.com/@rollup/rollup-win32-x64-msvc/-/rollup-win32-x64-msvc-4.34.9.tgz" @@ -89,7 +299,7 @@ resolved "https://registry.npmmirror.com/@types/marked/-/marked-5.0.2.tgz" integrity sha512-OucS4KMHhFzhz27KxmWg7J+kIYqyqoW5kdIEI319hqARQQUTqhao3M/F+uFnDXD0Rg72iDDZxZNxq5gvctmLlg== -"@types/node@^18.0.0 || ^20.0.0 || >=22.0.0", "@types/node@^22.13.9": +"@types/node@^22.13.9": version "22.13.9" resolved "https://registry.npmmirror.com/@types/node/-/node-22.13.9.tgz" integrity sha512-acBjXdRJ3A6Pb3tqnw9HZmyR3Fiol3aGxRCK1x3d+6CDAMjl7I649wpSd+yNURCjbOUGu9tqtLKnTGxmK6CyGw== @@ -111,7 +321,7 @@ resolved "https://registry.npmmirror.com/@vitejs/plugin-vue/-/plugin-vue-5.2.1.tgz" integrity sha512-cxh314tzaWwOLqVes2gnnCtvBDcM1UMdn+iFR+UjAn411dPT3tOmqrJjbMd7koZpMAmBM/GqeV4n9ge7JSiJJQ== -"@volar/language-core@~2.4.11", "@volar/language-core@2.4.11": +"@volar/language-core@2.4.11", "@volar/language-core@~2.4.11": version "2.4.11" resolved "https://registry.npmmirror.com/@volar/language-core/-/language-core-2.4.11.tgz" integrity sha512-lN2C1+ByfW9/JRPpqScuZt/4OrUUse57GLI6TbLgTIqBVemdl1wNcZ1qYGEo2+Gw8coYLgCy7SuKqn6IrQcQgg== @@ -143,7 +353,7 @@ estree-walker "^2.0.2" source-map-js "^1.2.0" -"@vue/compiler-dom@^3.5.0", "@vue/compiler-dom@3.5.13": +"@vue/compiler-dom@3.5.13", "@vue/compiler-dom@^3.5.0": version "3.5.13" resolved "https://registry.npmmirror.com/@vue/compiler-dom/-/compiler-dom-3.5.13.tgz" integrity sha512-ZOJ46sMOKUjO3e94wPdCzQ6P1Lx/vhp2RSvfaab88Ajexs0AHeV0uasYhi99WPaogmBlRHNRuly8xV75cNTMDA== @@ -229,7 +439,7 @@ "@vue/compiler-ssr" "3.5.13" "@vue/shared" "3.5.13" -"@vue/shared@^3.5.0", "@vue/shared@3.5.13": +"@vue/shared@3.5.13", "@vue/shared@^3.5.0": version "3.5.13" resolved "https://registry.npmmirror.com/@vue/shared/-/shared-3.5.13.tgz" integrity sha512-/hnE/qP5ZoGpol0a5mDi45bOd7t3tjYJBjsgCsivow7D48cJeV5l05RD82lPqi7gRiphZM37rnhW1l6ZoCNNnQ== @@ -312,7 +522,7 @@ combined-stream@^1.0.8: dependencies: delayed-stream "~1.0.0" -css-render@^0.15.10, css-render@^0.15.14, css-render@~0.15.14: +css-render@^0.15.10, css-render@^0.15.14: version "0.15.14" resolved "https://registry.npmmirror.com/css-render/-/css-render-0.15.14.tgz" integrity sha512-9nF4PdUle+5ta4W5SyZdLCCmFd37uVimSjg1evcTqKJCyvCEEj12WKzOSBNak6r4im4J4iYXKH1OWpUV5LBYFg== @@ -335,7 +545,7 @@ date-fns-tz@^3.1.3: resolved "https://registry.npmmirror.com/date-fns-tz/-/date-fns-tz-3.2.0.tgz" integrity sha512-sg8HqoTEulcbbbVXeg84u5UnlsQa8GS5QXMqjjYIhS4abEVVKIUwe0/l/UhrZdKaL/W5eWZNlbTeEIiOXTcsBQ== -"date-fns@^3.0.0 || ^4.0.0", date-fns@^3.6.0: +date-fns@^3.6.0: version "3.6.0" resolved "https://registry.npmmirror.com/date-fns/-/date-fns-3.6.0.tgz" integrity sha512-fRHTG8g/Gif+kSh50gaGEdToemgfj74aRX3swtiouboip5JDLAyDE9F11nHMIcvOaXeOC6D7SpNhi7uFyB7Uww== @@ -447,6 +657,11 @@ form-data@^4.0.0: es-set-tostringtag "^2.1.0" mime-types "^2.1.12" +fsevents@~2.3.2, fsevents@~2.3.3: + version "2.3.3" + resolved "https://registry.npmmirror.com/fsevents/-/fsevents-2.3.3.tgz#cac6407785d03675a2a5e1a5305c697b347d90d6" + integrity sha512-5xoDfX+fL7faATnagmWPpbFtwh/R77WmMMqqHGS65C3vvB0YHrgF+B1YmZ3441tMj5n63k0212XNoJwzlhffQw== + function-bind@^1.1.2: version "1.1.2" resolved "https://registry.npmmirror.com/function-bind/-/function-bind-1.1.2.tgz" @@ -658,7 +873,7 @@ treemate@^0.3.11: resolved "https://registry.npmmirror.com/treemate/-/treemate-0.3.11.tgz" integrity sha512-M8RGFoKtZ8dF+iwJfAJTOH/SM4KluKOKRJpjCMhI8bG3qB74zrFoArKZ62ll0Fr3mqkMJiQOmWYkdYgDeITYQg== -typescript@*, typescript@>=5.0.0, typescript@~5.7.2, typescript@5.x: +typescript@~5.7.2: version "5.7.3" resolved "https://registry.npmmirror.com/typescript/-/typescript-5.7.3.tgz" integrity sha512-84MVSjMEHP+FQRPy3pX9sTVV/INIex71s9TL2Gm5FG/WG1SqXeKyZ0k7/blY/4FdOzI12CBy1vGc4og/eus0fw== @@ -675,7 +890,7 @@ vdirs@^0.1.4, vdirs@^0.1.8: dependencies: evtd "^0.2.2" -"vite@^5.0.0 || ^6.0.0", vite@^6.2.0: +vite@^6.2.0: version "6.2.0" resolved "https://registry.npmmirror.com/vite/-/vite-6.2.0.tgz" integrity sha512-7dPxoo+WsT/64rDcwoOjk76XHj+TqNTIvHKcuMQ1k4/SeHDaQt5GFAeLYzrimZrMpn/O6DtdI03WUjdxuPM0oQ== @@ -706,7 +921,7 @@ vue-tsc@^2.2.4: "@volar/typescript" "~2.4.11" "@vue/language-core" "2.2.8" -vue@^3.0.0, vue@^3.0.11, vue@^3.2.25, vue@^3.4.0, vue@^3.5.13, vue@3.5.13: +vue@^3.5.13: version "3.5.13" resolved "https://registry.npmmirror.com/vue/-/vue-3.5.13.tgz" integrity sha512-wmeiSMxkZCSc+PM2w2VRsOYAZC8GdipNFRTsLSfodVqI9mbejKeXEGr8SckuLnrQPGe3oJN5c3K0vpoU9q/wCQ== diff --git a/stock_analyzer.py b/stock_analyzer.py index 57d0a71..c28d4ac 100644 --- a/stock_analyzer.py +++ b/stock_analyzer.py @@ -502,7 +502,8 @@ class StockAnalyzer: try: json_data = json.loads(data_content) - if 'choices' in json_data: + # 检查 choices 列表是否为空 + if 'choices' in json_data and json_data['choices']: delta = json_data['choices'][0].get('delta', {}) content = delta.get('content', '') From bcf64f00413e2713bf016feb223c54aa16143a01 Mon Sep 17 00:00:00 2001 From: Cassianvale Date: Thu, 6 Mar 2025 15:40:26 +0800 Subject: [PATCH 03/17] =?UTF-8?q?refactor:=20flask=E5=90=8E=E7=AB=AF?= =?UTF-8?q?=E6=94=B9=E4=B8=BA=E5=BC=82=E6=AD=A5fastapi?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- requirements.txt | 9 +- templates/index.html | 1287 ------------------------------------------ utils/api_control.py | 43 ++ web_server.py | 251 ++++---- 4 files changed, 202 insertions(+), 1388 deletions(-) delete mode 100644 templates/index.html create mode 100644 utils/api_control.py diff --git a/requirements.txt b/requirements.txt index c77a82b..f758152 100644 --- a/requirements.txt +++ b/requirements.txt @@ -10,11 +10,14 @@ scipy==1.15.1 akshare==1.16.22 tqdm==4.67.1 +# Web框架与异步处理 +fastapi==0.115.11 +uvicorn[standard]==0.34.0 +pydantic==2.10.6 +httpx==0.28.1 -# 网络和API请求 -requests==2.32.3 +# 环境配置 python-dotenv==1.0.1 -flask==3.1.0 # 日志和系统工具 loguru==0.7.2 diff --git a/templates/index.html b/templates/index.html deleted file mode 100644 index 0f159c7..0000000 --- a/templates/index.html +++ /dev/null @@ -1,1287 +0,0 @@ - - - - - - 股票分析系统 - - - - - - {% if announcement %} -
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股票批量分析

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- - - - - - - - - - - - - \ No newline at end of file diff --git a/utils/api_control.py b/utils/api_control.py new file mode 100644 index 0000000..ba10342 --- /dev/null +++ b/utils/api_control.py @@ -0,0 +1,43 @@ +#!/usr/bin/env python +# -*- encoding: utf-8 -*- + +from typing import Optional, Any +from fastapi import Response +from pydantic import BaseModel + + +class ResponseModel(BaseModel): + """ + 统一返回模型 + """ + code: int = 200 + msg: str = "Success" + data: Optional[Any] = None + + +class ApiResponse: + @staticmethod + def __response(code: int, msg: str, data: Optional[Any] = None) -> ResponseModel: + return ResponseModel(code=code, msg=msg, data=data) + + @classmethod + def success(cls, *, code: int = 200, msg: str = 'Success', data: Optional[Any] = None) -> Response: + response_model = cls.__response(code=code, msg=msg, data=data) + return cls(content=response_model.model_dump()) + + @classmethod + def fail(cls, *, code: int = 400, msg: str = 'Bad Request', data: Optional[Any] = None) -> Response: + response_model = cls.__response(code=code, msg=msg, data=data) + return cls(content=response_model.model_dump()) + +response_api = ApiResponse() + +""" 示例 +@app.get("/example-success") +async def example_success(): + return response_api.success(data={"key": "value"}) + +@app.get("/example-fail") +async def example_fail(): + return response_api.fail(msg="Something went wrong", data={"error": "details"}) +""" diff --git a/web_server.py b/web_server.py index a14ef1d..c761334 100644 --- a/web_server.py +++ b/web_server.py @@ -1,51 +1,80 @@ -from flask import Flask, render_template, request, jsonify, Response, stream_with_context, send_from_directory +from fastapi import FastAPI, Request, Response, Depends, HTTPException, BackgroundTasks +from fastapi.responses import JSONResponse, StreamingResponse, FileResponse, RedirectResponse +from fastapi.staticfiles import StaticFiles +from fastapi.middleware.cors import CORSMiddleware +from pydantic import BaseModel, Field +from typing import List, Optional, Generator from stock_analyzer import StockAnalyzer from us_stock_service import USStockService -from fund_service import FundService # 新增导入 +from fund_service import FundService +import asyncio import threading import os import traceback -import requests +import httpx from logger import get_logger from utils.api_utils import APIUtils # 加载环境变量 from dotenv import load_dotenv +import uvicorn load_dotenv() # 获取日志器 logger = get_logger() -app = Flask(__name__, - static_folder='frontend/dist', - static_url_path='/') +app = FastAPI( + title="Stock Scanner API", + description="股票分析API", + version="1.0.0" +) + +# 添加CORS中间件 +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], # 开发环境允许所有来源，生产环境应该限制 + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +# 设置静态文件 +frontend_dist = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'frontend', 'dist') +if os.path.exists(frontend_dist): + app.mount("/", StaticFiles(directory=frontend_dist, html=True), name="frontend") analyzer = StockAnalyzer() us_stock_service = USStockService() -fund_service = FundService() # 新增服务实例 +fund_service = FundService() -@app.route('/') -def index(): +# 定义请求和响应模型 +class AnalyzeRequest(BaseModel): + stock_codes: List[str] + market_type: str = "A" + api_url: Optional[str] = None + api_key: Optional[str] = None + api_model: Optional[str] = None + api_timeout: Optional[str] = None + +class TestAPIRequest(BaseModel): + api_url: str + api_key: str + api_model: Optional[str] = None + api_timeout: Optional[int] = 10 + +@app.get("/") +async def index(request: Request): # 检查是否使用前端构建版本 - frontend_dist = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'frontend', 'dist') if os.path.exists(frontend_dist): - return send_from_directory(frontend_dist, 'index.html') + index_file = os.path.join(frontend_dist, 'index.html') + return FileResponse(index_file) else: - # 传统模板渲染，用于兼容旧版本 - announcement = os.getenv('ANNOUNCEMENT_TEXT') or None - # 获取默认API配置信息 - default_api_url = os.getenv('API_URL', '') - default_api_model = os.getenv('API_MODEL', 'gpt-3.5-turbo') - default_api_timeout = os.getenv('API_TIMEOUT', '60') - # 不传递API_KEY到前端，出于安全考虑 - return render_template('index.html', - announcement=announcement, - default_api_url=default_api_url, - default_api_model=default_api_model, - default_api_timeout=default_api_timeout) + # 不再使用模板渲染，而是重定向到API文档页面 + logger.warning("前端构建目录不存在，重定向到API文档页面") + return RedirectResponse(url="/docs") -@app.route('/config') -def get_config(): +@app.get("/config") +async def get_config(): """返回系统配置信息""" config = { 'announcement': os.getenv('ANNOUNCEMENT_TEXT') or '', @@ -53,23 +82,22 @@ def get_config(): 'default_api_model': os.getenv('API_MODEL', 'gpt-3.5-turbo'), 'default_api_timeout': os.getenv('API_TIMEOUT', '60') } - return jsonify(config) + return config -@app.route('/analyze', methods=['POST']) -def analyze(): +@app.post("/analyze") +async def analyze(request: AnalyzeRequest): try: logger.info("开始处理分析请求") - data = request.json - stock_codes = data.get('stock_codes', []) - market_type = data.get('market_type', 'A') + stock_codes = request.stock_codes + market_type = request.market_type logger.debug(f"接收到分析请求: stock_codes={stock_codes}, market_type={market_type}") # 获取自定义API配置 - custom_api_url = data.get('api_url') - custom_api_key = data.get('api_key') - custom_api_model = data.get('api_model') - custom_api_timeout = data.get('api_timeout') + custom_api_url = request.api_url + custom_api_key = request.api_key + custom_api_model = request.api_model + custom_api_timeout = request.api_timeout logger.debug(f"自定义API配置: URL={custom_api_url}, 模型={custom_api_model}, API Key={'已提供' if custom_api_key else '未提供'}, Timeout={custom_api_timeout}") @@ -83,10 +111,10 @@ def analyze(): if not stock_codes: logger.warning("未提供股票代码") - return jsonify({'error': '请输入代码'}), 400 + raise HTTPException(status_code=400, detail="请输入代码") - # 使用流式响应 - def generate(): + # 定义流式生成器 + async def generate_stream(): if len(stock_codes) == 1: # 单个股票分析流式处理 stock_code = stock_codes[0].strip() @@ -97,7 +125,16 @@ def analyze(): logger.debug(f"开始处理股票 {stock_code} 的流式响应") chunk_count = 0 - for chunk in custom_analyzer.analyze_stock(stock_code, market_type, stream=True): + + # 使用线程池执行同步分析 + def run_analysis(): + return list(custom_analyzer.analyze_stock(stock_code, market_type, stream=True)) + + # 在线程中执行同步操作 + loop = asyncio.get_event_loop() + chunks = await loop.run_in_executor(None, run_analysis) + + for chunk in chunks: chunk_count += 1 yield chunk + '\n' logger.info(f"股票 {stock_code} 流式分析完成，共发送 {chunk_count} 个块") @@ -110,114 +147,132 @@ def analyze(): logger.debug(f"开始处理批量股票的流式响应") chunk_count = 0 - for chunk in custom_analyzer.scan_stocks( - [code.strip() for code in stock_codes], - min_score=0, - market_type=market_type, - stream=True - ): + + # 使用线程池执行同步分析 + def run_batch_analysis(): + return list(custom_analyzer.scan_stocks( + [code.strip() for code in stock_codes], + min_score=0, + market_type=market_type, + stream=True + )) + + # 在线程中执行同步操作 + loop = asyncio.get_event_loop() + chunks = await loop.run_in_executor(None, run_batch_analysis) + + for chunk in chunks: chunk_count += 1 yield chunk + '\n' logger.info(f"批量流式分析完成，共发送 {chunk_count} 个块") logger.info("成功创建流式响应生成器") - return Response(stream_with_context(generate()), mimetype='application/json') + return StreamingResponse(generate_stream(), media_type='application/json') except Exception as e: error_msg = f"分析时出错: {str(e)}" logger.error(error_msg) logger.exception(e) - return jsonify({'error': error_msg}), 500 + raise HTTPException(status_code=500, detail=error_msg) -@app.route('/search_us_stocks', methods=['GET']) -def search_us_stocks(): +@app.get("/search_us_stocks") +async def search_us_stocks(keyword: str = ""): try: - keyword = request.args.get('keyword', '') if not keyword: - return jsonify({'error': '请输入搜索关键词'}), 400 - - results = us_stock_service.search_us_stocks(keyword) - return jsonify({'results': results}) + raise HTTPException(status_code=400, detail="请输入搜索关键词") + + # 在异步上下文中运行同步的搜索函数 + loop = asyncio.get_event_loop() + results = await loop.run_in_executor(None, us_stock_service.search_us_stocks, keyword) + return {"results": results} except Exception as e: - print(f"搜索美股代码时出错: {str(e)}") - return jsonify({'error': str(e)}), 500 + logger.error(f"搜索美股代码时出错: {str(e)}") + raise HTTPException(status_code=500, detail=str(e)) -# 添加基金搜索路由 -@app.route('/search_funds', methods=['GET']) -def search_funds(): +@app.get("/search_funds") +async def search_funds(keyword: str = "", market_type: str = ""): try: - keyword = request.args.get('keyword', '') - market_type = request.args.get('market_type', '') if not keyword: - return jsonify({'error': '请输入搜索关键词'}), 400 - - results = fund_service.search_funds(keyword, market_type) - return jsonify({'results': results}) + raise HTTPException(status_code=400, detail="请输入搜索关键词") + + # 在异步上下文中运行同步的搜索函数 + loop = asyncio.get_event_loop() + results = await loop.run_in_executor(None, lambda: fund_service.search_funds(keyword, market_type)) + return {"results": results} except Exception as e: logger.error(f"搜索基金代码时出错: {str(e)}") - return jsonify({'error': str(e)}), 500 + raise HTTPException(status_code=500, detail=str(e)) -@app.route('/test_api_connection', methods=['POST']) -def test_api_connection(): +@app.post("/test_api_connection") +async def test_api_connection(request: TestAPIRequest): """测试API连接""" try: logger.info("开始测试API连接") - data = request.json - api_url = data.get('api_url') - api_key = data.get('api_key') - api_model = data.get('api_model') - api_timeout = data.get('api_timeout', 10) # 默认测试连接超时为10秒 + api_url = request.api_url + api_key = request.api_key + api_model = request.api_model + api_timeout = request.api_timeout logger.debug(f"测试API连接: URL={api_url}, 模型={api_model}, API Key={'已提供' if api_key else '未提供'}, Timeout={api_timeout}") if not api_url: logger.warning("未提供API URL") - return jsonify({'error': '请提供API URL'}), 400 + raise HTTPException(status_code=400, detail="请提供API URL") if not api_key: logger.warning("未提供API Key") - return jsonify({'error': '请提供API Key'}), 400 + raise HTTPException(status_code=400, detail="请提供API Key") # 构建API URL test_url = APIUtils.format_api_url(api_url) logger.debug(f"完整API测试URL: {test_url}") - # 发送测试请求 - response = requests.post( - test_url, - headers={ - "Authorization": f"Bearer {api_key}", - "Content-Type": "application/json" - }, - json={ - "model": api_model or "gpt-3.5-turbo", - "messages": [ - {"role": "user", "content": "Hello, this is a test message. Please respond with 'API connection successful'."} - ], - "max_tokens": 20 - }, - timeout=int(api_timeout) - ) + # 使用异步HTTP客户端发送测试请求 + async with httpx.AsyncClient(timeout=float(api_timeout)) as client: + response = await client.post( + test_url, + headers={ + "Authorization": f"Bearer {api_key}", + "Content-Type": "application/json" + }, + json={ + "model": api_model or "gpt-3.5-turbo", + "messages": [ + {"role": "user", "content": "Hello, this is a test message. Please respond with 'API connection successful'."} + ], + "max_tokens": 20 + } + ) # 检查响应 if response.status_code == 200: logger.info(f"API 连接测试成功: {response.status_code}") - return jsonify({'success': True, 'message': 'API 连接测试成功'}) + return {"success": True, "message": "API 连接测试成功"} else: - error_message = response.json().get('error', {}).get('message', '未知错误') + error_data = response.json() + error_message = error_data.get('error', {}).get('message', '未知错误') logger.warning(f"API连接测试失败: {response.status_code} - {error_message}") - return jsonify({'success': False, 'message': f'API 连接测试失败: {error_message}', 'status_code': response.status_code}), 400 + return JSONResponse( + status_code=400, + content={"success": False, "message": f"API 连接测试失败: {error_message}", "status_code": response.status_code} + ) - except requests.exceptions.RequestException as e: + except httpx.RequestError as e: logger.error(f"API 连接请求错误: {str(e)}") - return jsonify({'success': False, 'message': f'请求错误: {str(e)}'}), 400 + return JSONResponse( + status_code=400, + content={"success": False, "message": f"请求错误: {str(e)}"} + ) except Exception as e: logger.error(f"测试 API 连接时出错: {str(e)}") logger.exception(e) - return jsonify({'success': False, 'message': f'API 测试连接时出错: {str(e)}'}), 500 + return JSONResponse( + status_code=500, + content={"success": False, "message": f"API 测试连接时出错: {str(e)}"} + ) if __name__ == '__main__': logger.info("股票分析系统启动") - app.run(host='127.0.0.1', port=8888, debug=True) \ No newline at end of file + uvicorn.run("web_server:app", host="127.0.0.1", port=8888, reload=True) \ No newline at end of file From 1e53d16b3aa655f778e62324d3cfba1bf0252c3f Mon Sep 17 00:00:00 2001 From: Cassianvale Date: Thu, 6 Mar 2025 17:11:15 +0800 Subject: [PATCH 04/17] =?UTF-8?q?refactor:=20=E9=87=8D=E6=9E=84=E4=BB=A3?= =?UTF-8?q?=E7=A0=81=E7=BB=93=E6=9E=84?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- services/__init__.py | 2 + services/ai_analyzer.py | 269 +++++++++++++++++++++++++++++ services/fund_service_async.py | 225 ++++++++++++++++++++++++ services/stock_analyzer_service.py | 178 +++++++++++++++++++ services/stock_data_provider.py | 184 ++++++++++++++++++++ services/stock_scorer.py | 128 ++++++++++++++ services/technical_indicator.py | 187 ++++++++++++++++++++ services/us_stock_service_async.py | 151 ++++++++++++++++ web_server.py | 94 ++++++---- 9 files changed, 1380 insertions(+), 38 deletions(-) create mode 100644 services/__init__.py create mode 100644 services/ai_analyzer.py create mode 100644 services/fund_service_async.py create mode 100644 services/stock_analyzer_service.py create mode 100644 services/stock_data_provider.py create mode 100644 services/stock_scorer.py create mode 100644 services/technical_indicator.py create mode 100644 services/us_stock_service_async.py diff --git a/services/__init__.py b/services/__init__.py new file mode 100644 index 0000000..7267b70 --- /dev/null +++ b/services/__init__.py @@ -0,0 +1,2 @@ +# services包初始化文件 +# 用于组织股票分析服务的各个模块 \ No newline at end of file diff --git a/services/ai_analyzer.py b/services/ai_analyzer.py new file mode 100644 index 0000000..93c063f --- /dev/null +++ b/services/ai_analyzer.py @@ -0,0 +1,269 @@ +import pandas as pd +import numpy as np +import os +import json +import asyncio +import httpx +from typing import Dict, List, Optional, Any, Generator, AsyncGenerator +from dotenv import load_dotenv +from logger import get_logger +from utils.api_utils import APIUtils + +# 获取日志器 +logger = get_logger() + +class AIAnalyzer: + """ + 异步AI分析服务 + 负责调用AI API对股票数据进行分析 + """ + + def __init__(self, custom_api_url=None, custom_api_key=None, custom_api_model=None, custom_api_timeout=None): + """ + 初始化AI分析服务 + + Args: + custom_api_url: 自定义API URL + custom_api_key: 自定义API密钥 + custom_api_model: 自定义API模型 + custom_api_timeout: 自定义API超时时间 + """ + # 加载环境变量 + load_dotenv() + + # 设置API配置 + self.API_URL = custom_api_url or os.getenv('API_URL') + self.API_KEY = custom_api_key or os.getenv('API_KEY') + self.API_MODEL = custom_api_model or os.getenv('API_MODEL', 'gpt-3.5-turbo') + self.API_TIMEOUT = int(custom_api_timeout or os.getenv('API_TIMEOUT', 60)) + + logger.debug(f"初始化AIAnalyzer: API_URL={self.API_URL}, API_MODEL={self.API_MODEL}, API_KEY={'已提供' if self.API_KEY else '未提供'}, API_TIMEOUT={self.API_TIMEOUT}") + + async def get_ai_analysis(self, df: pd.DataFrame, stock_code: str, market_type: str = 'A', stream: bool = False) -> AsyncGenerator[str, None]: + """ + 对股票数据进行AI分析 + + Args: + df: 包含技术指标的DataFrame + stock_code: 股票代码 + market_type: 市场类型，默认为'A'股 + stream: 是否使用流式响应 + + Returns: + 异步生成器，生成分析结果字符串 + """ + try: + logger.info(f"开始AI分析 {stock_code}, 流式模式: {stream}") + recent_data = df.tail(14).to_dict('records') + + technical_summary = { + 'trend': 'upward' if df.iloc[-1]['MA5'] > df.iloc[-1]['MA20'] else 'downward', + 'volatility': f"{df.iloc[-1]['Volatility']:.2f}%", + 'volume_trend': 'increasing' if df.iloc[-1]['Volume_Ratio'] > 1 else 'decreasing', + 'rsi_level': df.iloc[-1]['RSI'] + } + + # 根据市场类型调整分析提示 + if market_type in ['ETF', 'LOF']: + prompt = f""" + 分析基金 {stock_code}： + + 技术指标概要： + {technical_summary} + + 近14日交易数据： + {recent_data} + + 请分析该基金的技术面状况，包括： + 1. 趋势分析：判断基金当前的趋势方向 + 2. 动量分析：基于RSI和交易量评估基金动量 + 3. 支撑与阻力位：确定关键价格位 + 4. 技术面总结 + 5. 投资建议 + + 将分析结果格式化为JSON，像这样： + {{ + "trend_analysis": "趋势分析结果...", + "momentum_analysis": "动量分析结果...", + "support_resistance": "支撑阻力位分析...", + "technical_summary": "技术面总结...", + "investment_advice": "投资建议..." + }} + """ + else: + prompt = f""" + 分析股票 {stock_code}： + + 技术指标概要： + {technical_summary} + + 近14日交易数据： + {recent_data} + + 请分析该股票的技术面状况，包括： + 1. 趋势分析：当前趋势方向及强度 + 2. 动量分析：基于MACD、RSI等指标 + 3. 支撑与阻力位：关键价格位分析 + 4. 成交量分析：交易量的变化及意义 + 5. 波动性评估：ATR和波动率分析 + 6. 技术面总结 + 7. 投资建议：根据技术分析给出操作建议 + + 将分析结果格式化为JSON，像这样： + {{ + "trend_analysis": "趋势分析结果...", + "momentum_analysis": "动量分析结果...", + "support_resistance": "支撑阻力位分析...", + "volume_analysis": "成交量分析...", + "volatility_assessment": "波动性评估...", + "technical_summary": "技术面总结...", + "investment_advice": "投资建议..." + }} + """ + + # 格式化API URL + api_url = APIUtils.format_api_url(self.API_URL) + + # 准备请求数据 + request_data = { + "model": self.API_MODEL, + "messages": [{"role": "user", "content": prompt}], + "temperature": 0.7, + "stream": stream + } + + # 准备请求头 + headers = { + "Content-Type": "application/json", + "Authorization": f"Bearer {self.API_KEY}" + } + + # 异步请求API + async with httpx.AsyncClient(timeout=self.API_TIMEOUT) as client: + # 记录请求 + logger.debug(f"发送AI请求: URL={api_url}, MODEL={self.API_MODEL}, STREAM={stream}") + + if stream: + # 流式响应处理 + async with client.stream("POST", api_url, json=request_data, headers=headers) as response: + if response.status_code != 200: + error_text = await response.aread() + error_data = json.loads(error_text) + error_message = error_data.get('error', {}).get('message', '未知错误') + logger.error(f"AI API请求失败: {response.status_code} - {error_message}") + yield json.dumps({"error": f"API请求失败: {error_message}"}) + return + + # 处理流式响应 + buffer = "" + collected_messages = [] + + async for chunk in response.aiter_text(): + if chunk: + chunk_str = chunk.strip() + if chunk_str.startswith("data: "): + chunk_str = chunk_str[6:] # 去除"data: "前缀 + + if chunk_str == "[DONE]": + continue + + try: + # 解析数据块 + chunk_data = json.loads(chunk_str) + delta = chunk_data.get("choices", [{}])[0].get("delta", {}) + content = delta.get("content", "") + + if content: + buffer += content + # 尝试提取完整的JSON + if buffer.strip().startswith("{") and buffer.strip().endswith("}"): + try: + result_json = json.loads(buffer) + yield json.dumps({ + "stock_code": stock_code, + "analysis": result_json + }) + buffer = "" # 重置缓冲区 + except json.JSONDecodeError: + # JSON不完整，继续收集 + pass + + # 达到一定长度就输出 + if len(buffer) > 100: + yield json.dumps({ + "stock_code": stock_code, + "partial_content": buffer + }) + collected_messages.append(buffer) + buffer = "" + except json.JSONDecodeError: + # 忽略无法解析的块 + continue + + # 处理最后的缓冲区 + if buffer: + yield json.dumps({ + "stock_code": stock_code, + "partial_content": buffer + }) + collected_messages.append(buffer) + + # 尝试从整个内容中提取JSON + full_content = "".join(collected_messages) + + # 如果没有成功解析JSON，返回原始内容 + if not full_content.strip().startswith("{"): + yield json.dumps({ + "stock_code": stock_code, + "raw_analysis": full_content + }) + else: + # 非流式响应处理 + response = await client.post(api_url, json=request_data, headers=headers) + + if response.status_code != 200: + error_data = response.json() + error_message = error_data.get('error', {}).get('message', '未知错误') + logger.error(f"AI API请求失败: {response.status_code} - {error_message}") + yield json.dumps({"error": f"API请求失败: {error_message}"}) + return + + response_data = response.json() + analysis_text = response_data.get("choices", [{}])[0].get("message", {}).get("content", "") + + try: + # 尝试解析JSON + analysis_json = json.loads(analysis_text) + yield json.dumps({ + "stock_code": stock_code, + "analysis": analysis_json + }) + except json.JSONDecodeError: + # 返回原始文本 + yield json.dumps({ + "stock_code": stock_code, + "raw_analysis": analysis_text + }) + + logger.info(f"完成对 {stock_code} 的AI分析") + + except Exception as e: + logger.error(f"AI分析 {stock_code} 时出错: {str(e)}") + logger.exception(e) + yield json.dumps({"error": f"分析出错: {str(e)}"}) + + def _truncate_json_for_logging(self, json_obj, max_length=500): + """ + 截断JSON对象以便记录日志 + + Args: + json_obj: JSON对象 + max_length: 最大长度 + + Returns: + 截断后的字符串 + """ + json_str = json.dumps(json_obj, ensure_ascii=False) + if len(json_str) <= max_length: + return json_str + return json_str[:max_length] + "..." \ No newline at end of file diff --git a/services/fund_service_async.py b/services/fund_service_async.py new file mode 100644 index 0000000..8bafada --- /dev/null +++ b/services/fund_service_async.py @@ -0,0 +1,225 @@ +import asyncio +import pandas as pd +from typing import List, Dict, Any, Optional +from logger import get_logger +from datetime import datetime, timedelta + +# 获取日志器 +logger = get_logger() + +class FundServiceAsync: + """ + 异步基金服务 + 提供基金数据的异步搜索和获取功能 + """ + + def __init__(self): + """初始化异步基金服务""" + logger.debug("初始化FundServiceAsync") + + # 添加缓存 + self._etf_cache = None + self._lof_cache = None + self._cache_timestamp = None + self._cache_duration = timedelta(minutes=30) # 缓存30分钟 + + async def search_funds(self, keyword: str, market_type: str = 'ETF') -> List[Dict[str, Any]]: + """ + 异步搜索基金代码 + + Args: + keyword: 搜索关键词 + market_type: 市场类型，'ETF'或'LOF' + + Returns: + 匹配的基金列表 + """ + try: + logger.info(f"异步搜索基金: {keyword}, 类型: {market_type}") + + # 获取基金数据 + df = await self._get_funds_data(market_type) + + # 模糊匹配搜索（同时匹配代码和名称） + mask = (df['name'].str.contains(keyword, case=False, na=False) | + df['symbol'].str.contains(keyword, case=False, na=False)) + results = df[mask] + + # 格式化返回结果并处理 NaN 值 + formatted_results = [] + for _, row in results.iterrows(): + formatted_results.append({ + 'name': row['name'] if pd.notna(row['name']) else '', + 'symbol': str(row['symbol']) if pd.notna(row['symbol']) else '', + 'price': float(row['price']) if pd.notna(row['price']) else 0.0, + 'volume': float(row['volume']) if pd.notna(row['volume']) else 0.0, + 'market_value': float(row['market_value']) if pd.notna(row['market_value']) else 0.0, + 'total_value': float(row['total_value']) if pd.notna(row['total_value']) else 0.0, + }) + + logger.info(f"基金搜索完成，找到 {len(formatted_results)} 个匹配项") + return formatted_results + + except Exception as e: + error_msg = f"搜索基金代码失败: {str(e)}" + logger.error(error_msg) + logger.exception(e) + raise Exception(error_msg) + + async def _get_funds_data(self, market_type: str = 'ETF') -> pd.DataFrame: + """ + 异步获取基金数据，支持缓存 + + Args: + market_type: 市场类型，'ETF'或'LOF' + + Returns: + 包含基金数据的DataFrame + """ + # 检查缓存是否有效 + now = datetime.now() + cache_valid = ( + self._cache_timestamp is not None and + (now - self._cache_timestamp) < self._cache_duration + ) + + if market_type == 'ETF' and cache_valid and self._etf_cache is not None: + logger.debug("使用ETF缓存数据") + return self._etf_cache + elif market_type == 'LOF' and cache_valid and self._lof_cache is not None: + logger.debug("使用LOF缓存数据") + return self._lof_cache + + # 缓存无效，重新获取数据 + try: + logger.debug(f"从API获取{market_type}数据") + + # 使用线程池执行同步的akshare调用 + if market_type == 'ETF': + df = await asyncio.to_thread(self._get_etf_data) + self._etf_cache = df + else: + df = await asyncio.to_thread(self._get_lof_data) + self._lof_cache = df + + self._cache_timestamp = now + return df + + except Exception as e: + logger.error(f"获取{market_type}数据失败: {str(e)}") + logger.exception(e) + raise + + def _get_etf_data(self) -> pd.DataFrame: + """ + 获取ETF数据（同步方法，将被异步方法调用） + + Returns: + 包含ETF数据的DataFrame + """ + import akshare as ak + + try: + # 获取ETF基金数据 + df = ak.fund_etf_spot_em() + + # 转换列名 + df = df.rename(columns={ + "代码": "symbol", + "名称": "name", + "最新价": "price", + "涨跌额": "price_change", + "涨跌幅": "price_change_percent", + "成交量": "volume", + "流通市值": "market_value", + "总市值": "total_value", + "基金折价率": "discount_rate", + }) + + return df + + except Exception as e: + logger.error(f"获取ETF数据失败: {str(e)}") + logger.exception(e) + raise Exception(f"获取ETF数据失败: {str(e)}") + + def _get_lof_data(self) -> pd.DataFrame: + """ + 获取LOF数据（同步方法，将被异步方法调用） + + Returns: + 包含LOF数据的DataFrame + """ + import akshare as ak + + try: + # 获取LOF基金数据 + df = ak.fund_lof_spot_em() + + # 转换列名 + df = df.rename(columns={ + "代码": "symbol", + "名称": "name", + "最新价": "price", + "涨跌额": "price_change", + "涨跌幅": "price_change_percent", + "成交量": "volume", + "流通市值": "market_value", + "总市值": "total_value", + "基金折价率": "discount_rate", + }) + + return df + + except Exception as e: + logger.error(f"获取LOF数据失败: {str(e)}") + logger.exception(e) + raise Exception(f"获取LOF数据失败: {str(e)}") + + async def get_fund_detail(self, symbol: str, market_type: str = 'ETF') -> Dict[str, Any]: + """ + 异步获取单个基金详细信息 + + Args: + symbol: 基金代码 + market_type: 市场类型，'ETF'或'LOF' + + Returns: + 基金详细信息 + """ + try: + logger.info(f"获取{market_type}基金详情: {symbol}") + + # 获取基金数据 + df = await self._get_funds_data(market_type) + + # 精确匹配基金代码 + result = df[df['symbol'] == symbol] + + if len(result) == 0: + raise Exception(f"未找到基金代码: {symbol}") + + # 获取第一行数据 + row = result.iloc[0] + + # 格式化为字典 + fund_detail = { + 'name': row['name'] if pd.notna(row['name']) else '', + 'symbol': str(row['symbol']) if pd.notna(row['symbol']) else '', + 'price': float(row['price']) if pd.notna(row['price']) else 0.0, + 'price_change': float(row['price_change']) if pd.notna(row['price_change']) else 0.0, + 'price_change_percent': float(row['price_change_percent'].strip('%'))/100 if pd.notna(row['price_change_percent']) else 0.0, + 'volume': float(row['volume']) if pd.notna(row['volume']) else 0.0, + 'market_value': float(row['market_value']) if pd.notna(row['market_value']) else 0.0, + 'total_value': float(row['total_value']) if pd.notna(row['total_value']) else 0.0, + 'discount_rate': float(row['discount_rate'].strip('%'))/100 if pd.notna(row['discount_rate']) else 0.0 + } + + logger.info(f"获取基金详情成功: {symbol}") + return fund_detail + + except Exception as e: + error_msg = f"获取基金详情失败: {str(e)}" + logger.error(error_msg) + logger.exception(e) + raise Exception(error_msg) \ No newline at end of file diff --git a/services/stock_analyzer_service.py b/services/stock_analyzer_service.py new file mode 100644 index 0000000..91df74a --- /dev/null +++ b/services/stock_analyzer_service.py @@ -0,0 +1,178 @@ +import pandas as pd +import numpy as np +import asyncio +import json +from typing import Dict, List, Optional, Tuple, Any, AsyncGenerator +from logger import get_logger +from services.stock_data_provider import StockDataProvider +from services.technical_indicator import TechnicalIndicator +from services.stock_scorer import StockScorer +from services.ai_analyzer import AIAnalyzer + +# 获取日志器 +logger = get_logger() + +class StockAnalyzerService: + """ + 股票分析服务 + 作为门面类协调数据提供、指标计算、评分和AI分析等组件 + """ + + def __init__(self, custom_api_url=None, custom_api_key=None, custom_api_model=None, custom_api_timeout=None): + """ + 初始化股票分析服务 + + Args: + custom_api_url: 自定义API URL + custom_api_key: 自定义API密钥 + custom_api_model: 自定义API模型 + custom_api_timeout: 自定义API超时时间 + """ + # 初始化各个组件 + self.data_provider = StockDataProvider() + self.indicator = TechnicalIndicator() + self.scorer = StockScorer() + self.ai_analyzer = AIAnalyzer( + custom_api_url=custom_api_url, + custom_api_key=custom_api_key, + custom_api_model=custom_api_model, + custom_api_timeout=custom_api_timeout + ) + + logger.info("初始化StockAnalyzerService完成") + + async def analyze_stock(self, stock_code: str, market_type: str = 'A', stream: bool = False) -> AsyncGenerator[str, None]: + """ + 分析单只股票 + + Args: + stock_code: 股票代码 + market_type: 市场类型，默认为'A'股 + stream: 是否使用流式响应 + + Returns: + 异步生成器，生成分析结果的JSON字符串 + """ + try: + logger.info(f"开始分析股票: {stock_code}, 市场: {market_type}") + + # 获取股票数据 + df = await self.data_provider.get_stock_data(stock_code, market_type) + + # 计算技术指标 + df_with_indicators = self.indicator.calculate_indicators(df) + + # 计算评分 + score = self.scorer.calculate_score(df_with_indicators) + recommendation = self.scorer.get_recommendation(score) + + # 生成基本分析结果 + basic_result = { + "stock_code": stock_code, + "score": score, + "recommendation": recommendation, + "data_point_count": len(df), + "market_type": market_type + } + + # 输出基本分析结果 + logger.info(f"基本分析结果: {json.dumps(basic_result)}") + yield json.dumps(basic_result) + + # 使用AI进行深入分析 + async for analysis_chunk in self.ai_analyzer.get_ai_analysis(df_with_indicators, stock_code, market_type, stream): + yield analysis_chunk + + logger.info(f"完成股票分析: {stock_code}") + + except Exception as e: + error_msg = f"分析股票 {stock_code} 时出错: {str(e)}" + logger.error(error_msg) + logger.exception(e) + yield json.dumps({"error": error_msg}) + + async def scan_stocks(self, stock_codes: List[str], market_type: str = 'A', min_score: int = 0, stream: bool = False) -> AsyncGenerator[str, None]: + """ + 批量扫描股票 + + Args: + stock_codes: 股票代码列表 + market_type: 市场类型 + min_score: 最低评分阈值 + stream: 是否使用流式响应 + + Returns: + 异步生成器，生成扫描结果的JSON字符串 + """ + try: + logger.info(f"开始批量扫描 {len(stock_codes)} 只股票, 市场: {market_type}") + + # 输出初始状态 + yield json.dumps({ + "status": "scanning", + "total_stocks": len(stock_codes), + "market_type": market_type, + "min_score": min_score + }) + + # 批量获取股票数据 + stock_data_dict = await self.data_provider.get_multiple_stocks_data(stock_codes, market_type) + + # 计算技术指标 + stock_with_indicators = {} + for code, df in stock_data_dict.items(): + try: + stock_with_indicators[code] = self.indicator.calculate_indicators(df) + except Exception as e: + logger.error(f"计算 {code} 技术指标时出错: {str(e)}") + + # 评分股票 + results = self.scorer.batch_score_stocks(stock_with_indicators) + + # 过滤低于最低评分的股票 + filtered_results = [r for r in results if r[1] >= min_score] + + # 输出评分结果 + yield json.dumps({ + "scan_results": [ + { + "stock_code": code, + "score": score, + "recommendation": rec + } for code, score, rec in filtered_results + ], + "total_matched": len(filtered_results), + "total_scanned": len(results) + }) + + # 如果需要进一步分析，对评分较高的股票进行AI分析 + if stream and filtered_results: + top_stocks = filtered_results[:3] # 只分析前3只评分最高的股票 + + for stock_code, score, _ in top_stocks: + df = stock_with_indicators.get(stock_code) + if df is not None: + # 输出正在分析的股票信息 + yield json.dumps({ + "analyzing": stock_code, + "score": score + }) + + # AI分析 + async for analysis_chunk in self.ai_analyzer.get_ai_analysis(df, stock_code, market_type, stream): + yield analysis_chunk + + # 输出扫描完成信息 + yield json.dumps({ + "status": "completed", + "total_scanned": len(results), + "total_matched": len(filtered_results) + }) + + logger.info(f"完成批量扫描 {len(stock_codes)} 只股票, 符合条件: {len(filtered_results)}") + + except Exception as e: + error_msg = f"批量扫描股票时出错: {str(e)}" + logger.error(error_msg) + logger.exception(e) + yield json.dumps({"error": error_msg}) \ No newline at end of file diff --git a/services/stock_data_provider.py b/services/stock_data_provider.py new file mode 100644 index 0000000..48cebb4 --- /dev/null +++ b/services/stock_data_provider.py @@ -0,0 +1,184 @@ +import pandas as pd +import numpy as np +from datetime import datetime, timedelta +import asyncio +import os +from typing import Dict, List, Optional, Tuple, Any +from logger import get_logger + +# 获取日志器 +logger = get_logger() + +class StockDataProvider: + """ + 异步股票数据提供服务 + 负责获取股票、基金等金融产品的历史数据 + """ + + def __init__(self): + """初始化数据提供者服务""" + logger.debug("初始化StockDataProvider") + + async def get_stock_data(self, stock_code: str, market_type: str = 'A', + start_date: Optional[str] = None, + end_date: Optional[str] = None) -> pd.DataFrame: + """ + 异步获取股票或基金数据 + + Args: + stock_code: 股票代码 + market_type: 市场类型，默认为'A'股 + start_date: 开始日期，格式YYYYMMDD，默认为一年前 + end_date: 结束日期，格式YYYYMMDD，默认为今天 + + Returns: + 包含历史数据的DataFrame + """ + # 使用线程池执行同步的akshare调用 + return await asyncio.to_thread( + self._get_stock_data_sync, + stock_code, + market_type, + start_date, + end_date + ) + + def _get_stock_data_sync(self, stock_code: str, market_type: str = 'A', + start_date: Optional[str] = None, + end_date: Optional[str] = None) -> pd.DataFrame: + """ + 同步获取股票数据的实现 + 将被异步方法调用 + """ + import akshare as ak + + if start_date is None: + start_date = (datetime.now() - timedelta(days=365)).strftime('%Y%m%d') + if end_date is None: + end_date = datetime.now().strftime('%Y%m%d') + + try: + # 验证股票代码格式 + if market_type == 'A': + # 上海证券交易所股票代码以6开头 + # 深圳证券交易所股票代码以0或3开头 + # 科创板股票代码以688开头 + # 北京证券交易所股票代码以8开头 + valid_prefixes = ['0', '3', '6', '688', '8'] + valid_format = False + + for prefix in valid_prefixes: + if stock_code.startswith(prefix): + valid_format = True + break + + if not valid_format: + error_msg = f"无效的A股股票代码格式: {stock_code}。A股代码应以0、3、6、688或8开头" + logger.error(f"[股票代码格式错误] {error_msg}") + raise ValueError(error_msg) + + logger.debug(f"获取A股数据: {stock_code}") + df = ak.stock_zh_a_hist( + symbol=stock_code, + start_date=start_date, + end_date=end_date, + adjust="qfq" + ) + + elif market_type in ['HK']: + logger.debug(f"获取港股数据: {stock_code}") + df = ak.stock_hk_daily( + symbol=stock_code, + start_date=start_date, + end_date=end_date, + adjust="qfq" + ) + + elif market_type in ['US']: + logger.debug(f"获取美股数据: {stock_code}") + df = ak.stock_us_daily( + symbol=stock_code, + adjust="qfq" + ) + # 过滤日期 + df = df[(df.index >= start_date) & (df.index <= end_date)] + + elif market_type in ['ETF', 'LOF']: + logger.debug(f"获取{market_type}基金数据: {stock_code}") + df = ak.fund_etf_hist_sina( + symbol=stock_code, + start_date=start_date.replace('-', ''), + end_date=end_date.replace('-', '') + ) + + else: + error_msg = f"不支持的市场类型: {market_type}" + logger.error(f"[市场类型错误] {error_msg}") + raise ValueError(error_msg) + + # 标准化列名 + if market_type == 'A': + # 根据实际数据结构调整列名映射 + # 实际数据列：['日期', '股票代码', '开盘', '收盘', '最高', '最低', '成交量', '成交额', '振幅', '涨跌幅', '涨跌额', '换手率'] + df.columns = ['Date', 'Code', 'Open', 'Close', 'High', 'Low', 'Volume', 'Amount', 'Amplitude', 'Change_pct', 'Change', 'Turnover'] + elif market_type in ['HK', 'US']: + # 根据实际情况调整 + df.columns = ['Date', 'Open', 'High', 'Low', 'Close', 'Volume', 'Amount'] + elif market_type in ['ETF', 'LOF']: + # 基金数据可能有不同的列 + df.columns = ['Date', 'Open', 'High', 'Low', 'Close', 'Volume', 'Amount'] + + # 确保日期列是日期类型 + if 'Date' in df.columns: + df['Date'] = pd.to_datetime(df['Date']) + df.set_index('Date', inplace=True) + + # 确保按日期升序排序 + df.sort_index(inplace=True) + + logger.info(f"成功获取{market_type}数据 {stock_code}, 数据点数: {len(df)}") + return df + + except Exception as e: + error_msg = f"获取{market_type}数据失败 {stock_code}: {str(e)}" + logger.error(error_msg) + logger.exception(e) + raise Exception(error_msg) + + async def get_multiple_stocks_data(self, stock_codes: List[str], + market_type: str = 'A', + start_date: Optional[str] = None, + end_date: Optional[str] = None, + max_concurrency: int = 5) -> Dict[str, pd.DataFrame]: + """ + 异步批量获取多只股票数据 + + Args: + stock_codes: 股票代码列表 + market_type: 市场类型，默认为'A'股 + start_date: 开始日期，格式YYYYMMDD + end_date: 结束日期，格式YYYYMMDD + max_concurrency: 最大并发数，默认为5 + + Returns: + 字典，键为股票代码，值为对应的DataFrame + """ + # 使用信号量控制并发数 + semaphore = asyncio.Semaphore(max_concurrency) + + async def get_with_semaphore(code): + async with semaphore: + try: + return code, await self.get_stock_data(code, market_type, start_date, end_date) + except Exception as e: + logger.error(f"获取股票 {code} 数据时出错: {str(e)}") + return code, None + + # 创建异步任务 + tasks = [get_with_semaphore(code) for code in stock_codes] + + # 等待所有任务完成 + results = await asyncio.gather(*tasks) + + # 构建结果字典，过滤掉失败的请求 + return {code: df for code, df in results if df is not None} \ No newline at end of file diff --git a/services/stock_scorer.py b/services/stock_scorer.py new file mode 100644 index 0000000..c631f14 --- /dev/null +++ b/services/stock_scorer.py @@ -0,0 +1,128 @@ +import pandas as pd +import numpy as np +from typing import Dict, Optional, Any, List, Tuple +from logger import get_logger + +# 获取日志器 +logger = get_logger() + +class StockScorer: + """ + 股票评分服务 + 负责根据技术指标计算股票的综合评分 + """ + + def __init__(self): + """初始化股票评分服务""" + logger.debug("初始化StockScorer") + + def calculate_score(self, df: pd.DataFrame) -> int: + """ + 计算股票评分（满分100分） + + Args: + df: 包含技术指标的DataFrame + + Returns: + 股票评分（0-100的整数） + """ + try: + # 使用最新的数据点进行评分 + latest = df.iloc[-1] + + # 初始得分为0 + score = 0 + + # 移动平均线评分（25分） + if latest['MA5'] > latest['MA20'] > latest['MA60']: + # 短期、中期和长期均线呈多头排列 + score += 25 + elif latest['MA5'] > latest['MA20']: + # 短期均线在中期均线之上 + score += 15 + elif latest['Close'] > latest['MA20']: + # 股价在中期均线之上 + score += 10 + + # RSI评分（25分） + rsi = latest['RSI'] + if 45 <= rsi <= 55: + # RSI在中间区域，可能即将爆发 + score += 15 + elif 55 < rsi < 70: + # RSI在强势区域但未超买 + score += 25 + elif 30 < rsi < 45: + # RSI在弱势区域但未超卖 + score += 10 + elif rsi >= 70: + # RSI超买 + score += 5 + elif rsi <= 30: + # RSI超卖 + score += 15 + + # MACD得分（20分） + if latest['MACD'] > latest['Signal']: + score += 20 + + # 成交量得分（30分） + if latest['Volume_Ratio'] > 1.5: + score += 30 + elif latest['Volume_Ratio'] > 1: + score += 15 + + return score + + except Exception as e: + logger.error(f"计算评分时出错: {str(e)}") + logger.exception(e) + raise + + def get_recommendation(self, score: int) -> str: + """ + 根据评分获取投资建议 + + Args: + score: 股票评分（0-100） + + Returns: + 投资建议文本 + """ + if score >= 80: + return "强烈推荐" + elif score >= 70: + return "推荐" + elif score >= 60: + return "谨慎推荐" + elif score >= 40: + return "观望" + elif score >= 20: + return "不推荐" + else: + return "强烈不推荐" + + def batch_score_stocks(self, stock_dfs: Dict[str, pd.DataFrame]) -> List[Tuple[str, int, str]]: + """ + 批量评分多只股票 + + Args: + stock_dfs: 字典，键为股票代码，值为DataFrame + + Returns: + 评分结果列表，每项为(股票代码, 评分, 推荐)的三元组 + """ + results = [] + + for stock_code, df in stock_dfs.items(): + try: + score = self.calculate_score(df) + recommendation = self.get_recommendation(score) + results.append((stock_code, score, recommendation)) + except Exception as e: + logger.error(f"评分股票 {stock_code} 时出错: {str(e)}") + + # 按评分降序排序 + results.sort(key=lambda x: x[1], reverse=True) + + return results \ No newline at end of file diff --git a/services/technical_indicator.py b/services/technical_indicator.py new file mode 100644 index 0000000..0f8aacb --- /dev/null +++ b/services/technical_indicator.py @@ -0,0 +1,187 @@ +import pandas as pd +import numpy as np +from typing import Dict, Optional, Any +from logger import get_logger + +# 获取日志器 +logger = get_logger() + +class TechnicalIndicator: + """ + 技术指标计算服务 + 负责计算常见的股票技术指标 + """ + + def __init__(self, params: Optional[Dict[str, Any]] = None): + """ + 初始化技术指标计算服务 + + Args: + params: 技术指标参数配置 + """ + # 默认参数设置 + self.params = params or { + 'ma_periods': {'short': 5, 'medium': 20, 'long': 60}, + 'rsi_period': 14, + 'bollinger_period': 20, + 'bollinger_std': 2, + 'volume_ma_period': 20, + 'atr_period': 14 + } + + logger.debug(f"初始化TechnicalIndicator，参数: {self.params}") + + def calculate_ema(self, series: pd.Series, period: int) -> pd.Series: + """ + 计算指数移动平均线 + + Args: + series: 价格序列 + period: 周期 + + Returns: + EMA序列 + """ + return series.ewm(span=period, adjust=False).mean() + + def calculate_rsi(self, series: pd.Series, period: int) -> pd.Series: + """ + 计算相对强弱指标(RSI) + + Args: + series: 价格序列 + period: 周期 + + Returns: + RSI序列 + """ + delta = series.diff() + gain = delta.where(delta > 0, 0) + loss = -delta.where(delta < 0, 0) + + avg_gain = gain.rolling(window=period).mean() + avg_loss = loss.rolling(window=period).mean() + + rs = avg_gain / avg_loss + rsi = 100 - (100 / (1 + rs)) + + return rsi + + def calculate_macd(self, series: pd.Series) -> tuple: + """ + 计算MACD指标 + + Args: + series: 价格序列 + + Returns: + (MACD线, 信号线, 柱状图)的元组 + """ + ema12 = self.calculate_ema(series, 12) + ema26 = self.calculate_ema(series, 26) + + macd = ema12 - ema26 + signal = self.calculate_ema(macd, 9) + histogram = macd - signal + + return macd, signal, histogram + + def calculate_bollinger_bands(self, series: pd.Series, period: int, std_dev: float) -> tuple: + """ + 计算布林带 + + Args: + series: 价格序列 + period: 周期 + std_dev: 标准差倍数 + + Returns: + (中轨, 上轨, 下轨)的元组 + """ + middle = series.rolling(window=period).mean() + std = series.rolling(window=period).std() + + upper = middle + std_dev * std + lower = middle - std_dev * std + + return middle, upper, lower + + def calculate_atr(self, df: pd.DataFrame, period: int) -> pd.Series: + """ + 计算平均真实波幅(ATR) + + Args: + df: 包含High, Low, Close列的DataFrame + period: 周期 + + Returns: + ATR序列 + """ + high = df['High'] + low = df['Low'] + close = df['Close'] + + tr1 = high - low + tr2 = abs(high - close.shift()) + tr3 = abs(low - close.shift()) + + tr = pd.concat([tr1, tr2, tr3], axis=1).max(axis=1) + atr = tr.rolling(window=period).mean() + + return atr + + def calculate_indicators(self, df: pd.DataFrame) -> pd.DataFrame: + """ + 计算所有技术指标 + + Args: + df: 原始价格数据，包含Open, High, Low, Close, Volume列 + + Returns: + 添加了技术指标的DataFrame + """ + try: + # 复制数据框 + result_df = df.copy() + + # 移动平均线 + for name, period in self.params['ma_periods'].items(): + result_df[f'MA{period}'] = result_df['Close'].rolling(window=period).mean() + + # RSI + result_df['RSI'] = self.calculate_rsi(result_df['Close'], self.params['rsi_period']) + + # MACD + macd, signal, histogram = self.calculate_macd(result_df['Close']) + result_df['MACD'] = macd + result_df['Signal'] = signal + result_df['Histogram'] = histogram + + # 布林带 + middle, upper, lower = self.calculate_bollinger_bands( + result_df['Close'], + self.params['bollinger_period'], + self.params['bollinger_std'] + ) + result_df['BB_Middle'] = middle + result_df['BB_Upper'] = upper + result_df['BB_Lower'] = lower + + # 成交量移动平均 + result_df['Volume_MA'] = result_df['Volume'].rolling(window=self.params['volume_ma_period']).mean() + + # 成交量比率 + result_df['Volume_Ratio'] = result_df['Volume'] / result_df['Volume_MA'] + + # ATR + result_df['ATR'] = self.calculate_atr(result_df, self.params['atr_period']) + + # 波动率 (过去20天收盘价的标准差/均值) + result_df['Volatility'] = result_df['Close'].rolling(window=20).std() / result_df['Close'].rolling(window=20).mean() * 100 + + return result_df + + except Exception as e: + logger.error(f"计算技术指标时出错: {str(e)}") + logger.exception(e) + raise \ No newline at end of file diff --git a/services/us_stock_service_async.py b/services/us_stock_service_async.py new file mode 100644 index 0000000..d0a5b0b --- /dev/null +++ b/services/us_stock_service_async.py @@ -0,0 +1,151 @@ +import asyncio +import pandas as pd +from typing import List, Dict, Any, Optional +from logger import get_logger + +# 获取日志器 +logger = get_logger() + +class USStockServiceAsync: + """ + 异步美股服务 + 提供美股数据的异步搜索和获取功能 + """ + + def __init__(self): + """初始化异步美股服务""" + logger.debug("初始化USStockServiceAsync") + + # 可选：添加缓存以减少频繁请求 + self._cache = None + self._cache_timestamp = None + + async def search_us_stocks(self, keyword: str) -> List[Dict[str, Any]]: + """ + 异步搜索美股代码 + + Args: + keyword: 搜索关键词 + + Returns: + 匹配的股票列表 + """ + try: + logger.info(f"异步搜索美股: {keyword}") + + # 使用线程池执行同步的akshare调用 + df = await asyncio.to_thread(self._get_us_stocks_data) + + # 模糊匹配搜索 + mask = df['name'].str.contains(keyword, case=False, na=False) + results = df[mask] + + # 格式化返回结果并处理 NaN 值 + formatted_results = [] + for _, row in results.iterrows(): + formatted_results.append({ + 'name': row['name'] if pd.notna(row['name']) else '', + 'symbol': str(row['symbol']) if pd.notna(row['symbol']) else '', + 'price': float(row['price']) if pd.notna(row['price']) else 0.0, + 'market_value': float(row['market_value']) if pd.notna(row['market_value']) else 0.0 + }) + + logger.info(f"美股搜索完成，找到 {len(formatted_results)} 个匹配项") + return formatted_results + + except Exception as e: + error_msg = f"搜索美股代码失败: {str(e)}" + logger.error(error_msg) + logger.exception(e) + raise Exception(error_msg) + + def _get_us_stocks_data(self) -> pd.DataFrame: + """ + 获取美股数据（同步方法，将被异步方法调用） + + Returns: + 包含美股数据的DataFrame + """ + import akshare as ak + + try: + # 获取美股数据 + df = ak.stock_us_spot_em() + + # 转换列名 + df = df.rename(columns={ + "序号": "index", + "名称": "name", + "最新价": "price", + "涨跌额": "price_change", + "涨跌幅": "price_change_percent", + "开盘价": "open", + "最高价": "high", + "最低价": "low", + "昨收价": "pre_close", + "总市值": "market_value", + "市盈率": "pe_ratio", + "成交量": "volume", + "成交额": "turnover", + "振幅": "amplitude", + "换手率": "turnover_rate", + "代码": "symbol" + }) + + return df + + except Exception as e: + logger.error(f"获取美股数据失败: {str(e)}") + logger.exception(e) + raise Exception(f"获取美股数据失败: {str(e)}") + + async def get_us_stock_detail(self, symbol: str) -> Dict[str, Any]: + """ + 异步获取单个美股详细信息 + + Args: + symbol: 股票代码 + + Returns: + 股票详细信息 + """ + try: + logger.info(f"获取美股详情: {symbol}") + + # 使用线程池执行同步的akshare调用 + df = await asyncio.to_thread(self._get_us_stocks_data) + + # 精确匹配股票代码 + result = df[df['symbol'] == symbol] + + if len(result) == 0: + raise Exception(f"未找到股票代码: {symbol}") + + # 获取第一行数据 + row = result.iloc[0] + + # 格式化为字典 + stock_detail = { + 'name': row['name'] if pd.notna(row['name']) else '', + 'symbol': str(row['symbol']) if pd.notna(row['symbol']) else '', + 'price': float(row['price']) if pd.notna(row['price']) else 0.0, + 'price_change': float(row['price_change']) if pd.notna(row['price_change']) else 0.0, + 'price_change_percent': float(row['price_change_percent'].strip('%'))/100 if pd.notna(row['price_change_percent']) else 0.0, + 'open': float(row['open']) if pd.notna(row['open']) else 0.0, + 'high': float(row['high']) if pd.notna(row['high']) else 0.0, + 'low': float(row['low']) if pd.notna(row['low']) else 0.0, + 'pre_close': float(row['pre_close']) if pd.notna(row['pre_close']) else 0.0, + 'market_value': float(row['market_value']) if pd.notna(row['market_value']) else 0.0, + 'pe_ratio': float(row['pe_ratio']) if pd.notna(row['pe_ratio']) else 0.0, + 'volume': float(row['volume']) if pd.notna(row['volume']) else 0.0, + 'turnover': float(row['turnover']) if pd.notna(row['turnover']) else 0.0 + } + + logger.info(f"获取美股详情成功: {symbol}") + return stock_detail + + except Exception as e: + error_msg = f"获取美股详情失败: {str(e)}" + logger.error(error_msg) + logger.exception(e) + raise Exception(error_msg) \ No newline at end of file diff --git a/web_server.py b/web_server.py index c761334..5550a49 100644 --- a/web_server.py +++ b/web_server.py @@ -3,10 +3,11 @@ from fastapi.responses import JSONResponse, StreamingResponse, FileResponse, Red from fastapi.staticfiles import StaticFiles from fastapi.middleware.cors import CORSMiddleware from pydantic import BaseModel, Field -from typing import List, Optional, Generator -from stock_analyzer import StockAnalyzer -from us_stock_service import USStockService -from fund_service import FundService +from typing import List, Optional, Dict, Any, Generator +from services.stock_analyzer_service import StockAnalyzerService +# 导入新的异步服务 +from services.us_stock_service_async import USStockServiceAsync +from services.fund_service_async import FundServiceAsync import asyncio import threading import os @@ -25,7 +26,7 @@ logger = get_logger() app = FastAPI( title="Stock Scanner API", - description="股票分析API", + description="异步股票分析API", version="1.0.0" ) @@ -43,9 +44,10 @@ frontend_dist = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'fronte if os.path.exists(frontend_dist): app.mount("/", StaticFiles(directory=frontend_dist, html=True), name="frontend") -analyzer = StockAnalyzer() -us_stock_service = USStockService() -fund_service = FundService() +# 初始化异步服务 +# StockAnalyzerService 不需要全局初始化，在 /analyze 接口中按需创建 +us_stock_service = USStockServiceAsync() +fund_service = FundServiceAsync() # 定义请求和响应模型 class AnalyzeRequest(BaseModel): @@ -102,7 +104,7 @@ async def analyze(request: AnalyzeRequest): logger.debug(f"自定义API配置: URL={custom_api_url}, 模型={custom_api_model}, API Key={'已提供' if custom_api_key else '未提供'}, Timeout={custom_api_timeout}") # 创建新的分析器实例，使用自定义配置 - custom_analyzer = StockAnalyzer( + custom_analyzer = StockAnalyzerService( custom_api_url=custom_api_url, custom_api_key=custom_api_key, custom_api_model=custom_api_model, @@ -126,17 +128,11 @@ async def analyze(request: AnalyzeRequest): logger.debug(f"开始处理股票 {stock_code} 的流式响应") chunk_count = 0 - # 使用线程池执行同步分析 - def run_analysis(): - return list(custom_analyzer.analyze_stock(stock_code, market_type, stream=True)) - - # 在线程中执行同步操作 - loop = asyncio.get_event_loop() - chunks = await loop.run_in_executor(None, run_analysis) - - for chunk in chunks: + # 使用异步生成器 + async for chunk in custom_analyzer.analyze_stock(stock_code, market_type, stream=True): chunk_count += 1 yield chunk + '\n' + logger.info(f"股票 {stock_code} 流式分析完成，共发送 {chunk_count} 个块") else: # 批量分析流式处理 @@ -148,22 +144,16 @@ async def analyze(request: AnalyzeRequest): logger.debug(f"开始处理批量股票的流式响应") chunk_count = 0 - # 使用线程池执行同步分析 - def run_batch_analysis(): - return list(custom_analyzer.scan_stocks( - [code.strip() for code in stock_codes], - min_score=0, - market_type=market_type, - stream=True - )) - - # 在线程中执行同步操作 - loop = asyncio.get_event_loop() - chunks = await loop.run_in_executor(None, run_batch_analysis) - - for chunk in chunks: + # 使用异步生成器 + async for chunk in custom_analyzer.scan_stocks( + [code.strip() for code in stock_codes], + min_score=0, + market_type=market_type, + stream=True + ): chunk_count += 1 yield chunk + '\n' + logger.info(f"批量流式分析完成，共发送 {chunk_count} 个块") logger.info("成功创建流式响应生成器") @@ -181,9 +171,8 @@ async def search_us_stocks(keyword: str = ""): if not keyword: raise HTTPException(status_code=400, detail="请输入搜索关键词") - # 在异步上下文中运行同步的搜索函数 - loop = asyncio.get_event_loop() - results = await loop.run_in_executor(None, us_stock_service.search_us_stocks, keyword) + # 直接使用异步服务的异步方法 + results = await us_stock_service.search_us_stocks(keyword) return {"results": results} except Exception as e: @@ -196,9 +185,8 @@ async def search_funds(keyword: str = "", market_type: str = ""): if not keyword: raise HTTPException(status_code=400, detail="请输入搜索关键词") - # 在异步上下文中运行同步的搜索函数 - loop = asyncio.get_event_loop() - results = await loop.run_in_executor(None, lambda: fund_service.search_funds(keyword, market_type)) + # 直接使用异步服务的异步方法 + results = await fund_service.search_funds(keyword, market_type) return {"results": results} except Exception as e: @@ -273,6 +261,36 @@ async def test_api_connection(request: TestAPIRequest): content={"success": False, "message": f"API 测试连接时出错: {str(e)}"} ) +# 新增 API 端点：获取美股详情 +@app.get("/us_stock_detail/{symbol}") +async def get_us_stock_detail(symbol: str): + try: + if not symbol: + raise HTTPException(status_code=400, detail="请提供股票代码") + + # 使用异步服务获取详情 + detail = await us_stock_service.get_us_stock_detail(symbol) + return detail + + except Exception as e: + logger.error(f"获取美股详情时出错: {str(e)}") + raise HTTPException(status_code=500, detail=str(e)) + +# 新增 API 端点：获取基金详情 +@app.get("/fund_detail/{symbol}") +async def get_fund_detail(symbol: str, market_type: str = "ETF"): + try: + if not symbol: + raise HTTPException(status_code=400, detail="请提供基金代码") + + # 使用异步服务获取详情 + detail = await fund_service.get_fund_detail(symbol, market_type) + return detail + + except Exception as e: + logger.error(f"获取基金详情时出错: {str(e)}") + raise HTTPException(status_code=500, detail=str(e)) + if __name__ == '__main__': logger.info("股票分析系统启动") uvicorn.run("web_server:app", host="127.0.0.1", port=8888, reload=True) \ No newline at end of file From 5444edf680bdf39c98d9f2731227d8d25a6842c8 Mon Sep 17 00:00:00 2001 From: Cassianvale Date: Thu, 6 Mar 2025 18:23:44 +0800 Subject: [PATCH 05/17] Update stock_analyzer_service.py --- services/stock_analyzer_service.py | 58 ++++++++++++++++++++++++++++-- 1 file changed, 55 insertions(+), 3 deletions(-) diff --git a/services/stock_analyzer_service.py b/services/stock_analyzer_service.py index 91df74a..2e24a72 100644 --- a/services/stock_analyzer_service.py +++ b/services/stock_analyzer_service.py @@ -2,6 +2,7 @@ import pandas as pd import numpy as np import asyncio import json +from datetime import datetime from typing import Dict, List, Optional, Tuple, Any, AsyncGenerator from logger import get_logger from services.stock_data_provider import StockDataProvider @@ -66,13 +67,64 @@ class StockAnalyzerService: score = self.scorer.calculate_score(df_with_indicators) recommendation = self.scorer.get_recommendation(score) + # 获取最新数据 + latest_data = df_with_indicators.iloc[-1] + previous_data = df_with_indicators.iloc[-2] if len(df_with_indicators) > 1 else latest_data + + # 计算价格变化百分比 + price_change = ((latest_data['Close'] - previous_data['Close']) / previous_data['Close']) * 100 + + # 确定MA趋势 + ma_short = latest_data.get('MA5', 0) + ma_medium = latest_data.get('MA20', 0) + ma_long = latest_data.get('MA60', 0) + + if ma_short > ma_medium > ma_long: + ma_trend = "UP" + elif ma_short < ma_medium < ma_long: + ma_trend = "DOWN" + else: + ma_trend = "FLAT" + + # 确定MACD信号 + macd = latest_data.get('MACD', 0) + signal = latest_data.get('Signal', 0) + + if macd > signal: + macd_signal = "BUY" + elif macd < signal: + macd_signal = "SELL" + else: + macd_signal = "HOLD" + + # 确定成交量状态 + volume = latest_data.get('Volume', 0) + volume_ma = latest_data.get('Volume_MA', 0) + + if volume > volume_ma * 1.5: + volume_status = "HIGH" + elif volume < volume_ma * 0.5: + volume_status = "LOW" + else: + volume_status = "NORMAL" + + # 当前分析日期 + analysis_date = datetime.now().strftime('%Y-%m-%d') + # 生成基本分析结果 basic_result = { "stock_code": stock_code, + "market_type": market_type, + "analysis_date": analysis_date, "score": score, + "price": latest_data['Close'], + "price_change": price_change, + "ma_trend": ma_trend, + "rsi": latest_data.get('RSI', 0), + "macd_signal": macd_signal, + "volume_status": volume_status, "recommendation": recommendation, - "data_point_count": len(df), - "market_type": market_type + "ai_analysis": "" } # 输出基本分析结果 @@ -175,4 +227,4 @@ class StockAnalyzerService: error_msg = f"批量扫描股票时出错: {str(e)}" logger.error(error_msg) logger.exception(e) - yield json.dumps({"error": error_msg}) \ No newline at end of file + yield json.dumps({"error": error_msg}) From 9246e7f02b1b773c8828907383f8e528bbcd4c02 Mon Sep 17 00:00:00 2001 From: Cassianvale Date: Thu, 6 Mar 2025 19:04:23 +0800 Subject: [PATCH 06/17] =?UTF-8?q?feat:=20=E5=A2=9E=E5=8A=A0=E6=97=A5?= =?UTF-8?q?=E5=BF=97?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- frontend/src/components/StockAnalysisApp.vue | 4 +++- services/ai_analyzer.py | 7 ++++++- 2 files changed, 9 insertions(+), 2 deletions(-) diff --git a/frontend/src/components/StockAnalysisApp.vue b/frontend/src/components/StockAnalysisApp.vue index 385523b..e852e01 100644 --- a/frontend/src/components/StockAnalysisApp.vue +++ b/frontend/src/components/StockAnalysisApp.vue @@ -162,7 +162,9 @@ const apiConfig = ref({ const marketOptions = [ { label: 'A股', value: 'A' }, { label: '港股', value: 'HK' }, - { label: '美股', value: 'US' } + { label: '美股', value: 'US' }, + { label: 'ETF', value: 'ETF' }, + { label: 'LOF', value: 'LOF' } ]; // 更新API配置 diff --git a/services/ai_analyzer.py b/services/ai_analyzer.py index 93c063f..f1d6049 100644 --- a/services/ai_analyzer.py +++ b/services/ai_analyzer.py @@ -54,14 +54,19 @@ class AIAnalyzer: """ try: logger.info(f"开始AI分析 {stock_code}, 流式模式: {stream}") + + # AI 分析内容 + # 最近14天的股票数据记录 recent_data = df.tail(14).to_dict('records') + # 包含trend, volatility, volume_trend, rsi_level的字典 technical_summary = { 'trend': 'upward' if df.iloc[-1]['MA5'] > df.iloc[-1]['MA20'] else 'downward', 'volatility': f"{df.iloc[-1]['Volatility']:.2f}%", 'volume_trend': 'increasing' if df.iloc[-1]['Volume_Ratio'] > 1 else 'decreasing', 'rsi_level': df.iloc[-1]['RSI'] } + print(recent_data, technical_summary) # 根据市场类型调整分析提示 if market_type in ['ETF', 'LOF']: @@ -210,7 +215,7 @@ class AIAnalyzer: # 尝试从整个内容中提取JSON full_content = "".join(collected_messages) - + print(f"尝试从整个内容中提取JSON: {full_content}") # 如果没有成功解析JSON，返回原始内容 if not full_content.strip().startswith("{"): yield json.dumps({ From 35cf295b29b1746f2c6415308017e5655536ccf8 Mon Sep 17 00:00:00 2001 From: Cassianvale Date: Thu, 6 Mar 2025 19:38:36 +0800 Subject: [PATCH 07/17] Update ai_analyzer.py --- services/ai_analyzer.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/services/ai_analyzer.py b/services/ai_analyzer.py index f1d6049..73ba626 100644 --- a/services/ai_analyzer.py +++ b/services/ai_analyzer.py @@ -66,7 +66,6 @@ class AIAnalyzer: 'volume_trend': 'increasing' if df.iloc[-1]['Volume_Ratio'] > 1 else 'decreasing', 'rsi_level': df.iloc[-1]['RSI'] } - print(recent_data, technical_summary) # 根据市场类型调整分析提示 if market_type in ['ETF', 'LOF']: @@ -197,7 +196,7 @@ class AIAnalyzer: if len(buffer) > 100: yield json.dumps({ "stock_code": stock_code, - "partial_content": buffer + "ai_analysis_chunk": buffer }) collected_messages.append(buffer) buffer = "" @@ -209,13 +208,13 @@ class AIAnalyzer: if buffer: yield json.dumps({ "stock_code": stock_code, - "partial_content": buffer + "ai_analysis_chunk": buffer }) collected_messages.append(buffer) # 尝试从整个内容中提取JSON full_content = "".join(collected_messages) - print(f"尝试从整个内容中提取JSON: {full_content}") + # 如果没有成功解析JSON，返回原始内容 if not full_content.strip().startswith("{"): yield json.dumps({ From ff5b820a579b6259d36ebaeb806afb8897bcfb26 Mon Sep 17 00:00:00 2001 From: Cassianvale Date: Thu, 6 Mar 2025 20:30:54 +0800 Subject: [PATCH 08/17] =?UTF-8?q?fix:=20=E4=BF=AE=E5=A4=8D=E5=89=8D?= =?UTF-8?q?=E7=AB=AF=E6=98=BE=E7=A4=BA=E9=97=AE=E9=A2=98?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- frontend/src/components/StockAnalysisApp.vue | 335 ++++++++++++++++++- frontend/src/components/StockCard.vue | 30 ++ services/ai_analyzer.py | 311 ++++++++++++----- services/stock_analyzer_service.py | 49 ++- 4 files changed, 608 insertions(+), 117 deletions(-) diff --git a/frontend/src/components/StockAnalysisApp.vue b/frontend/src/components/StockAnalysisApp.vue index e852e01..4b580a0 100644 --- a/frontend/src/components/StockAnalysisApp.vue +++ b/frontend/src/components/StockAnalysisApp.vue @@ -76,6 +76,45 @@
+
+ + 分析结果 ({{ analyzedStocks.length }}) + + + + 复制结果 + + + + 导出 + + + + + +
+