Merge branch 'pr-1' into dev

# Conflicts:
#	stock_analyzer.py
#	templates/index.html

.gitignore

@@ -1,2 +1,183 @@
-logs/*
+# log
-.*
+logs/
+*.log
+
+# Custom
+.vs/
+.vscode/
+.idea/
+.conda/
+.vs/
+.vscode/
+.idea/
+AppData/
+output/
+dist/
+main.build/
+main.dist/
+main.onefile-build/
+build_upload.log
+*report.xml
+*.spec
+*.zip
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

stock_analyzer.py

@@ -47,8 +47,25 @@ class StockAnalyzer:
             end_date = datetime.now().strftime('%Y%m%d')
             
         try:
-            # 根据市场类型获取数据
+            # 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)
+
                 df = ak.stock_zh_a_hist(
                     symbol=stock_code,
                     start_date=start_date,
@@ -108,8 +125,13 @@ class StockAnalyzer:
             
             return df.sort_values('date')
             
+        # except ValueError as ve:
+        #     # 捕获格式验证错误
+        #     logger.error(f"[股票代码格式错误] {str(ve)}")
+        #     raise Exception(f"股票代码格式错误: {str(ve)}")
         except Exception as e:
-            raise Exception(f"获取股票数据失败: {str(e)}")
+            logger.error(f"[获取数据失败] {str(e)}")
+            raise Exception(f"获取数据失败: {str(e)}")
             
     def calculate_ema(self, series, period):
         """计算指数移动平均线"""
@@ -192,7 +214,7 @@ class StockAnalyzer:
             raise
             
     def calculate_score(self, df):
-        """计算股票评分"""
+        """计算评分"""
         try:
             score = 0
             latest = df.iloc[-1]
@@ -325,12 +347,12 @@ class StockAnalyzer:
             # 检查API配置
             if not self.API_URL:
                 error_msg = "API URL未配置，无法进行AI分析"
-                logger.error(error_msg)
+                logger.error(f"[API配置错误] {error_msg}")
                 return error_msg if not stream else (yield json.dumps({"error": error_msg}))
                 
             if not self.API_KEY:
                 error_msg = "API Key未配置，无法进行AI分析"
-                logger.error(error_msg)
+                logger.error(f"[API配置错误] {error_msg}")
                 return error_msg if not stream else (yield json.dumps({"error": error_msg}))
             
             # 标准化API URL
@@ -379,12 +401,12 @@ class StockAnalyzer:
                             error_text = response.text[:500] if response.text else "无响应内容"
                             
                         error_msg = f"API请求失败: 状态码 {response.status_code}, 响应: {error_text}"
-                        logger.error(error_msg)
+                        logger.error(f"[API请求失败] {error_msg}")
                         yield json.dumps({"stock_code": stock_code, "error": error_msg})
                         
                 except Exception as e:
                     error_msg = f"流式API请求异常: {str(e)}"
-                    logger.error(error_msg)
+                    logger.error(f"[流式API异常] {error_msg}")
                     logger.exception(e)
                     yield json.dumps({"stock_code": stock_code, "error": error_msg})
             else:
@@ -415,18 +437,18 @@ class StockAnalyzer:
                             error_text = response.text[:500] if response.text else "无响应内容"
                             
                         error_msg = f"API请求失败: 状态码 {response.status_code}, 响应: {error_text}"
-                        logger.error(error_msg)
+                        logger.error(f"[API请求失败] {error_msg}")
                         return error_msg
                         
                 except Exception as e:
                     error_msg = f"非流式API请求异常: {str(e)}"
-                    logger.error(error_msg)
+                    logger.error(f"[非流式API异常] {error_msg}")
                     logger.exception(e)
                     return error_msg
             
         except Exception as e:
             error_msg = f"AI 分析过程中发生错误: {str(e)}"
-            logger.error(error_msg)
+            logger.error(f"[AI分析异常] {error_msg}")
             logger.exception(e)
             
             if stream:
@@ -495,7 +517,7 @@ class StockAnalyzer:
                                     })
                                     yield chunk_json
                         except json.JSONDecodeError as e:
-                            logger.error(f"JSON解析错误: {str(e)}, 行内容: {data_content}")
+                            logger.error(f"[JSON解析错误] {str(e)}, 行内容: {data_content}")
                             # 忽略无法解析的JSON
                             pass
                     else:
@@ -510,7 +532,7 @@ class StockAnalyzer:
         
         except Exception as e:
             error_msg = f"处理AI流式响应时出错: {str(e)}"
-            logger.error(error_msg)
+            logger.error(f"[流式响应异常] {error_msg}")
             logger.exception(e)
             yield json.dumps({"stock_code": stock_code, "error": error_msg})
 
@@ -530,13 +552,48 @@ class StockAnalyzer:
             return '强烈建议卖出'
     
     def analyze_stock(self, stock_code, market_type='A', stream=False):
-        """分析股票或基金"""
+        """分析单只"""
-        try:
+        logger.info(f"开始分析 {stock_code}, 市场类型: {market_type}, 流式模式: {stream}")
-            logger.info(f"开始分析: {stock_code}, 市场: {market_type}, 流式模式: {stream}")
         
-            # 获取数据
+        try:
-            logger.debug(f"获取 {stock_code} 数据")
+            # 获取股票数据
+            try:
                 df = self.get_stock_data(stock_code, market_type)
+            except Exception as e:
+                # 捕获股票数据获取异常
+                error_msg = str(e)
+                logger.error(f"[数据获取异常] {error_msg}")
+                
+                # 格式化错误响应
+                error_response = {
+                    'stock_code': stock_code, 
+                    'error': error_msg,
+                    'status': 'error',
+                    'timestamp': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+                }
+                
+                if stream:
+                    return (yield json.dumps(error_response))
+                else:
+                    return error_response
+            
+            # 检查数据是否为空
+            if df.empty:
+                error_msg = f" {stock_code} 数据为空"
+                logger.error(f"[空数据] {error_msg}")
+                
+                # 格式化错误响应
+                error_response = {
+                    'stock_code': stock_code, 
+                    'error': error_msg,
+                    'status': 'error',
+                    'timestamp': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+                }
+                
+                if stream:
+                    return (yield json.dumps(error_response))
+                else:
+                    return error_response
             
             # 计算技术指标
             logger.debug(f"计算 {stock_code} 技术指标")
@@ -592,61 +649,109 @@ class StockAnalyzer:
                 return report
             
         except Exception as e:
-            error_msg = f"分析 {stock_code} 时出错: {str(e)}"
+            error_msg = f"分析 {stock_code} 时出错: {str(e)}\n"
-            logger.error(error_msg)
+            logger.error(f"[分析异常] {error_msg}")
             logger.exception(e)
             
-            if stream:
+            # 格式化错误响应
-                error_json = json.dumps({'stock_code': stock_code, 'error': error_msg})
+            error_response = {
-                logger.info(f"流式错误输出: {error_json}")
+                'stock_code': stock_code, 
-                yield error_json
+                'error': error_msg,
-            else:
+                'status': 'error',
-                raise
+                'timestamp': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+            }
             
-    def scan_market(self, stock_list, min_score=60, market_type='A', stream=False):
+            if stream:
-        """扫描市场，寻找符合条件的"""
+                return (yield json.dumps(error_response))
-        logger.info(f"开始扫描市场，数量: {len(stock_list)}, 最低分数: {min_score}, 市场: {market_type}, 流式模式: {stream}")
+            else:
+                return error_response
+            
+    def scan_stocks(self, stock_codes, market_type='A', min_score=60, stream=False):
+        """扫描多只"""
+        logger.info(f"开始扫描 {len(stock_codes)} 只, 市场类型: {market_type}, 最低评分: {min_score}, 流式模式: {stream}")
         
         if not stream:
-            recommendations = []
+            # 非流式模式
+            recommended_stocks = []
+            stock_count = 0
+            error_count = 0
+            
+            for stock_code in stock_codes:
+                stock_count += 1
+                logger.info(f"扫描进度: {stock_count}/{len(stock_codes)}, 当前: {stock_code}")
                 
-            for stock_code in stock_list:
                 try:
                     logger.debug(f"分析: {stock_code}")
                     report = self.analyze_stock(stock_code, market_type)
+                    
+                    # 检查是否有错误
+                    if isinstance(report, dict) and 'error' in report:
+                        error_count += 1
+                        logger.warning(f"[扫描错误]  {stock_code}: {report['error']}")
+                        continue
+                    
+                    # 检查评分是否达到最低要求
                     if report['score'] >= min_score:
                         logger.info(f" {stock_code} 评分 {report['score']} >= {min_score}，添加到推荐列表")
-                        recommendations.append(report)
+                        recommended_stocks.append(report)
                     else:
                         logger.debug(f" {stock_code} 评分 {report['score']} < {min_score}，不添加到推荐列表")
                 except Exception as e:
-                    logger.error(f"分析 {stock_code} 时出错: {str(e)}")
+                    error_count += 1
+                    error_msg = f"分析 {stock_code} 时出错: {str(e)}"
+                    logger.error(f"[扫描异常] {error_msg}")
                     logger.exception(e)
+                    
+                    # 添加错误信息到推荐列表，确保前端能看到错误
+                    error_response = {
+                        'stock_code': stock_code, 
+                        'error': error_msg,
+                        'status': 'error',
+                        'timestamp': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+                    }
+                    recommended_stocks.append(error_response)
                     continue
             
-            # 按得分排序
+            logger.info(f"扫描完成，共 {stock_count} 只，{error_count} 只出错，{len(recommended_stocks)} 只推荐")
-            recommendations.sort(key=lambda x: x['score'], reverse=True)
+            return recommended_stocks
-            logger.info(f"扫描完成，找到 {len(recommendations)} 个推荐股票")
-            return recommendations
         else:
-            # 流式处理每个股票
+            # 流式模式
-            logger.info(f"开始流式扫描 {len(stock_list)} 只股票")
             stock_count = 0
-            for stock_code in stock_list:
+            error_count = 0
+            
+            for stock_code in stock_codes:
                 stock_count += 1
-                logger.debug(f"流式分析 {stock_code} ({stock_count}/{len(stock_list)})")
+                logger.info(f"流式扫描进度: {stock_count}/{len(stock_codes)}, 当前: {stock_code}")
+                
                 try:
-                    # 分析单只股票并获取流式结果
                     chunk_count = 0
                     for chunk in self.analyze_stock(stock_code, market_type, stream=True):
                         chunk_count += 1
+                        # 检查是否有错误信息
+                        try:
+                            chunk_data = json.loads(chunk)
+                            if 'error' in chunk_data:
+                                error_count += 1
+                                logger.warning(f"[流式扫描错误]  {stock_code}: {chunk_data['error']}")
+                        except:
+                            pass
                         yield chunk
                     logger.debug(f" {stock_code} 流式分析完成，共 {chunk_count} 个块")
                 except Exception as e:
+                    error_count += 1
                     error_msg = f"分析 {stock_code} 时出错: {str(e)}"
-                    logger.error(error_msg)
+                    logger.error(f"[流式扫描异常] {error_msg}")
                     logger.exception(e)
-                    error_json = json.dumps({'stock_code': stock_code, 'error': error_msg})
+                    
+                    # 格式化错误响应
+                    error_response = {
+                        'stock_code': stock_code, 
+                        'error': error_msg,
+                        'status': 'error',
+                        'timestamp': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+                    }
+                    error_json = json.dumps(error_response)
                     logger.info(f"流式错误输出: {error_json}")
                     yield error_json
-            logger.info(f"流式扫描完成，处理了 {stock_count} 只股票")
+            
+            logger.info(f"流式扫描完成，共处理 {stock_count} ，{error_count} 只出错")

templates/index.html

@@ -724,14 +724,56 @@
             if (chunk.error) {
                 // 添加或更新显示错误的卡片
                 let errorCard = document.getElementById(`error-${stockCode}`);
+                
+                // 处理错误信息，提取关键部分
+                let errorMessage = chunk.error;
+                
+                // 移除多余的错误前缀
+                errorMessage = errorMessage.replace(/获取股票数据失败: /g, '');
+                
+                // 格式化错误信息
+                let formattedError = errorMessage;
+                
+                // 针对特定类型的错误提供更友好的提示
+                if (errorMessage.includes('无效的A股股票代码格式')) {
+                    formattedError = `<strong>股票代码格式错误</strong>: ${stockCode} 不是有效的A股代码<br>
+                                     <small>A股代码应以0、3、6、688或8开头</small>`;
+                } else if (errorMessage.includes('股票代码格式错误')) {
+                    formattedError = `<strong>股票代码格式错误</strong>: ${errorMessage.split(':')[1] || errorMessage}`;
+                } else if (errorMessage.includes('数据为空')) {
+                    formattedError = `<strong>数据获取失败</strong>: 未找到股票 ${stockCode} 的交易数据`;
+                }
+                
                 if (!errorCard) {
                     errorCard = document.createElement('div');
                     errorCard.id = `error-${stockCode}`;
-                    errorCard.className = 'bg-red-50 p-4 rounded-lg text-red-600';
+                    errorCard.className = 'bg-red-50 p-4 rounded-lg text-red-600 mb-4 flex items-start';
-                    errorCard.innerHTML = `分析 ${stockCode} 出错: ${chunk.error}`;
+                    
+                    // 添加警告图标
+                    errorCard.innerHTML = `
+                        <div class="mr-3 flex-shrink-0">
+                            <svg class="h-5 w-5 text-red-500" fill="currentColor" viewBox="0 0 20 20">
+                                <path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zM8.707 7.293a1 1 0 00-1.414 1.414L8.586 10l-1.293 1.293a1 1 0 101.414 1.414L10 11.414l1.293 1.293a1 1 0 001.414-1.414L11.414 10l1.293-1.293a1 1 0 00-1.414-1.414L10 8.586 8.707 7.293z" clip-rule="evenodd"></path>
+                            </svg>
+                        </div>
+                        <div>
+                            <p class="text-sm font-medium">股票 ${stockCode} 分析失败</p>
+                            <p class="mt-1 text-sm">${formattedError}</p>
+                        </div>
+                    `;
                     container.appendChild(errorCard);
                 } else {
-                    errorCard.innerHTML = `分析 ${stockCode} 出错: ${chunk.error}`;
+                    errorCard.innerHTML = `
+                        <div class="mr-3 flex-shrink-0">
+                            <svg class="h-5 w-5 text-red-500" fill="currentColor" viewBox="0 0 20 20">
+                                <path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zM8.707 7.293a1 1 0 00-1.414 1.414L8.586 10l-1.293 1.293a1 1 0 101.414 1.414L10 11.414l1.293 1.293a1 1 0 001.414-1.414L11.414 10l1.293-1.293a1 1 0 00-1.414-1.414L10 8.586 8.707 7.293z" clip-rule="evenodd"></path>
+                            </svg>
+                        </div>
+                        <div>
+                            <p class="text-sm font-medium">股票 ${stockCode} 分析失败</p>
+                            <p class="mt-1 text-sm">${formattedError}</p>
+                        </div>
+                    `;
                 }
                 return;
             }

web_server.py

@@ -90,7 +90,7 @@ 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_market(
+                for chunk in custom_analyzer.scan_stocks(
                     [code.strip() for code in stock_codes], 
                     min_score=0, 
                     market_type=market_type,