diff --git a/.gitignore b/.gitignore
index 399ad79..db3d017 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,183 @@
-logs/*
-.*
\ No newline at end of file
+# 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/
diff --git a/stock_analyzer.py b/stock_analyzer.py
index a1fd87c..1d92aaa 100644
--- a/stock_analyzer.py
+++ b/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"""
+ logger.info(f"开始分析 {stock_code}, 市场类型: {market_type}, 流式模式: {stream}")
+
try:
- logger.info(f"开始分析: {stock_code}, 市场: {market_type}, 流式模式: {stream}")
+ # 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
- # 获取数据
- logger.debug(f"获取 {stock_code} 数据")
- df = self.get_stock_data(stock_code, market_type)
+ # 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)}"
- logger.error(error_msg)
+ error_msg = f"分析 {stock_code} 时出错: {str(e)}\n"
+ logger.error(f"[分析异常] {error_msg}")
logger.exception(e)
- if stream:
- error_json = json.dumps({'stock_code': stock_code, 'error': error_msg})
- logger.info(f"流式错误输出: {error_json}")
- yield error_json
- else:
- raise
+ # 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')
+ }
- def scan_market(self, stock_list, min_score=60, market_type='A', stream=False):
- """扫描市场，寻找符合条件的"""
- 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}")
+ if stream:
+ return (yield json.dumps(error_response))
+ 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_list:
+ 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}")
+
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)
- continue
- # 按得分排序
- recommendations.sort(key=lambda x: x['score'], reverse=True)
- logger.info(f"扫描完成，找到 {len(recommendations)} 个推荐股票")
- return recommendations
+ # 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
+
+ logger.info(f"扫描完成，共 {stock_count} 只，{error_count} 只出错，{len(recommended_stocks)} 只推荐")
+ return recommended_stocks
else:
- # 流式处理每个股票
- logger.info(f"开始流式扫描 {len(stock_list)} 只股票")
+ # 流式模式
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")
diff --git a/templates/index.html b/templates/index.html
index 86b7295..0f159c7 100644
--- a/templates/index.html
+++ b/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 = `股票代码格式错误: ${stockCode} 不是有效的A股代码
+ A股代码应以0、3、6、688或8开头`;
+ } else if (errorMessage.includes('股票代码格式错误')) {
+ formattedError = `股票代码格式错误: ${errorMessage.split(':')[1] || errorMessage}`;
+ } else if (errorMessage.includes('数据为空')) {
+ formattedError = `数据获取失败: 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.innerHTML = `分析 ${stockCode} 出错: ${chunk.error}`;
+ errorCard.className = 'bg-red-50 p-4 rounded-lg text-red-600 mb-4 flex items-start';
+
+ // 添加警告图标
+ errorCard.innerHTML = `
+
+
+
股票 ${stockCode} 分析失败
+
${formattedError}
+
+
股票 ${stockCode} 分析失败
+
${formattedError}
+