diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..ed99415 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,27 @@ +# 使用 Python 3.9 作为基础镜像 +FROM python:3.10-slim + +# 设置工作目录 +WORKDIR /app + +# 安装系统依赖 +RUN apt-get update && apt-get install -y \ + libgl1-mesa-glx \ + ca-certificates \ + && rm -rf /var/lib/apt/lists/* + +# 复制项目文件 +COPY . /app/ + +# 安装 Python 依赖 +RUN pip install --no-cache-dir -r requirements.txt +RUN pip install akshare --upgrade -i https://pypi.org/simple + +# 设置环境变量 +ENV PYTHONPATH=/app + +# 暴露端口（如果需要） +EXPOSE 8888 + +# 启动命令 +CMD ["python", "web_server.py"] \ No newline at end of file diff --git a/gui.py b/gui.py deleted file mode 100644 index 57b16f1..0000000 --- a/gui.py +++ /dev/null @@ -1,218 +0,0 @@ -import sys -from PyQt6.QtWidgets import (QApplication, QMainWindow, QWidget, QVBoxLayout, - QHBoxLayout, QLineEdit, QPushButton, QTextBrowser, - QLabel, QTextEdit, QMessageBox, QProgressBar) -from PyQt6.QtCore import Qt, QThread, pyqtSignal -from PyQt6.QtGui import QFont -import markdown2 -from stock_analyzer import StockAnalyzer # 导入股票分析器 - -class AnalysisWorker(QThread): - """后台工作线程，用于执行分析任务""" - finished = pyqtSignal(dict) - error = pyqtSignal(str) - progress = pyqtSignal(int) - - def __init__(self, analyzer, stock_code): - super().__init__() - self.analyzer = analyzer - self.stock_code = stock_code - - def run(self): - try: - report = self.analyzer.analyze_stock(self.stock_code) - self.finished.emit(report) - except Exception as e: - self.error.emit(str(e)) - -class BatchAnalysisWorker(QThread): - """后台工作线程，用于执行批量分析任务""" - finished = pyqtSignal(list) - error = pyqtSignal(str) - progress = pyqtSignal(int) - - def __init__(self, analyzer, stock_list): - super().__init__() - self.analyzer = analyzer - self.stock_list = stock_list - - def run(self): - try: - results = [] - total = len(self.stock_list) - for i, stock_code in enumerate(self.stock_list): - report = self.analyzer.analyze_stock(stock_code) - results.append(report) - self.progress.emit(int((i + 1) / total * 100)) - self.finished.emit(results) - except Exception as e: - self.error.emit(str(e)) - -class StockAnalyzerGUI(QMainWindow): - def __init__(self): - super().__init__() - self.analyzer = StockAnalyzer() - self.initUI() - - def initUI(self): - self.setWindowTitle('股票分析系统') - self.setGeometry(100, 100, 1200, 800) - - # 创建中央部件和布局 - central_widget = QWidget() - self.setCentralWidget(central_widget) - layout = QVBoxLayout(central_widget) - - # 创建输入区域 - input_layout = QHBoxLayout() - - # 单只股票分析部分 - single_stock_layout = QVBoxLayout() - single_label = QLabel('单只股票分析:') - single_label.setFont(QFont('Arial', 12, QFont.Weight.Bold)) - self.single_stock_input = QLineEdit() - self.single_stock_input.setPlaceholderText('输入股票代码（如：600000）') - self.single_stock_input.setFont(QFont('Arial', 10)) - self.analyze_btn = QPushButton('分析') - self.analyze_btn.setFont(QFont('Arial', 10, QFont.Weight.Bold)) - self.analyze_btn.clicked.connect(self.analyze_single_stock) - single_stock_layout.addWidget(single_label) - single_stock_layout.addWidget(self.single_stock_input) - single_stock_layout.addWidget(self.analyze_btn) - - # 批量分析部分 - batch_stock_layout = QVBoxLayout() - batch_label = QLabel('批量股票分析:') - batch_label.setFont(QFont('Arial', 12, QFont.Weight.Bold)) - self.batch_stock_input = QTextEdit() - self.batch_stock_input.setPlaceholderText('输入多个股票代码，每行一个') - self.batch_stock_input.setFont(QFont('Arial', 10)) - self.batch_stock_input.setMaximumHeight(100) - self.batch_analyze_btn = QPushButton('批量分析') - self.batch_analyze_btn.setFont(QFont('Arial', 10, QFont.Weight.Bold)) - self.batch_analyze_btn.clicked.connect(self.analyze_multiple_stocks) - batch_stock_layout.addWidget(batch_label) - batch_stock_layout.addWidget(self.batch_stock_input) - batch_stock_layout.addWidget(self.batch_analyze_btn) - - input_layout.addLayout(single_stock_layout) - input_layout.addLayout(batch_stock_layout) - - # 添加进度条 - self.progress_bar = QProgressBar() - self.progress_bar.setVisible(False) - - # 添加结果显示区域 - self.result_browser = QTextBrowser() - self.result_browser.setOpenExternalLinks(True) - self.result_browser.setFont(QFont('Arial', 10)) - - layout.addLayout(input_layout) - layout.addWidget(self.progress_bar) - layout.addWidget(self.result_browser) - - def format_report(self, report, is_single=True): - """将分析报告格式化为Markdown格式""" - md = f"""# 股票分析报告 - {report['stock_code']} - -## 基本信息 -- 分析日期：{report['analysis_date']} -- 当前价格：{report['price']:.2f} -- 价格变动：{report['price_change']:.2f}% - -## 技术指标 -- 均线趋势：{report['ma_trend']} -- RSI指标：{report['rsi']:.2f} -- MACD信号：{report['macd_signal']} -- 成交量状态：{report['volume_status']} - -## 评分与建议 -- 综合评分：{report['score']}分 -- 投资建议：{report['recommendation']} - -## AI分析 -{report['ai_analysis']} - ---- -""" - return md - - def analyze_single_stock(self): - """分析单只股票""" - stock_code = self.single_stock_input.text().strip() - if not stock_code: - QMessageBox.warning(self, '警告', '请输入股票代码') - return - - self.analyze_btn.setEnabled(False) - self.progress_bar.setVisible(True) - self.progress_bar.setValue(0) - - # 创建工作线程 - self.worker = AnalysisWorker(self.analyzer, stock_code) - self.worker.finished.connect(self.handle_single_analysis_result) - self.worker.error.connect(self.handle_analysis_error) - self.worker.progress.connect(self.progress_bar.setValue) - self.worker.start() - - def handle_single_analysis_result(self, report): - """处理单只股票分析结果""" - markdown_text = self.format_report(report) - html_content = markdown2.markdown(markdown_text) - self.result_browser.setHtml(html_content) - self.analyze_btn.setEnabled(True) - self.progress_bar.setVisible(False) - - def analyze_multiple_stocks(self): - """批量分析股票""" - text = self.batch_stock_input.toPlainText().strip() - if not text: - QMessageBox.warning(self, '警告', '请输入股票代码') - return - - stock_list = [code.strip() for code in text.split('\n') if code.strip()] - - self.batch_analyze_btn.setEnabled(False) - self.progress_bar.setVisible(True) - self.progress_bar.setValue(0) - - # 创建工作线程 - self.batch_worker = BatchAnalysisWorker(self.analyzer, stock_list) - self.batch_worker.finished.connect(self.handle_batch_analysis_result) - self.batch_worker.error.connect(self.handle_analysis_error) - self.batch_worker.progress.connect(self.progress_bar.setValue) - self.batch_worker.start() - - def handle_batch_analysis_result(self, recommendations): - """处理批量分析结果""" - # 生成markdown格式的报告 - markdown_text = "# 批量股票分析报告\n\n" - for rec in recommendations: - markdown_text += self.format_report(rec, False) - - html_content = markdown2.markdown(markdown_text) - self.result_browser.setHtml(html_content) - self.batch_analyze_btn.setEnabled(True) - self.progress_bar.setVisible(False) - - def handle_analysis_error(self, error_message): - """处理分析错误""" - QMessageBox.critical(self, '错误', f'分析过程中出现错误：{error_message}') - self.analyze_btn.setEnabled(True) - self.batch_analyze_btn.setEnabled(True) - self.progress_bar.setVisible(False) - -def main(): - app = QApplication(sys.argv) - - # 设置应用程序样式 - app.setStyle('Fusion') - - # 创建并显示主窗口 - window = StockAnalyzerGUI() - window.show() - - sys.exit(app.exec()) - -if __name__ == '__main__': - main() diff --git a/gui2.py b/gui2.py deleted file mode 100644 index 4124871..0000000 --- a/gui2.py +++ /dev/null @@ -1,497 +0,0 @@ -import sys -from PyQt6.QtWidgets import (QApplication, QMainWindow, QWidget, QVBoxLayout, - QHBoxLayout, QLineEdit, QPushButton, QTextBrowser, - QLabel, QTextEdit, QMessageBox, QProgressBar, - QFrame, QSizePolicy) -from PyQt6.QtCore import Qt, QThread, pyqtSignal -from PyQt6.QtGui import QFont, QPalette, QColor -import markdown2 -from stock_analyzer import StockAnalyzer - -class ModernFrame(QFrame): - """现代化的面板组件""" - def __init__(self, parent=None): - super().__init__(parent) - self.setFrameStyle(QFrame.Shape.StyledPanel | QFrame.Shadow.Raised) - self.setStyleSheet(""" - ModernFrame { - background-color: #ffffff; - border-radius: 10px; - border: 1px solid #e0e0e0; - } - """) - -class ModernButton(QPushButton): - """现代化的按钮组件""" - def __init__(self, text, parent=None, primary=True): - super().__init__(text, parent) - self.setMinimumHeight(40) - if primary: - self.setStyleSheet(""" - QPushButton { - background-color: #1a73e8; - color: white; - border: none; - border-radius: 5px; - padding: 8px 16px; - font-weight: bold; - } - QPushButton:hover { - background-color: #1557b0; - } - QPushButton:pressed { - background-color: #0d47a1; - } - QPushButton:disabled { - background-color: #cccccc; - } - """) - else: - self.setStyleSheet(""" - QPushButton { - background-color: #f8f9fa; - color: #1a73e8; - border: 1px solid #dadce0; - border-radius: 5px; - padding: 8px 16px; - font-weight: bold; - } - QPushButton:hover { - background-color: #f1f3f4; - border-color: #d2e3fc; - } - QPushButton:pressed { - background-color: #e8eaed; - } - QPushButton:disabled { - color: #5f6368; - border-color: #e0e0e0; - } - """) - -class ModernLineEdit(QLineEdit): - """现代化的输入框组件""" - def __init__(self, parent=None): - super().__init__(parent) - self.setMinimumHeight(40) - self.setStyleSheet(""" - QLineEdit { - border: 2px solid #e0e0e0; - border-radius: 5px; - padding: 8px 12px; - background-color: white; - selection-background-color: #cce0ff; - } - QLineEdit:focus { - border-color: #1a73e8; - } - QLineEdit:hover { - border-color: #999999; - } - """) - -class ModernTextEdit(QTextEdit): - """现代化的多行文本输入框组件""" - def __init__(self, parent=None): - super().__init__(parent) - self.setStyleSheet(""" - QTextEdit { - border: 2px solid #e0e0e0; - border-radius: 5px; - padding: 8px; - background-color: white; - selection-background-color: #cce0ff; - } - QTextEdit:focus { - border-color: #1a73e8; - } - QTextEdit:hover { - border-color: #999999; - } - """) - -class ModernProgressBar(QProgressBar): - """现代化的进度条组件""" - def __init__(self, parent=None): - super().__init__(parent) - self.setStyleSheet(""" - QProgressBar { - border: none; - border-radius: 3px; - background-color: #f0f0f0; - height: 6px; - text-align: center; - } - QProgressBar::chunk { - background-color: #1a73e8; - border-radius: 3px; - } - """) - self.setTextVisible(False) - -class AnalysisWorker(QThread): - """后台工作线程，用于执行分析任务""" - finished = pyqtSignal(dict) - error = pyqtSignal(str) - progress = pyqtSignal(int) - - def __init__(self, analyzer, stock_code): - super().__init__() - self.analyzer = analyzer - self.stock_code = stock_code - - def run(self): - try: - report = self.analyzer.analyze_stock(self.stock_code) - self.finished.emit(report) - except Exception as e: - self.error.emit(str(e)) - -class BatchAnalysisWorker(QThread): - """后台工作线程，用于执行批量分析任务""" - finished = pyqtSignal(list) - error = pyqtSignal(str) - progress = pyqtSignal(int) - - def __init__(self, analyzer, stock_list): - super().__init__() - self.analyzer = analyzer - self.stock_list = stock_list - - def run(self): - try: - results = [] - total = len(self.stock_list) - for i, stock_code in enumerate(self.stock_list): - report = self.analyzer.analyze_stock(stock_code) - results.append(report) - self.progress.emit(int((i + 1) / total * 100)) - self.finished.emit(results) - except Exception as e: - self.error.emit(str(e)) - -class ModernStockAnalyzerGUI(QMainWindow): - def __init__(self): - super().__init__() - self.analyzer = StockAnalyzer() - self.init_ui() - self.adjust_size_and_position() - - def adjust_size_and_position(self): - """调整窗口大小和位置以适应不同分辨率""" - screen = QApplication.primaryScreen() - if screen: - geometry = screen.availableGeometry() - # 设置窗口大小为屏幕的75% - width = int(geometry.width() * 0.75) - height = int(geometry.height() * 0.75) - self.resize(width, height) - - # 居中显示 - center = geometry.center() - frame = self.frameGeometry() - frame.moveCenter(center) - self.move(frame.topLeft()) - - def init_ui(self): - self.setWindowTitle('现代股票分析系统') - self.setStyleSheet(""" - QMainWindow { - background-color: #f8f9fa; - } - """) - - # 创建中央部件和主布局 - central_widget = QWidget() - self.setCentralWidget(central_widget) - main_layout = QVBoxLayout(central_widget) - main_layout.setSpacing(20) - main_layout.setContentsMargins(20, 20, 20, 20) - - # 创建标题 - title_label = QLabel('股票分析系统') - title_label.setStyleSheet(""" - QLabel { - color: #202124; - font-size: 24px; - font-weight: bold; - margin-bottom: 20px; - } - """) - main_layout.addWidget(title_label, alignment=Qt.AlignmentFlag.AlignTop) - - # 创建输入区域容器 - input_container = ModernFrame() - input_layout = QHBoxLayout(input_container) - input_layout.setSpacing(20) - input_layout.setContentsMargins(20, 20, 20, 20) - - # 单只股票分析部分 - single_stock_frame = self.create_single_stock_section() - input_layout.addWidget(single_stock_frame) - - # 分隔线 - separator = QFrame() - separator.setFrameShape(QFrame.Shape.VLine) - separator.setStyleSheet("background-color: #e0e0e0;") - input_layout.addWidget(separator) - - # 批量分析部分 - batch_stock_frame = self.create_batch_stock_section() - input_layout.addWidget(batch_stock_frame) - - main_layout.addWidget(input_container) - - # 进度条 - self.progress_bar = ModernProgressBar() - self.progress_bar.setVisible(False) - main_layout.addWidget(self.progress_bar) - - # 结果显示区域 - result_frame = ModernFrame() - result_layout = QVBoxLayout(result_frame) - result_layout.setContentsMargins(15, 15, 15, 15) - - result_label = QLabel('分析结果') - result_label.setStyleSheet(""" - QLabel { - color: #202124; - font-size: 18px; - font-weight: bold; - } - """) - result_layout.addWidget(result_label) - - self.result_browser = QTextBrowser() - self.result_browser.setOpenExternalLinks(True) - self.result_browser.setStyleSheet(""" - QTextBrowser { - border: none; - background-color: white; - font-size: 14px; - line-height: 1.5; - } - """) - result_layout.addWidget(self.result_browser) - - main_layout.addWidget(result_frame) - - def create_single_stock_section(self): - """创建单只股票分析部分""" - frame = QFrame() - layout = QVBoxLayout(frame) - layout.setSpacing(15) - - label = QLabel('单只股票分析') - label.setStyleSheet(""" - QLabel { - color: #202124; - font-size: 16px; - font-weight: bold; - } - """) - layout.addWidget(label) - - self.single_stock_input = ModernLineEdit() - self.single_stock_input.setPlaceholderText('输入股票代码（如：600000）') - layout.addWidget(self.single_stock_input) - - self.analyze_btn = ModernButton('分析') - self.analyze_btn.clicked.connect(self.analyze_single_stock) - layout.addWidget(self.analyze_btn) - - layout.addStretch() - return frame - - def create_batch_stock_section(self): - """创建批量分析部分""" - frame = QFrame() - layout = QVBoxLayout(frame) - layout.setSpacing(15) - - label = QLabel('批量股票分析') - label.setStyleSheet(""" - QLabel { - color: #202124; - font-size: 16px; - font-weight: bold; - } - """) - layout.addWidget(label) - - self.batch_stock_input = ModernTextEdit() - self.batch_stock_input.setPlaceholderText('输入多个股票代码，每行一个') - self.batch_stock_input.setMinimumHeight(100) - layout.addWidget(self.batch_stock_input) - - self.batch_analyze_btn = ModernButton('批量分析') - self.batch_analyze_btn.clicked.connect(self.analyze_multiple_stocks) - layout.addWidget(self.batch_analyze_btn) - - layout.addStretch() - return frame - - def format_report(self, report, is_single=True): - """将分析报告格式化为现代化的Markdown格式""" - md = f"""# 股票分析报告 - {report['stock_code']} - -## 基本信息 -- **分析日期：** {report['analysis_date']} -- **当前价格：** ¥{report['price']:.2f} -- **价格变动：** {report['price_change']:.2f}% - -## 技术指标 -- **均线趋势：** {report['ma_trend']} -- **RSI指标：** {report['rsi']:.2f} -- **MACD信号：** {report['macd_signal']} -- **成交量状态：** {report['volume_status']} - -## 评分与建议 -- **综合评分：** {report['score']}分 -- **投资建议：** {report['recommendation']} - -## AI分析 -{report['ai_analysis']} - ---- -""" - return md - - def analyze_single_stock(self): - """分析单只股票""" - stock_code = self.single_stock_input.text().strip() - if not stock_code: - self.show_warning('请输入股票代码') - return - - self.analyze_btn.setEnabled(False) - self.progress_bar.setVisible(True) - self.progress_bar.setValue(0) - - self.worker = AnalysisWorker(self.analyzer, stock_code) - self.worker.finished.connect(self.handle_single_analysis_result) - self.worker.error.connect(self.handle_analysis_error) - self.worker.progress.connect(self.progress_bar.setValue) - self.worker.start() - - def analyze_multiple_stocks(self): - """批量分析股票""" - text = self.batch_stock_input.toPlainText().strip() - if not text: - self.show_warning('请输入股票代码') - return - - stock_list = [code.strip() for code in text.split('\n') if code.strip()] - - self.batch_analyze_btn.setEnabled(False) - self.progress_bar.setVisible(True) - self.progress_bar.setValue(0) - - self.batch_worker = BatchAnalysisWorker(self.analyzer, stock_list) - self.batch_worker.finished.connect(self.handle_batch_analysis_result) - self.batch_worker.error.connect(self.handle_analysis_error) - self.batch_worker.progress.connect(self.progress_bar.setValue) - self.batch_worker.start() - - def handle_single_analysis_result(self, report): - """处理单只股票分析结果""" - markdown_text = self.format_report(report) - html_content = markdown2.markdown(markdown_text, extras=['tables', 'fenced-code-blocks']) - self.result_browser.setHtml(html_content) - self.analyze_btn.setEnabled(True) - self.progress_bar.setVisible(False) - - def handle_batch_analysis_result(self, recommendations): - """处理批量分析结果""" - markdown_text = "# 批量股票分析报告\n\n" - for rec in recommendations: - markdown_text += self.format_report(rec, False) - - html_content = markdown2.markdown(markdown_text, extras=['tables', 'fenced-code-blocks']) - self.result_browser.setHtml(html_content) - self.batch_analyze_btn.setEnabled(True) - self.progress_bar.setVisible(False) - - def handle_analysis_error(self, error_message): - """处理分析错误""" - self.show_error(f'分析过程中出现错误：{error_message}') - self.analyze_btn.setEnabled(True) - self.batch_analyze_btn.setEnabled(True) - self.progress_bar.setVisible(False) - - def show_warning(self, message): - """显示警告对话框""" - warning = QMessageBox(self) - warning.setIcon(QMessageBox.Icon.Warning) - warning.setWindowTitle('警告') - warning.setText(message) - warning.setStandardButtons(QMessageBox.StandardButton.Ok) - warning.setStyleSheet(""" - QMessageBox { - background-color: white; - } - QMessageBox QLabel { - color: #202124; - min-width: 200px; - } - QPushButton { - background-color: #1a73e8; - color: white; - border: none; - border-radius: 4px; - padding: 8px 16px; - min-width: 80px; - } - QPushButton:hover { - background-color: #1557b0; - } - QPushButton:pressed { - background-color: #0d47a1; - } - """) - warning.exec() - - def show_error(self, message): - """显示错误对话框""" - error = QMessageBox(self) - error.setIcon(QMessageBox.Icon.Critical) - error.setWindowTitle('错误') - error.setText(message) - error.setStandardButtons(QMessageBox.StandardButton.Ok) - error.setStyleSheet(""" - QMessageBox { - background-color: white; - } - QMessageBox QLabel { - color: #202124; - min-width: 200px; - } - QPushButton { - background-color: #1a73e8; - color: white; - border: none; - border-radius: 4px; - padding: 8px 16px; - min-width: 80px; - } - QPushButton:hover { - background-color: #1557b0; - } - QPushButton:pressed { - background-color: #0d47a1; - } - """) - error.exec() - -def main(): - app = QApplication(sys.argv) - app.setStyle('Fusion') - - # 创建并显示主窗口 - window = ModernStockAnalyzerGUI() - window.show() - - sys.exit(app.exec()) - -if __name__ == '__main__': - main() diff --git a/requirements.txt b/requirements.txt index 2f7f9d7..a79b0b4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,5 +1,5 @@ # 基础科学计算和数据处理库 -numpy==2.0.0 +numpy==2.1.2 pandas==2.2.2 scipy==1.15.1 @@ -7,13 +7,11 @@ scipy==1.15.1 akshare==1.15.87 tqdm==4.67.1 -# GUI库 -PyQt6==6.8.1 -markdown2==2.5.3 # 网络和API请求 requests==2.32.3 python-dotenv==1.0.1 +flask==3.1.0 # 日志和系统工具 loguru==0.7.2 diff --git a/stock_analyzer.py b/stock_analyzer.py index db8dac1..0b083e1 100644 --- a/stock_analyzer.py +++ b/stock_analyzer.py @@ -18,7 +18,7 @@ class StockAnalyzer: load_dotenv() # 设置 Gemini API - self.gemini_api_url = "https://api.xxx.xxx" + self.gemini_api_url = os.getenv('GEMINI_API_URL') self.gemini_api_key = os.getenv('GEMINI_API_KEY') # 配置参数 @@ -30,8 +30,15 @@ class StockAnalyzer: 'volume_ma_period': 20, 'atr_period': 14 } + + # 添加市场类型枚举 + self.MARKET_TYPES = { + 'A': 'A股', + 'HK': '港股', + 'CRYPTO': '加密货币' + } - def get_stock_data(self, stock_code, start_date=None, end_date=None): + def get_stock_data(self, stock_code, market_type='A', start_date=None, end_date=None, ): """获取股票数据""" import akshare as ak @@ -41,11 +48,33 @@ class StockAnalyzer: end_date = datetime.now().strftime('%Y%m%d') try: - # 使用 akshare 获取股票数据 - df = ak.stock_zh_a_hist(symbol=stock_code, - start_date=start_date, - end_date=end_date, - adjust="qfq") + # 根据市场类型获取数据 + if market_type == 'A': + df = ak.stock_zh_a_hist( + symbol=stock_code, + start_date=start_date, + end_date=end_date, + adjust="qfq" + ) + # A股数据列名映射 + elif market_type == 'HK': + df = ak.stock_hk_daily( + symbol=stock_code, + adjust="qfq" + ) + elif market_type == 'US': + df = ak.stock_us_hist( + symbol=stock_code, + start_date=start_date, + end_date=end_date, + adjust="qfq" + ) + elif market_type == 'CRYPTO': + df = ak.crypto_js_spot( + symbol=stock_code + ) + else: + raise ValueError(f"不支持的市场类型: {market_type}") # 重命名列名以匹配分析需求 df = df.rename(columns={ @@ -225,7 +254,7 @@ class StockAnalyzer: } data = { - "model": "gemini-1.5-flash", + "model": os.getenv('GEMINI_API_MODEL'), "messages": [{"role": "user", "content": prompt}] } @@ -233,9 +262,12 @@ class StockAnalyzer: f"{self.gemini_api_url}/v1/chat/completions", headers=headers, json=data, - timeout=10 + timeout=30 ) - + print(headers) + print(data) + print(response.json()) + if response.status_code == 200: return response.json()['choices'][0]['message']['content'] else: @@ -258,11 +290,11 @@ class StockAnalyzer: else: return '强烈建议卖出' - def analyze_stock(self, stock_code): + def analyze_stock(self, stock_code, market_type='A'): """分析单个股票""" try: # 获取股票数据 - df = self.get_stock_data(stock_code) + df = self.get_stock_data(stock_code, market_type) # 计算技术指标 df = self.calculate_indicators(df) @@ -295,13 +327,13 @@ class StockAnalyzer: self.logger.error(f"分析股票时出错: {str(e)}") raise - def scan_market(self, stock_list, min_score=60): + def scan_market(self, stock_list, min_score=60, market_type='A'): """扫描市场，寻找符合条件的股票""" recommendations = [] for stock_code in stock_list: try: - report = self.analyze_stock(stock_code) + report = self.analyze_stock(stock_code, market_type) if report['score'] >= min_score: recommendations.append(report) except Exception as e: diff --git a/templates/index.html b/templates/index.html index 6bd1b55..cf641f1 100644 --- a/templates/index.html +++ b/templates/index.html @@ -10,130 +10,206 @@

股票分析系统

-
- -
-

单只股票分析

-
- -
- -
- +
-

批量股票分析

+

股票批量分析

+ +
+ + +
+ +
+ + placeholder="输入代码，支持多个代码（用回车或逗号分隔）">
-
-
- -
-

分析结果

-
-
-
+ +
+

分析结果

+
+
+ + \ No newline at end of file diff --git a/web_app.py b/web_app.py deleted file mode 100644 index 0092432..0000000 --- a/web_app.py +++ /dev/null @@ -1,39 +0,0 @@ -from flask import Flask, request, jsonify, render_template -from stock_analyzer import StockAnalyzer -import os - -app = Flask(__name__) -analyzer = StockAnalyzer() - -@app.route('/') -def index(): - return render_template('index.html') - -@app.route('/api/analyze', methods=['POST']) -def analyze(): - try: - data = request.json - stock_code = data.get('stock_code') - if not stock_code: - return jsonify({'error': '请提供股票代码'}), 400 - - result = analyzer.analyze_stock(stock_code) - return jsonify(result) - except Exception as e: - return jsonify({'error': str(e)}), 500 - -@app.route('/api/batch-analyze', methods=['POST']) -def batch_analyze(): - try: - data = request.json - stock_list = data.get('stock_list', []) - if not stock_list: - return jsonify({'error': '请提供股票代码列表'}), 400 - - results = analyzer.scan_market(stock_list) - return jsonify(results) - except Exception as e: - return jsonify({'error': str(e)}), 500 - -if __name__ == '__main__': - app.run(host='0.0.0.0', port=8443) diff --git a/web_server.py b/web_server.py new file mode 100644 index 0000000..2cb843c --- /dev/null +++ b/web_server.py @@ -0,0 +1,62 @@ +from flask import Flask, render_template, request, jsonify +from stock_analyzer import StockAnalyzer +from us_stock_service import USStockService +import threading +import logging +from logging.handlers import RotatingFileHandler +import traceback + +app = Flask(__name__) +analyzer = StockAnalyzer() +us_stock_service = USStockService() + +# 配置日志 +logging.basicConfig(level=logging.INFO) +handler = RotatingFileHandler('flask_app.log', maxBytes=10000000, backupCount=5) +handler.setFormatter(logging.Formatter( + '[%(asctime)s] %(levelname)s in %(module)s: %(message)s' +)) +app.logger.addHandler(handler) + +@app.route('/') +def index(): + return render_template('index.html') + +@app.route('/analyze', methods=['POST']) +def analyze(): + try: + data = request.json + stock_codes = data.get('stock_codes', []) + market_type = data.get('market_type', 'A') + + if not stock_codes: + return jsonify({'error': '请输入代码'}), 400 + + results = [] + for stock_code in stock_codes: + result = analyzer.analyze_stock(stock_code.strip(), market_type) + results.append(result) + + return jsonify({'results': results}) + except Exception as e: + return jsonify({'error': str(e)}), 500 + +@app.route('/search_us_stocks', methods=['GET']) +def search_us_stocks(): + 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}) + + except Exception as e: + app.logger.error(f"搜索美股代码时出错: {str(e)}") + return jsonify({'error': str(e)}), 500 + +if __name__ == '__main__': + # 将 host 设置为 '0.0.0.0' 使其支持所有网络接口访问 + app.run(host='0.0.0.0', port=8888, debug=True) + + \ No newline at end of file diff --git a/全部股票分析推荐1.py b/全部股票分析推荐1.py deleted file mode 100644 index 3190e70..0000000 --- a/全部股票分析推荐1.py +++ /dev/null @@ -1,602 +0,0 @@ -"""" -Stock Analysis System -优化后的全盘股票技术分析系统——用于A股市场股票的全面分析，已加速分析并增加额外指标。 -""" - -import os -import time -import random -import logging -import traceback -from datetime import datetime, timedelta -from concurrent.futures import ThreadPoolExecutor -from typing import Dict, List, Optional, Tuple, Union -from dataclasses import dataclass - -import numpy as np -import pandas as pd -import akshare as ak -from tqdm import tqdm - -# ------------------------------- -# **技术指标配置** -# ------------------------------- -@dataclass -class TechnicalParams: - """技术指标参数配置""" - ma_periods: Dict[str, int] - rsi_period: int - bollinger_period: int - bollinger_std: int - volume_ma_period: int - atr_period: int - - @classmethod - def default(cls) -> 'TechnicalParams': - """返回默认的技术指标参数""" - return cls( - ma_periods={'short': 5, 'medium': 20, 'long': 60}, - rsi_period=14, - bollinger_period=20, - bollinger_std=2, - volume_ma_period=20, - atr_period=14 - ) - -# ------------------------------- -# **股票分析引擎** -# ------------------------------- -class StockAnalyzer: - """股票分析引擎，计算各类技术指标""" - - def __init__(self, params: Optional[TechnicalParams] = None): - """ - 初始化股票分析引擎 - - Args: - params: 技术指标配置参数 - """ - self._setup_logging() - self.params = params or TechnicalParams.default() - - def _setup_logging(self) -> None: - """配置日志记录""" - logging.basicConfig( - level=logging.INFO, - format='%(asctime)s - %(levelname)s - %(message)s', - datefmt='%Y-%m-%d %H:%M:%S' - ) - self.logger = logging.getLogger(__name__) - - def get_stock_data(self, stock_code: str, - start_date: Optional[str] = None, - end_date: Optional[str] = None) -> pd.DataFrame: - """ - 获取单只股票历史数据，默认使用前一年的数据。 - - Args: - stock_code: 股票代码（可以带市场前缀或纯代码） - start_date: 开始日期(格式YYYYMMDD) - end_date: 结束日期(格式YYYYMMDD) - - Returns: - 包含日期、开盘、收盘、最高、最低、成交量的 DataFrame - """ - try: - if not start_date: - start_date = (datetime.now() - timedelta(days=365)).strftime('%Y%m%d') - if not end_date: - end_date = datetime.now().strftime('%Y%m%d') - - code = stock_code[2:] if stock_code.startswith(('sz', 'sh')) else stock_code - - df = ak.stock_zh_a_hist( - symbol=code, - start_date=start_date, - end_date=end_date, - adjust="qfq" - ) - - self.logger.info(f"获取到 {len(df)} 行数据，列名：{df.columns.tolist()}") - - df = df.rename(columns={ - "日期": "date", - "开盘": "open", - "收盘": "close", - "最高": "high", - "最低": "low", - "成交量": "volume", - "trade_date": "date" - }) - - required_columns = {'date', 'open', 'close', 'high', 'low', 'volume'} - missing_columns = required_columns - set(df.columns) - if missing_columns: - raise ValueError(f"缺失必须字段: {missing_columns}") - - df['date'] = pd.to_datetime(df['date'], errors='coerce') - numeric_columns = ['open', 'close', 'high', 'low', 'volume'] - df[numeric_columns] = df[numeric_columns].apply(pd.to_numeric, errors='coerce') - df_cleaned = df.dropna(subset=['date'] + numeric_columns).sort_values('date') - - if len(df_cleaned) < 60: - raise ValueError(f"数据不足（仅 {len(df_cleaned)} 行），无法计算至少60日均线") - - return df_cleaned - - except Exception as e: - self.logger.error(f"获取股票数据失败，股票代码 {stock_code}，错误信息：{str(e)}") - raise ValueError(f"股票 {stock_code} 数据获取出错: {str(e)}") - - @staticmethod - def calculate_ema(series: pd.Series, period: int) -> pd.Series: - """计算 EMA""" - return series.ewm(span=period, adjust=False).mean() - - @staticmethod - def calculate_rsi(series: pd.Series, period: int) -> pd.Series: - """ - 计算 RSI（指数加权移动平均法） - """ - delta = series.diff() - gain = delta.clip(lower=0) - loss = -delta.clip(upper=0) - avg_gain = gain.ewm(com=period - 1, adjust=False).mean() - avg_loss = loss.ewm(com=period - 1, adjust=False).mean() - rs = avg_gain / (avg_loss + 1e-10) - return 100 - (100 / (1 + rs)) - - @staticmethod - def calculate_macd(series: pd.Series) -> Tuple[pd.Series, pd.Series, pd.Series]: - """计算 MACD、信号线和直方图""" - exp1 = series.ewm(span=12, adjust=False).mean() - exp2 = series.ewm(span=26, adjust=False).mean() - macd = exp1 - exp2 - signal = macd.ewm(span=9, adjust=False).mean() - return macd, signal, macd - signal - - @staticmethod - def calculate_bollinger_bands(series: pd.Series, period: int, std_dev: int) -> Tuple[pd.Series, pd.Series, pd.Series]: - """计算 Bollinger 通道""" - middle = series.rolling(window=period, min_periods=period).mean() - std = series.rolling(window=period, min_periods=period).std() - upper = middle + std * std_dev - lower = middle - std * std_dev - return upper, middle, lower - - def calculate_atr(self, df: pd.DataFrame, period: int) -> pd.Series: - """计算 ATR""" - high = df['high'] - low = df['low'] - prev_close = df['close'].shift(1) - tr = pd.concat([ - high - low, - (high - prev_close).abs(), - (low - prev_close).abs() - ], axis=1).max(axis=1) - return tr.rolling(window=period, min_periods=period).mean() - - @staticmethod - def calculate_obv(series_close: pd.Series, series_volume: pd.Series) -> pd.Series: - """计算 OBV（能量潮指标）""" - diff = series_close.diff().fillna(0) - obv = np.where(diff > 0, series_volume, np.where(diff < 0, -series_volume, 0)) - return pd.Series(obv, index=series_close.index).cumsum() - - @staticmethod - def calculate_stochastic(series_close: pd.Series, window: int = 14) -> Tuple[pd.Series, pd.Series]: - """ - 计算随机指标（Stochastic Oscillator） - %K = (close - lowest_low) / (highest_high - lowest_low)*100 - %D 为 %K 的3日简单移动平均 - """ - lowest = series_close.rolling(window=window, min_periods=window).min() - highest = series_close.rolling(window=window, min_periods=window).max() - percentK = (series_close - lowest) / (highest - lowest + 1e-10) * 100 - percentD = percentK.rolling(window=3, min_periods=3).mean() - return percentK, percentD - - def calculate_indicators(self, df: pd.DataFrame) -> pd.DataFrame: - """计算所有技术指标，并增加 OBV 和随机指标""" - try: - # 移动均线 - for key, period in self.params.ma_periods.items(): - df[f'MA{period}'] = self.calculate_ema(df['close'], period) - df['RSI'] = self.calculate_rsi(df['close'], self.params.rsi_period) - df['MACD'], df['Signal'], df['MACD_hist'] = self.calculate_macd(df['close']) - df['BB_upper'], df['BB_middle'], df['BB_lower'] = self.calculate_bollinger_bands( - df['close'], self.params.bollinger_period, self.params.bollinger_std) - df['Volume_MA'] = df['volume'].rolling(window=self.params.volume_ma_period, - min_periods=self.params.volume_ma_period).mean() - df['Volume_Ratio'] = df['volume'] / (df['Volume_MA'] + 1e-10) - df['ATR'] = self.calculate_atr(df, self.params.atr_period) - df['Volatility'] = df['ATR'] / df['close'] * 100 - df['ROC'] = df['close'].pct_change(periods=10) * 100 - - # 增加 OBV 指标 - df['OBV'] = self.calculate_obv(df['close'], df['volume']) - df['OBV_MA10'] = df['OBV'].rolling(window=10, min_periods=10).mean() - - # 增加随机指标 Stochastic - df['%K'], df['%D'] = self.calculate_stochastic(df['close'], window=14) - - return df - - except Exception as e: - self.logger.error(f"指标计算出错：{str(e)}") - raise - - def calculate_score(self, df: pd.DataFrame) -> float: - """ - 计算股票综合打分（基本打分满分100分），并根据 OBV 与随机指标调整±5分， - 使量化结果更全面。 - 基本打分逻辑不变： - 趋势（30分）、RSI（20分）、MACD（20分）、成交量（30分） - 附加指标调整： - OBV：OBV > OBV_MA10，+5分；反之，-5分； - 随机指标：%K < 20为超卖，+5分；%K > 80为超买，-5分。 - """ - try: - score = 0 - latest = df.iloc[-1] - # 趋势打分 - if latest['MA5'] > latest['MA20'] and latest['MA20'] > latest['MA60']: - score += 30 - else: - if latest['MA5'] > latest['MA20']: - score += 15 - if latest['MA20'] > latest['MA60']: - score += 15 - # RSI 打分 - if 30 <= latest['RSI'] <= 70: - score += 20 - elif latest['RSI'] < 30: - score += 15 - # MACD 打分 - if latest['MACD'] > latest['Signal']: - score += 20 - # 成交量打分 - if latest['Volume_Ratio'] > 1.5: - score += 30 - elif latest['Volume_Ratio'] > 1: - score += 15 - - # 附加 OBV 调整 - if latest['OBV'] > latest['OBV_MA10']: - score += 5 - else: - score -= 5 - - # 附加随机指标调整 - if latest['%K'] < 20: - score += 5 - elif latest['%K'] > 80: - score -= 5 - - return score - - except Exception as e: - self.logger.error(f"计算打分失败：{str(e)}") - raise - - @staticmethod - def get_recommendation(score: float) -> str: - """根据最终打分给出投资建议""" - if score >= 80: - return '强烈推荐买入' - elif score >= 60: - return '建议买入' - elif score >= 40: - return '建议观望' - elif score >= 20: - return '建议卖出' - else: - return '强烈建议卖出' - - def analyze_stock(self, stock_code: str) -> Dict: - """针对单只股票执行完整的技术分析流程""" - try: - df = self.get_stock_data(stock_code) - df = self.calculate_indicators(df) - score = self.calculate_score(df) - latest = df.iloc[-1] - prev = df.iloc[-2] - return { - 'stock_code': stock_code, - 'analysis_date': datetime.now().strftime('%Y-%m-%d'), - 'score': score, - 'price': latest['close'], - 'price_change': (latest['close'] - prev['close']) / prev['close'] * 100, - 'ma_trend': 'UP' if latest['MA5'] > latest['MA20'] else 'DOWN', - 'rsi': latest['RSI'], - 'macd_signal': 'BUY' if latest['MACD'] > latest['Signal'] else 'SELL', - 'volume_status': 'HIGH' if latest['Volume_Ratio'] > 1.5 else 'NORMAL', - 'recommendation': self.get_recommendation(score) - } - - except Exception as e: - self.logger.error(f"分析股票 {stock_code} 失败：{str(e)}") - raise - -# ------------------------------- -# **全盘股票扫描器** -# ------------------------------- -class TopStockScanner: - """全盘筛选高打分股票的扫描器""" - - def __init__(self, max_workers: int = 20, min_score: float = 85): - """ - 初始化扫描器 - - Args: - max_workers: 并发线程数量（已增至20以加速分析） - min_score: 高分最低阈值 - """ - self.analyzer = StockAnalyzer() - self.max_workers = max_workers - self.min_score = min_score - self.logger = logging.getLogger(__name__) - - def get_all_stocks(self) -> List[str]: - """ - 获取所有上市 A 股股票代码（全盘版）。 - 使用 ak.stock_info_sh_name_code(symbol="主板A股") 与 ak.stock_info_sz_name_code(symbol="A股列表")， - 候选字段列表为：['A股代码', '证券代码', '股票代码', 'code'] 。 - """ - try: - sh_df = ak.stock_info_sh_name_code(symbol="主板A股") - sz_df = ak.stock_info_sz_name_code(symbol="A股列表") - candidate_cols = ['A股代码', '证券代码', '股票代码', 'code'] - - def get_codes(df: pd.DataFrame) -> set: - for col in candidate_cols: - if col in df.columns: - return {str(code).zfill(6) for code in df[col]} - raise KeyError(f"未能找到股票代码字段，现有字段：{df.columns.tolist()}") - - sh_codes = get_codes(sh_df) - sz_codes = get_codes(sz_df) - all_codes = sorted(sh_codes | sz_codes) - self.logger.info(f"完整股票列表获取到 {len(all_codes)} 支股票信息") - print(f"\n开始分析 {len(all_codes)} 支股票...") - return all_codes - - except Exception as e: - self.logger.error(f"获取股票列表失败：{str(e)}") - raise - - def analyze_stock_safe(self, stock_code: str, max_retries: int = 3) -> Optional[Dict]: - """ - 安全分析单只股票（加入重试机制），数据异常则跳过。 - """ - for attempt in range(max_retries): - try: - return self.analyzer.analyze_stock(stock_code) - except ValueError as e: - self.logger.warning(f"跳过股票 {stock_code}: {str(e)}") - return None - except Exception as e: - if attempt == max_retries - 1: - self.logger.error(f"股票 {stock_code} 分析尝试 {max_retries} 次后失败：{str(e)}") - return None - self.logger.warning(f"股票 {stock_code} 第 {attempt+1} 次分析失败：{str(e)}") - time.sleep(random.uniform(2, 5)) - - def process_batch(self, stock_codes: List[str]) -> List[Dict]: - """利用多线程并行处理一批股票的分析任务""" - results = [] - with ThreadPoolExecutor(max_workers=self.max_workers) as executor: - futures = {executor.submit(self.analyze_stock_safe, code): code for code in stock_codes} - for future in tqdm(futures, desc="分析进度", ncols=80): - try: - result = future.result() - if result is not None: - results.append(result) - except Exception as e: - stock = futures[future] - self.logger.error(f"处理股票 {stock} 时出错：{str(e)}") - return results - - def save_intermediate_results(self, results: List[Dict]) -> None: - """周期性保存中间结果，便于后续查看进度""" - try: - df = pd.DataFrame(results) - high_score_stocks = df[df['score'] >= self.min_score].sort_values('score', ascending=False) - output_lines = [ - "=" * 80, - f"股票扫描中间结果 - {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}", - f"共分析 {len(results)} 支股票", - "=" * 80, - f"\n发现 {len(high_score_stocks)} 支高分股票（得分≥{self.min_score}）：" - ] - for _, row in high_score_stocks.iterrows(): - output_lines.extend([ - f"\n股票代码: {row['stock_code']}", - f"得分: {row['score']:.1f} | 价格: ¥{row['price']:.2f} | 涨跌幅: {row['price_change']:.2f}%" - ]) - - os.makedirs('scanner', exist_ok=True) - with open('scanner/temp_results.txt', 'w', encoding='utf-8') as f: - f.write('\n'.join(output_lines)) - - except Exception as e: - self.logger.error(f"保存中间结果失败：{str(e)}") - - def get_high_score_stocks(self, batch_size: int = 20) -> List[Dict]: - """扫描全盘股票，返回高打分结果列表""" - try: - all_stocks = self.get_all_stocks() - total_stocks = len(all_stocks) - print(f"\n开始扫描 {total_stocks} 支股票……") - results = [] - total_batches = (total_stocks + batch_size - 1) // batch_size - - for i in range(0, total_stocks, batch_size): - batch_number = i // batch_size + 1 - print(f"\r当前进度: 批次 {batch_number}/{total_batches}", end="") - batch = all_stocks[i:i + batch_size] - batch_results = self.process_batch(batch) - results.extend(batch_results) - if i + batch_size < total_stocks: - time.sleep(random.uniform(3, 5)) - if results and ((len(results) % 100 == 0) or (i + batch_size >= total_stocks)): - self.save_intermediate_results(results) - print("\n扫描结束！") - - if results: - df_results = pd.DataFrame(results) - high_score_stocks = df_results[df_results['score'] >= self.min_score].sort_values('score', ascending=False) - formatted_results = [] - for _, row in high_score_stocks.iterrows(): - formatted_results.append({ - '股票代码': row['stock_code'], - '评分': f"{row['score']:.1f}", - '当前价格': f"¥{row['price']:.2f}", - '涨跌幅': f"{row['price_change']:.2f}%", - 'RSI指标': f"{row['rsi']:.2f}", - '均线趋势': '上升' if row['ma_trend'] == 'UP' else '下降', - 'MACD信号': '买入' if row['macd_signal'] == 'BUY' else '卖出', - '成交量状态': '放量' if row['volume_status'] == 'HIGH' else '正常', - '投资建议': row['recommendation'] - }) - return formatted_results - return [] - - except Exception as e: - self.logger.error(f"全盘扫描失败：{str(e)}") - raise - -# ------------------------------- -# **结果分组与报告生成** -# ------------------------------- -def format_price_category(price: float) -> str: - """将价格划分为区间（例如 32.5 -> '30-40'）""" - base = (price // 10) * 10 - return f"{int(base)}-{int(base+10)}" - -def save_results_by_price(results: List[Dict]) -> None: - """按价格区间保存分析结果至文件""" - try: - os.makedirs('scanner', exist_ok=True) - price_groups = {} - for stock in results: - price = float(stock['当前价格'].replace('¥', '')) - category = format_price_category(price) - price_groups.setdefault(category, []).append(stock) - - for category, stocks in price_groups.items(): - output_lines = [ - "=" * 80, - f"股票分析结果 - 价格区间: {category}元", - f"分析时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}", - "=" * 80, - f"\n该区间共发现 {len(stocks)} 支高分股票（得分≥85）：", - "-" * 80 - ] - stocks.sort(key=lambda x: float(x['评分']), reverse=True) - for i, stock in enumerate(stocks, 1): - output_lines.extend([ - f"\n{i}. 股票代码: {stock['股票代码']}", - f" 评分: {stock['评分']} | 价格: {stock['当前价格']} | 涨跌幅: {stock['涨跌幅']}", - f" RSI指标: {stock['RSI指标']} | 均线趋势: {stock['均线趋势']} | MACD信号: {stock['MACD信号']}", - f" 成交量状态: {stock['成交量状态']}", - f" 投资建议: {stock['投资建议']}", - "-" * 80 - ]) - output_lines.extend([ - f"\n价格区间 {category}元 分析汇总：", - f"1. 股票数量: {len(stocks)}", - f"2. 平均评分: {np.mean([float(stock['评分']) for stock in stocks]):.1f}", - f"3. 买入信号股票数: {sum(1 for stock in stocks if stock['MACD信号'] == '买入')}", - f"4. 放量股票数: {sum(1 for stock in stocks if stock['成交量状态'] == '放量')}" - ]) - - filename = f'scanner/price_{category.replace("-", "_")}.txt' - with open(filename, 'w', encoding='utf-8') as f: - f.write('\n'.join(output_lines)) - create_summary_file(price_groups) - except Exception as e: - logging.error(f"保存结果时发生错误: {str(e)}") - raise - -def create_summary_file(price_groups: Dict[str, List[Dict]]) -> None: - """生成综合汇总报告""" - try: - output_lines = [ - "=" * 80, - "A股市场优质股票筛选报告", - f"分析时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}", - "=" * 80 - ] - total_stocks = sum(len(stocks) for stocks in price_groups.values()) - all_scores = [float(stock['评分']) for stocks in price_groups.values() for stock in stocks] - - output_lines.extend([ - "\n整体统计：", - f"1. 共筛选出 {total_stocks} 支高分股票（得分≥85）", - f"2. 平均评分: {np.mean(all_scores):.1f}", - f"3. 最高评分: {max(all_scores):.1f}", - "\n各价格区间分布：", - "-" * 80 - ]) - for category, stocks in sorted(price_groups.items(), key=lambda x: float(x[0].split('-')[0])): - output_lines.extend([ - f"\n价格区间 {category}元：", - f" - 股票数量: {len(stocks)}", - f" - 平均评分: {np.mean([float(stock['评分']) for stock in stocks]):.1f}" - ]) - - with open('scanner/summary.txt', 'w', encoding='utf-8') as f: - f.write('\n'.join(output_lines)) - except Exception as e: - logging.error(f"生成汇总报告失败：{str(e)}") - raise - -# ------------------------------- -# **主程序入口** -# ------------------------------- -def main(): - """程序主入口""" - print("\n" + "=" * 80) - print("Market-Wide High-Score Stock Scanner".center(76)) - print("=" * 80) - - scanner = TopStockScanner(max_workers=20) # 已提升至20线程 - try: - print("\n开始全盘扫描股票……") - high_score_stocks = scanner.get_high_score_stocks(batch_size=20) - if not high_score_stocks: - print("\n未找到得分大于等于85分的股票。") - return - - save_results_by_price(high_score_stocks) - - print(f"\n分析完成！结果已保存至 scanner 文件夹中：") - print("1. 按价格区间保存的详细分析文件（price_XX_YY.txt）") - print("2. 汇总报告（summary.txt）") - - temp_file = 'scanner/temp_results.txt' - if os.path.exists(temp_file): - os.remove(temp_file) - - print("\n" + "=" * 80) - input("\n按Enter键退出……") - - except Exception as e: - error_msg = f"\n程序错误：{str(e)}\n" - print("=" * 80) - print(error_msg) - print("=" * 80) - os.makedirs('scanner', exist_ok=True) - with open('scanner/error_log.txt', 'w', encoding='utf-8') as f: - f.write("Stock Analysis System Error Report\n") - f.write("=" * 80 + "\n") - f.write(f"Time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n") - f.write(f"Error: {str(e)}\n") - f.write("=" * 80 + "\n") - f.write(f"详细堆栈信息:\n{traceback.format_exc()}") - print("错误日志已保存至 scanner/error_log.txt") - input("\n按Enter键退出……") - -if __name__ == "__main__": - main()