{"id":1160337,"date":"2025-01-13T19:03:40","date_gmt":"2025-01-13T11:03:40","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1160337.html"},"modified":"2025-01-13T19:03:43","modified_gmt":"2025-01-13T11:03:43","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e7%bc%96%e5%86%99%e7%82%92%e8%82%a1%e8%bd%af%e4%bb%b6","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1160337.html","title":{"rendered":"\u5982\u4f55\u7528Python\u7f16\u5199\u7092\u80a1\u8f6f\u4ef6"},"content":{"rendered":"

\"\u5982\u4f55\u7528Python\u7f16\u5199\u7092\u80a1\u8f6f\u4ef6\"<\/p>\n

\u7528Python\u7f16\u5199\u7092\u80a1\u8f6f\u4ef6\u7684\u4e3b\u8981\u6b65\u9aa4\u5305\u62ec\uff1a\u6570\u636e\u83b7\u53d6\u3001\u6570\u636e\u5904\u7406\u3001\u7b56\u7565\u7f16\u5199\u3001\u56de\u6d4b\u7cfb\u7edf\u3001\u4ea4\u6613\u63a5\u53e3\u3001\u7528\u6237\u754c\u9762\u3002<\/strong> \u5176\u4e2d\uff0c\u6570\u636e\u83b7\u53d6\u662f\u7092\u80a1\u8f6f\u4ef6\u7684\u57fa\u7840\uff0c\u4e3b\u8981\u662f\u901a\u8fc7\u8c03\u7528API\u4ece\u91d1\u878d\u6570\u636e\u63d0\u4f9b\u5546\u5904\u83b7\u53d6\u5b9e\u65f6\u548c\u5386\u53f2\u6570\u636e\u3002\u63a5\u4e0b\u6765\u8be6\u7ec6\u63cf\u8ff0\u4e00\u4e0b\u6570\u636e\u83b7\u53d6\u7684\u8fc7\u7a0b\u3002<\/p>\n<\/p>\n

\u6570\u636e\u83b7\u53d6\u662f\u6574\u4e2a\u7092\u80a1\u8f6f\u4ef6\u7684\u57fa\u7840\u3002Python\u4e2d\u6709\u591a\u4e2a\u5e93\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u83b7\u53d6\u80a1\u7968\u6570\u636e\uff0c\u4f8b\u5982yfinance<\/code>\u3001alpha_vantage<\/code>\u3001pandas_datareader<\/code>\u7b49\u3002\u4ee5yfinance<\/code>\u4e3a\u4f8b\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u6b65\u9aa4\u83b7\u53d6\u80a1\u7968\u6570\u636e\uff1a<\/p>\n<\/p>\n

    \n
  1. \n

    \u5b89\u88c5yfinance<\/code>\u5e93\uff1a\u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u5b89\u88c5yfinance<\/code>\u5e93\u3002<\/p>\n<\/p>\n

    pip install yfinance<\/p>\n
    <\/code><\/pre>\n<\/p>\n<\/li>\n
  2. \n
    \u5bfc\u5165\u5e76\u4f7f\u7528yfinance<\/code>\u5e93\u83b7\u53d6\u6570\u636e\uff1a<\/p>\n<\/p>\n
    import yfinance as yf<\/p>\n
    \u83b7\u53d6\u7279\u5b9a\u80a1\u7968\u7684\u5386\u53f2\u6570\u636e<\/strong><\/h2>\n
    ticker = 'AAPL'<\/p>\n
    data = yf.download(ticker, start='2020-01-01', end='2021-01-01')<\/p>\n
    print(data.head())<\/p>\n
    <\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n
    \u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u83b7\u53d6\u82f9\u679c\u516c\u53f8\u57282020\u5e74\u4e00\u5e74\u7684\u5386\u53f2\u80a1\u7968\u6570\u636e\u3002\u63a5\u4e0b\u6765\uff0c\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u5904\u7406\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n
    \u4e00\u3001\u6570\u636e\u83b7\u53d6<\/p>\n<\/p>\n
      \n
    1. \n
      \u4f7f\u7528yfinance\u5e93\u83b7\u53d6\u6570\u636e<\/strong><\/p>\n<\/p>\n
      yfinance<\/code>\u5e93\u662f\u4e00\u4e2a\u975e\u5e38\u65b9\u4fbf\u7684\u5de5\u5177\uff0c\u53ef\u4ee5\u83b7\u53d6\u5404\u79cd\u80a1\u7968\u7684\u5386\u53f2\u6570\u636e\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u7b80\u5355\u7684\u4ee3\u7801\u5b9e\u73b0\u6570\u636e\u4e0b\u8f7d\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
      import yfinance as yf<\/p>\n
      \u4e0b\u8f7d\u7279\u5b9a\u80a1\u7968\u7684\u6570\u636e<\/strong><\/h2>\n
      ticker = yf.Ticker('AAPL')<\/p>\n
      \u83b7\u53d6\u5386\u53f2\u5e02\u573a\u6570\u636e<\/strong><\/h2>\n
      hist = ticker.history(period="1y")<\/p>\n
      print(hist.head())<\/p>\n
      <\/code><\/pre>\n<\/p>\n<\/li>\n
    2. \n
      \u4f7f\u7528alpha_vantage\u5e93\u83b7\u53d6\u6570\u636e<\/strong><\/p>\n<\/p>\n
      alpha_vantage<\/code>\u5e93\u4e5f\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u91d1\u878d\u6570\u636e\u3002\u4f7f\u7528\u8be5\u5e93\u9700\u8981\u5148\u6ce8\u518c\u4e00\u4e2aAPI key\uff1a<\/p>\n<\/p>\n
      from alpha_vantage.timeseries import TimeSeries<\/p>\n
      \u8bbe\u7f6eAPI key<\/strong><\/h2>\n
      api_key = 'your_api_key'<\/p>\n
      ts = TimeSeries(key=api_key, output_format='pandas')<\/p>\n
      data, meta_data = ts.get_intraday(symbol='AAPL',interval='1min', outputsize='full')<\/p>\n
      print(data.head())<\/p>\n
      <\/code><\/pre>\n<\/p>\n<\/li>\n
    3. \n
      \u4f7f\u7528pandas_datareader\u5e93\u83b7\u53d6\u6570\u636e<\/strong><\/p>\n<\/p>\n
      pandas_datareader<\/code>\u5e93\u4e5f\u662f\u4e00\u4e2a\u975e\u5e38\u6d41\u884c\u7684\u9009\u62e9\uff0c\u53ef\u4ee5\u83b7\u53d6\u5404\u79cd\u91d1\u878d\u6570\u636e\uff1a<\/p>\n<\/p>\n
      import pandas_datareader.data as web<\/p>\n
      from datetime import datetime<\/p>\n
      start = datetime(2020, 1, 1)<\/p>\n
      end = datetime(2021, 1, 1)<\/p>\n
      \u83b7\u53d6\u82f9\u679c\u516c\u53f8\u80a1\u7968\u6570\u636e<\/strong><\/h2>\n
      df = web.DataReader('AAPL', 'yahoo', start, end)<\/p>\n
      print(df.head())<\/p>\n
      <\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n
      \u4e8c\u3001\u6570\u636e\u5904\u7406<\/p>\n<\/p>\n
        \n
      1. \n
        \u6570\u636e\u6e05\u6d17<\/strong><\/p>\n<\/p>\n
        \u5728\u83b7\u53d6\u6570\u636e\u540e\uff0c\u6211\u4eec\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u6e05\u6d17\u548c\u5904\u7406\uff0c\u4f8b\u5982\u5904\u7406\u7f3a\u5931\u503c\u3001\u8c03\u6574\u6570\u636e\u683c\u5f0f\u7b49\uff1a<\/p>\n<\/p>\n
        # \u5904\u7406\u7f3a\u5931\u503c<\/p>\n
        data = data.dropna()<\/p>\n
        \u8c03\u6574\u6570\u636e\u683c\u5f0f<\/strong><\/h2>\n
        data['Date'] = pd.to_datetime(data.index)<\/p>\n
        data.set_index('Date', inplace=True)<\/p>\n
        <\/code><\/pre>\n<\/p>\n<\/li>\n
      2. \n
        \u6570\u636e\u8f6c\u6362<\/strong><\/p>\n<\/p>\n
        \u6709\u65f6\u6211\u4eec\u9700\u8981\u5c06\u6570\u636e\u8f6c\u6362\u4e3a\u7279\u5b9a\u7684\u683c\u5f0f\uff0c\u4ee5\u4fbf\u8fdb\u884c\u540e\u7eed\u5206\u6790\u548c\u5904\u7406\u3002\u4f8b\u5982\uff0c\u5c06\u6570\u636e\u8f6c\u6362\u4e3anumpy\u6570\u7ec4\u6216\u8005pandas dataframe\uff1a<\/p>\n<\/p>\n
        import numpy as np<\/p>\n
        \u5c06\u6570\u636e\u8f6c\u6362\u4e3anumpy\u6570\u7ec4<\/strong><\/h2>\n
        data_np = data.to_numpy()<\/p>\n
        \u5c06\u6570\u636e\u8f6c\u6362\u4e3apandas dataframe<\/strong><\/h2>\n
        data_df = pd.DataFrame(data_np, columns=['Open', 'High', 'Low', 'Close', 'Volume'])<\/p>\n
        <\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n
        \u4e09\u3001\u7b56\u7565\u7f16\u5199<\/p>\n<\/p>\n
          \n
        1. \n
          \u5747\u7ebf\u7b56\u7565<\/strong><\/p>\n<\/p>\n
          \u5747\u7ebf\u7b56\u7565\u662f\u6700\u57fa\u7840\u7684\u6280\u672f\u5206\u6790\u7b56\u7565\u4e4b\u4e00\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8ba1\u7b97\u79fb\u52a8\u5e73\u5747\u7ebf\u6765\u5224\u65ad\u4e70\u5356\u65f6\u673a\uff1a<\/p>\n<\/p>\n
          # \u8ba1\u7b97\u77ed\u671f\u548c\u957f\u671f\u79fb\u52a8\u5e73\u5747\u7ebf<\/p>\n
          data['SMA50'] = data['Close'].rolling(window=50).mean()<\/p>\n
          data['SMA200'] = data['Close'].rolling(window=200).mean()<\/p>\n
          \u7b56\u7565\u6761\u4ef6<\/strong><\/h2>\n
          buy_signal = (data['SMA50'] > data['SMA200'])<\/p>\n
          sell_signal = (data['SMA50'] < data['SMA200'])<\/p>\n
          <\/code><\/pre>\n<\/p>\n<\/li>\n
        2. \n
          \u52a8\u91cf\u7b56\u7565<\/strong><\/p>\n<\/p>\n
          \u52a8\u91cf\u7b56\u7565\u662f\u901a\u8fc7\u5224\u65ad\u80a1\u7968\u4ef7\u683c\u7684\u4e0a\u6da8\u6216\u4e0b\u8dcc\u8d8b\u52bf\u6765\u505a\u51fa\u4e70\u5356\u51b3\u7b56\uff1a<\/p>\n<\/p>\n
          # \u8ba1\u7b97\u80a1\u7968\u4ef7\u683c\u7684\u53d8\u5316<\/p>\n
          data['Momentum'] = data['Close'] - data['Close'].shift(1)<\/p>\n
          \u7b56\u7565\u6761\u4ef6<\/strong><\/h2>\n
          buy_signal = (data['Momentum'] > 0)<\/p>\n
          sell_signal = (data['Momentum'] < 0)<\/p>\n
          <\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n
          \u56db\u3001\u56de\u6d4b\u7cfb\u7edf<\/p>\n<\/p>\n
            \n
          1. \n
            \u56de\u6d4b\u6846\u67b6<\/strong><\/p>\n<\/p>\n
            \u56de\u6d4b\u662f\u9a8c\u8bc1\u7b56\u7565\u6709\u6548\u6027\u7684\u91cd\u8981\u6b65\u9aa4\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528backtrader<\/code>\u5e93\u6765\u6784\u5efa\u56de\u6d4b\u6846\u67b6\uff1a<\/p>\n<\/p>\n
            import backtrader as bt<\/p>\n
            class MyStrategy(bt.Strategy):<\/p>\n
                def __init__(self):<\/p>\n
                    self.sma50 = bt.indicators.SimpleMovingAverage(self.data.close, period=50)<\/p>\n
                    self.sma200 = bt.indicators.SimpleMovingAverage(self.data.close, period=200)<\/p>\n
                def next(self):<\/p>\n
                    if self.sma50 > self.sma200:<\/p>\n
                        self.buy()<\/p>\n
                    elif self.sma50 < self.sma200:<\/p>\n
                        self.sell()<\/p>\n
            \u521b\u5efa\u56de\u6d4b\u5f15\u64ce<\/strong><\/h2>\n
            cerebro = bt.Cerebro()<\/p>\n
            \u6dfb\u52a0\u7b56\u7565<\/strong><\/h2>\n
            cerebro.addstrategy(MyStrategy)<\/p>\n
            \u52a0\u8f7d\u6570\u636e<\/strong><\/h2>\n
            data = bt.feeds.PandasData(dataname=df)<\/p>\n
            cerebro.adddata(data)<\/p>\n
            \u8fd0\u884c\u56de\u6d4b<\/strong><\/h2>\n
            cerebro.run()<\/p>\n
            <\/code><\/pre>\n<\/p>\n<\/li>\n
          2. \n
            \u7b56\u7565\u8bc4\u4f30<\/strong><\/p>\n<\/p>\n
            \u5728\u56de\u6d4b\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u9700\u8981\u5bf9\u7b56\u7565\u8fdb\u884c\u8bc4\u4f30\uff0c\u4ee5\u5224\u65ad\u7b56\u7565\u7684\u6709\u6548\u6027\uff1a<\/p>\n<\/p>\n
            # \u6253\u5370\u7b56\u7565\u7684\u56de\u6d4b\u7ed3\u679c<\/p>\n
            print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())<\/p>\n
            \u7ed8\u5236\u7b56\u7565\u7684\u56de\u6d4b\u66f2\u7ebf<\/strong><\/h2>\n
            cerebro.plot()<\/p>\n
            <\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n
            \u4e94\u3001\u4ea4\u6613\u63a5\u53e3<\/p>\n<\/p>\n
              \n
            1. \n
              \u8c03\u7528\u4ea4\u6613API<\/strong><\/p>\n<\/p>\n
              \u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8c03\u7528\u4ea4\u6613\u5e73\u53f0\u7684API\u63a5\u53e3\uff0c\u5b9e\u73b0\u81ea\u52a8\u4ea4\u6613\u3002\u4ee5alpaca<\/code>\u4ea4\u6613\u5e73\u53f0\u4e3a\u4f8b\uff1a<\/p>\n<\/p>\n
              import alpaca_trade_api as tradeapi<\/p>\n
              \u8bbe\u7f6eAPI key\u548csecret<\/strong><\/h2>\n
              api = tradeapi.REST('your_api_key', 'your_api_secret', base_url='https:\/\/paper-api.alpaca.markets')<\/p>\n
              \u521b\u5efa\u8ba2\u5355<\/strong><\/h2>\n
              order = api.submit_order(<\/p>\n
                  symbol='AAPL',<\/p>\n
                  qty=1,<\/p>\n
                  side='buy',<\/p>\n
                  type='market',<\/p>\n
                  time_in_force='gtc'<\/p>\n
              )<\/p>\n
              <\/code><\/pre>\n<\/p>\n<\/li>\n
            2. \n
              \u4ea4\u6613\u4fe1\u53f7<\/strong><\/p>\n<\/p>\n
              \u6839\u636e\u7b56\u7565\u751f\u6210\u7684\u4e70\u5356\u4fe1\u53f7\uff0c\u81ea\u52a8\u6267\u884c\u4ea4\u6613\uff1a<\/p>\n<\/p>\n
              if buy_signal:<\/p>\n
                  api.submit_order(symbol='AAPL', qty=1, side='buy', type='market', time_in_force='gtc')<\/p>\n
              elif sell_signal:<\/p>\n
                  api.submit_order(symbol='AAPL', qty=1, side='sell', type='market', time_in_force='gtc')<\/p>\n
              <\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n
              \u516d\u3001\u7528\u6237\u754c\u9762<\/p>\n<\/p>\n
                \n
              1. \n
                \u4f7f\u7528Dash\u6784\u5efa\u7528\u6237\u754c\u9762<\/strong><\/p>\n<\/p>\n
                Dash<\/code>\u662f\u4e00\u4e2a\u7528Python\u7f16\u5199\u7684\u5f00\u6e90Web\u5e94\u7528\u6846\u67b6\uff0c\u53ef\u4ee5\u7528\u6765\u6784\u5efa\u6570\u636e\u53ef\u89c6\u5316\u7528\u6237\u754c\u9762\uff1a<\/p>\n<\/p>\n
                import dash<\/p>\n
                import dash_core_components as dcc<\/p>\n
                import dash_html_components as html<\/p>\n
                from dash.dependencies import Input, Output<\/p>\n
                app = dash.Dash(__name__)<\/p>\n
                app.layout = html.Div([<\/p>\n
                    dcc.Graph(id='price-chart'),<\/p>\n
                    dcc.Interval(id='interval-component', interval=1*60000, n_intervals=0)<\/p>\n
                ])<\/p>\n
                @app.callback(Output('price-chart', 'figure'), [Input('interval-component', 'n_intervals')])<\/p>\n
                def update_chart(n):<\/p>\n
                    data = yf.download('AAPL', period='1d', interval='1m')<\/p>\n
                    fig = {<\/p>\n
                        'data': [{'x': data.index, 'y': data['Close'], 'type': 'line', 'name': 'AAPL'}],<\/p>\n
                        'layout': {'title': 'Stock Price'}<\/p>\n
                    }<\/p>\n
                    return fig<\/p>\n
                if __name__ == '__mAI<\/a>n__':<\/p>\n
                    app.run_server(debug=True)<\/p>\n
                <\/code><\/pre>\n<\/p>\n<\/li>\n
              2. \n
                \u4f7f\u7528Tkinter\u6784\u5efa\u684c\u9762\u5e94\u7528<\/strong><\/p>\n<\/p>\n
                Tkinter<\/code>\u662fPython\u7684\u6807\u51c6GUI\u5e93\uff0c\u53ef\u4ee5\u7528\u6765\u6784\u5efa\u684c\u9762\u5e94\u7528\uff1a<\/p>\n<\/p>\n
                import tkinter as tk<\/p>\n
                from tkinter import ttk<\/p>\n
                import yfinance as yf<\/p>\n
                class StockApp:<\/p>\n
                    def __init__(self, root):<\/p>\n
                        self.root = root<\/p>\n
                        self.root.title("Stock App")<\/p>\n
                        self.ticker_label = ttk.Label(root, text="Ticker:")<\/p>\n
                        self.ticker_label.grid(row=0, column=0)<\/p>\n
                        self.ticker_entry = ttk.Entry(root)<\/p>\n
                        self.ticker_entry.grid(row=0, column=1)<\/p>\n
                        self.get_data_button = ttk.Button(root, text="Get Data", command=self.get_data)<\/p>\n
                        self.get_data_button.grid(row=0, column=2)<\/p>\n
                        self.text = tk.Text(root)<\/p>\n
                        self.text.grid(row=1, column=0, columnspan=3)<\/p>\n
                    def get_data(self):<\/p>\n
                        ticker = self.ticker_entry.get()<\/p>\n
                        data = yf.download(ticker, period='1d', interval='1m')<\/p>\n
                        self.text.delete(1.0, tk.END)<\/p>\n
                        self.text.insert(tk.END, str(data))<\/p>\n
                if __name__ == "__main__":<\/p>\n
                    root = tk.Tk()<\/p>\n
                    app = StockApp(root)<\/p>\n
                    root.mainloop()<\/p>\n
                <\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n
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