{"id":1132112,"date":"2025-01-08T20:54:19","date_gmt":"2025-01-08T12:54:19","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1132112.html"},"modified":"2025-01-08T20:54:21","modified_gmt":"2025-01-08T12:54:21","slug":"python%e9%87%8f%e5%8c%96%e4%ba%a4%e6%98%93%e5%a6%82%e4%bd%95%e8%8e%b7%e5%8f%96%e8%82%a1%e7%a5%a8%e6%95%b0%e6%8d%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1132112.html","title":{"rendered":"python\u91cf\u5316\u4ea4\u6613\u5982\u4f55\u83b7\u53d6\u80a1\u7968\u6570\u636e"},"content":{"rendered":"

\"python\u91cf\u5316\u4ea4\u6613\u5982\u4f55\u83b7\u53d6\u80a1\u7968\u6570\u636e\"<\/p>\n

Python\u91cf\u5316\u4ea4\u6613\u83b7\u53d6\u80a1\u7968\u6570\u636e\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528API\u63a5\u53e3\u3001Web Scraping\u3001\u6570\u636e\u5e93\u67e5\u8be2\u3001\u4f7f\u7528\u91d1\u878d\u6570\u636e\u5e73\u53f0\u3002<\/strong> \u5176\u4e2d\uff0c\u4f7f\u7528API\u63a5\u53e3\u662f\u6700\u5e38\u89c1\u4e14\u9ad8\u6548\u7684\u65b9\u6cd5\u3002API\u63a5\u53e3\u63d0\u4f9b\u4e86\u4fbf\u6377\u7684\u65b9\u5f0f\u6765\u83b7\u53d6\u5b9e\u65f6\u548c\u5386\u53f2\u80a1\u7968\u6570\u636e\uff0c\u5e76\u4e14\u901a\u5e38\u6709\u8be6\u7ec6\u7684\u6587\u6863\u548c\u652f\u6301\u3002\u5e38\u89c1\u7684API\u63d0\u4f9b\u5546\u5305\u62ecYahoo Finance\u3001Alpha Vantage\u3001Quandl\u7b49\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u6765\u83b7\u53d6\u80a1\u7968\u6570\u636e\u3002<\/p>\n<\/p>\n

\n

\u4e00\u3001\u4f7f\u7528API\u63a5\u53e3<\/h3>\n<\/p>\n

API\u63a5\u53e3\u662f\u83b7\u53d6\u80a1\u7968\u6570\u636e\u7684\u4e00\u79cd\u975e\u5e38\u4fbf\u6377\u548c\u9ad8\u6548\u7684\u65b9\u6cd5\u3002\u901a\u8fc7API\u63a5\u53e3\uff0c\u7528\u6237\u53ef\u4ee5\u8f7b\u677e\u83b7\u53d6\u5b9e\u65f6\u548c\u5386\u53f2\u80a1\u7968\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684API\u63a5\u53e3\u53ca\u5176\u4f7f\u7528\u65b9\u6cd5\u3002<\/p>\n<\/p>\n

1. Alpha Vantage<\/h4>\n<\/p>\n

Alpha Vantage \u63d0\u4f9b\u514d\u8d39\u7684API\u63a5\u53e3\uff0c\u80fd\u591f\u63d0\u4f9b\u5168\u7403\u80a1\u7968\u3001\u5916\u6c47\u3001\u52a0\u5bc6\u8d27\u5e01\u7b49\u5e02\u573a\u7684\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528Alpha Vantage\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n

    \n
  1. \u6ce8\u518c\u83b7\u53d6API Key<\/strong>\uff1a\u9996\u5148\uff0c\u9700\u8981\u5728Alpha Vantage\u5b98\u7f51\u6ce8\u518c\u4e00\u4e2a\u8d26\u6237\uff0c\u5e76\u83b7\u53d6API Key\u3002<\/li>\n
  2. \u5b89\u88c5\u76f8\u5173\u5e93<\/strong>\uff1a\u4f7f\u7528requests<\/code>\u5e93\u6216\u8005\u5176\u4ed6HTTP\u5ba2\u6237\u7aef\u6765\u53d1\u9001API\u8bf7\u6c42\u3002<\/li>\n
  3. \u53d1\u9001API\u8bf7\u6c42<\/strong>\uff1a\u5229\u7528API Key\u548c\u80a1\u7968\u4ee3\u7801\u53d1\u9001\u8bf7\u6c42\u5e76\u83b7\u53d6\u6570\u636e\u3002<\/li>\n<\/ol>\n

    import requests<\/p>\n
    API_KEY = 'your_api_key'<\/p>\n
    symbol = 'AAPL'<\/p>\n
    url = f'https:\/\/www.alphavantage.co\/query?function=TIME_SERIES_DAI<\/a>LY&symbol={symbol}&apikey={API_KEY}'<\/p>\n
    response = requests.get(url)<\/p>\n
    data = response.json()<\/p>\n
    \u89e3\u6790\u6570\u636e<\/strong><\/h2>\n
    time_series = data['Time Series (Daily)']<\/p>\n
    for date, stats in time_series.items():<\/p>\n
        print(f"Date: {date}, Open: {stats['1. open']}, High: {stats['2. high']}, Low: {stats['3. low']}, Close: {stats['4. close']}")<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2. Yahoo Finance API<\/h4>\n<\/p>\n
    Yahoo Finance API\u4e5f\u975e\u5e38\u6d41\u884c\uff0c\u63d0\u4f9b\u5168\u9762\u7684\u5e02\u573a\u6570\u636e\u3002\u53ef\u4ee5\u901a\u8fc7yfinance<\/code>\u5e93\u6765\u83b7\u53d6\u6570\u636e\u3002<\/p>\n<\/p>\n
    import yfinance as yf<\/p>\n
    \u83b7\u53d6\u80a1\u7968\u6570\u636e<\/strong><\/h2>\n
    ticker = 'AAPL'<\/p>\n
    stock = yf.Ticker(ticker)<\/p>\n
    hist = stock.history(period='1mo')<\/p>\n
    print(hist)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e8c\u3001Web Scraping<\/h3>\n<\/p>\n
    Web Scraping\u662f\u53e6\u4e00\u79cd\u83b7\u53d6\u80a1\u7968\u6570\u636e\u7684\u65b9\u6cd5\uff0c\u9002\u7528\u4e8e\u90a3\u4e9b\u6ca1\u6709\u63d0\u4f9bAPI\u63a5\u53e3\u7684\u7f51\u7ad9\u3002<\/p>\n<\/p>\n
    1. \u4f7f\u7528BeautifulSoup\u548cRequests<\/h4>\n<\/p>\n
    BeautifulSoup\u548cRequests\u662fPython\u4e2d\u5e38\u7528\u7684Web Scraping\u5e93\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
    import requests<\/p>\n
    from bs4 import BeautifulSoup<\/p>\n
    url = 'https:\/\/finance.yahoo.com\/quote\/AAPL\/history'<\/p>\n
    response = requests.get(url)<\/p>\n
    soup = BeautifulSoup(response.text, 'html.parser')<\/p>\n
    \u89e3\u6790\u80a1\u7968\u6570\u636e<\/strong><\/h2>\n
    table = soup.find('table', {'data-test': 'historical-prices'})<\/p>\n
    rows = table.find_all('tr')<\/p>\n
    for row in rows[1:]:<\/p>\n
        cols = row.find_all('td')<\/p>\n
        if len(cols) > 0:<\/p>\n
            date = cols[0].text<\/p>\n
            close_price = cols[4].text<\/p>\n
            print(f"Date: {date}, Close Price: {close_price}")<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2. \u4f7f\u7528Selenium<\/h4>\n<\/p>\n
    Selenium\u7528\u4e8e\u6a21\u62df\u6d4f\u89c8\u5668\u64cd\u4f5c\uff0c\u53ef\u4ee5\u5904\u7406\u52a8\u6001\u52a0\u8f7d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
    from selenium import webdriver<\/p>\n
    driver = webdriver.Chrome(executable_path='\/path\/to\/chromedriver')<\/p>\n
    driver.get('https:\/\/finance.yahoo.com\/quote\/AAPL\/history')<\/p>\n
    \u7b49\u5f85\u9875\u9762\u52a0\u8f7d\u5b8c\u6bd5<\/strong><\/h2>\n
    import time<\/p>\n
    time.sleep(5)<\/p>\n
    \u83b7\u53d6\u6570\u636e<\/strong><\/h2>\n
    table = driver.find_element_by_xpath('\/\/table[@data-test="historical-prices"]')<\/p>\n
    rows = table.find_elements_by_tag_name('tr')<\/p>\n
    for row in rows[1:]:<\/p>\n
        cols = row.find_elements_by_tag_name('td')<\/p>\n
        if len(cols) > 0:<\/p>\n
            date = cols[0].text<\/p>\n
            close_price = cols[4].text<\/p>\n
            print(f"Date: {date}, Close Price: {close_price}")<\/p>\n
    driver.quit()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e09\u3001\u6570\u636e\u5e93\u67e5\u8be2<\/h3>\n<\/p>\n
    \u4e00\u4e9b\u91d1\u878d\u6570\u636e\u5e73\u53f0\u63d0\u4f9b\u6570\u636e\u5e93\u67e5\u8be2\u63a5\u53e3\uff0c\u53ef\u4ee5\u76f4\u63a5\u8fde\u63a5\u6570\u636e\u5e93\u83b7\u53d6\u80a1\u7968\u6570\u636e\u3002<\/p>\n<\/p>\n
    1. \u4f7f\u7528SQLAlchemy\u8fde\u63a5\u6570\u636e\u5e93<\/h4>\n<\/p>\n
    SQLAlchemy\u662fPython\u4e2d\u5e38\u7528\u7684ORM\u5e93\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fde\u63a5\u548c\u64cd\u4f5c\u6570\u636e\u5e93\u3002<\/p>\n<\/p>\n
    from sqlalchemy import create_engine<\/p>\n
    import pandas as pd<\/p>\n
    \u521b\u5efa\u6570\u636e\u5e93\u8fde\u63a5<\/strong><\/h2>\n
    engine = create_engine('postgresql:\/\/username:password@localhost:5432\/stock_data')<\/p>\n
    \u67e5\u8be2\u80a1\u7968\u6570\u636e<\/strong><\/h2>\n
    query = "SELECT * FROM stock_prices WHERE symbol = 'AAPL'"<\/p>\n
    df = pd.read_sql_query(query, engine)<\/p>\n
    print(df)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u56db\u3001\u4f7f\u7528\u91d1\u878d\u6570\u636e\u5e73\u53f0<\/h3>\n<\/p>\n
    \u8bb8\u591a\u91d1\u878d\u6570\u636e\u5e73\u53f0\u63d0\u4f9b\u4e30\u5bcc\u7684\u80a1\u7968\u6570\u636e\uff0c\u5e76\u4e14\u901a\u5e38\u6709\u8be6\u7ec6\u7684\u6587\u6863\u548c\u652f\u6301\u3002<\/p>\n<\/p>\n
    1. Quandl<\/h4>\n<\/p>\n
    Quandl\u63d0\u4f9b\u5168\u9762\u7684\u91d1\u878d\u6570\u636e\uff0c\u53ef\u4ee5\u901a\u8fc7\u5176API\u63a5\u53e3\u83b7\u53d6\u6570\u636e\u3002<\/p>\n<\/p>\n
    import quandl<\/p>\n
    quandl.ApiConfig.api_key = 'your_api_key'<\/p>\n
    data = quandl.get('WIKI\/AAPL')<\/p>\n
    print(data.head())<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2. Bloomberg Terminal<\/h4>\n<\/p>\n
    Bloomberg Terminal\u662f\u4e00\u4e2a\u4e13\u4e1a\u7684\u91d1\u878d\u6570\u636e\u5e73\u53f0\uff0c\u63d0\u4f9b\u5168\u9762\u7684\u5e02\u573a\u6570\u636e\u3002\u53ef\u4ee5\u901a\u8fc7\u5176API\u63a5\u53e3\u83b7\u53d6\u6570\u636e\u3002<\/p>\n<\/p>\n
    from blpapi import Session<\/p>\n
    session = Session()<\/p>\n
    session.start()<\/p>\n
    session.openService("\/\/blp\/refdata")<\/p>\n
    refDataService = session.getService("\/\/blp\/refdata")<\/p>\n
    request = refDataService.createRequest("HistoricalDataRequest")<\/p>\n
    request.getElement("securities").appendValue("AAPL US Equity")<\/p>\n
    request.getElement("fields").appendValue("PX_LAST")<\/p>\n
    request.set("startDate", "20220101")<\/p>\n
    request.set("endDate", "20221231")<\/p>\n
    session.sendRequest(request)<\/p>\n
    while(True):<\/p>\n
        event = session.nextEvent()<\/p>\n
        for msg in event:<\/p>\n
            print(msg)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e94\u3001\u6570\u636e\u5b58\u50a8\u548c\u5904\u7406<\/h3>\n<\/p>\n
    \u83b7\u53d6\u5230\u80a1\u7968\u6570\u636e\u540e\uff0c\u901a\u5e38\u9700\u8981\u8fdb\u884c\u5b58\u50a8\u548c\u5904\u7406\uff0c\u4ee5\u4fbf\u4e8e\u540e\u7eed\u7684\u5206\u6790\u548c\u4f7f\u7528\u3002<\/p>\n<\/p>\n
    1. \u5b58\u50a8\u6570\u636e<\/h4>\n<\/p>\n
    \u53ef\u4ee5\u5c06\u6570\u636e\u5b58\u50a8\u5728\u6570\u636e\u5e93\u3001CSV\u6587\u4ef6\u6216\u8005HDF5\u6587\u4ef6\u4e2d\u3002<\/p>\n<\/p>\n
    # \u5b58\u50a8\u5230CSV\u6587\u4ef6<\/p>\n
    df.to_csv('stock_data.csv', index=False)<\/p>\n
    \u5b58\u50a8\u5230HDF5\u6587\u4ef6<\/strong><\/h2>\n
    df.to_hdf('stock_data.h5', key='df', mode='w')<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2. \u6570\u636e\u5904\u7406<\/h4>\n<\/p>\n
    \u6570\u636e\u5904\u7406\u662f\u91cf\u5316\u4ea4\u6613\u4e2d\u7684\u5173\u952e\u6b65\u9aa4\uff0c\u901a\u5e38\u5305\u62ec\u6570\u636e\u6e05\u6d17\u3001\u6570\u636e\u8f6c\u6362\u548c\u7279\u5f81\u5de5\u7a0b\u7b49\u3002<\/p>\n<\/p>\n
    # \u6570\u636e\u6e05\u6d17<\/p>\n
    df.dropna(inplace=True)<\/p>\n
    \u6570\u636e\u8f6c\u6362<\/strong><\/h2>\n
    df['date'] = pd.to_datetime(df['date'])<\/p>\n
    df.set_index('date', inplace=True)<\/p>\n
    \u7279\u5f81\u5de5\u7a0b<\/strong><\/h2>\n
    df['returns'] = df['close'].pct_change()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
    \u901a\u8fc7\u4e0a\u8ff0\u65b9\u6cd5\uff0cPython\u91cf\u5316\u4ea4\u6613\u4e2d\u83b7\u53d6\u80a1\u7968\u6570\u636e\u53d8\u5f97\u975e\u5e38\u7b80\u5355\u548c\u9ad8\u6548\u3002\u4f7f\u7528API\u63a5\u53e3\u83b7\u53d6\u6570\u636e<\/strong>\u662f\u6700\u5e38\u89c1\u548c\u4fbf\u6377\u7684\u65b9\u6cd5\uff0c\u5176\u6b21\u662f\u901a\u8fc7Web Scraping\u83b7\u53d6\u6570\u636e<\/strong>\uff0c\u7136\u540e\u662f\u901a\u8fc7\u6570\u636e\u5e93\u67e5\u8be2\u548c\u4f7f\u7528\u91d1\u878d\u6570\u636e\u5e73\u53f0\u83b7\u53d6\u6570\u636e<\/strong>\u3002\u83b7\u53d6\u5230\u6570\u636e\u540e\uff0c\u9700\u8981\u8fdb\u884c\u9002\u5f53\u7684\u5b58\u50a8\u548c\u5904\u7406\uff0c\u4ee5\u4fbf\u4e8e\u540e\u7eed\u7684\u5206\u6790\u548c\u4f7f\u7528\u3002\u5e0c\u671b\u8fd9\u7bc7\u6587\u7ae0\u80fd\u591f\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u7406\u89e3\u548c\u638c\u63e1Python\u91cf\u5316\u4ea4\u6613\u4e2d\u83b7\u53d6\u80a1\u7968\u6570\u636e\u7684\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u5728Python\u4e2d\u83b7\u53d6\u5b9e\u65f6\u80a1\u7968\u6570\u636e\uff1f<\/strong>
    \u5728Python\u4e2d\u83b7\u53d6\u5b9e\u65f6\u80a1\u7968\u6570\u636e\u53ef\u4ee5\u4f7f\u7528\u591a\u79cdAPI\u548c\u5e93\uff0c\u4f8b\u5982Alpha Vantage\u3001Yahoo Finance\u548cIEX Cloud\u3002\u901a\u8fc7\u8fd9\u4e9b\u5e73\u53f0\uff0c\u7528\u6237\u53ef\u4ee5\u6ce8\u518c\u5e76\u83b7\u53d6API\u5bc6\u94a5\uff0c\u7136\u540e\u4f7f\u7528requests<\/code>\u5e93\u6216\u8005\u4e13\u95e8\u7684\u5e93\u5982yfinance<\/code>\u6765\u63d0\u53d6\u5b9e\u65f6\u6570\u636e\u3002\u6b64\u5916\uff0c\u8fd8\u53ef\u4ee5\u901a\u8fc7Web\u722c\u866b\u6280\u672f\u4ece\u91d1\u878d\u7f51\u7ad9\u6293\u53d6\u6570\u636e\uff0c\u4f46\u9700\u9075\u5b88\u76f8\u5173\u7f51\u7ad9\u7684\u4f7f\u7528\u6761\u6b3e\u3002<\/p>\n
    \u6709\u54ea\u4e9bPython\u5e93\u9002\u5408\u8fdb\u884c\u80a1\u7968\u6570\u636e\u5206\u6790\uff1f<\/strong>
    \u5728\u8fdb\u884c\u80a1\u7968\u6570\u636e\u5206\u6790\u65f6\uff0c\u6709\u51e0\u4e2a\u6d41\u884c\u7684Python\u5e93\u975e\u5e38\u6709\u7528\u3002pandas<\/code>\u662f\u5904\u7406\u6570\u636e\u7684\u5f3a\u5927\u5de5\u5177\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u5904\u7406\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u3002matplotlib<\/code>\u548cseaborn<\/code>\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\uff0c\u5e2e\u52a9\u7528\u6237\u66f4\u597d\u5730\u7406\u89e3\u6570\u636e\u8d8b\u52bf\u3002TA-Lib<\/code>\u548cBacktrader<\/code>\u5219\u4e13\u6ce8\u4e8e\u6280\u672f\u5206\u6790\u548c\u56de\u6d4b\u7b56\u7565\u3002<\/p>\n
    \u5982\u4f55\u5904\u7406\u83b7\u53d6\u7684\u80a1\u7968\u6570\u636e\u4ee5\u8fdb\u884c\u91cf\u5316\u4ea4\u6613\uff1f<\/strong>
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