macrotrends金融数据抓取

最新推荐文章于 2025-06-25 17:09:21 发布

原创最新推荐文章于 2025-06-25 17:09:21 发布 · 789 阅读

1 ·

CC 4.0 BY-SA版权

Python 专栏收录该内容

48 篇文章

订阅专栏

本文介绍了一种从网络抓取指定LIBOR利率历史数据的方法，并将其保存为CSV文件的过程。该过程涉及通过特定网址获取网页源代码，解析数据并最终以CSV格式存储。


def createLIBOR_Rate_CSV():
    for LIBOR_Rate_Date_Period, DataId in LIBOR_Rate_Date_Period2DataId.items():
        webpageSourceCode = getWebResponseText(f'https://www.macrotrends.net/assets/php/chart_iframe_comp.php?id={DataId}&url=1-month-libor-rate-historical-chart')
        originalDataStr = originalDataPtn.search(webpageSourceCode, pos=8000).group(1)

        rowDataList = []
        for tableRowData in eval(originalDataStr):
            rowDataList.append([tableRowData['date'], tableRowData.get('close')])  # 后面这个数据最近几天没有值
        # print(rowDataList)
        with open(f'./FinancialCharts/static/FinancialCharts/FinancialData/{LIBOR_Rate_Date_Period}.csv', 'w', newline='') as csvfile:  # If csvfile is a file object, it should be opened with newline=''
            writer = csv.writer(csvfile)  # , quoting=csv.QUOTE_NONNUMERIC
            writer.writerow(['date', 'close'])
            writer.writerows(rowDataList)