From 41beb2ec33f6b60cd1866949cba1b9b7a2921258 Mon Sep 17 00:00:00 2001 From: unknown Date: Thu, 28 Aug 2025 22:09:59 +0800 Subject: [PATCH] update Export Data Farmat --- DataAnalysis/DataExporter.py | 4 ++-- DataAnalysis/MarketDataCalculator.py | 32 ++++------------------------ UpdateFutuData/KLineUpdater.py | 2 +- config/HK_futu.txt | 5 ++++- 4 files changed, 11 insertions(+), 32 deletions(-) diff --git a/DataAnalysis/DataExporter.py b/DataAnalysis/DataExporter.py index 01f9b8c..573597f 100644 --- a/DataAnalysis/DataExporter.py +++ b/DataAnalysis/DataExporter.py @@ -45,11 +45,11 @@ class DataExporter: field_names = [col['COLUMN_NAME'] for col in columns if col['COLUMN_NAME'] not in ('id', 'update_time')] - # 查询数据 + # 查询数据, 按照 avg_all 字段倒叙排列 data = db.execute_query(f""" SELECT {', '.join(field_names)} FROM {table_name} - ORDER BY stock_code + ORDER BY avg_all DESC """) if not data: diff --git a/DataAnalysis/MarketDataCalculator.py b/DataAnalysis/MarketDataCalculator.py index e9d943f..371d6e8 100644 --- a/DataAnalysis/MarketDataCalculator.py +++ b/DataAnalysis/MarketDataCalculator.py @@ -31,33 +31,6 @@ class MarketDataCalculator: - 导出数据到CSV文件 """ - # # 表头映射配置 - # HEADER_MAP = { - # 'stock_code': '股票代码', - # 'stock_name': '股票名称', - # 'ym_2501': '2025年01月', - # 'ym_2502': '2025年02月', - # 'ym_2503': '2025年03月', - # 'ym_2504': '2025年04月', - # 'ym_2505': '2025年05月', - # 'ym_2506': '2025年06月', - # 'ym_2507': '2025年07月', - # 'ym_2508': '2025年08月', - # 'avg_all': '月度均值' - # } - - # # 月份范围配置 - # MONTH_RANGES = { - # 'ym_2501': ('2025-01-01', '2025-01-31'), - # 'ym_2502': ('2025-02-01', '2025-02-28'), - # 'ym_2503': ('2025-03-01', '2025-03-31'), - # 'ym_2504': ('2025-04-01', '2025-04-30'), - # 'ym_2505': ('2025-05-01', '2025-05-31'), - # 'ym_2506': ('2025-06-01', '2025-06-30'), - # 'ym_2507': ('2025-07-01', '2025-07-31'), - # 'ym_2508': ('2025-08-01', '2025-08-31') - # } - def __init__(self, db_config: dict, logger_name: str = 'Calculate'): """ 初始化市场数据计算器 @@ -155,7 +128,9 @@ class MarketDataCalculator: """.format(source_table) result = db.execute_query(sql, (stock_code, start_date, end_date)) - monthly_data[month_col] = float(result[0]['avg_close']) * 1000 if result and result[0]['avg_close'] else None + # 保存小数点后两位，以亿为单位 + # monthly_data[month_col] = float(result[0]['avg_close']) * 1000 if result and result[0]['avg_close'] else None + monthly_data[month_col] = round(float(result[0]['avg_close']) * 1000 / 100000000, 3) if result and result[0]['avg_close'] else None # 提取所有以 'ym_' 开头的键的值 ym_values = [value for key, value in monthly_data.items() if key.startswith('ym_')] @@ -167,6 +142,7 @@ class MarketDataCalculator: monthly_data['avg_all'] = average self.logger.debug(f"股票 {stock_code} 月间流通市值平均值为: {average}") else: + monthly_data['avg_all'] = 0 # 给一个空值，保证数据库不报错 self.logger.warning(f"股票 {stock_code} 没有有效的月度数据") # 插入或更新数据 diff --git a/UpdateFutuData/KLineUpdater.py b/UpdateFutuData/KLineUpdater.py index 2dfdf45..94ff100 100644 --- a/UpdateFutuData/KLineUpdater.py +++ b/UpdateFutuData/KLineUpdater.py @@ -362,7 +362,7 @@ class KLineUpdater: # 这里可以添加具体的更新逻辑 # 例如：遍历股票代码，获取数据并保存到数据库 # 每天收盘后更新数据 -> 操作界面中，这个参数需要放出来 - start_date = (datetime.now() - timedelta(days = 3 * 356)).strftime("%Y-%m-%d") + start_date = (datetime.now() - timedelta(days = 1)).strftime("%Y-%m-%d") end_date = (datetime.now() + timedelta(days = 1)).strftime("%Y-%m-%d") # 获取流通股数据字典 diff --git a/config/HK_futu.txt b/config/HK_futu.txt index 7b7700a..c4b5a77 100644 --- a/config/HK_futu.txt +++ b/config/HK_futu.txt @@ -892,4 +892,7 @@ HK.01591 HK.01715 HK.00489 HK.08218 -HK.06960 \ No newline at end of file +HK.06960 +HK.02936 +HK.03858 +HK.08132 \ No newline at end of file