126 lines
4.3 KiB
Python
126 lines
4.3 KiB
Python
"""
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Script Name:
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Description: 根据yahoo提供的不复权数据，和分红及拆股数据，来计算前复权和后复权数据。
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注意：
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结果对不上！
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按照yahoo规则，不复权数据已经处理了拆股，所以只要把分红加上去就行，但处理结果与它返回的前复权数据，仍然对不对上！
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有些比如AAPL，差不多可以对得上；但对于KDP等，差异甚大，找不到原因。。
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所以，这个程序暂时无法使用。。。
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Author: [Your Name]
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Created Date: YYYY-MM-DD
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Last Modified: YYYY-MM-DD
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Version: 1.0
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Modification History:
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- YYYY-MM-DD [Your Name]:
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- YYYY-MM-DD [Your Name]:
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- YYYY-MM-DD [Your Name]:
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"""
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import pymysql
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import pandas as pd
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import logging
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import os
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import time
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import config
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# 设置日志
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filename = os.path.splitext(os.path.basename(__file__))[0]
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config.setup_logging(f"./log/{filename}.log")
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logger = logging.getLogger()
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# 数据库连接函数
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def connect_to_db():
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return pymysql.connect(**config.db_config)
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# 读取 sp500 表中的所有行，获取 code 和 name
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def fetch_sp500_codes(connection):
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query = "SELECT code, code_name as name FROM sp500 "
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return pd.read_sql(query, connection)
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# 读取 sp500_his_kline_none 表中的数据并按 time_key 降序排列
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def fetch_sp500_his_kline_none(connection, code):
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query = f"SELECT * FROM sp500_his_kline_none WHERE code = '{code}' ORDER BY time_key DESC"
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return pd.read_sql(query, connection)
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# 将计算结果插入到 sp500_ajust_kline_202410 表中
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def insert_adjusted_kline_data(connection, data):
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try:
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with connection.cursor() as cursor:
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insert_query = """
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INSERT INTO sp500_ajust_kline_202410 (code, name, time_key, hfq_open, hfq_close, qfq_open, qfq_close, none_open, none_close)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
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ON DUPLICATE KEY UPDATE
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hfq_open = VALUES(hfq_open),
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hfq_close = VALUES(hfq_close),
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qfq_open = VALUES(qfq_open),
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qfq_close = VALUES(qfq_close),
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none_open = VALUES(none_open),
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none_close = VALUES(none_close)
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"""
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cursor.executemany(insert_query, data)
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connection.commit()
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except Exception as e:
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logger.error(f"Error inserting data: {e}")
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# 计算前复权和后复权的价格，并插入到 sp500_ajust_kline_202410
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def process_and_insert_adjusted_kline(connection, code, name, result_none):
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dividends_qfq = 0
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dividends_hfq = 0
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dividends_total = result_none['dividends'].sum()
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adjusted_data = []
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for index, row in result_none.iterrows():
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# 计算前复权和后复权的开盘价和收盘价
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qfq_close = row['close'] - dividends_qfq
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qfq_open = row['open'] - dividends_qfq
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hfq_close = row['close'] + dividends_hfq
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hfq_open = row['open'] + dividends_hfq
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adjusted_data.append((
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row['code'], row['name'], row['time_key'],
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hfq_open, hfq_close, qfq_open, qfq_close,
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row['open'], row['close']
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))
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dividends_qfq += row['dividends']
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dividends_hfq = dividends_total - dividends_qfq
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# 插入到 sp500_ajust_kline_202410 表中
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insert_adjusted_kline_data(connection, adjusted_data)
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logger.info(f"Successfully processed and inserted data for code {code}")
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# 主函数
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def main():
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try:
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connection = connect_to_db()
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# 读取 sp500 表中的所有行，得到 code 和 name 字段
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sp500_codes = fetch_sp500_codes(connection)
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for index, row in sp500_codes.iterrows():
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code = row['code']
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name = row['name']
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logger.info(f"Processing data for code: {code}, name: {name}")
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# 读取 sp500_his_kline_none 表中的数据并按 time_key 降序排列
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result_none = fetch_sp500_his_kline_none(connection, code)
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if result_none.empty:
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logger.warning(f"No data found for code: {code}")
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continue
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# 处理并插入调整后的 K 线数据
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process_and_insert_adjusted_kline(connection, code, name, result_none)
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except Exception as e:
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logger.error(f"Error occurred: {e}")
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finally:
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if connection:
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connection.close()
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if __name__ == "__main__":
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main() |