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codex_jxs_code/strategy/data_loader.py
2026-02-23 04:09:34 +08:00

70 lines
2.1 KiB
Python

"""
数据加载模块 - 从 SQLite 加载多周期K线数据为 DataFrame
"""
import pandas as pd
from peewee import SqliteDatabase
from pathlib import Path
DB_PATH = Path(__file__).parent.parent / 'models' / 'database.db'
# 周期 -> 表名
PERIOD_MAP = {
'1m': 'bitmart_eth_1m',
'3m': 'bitmart_eth_3m',
'5m': 'bitmart_eth_5m',
'15m': 'bitmart_eth_15m',
'30m': 'bitmart_eth_30m',
'1h': 'bitmart_eth_1h',
}
def load_klines(period: str, start_date: str, end_date: str) -> pd.DataFrame:
"""
加载指定周期、指定日期范围的K线数据
:param period: '1m','3m','5m','15m','30m','1h'
:param start_date: 'YYYY-MM-DD'
:param end_date: 'YYYY-MM-DD' (不包含该日)
:return: DataFrame with columns: datetime, open, high, low, close
"""
table = PERIOD_MAP.get(period)
if not table:
raise ValueError(f"不支持的周期: {period}, 可选: {list(PERIOD_MAP.keys())}")
start_ts = int(pd.Timestamp(start_date).timestamp() * 1000)
end_ts = int(pd.Timestamp(end_date).timestamp() * 1000)
db = SqliteDatabase(str(DB_PATH))
db.connect()
cursor = db.execute_sql(
f'SELECT id, open, high, low, close FROM [{table}] '
f'WHERE id >= ? AND id < ? ORDER BY id',
(start_ts, end_ts)
)
rows = cursor.fetchall()
db.close()
df = pd.DataFrame(rows, columns=['timestamp_ms', 'open', 'high', 'low', 'close'])
df['datetime'] = pd.to_datetime(df['timestamp_ms'], unit='ms')
df.set_index('datetime', inplace=True)
df.drop(columns=['timestamp_ms'], inplace=True)
df = df.astype(float)
return df
def load_multi_period(periods: list, start_date: str, end_date: str) -> dict:
"""
加载多个周期的数据
:return: {period: DataFrame}
"""
result = {}
for p in periods:
result[p] = load_klines(p, start_date, end_date)
print(f" 加载 {p}: {len(result[p])} 条 ({start_date} ~ {end_date})")
return result
if __name__ == '__main__':
data = load_multi_period(['5m', '15m', '1h'], '2020-01-01', '2024-01-01')
for k, v in data.items():
print(f"{k}: {v.shape}, {v.index[0]} ~ {v.index[-1]}")