File size: 2,835 Bytes
4c34a21 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | # backend/app/data_cache.py
"""
本地 Parquet 数据缓存层 — 减少 yfinance 重复下载，提升回测响应速度
"""
import os
import pandas as pd
import hashlib
from datetime import datetime, timedelta
CACHE_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "data_cache")
os.makedirs(CACHE_DIR, exist_ok=True)
# 缓存 TTL 配置（秒）
CACHE_TTL = {
"1m": 60 * 30, # 30分钟
"5m": 60 * 60, # 1小时
"15m": 60 * 60 * 2, # 2小时
"30m": 60 * 60 * 4, # 4小时
"1h": 60 * 60 * 8, # 8小时
"1d": 60 * 60 * 24, # 24小时
}
def _cache_key(ticker: str, period: str, interval: str) -> str:
raw = f"{ticker}_{period}_{interval}"
return hashlib.md5(raw.encode()).hexdigest()[:12]
def _cache_path(key: str) -> str:
return os.path.join(CACHE_DIR, f"{key}.parquet")
def _meta_path(key: str) -> str:
return os.path.join(CACHE_DIR, f"{key}.meta")
def get_cached(ticker: str, period: str, interval: str):
"""读取缓存，过期或不存在返回 None"""
key = _cache_key(ticker, period, interval)
parquet_file = _cache_path(key)
meta_file = _meta_path(key)
if not os.path.exists(parquet_file) or not os.path.exists(meta_file):
return None
# 检查过期时间
try:
with open(meta_file, 'r') as f:
saved_time = float(f.read().strip())
except Exception:
return None
ttl = CACHE_TTL.get(interval, 3600)
if datetime.now().timestamp() - saved_time > ttl:
return None # 已过期
try:
df = pd.read_parquet(parquet_file)
return df
except Exception:
return None
def save_cache(ticker: str, period: str, interval: str, df: pd.DataFrame):
"""保存数据到 Parquet 缓存"""
if df is None or df.empty:
return
key = _cache_key(ticker, period, interval)
try:
df.to_parquet(_cache_path(key))
with open(_meta_path(key), 'w') as f:
f.write(str(datetime.now().timestamp()))
except Exception as e:
print(f"缓存写入失败: {e}")
def invalidate_cache(ticker: str = None):
"""清除缓存，ticker=None 时清除全部"""
for fname in os.listdir(CACHE_DIR):
fpath = os.path.join(CACHE_DIR, fname)
try:
os.remove(fpath)
except Exception:
pass
def get_cache_stats() -> dict:
"""返回缓存使用统计"""
try:
files = [f for f in os.listdir(CACHE_DIR) if f.endswith('.parquet')]
total_size = sum(os.path.getsize(os.path.join(CACHE_DIR, f)) for f in os.listdir(CACHE_DIR))
except Exception:
files = []
total_size = 0
return {
"cached_datasets": len(files),
"total_size_mb": round(total_size / 1024 / 1024, 2),
"cache_dir": CACHE_DIR
}
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