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8e10b93 5bf34fc 8e10b93 5bf34fc 8e10b93 | 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 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 | """
File-based cache for price data with collision-proof keys.
Provides:
- Parquet-based storage for efficiency
- Collision-proof cache keys via fetch_params fingerprint
- Cache invalidation and cleanup
"""
import hashlib
import json
import logging
from pathlib import Path
from datetime import datetime, timezone
from typing import Optional
import pandas as pd
from screener.core.fingerprint import compute_file_fingerprint
logger = logging.getLogger(__name__)
class FetchParams:
"""
Immutable fetch parameters that define a unique cache entry.
COLLISION-PROOF GUARANTEE:
Any change to these parameters produces a different cache key.
"""
def __init__(
self,
symbol: str,
start_date: str,
end_date: str,
interval: str = "1d",
resample_rule: str = "W-FRI",
price_field: str = "Close",
auto_adjust: bool = True,
actions: bool = True
):
self.symbol = symbol
self.start_date = start_date
self.end_date = end_date
self.interval = interval
self.resample_rule = resample_rule
self.price_field = price_field
self.auto_adjust = auto_adjust
self.actions = actions
def to_dict(self) -> dict:
"""Convert to ordered dict for hashing."""
return {
"symbol": self.symbol,
"start_date": self.start_date,
"end_date": self.end_date,
"interval": self.interval,
"resample_rule": self.resample_rule,
"price_field": self.price_field,
"auto_adjust": self.auto_adjust,
"actions": self.actions
}
def fingerprint(self) -> str:
"""
Compute deterministic fingerprint of fetch params.
Returns 8-char hex string (collision probability ~1 in 4 billion).
"""
data = json.dumps(self.to_dict(), sort_keys=True).encode("utf-8")
return hashlib.sha256(data).hexdigest()[:8]
def cache_key(self) -> str:
"""
Generate collision-proof cache key.
Format: {safe_symbol}_{start}_{end}_{params_fingerprint}
Example: HG_F_2018-01-01_2024-01-19_a3f2c891
"""
safe_symbol = self.symbol.replace("=", "_").replace("^", "_").replace(".", "_")
return f"{safe_symbol}_{self.start_date}_{self.end_date}_{self.fingerprint()}"
class PriceCache:
"""
File-based cache for raw price data with collision-proof keys.
Stores DataFrames as Parquet files.
Tracks fingerprints for integrity verification.
CACHE KEY CONTRACT (COLLISION-PROOF):
Cache key = f"{symbol}_{start}_{end}_{params_fingerprint}"
The params_fingerprint is a SHA256 hash of:
- symbol, start_date, end_date
- interval (e.g., "1d")
- resample_rule (e.g., "W-FRI")
- price_field (e.g., "Close")
- auto_adjust, actions
This GUARANTEES that any change to fetch parameters produces
a different cache file, eliminating collision risk.
"""
def __init__(self, cache_dir: str | Path, namespace: Optional[str] = None):
"""
Initialize cache.
Args:
cache_dir: Base directory for cache files
namespace: Optional namespace subdirectory (e.g., config_hash[:8])
"""
self.base_dir = Path(cache_dir)
# Use namespace subdirectory if provided
if namespace:
self.cache_dir = self.base_dir / namespace
else:
self.cache_dir = self.base_dir
self.cache_dir.mkdir(parents=True, exist_ok=True)
self.checksums_file = self.cache_dir / "checksums.json"
self._checksums: dict[str, dict] = {}
self._load_checksums()
def _load_checksums(self):
"""Load existing checksums from file."""
if self.checksums_file.exists():
with open(self.checksums_file, "r") as f:
self._checksums = json.load(f)
def _save_checksums(self):
"""Save checksums to file."""
with open(self.checksums_file, "w") as f:
json.dump(self._checksums, f, indent=2, sort_keys=True)
def _make_path(self, cache_key: str) -> Path:
"""Get file path for cache key."""
return self.cache_dir / f"{cache_key}.parquet"
def get(self, params: FetchParams) -> Optional[pd.DataFrame]:
"""
Get cached DataFrame for fetch params.
Args:
params: FetchParams object defining the cache entry
Returns:
DataFrame if cached and valid, None otherwise
"""
cache_key = params.cache_key()
path = self._make_path(cache_key)
# Debug log for cache lookup
exists = path.exists()
logger.info(f"Cache lookup: {params.symbol} -> {path.name} (exists={exists})")
if not exists:
return None
try:
df = pd.read_parquet(path)
logger.info(f"Cache hit: {params.symbol} ({len(df)} rows)")
return df
except Exception as e:
logger.warning(f"Cache read failed for {params.symbol}: {e}")
return None
def put(self, params: FetchParams, df: pd.DataFrame) -> str:
"""
Store DataFrame in cache.
Args:
params: FetchParams object defining the cache entry
df: DataFrame to cache
Returns:
Fingerprint of stored file
"""
cache_key = params.cache_key()
path = self._make_path(cache_key)
df.to_parquet(path, index=True)
fingerprint = compute_file_fingerprint(path)
# Store metadata with checksum
self._checksums[cache_key] = {
"sha256": fingerprint,
"params": params.to_dict(),
"rows": len(df),
"cached_at": datetime.now(timezone.utc).isoformat()
}
self._save_checksums()
logger.debug(f"Cached: {params.symbol} ({len(df)} rows)")
return fingerprint
def has(self, params: FetchParams) -> bool:
"""Check if params are cached."""
cache_key = params.cache_key()
return self._make_path(cache_key).exists()
def get_metadata(self, params: FetchParams) -> Optional[dict]:
"""Get metadata for cached entry."""
cache_key = params.cache_key()
return self._checksums.get(cache_key)
def clear(self, older_than_days: Optional[int] = None):
"""
Clear cache files.
Args:
older_than_days: Only clear files older than N days (None = all)
"""
import os
from datetime import timedelta
cutoff = None
if older_than_days is not None:
cutoff = datetime.now(timezone.utc) - timedelta(days=older_than_days)
cleared = 0
for path in self.cache_dir.glob("*.parquet"):
should_clear = True
if cutoff is not None:
mtime = datetime.fromtimestamp(
os.path.getmtime(path),
tz=timezone.utc
)
should_clear = mtime < cutoff
if should_clear:
path.unlink()
cleared += 1
# Rebuild checksums from remaining files
remaining_keys = set()
for path in self.cache_dir.glob("*.parquet"):
remaining_keys.add(path.stem)
self._checksums = {k: v for k, v in self._checksums.items() if k in remaining_keys}
self._save_checksums()
logger.info(f"Cleared {cleared} cache files")
# Backward compatibility wrapper
def create_fetch_params(
symbol: str,
start_date: str,
end_date: str,
**kwargs
) -> FetchParams:
"""Helper to create FetchParams with defaults."""
return FetchParams(
symbol=symbol,
start_date=start_date,
end_date=end_date,
**kwargs
)
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