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0125724 | 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 | """
TradeSense AI β In-Memory Market Data Cache
TTL-enforced caching with rich audit metadata. API credentials are NEVER stored.
"""
import time
from datetime import date, datetime, timezone
from typing import Dict, Optional, Tuple, Any
import pandas as pd
from backend.config.settings import settings
from backend.app.schemas.contracts import DatasetMetadata
class CacheEntryMetadata:
"""
Audit metadata stored alongside each cached dataset.
SECURITY: Must never contain API keys, auth headers, or secrets.
"""
__slots__ = (
"ticker", "start_date", "end_date", "cutoff_session",
"dataset_version", "quality_status", "provider",
"lineage_hash", "created_at", "expires_at",
)
def __init__(
self,
ticker: str,
start_date: date,
end_date: date,
cutoff_session: date,
dataset_version: str,
quality_status: str,
provider: str,
lineage_hash: str,
ttl_seconds: int,
):
self.ticker = ticker
self.start_date = start_date
self.end_date = end_date
self.cutoff_session = cutoff_session
self.dataset_version = dataset_version
self.quality_status = quality_status
self.provider = provider
self.lineage_hash = lineage_hash
self.created_at: datetime = datetime.now(timezone.utc)
self.expires_at: float = time.time() + ttl_seconds
def is_expired(self) -> bool:
return time.time() > self.expires_at
def safe_dict(self) -> Dict[str, Any]:
"""Returns a safe, credential-free audit snapshot of this entry."""
return {
"ticker": self.ticker,
"start_date": str(self.start_date),
"end_date": str(self.end_date),
"cutoff_session": str(self.cutoff_session),
"dataset_version": self.dataset_version,
"quality_status": self.quality_status,
"provider": self.provider,
"lineage_hash": self.lineage_hash,
"created_at": self.created_at.isoformat(),
"expires_at": datetime.fromtimestamp(self.expires_at, tz=timezone.utc).isoformat(),
}
class CacheEntry:
"""Stores a frozen DataFrame + DatasetMetadata pair with TTL enforcement."""
def __init__(
self,
df: pd.DataFrame,
metadata: DatasetMetadata,
ttl_seconds: int,
):
self.df = df.copy()
self.metadata = metadata
self.cache_meta = CacheEntryMetadata(
ticker=metadata.ticker,
start_date=metadata.start_session,
end_date=metadata.cutoff_session,
cutoff_session=metadata.cutoff_session,
dataset_version=metadata.dataset_version,
quality_status=(
metadata.quality_report.quality_status.value
if metadata.quality_report else "UNKNOWN"
),
provider=metadata.source_primary,
lineage_hash=metadata.sha256_hash,
ttl_seconds=ttl_seconds,
)
def is_expired(self) -> bool:
return self.cache_meta.is_expired()
class MarketDataCache:
"""
Thread-safe in-memory cache for canonical OHLCV datasets.
Enforces:
- TTL expiry
- Cutoff T validation on retrieval (cached data cannot bypass temporal isolation)
- No credential storage
"""
def __init__(self):
self._cache: Dict[str, CacheEntry] = {}
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Internal helpers
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
@staticmethod
def _build_key(ticker: str, start_date: Any, end_date: Any, cutoff_session: Any) -> str:
return f"{ticker.upper()}|{start_date}|{end_date}|{cutoff_session}"
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Public API
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def get(
self,
ticker: str,
start_date: Any,
end_date: Any,
cutoff_session: Any,
) -> Optional[Tuple[pd.DataFrame, DatasetMetadata]]:
"""
Returns a cached (DataFrame, DatasetMetadata) pair if:
- The cache is enabled
- An unexpired entry exists for this key
- The cached dataset's cutoff_session matches the requested cutoff (temporal safety)
"""
if not settings.market_data.cache_enabled:
return None
key = self._build_key(ticker, start_date, end_date, cutoff_session)
entry = self._cache.get(key)
if entry is None:
return None
if entry.is_expired():
del self._cache[key]
return None
# CRITICAL: Validate that the cached cutoff matches the requested cutoff.
# This prevents stale cache entries from violating temporal isolation.
if str(entry.cache_meta.cutoff_session) != str(cutoff_session):
return None
return entry.df.copy(), entry.metadata
def set(
self,
ticker: str,
start_date: Any,
end_date: Any,
cutoff_session: Any,
df: pd.DataFrame,
metadata: DatasetMetadata,
is_historical: bool = True,
) -> None:
"""Stores a canonical dataset under the given key with appropriate TTL."""
if not settings.market_data.cache_enabled:
return
key = self._build_key(ticker, start_date, end_date, cutoff_session)
ttl = (
settings.market_data.historical_cache_ttl_seconds
if is_historical
else settings.market_data.latest_data_cache_ttl_seconds
)
self._cache[key] = CacheEntry(df, metadata, ttl)
def get_entry_metadata(
self,
ticker: str,
start_date: Any,
end_date: Any,
cutoff_session: Any,
) -> Optional[Dict[str, Any]]:
"""Returns safe, credential-free metadata for a cached entry."""
key = self._build_key(ticker, start_date, end_date, cutoff_session)
entry = self._cache.get(key)
if entry is None or entry.is_expired():
return None
return entry.cache_meta.safe_dict()
def invalidate(self, ticker: str) -> int:
"""Evicts all entries for a ticker. Returns count evicted."""
keys_to_drop = [k for k in self._cache if k.startswith(f"{ticker.upper()}|")]
for k in keys_to_drop:
del self._cache[k]
return len(keys_to_drop)
def clear(self) -> None:
self._cache.clear()
def stats(self) -> Dict[str, Any]:
"""Returns aggregate cache statistics (no credentials)."""
live = sum(1 for e in self._cache.values() if not e.is_expired())
return {
"total_entries": len(self._cache),
"live_entries": live,
"expired_entries": len(self._cache) - live,
}
# Global Singleton Market Data Cache
data_cache = MarketDataCache()
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