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"""
Database Query Functions for Cached Market Data
Provides REAL data access from cached_market_data and cached_ohlc tables
CRITICAL RULES:
- ONLY read from database - NEVER generate fake data
- Return empty list if no data found
- All queries must be REAL database operations
"""
import logging
from datetime import datetime, timedelta
from typing import Optional, List, Dict, Any
from sqlalchemy import desc, and_, func
from sqlalchemy.orm import Session
from database.models import CachedMarketData, CachedOHLC
from database.db_manager import DatabaseManager
from utils.logger import setup_logger
logger = setup_logger("cache_queries")
class CacheQueries:
"""
Database query operations for cached market data
CRITICAL: All methods return REAL data from database ONLY
"""
def __init__(self, db_manager: DatabaseManager):
self.db = db_manager
def get_cached_market_data(
self,
symbols: Optional[List[str]] = None,
limit: int = 100
) -> List[Dict[str, Any]]:
"""
Get cached market data from database
CRITICAL RULES:
- ONLY read from cached_market_data table
- NEVER generate or fake data
- Return empty list if no data found
- Use DISTINCT ON to get latest data per symbol
Args:
symbols: List of symbols to filter (e.g., ['BTC', 'ETH'])
limit: Maximum number of records
Returns:
List of dictionaries with REAL market data from database
"""
try:
with self.db.get_session() as session:
# Subquery to get latest fetched_at for each symbol
subq = session.query(
CachedMarketData.symbol,
func.max(CachedMarketData.fetched_at).label('max_fetched_at')
).group_by(CachedMarketData.symbol)
if symbols:
subq = subq.filter(CachedMarketData.symbol.in_(symbols))
subq = subq.subquery()
# Join to get full records for latest entries
query = session.query(CachedMarketData).join(
subq,
and_(
CachedMarketData.symbol == subq.c.symbol,
CachedMarketData.fetched_at == subq.c.max_fetched_at
)
).order_by(desc(CachedMarketData.fetched_at)).limit(limit)
results = query.all()
if not results:
logger.info(f"No cached market data found for symbols={symbols}")
return []
# Convert to dictionaries - REAL data from database
data = []
for row in results:
data.append({
"symbol": row.symbol,
"price": float(row.price),
"market_cap": float(row.market_cap) if row.market_cap else None,
"volume_24h": float(row.volume_24h) if row.volume_24h else None,
"change_24h": float(row.change_24h) if row.change_24h else None,
"high_24h": float(row.high_24h) if row.high_24h else None,
"low_24h": float(row.low_24h) if row.low_24h else None,
"provider": row.provider,
"fetched_at": row.fetched_at
})
logger.info(f"Retrieved {len(data)} cached market records")
return data
except Exception as e:
logger.error(f"Database error in get_cached_market_data: {e}", exc_info=True)
# Return empty list on error - NEVER fake data
return []
def get_cached_ohlc(
self,
symbol: str,
interval: str = "1h",
limit: int = 1000
) -> List[Dict[str, Any]]:
"""
Get cached OHLC data from database
CRITICAL RULES:
- ONLY read from cached_ohlc table
- NEVER generate fake candles
- Return empty list if no data found
- Order by timestamp ASC for chart display
Args:
symbol: Trading pair symbol (e.g., 'BTCUSDT')
interval: Candle interval (e.g., '1h', '4h', '1d')
limit: Maximum number of candles
Returns:
List of dictionaries with REAL OHLC data from database
"""
try:
with self.db.get_session() as session:
# Query for OHLC data
query = session.query(CachedOHLC).filter(
and_(
CachedOHLC.symbol == symbol,
CachedOHLC.interval == interval
)
).order_by(desc(CachedOHLC.timestamp)).limit(limit)
results = query.all()
if not results:
logger.info(f"No cached OHLC data found for {symbol} {interval}")
return []
# Convert to dictionaries - REAL candle data from database
# Reverse order for chronological display
data = []
for row in reversed(results):
data.append({
"timestamp": row.timestamp,
"open": float(row.open),
"high": float(row.high),
"low": float(row.low),
"close": float(row.close),
"volume": float(row.volume),
"provider": row.provider,
"fetched_at": row.fetched_at
})
logger.info(f"Retrieved {len(data)} OHLC candles for {symbol} {interval}")
return data
except Exception as e:
logger.error(f"Database error in get_cached_ohlc: {e}", exc_info=True)
# Return empty list on error - NEVER fake data
return []
def save_market_data(
self,
symbol: str,
price: float,
market_cap: Optional[float] = None,
volume_24h: Optional[float] = None,
change_24h: Optional[float] = None,
high_24h: Optional[float] = None,
low_24h: Optional[float] = None,
provider: str = "unknown"
) -> bool:
"""
Save market data to cache
CRITICAL: Only used by background workers to store REAL API data
Args:
symbol: Crypto symbol
price: Current price (REAL from API)
market_cap: Market cap (REAL from API)
volume_24h: 24h volume (REAL from API)
change_24h: 24h change (REAL from API)
high_24h: 24h high (REAL from API)
low_24h: 24h low (REAL from API)
provider: Data provider name
Returns:
bool: True if saved successfully
"""
try:
with self.db.get_session() as session:
# Create new record with REAL data
record = CachedMarketData(
symbol=symbol,
price=price,
market_cap=market_cap,
volume_24h=volume_24h,
change_24h=change_24h,
high_24h=high_24h,
low_24h=low_24h,
provider=provider,
fetched_at=datetime.utcnow()
)
session.add(record)
session.commit()
logger.info(f"Saved market data for {symbol} from {provider}")
return True
except Exception as e:
logger.error(f"Error saving market data for {symbol}: {e}", exc_info=True)
return False
def save_ohlc_candle(
self,
symbol: str,
interval: str,
timestamp: datetime,
open_price: float,
high: float,
low: float,
close: float,
volume: float,
provider: str = "unknown"
) -> bool:
"""
Save OHLC candle to cache
CRITICAL: Only used by background workers to store REAL candle data
Args:
symbol: Trading pair symbol
interval: Candle interval
timestamp: Candle open time (REAL from API)
open_price: Open price (REAL from API)
high: High price (REAL from API)
low: Low price (REAL from API)
close: Close price (REAL from API)
volume: Volume (REAL from API)
provider: Data provider name
Returns:
bool: True if saved successfully
"""
try:
with self.db.get_session() as session:
# Check if candle already exists
existing = session.query(CachedOHLC).filter(
and_(
CachedOHLC.symbol == symbol,
CachedOHLC.interval == interval,
CachedOHLC.timestamp == timestamp
)
).first()
if existing:
# Update existing candle
existing.open = open_price
existing.high = high
existing.low = low
existing.close = close
existing.volume = volume
existing.provider = provider
existing.fetched_at = datetime.utcnow()
else:
# Create new candle with REAL data
record = CachedOHLC(
symbol=symbol,
interval=interval,
timestamp=timestamp,
open=open_price,
high=high,
low=low,
close=close,
volume=volume,
provider=provider,
fetched_at=datetime.utcnow()
)
session.add(record)
session.commit()
logger.debug(f"Saved OHLC candle for {symbol} {interval} at {timestamp}")
return True
except Exception as e:
logger.error(f"Error saving OHLC candle for {symbol}: {e}", exc_info=True)
return False
def cleanup_old_data(self, days: int = 7) -> Dict[str, int]:
"""
Remove old cached data to manage storage
Args:
days: Remove data older than N days
Returns:
Dictionary with counts of deleted records
"""
try:
with self.db.get_session() as session:
cutoff_time = datetime.utcnow() - timedelta(days=days)
deleted_counts = {}
# Clean old market data
deleted = session.query(CachedMarketData).filter(
CachedMarketData.fetched_at < cutoff_time
).delete()
deleted_counts['market_data'] = deleted
# Clean old OHLC data
deleted = session.query(CachedOHLC).filter(
CachedOHLC.fetched_at < cutoff_time
).delete()
deleted_counts['ohlc'] = deleted
session.commit()
total_deleted = sum(deleted_counts.values())
logger.info(f"Cleaned up {total_deleted} old cache records (older than {days} days)")
return deleted_counts
except Exception as e:
logger.error(f"Error cleaning up old data: {e}", exc_info=True)
return {}
# Global instance
_cache_queries = None
def get_cache_queries(db_manager: Optional[DatabaseManager] = None) -> CacheQueries:
"""
Get global CacheQueries instance
Args:
db_manager: DatabaseManager instance (optional, will use global if not provided)
Returns:
CacheQueries instance
"""
global _cache_queries
if _cache_queries is None:
if db_manager is None:
from database.db_manager import db_manager as global_db
db_manager = global_db
_cache_queries = CacheQueries(db_manager)
return _cache_queries
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