Fix concurrent connection usage in multi-timeframe generator

src/data_collector/custom_timeframe_generator.py

@@ -131,7 +131,7 @@ class CustomTimeframeGenerator:
                 return days * 1440
         return 1
 
-    async def aggregate_and_upsert(self, symbol: str, interval: str, bucket_start: datetime) -> None:
+    async def aggregate_and_upsert(self, symbol: str, interval: str, bucket_start: datetime, conn=None) -> None:
         """Aggregate 1m data for a specific bucket and upsert"""
         bucket_end = bucket_start # Initialize
         
@@ -159,7 +159,15 @@ class CustomTimeframeGenerator:
         else:
             bucket_end = bucket_start + timedelta(minutes=1)
 
-        async with self.db.acquire() as conn:
+        # Use provided connection or acquire a new one
+        if conn is None:
+            async with self.db.acquire() as connection:
+                await self._process_aggregation(connection, symbol, interval, source_interval, bucket_start, bucket_end, expected_count)
+        else:
+            await self._process_aggregation(conn, symbol, interval, source_interval, bucket_start, bucket_end, expected_count)
+
+    async def _process_aggregation(self, conn, symbol, interval, source_interval, bucket_start, bucket_end, expected_count):
+        """Internal method to perform aggregation using a specific connection"""
         rows = await conn.fetch(f"""
             SELECT time, open, high, low, close, volume
             FROM candles
@@ -186,12 +194,11 @@ class CustomTimeframeGenerator:
             is_complete=is_complete
         )
         
-            await self._upsert_candle(candle)
+        await self._upsert_candle(candle, conn)
 
-    async def _upsert_candle(self, c: CustomCandle) -> None:
-        """Upsert a single candle"""
-        async with self.db.acquire() as conn:
-            await conn.execute("""
+    async def _upsert_candle(self, c: CustomCandle, conn=None) -> None:
+        """Upsert a single candle using provided connection or acquiring a new one"""
+        query = """
             INSERT INTO candles (time, symbol, interval, open, high, low, close, volume, validated)
             VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9)
             ON CONFLICT (time, symbol, interval) DO UPDATE SET
@@ -202,12 +209,20 @@ class CustomTimeframeGenerator:
                 volume = EXCLUDED.volume,
                 validated = EXCLUDED.validated,
                 created_at = NOW()
-            """, c.time, c.symbol, c.interval, c.open, c.high, c.low, c.close, c.volume, c.is_complete)
+        """
+        values = (c.time, c.symbol, c.interval, c.open, c.high, c.low, c.close, c.volume, c.is_complete)
+        
+        if conn is None:
+            async with self.db.acquire() as connection:
+                await connection.execute(query, *values)
+        else:
+            await conn.execute(query, *values)
 
     async def update_realtime(self, new_1m_candles: List[Candle]) -> None:
         """
         Update ALL timeframes (standard and custom) based on new 1m candles.
         Called after 1m buffer flush.
+        Uses a single connection for all updates sequentially to prevent pool exhaustion.
         """
         if not new_1m_candles:
             return
@@ -215,21 +230,29 @@ class CustomTimeframeGenerator:
         if not self.first_1m_time:
             await self.initialize()
             
+        if not self.first_1m_time:
+            return
+            
         symbol = new_1m_candles[0].symbol
         
-        # 1. Update all intervals except 1m and 148m
+        async with self.db.acquire() as conn:
+            # 1. Update all standard intervals + 37m sequentially
+            # sequential is required because we are sharing the same connection 'conn'
             intervals_to_update = list(self.STANDARD_INTERVALS.keys()) + ['37m']
             
-        tasks = []
             for interval in intervals_to_update:
+                try:
                     bucket_start = self.get_bucket_start(new_1m_candles[-1].time, interval)
-            tasks.append(self.aggregate_and_upsert(symbol, interval, bucket_start))
-            
-        await asyncio.gather(*tasks)
+                    await self.aggregate_and_upsert(symbol, interval, bucket_start, conn=conn)
+                except Exception as e:
+                    logger.error(f"Error updating interval {interval}: {e}")
             
             # 2. Update 148m (it depends on 37m being updated first)
+            try:
                 bucket_148m = self.get_bucket_start(new_1m_candles[-1].time, '148m')
-        await self.aggregate_and_upsert(symbol, '148m', bucket_148m)
+                await self.aggregate_and_upsert(symbol, '148m', bucket_148m, conn=conn)
+            except Exception as e:
+                logger.error(f"Error updating interval 148m: {e}")
 
     async def generate_historical(self, interval: str, batch_size: int = 5000) -> int:
         """