排查加log

config_examples/staticgrid.json

@@ -7,7 +7,7 @@
   "dry_run": false,
   "timeframe": "1h",
   "position_adjustment_enable": true,
-  "process_only_new_candles": false,
+  "process_only_new_candles": true,
   "max_entry_position_adjustment": -1,
   "exchange": {
     "name": "okx",

freqtrade/templates/staticgrid.py

@@ -1,6 +1,9 @@
 # /freqtrade/user_data/strategies/StaticGrid.py
 from freqtrade.strategy import IStrategy
 from pandas import DataFrame
+import logging
+
+logger = logging.getLogger(__name__)
 
 class StaticGrid(IStrategy):
     INTERFACE_VERSION = 3
@@ -28,17 +31,30 @@ class StaticGrid(IStrategy):
         """
         dataframe['enter_long'] = False
         
+        # Debug: Check if we have data
+        if len(dataframe) == 0:
+            logger.warning("[StaticGrid] Empty dataframe!")
+            return dataframe
+        
+        logger.info(f"[StaticGrid] Processing {len(dataframe)} candles. Latest close: {dataframe['close'].iloc[-1]:.2f}")
+        
         # Generate all grid points
         num_grids = int((self.UPPER - self.LOWER) / self.STEP) + 1
+        entry_count = 0
+        
         for i in range(num_grids):
             grid_price = self.LOWER + i * self.STEP
             
             # Buy if low touches this grid point (with 0.1% tolerance)
-            dataframe.loc[
-                (dataframe['low'] <= grid_price * 1.001) & (dataframe['volume'] > 0),
-                'enter_long'
-            ] = True
+            mask = (dataframe['low'] <= grid_price * 1.001) & (dataframe['volume'] > 0)
+            entries = mask.sum()
+            
+            if entries > 0:
+                dataframe.loc[mask, 'enter_long'] = True
+                entry_count += entries
+                logger.debug(f"[StaticGrid] Grid {grid_price:.0f}: {entries} entries")
         
+        logger.info(f"[StaticGrid] Total entries marked: {entry_count}")
         return dataframe
 
     def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -46,6 +62,11 @@ class StaticGrid(IStrategy):
         Exit logic: Sell when price bounces back (any upward movement = profit)
         """
         dataframe['exit_long'] = (dataframe['close'] > dataframe['close'].shift(1)).fillna(False)
+        
+        exit_count = dataframe['exit_long'].sum()
+        if exit_count > 0:
+            logger.debug(f"[StaticGrid] Exit signals: {exit_count}")
+        
         return dataframe
 
     def custom_stake_amount(self, **kwargs) -> float: