dev progress

lib/pt_strategy/live/live_strategy.py

@@ -12,6 +12,7 @@ from cvttpy_tools.app import App
 from cvttpy_tools.config import Config
 from cvttpy_tools.settings.cvtt_types import IntervalSecT
 from cvttpy_tools.timeutils import SecPerHour
+from cvttpy_tools.logger import Log
 
 # ---
 from cvttpy_trading.trading.instrument import ExchangeInstrument
@@ -117,27 +118,36 @@ class PtLiveStrategy(NamedObject):
         self, hist_aggr: List[MdTradesAggregate]
     ) -> None:
         # Log.info(f"on_mkt_data_hist_snapshot: {aggr}")
-        # await self.pt_mkt_data_.on_mkt_data_hist_snapshot(snapshot=aggr)
-        pass  # URGENT PtiveStrategy.on_mkt_data_hist_snapshot()
+        if not self._is_md_actual(hist_aggr=hist_aggr):
+            return
 
-        # if market_data_df is not None:
-        #     self.trading_pair_.market_data_ = market_data_df
-        #     self.model_data_policy_.advance()
-        #     prediction = self.trading_pair_.run(
-        #         market_data_df, self.model_data_policy_.advance()
-        #     )
-        #     self.predictions_ = pd.concat(
-        #         [self.predictions_, prediction.to_df()], ignore_index=True
-        #     )
+        market_data_df: Optional[pd.DataFrame] = self._create_md_pdf(hist_aggr=hist_aggr)
+        if market_data_df is None:
+            Log.warning(f"{self.fname()} Unable to create market data df")
+            return
 
-        #     trading_instructions: List[TradingInstruction] = (
-        #         self._create_trading_instructions(
-        #             prediction=prediction, last_row=market_data_df.iloc[-1]
-        #         )
-        #     )
-        #     if len(trading_instructions) > 0:
-        #         await self._send_trading_instructions(trading_instructions)
-        #     # trades = self._create_trades(prediction=prediction, last_row=market_data_df.iloc[-1])
+        self.trading_pair_.market_data_ = market_data_df
+        self.model_data_policy_.advance()
+        prediction = self.trading_pair_.run(
+            market_data_df, self.model_data_policy_.advance()
+        )
+        self.predictions_df_ = pd.concat(
+            [self.predictions_df_, prediction.to_df()], ignore_index=True
+        )
+
+        trading_instructions: List[TradingInstruction] = (
+            self._create_trading_instructions(
+                prediction=prediction, last_row=market_data_df.iloc[-1]
+            )
+        )
+        if len(trading_instructions) > 0:
+            await self._send_trading_instructions(trading_instructions)
+
+    def _is_md_actual(self, hist_aggr: List[MdTradesAggregate]) -> bool:
+        return False # URGENT _is_md_actual
+
+    def _create_md_pdf(self, hist_aggr: List[MdTradesAggregate]) -> Optional[pd.DataFrame]:
+        return None # URGENT _create_md_pdf
 
     def interval_sec(self) -> IntervalSecT:
         return self.interval_sec_