(feat) add position executor data

pages/strategy_performance/app.py

@@ -152,7 +152,7 @@ st.plotly_chart(time_filtered_performance_charts.pnl_over_time(), use_container_
 # Market activity section
 st.subheader("💱 Market activity")
 if "Error" in selected_db.status["market_data"] or time_filtered_strategy_data.market_data.empty:
-    st.warning("Market data is not available so the candles graph is not going to be rendered. "
+    st.warning("Market data is not available so the candles graph is not going to be rendered."
                "Make sure that you are using the latest version of Hummingbot and market data recorder activated.")
 else:
     col1, col2, col3, col4 = st.columns(4)
@@ -200,9 +200,18 @@ else:
     else:
         st.plotly_chart(candles_graph(candles_df, page_filtered_strategy_data), use_container_width=True)
 
+# Position executor section
+st.divider()
+st.subheader("🤖 Position executor")
+if "Error" in selected_db.status["position_executor"] or strategy_data.position_executor.empty:
+    st.warning("Position executor data is not available so position executor graphs are not going to be rendered."
+               "Make sure that you are using the latest version of Hummingbot.")
+else:
+    st.dataframe(strategy_data.position_executor, use_container_width=True)
+
 # Community metrics section
 st.divider()
-st.subheader("📈 Metrics")
+st.subheader("👥 Community Metrics")
 with st.container():
     col1, col2, col3, col4, col5 = st.columns(5)
     with col1:

utils/database_manager.py

@@ -13,7 +13,6 @@ class DatabaseManager:
         self.db_name = db_name
         # TODO: Create db path for all types of db
         self.db_path = f'sqlite:///{os.path.join(db_name)}'
-        self.executors_path = executors_path
         self.engine = create_engine(self.db_path, connect_args={'check_same_thread': False})
         self.session_maker = sessionmaker(bind=self.engine)
 
@@ -131,6 +130,18 @@ class DatabaseManager:
             query += f" WHERE {' AND '.join(conditions)}"
         return query
 
+    @staticmethod
+    def _get_position_executor_query(start_date=None, end_date=None):
+        query = "SELECT * FROM PositionExecutors"
+        conditions = []
+        if start_date:
+            conditions.append(f"timestamp >= '{start_date}'")
+        if end_date:
+            conditions.append(f"timestamp <= '{end_date}'")
+        if conditions:
+            query += f" WHERE {' AND '.join(conditions)}"
+        return query
+
     def get_orders(self, config_file_path=None, start_date=None, end_date=None):
         with self.session_maker() as session:
             query = self._get_orders_query(config_file_path, start_date, end_date)
@@ -183,16 +194,9 @@ class DatabaseManager:
         return market_data
 
     def get_position_executor_data(self, start_date=None, end_date=None) -> pd.DataFrame:
-        df = pd.DataFrame()
-        files = [file for file in os.listdir(self.executors_path) if ".csv" in file and file != "trades_market_making_.csv"]
-        for file in files:
-            df0 = pd.read_csv(f"{self.executors_path}/{file}")
-            df = pd.concat([df, df0])
-        df["datetime"] = pd.to_datetime(df["timestamp"], unit="s")
-        if start_date:
-            df = df[df["datetime"] >= start_date]
-        if end_date:
-            df = df[df["datetime"] <= end_date]
-        return df
-
-
+        with self.session_maker() as session:
+            query = self._get_position_executor_query(start_date, end_date)
+            position_executor = pd.read_sql_query(text(query), session.connection())
+            position_executor.set_index("timestamp", inplace=True)
+            position_executor["datetime"] = pd.to_datetime(position_executor.index, unit="ms")
+        return position_executor