testdata

src/aiomql/core/backtester/test_data.py

@@ -4,7 +4,8 @@ import pytz
 import numpy as np
 import pandas as pd
 from pandas import DataFrame
-from MetaTrader5 import Tick, SymbolInfo, AccountInfo
+from MetaTrader5 import Tick, SymbolInfo, AccountInfo, TradeOrder, TradePosition, TradeDeal
+import MetaTrader5
 
 from ..constants import TimeFrame, CopyTicks
 from .get_data import Data, GetData
@@ -14,6 +15,9 @@ tz = pytz.timezone('Etc/UTC')
 
 
 class TestData:
+    history_orders: DataFrame
+    history_deals: DataFrame
+    
     def __init__(self, data: Data):
         self._data = data
         self.account = data['account']
@@ -24,7 +28,12 @@ class TestData:
         self.interval = data['interval']
         self.cursor = 0
         self.iter = iter(self.interval)
-    
+        self.orders: dict[str, dict[int, TradeOrder]] = {}
+        self.open_orders: dict[int, TradeOrder] = {}
+        self.positions: dict[str, dict[int, TradePosition]] = {}
+        self.open_positions = dict[int, TradePosition] = {}
+        self.history_deals = dict[str, dict[int, TradeDeal]] = {}
+
     def __next__(self):
         self.cursor = next(self.iter)
         return self.cursor
@@ -58,7 +67,7 @@ class TestData:
         rates = self.rates[symbol][timeframe.name]
         start = int(datetime.timestamp(date_from)) if isinstance(date_from, datetime) else int(date_from)
         start = round_down(start, timeframe.time)
-        start = rates[rates.index <= start].index
+        start = rates[rates.index <= start].iloc[-1].name
         start = rates.index.get_loc(start)
         end = start + count
         return rates.iloc[start:end].to_numpy()
@@ -69,17 +78,51 @@ class TestData:
         end = end or None
         return rates.iloc[-start_pos:end].to_numpy()
 
-    def get_rates_range(self, symbol: str, timeframe: TimeFrame, date_from: datetime, date_to: datetime) -> np.ndarray:
+    def get_rates_range(self, symbol: str, timeframe: TimeFrame, date_from: datetime | float, date_to: datetime | float) -> np.ndarray:
         rates = self.rates[symbol][timeframe.name]
-        start = round_down(int(datetime.timestamp(date_from)), timeframe.time)
-        start = rates[rates.index <= start].iloc[-1].index
-        end = round_up(int(datetime.timestamp(date_to)), timeframe.time)
-        end = rates[rates.index >= end].index
+        start = int(datetime.timestamp(date_from)) if isinstance(date_from, datetime) else int(date_from)
+        start = round_down(start, timeframe.time)
+        start = rates[rates.index <= start].iloc[-1].name
+        end = int(datetime.timestamp(date_to)) if isinstance(date_to, datetime) else int(date_to)
+        end = round_up(end, timeframe.time)
+        end = rates[rates.index >= end].iloc[-1].name
         return rates.loc[start:end].to_numpy()
 
-    def get_ticks_from(self, symbol: str, date_from: datetime | float, count: int, flags: CopyTicks) -> DataFrame:
+    def get_ticks_from(self, symbol: str, date_from: datetime | float, count: int, flags: CopyTicks) -> np.ndarray:
         ticks = self.ticks[symbol]
         start = int(datetime.timestamp(date_from)) if isinstance(date_from, datetime) else int(date_from)
-        start = round_down(start, 1)
+        start = ticks[ticks.index <= start].iloc[-1].name
+        start = ticks.index.get_loc(start)
         end = start + count
-        return ticks.loc[start:end]
+        return ticks.iloc[start:end]
+    
+    def get_ticks_range(self, symbol: str, date_from: datetime | float, date_to: datetime | float, flags) -> np.ndarray:
+        ticks = self.ticks[symbol]
+        start = int(datetime.timestamp(date_from)) if isinstance(date_from, datetime) else int(date_from)
+        start = ticks[ticks.index <= start].iloc[-1].index
+        end = int(datetime.timestamp(date_to)) if isinstance(date_to, datetime) else int(date_to)
+        end = ticks[ticks.index >= end].iloc[-1].index
+        return ticks.loc[start:end].to_numpy()
+    
+    def get_orders_total(self) -> int:
+        return len(self.live_orders)
+    
+    def get_orders(self, symbol: str = '', group: str = '', ticket: int = None) -> tuple[TradeOrder, ...]:
+        if ticket:
+            return self.live_orders.get(ticket, ())
+        
+        elif symbol:
+            return tuple(order for order in self.orders.get(symbol, ()) if order.ticket in self.live_orders)
+        
+        elif group:
+            return tuple(self.live_orders.values())
+    
+        else:
+            return tuple(self.live_orders.values())
+    
+    def history_orders_total(self, date_from: datetime | float, date_to: datetime | float):
+        start =  
+
+
+
+