pozn do runu, prgbar na queu,report

v2realbot/ENTRY_ClassicSL_v01.py

@@ -157,7 +157,7 @@ def init(state: StrategyState):
 
     today = time_to.date()
     several_days_ago = today - timedelta(days=40)
-    printanyway(f"{today=}",f"{several_days_ago=}")
+    #printanyway(f"{today=}",f"{several_days_ago=}")
     clientTrading = TradingClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=False)
     #get all market days from here to 40days ago
     calendar_request = GetCalendarRequest(start=several_days_ago,end=today)
@@ -174,13 +174,13 @@ def init(state: StrategyState):
             #history_datetime_to = zoneNY.localize(session.close)
             history_datetime_to = session.close
             break
-    printanyway("Previous Market Day Close:", history_datetime_to)
+    #printanyway("Previous Market Day Close:", history_datetime_to)
-    printanyway("Market day 40days ago Open:", history_datetime_from)
+    #printanyway("Market day 40days ago Open:", history_datetime_from)
 
-    printanyway(history_datetime_from, history_datetime_to)
+    #printanyway(history_datetime_from, history_datetime_to)
     #az do predchziho market dne dne
     state.dailyBars = get_historical_bars(state.symbol, history_datetime_from, history_datetime_to, TimeFrame.Day)
-    printanyway("daily bars FILLED", state.dailyBars)
+    #printanyway("daily bars FILLED", state.dailyBars)
     #zatim ukladame do extData - pro instant indicatory a gui
     state.extData["dailyBars"] = state.dailyBars
 

v2realbot/controller/services.py

@@ -476,6 +476,8 @@ def batch_run_manager(id: UUID, runReq: RunRequest, rundays: list[RunDay]):
     note_from_run_request = runReq.note
     first = None
     last = None
+    first_frm = runReq.bt_from.strftime("%d.%m.")
+    last_frm = runReq.bt_to.strftime("%d.%m.")
     for day in rundays:
         cnt += 1
         if cnt == 1:
@@ -486,7 +488,7 @@ def batch_run_manager(id: UUID, runReq: RunRequest, rundays: list[RunDay]):
         print("Datum do", day.end)
         runReq.bt_from = day.start
         runReq.bt_to = day.end
-        runReq.note = f"Batch {batch_id} #{cnt}/{cnt_max} {day.name} N:{day.note} {note_from_run_request}"
+        runReq.note = f"{first_frm}-{last_frm} Batch {batch_id} #{cnt}/{cnt_max} {day.name} N:{day.note} {note_from_run_request}"
 
         #protoze jsme v ridicim vlaknu, poustime za sebou jednotlive stratiny v synchronnim modu
         res, id_val = run_stratin(id=id, runReq=runReq, synchronous=True, inter_batch_params=inter_batch_params)

v2realbot/reporting/metricstoolsimage.py

@@ -16,6 +16,8 @@ from pathlib import Path
 from v2realbot.config import WEB_API_KEY, DATA_DIR, MEDIA_DIRECTORY
 from v2realbot.enums.enums import RecordType, StartBarAlign, Mode, Account, OrderSide
 from io import BytesIO
+from v2realbot.utils.historicals import get_historical_bars
+from alpaca.data.timeframe import TimeFrame, TimeFrameUnit
 # Assuming Trade, TradeStatus, TradeDirection, TradeStoplossType classes are defined elsewhere
 
 def generate_trading_report_image(runner_ids: list = None, batch_id: str = None, stream: bool = False):
@@ -35,7 +37,13 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
             return -1, f"no batch {batch_id} found"
         
     trades = []
+    cnt_max = len(runner_ids) 
+    cnt = 0
+    #zatim zjistujeme start a end z min a max dni - jelikoz muze byt i seznam runner_ids a nejenom batch
+    end_date = None
+    start_date = None
     for id in runner_ids:
+        cnt += 1
         #get runner
         res, sada =cs.get_archived_runner_header_byID(id)
         if res != 0:
@@ -45,8 +53,11 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
         print("archrunner")
         print(sada)
     
+        if cnt == 1:
+            start_date = sada.bt_from if sada.mode in [Mode.BT,Mode.PREP] else sada.started
+        if cnt == cnt_max:
+            end_date = sada.bt_to if sada.mode in [Mode.BT or Mode.PREP] else sada.stopped
         # Parse trades
-        #trades = [Trade(**trade_dict) for trade_dict in set.metrics["prescr_trades"]]
 
         trades_dicts =  sada.metrics["prescr_trades"]
 
@@ -58,6 +69,27 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
 
         print(trades)
 
+    symbol = sada.symbol
+    #hour bars for backtested period
+    print(start_date,end_date)
+    bars= get_historical_bars(symbol, start_date, end_date, TimeFrame.Hour)
+    print("bars for given period",bars)
+    """Bars a dictionary with the following keys:
+        * high: A list of high prices
+        * low: A list of low prices
+        * volume: A list of volumes
+        * close: A list of close prices
+        * hlcc4: A list of HLCC4 indicators
+        * open: A list of open prices
+        * time: A list of times in UTC (ISO 8601 format)
+        * trades: A list of number of trades
+        * resolution: A list of resolutions (all set to 'D')
+        * confirmed: A list of booleans (all set to True)
+        * vwap: A list of VWAP indicator
+        * updated: A list of booleans (all set to True)
+        * index: A list of integers (from 0 to the length of the list of daily bars)
+    """
+
     # Filter to only use trades with status 'CLOSED'
     closed_trades = [trade for trade in trades if trade.status == TradeStatus.CLOSED]
 
@@ -83,7 +115,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
     long_profits = [trade.profit for trade in closed_trades if trade.direction == TradeDirection.LONG and trade.profit is not None]
     short_profits = [trade.profit for trade in closed_trades if trade.direction == TradeDirection.SHORT and trade.profit is not None]
 
-    # # Setting up dark mode for the plots
+    # Setting up dark mode for the plots
     plt.style.use('dark_background')
 
     # Optionally, you can further customize colors, labels, and axes
@@ -104,45 +136,44 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
     }
     plt.rcParams.update(params)
 
-    #NEW LOOK
+
-    # # Set the style to dark mode with custom settings
+    #Custom dark theme similar to the provided image
+    # dark_finance_theme = {
+    #     'background': '#1a1a1a',  # Very dark (almost black) background
+    #     'text': '#eaeaea',       # Light grey text for readability
+    #     'grid': '#333333',       # Dark grey grid lines
+    #     'accent': '#2e91e5',     # Bright blue accent for main elements
+    #     'secondary': '#e15f99',  # Secondary pink/magenta color for highlights
+    #     'highlight': '#fcba03',  # Gold-like color for special highlights
+    # }
+
+    # # Apply the theme settings
     # plt.style.use('dark_background')
+    # plt.rcParams.update({
+    #     'figure.facecolor': dark_finance_theme['background'],
+    #     'axes.facecolor': dark_finance_theme['background'],
+    #     'axes.edgecolor': dark_finance_theme['text'],
+    #     'axes.labelcolor': dark_finance_theme['text'],
+    #     'axes.titlesize': 12,
+    #     'axes.labelsize': 10,
+    #     'xtick.color': dark_finance_theme['text'],
+    #     'xtick.labelsize': 8,
+    #     'ytick.color': dark_finance_theme['text'],
+    #     'ytick.labelsize': 8,
+    #     'grid.color': dark_finance_theme['grid'],
+    #     'grid.linestyle': '-',
+    #     'grid.linewidth': 0.6,
+    #     'legend.facecolor': dark_finance_theme['background'],
+    #     'legend.edgecolor': dark_finance_theme['background'],
+    #     'legend.fontsize': 10,
+    #     'text.color': dark_finance_theme['text'],
+    #     'lines.color': dark_finance_theme['accent'],
+    #     'patch.edgecolor': dark_finance_theme['accent'],
+    # })
 
-    # # Define a custom dark theme color palette
-    # dark_theme_colors = {
-    #     'background': '#1c1c1c',  # Dark gray
-    #     'text': '#d6d6d6',       # Light gray for a subtle contrast
-    #     'grid': '#414141',       # Slightly lighter gray than background for grid
-    #     'highlight': '#3498db',  # Bright blue for highlights (max/min points, etc.)
-    #     'warning': '#e74c3c',    # Red color for warnings or important highlights
-    #     'neutral': '#7f8c8d',    # Neutral color for less important elements
-    # }
 
-    # # Customize the color scheme
+    # Create a combined figure for all plots 11,7 ideal na 3,4
-    # params = {
+    fig, axs = plt.subplots(3, 4, figsize=(12, 7))
-    #     'figure.facecolor': dark_theme_colors['background'],
-    #     'axes.titlesize': 10,
-    #     'axes.labelsize': 9,
-    #     'xtick.labelsize': 9,
-    #     'ytick.labelsize': 9,
-    #     'axes.labelcolor': dark_theme_colors['text'],
-    #     'axes.facecolor': dark_theme_colors['background'],
-    #     'axes.grid': False,  # Control grid visibility
-    #     'axes.edgecolor': dark_theme_colors['text'],
-    #     'xtick.color': dark_theme_colors['text'],
-    #     'ytick.color': dark_theme_colors['text'],
-    #     'text.color': dark_theme_colors['text'],
-    #     'legend.facecolor': dark_theme_colors['background'],
-    #     'legend.edgecolor': dark_theme_colors['text'],
-    #     'legend.fontsize': 8,
-    #     'legend.title_fontsize': 9,
-    # }
-
-    # # Apply the custom color scheme
-    # plt.rcParams.update(params)
-
-    # Create a combined figure for all plots
-    fig, axs = plt.subplots(3, 4, figsize=(11, 7))
 
     #TITLE
     title = ""
@@ -229,43 +260,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
     place_annotation(axs[0, 3], 0, long_count, offset)
     place_annotation(axs[0, 3], 1, short_count, offset)
 
-
+    #PLOT 5 - Heatman (exit time)
-    #Cumulative profit - bud 1 den nebo vice dni
-    if len(runner_ids)== 1:
-        if cumulative_profits.size > 0:
-            # Plot 3: Cumulative Profit Over Time with Max Profit Point
-            max_profit_time = exit_times[np.argmax(cumulative_profits)]
-            max_profit = max(cumulative_profits)
-            min_profit_time = exit_times[np.argmin(cumulative_profits)]
-            min_profit = min(cumulative_profits)
-            sns.lineplot(x=exit_times, y=cumulative_profits, label='Cumulative Profit', ax=axs[1, 3])
-            axs[1, 3].scatter(max_profit_time, max_profit, color='green', label='Max Profit')
-            axs[1, 3].scatter(min_profit_time, min_profit, color='red', label='Min Profit')
-            # Format dates on the x-axis
-            axs[1, 3].xaxis.set_major_formatter(mdates.DateFormatter('%H', tz=zoneNY))
-            axs[1, 3].set_title('Cumulative Profit Over Time')
-            axs[1, 3].legend()
-        else:
-            # Handle the case where cumulative_profits is empty
-            axs[1, 3].text(0.5, 0.5, 'No profit data available', 
-                            horizontalalignment='center', 
-                            verticalalignment='center', 
-                            transform=axs[1, 3].transAxes)
-            axs[1, 3].set_title('Cumulative Profit Over Time')
-    else:
-        # Calculate cumulative profit
-        # Additional Plot: Cumulative Profit Over Time
-        # Sort trades by exit time
-        sorted_trades = sorted([trade for trade in trades if trade.status == TradeStatus.CLOSED], 
-                            key=lambda x: x.exit_time)
-        cumulative_profits_sorted = np.cumsum([trade.profit for trade in sorted_trades])
-        exit_times_sorted = [trade.exit_time for trade in sorted_trades if trade.exit_time is not None]
-        axs[1, 3].plot(exit_times_sorted, cumulative_profits_sorted, color='blue')
-        axs[1, 3].set_title('Cumulative Profit Over Time')
-        axs[1, 3].set_xlabel('Time')
-        axs[1, 3].set_ylabel('Cumulative Profit')
-        axs[1, 3].xaxis.set_major_formatter(mdates.DateFormatter('%d', tz=zoneNY))
-
     # Creating a DataFrame for the heatmap
     heatmap_data_list = []
     for trade in trades:
@@ -281,7 +276,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
         heatmap_data = heatmap_data.groupby(['Day', 'Hour']).sum().reset_index()
         heatmap_pivot = heatmap_data.pivot(index='Day', columns='Hour', values='Profit')
 
-        # Plot 3: Heatmap of Profits
+        # Heatmap of Profits
         sns.heatmap(heatmap_pivot, cmap='viridis', ax=axs[1, 0])
         axs[1, 0].set_title('Heatmap of Profits (based on Exit time)')
         axs[1, 0].set_xlabel('Hour of Day')
@@ -294,15 +289,15 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
                             transform=axs[1, 0].transAxes)
             axs[1, 0].set_title('Heatmap of Profits (based on Exit time)')       
     
-    # Plot 9: Profit/Loss Distribution Histogram
+    # Plot 6: Profit/Loss Distribution Histogram
     sns.histplot(profits, bins=30, ax=axs[1, 1], kde=True, color='skyblue')
     axs[1, 1].set_title('Profit/Loss Distribution')
     axs[1, 1].set_xlabel('Profit/Loss')
     axs[1, 1].set_ylabel('Frequency')
 
-    # Plot 5
+    # Plot 7
-    #    - pro 1 den: Position Size Distribution   
+    #    - for 1 den: Position Size Distribution   
-    #    - pro vice dnu:  Trade Duration vs. Profit/Loss
+    #    - for more days:  Trade Duration vs. Profit/Loss
     if len(runner_ids) == 1:
         
         sizes = [trade.size for trade in closed_trades if trade.size is not None]
@@ -331,7 +326,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
                 ##trade_volumes.append(trade.size)  # or any other measure of trade size
                 trade_types.append('Long' if trade.direction == TradeDirection.LONG else 'Short')
 
-        # Plot 8: Trade Duration vs. Profit/Loss
+        # Trade Duration vs. Profit/Loss
         scatter_data = pd.DataFrame({
             'Duration': trade_durations,
             'Profit': trade_profits,
@@ -345,7 +340,91 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
         axs[1, 2].set_ylabel('Profit/Loss')
 
 
-    # Plot 6: Daily Relative Profit Chart
+    #Plot 8 Cumulative profit - bud 1 den nebo vice dni + pridame pod to vyvoj ceny
+    # Extract the closing prices and times
+    closing_prices = bars['close']
+    #times = bars['time']  # Assuming this is a list of pandas Timestamp objects
+    times = pd.to_datetime(bars['time'])  # Ensure this is a Pandas datetime series
+    # # Plot the closing prices over time
+    # axs[0, 4].plot(times, closing_prices, color='blue')
+    # axs[0, 4].tick_params(axis='x', rotation=45)  # Rotate date labels if necessar
+    # axs[0, 4].xaxis.set_major_formatter(mdates.DateFormatter('%H', tz=zoneNY))
+
+    if len(runner_ids)== 1:
+        if cumulative_profits.size > 0:
+            # Plot 3: Cumulative Profit Over Time with Max Profit Point
+            max_profit_time = exit_times[np.argmax(cumulative_profits)]
+            max_profit = max(cumulative_profits)
+            min_profit_time = exit_times[np.argmin(cumulative_profits)]
+            min_profit = min(cumulative_profits)
+
+            #Plot Cumulative Profit Over Time with Max Profit Point on the primary y-axis
+            # Create a secondary y-axis for the closing prices
+            ax2 = axs[1, 3].twinx()
+            ax2.plot(times, closing_prices, label='Closing Price', color='orange')
+            ax2.set_ylabel('Closing Price', color='orange')
+            ax2.tick_params(axis='y', labelcolor='orange')
+            
+            # Set the limits for the x-axis to cover the full range of 'times'
+            axs[1, 3].set_xlim(times.min(), times.max())
+            sns.lineplot(x=exit_times, y=cumulative_profits, ax=axs[1, 3], color='limegreen')
+            axs[1, 3].scatter(max_profit_time, max_profit, color='green', label='Max Profit')
+            axs[1, 3].scatter(min_profit_time, min_profit, color='red', label='Min Profit')
+            axs[1, 3].set_xlabel('Time')
+            axs[1, 3].set_ylabel('Cumulative Profit', color='limegreen')
+            axs[1, 3].tick_params(axis='y', labelcolor='limegreen')
+            axs[1, 3].xaxis.set_major_formatter(mdates.DateFormatter('%H', tz=zoneNY))
+            # Add legends to the plot
+            # lines, labels = axs[1, 3].get_legend_handles_labels()
+            # lines2, labels2 = ax2.get_legend_handles_labels()
+            # axs[1, 3].legend(lines + lines2, labels + labels2, loc='upper left')
+        else:
+            # Handle the case where cumulative_profits is empty
+            axs[1, 3].text(0.5, 0.5, 'No profit data available', 
+                            horizontalalignment='center', 
+                            verticalalignment='center', 
+                            transform=axs[1, 3].transAxes)
+            axs[1, 3].set_title('Cumulative Profit Over Time')
+    else:
+        # Calculate cumulative profit
+        # Additional Plot: Cumulative Profit Over Time
+        # Sort trades by exit time
+
+        # # Set the limits for the x-axis to cover the full range of 'times'
+        # axs[1, 3].set_xlim(times.min(), times.max())
+
+        sorted_trades = sorted([trade for trade in trades if trade.status == TradeStatus.CLOSED], 
+                            key=lambda x: x.exit_time)
+        cumulative_profits_sorted = np.cumsum([trade.profit for trade in sorted_trades])
+        exit_times_sorted = [trade.exit_time for trade in sorted_trades if trade.exit_time is not None]
+
+        # Create a secondary y-axis for the closing prices
+        ax2 = axs[1, 3].twinx()
+        ax2.plot(times, closing_prices, label='Closing Price', color='orange')
+        ax2.set_ylabel('Closing Price', color='orange')
+        ax2.tick_params(axis='y', labelcolor='orange')
+
+        axs[1, 3].set_xlim(times.min(), times.max())
+        # Plot Cumulative Profit Over Time on the primary y-axis
+        axs[1, 3].plot(exit_times_sorted, cumulative_profits_sorted, label='Cumulative Profit', color='blue')
+        axs[1, 3].set_xlabel('Time')
+        axs[1, 3].set_ylabel('Cumulative Profit', color='blue')
+        axs[1, 3].tick_params(axis='y', labelcolor='blue')
+
+        # Format dates on the x-axis
+        axs[1, 3].xaxis.set_major_formatter(mdates.DateFormatter('%d.%m.', tz=zoneNY))
+        axs[1, 3].tick_params(axis='x', rotation=45)  # Rotate date labels if necessary
+
+        # Set the title
+        axs[1, 3].set_title('Cumulative Profit and Closing Price Over Time')
+
+        # Add legends to the plot
+        # axs[1, 3].legend(loc='upper left')
+        # ax2.legend(loc='upper right')
+
+    # Plot 9
+    # - for 1 day: Daily Relative Profit Chart
+    # - for more days: Heatmap of Profits (based on Entry time)
     if len(runner_ids) == 1:
         daily_rel_profits = [trade.rel_profit for trade in closed_trades if trade.rel_profit is not None]
         sns.lineplot(x=range(len(daily_rel_profits)), y=daily_rel_profits, ax=axs[2, 0])
@@ -365,13 +444,13 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
         heatmap_data = heatmap_data.groupby(['Day', 'Hour']).sum().reset_index()
         heatmap_pivot = heatmap_data.pivot(index='Day', columns='Hour', values='Profit')
 
-        # Plot 3: Heatmap of Profits
+        # Heatmap of Profits
         sns.heatmap(heatmap_pivot, cmap='viridis', ax=axs[2, 0])
         axs[2, 0].set_title('Heatmap of Profits (based on Entry time)')
         axs[2, 0].set_xlabel('Hour of Day')
         axs[2, 0].set_ylabel('Day')
 
-    # Plot 8: Profits Based on Hour of the Day (Entry)
+    # Plot 10: Profits Based on Hour of the Day (Entry)
     entry_hours = [trade.entry_time.hour for trade in closed_trades if trade.entry_time is not None]
     profits_by_hour = {}
     for hour, trade in zip(entry_hours, closed_trades):
@@ -396,7 +475,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
                         transform=axs[2, 1].transAxes)
         axs[2, 1].set_title('Profits by Hour of Day (Entry)')
 
-    # Plot 9: Profits Based on Hour of the Day - based on Exit
+    # Plot 11: Profits Based on Hour of the Day - based on Exit
     exit_hours = [trade.exit_time.hour for trade in closed_trades if trade.exit_time is not None]
     profits_by_hour = {}
     for hour, trade in zip(exit_hours, closed_trades):
@@ -421,7 +500,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
                         transform=axs[2, 2].transAxes)
         axs[2, 2].set_title('Profits by Hour of Day (Exit)')
 
-    # Calculate profits by day of the week
+    # Plot 12: Calculate profits by day of the week
     day_of_week_profits = {i: 0 for i in range(7)}  # Dictionary to store profits for each day of the week
 
     for trade in trades:
@@ -459,7 +538,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
 # Example usage
 # trades = [list of Trade objects]
 if __name__ == '__main__':
-    id_list = ["c3e31cb5-ddf9-467e-a932-2118f6844355"]
+    # id_list = ["e8938b2e-8462-441a-8a82-d823c6a025cb"]
-    generate_trading_report_image(runner_ids=id_list)
+    # generate_trading_report_image(runner_ids=id_list)
-    # batch_id = "90973e57"
+    batch_id = "90973e57"
-    # generate_trading_report_image(batch_id=batch_id)
+    generate_trading_report_image(batch_id=batch_id)

v2realbot/strategy/base.py

@@ -28,6 +28,7 @@ from uuid import UUID
 from rich import print as printnow
 from collections import defaultdict
 import v2realbot.strategyblocks.activetrade.sl.optimsl as optimsl
+from tqdm import tqdm
 
 if PROFILING_NEXT_ENABLED:
     from pyinstrument import Profiler
@@ -418,40 +419,42 @@ class Strategy:
         
         #main strat loop
         print(self.name, "Waiting for DATA")
-        while True:
+        with tqdm(total=self.q1.qsize()) as pbar:
-            try:
+            while True:
-                #block 5s, after that check signals
+                try:
-                item = self.q1.get(timeout=HEARTBEAT_TIMEOUT)
+                    #block 5s, after that check signals
-                #printnow(current_thread().name, "Items waiting in queue:", self.q1.qsize())
+                    item = self.q1.get(timeout=HEARTBEAT_TIMEOUT)
-            except queue.Empty:
+                    #printnow(current_thread().name, "Items waiting in queue:", self.q1.qsize())
-                #check signals
+                except queue.Empty:
-                if self.se.is_set():
+                    #check signals
-                    print(current_thread().name, "Stopping signal")
+                    if self.se.is_set():
+                        print(current_thread().name, "Stopping signal")
+                        break
+                    if self.pe.is_set():
+                        print(current_thread().name, "Paused.")
+                        continue
+                    else:
+                        print(current_thread().name, "HEARTBEAT - no trades or signals")
+                        continue
+                #prijde posledni zaznam nebo stop event signal 
+                if item == "last" or self.se.is_set():
+                    print(current_thread().name, "stopping")
                     break
-                if self.pe.is_set():
+                elif self.pe.is_set():
                     print(current_thread().name, "Paused.")
                     continue
-                else:
+                #self.state.iter_log(event="INGEST",msg="New data ingested", item=item)
-                    print(current_thread().name, "HEARTBEAT - no trades or signals")
+                print("New data ingested", item)
-                    continue
+                print("bars list - previous", self.state.bars)
-            #prijde posledni zaznam nebo stop event signal 
+                #TODO sem pridat ochranu kulometu 
-            if item == "last" or self.se.is_set():
+                #pokud je updatetime aktualniho baru mensi nez LIMIT a nejde o potvrzovaci bar
-                print(current_thread().name, "stopping")
+                #tak jej vyhodit
-                break
+                #zabraní se tím akcím na než bych stejně nešlo reagovat
-            elif self.pe.is_set():
+                #TODO jeste promyslet
-                print(current_thread().name, "Paused.")
+                
-                continue
+                #calling main loop
-            #self.state.iter_log(event="INGEST",msg="New data ingested", item=item)
+                self.strat_loop(item=item)
-            print("New data ingested", item)
+                pbar.update(1)
-            print("bars list - previous", self.state.bars)
-            #TODO sem pridat ochranu kulometu 
-            #pokud je updatetime aktualniho baru mensi nez LIMIT a nejde o potvrzovaci bar
-            #tak jej vyhodit
-            #zabraní se tím akcím na než bych stejně nešlo reagovat
-            #TODO jeste promyslet
-            
-            #calling main loop
-            self.strat_loop(item=item)
 
         tlog(f"FINISHED")
         print(40*"*",self.mode, "STRATEGY ", self.name,"STOPPING",40*"*")