pozn do runu, prgbar na queu,report
This commit is contained in:
David Brazda
@@ -157,7 +157,7 @@ def init(state: StrategyState):
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today = time_to.date()
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several_days_ago = today - timedelta(days=40)
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printanyway(f"{today=}",f"{several_days_ago=}")
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#printanyway(f"{today=}",f"{several_days_ago=}")
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clientTrading = TradingClient(ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, raw_data=False)
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#get all market days from here to 40days ago
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calendar_request = GetCalendarRequest(start=several_days_ago,end=today)
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@@ -174,13 +174,13 @@ def init(state: StrategyState):
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#history_datetime_to = zoneNY.localize(session.close)
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history_datetime_to = session.close
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break
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printanyway("Previous Market Day Close:", history_datetime_to)
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printanyway("Market day 40days ago Open:", history_datetime_from)
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#printanyway("Previous Market Day Close:", history_datetime_to)
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#printanyway("Market day 40days ago Open:", history_datetime_from)
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printanyway(history_datetime_from, history_datetime_to)
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#printanyway(history_datetime_from, history_datetime_to)
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#az do predchziho market dne dne
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state.dailyBars = get_historical_bars(state.symbol, history_datetime_from, history_datetime_to, TimeFrame.Day)
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printanyway("daily bars FILLED", state.dailyBars)
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#printanyway("daily bars FILLED", state.dailyBars)
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#zatim ukladame do extData - pro instant indicatory a gui
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state.extData["dailyBars"] = state.dailyBars
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@@ -476,6 +476,8 @@ def batch_run_manager(id: UUID, runReq: RunRequest, rundays: list[RunDay]):
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note_from_run_request = runReq.note
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first = None
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last = None
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first_frm = runReq.bt_from.strftime("%d.%m.")
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last_frm = runReq.bt_to.strftime("%d.%m.")
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for day in rundays:
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cnt += 1
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if cnt == 1:
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@@ -486,7 +488,7 @@ def batch_run_manager(id: UUID, runReq: RunRequest, rundays: list[RunDay]):
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print("Datum do", day.end)
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runReq.bt_from = day.start
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runReq.bt_to = day.end
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runReq.note = f"Batch {batch_id} #{cnt}/{cnt_max} {day.name} N:{day.note} {note_from_run_request}"
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runReq.note = f"{first_frm}-{last_frm} Batch {batch_id} #{cnt}/{cnt_max} {day.name} N:{day.note} {note_from_run_request}"
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#protoze jsme v ridicim vlaknu, poustime za sebou jednotlive stratiny v synchronnim modu
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res, id_val = run_stratin(id=id, runReq=runReq, synchronous=True, inter_batch_params=inter_batch_params)
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@@ -16,6 +16,8 @@ from pathlib import Path
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from v2realbot.config import WEB_API_KEY, DATA_DIR, MEDIA_DIRECTORY
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from v2realbot.enums.enums import RecordType, StartBarAlign, Mode, Account, OrderSide
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from io import BytesIO
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from v2realbot.utils.historicals import get_historical_bars
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from alpaca.data.timeframe import TimeFrame, TimeFrameUnit
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# Assuming Trade, TradeStatus, TradeDirection, TradeStoplossType classes are defined elsewhere
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def generate_trading_report_image(runner_ids: list = None, batch_id: str = None, stream: bool = False):
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@@ -35,7 +37,13 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
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return -1, f"no batch {batch_id} found"
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trades = []
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cnt_max = len(runner_ids)
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cnt = 0
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#zatim zjistujeme start a end z min a max dni - jelikoz muze byt i seznam runner_ids a nejenom batch
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end_date = None
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start_date = None
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for id in runner_ids:
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cnt += 1
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#get runner
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res, sada =cs.get_archived_runner_header_byID(id)
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if res != 0:
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@@ -45,8 +53,11 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
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print("archrunner")
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print(sada)
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if cnt == 1:
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start_date = sada.bt_from if sada.mode in [Mode.BT,Mode.PREP] else sada.started
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if cnt == cnt_max:
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end_date = sada.bt_to if sada.mode in [Mode.BT or Mode.PREP] else sada.stopped
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# Parse trades
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#trades = [Trade(**trade_dict) for trade_dict in set.metrics["prescr_trades"]]
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trades_dicts = sada.metrics["prescr_trades"]
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@@ -58,6 +69,27 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
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print(trades)
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symbol = sada.symbol
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#hour bars for backtested period
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print(start_date,end_date)
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bars= get_historical_bars(symbol, start_date, end_date, TimeFrame.Hour)
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print("bars for given period",bars)
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"""Bars a dictionary with the following keys:
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* high: A list of high prices
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* low: A list of low prices
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* volume: A list of volumes
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* close: A list of close prices
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* hlcc4: A list of HLCC4 indicators
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* open: A list of open prices
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* time: A list of times in UTC (ISO 8601 format)
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* trades: A list of number of trades
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* resolution: A list of resolutions (all set to 'D')
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* confirmed: A list of booleans (all set to True)
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* vwap: A list of VWAP indicator
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* updated: A list of booleans (all set to True)
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* index: A list of integers (from 0 to the length of the list of daily bars)
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"""
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# Filter to only use trades with status 'CLOSED'
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closed_trades = [trade for trade in trades if trade.status == TradeStatus.CLOSED]
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@@ -83,7 +115,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
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long_profits = [trade.profit for trade in closed_trades if trade.direction == TradeDirection.LONG and trade.profit is not None]
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short_profits = [trade.profit for trade in closed_trades if trade.direction == TradeDirection.SHORT and trade.profit is not None]
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# # Setting up dark mode for the plots
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# Setting up dark mode for the plots
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plt.style.use('dark_background')
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# Optionally, you can further customize colors, labels, and axes
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@@ -104,45 +136,44 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
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}
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plt.rcParams.update(params)
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#NEW LOOK
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# # Set the style to dark mode with custom settings
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#Custom dark theme similar to the provided image
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# dark_finance_theme = {
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# 'background': '#1a1a1a', # Very dark (almost black) background
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# 'text': '#eaeaea', # Light grey text for readability
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# 'grid': '#333333', # Dark grey grid lines
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# 'accent': '#2e91e5', # Bright blue accent for main elements
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# 'secondary': '#e15f99', # Secondary pink/magenta color for highlights
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# 'highlight': '#fcba03', # Gold-like color for special highlights
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# }
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# # Apply the theme settings
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# plt.style.use('dark_background')
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# plt.rcParams.update({
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# 'figure.facecolor': dark_finance_theme['background'],
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# 'axes.facecolor': dark_finance_theme['background'],
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# 'axes.edgecolor': dark_finance_theme['text'],
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# 'axes.labelcolor': dark_finance_theme['text'],
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# 'axes.titlesize': 12,
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# 'axes.labelsize': 10,
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# 'xtick.color': dark_finance_theme['text'],
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# 'xtick.labelsize': 8,
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# 'ytick.color': dark_finance_theme['text'],
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# 'ytick.labelsize': 8,
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# 'grid.color': dark_finance_theme['grid'],
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# 'grid.linestyle': '-',
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# 'grid.linewidth': 0.6,
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# 'legend.facecolor': dark_finance_theme['background'],
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# 'legend.edgecolor': dark_finance_theme['background'],
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# 'legend.fontsize': 10,
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# 'text.color': dark_finance_theme['text'],
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# 'lines.color': dark_finance_theme['accent'],
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# 'patch.edgecolor': dark_finance_theme['accent'],
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# })
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# # Define a custom dark theme color palette
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# dark_theme_colors = {
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# 'background': '#1c1c1c', # Dark gray
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# 'text': '#d6d6d6', # Light gray for a subtle contrast
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# 'grid': '#414141', # Slightly lighter gray than background for grid
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# 'highlight': '#3498db', # Bright blue for highlights (max/min points, etc.)
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# 'warning': '#e74c3c', # Red color for warnings or important highlights
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# 'neutral': '#7f8c8d', # Neutral color for less important elements
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# }
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# # Customize the color scheme
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# params = {
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# 'figure.facecolor': dark_theme_colors['background'],
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# 'axes.titlesize': 10,
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# 'axes.labelsize': 9,
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# 'xtick.labelsize': 9,
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# 'ytick.labelsize': 9,
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# 'axes.labelcolor': dark_theme_colors['text'],
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# 'axes.facecolor': dark_theme_colors['background'],
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# 'axes.grid': False, # Control grid visibility
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# 'axes.edgecolor': dark_theme_colors['text'],
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# 'xtick.color': dark_theme_colors['text'],
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# 'ytick.color': dark_theme_colors['text'],
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# 'text.color': dark_theme_colors['text'],
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# 'legend.facecolor': dark_theme_colors['background'],
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# 'legend.edgecolor': dark_theme_colors['text'],
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# 'legend.fontsize': 8,
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# 'legend.title_fontsize': 9,
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# }
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# # Apply the custom color scheme
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# plt.rcParams.update(params)
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# Create a combined figure for all plots
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fig, axs = plt.subplots(3, 4, figsize=(11, 7))
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# Create a combined figure for all plots 11,7 ideal na 3,4
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fig, axs = plt.subplots(3, 4, figsize=(12, 7))
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#TITLE
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title = ""
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@@ -229,43 +260,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
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place_annotation(axs[0, 3], 0, long_count, offset)
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place_annotation(axs[0, 3], 1, short_count, offset)
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#Cumulative profit - bud 1 den nebo vice dni
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if len(runner_ids)== 1:
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if cumulative_profits.size > 0:
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# Plot 3: Cumulative Profit Over Time with Max Profit Point
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max_profit_time = exit_times[np.argmax(cumulative_profits)]
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max_profit = max(cumulative_profits)
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min_profit_time = exit_times[np.argmin(cumulative_profits)]
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min_profit = min(cumulative_profits)
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sns.lineplot(x=exit_times, y=cumulative_profits, label='Cumulative Profit', ax=axs[1, 3])
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axs[1, 3].scatter(max_profit_time, max_profit, color='green', label='Max Profit')
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axs[1, 3].scatter(min_profit_time, min_profit, color='red', label='Min Profit')
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# Format dates on the x-axis
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axs[1, 3].xaxis.set_major_formatter(mdates.DateFormatter('%H', tz=zoneNY))
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axs[1, 3].set_title('Cumulative Profit Over Time')
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axs[1, 3].legend()
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else:
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# Handle the case where cumulative_profits is empty
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axs[1, 3].text(0.5, 0.5, 'No profit data available',
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horizontalalignment='center',
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verticalalignment='center',
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transform=axs[1, 3].transAxes)
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axs[1, 3].set_title('Cumulative Profit Over Time')
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else:
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# Calculate cumulative profit
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# Additional Plot: Cumulative Profit Over Time
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# Sort trades by exit time
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sorted_trades = sorted([trade for trade in trades if trade.status == TradeStatus.CLOSED],
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key=lambda x: x.exit_time)
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cumulative_profits_sorted = np.cumsum([trade.profit for trade in sorted_trades])
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exit_times_sorted = [trade.exit_time for trade in sorted_trades if trade.exit_time is not None]
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axs[1, 3].plot(exit_times_sorted, cumulative_profits_sorted, color='blue')
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axs[1, 3].set_title('Cumulative Profit Over Time')
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axs[1, 3].set_xlabel('Time')
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axs[1, 3].set_ylabel('Cumulative Profit')
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axs[1, 3].xaxis.set_major_formatter(mdates.DateFormatter('%d', tz=zoneNY))
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#PLOT 5 - Heatman (exit time)
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# Creating a DataFrame for the heatmap
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heatmap_data_list = []
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for trade in trades:
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@@ -281,7 +276,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
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heatmap_data = heatmap_data.groupby(['Day', 'Hour']).sum().reset_index()
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heatmap_pivot = heatmap_data.pivot(index='Day', columns='Hour', values='Profit')
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# Plot 3: Heatmap of Profits
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# Heatmap of Profits
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sns.heatmap(heatmap_pivot, cmap='viridis', ax=axs[1, 0])
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axs[1, 0].set_title('Heatmap of Profits (based on Exit time)')
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axs[1, 0].set_xlabel('Hour of Day')
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@@ -294,15 +289,15 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
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transform=axs[1, 0].transAxes)
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axs[1, 0].set_title('Heatmap of Profits (based on Exit time)')
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# Plot 9: Profit/Loss Distribution Histogram
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# Plot 6: Profit/Loss Distribution Histogram
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sns.histplot(profits, bins=30, ax=axs[1, 1], kde=True, color='skyblue')
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axs[1, 1].set_title('Profit/Loss Distribution')
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axs[1, 1].set_xlabel('Profit/Loss')
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axs[1, 1].set_ylabel('Frequency')
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# Plot 5
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# - pro 1 den: Position Size Distribution
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# - pro vice dnu: Trade Duration vs. Profit/Loss
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# Plot 7
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# - for 1 den: Position Size Distribution
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# - for more days: Trade Duration vs. Profit/Loss
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if len(runner_ids) == 1:
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sizes = [trade.size for trade in closed_trades if trade.size is not None]
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@@ -331,7 +326,7 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
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##trade_volumes.append(trade.size) # or any other measure of trade size
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trade_types.append('Long' if trade.direction == TradeDirection.LONG else 'Short')
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# Plot 8: Trade Duration vs. Profit/Loss
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# Trade Duration vs. Profit/Loss
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scatter_data = pd.DataFrame({
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'Duration': trade_durations,
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'Profit': trade_profits,
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@@ -345,7 +340,91 @@ def generate_trading_report_image(runner_ids: list = None, batch_id: str = None,
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axs[1, 2].set_ylabel('Profit/Loss')
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# Plot 6: Daily Relative Profit Chart
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#Plot 8 Cumulative profit - bud 1 den nebo vice dni + pridame pod to vyvoj ceny
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# Extract the closing prices and times
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closing_prices = bars['close']
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#times = bars['time'] # Assuming this is a list of pandas Timestamp objects
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times = pd.to_datetime(bars['time']) # Ensure this is a Pandas datetime series
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# # Plot the closing prices over time
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# axs[0, 4].plot(times, closing_prices, color='blue')
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# axs[0, 4].tick_params(axis='x', rotation=45) # Rotate date labels if necessar
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# axs[0, 4].xaxis.set_major_formatter(mdates.DateFormatter('%H', tz=zoneNY))
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if len(runner_ids)== 1:
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if cumulative_profits.size > 0:
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# Plot 3: Cumulative Profit Over Time with Max Profit Point
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max_profit_time = exit_times[np.argmax(cumulative_profits)]
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max_profit = max(cumulative_profits)
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min_profit_time = exit_times[np.argmin(cumulative_profits)]
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min_profit = min(cumulative_profits)
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#Plot Cumulative Profit Over Time with Max Profit Point on the primary y-axis
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# Create a secondary y-axis for the closing prices
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ax2 = axs[1, 3].twinx()
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ax2.plot(times, closing_prices, label='Closing Price', color='orange')
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ax2.set_ylabel('Closing Price', color='orange')
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ax2.tick_params(axis='y', labelcolor='orange')
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# Set the limits for the x-axis to cover the full range of 'times'
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axs[1, 3].set_xlim(times.min(), times.max())
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sns.lineplot(x=exit_times, y=cumulative_profits, ax=axs[1, 3], color='limegreen')
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axs[1, 3].scatter(max_profit_time, max_profit, color='green', label='Max Profit')
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axs[1, 3].scatter(min_profit_time, min_profit, color='red', label='Min Profit')
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axs[1, 3].set_xlabel('Time')
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axs[1, 3].set_ylabel('Cumulative Profit', color='limegreen')
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axs[1, 3].tick_params(axis='y', labelcolor='limegreen')
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axs[1, 3].xaxis.set_major_formatter(mdates.DateFormatter('%H', tz=zoneNY))
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# Add legends to the plot
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# lines, labels = axs[1, 3].get_legend_handles_labels()
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# lines2, labels2 = ax2.get_legend_handles_labels()
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# axs[1, 3].legend(lines + lines2, labels + labels2, loc='upper left')
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else:
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# Handle the case where cumulative_profits is empty
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axs[1, 3].text(0.5, 0.5, 'No profit data available',
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horizontalalignment='center',
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verticalalignment='center',
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transform=axs[1, 3].transAxes)
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axs[1, 3].set_title('Cumulative Profit Over Time')
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else:
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# Calculate cumulative profit
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# Additional Plot: Cumulative Profit Over Time
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# Sort trades by exit time
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# # Set the limits for the x-axis to cover the full range of 'times'
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# axs[1, 3].set_xlim(times.min(), times.max())
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sorted_trades = sorted([trade for trade in trades if trade.status == TradeStatus.CLOSED],
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key=lambda x: x.exit_time)
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cumulative_profits_sorted = np.cumsum([trade.profit for trade in sorted_trades])
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exit_times_sorted = [trade.exit_time for trade in sorted_trades if trade.exit_time is not None]
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# Create a secondary y-axis for the closing prices
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ax2 = axs[1, 3].twinx()
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ax2.plot(times, closing_prices, label='Closing Price', color='orange')
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ax2.set_ylabel('Closing Price', color='orange')
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ax2.tick_params(axis='y', labelcolor='orange')
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axs[1, 3].set_xlim(times.min(), times.max())
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# Plot Cumulative Profit Over Time on the primary y-axis
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axs[1, 3].plot(exit_times_sorted, cumulative_profits_sorted, label='Cumulative Profit', color='blue')
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axs[1, 3].set_xlabel('Time')
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axs[1, 3].set_ylabel('Cumulative Profit', color='blue')
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axs[1, 3].tick_params(axis='y', labelcolor='blue')
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# Format dates on the x-axis
|
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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"]
|
||||
generate_trading_report_image(runner_ids=id_list)
|
||||
# batch_id = "90973e57"
|
||||
# generate_trading_report_image(batch_id=batch_id)
|
||||
# id_list = ["e8938b2e-8462-441a-8a82-d823c6a025cb"]
|
||||
# generate_trading_report_image(runner_ids=id_list)
|
||||
batch_id = "90973e57"
|
||||
generate_trading_report_image(batch_id=batch_id)
|
||||
|
||||
+34
-31
@@ -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:
|
||||
try:
|
||||
#block 5s, after that check signals
|
||||
item = self.q1.get(timeout=HEARTBEAT_TIMEOUT)
|
||||
#printnow(current_thread().name, "Items waiting in queue:", self.q1.qsize())
|
||||
except queue.Empty:
|
||||
#check signals
|
||||
if self.se.is_set():
|
||||
print(current_thread().name, "Stopping signal")
|
||||
with tqdm(total=self.q1.qsize()) as pbar:
|
||||
while True:
|
||||
try:
|
||||
#block 5s, after that check signals
|
||||
item = self.q1.get(timeout=HEARTBEAT_TIMEOUT)
|
||||
#printnow(current_thread().name, "Items waiting in queue:", self.q1.qsize())
|
||||
except queue.Empty:
|
||||
#check signals
|
||||
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:
|
||||
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
|
||||
elif self.pe.is_set():
|
||||
print(current_thread().name, "Paused.")
|
||||
continue
|
||||
#self.state.iter_log(event="INGEST",msg="New data ingested", item=item)
|
||||
print("New data ingested", item)
|
||||
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)
|
||||
#self.state.iter_log(event="INGEST",msg="New data ingested", item=item)
|
||||
print("New data ingested", item)
|
||||
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)
|
||||
pbar.update(1)
|
||||
|
||||
tlog(f"FINISHED")
|
||||
print(40*"*",self.mode, "STRATEGY ", self.name,"STOPPING",40*"*")
|
||||
|
||||
Reference in New Issue
Block a user