diff --git a/media/basic/.gitignore b/media/basic/.gitignore
new file mode 100644
index 0000000..0baf103
--- /dev/null
+++ b/media/basic/.gitignore
@@ -0,0 +1,5 @@
+# Ignore everything in this directory
+*
+
+# Except this file
+!.gitignore
\ No newline at end of file
diff --git a/v2realbot/common/PrescribedTradeModel.py b/v2realbot/common/PrescribedTradeModel.py
index 6bfa6a2..db14bff 100644
--- a/v2realbot/common/PrescribedTradeModel.py
+++ b/v2realbot/common/PrescribedTradeModel.py
@@ -30,6 +30,8 @@ class Trade(BaseModel):
entry_price: Optional[float] = None
goal_price: Optional[float] = None
size: Optional[int] = None
+ # size_multiplier je pomocna promenna pro pocitani relativniho denniho profit
+ size_multiplier: Optional[float] = None
# stoploss_type: TradeStoplossType
stoploss_value: Optional[float] = None
profit: Optional[float] = 0
diff --git a/v2realbot/config.py b/v2realbot/config.py
index 452ec5c..ea8f408 100644
--- a/v2realbot/config.py
+++ b/v2realbot/config.py
@@ -1,6 +1,10 @@
from alpaca.data.enums import DataFeed
from v2realbot.enums.enums import Mode, Account, FillCondition
from appdirs import user_data_dir
+from pathlib import Path
+
+#directory for generated images and basic reports
+MEDIA_DIRECTORY = Path(__file__).parent.parent / "media"
#'0.0.0.0',
#currently only prod server has acces to LIVE
diff --git a/v2realbot/controller/services.py b/v2realbot/controller/services.py
index 33a8673..8665d88 100644
--- a/v2realbot/controller/services.py
+++ b/v2realbot/controller/services.py
@@ -13,7 +13,7 @@ from v2realbot.utils.ilog import delete_logs
from v2realbot.common.PrescribedTradeModel import Trade, TradeDirection, TradeStatus, TradeStoplossType
from datetime import datetime
from threading import Thread, current_thread, Event, enumerate
-from v2realbot.config import STRATVARS_UNCHANGEABLES, ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, ACCOUNT1_LIVE_API_KEY, ACCOUNT1_LIVE_SECRET_KEY, DATA_DIR,BT_FILL_CONS_TRADES_REQUIRED,BT_FILL_LOG_SURROUNDING_TRADES,BT_FILL_CONDITION_BUY_LIMIT,BT_FILL_CONDITION_SELL_LIMIT, GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN
+from v2realbot.config import STRATVARS_UNCHANGEABLES, ACCOUNT1_PAPER_API_KEY, ACCOUNT1_PAPER_SECRET_KEY, ACCOUNT1_LIVE_API_KEY, ACCOUNT1_LIVE_SECRET_KEY, DATA_DIR,BT_FILL_CONS_TRADES_REQUIRED,BT_FILL_LOG_SURROUNDING_TRADES,BT_FILL_CONDITION_BUY_LIMIT,BT_FILL_CONDITION_SELL_LIMIT, GROUP_TRADES_WITH_TIMESTAMP_LESS_THAN, MEDIA_DIRECTORY
import importlib
from alpaca.trading.requests import GetCalendarRequest
from alpaca.trading.client import TradingClient
@@ -35,6 +35,8 @@ import v2realbot.strategyblocks.indicators.custom as ci
from v2realbot.strategyblocks.inits.init_indicators import initialize_dynamic_indicators
from v2realbot.strategyblocks.indicators.indicators_hub import populate_dynamic_indicators
from v2realbot.interfaces.backtest_interface import BacktestInterface
+import os
+from v2realbot.reporting.metricstoolsimage import generate_trading_report_image
#from pyinstrument import Profiler
#adding lock to ensure thread safety of TinyDB (in future will be migrated to proper db)
@@ -332,6 +334,12 @@ def capsule(target: object, db: object, inter_batch_params: dict = None):
archive_runner(runner=i, strat=target, inter_batch_params=inter_batch_params)
#mazeme runner po skonceni instance
db.runners.remove(i)
+ #vytvoreni report image pro RUNNER
+ try:
+ generate_trading_report_image(runner_ids=[str(i.id)])
+ print("DAILY REPORT IMAGE CREATED")
+ except Exception as e:
+ print("Nepodarilo se vytvorit report image", str(e)+format_exc())
print("Runner STOPPED")
@@ -500,6 +508,13 @@ def batch_run_manager(id: UUID, runReq: RunRequest, rundays: list[RunDay]):
#i.history += str(runner.__dict__)+"
"
db.save()
+ #vytvoreni report image pro batch
+ try:
+ generate_trading_report_image(batch_id=batch_id)
+ print("BATCH REPORT IMAGE CREATED")
+ except Exception as e:
+ print("Nepodarilo se vytvorit report image", str(e)+format_exc())
+
#stratin run
def run_stratin(id: UUID, runReq: RunRequest, synchronous: bool = False, inter_batch_params: dict = None):
if runReq.mode == Mode.BT:
@@ -676,12 +691,6 @@ def populate_metrics_output_directory(strat: StrategyInstance, inter_batch_param
res["profit"]["batch_sum_profit"] = int(inter_batch_params["batch_profit"])
res["profit"]["batch_sum_rel_profit"] = inter_batch_params["batch_rel_profit"]
- #rel_profit zprumerovane
- res["profit"]["daily_rel_profit_avg"] = float(np.sum(strat.state.rel_profit_cum)) if len(strat.state.rel_profit_cum) > 0 else 0
- #rel_profit rozepsane zisky
- res["profit"]["daily_rel_profit_list"] = strat.state.rel_profit_cum
-
-
#metrikz z prescribedTrades, pokud existuji
try:
long_profit = 0
@@ -696,39 +705,53 @@ def populate_metrics_output_directory(strat: StrategyInstance, inter_batch_param
max_loss_time = None
long_cnt = 0
short_cnt = 0
+ sum_wins_profit= 0
+ sum_loss = 0
if "prescribedTrades" in strat.state.vars:
for trade in strat.state.vars.prescribedTrades:
- if trade.profit_sum < max_loss:
- max_loss = trade.profit_sum
- max_loss_time = trade.last_update
- if trade.profit_sum > max_profit:
- max_profit = trade.profit_sum
- max_profit_time = trade.last_update
- if trade.status == TradeStatus.ACTIVATED and trade.direction == TradeDirection.LONG:
- long_cnt += 1
- if trade.profit is not None:
- long_profit += trade.profit
- if trade.profit < 0:
- long_losses += trade.profit
- if trade.profit > 0:
- long_wins += trade.profit
- if trade.status == TradeStatus.ACTIVATED and trade.direction == TradeDirection.SHORT:
- short_cnt +=1
- if trade.profit is not None:
- short_profit += trade.profit
- if trade.profit < 0:
- short_losses += trade.profit
- if trade.profit > 0:
- short_wins += trade.profit
+ if trade.status == TradeStatus.CLOSED:
+ if trade.profit_sum < max_loss:
+ max_loss = trade.profit_sum
+ max_loss_time = trade.last_update
+ if trade.profit_sum > max_profit:
+ max_profit = trade.profit_sum
+ max_profit_time = trade.last_update
+ if trade.direction == TradeDirection.LONG:
+ long_cnt += 1
+ if trade.profit is not None:
+ long_profit += trade.profit
+ if trade.profit < 0:
+ long_losses += trade.profit
+ if trade.profit > 0:
+ long_wins += trade.profit
+ if trade.direction == TradeDirection.SHORT:
+ short_cnt +=1
+ if trade.profit is not None:
+ short_profit += trade.profit
+ if trade.profit < 0:
+ short_losses += trade.profit
+ if trade.profit > 0:
+ short_wins += trade.profit
+ sum_wins = long_wins + short_wins
+ sum_losses = long_losses + short_losses
+ #toto nejak narovnat, mozna diskutovat s Martinem nebo s Vercou
+
+ #zatim to neukazuje moc jasne - poznámka: ztráta by měla být jenom negativní profit, nikoliv nová veličina
+ #jediná vyjímka je u max.kumulativní ztráty (drawdown)
+ res["profit"]["sum_wins"] = sum_wins
+ res["profit"]["sum_losses"] = sum_losses
res["profit"]["long_cnt"] = long_cnt
- res["profit"]["short_cnt"] = short_cnt
+ res["profit"]["short_cnt"] = short_cnt
+ #celkovy profit za long/short
res["profit"]["long_profit"] = round(long_profit,2)
res["profit"]["short_profit"] = round(short_profit,2)
- res["profit"]["max_profit"] = round(max_profit,2)
- res["profit"]["max_profit_time"] = str(max_profit_time)
- res["profit"]["max_loss"] = round(max_loss,2)
- res["profit"]["max_loss_time"] = str(max_loss_time)
+ #maximalni kumulativni profit (tzn. peaky profitu)
+ res["profit"]["max_profit_cum"] = round(max_profit,2)
+ res["profit"]["max_profit_cum_time"] = str(max_profit_time)
+ #maximalni kumulativni ztrata (tzn. peaky v lossu)
+ res["profit"]["max_loss_cum"] = round(max_loss,2)
+ res["profit"]["max_loss_time_cum"] = str(max_loss_time)
res["profit"]["long_wins"] = round(long_wins,2)
res["profit"]["long_losses"] = round(long_losses,2)
res["profit"]["short_wins"] = round(short_wins,2)
@@ -739,7 +762,13 @@ def populate_metrics_output_directory(strat: StrategyInstance, inter_batch_param
rp_string = "RP" + str(float(np.sum(strat.state.rel_profit_cum))) if len(strat.state.rel_profit_cum) >0 else "noRP"
##summary pro rychle zobrazeni P333L-222 PT9:30 PL10:30
- res["profit"]["sum"]="P"+str(int(max_profit))+"L"+str(int(max_loss))+" "+ mpt_string+" " + mlt_string + rp_string + " "+str(strat.state.rel_profit_cum)
+ res["profit"]["sum"]="P"+str(int(sum_wins))+"L"+str(int(sum_losses))+" "+"MCP"+str(int(max_profit))+"MCL(DD)"+str(int(max_loss))+" "+ mpt_string+" " + mlt_string + rp_string + " "+str(strat.state.rel_profit_cum)
+
+ #rel_profit zprumerovane
+ res["profit"]["daily_rel_profit_sum"] = float(np.sum(strat.state.rel_profit_cum)) if len(strat.state.rel_profit_cum) > 0 else 0
+ #rel_profit rozepsane zisky
+ res["profit"]["daily_rel_profit_list"] = strat.state.rel_profit_cum
+
#vlozeni celeho listu
res["prescr_trades"]=json.loads(json.dumps(strat.state.vars.prescribedTrades, default=json_serial))
@@ -1007,6 +1036,25 @@ def edit_archived_runners(runner_id: UUID, archChange: RunArchiveChange):
print(errmsg)
return -2, errmsg
+
+def delete_report_files(id):
+
+ #ZATIM MAME JEN BASIC
+ #delete report images
+ image_file_name = f"{id}.png"
+ image_path = str(MEDIA_DIRECTORY / "basic" / image_file_name)
+ try:
+ if os.path.exists(image_path):
+ os.remove(image_path)
+ print(f"File {image_path} has been deleted.")
+ return (0, "deleted")
+ else:
+ print(f"No File {image_path} found to delte.")
+ return (1, "not found")
+ except Exception as e:
+ print(f"An error occurred while deleting the file: {e}")
+ return (-1, str(e))
+
#delete runner in archive and archive detail and runner logs
#predelano do JEDNE TRANSAKCE
def delete_archived_runners_byIDs(ids: list[UUID]):
@@ -1016,6 +1064,19 @@ def delete_archived_runners_byIDs(ids: list[UUID]):
for id in ids:
c = conn.cursor()
print(str(id))
+
+ # Get batch_id for the current runner_id
+ c.execute("SELECT batch_id FROM runner_header WHERE runner_id = ?", (str(id),))
+ batch_id = c.fetchone()
+ if batch_id:
+ batch_id = batch_id[0]
+ # Check if this is the last record with the given batch_id
+ c.execute("SELECT COUNT(*) FROM runner_header WHERE batch_id = ?", (batch_id,))
+ count = c.fetchone()[0]
+ if count == 1:
+ # If it's the last record, call delete_report_files
+ delete_report_files(batch_id)
+
resh = c.execute(f"DELETE from runner_header WHERE runner_id='{str(id)}';")
print("header deleted",resh.rowcount)
resd = c.execute(f"DELETE from runner_detail WHERE runner_id='{str(id)}';")
@@ -1025,6 +1086,9 @@ def delete_archived_runners_byIDs(ids: list[UUID]):
out.append(str(id) + ": " + str(resh.rowcount) + " " + str(resd.rowcount) + " " + str(resl.rowcount))
conn.commit()
print("commit")
+
+ delete_report_files(id)
+
# if resh.rowcount == 0 or resd.rowcount == 0:
# return -1, "not found "+str(resh.rowcount) + " " + str(resd.rowcount) + " " + str(resl.rowcount)
return 0, out
@@ -1044,6 +1108,15 @@ def delete_archive_header_byID(id: UUID):
res = execute_with_retry(c,statement)
conn.commit()
print("deleted", res.rowcount)
+ #delete report images
+ image_file_name = f"report_{id}.png"
+ image_path = str(MEDIA_DIRECTORY / image_file_name)
+ try:
+ if os.path.exists(image_path):
+ os.remove(image_path)
+ print(f"File {image_path} has been deleted.")
+ except Exception as e:
+ print(f"An error occurred while deleting the file: {e}")
finally:
pool.release_connection(conn)
return res.rowcount
diff --git a/v2realbot/loader/trade_offline_streamer.py b/v2realbot/loader/trade_offline_streamer.py
index 44840d7..ad68051 100644
--- a/v2realbot/loader/trade_offline_streamer.py
+++ b/v2realbot/loader/trade_offline_streamer.py
@@ -8,7 +8,7 @@ from alpaca.data.enums import DataFeed
from alpaca.data.historical import StockHistoricalDataClient
from alpaca.data.requests import StockLatestQuoteRequest, StockBarsRequest, StockTradesRequest
from threading import Thread, current_thread
-from v2realbot.utils.utils import parse_alpaca_timestamp, ltp, zoneNY, print
+from v2realbot.utils.utils import parse_alpaca_timestamp, ltp, zoneNY
from v2realbot.utils.tlog import tlog
from datetime import datetime, timedelta, date
from threading import Thread
@@ -21,6 +21,8 @@ import os
from rich import print
import queue
from alpaca.trading.models import Calendar
+from tqdm import tqdm
+
"""
Trade offline data streamer, based on Alpaca historical data.
"""
@@ -212,7 +214,7 @@ class Trade_Offline_Streamer(Thread):
cnt = 1
- for t in tradesResponse[symbol]:
+ for t in tqdm(tradesResponse[symbol]):
#protoze je zde cely den, poustime dal, jen ty relevantni
#pokud je start_time < trade < end_time
diff --git a/v2realbot/main.py b/v2realbot/main.py
index 2407c7c..c9fed75 100644
--- a/v2realbot/main.py
+++ b/v2realbot/main.py
@@ -1,6 +1,6 @@
import os,sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-from v2realbot.config import WEB_API_KEY, DATA_DIR
+from v2realbot.config import WEB_API_KEY, DATA_DIR, MEDIA_DIRECTORY
from alpaca.data.timeframe import TimeFrame, TimeFrameUnit
from datetime import datetime
import os
@@ -13,7 +13,7 @@ import v2realbot.controller.services as cs
from v2realbot.utils.ilog import get_log_window
from v2realbot.common.model import StrategyInstance, RunnerView, RunRequest, Trade, RunArchive, RunArchiveView, RunArchiveDetail, Bar, RunArchiveChange, TestList, ConfigItem, InstantIndicator
from fastapi import FastAPI, WebSocket, WebSocketDisconnect, Depends, HTTPException, status, WebSocketException, Cookie, Query
-from fastapi.responses import FileResponse
+from fastapi.responses import FileResponse, StreamingResponse
from fastapi.staticfiles import StaticFiles
from fastapi.security import HTTPBasic, HTTPBasicCredentials
from v2realbot.enums.enums import Env, Mode
@@ -30,6 +30,9 @@ from v2realbot.utils.sysutils import get_environment
from uuid import uuid4
from sqlite3 import OperationalError
from time import sleep
+import v2realbot.reporting.metricstools as mt
+from v2realbot.reporting.metricstoolsimage import generate_trading_report_image
+from traceback import format_exc
#from async io import Queue, QueueEmpty
# install()
@@ -64,6 +67,7 @@ def api_key_auth(api_key: str = Depends(X_API_KEY)):
app = FastAPI()
root = os.path.dirname(os.path.abspath(__file__))
app.mount("/static", StaticFiles(html=True, directory=os.path.join(root, 'static')), name="static")
+app.mount("/media", StaticFiles(directory=str(MEDIA_DIRECTORY)), name="media")
#app.mount("/", StaticFiles(html=True, directory=os.path.join(root, 'static')), name="www")
security = HTTPBasic()
@@ -459,7 +463,6 @@ def _delete_indicator_byName(runner_id: UUID, indicator: InstantIndicator):
raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error not changed: {res}:{runner_id}:{vals}")
-
#edit archived runner ("note",..)
@app.patch("/archived_runners/{runner_id}", dependencies=[Depends(api_key_auth)])
def _edit_archived_runners(archChange: RunArchiveChange, runner_id: UUID):
@@ -509,6 +512,31 @@ def _get_alpaca_history_bars(symbol: str, datetime_object_from: datetime, dateti
else:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"No data found {res} {set}")
+#get pdf report - WIP
+@app.put("/archived_runners/{runner_id}/generatepdf", dependencies=[Depends(api_key_auth)], responses={200: {"content": {"application/pdf": {}}}})
+def _generat_pdf(runner_id: UUID):
+ #jako vstup umouznit i seznam runneru - vytvori to pote report ze vsech techto
+ #pripadne mit jako vstup batch a udelat to pro batch ()
+ res, vals = mt.create_trading_report_pdf(id=runner_id)
+ if res == 0:
+ # Return the PDF data as a streaming response {str(runner_id)}
+ return StreamingResponse(vals, media_type="application/pdf", headers={"Content-Disposition": "attachment; filename=report.pdf"})
+ elif res == -1:
+ raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Error no runner: {runner_id} {res}:{vals}")
+ else:
+ raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error not changed: {res}:{runner_id}:{vals}")
+
+#generate image based list of ids
+@app.post("/archived_runners/generatereportimage", dependencies=[Depends(api_key_auth)], responses={200: {"content": {"image/png": {}}}})
+def _generate_report_image(runner_ids: list[UUID]):
+ try:
+ res, stream = generate_trading_report_image(runner_ids=runner_ids,stream=True)
+ if res == 0: return StreamingResponse(stream, media_type="image/png",headers={"Content-Disposition": "attachment; filename=report.png"})
+ elif res < 0:
+ raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error: {res}:{id}")
+ except Exception as e:
+ raise HTTPException(status_code=status.HTTP_406_NOT_ACCEPTABLE, detail=f"Error: {str(e)}" + format_exc())
+
#TestList APIS - do budoucna predelat SQL do separatnich funkci
@app.post('/testlists/', dependencies=[Depends(api_key_auth)])
def create_record(testlist: TestList):
diff --git a/v2realbot/reporting/__init__.py b/v2realbot/reporting/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/v2realbot/reporting/metricstools.py b/v2realbot/reporting/metricstools.py
new file mode 100644
index 0000000..1517428
--- /dev/null
+++ b/v2realbot/reporting/metricstools.py
@@ -0,0 +1,145 @@
+import json
+import numpy as np
+import matplotlib
+matplotlib.use('Agg') # Set the Matplotlib backend to 'Agg'
+import matplotlib.pyplot as plt
+import seaborn as sns
+import pandas as pd
+from fpdf import FPDF, XPos, YPos
+from datetime import datetime
+from io import BytesIO
+import v2realbot.controller.services as cs
+from rich import print
+def create_trading_report_pdf(id, direct = True, output_file='trading_report.pdf'):
+
+ #get runner
+ res, set =cs.get_archived_runner_header_byID(id)
+ if res != 0:
+ return -1, f"no runner {id} found"
+
+ print("archrunner")
+ print(set)
+
+ # Parse JSON data
+ data = set.metrics
+ profit_data = data["profit"]
+ pos_cnt_data = data["pos_cnt"]
+ prescr_trades_data = data["prescr_trades"]
+
+ # PDF setup
+ pdf = FPDF()
+ pdf.set_auto_page_break(auto=True, margin=15)
+ pdf.set_font("Helvetica", size=10)
+
+ # Start the first page for plots
+ pdf.add_page()
+
+ # Create a combined figure for all plots (adjusting the layout to 3x3)
+ fig, axs = plt.subplots(3, 3, figsize=(15, 15))
+
+ # Plot 1: Overall Profit Summary Chart
+ sns.barplot(x=['Total Wins', 'Total Losses', 'Net Profit'],
+ y=[profit_data["sum_wins"], profit_data["sum_losses"],
+ profit_data["sum_wins"] - profit_data["sum_losses"]],
+ ax=axs[0, 0])
+ axs[0, 0].set_title('Overall Profit Summary')
+
+ # Plot 2: Profit Distribution by Trade Type
+ axs[0, 1].pie([profit_data["long_profit"], profit_data["short_profit"]],
+ labels=['Long Profit', 'Short Profit'], autopct='%1.1f%%')
+ axs[0, 1].set_title('Profit Distribution by Trade Type')
+
+ # Plot 3: Cumulative Profit Over Time Line Chart
+ exit_times = [datetime.fromtimestamp(trade["exit_time"]) for trade in prescr_trades_data]
+ cumulative_profits = [trade["profit_sum"] for trade in prescr_trades_data]
+ sns.lineplot(x=exit_times, y=cumulative_profits, ax=axs[0, 2])
+ axs[0, 2].set_title('Cumulative Profit Over Time')
+ axs[0, 2].tick_params(axis='x', rotation=45)
+
+ # Plot 4: Cumulative Profit Over Time with Max Profit Point
+ sns.lineplot(x=exit_times, y=cumulative_profits, label='Cumulative Profit', ax=axs[1, 0])
+ max_profit_time = datetime.fromisoformat(profit_data["max_profit_cum_time"])
+ max_profit = profit_data["max_profit_cum"]
+ axs[1, 0].scatter(max_profit_time, max_profit, color='green', label='Max Profit')
+ axs[1, 0].set_title('Cumulative Profit Over Time with Max Profit Point')
+ axs[1, 0].tick_params(axis='x', rotation=45)
+ axs[1, 0].legend()
+
+ # Plot 5: Trade Counts Bar Chart
+ sns.barplot(x=['Long Trades', 'Short Trades'],
+ y=[profit_data["long_cnt"], profit_data["short_cnt"]],
+ ax=axs[1, 1])
+ axs[1, 1].set_title('Trade Counts')
+
+ # Plot 6: Position Size Distribution
+ sns.barplot(x=list(pos_cnt_data.keys()), y=list(pos_cnt_data.values()), ax=axs[1, 2])
+ axs[1, 2].set_title('Position Size Distribution')
+
+ # Plot 7: Daily Relative Profit Chart
+ sns.lineplot(x=range(len(profit_data["daily_rel_profit_list"])), y=profit_data["daily_rel_profit_list"], ax=axs[2, 0])
+ axs[2, 0].set_title('Daily Relative Profit')
+ axs[2, 0].set_xlabel('Trade Number')
+ axs[2, 0].set_ylabel('Relative Profit')
+
+ # Adjust layout, save the combined plot, and add it to the PDF
+ # plt.tight_layout()
+ # plt.savefig("combined_plot.png", format="png", bbox_inches="tight")
+ # plt.close()
+ # pdf.image("combined_plot.png", x=10, y=20, w=180)
+
+ plt.tight_layout()
+ plot_buffer = BytesIO()
+ plt.savefig(plot_buffer, format="png")
+ plt.close()
+ plot_buffer.seek(0)
+ pdf.image(plot_buffer, x=10, y=20, w=180)
+ plot_buffer.close()
+
+ # Start a new page for the table and additional information
+ pdf.add_page()
+
+ # 8. Individual Trade Details Table
+ pdf.set_font("Helvetica", size=8)
+ trade_fields = ['id', 'direction', 'entry_time', 'exit_time', 'profit', 'profit_sum', 'rel_profit']
+ trades_table_data = [{field: trade[field] for field in trade_fields} for trade in prescr_trades_data]
+ trades_table = pd.DataFrame(trades_table_data)
+ for row in trades_table.values:
+ for cell in row:
+ pdf.cell(40, 10, str(cell), border=1)
+ pdf.ln()
+
+ # Profit/Loss Ratio and Relative Profit Metrics
+ profit_loss_ratio = "N/A" if profit_data["sum_losses"] == 0 else str(profit_data["sum_wins"] / profit_data["sum_losses"])
+ relative_profit = profit_data["daily_rel_profit_sum"]
+ pdf.cell(0, 10, f"Profit/Loss Ratio: {profit_loss_ratio}", new_x=XPos.LMARGIN, new_y=YPos.NEXT)
+ pdf.cell(0, 10, f"Total Relative Profit: {relative_profit}", new_x=XPos.LMARGIN, new_y=YPos.NEXT)
+
+ # Summary of Key Metrics
+ pdf.cell(0, 10, "\nSummary of Key Metrics:", new_x=XPos.LMARGIN, new_y=YPos.NEXT)
+ pdf.cell(0, 10, f"Total Number of Trades: {profit_data['long_cnt'] + profit_data['short_cnt']}", new_x=XPos.LMARGIN, new_y=YPos.NEXT)
+ pdf.cell(0, 10, f"Total Profit: {profit_data['sum_wins']}", new_x=XPos.LMARGIN, new_y=YPos.NEXT)
+ pdf.cell(0, 10, f"Total Loss: {profit_data['sum_losses']}", new_x=XPos.LMARGIN, new_y=YPos.NEXT)
+ best_trade_profit = max(profit_data["long_wins"], profit_data["short_wins"])
+ pdf.cell(0, 10, f"Best Trade Profit: {best_trade_profit}", new_x=XPos.LMARGIN, new_y=YPos.NEXT)
+ worst_trade_profit = min(trade["profit"] for trade in prescr_trades_data)
+ pdf.cell(0, 10, f"Worst Trade Profit: {worst_trade_profit}", new_x=XPos.LMARGIN, new_y=YPos.NEXT)
+
+ # Save PDF
+ pdf.output(output_file)
+
+ if direct is False:
+ # Save PDF
+ pdf.output(output_file)
+ else:
+ # Instead of saving to a file, write to a BytesIO buffer
+ pdf_buffer = BytesIO()
+ pdf.output(pdf_buffer)
+ pdf_buffer.seek(0) # Move to the beginning of the BytesIO buffer
+ return 0, pdf_buffer
+
+# Example usage:
+if __name__ == '__main__':
+ id = "c3e31cb5-ddf9-467e-a932-2118f6844355"
+ res, val = create_trading_report_pdf(id, True)
+
+ print(res,val)
diff --git a/v2realbot/reporting/metricstoolsimage.py b/v2realbot/reporting/metricstoolsimage.py
new file mode 100644
index 0000000..d4cadf5
--- /dev/null
+++ b/v2realbot/reporting/metricstoolsimage.py
@@ -0,0 +1,382 @@
+import matplotlib
+import matplotlib.dates as mdates
+matplotlib.use('Agg') # Set the Matplotlib backend to 'Agg'
+import matplotlib.pyplot as plt
+import seaborn as sns
+import pandas as pd
+from datetime import datetime
+from typing import List
+from enum import Enum
+import numpy as np
+import v2realbot.controller.services as cs
+from rich import print
+from v2realbot.common.PrescribedTradeModel import TradeDirection, TradeStatus, Trade, TradeStoplossType
+from v2realbot.utils.utils import isrising, isfalling,zoneNY, price2dec, safe_get, print
+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
+# 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):
+
+ #TODO dopracovat drawdown a minimalni a maximalni profity nikoliv cumulovane, zamyslet se
+ #TODO list of runner_ids
+ #TODO pridelat na vytvoreni runnera a batche, samostatne REST API + na remove archrunnera
+
+ if runner_ids is None and batch_id is None:
+ return -2, f"runner_id or batch_id must be present"
+
+ if batch_id is not None:
+ res, runner_ids =cs.get_archived_runnerslist_byBatchID(batch_id)
+
+ if res != 0:
+ print(f"no batch {batch_id} found")
+ return -1, f"no batch {batch_id} found"
+
+ trades = []
+ for id in runner_ids:
+ #get runner
+ res, sada =cs.get_archived_runner_header_byID(id)
+ if res != 0:
+ print(f"no runner {id} found")
+ return -1, f"no runner {id} found"
+
+ print("archrunner")
+ print(sada)
+
+ # Parse trades
+ #trades = [Trade(**trade_dict) for trade_dict in set.metrics["prescr_trades"]]
+
+ trades_dicts = sada.metrics["prescr_trades"]
+
+ for trade_dict in trades_dicts:
+ trade_dict['last_update'] = datetime.fromtimestamp(trade_dict.get('last_update')).astimezone(zoneNY)
+ trade_dict['entry_time'] = datetime.fromtimestamp(trade_dict.get('entry_time')).astimezone(zoneNY)
+ trade_dict['exit_time'] = datetime.fromtimestamp(trade_dict.get('exit_time')).astimezone(zoneNY)
+ trades.append(Trade(**trade_dict))
+
+ print(trades)
+
+ # Filter to only use trades with status 'CLOSED'
+ closed_trades = [trade for trade in trades if trade.status == TradeStatus.CLOSED]
+
+ # Data extraction for the plots
+ exit_times = [trade.exit_time for trade in closed_trades if trade.exit_time is not None]
+ cumulative_profits = [trade.profit_sum for trade in closed_trades if trade.profit_sum is not None]
+ profits = [trade.profit for trade in closed_trades if trade.profit is not None]
+ wins = [trade.profit for trade in closed_trades if trade.profit > 0]
+ losses = [trade.profit for trade in closed_trades if trade.profit < 0]
+
+ wins_long = [trade.profit for trade in closed_trades if trade.profit > 0 and trade.direction == TradeDirection.LONG]
+ losses_long = [trade.profit for trade in closed_trades if trade.profit < 0 and trade.direction == TradeDirection.LONG]
+ wins_short = [trade.profit for trade in closed_trades if trade.profit > 0 and trade.direction == TradeDirection.SHORT]
+ losses_short = [trade.profit for trade in closed_trades if trade.profit < 0 and trade.direction == TradeDirection.SHORT]
+
+ directions = [trade.direction for trade in closed_trades]
+
+ 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
+ plt.style.use('dark_background')
+
+ # Optionally, you can further customize colors, labels, and axes
+ params = {
+ 'axes.titlesize': 9,
+ 'axes.labelsize': 8,
+ 'xtick.labelsize': 9,
+ 'ytick.labelsize': 9,
+ 'axes.labelcolor': '#a9a9a9', #a1a3aa',
+ 'axes.facecolor': '#121722', #'#0e0e0e', #202020', # Dark background for plot area
+ 'axes.grid': False, # Turn off the grid globally
+ 'grid.color': 'gray', # If the grid is on, set grid line color
+ 'grid.linestyle': '--', # Grid line style
+ 'grid.linewidth': 1,
+ 'xtick.color': '#a9a9a9',
+ 'ytick.color': '#a9a9a9',
+ 'axes.edgecolor': '#a9a9a9'
+ }
+ plt.rcParams.update(params)
+
+ # Create a combined figure for all plots
+ fig, axs = plt.subplots(3, 4, figsize=(11, 7))
+
+ #TITLE
+ title = ""
+ cnt_ids = len(runner_ids)
+ if batch_id is not None:
+ title = "Batch: "+str(batch_id)+ " "
+
+ title += "Days: " + str(cnt_ids)
+ if cnt_ids == 1:
+ title += " ("+str(runner_ids[0])[0:14]+") "
+
+ if sada.mode == Mode.BT:
+ datum = sada.bt_from
+ else:
+ datum = sada.started
+
+ title += datum.strftime("%d.%m.%Y %H:%M")
+
+
+ # Add a title to the figure
+ fig.suptitle(title, fontsize=15, color='white')
+
+ # Plot 1: Overall Profit Summary Chart
+ total_wins = int(sum(wins))
+ total_losses = int(sum(losses))
+ net_profit = int(sum(profits))
+ sns.barplot(x=['Total', 'Wins','Losses'],
+ y=[net_profit, total_wins, total_losses],
+ ax=axs[0, 0])
+ axs[0, 0].set_title('Overall Profit Summary')
+ # Define the offset for placing text inside the bars
+ offset = max(total_wins, abs(total_losses), net_profit) * 0.05 # 5% of the highest (or lowest) bar value
+
+ # Function to place text annotation
+ def place_annotation(ax, x, value, offset):
+ va = 'top' if value >= 0 else 'bottom'
+ y = value - offset if value >= 0 else value + offset
+ ax.text(x, y, f'{value}', ha='center', va=va, color='black', fontsize=12)
+
+ # Annotate the Total Wins, Losses, and Net Profit bars
+ place_annotation(axs[0, 0], 0, net_profit, offset)
+ place_annotation(axs[0, 0], 1, total_wins, offset)
+ place_annotation(axs[0, 0], 2, total_losses, offset)
+
+ # Plot 2: LONG - profit summary
+ total_wins_long = int(sum(wins_long))
+ total_losses_long = int(sum(losses_long))
+ total_long = total_wins_long + total_losses_long
+ sns.barplot(x=['Total', 'Wins','Losses'],
+ y=[total_long, total_wins_long, total_losses_long],
+ ax=axs[0, 1])
+ axs[0, 1].set_title('LONG Profit Summary')
+ # Define the offset for placing text inside the bars
+ offset = max(total_wins_long, abs(total_losses_long)) * 0.05 # 5% of the highest (or lowest) bar value
+
+ place_annotation(axs[0, 1], 0, total_long, offset)
+ place_annotation(axs[0, 1], 1, total_wins_long, offset)
+ place_annotation(axs[0, 1], 2, total_losses_long, offset)
+
+
+ # Plot 3: SHORT - profit summary
+ total_wins_short =int(sum(wins_short))
+ total_losses_short = int(sum(losses_short))
+ total_short = total_wins_short + total_losses_short
+ sns.barplot(x=['Total', 'Wins', 'Losses'],
+ y=[total_short, total_wins_short,
+ total_losses_short],
+ ax=axs[0, 2])
+ axs[0, 2].set_title('SHORT Profit Summary')
+ # Define the offset for placing text inside the bars
+ offset = max(total_wins_short, abs(total_losses_short)) * 0.05 # 5% of the highest (or lowest) bar value
+
+ place_annotation(axs[0, 2], 0, total_short, offset)
+ place_annotation(axs[0, 2], 1, total_wins_short, offset)
+ place_annotation(axs[0, 2], 2, total_losses_short, offset)
+
+ # Plot 4: Trade Counts Bar Chart
+ long_count = len([trade for trade in closed_trades if trade.direction == TradeDirection.LONG])
+ short_count = len([trade for trade in closed_trades if trade.direction == TradeDirection.SHORT])
+ sns.barplot(x=['Long Trades', 'Short Trades'], y=[long_count, short_count], ax=axs[0, 3])
+ axs[0, 3].set_title('Trade Counts')
+ offset = max(long_count, short_count) * 0.05 # 5% of the highest (or lowest) bar value
+
+ place_annotation(axs[0, 3], 0, long_count, offset)
+ place_annotation(axs[0, 3], 1, short_count, offset)
+
+
+ #Cumulative profit - bud 1 den nebo vice dni
+ if len(runner_ids)== 1:
+ # 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:
+ # 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 = np.cumsum([trade.profit for trade in sorted_trades])
+ exit_times_sorted = [trade.exit_time for trade in sorted_trades]
+ axs[1, 3].plot(exit_times_sorted, cumulative_profits, 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:
+ if trade.status == TradeStatus.CLOSED:
+ day = trade.exit_time.strftime('%m-%d') # Format date as 'MM-DD'
+ #day = trade.exit_time.date()
+ hour = trade.exit_time.hour
+ profit = trade.profit
+ heatmap_data_list.append({'Day': day, 'Hour': hour, 'Profit': profit})
+
+ heatmap_data = pd.DataFrame(heatmap_data_list)
+ 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
+ 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')
+ axs[1, 0].set_ylabel('Day')
+
+ # Plot 9: 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
+ # - pro 1 den: Position Size Distribution
+ # - pro vice dnu: Trade Duration vs. Profit/Loss
+ if len(runner_ids) == 1:
+
+ sizes = [trade.size for trade in closed_trades if trade.size is not None]
+ size_counts = {size: sizes.count(size) for size in set(sizes)}
+ sns.barplot(x=list(size_counts.keys()), y=list(size_counts.values()), ax=axs[1, 2])
+ axs[1, 2].set_title('Position Size Distribution')
+ else:
+ trade_durations = []
+ trade_profits = []
+ #trade_volumes = [] # Assuming you have a way to measure the size/volume of each trade
+ trade_types = [] # 'Long' or 'Short'
+
+ for trade in trades:
+ if trade.status == TradeStatus.CLOSED:
+ duration = (trade.exit_time - trade.entry_time).total_seconds() / 60 # Duration in minutes (3600 for hours)
+ trade_durations.append(duration)
+ trade_profits.append(trade.profit)
+ ##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
+ scatter_data = pd.DataFrame({
+ 'Duration': trade_durations,
+ 'Profit': trade_profits,
+ #'Volume': trade_volumes,
+ 'Type': trade_types
+ })
+ #sns.scatterplot(data=scatter_data, x='Duration', y='Profit', size='Volume', hue='Type', ax=axs[1, 2])
+ sns.scatterplot(data=scatter_data, x='Duration', y='Profit', hue='Type', ax=axs[1, 2])
+ axs[1, 2].set_title('Trade Duration vs. Profit/Loss')
+ axs[1, 2].set_xlabel('Duration (Minutes)')
+ axs[1, 2].set_ylabel('Profit/Loss')
+
+
+ # Plot 6: Daily Relative Profit Chart
+ 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])
+ axs[2, 0].set_title('Daily Relative Profit')
+ else:
+ # Creating a DataFrame for the heatmap
+ heatmap_data_list = []
+ for trade in trades:
+ if trade.status == TradeStatus.CLOSED:
+ day = trade.entry_time.strftime('%m-%d') # Format date as 'MM-DD'
+ #day = trade.entry_time.date()
+ hour = trade.entry_time.hour
+ profit = trade.profit
+ heatmap_data_list.append({'Day': day, 'Hour': hour, 'Profit': profit})
+
+ heatmap_data = pd.DataFrame(heatmap_data_list)
+ 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
+ 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)
+ 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):
+ if hour not in profits_by_hour:
+ profits_by_hour[hour] = 0
+ profits_by_hour[hour] += trade.profit
+
+ # Sorting by hour for plotting
+ sorted_hours = sorted(profits_by_hour.keys())
+ sorted_profits = [profits_by_hour[hour] for hour in sorted_hours]
+
+ sns.barplot(x=sorted_hours, y=sorted_profits, ax=axs[2, 1])
+ axs[2, 1].set_title('Profits by Hour of Day (Entry)')
+ axs[2, 1].set_xlabel('Hour of Day')
+ axs[2, 1].set_ylabel('Profit')
+
+ # Plot 9: 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):
+ if hour not in profits_by_hour:
+ profits_by_hour[hour] = 0
+ profits_by_hour[hour] += trade.profit
+
+ # Sorting by hour for plotting
+ sorted_hours = sorted(profits_by_hour.keys())
+ sorted_profits = [profits_by_hour[hour] for hour in sorted_hours]
+
+ sns.barplot(x=sorted_hours, y=sorted_profits, ax=axs[2, 2])
+ axs[2, 2].set_title('Profits by Hour of Day (Exit)')
+ axs[2, 2].set_xlabel('Hour of Day')
+ axs[2, 2].set_ylabel('Profit')
+
+ # 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:
+ if trade.status == TradeStatus.CLOSED:
+ day_of_week = trade.exit_time.weekday() # Monday is 0 and Sunday is 6
+ day_of_week_profits[day_of_week] += trade.profit
+
+ days = ['Mo', 'Tue', 'Wed', 'Thu', 'Fri']
+ # Additional Plot: Strategy Performance by Day of the Week
+ axs[2, 3].bar(days, [day_of_week_profits[i] for i in range(5)])
+ axs[2, 3].set_title('Profit by Day of the Week')
+ axs[2, 3].set_xlabel('Day of the Week')
+ axs[2, 3].set_ylabel('Cumulative Profit')
+
+ #filename
+ file = batch_id if batch_id is not None else runner_ids[0]
+ image_file_name = f"{file}.png"
+ image_path = str(MEDIA_DIRECTORY / "basic" / image_file_name)
+
+ # Adjust layout and save the combined plot as an image
+ plt.tight_layout()
+
+ if stream is False:
+ plt.savefig(image_path)
+ plt.close()
+ else:
+ # Return the image as a BytesIO stream
+ img_stream = BytesIO()
+ plt.savefig(img_stream, format='png')
+ plt.close()
+ img_stream.seek(0) # Rewind the stream to the beginning
+ return 0, img_stream
+
+# 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)
diff --git a/v2realbot/static/index.html b/v2realbot/static/index.html
index bf18666..63f9e6d 100644
--- a/v2realbot/static/index.html
+++ b/v2realbot/static/index.html
@@ -279,7 +279,9 @@
-
+
+
![]()
+
diff --git a/v2realbot/static/js/archivetables.js b/v2realbot/static/js/archivetables.js
index 2dbb909..d16036d 100644
--- a/v2realbot/static/js/archivetables.js
+++ b/v2realbot/static/js/archivetables.js
@@ -110,9 +110,61 @@ function prepare_export() {
return trdList
}
+function display_image(imageUrl) {
+ // Attempt to load the image
+ var img = new Image();
+ img.src = imageUrl;
+ img.onload = function() {
+ // If the image loads successfully, display it
+ $('#previewImg').attr('src', imageUrl);
+ $('#imagePreview').show();
+ };
+ img.onerror = function() {
+ console.log("no image available")
+ // If the image fails to load, do nothing
+ };
+}
+
$(document).ready(function () {
archiveRecords.ajax.reload();
+ // Use 'td:nth-child(2)' to target the second column
+ $('#archiveTable tbody').on('click', 'td:nth-child(2)', function () {
+ var data = archiveRecords.row(this).data();
+ //var imageUrl = '/media/report_'+data.id+".png"; // Replace with your logic to get image URL
+ var imageUrl = '/media/basic/'+data.id+'.png'; // Replace with your logic to get image URL
+ console.log(imageUrl)
+ display_image(imageUrl)
+ });
+
+ // Use 'td:nth-child(2)' to target the second column
+ $('#archiveTable tbody').on('click', 'td:nth-child(18)', function () {
+ var data = archiveRecords.row(this).data();
+ if (data.batch_id) {
+ //var imageUrl = '/media/report_'+data.id+".png"; // Replace with your logic to get image URL
+ var imageUrl = '/media/basic/'+data.batch_id+'.png'; // Replace with your logic to get image URL
+ console.log(imageUrl)
+ display_image(imageUrl)
+ }
+ });
+
+ // $('#archiveTable tbody').on('mouseleave', 'td:nth-child(2)', function () {
+ // $('#imagePreview').hide();
+ // });
+
+ // Hide image on click anywhere in the document
+ $(document).on('click', function() {
+ $('#imagePreview').hide();
+ });
+
+ function hideImage() {
+ $('#imagePreview').hide();
+ }
+ // $('#archiveTable tbody').on('mousemove', 'td:nth-child(2)', function(e) {
+ // $('#imagePreview').css({'top': e.pageY + 10, 'left': e.pageX + 10});
+ // });
+
+
//button export
$('#button_export_xml').click(function () {
xmled = convertToXml(prepare_export())
@@ -360,6 +412,46 @@ $(document).ready(function () {
}
});
+ //generate report button
+ $('#button_report').click(function () {
+ rows = archiveRecords.rows('.selected');
+ if (rows == undefined) {
+ return
+ }
+ runnerIds = []
+ if(rows.data().length > 0 ) {
+ // Loop through the selected rows and display an alert with each row's ID
+ rows.every(function (rowIdx, tableLoop, rowLoop ) {
+ var data = this.data()
+ runnerIds.push(data.id);
+ });
+ }
+ $.ajax({
+ url:"/archived_runners/generatereportimage",
+ beforeSend: function (xhr) {
+ xhr.setRequestHeader('X-API-Key',
+ API_KEY); },
+ method:"POST",
+ xhrFields: {
+ responseType: 'blob'
+ },
+ contentType: "application/json",
+ processData: false,
+ data: JSON.stringify(runnerIds),
+ success:function(blob){
+ var url = window.URL || window.webkitURL;
+ console.log("vraceny obraz", blob)
+ console.log("url",url.createObjectURL(blob))
+ display_image(url.createObjectURL(blob))
+ },
+ error: function(xhr, status, error) {
+ console.log("proc to skace do erroru?")
+ //window.alert(JSON.stringify(xhr));
+ console.log(JSON.stringify(xhr));
+ }
+ })
+ });
+
//delete button
$('#button_delete_arch').click(function () {
diff --git a/v2realbot/static/main.css b/v2realbot/static/main.css
index 1f2cf1f..16687d7 100644
--- a/v2realbot/static/main.css
+++ b/v2realbot/static/main.css
@@ -164,7 +164,14 @@ table.dataTable thead>tr>th.sorting_asc:before, table.dataTable thead>tr>th.sort
--bs-gradient: none;
}
-
+#imagePreview {
+ display: none;
+ position: fixed;
+ z-index: 100;
+ left: 50%;
+ top: 50%;
+ transform: translate(-50%, -50%);
+}
/* .btn-outline-success {
--bs-btn-color: #316164;
diff --git a/v2realbot/strategy/StrategyClassicSL.py b/v2realbot/strategy/StrategyClassicSL.py
index 04b0c3c..a9e3d6f 100644
--- a/v2realbot/strategy/StrategyClassicSL.py
+++ b/v2realbot/strategy/StrategyClassicSL.py
@@ -129,14 +129,27 @@ class StrategyClassicSL(Strategy):
#pokud jde o finalni FILL - pridame do pole tento celkovy relativnich profit (ze ktereho se pocita kumulativni relativni profit)
rel_profit_cum_calculated = 0
-
+ partial_exit = False
+ partial_last = False
if data.event == TradeEvent.FILL:
- #TODO pokud mame partial exit, tak se spravne vypocita relativni profit, ale
- # je jen na mensi mnozszvi take z nej delat cum_calculate je blbost - OPRAVIT
- self.state.rel_profit_cum.append(rel_profit)
- rel_profit_cum_calculated = round(np.sum(self.state.rel_profit_cum),5)
+ #jde o partial EXIT dvááme si rel.profit do docasne promenne, po poslednim exitu z nich vypocteme skutecny rel.profit
+ if data.position_qty != 0:
+ self.state.docasny_rel_profit.append(rel_profit)
+ partial_exit = True
+ else:
+ #jde o posledni z PARTIAL EXITU tzn.data.position_qty == 0
+ if len(self.state.docasny_rel_profit) > 0:
+ #pricteme aktualni rel profit
+ self.state.docasny_rel_profit.append(rel_profit)
+ #a z rel profitu tohoto tradu vypocteme prumer, ktery teprve ulozime
+ rel_profit = round(np.mean(self.state.docasny_rel_profit),5)
+ self.state.docasny_rel_profit = []
+ partial_last = True
- self.state.ilog(e=f"BUY notif - SHORT PROFIT:{round(float(trade_profit),3)} celkem:{round(float(self.state.profit),3)} rel:{float(rel_profit)} rel_cum:{round(rel_profit_cum_calculated,7)}", msg=str(data.event), rel_profit_cum=str(self.state.rel_profit_cum), bought_amount=bought_amount, avg_costs=avg_costs, trade_qty=data.qty, trade_price=data.price, orderid=str(data.order.id))
+ self.state.rel_profit_cum.append(rel_profit)
+ rel_profit_cum_calculated = round(np.sum(self.state.rel_profit_cum),5)
+
+ self.state.ilog(e=f"BUY notif - SHORT PROFIT: {partial_exit=} {partial_last=} {round(float(trade_profit),3)} celkem:{round(float(self.state.profit),3)} rel:{float(rel_profit)} rel_cum:{round(rel_profit_cum_calculated,7)}", msg=str(data.event), rel_profit_cum=str(self.state.rel_profit_cum), bought_amount=bought_amount, avg_costs=avg_costs, trade_qty=data.qty, trade_price=data.price, orderid=str(data.order.id))
#zapsat profit do prescr.trades
for trade in self.state.vars.prescribedTrades:
@@ -260,12 +273,27 @@ class StrategyClassicSL(Strategy):
rel_profit = round((trade_profit / (vstup_cena * float(data.order.qty))) * 100,5)
rel_profit_cum_calculated = 0
- #pokud jde o finalni FILL - pridame do pole relativnich profit (ze ktereho se pocita kumulativni relativni profit)
+ partial_exit = False
+ partial_last = False
if data.event == TradeEvent.FILL:
- self.state.rel_profit_cum.append(rel_profit)
- rel_profit_cum_calculated = round(np.sum(self.state.rel_profit_cum),5)
+ #jde o partial EXIT dvááme si rel.profit do docasne promenne, po poslednim exitu z nich vypocteme skutecny rel.profit
+ if data.position_qty != 0:
+ self.state.docasny_rel_profit.append(rel_profit)
+ partial_exit = True
+ else:
+ #jde o posledni z PARTIAL EXITU tzn.data.position_qty == 0
+ if len(self.state.docasny_rel_profit) > 0:
+ #pricteme aktualni rel profit
+ self.state.docasny_rel_profit.append(rel_profit)
+ #a z rel profitu tohoto tradu vypocteme prumer, ktery teprve ulozime
+ rel_profit = round(np.mean(self.state.docasny_rel_profit),5)
+ self.state.docasny_rel_profit = []
+ partial_last = True
- self.state.ilog(e=f"SELL notif - PROFIT:{round(float(trade_profit),3)} celkem:{round(float(self.state.profit),3)} rel:{float(rel_profit)} rel_cum:{round(rel_profit_cum_calculated,7)}", msg=str(data.event), rel_profit_cum = str(self.state.rel_profit_cum), sold_amount=sold_amount, avg_costs=avg_costs, trade_qty=data.qty, trade_price=data.price, orderid=str(data.order.id))
+ self.state.rel_profit_cum.append(rel_profit)
+ rel_profit_cum_calculated = round(np.sum(self.state.rel_profit_cum),5)
+
+ self.state.ilog(e=f"SELL notif - LONG PROFIT {partial_exit=} {partial_last=}:{round(float(trade_profit),3)} celkem:{round(float(self.state.profit),3)} rel:{float(rel_profit)} rel_cum:{round(rel_profit_cum_calculated,7)}", msg=str(data.event), rel_profit_cum = str(self.state.rel_profit_cum), sold_amount=sold_amount, avg_costs=avg_costs, trade_qty=data.qty, trade_price=data.price, orderid=str(data.order.id))
#zapsat profit do prescr.trades
for trade in self.state.vars.prescribedTrades:
diff --git a/v2realbot/strategy/base.py b/v2realbot/strategy/base.py
index c1b721e..64f16c4 100644
--- a/v2realbot/strategy/base.py
+++ b/v2realbot/strategy/base.py
@@ -707,6 +707,7 @@ class StrategyState:
self.runner_id = runner_id
self.bt = bt
self.dont_exit_already_activated = False
+ self.docasny_rel_profit = []
self.ilog_save = ilog_save
self.sl_optimizer_short = optimsl.SLOptimizer(ptm.TradeDirection.SHORT)
self.sl_optimizer_long = optimsl.SLOptimizer(ptm.TradeDirection.LONG)
diff --git a/v2realbot/strategyblocks/indicators/helpers.py b/v2realbot/strategyblocks/indicators/helpers.py
index 5c421cd..7e1c574 100644
--- a/v2realbot/strategyblocks/indicators/helpers.py
+++ b/v2realbot/strategyblocks/indicators/helpers.py
@@ -82,7 +82,10 @@ def get_source_series(state, source: str):
try:
return state.bars[source]
except KeyError:
- return state.indicators[source]
+ try:
+ return state.indicators[source]
+ except KeyError:
+ return None
else:
dict_name = source[:split_index]
key = source[split_index + 1:]
diff --git a/v2realbot/strategyblocks/newtrade/signals.py b/v2realbot/strategyblocks/newtrade/signals.py
index b9b1040..71f7320 100644
--- a/v2realbot/strategyblocks/newtrade/signals.py
+++ b/v2realbot/strategyblocks/newtrade/signals.py
@@ -7,6 +7,7 @@ from datetime import datetime
from rich import print as printanyway
from traceback import format_exc
from v2realbot.strategyblocks.newtrade.conditions import go_conditions_met, common_go_preconditions_check
+from v2realbot.strategyblocks.newtrade.sizing import get_size, get_multiplier
def signal_search(state: StrategyState, data):
# SIGNAL sekce ve stratvars obsahuje signaly: Ty se skladaji z obecnych parametru a podsekce podminek.
@@ -42,7 +43,7 @@ def execute_signal_generator(state, data, name):
options = safe_get(state.vars.signals, name, None)
if options is None:
- state.ilog(lvl=1,e="No options for {name} in stratvars")
+ state.ilog(lvl=1,e=f"No options for {name} in stratvars")
return
if common_go_preconditions_check(state, data, signalname=name, options=options) is False:
@@ -71,20 +72,26 @@ def execute_signal_generator(state, data, name):
if long_enabled is False:
state.ilog(lvl=1,e=f"{name} LONG DISABLED")
if long_enabled and go_conditions_met(state, data,signalname=name, direction=TradeDirection.LONG):
+ multiplier = get_multiplier(state, data, options, TradeDirection.LONG)
state.vars.prescribedTrades.append(Trade(
id=uuid4(),
last_update=datetime.fromtimestamp(state.time).astimezone(zoneNY),
status=TradeStatus.READY,
generated_by=name,
+ size=multiplier*state.vars.chunk,
+ size_multiplier = multiplier,
direction=TradeDirection.LONG,
entry_price=None,
stoploss_value = None))
elif short_enabled and go_conditions_met(state, data, signalname=name, direction=TradeDirection.SHORT):
+ multiplier = get_multiplier(state, data, options, TradeDirection.SHORT)
state.vars.prescribedTrades.append(Trade(
id=uuid4(),
last_update=datetime.fromtimestamp(state.time).astimezone(zoneNY),
status=TradeStatus.READY,
generated_by=name,
+ size=multiplier*state.vars.chunk,
+ size_multiplier = multiplier,
direction=TradeDirection.SHORT,
entry_price=None,
stoploss_value = None))
diff --git a/v2realbot/strategyblocks/newtrade/sizing.py b/v2realbot/strategyblocks/newtrade/sizing.py
new file mode 100644
index 0000000..a6a76e6
--- /dev/null
+++ b/v2realbot/strategyblocks/newtrade/sizing.py
@@ -0,0 +1,143 @@
+from v2realbot.strategy.base import StrategyState
+from v2realbot.common.PrescribedTradeModel import Trade, TradeDirection, TradeStatus
+import v2realbot.utils.utils as utls
+from v2realbot.config import KW
+from uuid import uuid4
+from datetime import datetime
+from rich import print as printanyway
+from traceback import format_exc
+from v2realbot.strategyblocks.newtrade.conditions import go_conditions_met, common_go_preconditions_check
+from v2realbot.strategyblocks.indicators.helpers import get_source_series
+import numpy as np
+
+def get_size(state: StrategyState, data, signaloptions: dict, direction: TradeDirection):
+ return state.vars.chunk * get_multiplier(state, signaloptions, direction)
+
+def get_multiplier(state: StrategyState, data, signaloptions: dict, direction: TradeDirection):
+ """"
+ Function return dynamic sizing multiplier according to directive and current trades.
+
+ Default: state.vars.chunk
+
+ Additional sizing logic is layered on top of each other according to directives.
+
+ Currently supporting:
+ 1) pattern sizing U-shape, hat-shape (x - bars, minutes, y - sizing multiplier 0 to 1 )
+ 2) probes
+
+ Future ideas:
+ - ML sizing model
+
+ DIRECTIVES:
+ #sondy na zacatku market
+ probe_enabled = true # sonda zapnuta
+ number = 1 # pocet sond
+ probe_size = 0.01 #velikost sondy, nasobek def size
+
+ #pattern - dynamicka uprava na zaklade casu
+ pattern_enabled = true
+ pattern_source = "minutes" #or any series - indicators, bars or state etc. (index[-1], np.sum(state.rel_profit_cum)...)
+ pattern_source_vals = [0,30,90, 200, 300, 390]
+ pattern_sizing_vals = [0.1,0.5, 0.8, 1, 0.6, 0.1]
+
+ #np.interp(atr10, [0.001, 0.06], [1, 5])
+ #size_multiplier = np.interp(pattern_source, [SIZING_pattern_source_vals], [SIZING_pattern_sizing_vals])
+
+
+ #TODO
+ - pomocna graf pro vizualizaci interpolace - v tools/sizingpatternvisual.py
+ - dopsat do dokumentace direktiv - do tabulky
+ - ukládat sizing coeff do prescrTrades
+ - upravit výpočet denního relativniho profitu u tradu na základě vstupního sizing koeficientu
+ - vyresit zda max_oss_to_quit_rel aplikovat bud per alokovana pozice nebo trade
+ (pokud mam na trade, pak mi zafunguje i na minimalni sodnu) Zatim bude
+ realizován takto
+
+ - nejprve ověří rel profit tradu a pokud přesáhne, strategie se suspendne
+ - poté se rel profit tradu vynásobí multiplikátorem a započte se do denního rel profitu, jehož
+ výše se následně také ověří
+
+ NOTE: zatim neupraveno, a do denniho rel profitu se zapocitava plnym pomerem, diky tomu
+ si muzu dat i na sondu -0.5 suspend strategie. Nevyhoda: rel.profit presne neodpovida
+
+ [stratvars.signals.morning1.sizing] #specificke pro dany signal
+ probe_enabled = true
+ probe_size = 0.01
+ pattern_enabled = true
+ # pattern_source = "minutes" #or any series - indicators, bars or state etc. (index[-1], np.sum(state.rel_profit_cum)...)
+ pattern_source_axis = [0,30,90, 200, 300, 390]
+ pattern_size_axis = [0.1,0.5, 0.8, 1, 0.6, 0.1]
+
+ [stratvars.sizing] #obecne jako fallback pro vsechny signaly
+ probe_enabled = true
+ probe_size = 0.01
+ pattern_enabled = true
+ # pattern_source = "minutes" #or any series - indicators, bars or state etc. (index[-1], np.sum(state.rel_profit_cum)...)
+ pattern_source_axis = [0,30,90, 200, 300, 390]
+ pattern_size_axis = [0.1,0.5, 0.8, 1, 0.6, 0.1]
+
+ """""
+ multiplier = 1
+
+ #fallback common sizing sekci
+ fallback_options = utls.safe_get(state.vars, 'sizing', None)
+
+ #signal specific sekce
+ options = utls.safe_get(signaloptions, 'sizing', fallback_options)
+
+ if options is None:
+ state.ilog(lvl=1,e="No sizing options common or signal specific in stratvars")
+ return multiplier
+
+ #PROBE ENABLED
+ # probe_enabled = true # sonda zapnuta
+ # probe_number = 1 # pocet sond
+ # probe_size = 0.01 #velikost sondy, nasobek def size
+
+ probe_enabled = utls.safe_get(options, "probe_enabled", False)
+
+ if probe_enabled:
+ #zatim pouze probe number 1 natvrdo, tzn. nesmi byt trade pro aktivace
+ if state.vars.last_in_index is None:
+ #probe_number = utls.safe_get(options, "probe_number",1)
+ probe_size = float(utls.safe_get(options, "probe_size", 0.1))
+ state.ilog(lvl=1,e=f"SIZER - PROBE - setting multiplier to {probe_size}", options=options)
+ return probe_size
+
+ #SIZING PATTER
+ # pattern_enabled = true
+ # pattern_source = "minutes" #or any series - indicators, bars or state etc. (index[-1], np.sum(state.rel_profit_cum)...)
+ # pattern_source_axis = [0,30,90, 200, 300, 390]
+ # pattern_size_axis = [0.1,0.5, 0.8, 1, 0.6, 0.1]
+ pattern_enabled = utls.safe_get(options, "pattern_enabled", False)
+
+ if pattern_enabled:
+ input_value = None
+ pattern_source = utls.safe_get(options, "pattern_source", "minutes")
+
+ #TODO do budoucna mozna sem dát libovolnou series např. index, time, profit, rel_profit?
+ if pattern_source != "minutes":
+
+ input_value = eval(pattern_source, {'state': state, 'np': np, 'utls': utls}, state.ind_mapping)
+
+ if input_value is None:
+ state.ilog(lvl=1,e=f"SIZER - ERROR Pattern source is None, after evaluation of expression", options=str(options))
+ return multiplier
+ else:
+ input_value = utls.minutes_since_market_open(datetime.fromtimestamp(data['updated']).astimezone(utls.zoneNY))
+
+ pattern_source_axis = utls.safe_get(options, "pattern_source_axis", None)
+ pattern_size_axis = utls.safe_get(options, "pattern_size_axis", None)
+
+ if pattern_source_axis is None or pattern_size_axis is None:
+ state.ilog(lvl=1,e=f"SIZER - Pattern source and size axis must be set", options=str(options))
+ return multiplier
+
+ state.ilog(lvl=1,e=f"SIZER - Input value of {pattern_source} value {input_value}", options=options, time=state.time)
+ multiplier = np.interp(input_value, pattern_source_axis, pattern_size_axis)
+ state.ilog(lvl=1,e=f"SIZER - Interpolated value {multiplier}", input_value=input_value, pattern_source_axis=pattern_source_axis, pattern_size_axis=pattern_size_axis, options=options, time=state.time)
+
+ if multiplier > 1 or multiplier <= 0:
+ state.ilog(lvl=1,e=f"SIZER - Mame nekde problem MULTIPLIER mimo RANGE ERROR {multiplier}", options=options, time=state.time)
+ multiplier = 1
+ return multiplier
diff --git a/v2realbot/tools/sizingpattervisual.py b/v2realbot/tools/sizingpattervisual.py
new file mode 100644
index 0000000..b5716a5
--- /dev/null
+++ b/v2realbot/tools/sizingpattervisual.py
@@ -0,0 +1,29 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Sem zadat pattern X a Y pro VIZUALIZACI
+
+#minutes
+pattern_x = [0, 30, 90, 200, 300, 390]
+pattern_y = [0.1, 0.5, 0.8, 1, 0.6, 0.1]
+
+#bar index - použitelné u time scale barů
+pattern_x = [0, 30, 90, 200, 300, 390]
+pattern_y = [0.1, 0.5, 0.8, 1, 0.6, 0.1]
+
+#celkový profit
+
+# Generating a range of input values for interpolation
+input_values = np.linspace(min(pattern_x), max(pattern_x), 500)
+multipliers = np.interp(input_values, pattern_x, pattern_y)
+
+# Plotting
+plt.figure(figsize=(10, 6))
+plt.plot(pattern_x, pattern_y, 'o', label='Original Points')
+plt.plot(input_values, multipliers, label='Interpolated Values')
+plt.xlabel('X values')
+plt.ylabel('Interpolated Multipliers')
+plt.title('Interpolation Chart')
+plt.legend()
+plt.grid(True)
+plt.show()
diff --git a/v2realbot/utils/utils.py b/v2realbot/utils/utils.py
index 5bc2a24..d2cc6f1 100644
--- a/v2realbot/utils/utils.py
+++ b/v2realbot/utils/utils.py
@@ -464,6 +464,30 @@ def is_open_rush(dt: datetime, mins: int = 30):
rushtime = (datetime.combine(date.today(), business_hours["from"]) + timedelta(minutes=mins)).time()
return business_hours["from"] <= dt.time() < rushtime
+
+#TODO v budoucnu predelat - v initu nacist jednou market open cas a ten pouzivat vsude
+#kde je treba (ted je tady natvrdo 9.30)
+def minutes_since_market_open(datetime_aware: datetime):
+ """
+ Calculate the number of minutes elapsed from 9:30 AM to the given timezone-aware datetime of the same day.
+ This version is optimized for speed and should be used when calling in a loop.
+
+ :param datetime_aware: A timezone-aware datetime object representing the time to compare.
+ :return: The number of minutes since today's 9:30 AM.
+ """
+ # Ensure the input datetime is timezone-aware
+ if datetime_aware.tzinfo is None or datetime_aware.tzinfo.utcoffset(datetime_aware) is None:
+ raise ValueError("The input datetime must be timezone-aware.")
+
+ # Calculate minutes since midnight for both times
+ minutes_since_midnight = datetime_aware.hour * 60 + datetime_aware.minute
+ morning_minutes = 9 * 60 + 30
+
+ # Calculate the difference
+ delta_minutes = minutes_since_midnight - morning_minutes
+
+ return delta_minutes if delta_minutes >= 0 else 0
+
#optimalized by BARD
def is_window_open(dt: datetime, start: int = 0, end: int = 390):
""""