feat: Add Phase 4 advanced metrics and components
- Add advanced metrics dashboard with trade analytics - Add new trading components (EntryTypeAnalysis, MultiDayPositionTracker, NewsEventTracker, etc.) - Add strategy mode selector and trend confirmation - Add risk automation panel and slippage correlation analysis - Add daily trading plan enhancements with modal components - Add custom hooks (useApi, useLocalStorage, useAdvancedTradeMetrics) - Add broker service integration and trading API - Add test setup and vitest configuration - Include parquet data files for live market data - Add comprehensive documentation in docs/ folder
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Krikorios
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#!/usr/bin/env python3
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"""Utility script to pull historical bars from MetaTrader 5 into live_store.
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Run inside the backend virtualenv with DATA_PROVIDER=metatrader.
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"""
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import argparse
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from datetime import datetime, timedelta
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try:
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import MetaTrader5 as mt5 # type: ignore
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except Exception as exc: # pragma: no cover
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raise SystemExit("MetaTrader5 package not installed.") from exc
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from app.streaming.live_store import live_store
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def parse_args():
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parser = argparse.ArgumentParser(description="Import MT5 history into live_store.")
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parser.add_argument("symbol", help="Symbol, e.g., XAUUSD")
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parser.add_argument("timeframe", help="MT5 timeframe, e.g., 1m, 5m, 1h", default="1m")
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parser.add_argument("bars", type=int, default=1000, nargs="?", help="Number of bars to fetch")
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return parser.parse_args()
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def resolve_timeframe(name: str):
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mapping = {
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"1m": mt5.TIMEFRAME_M1,
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"5m": mt5.TIMEFRAME_M5,
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"15m": mt5.TIMEFRAME_M15,
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"30m": mt5.TIMEFRAME_M30,
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"60m": mt5.TIMEFRAME_H1,
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"1h": mt5.TIMEFRAME_H1,
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"4h": mt5.TIMEFRAME_H4,
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"1d": mt5.TIMEFRAME_D1,
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}
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return mapping.get(name.lower(), mt5.TIMEFRAME_M1)
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def main():
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args = parse_args()
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if not mt5.initialize():
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raise SystemExit(f"Failed to initialize MetaTrader5: {mt5.last_error()}")
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timeframe = resolve_timeframe(args.timeframe)
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rates = mt5.copy_rates_from_pos(args.symbol, timeframe, 0, args.bars)
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if not rates:
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raise SystemExit("No rates returned. Check symbol/timeframe.")
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for row in rates:
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live_store.ingest_bar(
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symbol=args.symbol,
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timeframe=args.timeframe,
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bar={
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"time": int(row['time']),
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"open": float(row['open']),
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"high": float(row['high']),
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"low": float(row['low']),
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"close": float(row['close']),
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"volume": float(row.get('tick_volume', 0.0)),
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},
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)
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print(f"Imported {len(rates)} bars for {args.symbol} {args.timeframe}")
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if __name__ == "__main__":
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main()
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@@ -0,0 +1,125 @@
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#!/usr/bin/env python3
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"""Utility for priming LiveStore and flushing sample candles to parquet.
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This script spins up the configured streaming data provider (local simulator by
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default), keeps it running for a short window, and forces flushes so that
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parquet partitions are materialized under ``data/parquet/live``.
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"""
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from __future__ import annotations
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import argparse
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import asyncio
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import contextlib
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import os
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from pathlib import Path
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from typing import Tuple
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import sys
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PROJECT_ROOT = Path(__file__).resolve().parents[1]
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if str(PROJECT_ROOT) not in sys.path:
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sys.path.insert(0, str(PROJECT_ROOT))
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from app.streaming.live_store import live_store
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from app.streaming.data_provider import data_provider
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def _parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser(description="Prime LiveStore and flush parquet output for a symbol/timeframe")
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parser.add_argument("--symbol", default="XAUUSD", help="Symbol to stream (default: XAUUSD)")
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parser.add_argument("--timeframe", default="1m", help="Timeframe to stream (default: 1m)")
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parser.add_argument(
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"--duration",
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type=int,
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default=120,
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help="How long to keep the stream hot (seconds, default: 120)",
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)
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parser.add_argument(
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"--flush-interval",
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type=int,
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default=30,
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help="How often to flush to parquet during the run (seconds, default: 30)",
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)
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return parser.parse_args()
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async def _maybe_consume(queue: asyncio.Queue) -> None:
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"""Continuously drain the queue so it doesn't grow unbounded."""
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try:
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while True:
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item = await queue.get()
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if item is None:
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break
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except asyncio.CancelledError:
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pass
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async def _prime_store(symbol: str, timeframe: str, duration: int, flush_interval: int) -> Tuple[int, Path]:
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symbol = symbol.upper().replace("/", "")
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timeframe = timeframe.lower()
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os.makedirs(live_store.root, exist_ok=True)
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target_dir = Path(live_store.root) / symbol / timeframe
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target_dir.mkdir(parents=True, exist_ok=True)
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queue, unsubscribe = await data_provider.subscribe(symbol, timeframe=timeframe)
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consumer_task = asyncio.create_task(_maybe_consume(queue))
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try:
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loop = asyncio.get_running_loop()
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start = loop.time()
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next_flush = flush_interval
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while True:
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elapsed = loop.time() - start
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if elapsed >= duration:
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break
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sleep_for = max(0.0, min(next_flush - elapsed, 1.0))
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await asyncio.sleep(sleep_for)
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elapsed = loop.time() - start
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if elapsed + 1e-6 >= next_flush:
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await live_store.flush_parquet()
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next_flush += flush_interval
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finally:
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await unsubscribe()
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consumer_task.cancel()
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with contextlib.suppress(Exception):
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await consumer_task
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await live_store.flush_parquet()
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history = live_store.get_history(symbol, timeframe)
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return len(history), target_dir
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async def _async_main() -> None:
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args = _parse_args()
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bars, target_dir = await _prime_store(
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symbol=args.symbol,
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timeframe=args.timeframe,
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duration=args.duration,
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flush_interval=args.flush_interval,
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)
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partitions = sorted(target_dir.glob("date=*"))
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total_files = sum(len(list(part.glob("*.parquet"))) for part in partitions)
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latest_partition = partitions[-1] if partitions else None
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print("\nLiveStore setup complete:")
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print(f" Symbol: {args.symbol.upper().replace('/', '')}")
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print(f" Timeframe: {args.timeframe}")
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print(f" Bars in memory: {bars}")
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print(f" Root directory: {target_dir}")
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print(f" Partitions found: {len(partitions)}")
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print(f" Parquet files: {total_files}")
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if latest_partition:
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print(f" Latest partition: {latest_partition}")
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def main() -> None:
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asyncio.run(_async_main())
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if __name__ == "__main__":
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main()
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