fix: ticker-based asset_class fallback + backfill migration for NULL rows
- _normalize_asset_class() now accepts ticker param and infers class from a full ticker→class lookup table (energy/metals/agri/indices/equities/forex) - init_db() runs one-time UPDATE to backfill all NULL asset_class rows in trade_entry_prices and skipped_trades using known ticker lists - log_trade_entries and log_skipped_trade pass ticker to normalizer - Frontend _normalizeAssetClass() gets same ticker lookup + pattern fallbacks for =F futures, NSE: prefixed equities, =X currency pairs - All 3 filter calls now pass t.underlying as second argument Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -230,6 +230,28 @@ def init_db():
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except Exception:
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pass
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# One-time migration: fix existing NULL asset_class rows using ticker lookup
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_backfill_cases = [
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("energy", "'CL=F','BZ=F','NG=F','RB=F','HO=F','XLE','XOP','USO','UCO','BOIL','UNG'"),
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("metals", "'GC=F','SI=F','HG=F','PA=F','PL=F','GLD','IAU','SLV','GDX','GDXJ','GLDM','PPLT'"),
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("agriculture", "'ZC=F','ZS=F','ZW=F','CC=F','KC=F','CT=F','OJ=F','CORN','WEAT','SOYB','DBA'"),
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("indices", "'^GSPC','^NDX','^DJI','^RUT','SPY','QQQ','IWM','DIA','RSP','VGK','EEM','EWZ','FXI','EWJ','EFA','ACWI','INDA','^NSEI','^HSI','EWG','EWU','EWI'"),
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("equities", "'XLF','XLK','XLV','XLI','XLP','XLU','XLY','XLRE','XLB','XLC'"),
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("forex", "'DX-Y.NYB','UUP','FXE','FXY','EUO','YCS','FXA','FXB','FXF'"),
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]
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for _cls, _tickers in _backfill_cases:
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try:
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c.execute(
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f"UPDATE trade_entry_prices SET asset_class=? WHERE (asset_class IS NULL OR asset_class='') AND underlying IN ({_tickers})",
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(_cls,)
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)
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c.execute(
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f"UPDATE skipped_trades SET asset_class=? WHERE (asset_class IS NULL OR asset_class='') AND underlying IN ({_tickers})",
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(_cls,)
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)
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except Exception:
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pass
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c.execute("""CREATE TABLE IF NOT EXISTS risk_profiles (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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name TEXT NOT NULL,
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@@ -1027,24 +1049,77 @@ def _normalize_yf_ticker(ticker: str) -> str:
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return t
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def _normalize_asset_class(cls: str) -> str:
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"""Map AI-returned asset_class variants to canonical keys used in the UI."""
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if not cls:
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_TICKER_ASSET_CLASS: dict = {
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# Energy
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"CL=F": "energy", "BZ=F": "energy", "NG=F": "energy", "RB=F": "energy", "HO=F": "energy",
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"XLE": "energy", "XOP": "energy", "USO": "energy", "UCO": "energy", "BOIL": "energy", "UNG": "energy",
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# Metals
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"GC=F": "metals", "SI=F": "metals", "HG=F": "metals", "PA=F": "metals", "PL=F": "metals",
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"GLD": "metals", "IAU": "metals", "SLV": "metals", "GDX": "metals", "GDXJ": "metals",
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"PPLT": "metals", "DBP": "metals", "GLDM": "metals",
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# Agriculture
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"ZC=F": "agriculture", "ZS=F": "agriculture", "ZW=F": "agriculture",
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"CC=F": "agriculture", "KC=F": "agriculture", "CT=F": "agriculture", "OJ=F": "agriculture",
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"CORN": "agriculture", "WEAT": "agriculture", "SOYB": "agriculture", "DBA": "agriculture",
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# Indices
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"^GSPC": "indices", "^NDX": "indices", "^DJI": "indices", "^RUT": "indices",
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"SPY": "indices", "QQQ": "indices", "IWM": "indices", "DIA": "indices", "RSP": "indices",
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"VGK": "indices", "EEM": "indices", "EWZ": "indices", "FXI": "indices",
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"EWJ": "indices", "EFA": "indices", "ACWI": "indices", "INDA": "indices",
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"^NSEI": "indices", "^HSI": "indices", "EWG": "indices", "EWU": "indices", "EWI": "indices",
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# Equities (sector ETFs & individual stocks treated as equities)
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"XLF": "equities", "XLK": "equities", "XLV": "equities", "XLI": "equities",
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"XLP": "equities", "XLU": "equities", "XLY": "equities", "XLRE": "equities",
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"XLB": "equities", "XLC": "equities",
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# Forex
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"DX-Y.NYB": "forex", "UUP": "forex", "FXE": "forex", "FXY": "forex",
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"EUO": "forex", "YCS": "forex", "FXA": "forex", "FXB": "forex", "FXF": "forex",
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}
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def _asset_class_from_ticker(ticker: str) -> str:
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"""Infer asset class from ticker symbol when no explicit class is available."""
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if not ticker:
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return ""
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c = cls.lower().strip()
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if any(k in c for k in ("energy", "oil", "gas", "petrol", "brent", "wti")):
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return "energy"
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if any(k in c for k in ("metal", "gold", "silver", "copper", "mining", "precious")):
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return "metals"
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if any(k in c for k in ("agri", "grain", "corn", "wheat", "soy", "crop", "coton", "coffee", "cocoa")):
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return "agriculture"
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if any(k in c for k in ("index", "indic", "indices", "spx", "nasdaq", "dow", "s&p", "russell", "cac", "dax")):
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return "indices"
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if any(k in c for k in ("equit", "stock", "action", "share", "sector", "xle", "xlf", "xlk")):
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return "equities"
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if any(k in c for k in ("forex", "currency", "fx", "devise", "change", "eur", "usd", "jpy", "dxy")):
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t = ticker.upper().strip()
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if t in _TICKER_ASSET_CLASS:
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return _TICKER_ASSET_CLASS[t]
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# Futures suffix patterns
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if t.endswith("=F"):
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stem = t[:-2]
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if stem[:2] in ("CL", "RB", "HO", "NG", "BZ"):
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return "energy"
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if stem[:2] in ("GC", "SI", "HG", "PA", "PL"):
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return "metals"
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if stem[:2] in ("ZC", "ZS", "ZW", "CC", "KC", "CT"):
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return "agriculture"
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# Currency pairs
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if "=X" in t or "/" in t:
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return "forex"
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return c
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return ""
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def _normalize_asset_class(cls: str, ticker: str = "") -> str:
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"""Map AI-returned asset_class variants to canonical keys, with ticker fallback."""
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if cls:
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c = cls.lower().strip()
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if any(k in c for k in ("energy", "oil", "gas", "petrol", "brent", "wti")):
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return "energy"
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if any(k in c for k in ("metal", "gold", "silver", "copper", "mining", "precious")):
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return "metals"
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if any(k in c for k in ("agri", "grain", "corn", "wheat", "soy", "crop", "coton", "coffee", "cocoa")):
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return "agriculture"
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if any(k in c for k in ("index", "indic", "indices", "spx", "nasdaq", "dow", "s&p", "russell", "cac", "dax")):
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return "indices"
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if any(k in c for k in ("equit", "stock", "action", "share", "sector")):
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return "equities"
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if any(k in c for k in ("forex", "currency", "fx", "devise", "change", "eur", "usd", "jpy", "dxy")):
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return "forex"
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# Already a canonical value
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if c in ("energy", "metals", "agriculture", "indices", "equities", "forex"):
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return c
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# Fallback: infer from ticker
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return _asset_class_from_ticker(ticker)
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def log_trade_entries(run_id: str, scored_patterns: List[Dict[str, Any]], quotes: Dict[str, Any]):
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@@ -1215,7 +1290,8 @@ def log_trade_entries(run_id: str, scored_patterns: List[Dict[str, Any]], quotes
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trade.get("asset_class") or
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sp.get("asset_class") or
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_orig.get("asset_class") or
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""
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"",
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ticker=ticker_key
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)
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conn.execute("""INSERT INTO trade_entry_prices
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(run_id, pattern_id, pattern_name, underlying, strategy,
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@@ -1407,7 +1483,7 @@ def log_skipped_trade(run_id: str, pattern_id: str, pattern_name: str,
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expected_move_pct, skip_reason, skip_detail, asset_class)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
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(run_id, pattern_id, pattern_name, underlying, strategy, score,
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expected_move_pct, skip_reason, skip_detail, _normalize_asset_class(asset_class))
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expected_move_pct, skip_reason, skip_detail, _normalize_asset_class(asset_class, ticker=underlying))
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)
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conn.commit()
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conn.close()
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@@ -240,16 +240,61 @@ function _isBearishStr(strategy: string) {
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}
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// Normalize AI-returned asset_class variants to canonical CATEGORIES keys
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function _normalizeAssetClass(cls: string | null | undefined): string {
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if (!cls) return ''
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const c = cls.toLowerCase().trim()
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if (/energy|oil|gas|petrol|brent|wti/.test(c)) return 'energy'
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if (/metal|gold|silver|copper|mining|precious/.test(c)) return 'metals'
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if (/agri|grain|corn|wheat|soy|crop|coton|coffee|cocoa/.test(c)) return 'agriculture'
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if (/index|indic|indices|spx|nasdaq|dow|s&p|russell|cac|dax/.test(c)) return 'indices'
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if (/equit|stock|action|share|sector|xle|xlf|xlk/.test(c)) return 'equities'
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if (/forex|currency|fx|devise|change|eur|usd|jpy|dxy/.test(c)) return 'forex'
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return c
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const _TICKER_TO_CLASS: Record<string, string> = {
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// Energy
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'CL=F': 'energy', 'BZ=F': 'energy', 'NG=F': 'energy', 'RB=F': 'energy', 'HO=F': 'energy',
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'XLE': 'energy', 'XOP': 'energy', 'USO': 'energy', 'UCO': 'energy', 'BOIL': 'energy', 'UNG': 'energy',
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// Metals
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'GC=F': 'metals', 'SI=F': 'metals', 'HG=F': 'metals', 'PA=F': 'metals', 'PL=F': 'metals',
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'GLD': 'metals', 'IAU': 'metals', 'SLV': 'metals', 'GDX': 'metals', 'GDXJ': 'metals',
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'PPLT': 'metals', 'DBP': 'metals', 'GLDM': 'metals',
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// Agriculture
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'ZC=F': 'agriculture', 'ZS=F': 'agriculture', 'ZW=F': 'agriculture',
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'CC=F': 'agriculture', 'KC=F': 'agriculture', 'CT=F': 'agriculture', 'OJ=F': 'agriculture',
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'CORN': 'agriculture', 'WEAT': 'agriculture', 'SOYB': 'agriculture', 'DBA': 'agriculture',
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// Indices
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'^GSPC': 'indices', '^NDX': 'indices', '^DJI': 'indices', '^RUT': 'indices',
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'SPY': 'indices', 'QQQ': 'indices', 'IWM': 'indices', 'DIA': 'indices', 'RSP': 'indices',
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'VGK': 'indices', 'EEM': 'indices', 'EWZ': 'indices', 'FXI': 'indices',
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'EWJ': 'indices', 'EFA': 'indices', 'ACWI': 'indices', 'INDA': 'indices',
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'^NSEI': 'indices', '^HSI': 'indices', 'EWG': 'indices', 'EWU': 'indices', 'EWI': 'indices',
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// Equities (sector ETFs)
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'XLF': 'equities', 'XLK': 'equities', 'XLV': 'equities', 'XLI': 'equities',
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'XLP': 'equities', 'XLU': 'equities', 'XLY': 'equities', 'XLRE': 'equities',
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'XLB': 'equities', 'XLC': 'equities',
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// Forex
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'DX-Y.NYB': 'forex', 'UUP': 'forex', 'FXE': 'forex', 'FXY': 'forex',
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'EUO': 'forex', 'YCS': 'forex', 'FXA': 'forex', 'FXB': 'forex', 'FXF': 'forex',
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}
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function _normalizeAssetClass(cls: string | null | undefined, ticker?: string | null): string {
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if (cls) {
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const c = cls.toLowerCase().trim()
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if (/energy|oil|gas|petrol|brent|wti/.test(c)) return 'energy'
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if (/metal|gold|silver|copper|mining|precious/.test(c)) return 'metals'
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if (/agri|grain|corn|wheat|soy|crop|coton|coffee|cocoa/.test(c)) return 'agriculture'
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if (/index|indic|indices|spx|nasdaq|dow|s&p|russell|cac|dax/.test(c)) return 'indices'
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if (/equit|stock|action|share|sector/.test(c)) return 'equities'
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if (/forex|currency|fx|devise|change|eur|usd|jpy|dxy/.test(c)) return 'forex'
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if (['energy', 'metals', 'agriculture', 'indices', 'equities', 'forex'].includes(c)) return c
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}
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// Fallback: infer from ticker symbol
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if (ticker) {
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const t = ticker.toUpperCase().trim()
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if (_TICKER_TO_CLASS[t]) return _TICKER_TO_CLASS[t]
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// NSE: or other exchange-prefixed equities
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if (t.includes(':')) return 'equities'
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// Remaining =F futures: crude/energy or precious/metals heuristic
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if (t.endsWith('=F')) {
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const stem = t.slice(0, 2)
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if (['CL', 'RB', 'HO', 'NG', 'BZ'].includes(stem)) return 'energy'
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if (['GC', 'SI', 'HG', 'PA', 'PL'].includes(stem)) return 'metals'
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if (['ZC', 'ZS', 'ZW', 'CC', 'KC', 'CT'].includes(stem)) return 'agriculture'
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}
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// Currency pairs
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if (t.includes('=X') || t.includes('/')) return 'forex'
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}
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return cls?.toLowerCase().trim() ?? ''
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}
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interface FilterBarProps {
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@@ -343,7 +388,7 @@ function ClosedTradesSection({ days }: { days: number }) {
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const trades = allTrades.filter((t: any) => {
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const q = search.toLowerCase()
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if (q && !`${t.underlying} ${t.strategy ?? ''} ${t.pattern_name ?? ''}`.toLowerCase().includes(q)) return false
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if (assetClass !== 'all' && _normalizeAssetClass(t.asset_class) !== assetClass) return false
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if (assetClass !== 'all' && _normalizeAssetClass(t.asset_class, t.underlying) !== assetClass) return false
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const bearish = _isBearishStr(t.strategy ?? '')
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if (direction === 'bullish' && bearish) return false
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if (direction === 'bearish' && !bearish) return false
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@@ -913,7 +958,7 @@ function TradeMtmSection({ days }: { days: number }) {
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if ((t.latest_score ?? t.score_at_entry ?? 0) < minScoreFilter) return false
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const q = search.toLowerCase()
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if (q && !`${t.underlying} ${t.strategy ?? ''} ${t.pattern_name ?? ''}`.toLowerCase().includes(q)) return false
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if (assetClass !== 'all' && _normalizeAssetClass(t.asset_class) !== assetClass) return false
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if (assetClass !== 'all' && _normalizeAssetClass(t.asset_class, t.underlying) !== assetClass) return false
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const bearish = _isBearishStr(t.strategy ?? '')
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if (direction === 'bullish' && bearish) return false
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if (direction === 'bearish' && !bearish) return false
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@@ -1645,7 +1690,7 @@ function SkippedTradesSection({ days }: { days: number }) {
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const trades = allTrades.filter((t: any) => {
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const q = search.toLowerCase()
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if (q && !`${t.underlying} ${t.strategy ?? ''} ${t.pattern_name ?? ''}`.toLowerCase().includes(q)) return false
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if (assetClass !== 'all' && _normalizeAssetClass(t.asset_class) !== assetClass) return false
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if (assetClass !== 'all' && _normalizeAssetClass(t.asset_class, t.underlying) !== assetClass) return false
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if (reasonFilter !== 'all' && t.skip_reason !== reasonFilter) return false
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return true
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})
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