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fix: ticker-based asset_class fallback + backfill migration for NULL rows

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- _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:
OpenSquared
2026-06-20 18:58:25 +02:00
parent 7c0ff703b0
commit 5d3ff19393
2 changed files with 152 additions and 31 deletions
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112
backend/services/database.py
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@@ -230,6 +230,28 @@ def init_db():
except Exception:
pass
# One-time migration: fix existing NULL asset_class rows using ticker lookup
_backfill_cases = [
("energy", "'CL=F','BZ=F','NG=F','RB=F','HO=F','XLE','XOP','USO','UCO','BOIL','UNG'"),
("metals", "'GC=F','SI=F','HG=F','PA=F','PL=F','GLD','IAU','SLV','GDX','GDXJ','GLDM','PPLT'"),
("agriculture", "'ZC=F','ZS=F','ZW=F','CC=F','KC=F','CT=F','OJ=F','CORN','WEAT','SOYB','DBA'"),
("indices", "'^GSPC','^NDX','^DJI','^RUT','SPY','QQQ','IWM','DIA','RSP','VGK','EEM','EWZ','FXI','EWJ','EFA','ACWI','INDA','^NSEI','^HSI','EWG','EWU','EWI'"),
("equities", "'XLF','XLK','XLV','XLI','XLP','XLU','XLY','XLRE','XLB','XLC'"),
("forex", "'DX-Y.NYB','UUP','FXE','FXY','EUO','YCS','FXA','FXB','FXF'"),
]
for _cls, _tickers in _backfill_cases:
try:
c.execute(
f"UPDATE trade_entry_prices SET asset_class=? WHERE (asset_class IS NULL OR asset_class='') AND underlying IN ({_tickers})",
(_cls,)
)
c.execute(
f"UPDATE skipped_trades SET asset_class=? WHERE (asset_class IS NULL OR asset_class='') AND underlying IN ({_tickers})",
(_cls,)
)
except Exception:
pass
c.execute("""CREATE TABLE IF NOT EXISTS risk_profiles (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL,
@@ -1027,24 +1049,77 @@ def _normalize_yf_ticker(ticker: str) -> str:
return t
def _normalize_asset_class(cls: str) -> str:
"""Map AI-returned asset_class variants to canonical keys used in the UI."""
if not cls:
_TICKER_ASSET_CLASS: dict = {
# Energy
"CL=F": "energy", "BZ=F": "energy", "NG=F": "energy", "RB=F": "energy", "HO=F": "energy",
"XLE": "energy", "XOP": "energy", "USO": "energy", "UCO": "energy", "BOIL": "energy", "UNG": "energy",
# Metals
"GC=F": "metals", "SI=F": "metals", "HG=F": "metals", "PA=F": "metals", "PL=F": "metals",
"GLD": "metals", "IAU": "metals", "SLV": "metals", "GDX": "metals", "GDXJ": "metals",
"PPLT": "metals", "DBP": "metals", "GLDM": "metals",
# Agriculture
"ZC=F": "agriculture", "ZS=F": "agriculture", "ZW=F": "agriculture",
"CC=F": "agriculture", "KC=F": "agriculture", "CT=F": "agriculture", "OJ=F": "agriculture",
"CORN": "agriculture", "WEAT": "agriculture", "SOYB": "agriculture", "DBA": "agriculture",
# Indices
"^GSPC": "indices", "^NDX": "indices", "^DJI": "indices", "^RUT": "indices",
"SPY": "indices", "QQQ": "indices", "IWM": "indices", "DIA": "indices", "RSP": "indices",
"VGK": "indices", "EEM": "indices", "EWZ": "indices", "FXI": "indices",
"EWJ": "indices", "EFA": "indices", "ACWI": "indices", "INDA": "indices",
"^NSEI": "indices", "^HSI": "indices", "EWG": "indices", "EWU": "indices", "EWI": "indices",
# Equities (sector ETFs & individual stocks treated as equities)
"XLF": "equities", "XLK": "equities", "XLV": "equities", "XLI": "equities",
"XLP": "equities", "XLU": "equities", "XLY": "equities", "XLRE": "equities",
"XLB": "equities", "XLC": "equities",
# Forex
"DX-Y.NYB": "forex", "UUP": "forex", "FXE": "forex", "FXY": "forex",
"EUO": "forex", "YCS": "forex", "FXA": "forex", "FXB": "forex", "FXF": "forex",
}
def _asset_class_from_ticker(ticker: str) -> str:
"""Infer asset class from ticker symbol when no explicit class is available."""
if not ticker:
return ""
c = cls.lower().strip()
if any(k in c for k in ("energy", "oil", "gas", "petrol", "brent", "wti")):
return "energy"
if any(k in c for k in ("metal", "gold", "silver", "copper", "mining", "precious")):
return "metals"
if any(k in c for k in ("agri", "grain", "corn", "wheat", "soy", "crop", "coton", "coffee", "cocoa")):
return "agriculture"
if any(k in c for k in ("index", "indic", "indices", "spx", "nasdaq", "dow", "s&p", "russell", "cac", "dax")):
return "indices"
if any(k in c for k in ("equit", "stock", "action", "share", "sector", "xle", "xlf", "xlk")):
return "equities"
if any(k in c for k in ("forex", "currency", "fx", "devise", "change", "eur", "usd", "jpy", "dxy")):
t = ticker.upper().strip()
if t in _TICKER_ASSET_CLASS:
return _TICKER_ASSET_CLASS[t]
# Futures suffix patterns
if t.endswith("=F"):
stem = t[:-2]
if stem[:2] in ("CL", "RB", "HO", "NG", "BZ"):
return "energy"
if stem[:2] in ("GC", "SI", "HG", "PA", "PL"):
return "metals"
if stem[:2] in ("ZC", "ZS", "ZW", "CC", "KC", "CT"):
return "agriculture"
# Currency pairs
if "=X" in t or "/" in t:
return "forex"
return c
return ""
def _normalize_asset_class(cls: str, ticker: str = "") -> str:
"""Map AI-returned asset_class variants to canonical keys, with ticker fallback."""
if cls:
c = cls.lower().strip()
if any(k in c for k in ("energy", "oil", "gas", "petrol", "brent", "wti")):
return "energy"
if any(k in c for k in ("metal", "gold", "silver", "copper", "mining", "precious")):
return "metals"
if any(k in c for k in ("agri", "grain", "corn", "wheat", "soy", "crop", "coton", "coffee", "cocoa")):
return "agriculture"
if any(k in c for k in ("index", "indic", "indices", "spx", "nasdaq", "dow", "s&p", "russell", "cac", "dax")):
return "indices"
if any(k in c for k in ("equit", "stock", "action", "share", "sector")):
return "equities"
if any(k in c for k in ("forex", "currency", "fx", "devise", "change", "eur", "usd", "jpy", "dxy")):
return "forex"
# Already a canonical value
if c in ("energy", "metals", "agriculture", "indices", "equities", "forex"):
return c
# Fallback: infer from ticker
return _asset_class_from_ticker(ticker)
def log_trade_entries(run_id: str, scored_patterns: List[Dict[str, Any]], quotes: Dict[str, Any]):
@@ -1215,7 +1290,8 @@ def log_trade_entries(run_id: str, scored_patterns: List[Dict[str, Any]], quotes
trade.get("asset_class") or
sp.get("asset_class") or
_orig.get("asset_class") or
""
"",
ticker=ticker_key
)
conn.execute("""INSERT INTO trade_entry_prices
(run_id, pattern_id, pattern_name, underlying, strategy,
@@ -1407,7 +1483,7 @@ def log_skipped_trade(run_id: str, pattern_id: str, pattern_name: str,
expected_move_pct, skip_reason, skip_detail, asset_class)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
(run_id, pattern_id, pattern_name, underlying, strategy, score,
expected_move_pct, skip_reason, skip_detail, _normalize_asset_class(asset_class))
expected_move_pct, skip_reason, skip_detail, _normalize_asset_class(asset_class, ticker=underlying))
)
conn.commit()
conn.close()