gavindiaz/NexQuant
1
0
Fork 0
mirror of https://github.com/NicolasBohn/NexQuant.git synced 2026-08-04 18:57:44 +00:00
Code Issues Packages Projects Releases Wiki Activity

fix: resolve dead code, shell injection risk, mutable defaults, and other bugs

Browse Source 
- strategy_orchestrator.py: remove unreachable dead 'if not factor_values' after early return
- strategy_orchestrator.py: eliminate duplicate OHLVC load in evaluate_strategy
- env.py: escape single-quotes in Docker entry to prevent shell injection (CWE-78)
- env.py: replace mutable default args with None pattern in DockerEnv subclasses
- factor_runner.py: move pandarallel.initialize() from import-time to lazy init
This commit is contained in:
TPTBusiness
2026-05-02 23:21:38 +02:00
parent 20428f7d91
commit 15084f593c
3 changed files with 156 additions and 167 deletions
Download Patch File Download Diff File Expand all files Collapse all files
rdagent/components/coder/strategy_orchestrator.py
+12 -16
View File
@@ -749,18 +749,15 @@ signal = signal.rolling(window=3, min_periods=1).mean().round().astype(int)
}
# Align factor values with common index
if not factor_values:
df_factors = pd.DataFrame()
else:
# Find common index across all series
common_idx = None
for name, s in factor_values.items():
if common_idx is None:
common_idx = s.index
else:
common_idx = common_idx.intersection(s.index)
# Find common index across all series
common_idx = None
for name, s in factor_values.items():
if common_idx is None:
common_idx = s.index
else:
common_idx = common_idx.intersection(s.index)
if common_idx is not None and len(common_idx) > 100:
if common_idx is not None and len(common_idx) > 100:
df_factors = pd.DataFrame({
name: s.reindex(common_idx) for name, s in factor_values.items()
}).dropna()
@@ -826,16 +823,15 @@ signal = signal.rolling(window=3, min_periods=1).mean().round().astype(int)
"factors_used": factor_names,
}
if "signal" not in local_vars:
signal = local_vars.get("signal")
if signal is None or (isinstance(signal, pd.Series) and signal.empty):
return {
"strategy_name": strategy_name,
"status": "rejected",
"reason": "Strategy did not produce 'signal' variable",
"reason": "Strategy did not produce valid 'signal' variable",
"factors_used": factor_names,
}
signal = local_vars["signal"]
logger.info(
f"[DEBUG] {strategy_name}: signal stats: "
f"len={len(signal)}, "
@@ -852,7 +848,7 @@ signal = signal.rolling(window=3, min_periods=1).mean().round().astype(int)
backtest_signal_ftmo,
)
close = self.load_ohlcv_close()
# Reuse the already-loaded close from above; create a synthetic proxy if unavailable
if close is None:
logger.warning("OHLCV data unavailable, using factor-mean proxy")
proxy = df_factors.mean(axis=1).astype(float)