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ci: fix lint baseline and stabilize failing main tests
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agentson
2026-03-01 20:17:13 +09:00
parent 6f047a6daf
commit 5730f0db2a
64 changed files with 1041 additions and 1380 deletions
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52
src/evolution/optimizer.py
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@@ -80,26 +80,26 @@ class EvolutionOptimizer:
# Convert to dict format for analysis
failures = []
for decision in losing_decisions:
failures.append({
"decision_id": decision.decision_id,
"timestamp": decision.timestamp,
"stock_code": decision.stock_code,
"market": decision.market,
"exchange_code": decision.exchange_code,
"action": decision.action,
"confidence": decision.confidence,
"rationale": decision.rationale,
"outcome_pnl": decision.outcome_pnl,
"outcome_accuracy": decision.outcome_accuracy,
"context_snapshot": decision.context_snapshot,
"input_data": decision.input_data,
})
failures.append(
{
"decision_id": decision.decision_id,
"timestamp": decision.timestamp,
"stock_code": decision.stock_code,
"market": decision.market,
"exchange_code": decision.exchange_code,
"action": decision.action,
"confidence": decision.confidence,
"rationale": decision.rationale,
"outcome_pnl": decision.outcome_pnl,
"outcome_accuracy": decision.outcome_accuracy,
"context_snapshot": decision.context_snapshot,
"input_data": decision.input_data,
}
)
return failures
def identify_failure_patterns(
self, failures: list[dict[str, Any]]
) -> dict[str, Any]:
def identify_failure_patterns(self, failures: list[dict[str, Any]]) -> dict[str, Any]:
"""Identify patterns in losing decisions.
Analyzes:
@@ -143,12 +143,8 @@ class EvolutionOptimizer:
total_confidence += failure.get("confidence", 0)
total_loss += failure.get("outcome_pnl", 0.0)
patterns["avg_confidence"] = (
round(total_confidence / len(failures), 2) if failures else 0.0
)
patterns["avg_loss"] = (
round(total_loss / len(failures), 2) if failures else 0.0
)
patterns["avg_confidence"] = round(total_confidence / len(failures), 2) if failures else 0.0
patterns["avg_loss"] = round(total_loss / len(failures), 2) if failures else 0.0
# Convert Counters to regular dicts for JSON serialization
patterns["markets"] = dict(patterns["markets"])
@@ -197,7 +193,8 @@ class EvolutionOptimizer:
prompt = (
"You are a quantitative trading strategy developer.\n"
"Analyze these failed trades and their patterns, then generate an improved strategy.\n\n"
"Analyze these failed trades and their patterns, "
"then generate an improved strategy.\n\n"
f"Failure Patterns:\n{json.dumps(patterns, indent=2)}\n\n"
f"Sample Failed Trades (first 5):\n"
f"{json.dumps(failures[:5], indent=2, default=str)}\n\n"
@@ -214,7 +211,8 @@ class EvolutionOptimizer:
try:
response = await self._client.aio.models.generate_content(
model=self._model_name, contents=prompt,
model=self._model_name,
contents=prompt,
)
body = response.text.strip()
except Exception as exc:
@@ -280,9 +278,7 @@ class EvolutionOptimizer:
logger.info("Strategy validation PASSED")
return True
else:
logger.warning(
"Strategy validation FAILED:\n%s", result.stdout + result.stderr
)
logger.warning("Strategy validation FAILED:\n%s", result.stdout + result.stderr)
# Clean up failing strategy
strategy_path.unlink(missing_ok=True)
return False