Two issues caused the agent to get stuck after the last log message
from a completed scanner (e.g. "✓ reddit_trending: 11 candidates"):
1. `as_completed()` had no global timeout. If a scanner thread blocked
in a non-interruptible I/O call, `as_completed()` waited forever
because it only yields a future once it has finished — the per-future
`future.result(timeout=N)` call was never even reached.
Fixed by passing `timeout=global_timeout` to `as_completed()` so
the outer iterator raises TimeoutError after a capped wall-clock
budget, then logs which scanners didn't complete and continues.
2. `SectorRotationScanner` called `get_ticker_info()` (one HTTP request
per ticker) in a serial loop for up to 100 tickers from a 592-ticker
file, easily exceeding the 30 s per-scanner budget.
Fixed by batch-downloading close prices for all tickers in a single
`download_history()` call, computing 5-day returns locally, and only
calling `get_ticker_info()` for the small subset of laggard tickers
(<2% 5d move) that actually need a sector label.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add ML signal scanner results table logging
- Add log_prompts_console config flag for prompt visibility control
- Expand ranker investment thesis to 4-6 sentence structured reasoning
- Linter auto-formatting across modified files
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Major additions:
- ML win probability scanner: scans ticker universe using trained
LightGBM/TabPFN model, surfaces candidates with P(WIN) above threshold
- 30-feature engineering pipeline (20 base + 10 interaction features)
computed from OHLCV data via stockstats + pandas
- Triple-barrier labeling for training data generation
- Dataset builder and training script with calibration analysis
- Discovery enrichment: confluence scoring, short interest extraction,
earnings estimates, options signal normalization, quant pre-score
- Configurable prompt logging (log_prompts_console flag)
- Enhanced ranker investment thesis (4-6 sentence reasoning)
- Typed DiscoveryConfig dataclass for all discovery settings
- Console price charts for visual ticker analysis
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Final fix for scanner registration issue. Previous attempts
to add scanner import at module level were removed by the
pre-commit hook's ruff --fix auto-formatter.
Solution:
- Import scanners inside DiscoveryGraph.__init__() method
- Use the import (assign to _) so it's not "unused"
- Linter won't remove imports that are actually used
This ensures scanners always load when DiscoveryGraph is instantiated.
Verified: 8 scanners now properly registered
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
The scanner import needs # noqa: F401 to prevent linters from
removing it as "unused". The import is required for side effects
(triggering scanner registration).
Without this:
- Pre-commit hook removes the import
- Scanners don't register
- Discovery returns 0 candidates
Fix:
- Added # noqa: F401 comment to scanner import
- Linter will now preserve this import
- Verified 8 scanners properly registered
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Critical bugfix: Scanner modules weren't being imported, causing
SCANNER_REGISTRY to remain empty and discovery to return 0 candidates.
Root Cause:
- Import line "from tradingagents.dataflows.discovery import scanners"
was accidentally removed during concurrent execution refactoring
- Without this import, scanner @register() decorators never execute
- Result: SCANNER_REGISTRY.get_all_scanners() returns empty list
Fix:
- Restored scanner import in discovery_graph.py line 6
- Scanners now properly register on module import
- Verified 8 scanners now registered and working
Impact:
- Before: 0 candidates, 0 recommendations
- After: 60-70 candidates, 15 recommendations (normal operation)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Youssef Aitousarrah