In dataflow API wrappers, generic `except Exception` handlers were swallowing
timeout exceptions (like `requests.exceptions.Timeout` and `ThirdPartyTimeoutError`),
preventing upstream retry logic and proper error handling from functioning correctly.
This patch:
- Adds explicit catching of `requests.exceptions.Timeout` to raise as `ThirdPartyTimeoutError` in `yfinance` wrapper modules (`y_finance.py`, `yfinance_news.py`, `yfinance_scanner.py`).
- Adds explicit catching and re-raising of `ThirdPartyTimeoutError` before generic exception handlers across the dataflows.
- Retains existing exception inheritance logic to avoid backward compatibility breaks.
- Updates `TestEnsureIndexesInInit` to use the explicit `ensure_indexes()` call per lazy loading changes.
Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* Initial plan
* Improve Industry Deep Dive quality: enrich tool data, explicit sector keys, tool-call nudge
- Enrich get_industry_performance_yfinance with 1-day/1-week/1-month price returns
via batched yf.download() for top 10 tickers (Step 1)
- Add VALID_SECTOR_KEYS, _DISPLAY_TO_KEY, _extract_top_sectors() to industry_deep_dive.py
to pre-extract top sectors from Phase 1 report and inject them into the prompt (Step 2)
- Add tool-call nudge to run_tool_loop: if first LLM response has no tool calls and is
under 500 chars, re-prompt with explicit instruction to call tools (Step 3)
- Update scanner_tools.py get_industry_performance docstring to list all valid sector keys (Step 4)
- Add 15 unit tests covering _extract_top_sectors, tool_runner nudge, and enriched output (Step 5)
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* Address code review: move cols[3] access into try block for IndexError safety
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
* fix: align display row count with download count in get_industry_performance_yfinance
The enriched function downloads price data for top 10 tickers but displayed
20 rows, causing rows 11-20 to show N/A in all price columns. This broke
test_industry_perf_falls_back_to_yfinance which asserts N/A count < 5.
Now both download and display use head(10) for consistency.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: aguzererler <6199053+aguzererler@users.noreply.github.com>
Co-authored-by: Ahmet Guzererler <guzererler@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
The scanner pipeline now runs end-to-end: Phase 1 (geopolitical, market
movers, sector scanners in parallel via Ollama), Phase 2 (industry deep
dive), Phase 3 (macro synthesis via OpenRouter/DeepSeek R1).
Key changes:
- Add tool_runner.py with run_tool_loop() for inline tool execution in
scanner agents (scanner graph has no ToolNode, unlike trading graph)
- Fix vendor fallback: catch AlphaVantageError base class, raise on
total failure instead of embedding errors in return values
- Rewrite yfinance sector perf to use SPDR ETF proxies (Sector.overview
has no performance data)
- Fix Ollama remote host support in openai_client.py
- Add LangGraph state reducers for parallel fan-out writes
- Add --date CLI flag for non-interactive scanner invocation
- Fix .env loading to find keys from both CWD and project root
- Add hybrid LLM config (per-tier provider/backend_url)
- Add project tracking: DECISIONS.md, PROGRESS.md, MISTAKES.md
- Add 9 new test files covering exceptions, fallback, and routing
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Created new files for industry performance, market indices, market movers, sector performance, and topic news.
- Implemented end-to-end tests for scanner functionality, ensuring all tools return expected data formats and can save results to files.
- Added integration tests to verify scanner tools work seamlessly with the CLI scan command.
- Enhanced test coverage for individual scanner tools, validating output structure and content.
## Summary
The changes refactor the scanner tool invocation to use LangChain's StructuredTool `.invoke()` method consistently across the codebase. This includes updating the CLI scan command, rewriting tests to use the new invocation pattern, and correcting yfinance screener key mappings. The changes also add comprehensive end-to-end test suites for scanner functionality.
## Issues Found
| Severity | File:Line | Issue |
|----------|-----------|-------|
| WARNING | cli/main.py:1193-1218 | Inconsistent error handling - some tools check for "Error" prefix while others check for "No data" prefix, but the actual error messages from yfinance_scanner.py use different formats |
| WARNING | tradingagents/dataflows/yfinance_scanner.py:34 | The condition `if not data or 'quotes' not in data:` may not catch all error cases - yfinance screener can return empty data structures that evaluate to False but don't contain 'quotes' key |
| SUGGESTION | tests/test_scanner_tools.py:38-46 | Test could be more robust by checking for actual data content rather than just headers |
| SUGGESTION | cli/main.py:1193-1218 | Consider extracting the scanner tool invocation pattern into a helper function to reduce duplication |
## Detailed Findings
### File: cli/main.py:1193-1218
- **Confidence:** 85%
- **Problem:** The error handling checks for different prefixes ("Error" vs "No data") but the actual functions in yfinance_scanner.py return error messages with different formats (e.g., "Error fetching market movers for..."). This inconsistency could lead to improper error handling where error results are still saved to files.
- **Suggestion:** Standardize error checking by creating a helper function that checks if a result indicates an error, or modify the yfinance_scanner functions to return consistent error prefixes.
### File: tradingagents/dataflows/yfinance_scanner.py:34
- **Confidence:** 80%
- **Problem:** The condition `if not data or 'quotes' not in data:` assumes that if data exists, it will contain a 'quotes' key. However, yfinance screener might return data in different formats or empty objects that don't contain this key, leading to potential KeyError exceptions.
- **Suggestion:** Add more robust checking: `if not data or not isinstance(data, dict) or 'quotes' not in data:` to prevent attribute errors.
### File: tests/test_scanner_tools.py:38-46
- **Confidence:** 75%
- **Problem:** The test for market movers only checks that the result contains the expected header but doesn't verify that actual financial data is present in the table rows.
- **Suggestion:** Enhance the test to verify that data rows are present (e.g., check for table rows with actual data, not just headers).
### File: cli/main.py:1193-1218
- **Confidence:** 70%
- **Problem:** The scanner tool invocation pattern is repeated 5 times with only minor variations in arguments, violating the DRY principle.
- **Suggestion:** Extract this pattern into a helper function like `invoke_scanner_tool(tool, args, filename)` to reduce code duplication and improve maintainability.
## Recommendation
**APPROVE WITH SUGGESTIONS**
The changes are fundamentally sound and improve code consistency by standardizing on the StructuredTool `.invoke()` interface. The added test coverage is excellent. Addressing the minor issues noted above would further improve robustness and maintainability.
- Added market-wide analysis capabilities (movers, indices, sectors, industries, topic news)
- Implemented yfinance and Alpha Vantage data fetching modules
- Added LangChain tools for scanner functions
- Created scanner state definitions and graph components
- Integrated scan command into CLI
- Added configuration for scanner_data vendor routing
- Included test files for scanner components
This implements a new feature for global macro scanning to identify market-wide trends and opportunities.
ahmet guzererler
Copilot