- Apply Black formatting to all test files
- Fix Mock objects to include tool_calls attribute for len() checks
- Add proper __name__ attributes to mock toolkit methods for @tool decorator
- Create mock_toolkit_fix helper for consistent toolkit mocking
All tests should now pass with proper mocking setup.
- Added extended tests for market analyst functionality
- Created tests for signal processing module
- Added tests for propagation module
- Created tests for reflection module
- Added placeholder tests for dataflows utils
- Improved mock fixtures and test utilities
These tests focus on:
- Proper mock usage with __name__ attributes
- Error handling scenarios
- Multiple input variations
- State management
- Memory updates
- Tool call tracking
This should significantly improve test coverage towards the 60% target.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Updated mock_toolkit fixture to create proper mock functions with __name__ attributes
- Fixed TypeError/ValueError issues where Mock objects were passed to tool decorators
- Downgraded numpy to 1.26.4 and pandas to 2.1.4 to resolve import performance issues
- Added test scripts to verify mock fixes are working correctly
The mock functions now properly implement:
- __name__ attribute for tool decorator compatibility
- name attribute for tool name extraction
- Callable interface with proper return values
- Mock tracking capabilities (called, call_count, etc.)
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Changed import from tradingagents.dataflows.interface to tradingagents.dataflows.config
- Updated test patches to use correct import path
- Fixes CI test collection failure
- Added support for running CLI and Ollama server via Docker
- Introduced tests for local embeddings model and standalone Docker setup
- Enabled conditional Ollama server launch via LLM_PROVIDER