- Created comprehensive E2E test in tests/e2e/test_full_simulation_workflow.py
- Tests new trading_days schema with manually populated data
- Verifies database helper methods work correctly
- Tests Results API structure and filtering
- Validates holdings chain across multiple days
- Checks daily P&L calculation and storage
- Verifies reasoning summary/full retrieval
- Fixed database index creation for backward compatibility with old schema
- Added migration script for cleaning old positions table
- Test uses dependency override to ensure API uses correct database
NOTE: Test does not run full simulation since model_day_executor
has not yet been migrated to new schema. Instead directly populates
trading_days table and validates API layer works correctly.
Test verifies Task 9 requirements from implementation plan.
Add comprehensive suite of testing scripts for different workflows:
- test.sh: Interactive menu for all testing operations
- quick_test.sh: Fast unit test feedback (~10-30s)
- run_tests.sh: Main test runner with full configuration options
- coverage_report.sh: Coverage analysis with HTML/JSON/terminal reports
- ci_test.sh: CI/CD optimized testing with JUnit/coverage XML output
Features:
- Colored terminal output with clear error messages
- Consistent option flags across all scripts
- Support for test markers (unit, integration, e2e, slow, etc.)
- Parallel execution support
- Coverage thresholds (default: 85%)
- Virtual environment and dependency checks
Documentation:
- Update CLAUDE.md with testing section and examples
- Expand docs/developer/testing.md with comprehensive guide
- Add scripts/README.md with quick reference
All scripts are tested and executable. This standardizes the testing
process for local development, CI/CD, and pull request workflows.
Update all shell scripts to use the new AI-Trader-Server naming throughout.
Changes:
- main.sh: Update comments and echo statements
- entrypoint.sh: Update startup message
- scripts/validate_docker_build.sh: Update title, container name references,
and docker image tag from ai-trader-test to ai-trader-server-test
- scripts/test_api_endpoints.sh: Update title and docker-compose command
Part of Phase 4: Internal Configuration & Metadata (Task 19)
Phase 2 progress - API integration complete.
API Changes:
- Replace date_range (List[str]) with start_date/end_date (str)
- Add automatic end_date defaulting to start_date for single day
- Add date format validation
- Integrate PriceDataManager for on-demand downloads
- Add rate limit handling (trusts provider, no pre-config)
- Validate date ranges with configurable max days (MAX_SIMULATION_DAYS)
New Modules:
- api/date_utils.py - Date validation and expansion utilities
- scripts/migrate_price_data.py - Migration script for merged.jsonl
API Flow:
1. Validate date range (start <= end, max 30 days, not future)
2. Check missing price data coverage
3. Download missing data if AUTO_DOWNLOAD_PRICE_DATA=true
4. Priority-based download (maximize date completion)
5. Create job with available trading dates
6. Graceful handling of partial data (rate limits)
Configuration:
- AUTO_DOWNLOAD_PRICE_DATA (default: true)
- MAX_SIMULATION_DAYS (default: 30)
- No rate limit configuration needed
Still TODO:
- Update tools/price_tools.py to read from database
- Implement simulation run tracking
- Update .env.example
- Comprehensive testing
- Documentation updates
Breaking Changes:
- API request format changed (date_range -> start_date/end_date)
- This completes v0.3.0 preparation
- Read API_PORT from .env file if it exists
- Construct API_BASE_URL using configured port
- Display which URL is being tested
- Consistent with validate_docker_build.sh behavior
- Read API_PORT from .env file if it exists
- Use configured port instead of hardcoded 8080
- Display which port is being tested
- Fixes validation when API_PORT is customized
- Add retry logic (up to 15 attempts over 30 seconds)
- Add comprehensive diagnostics on failure
- Test endpoint from inside container to isolate networking issues
- Show recent logs if health check fails
- Better error messages for troubleshooting
Removes dual-mode deployment complexity, focusing on REST API service only.
Changes:
- Removed batch mode from docker-compose.yml (now single ai-trader service)
- Deleted scripts/test_batch_mode.sh validation script
- Renamed entrypoint-api.sh to entrypoint.sh (now default)
- Simplified Dockerfile (single entrypoint, removed CMD)
- Updated validation scripts to use 'ai-trader' service name
- Updated documentation (README.md, TESTING_GUIDE.md, CHANGELOG.md)
Benefits:
- Eliminates port conflicts between batch and API services
- Simpler configuration and deployment
- API-first architecture aligned with Windmill integration
- Reduced maintenance complexity
Breaking Changes:
- Batch mode no longer available
- All simulations must use REST API endpoints
