Call _prepare_data before executing trades:
- Download missing data if needed
- Filter completed dates
- Store warnings
- Handle empty date scenarios
Co-Authored-By: Claude <noreply@anthropic.com>
Orchestrate data preparation phase:
- Check missing data
- Download if needed
- Filter completed dates
- Update job status
Co-Authored-By: Claude <noreply@anthropic.com>
Critical fixes identified in code review:
1. Add warnings column migration to _migrate_schema()
- Checks if warnings column exists in jobs table
- Adds column via ALTER TABLE if missing
- Ensures existing databases get new column on upgrade
2. Document CHECK constraint limitation
- Added docstring explaining ALTER TABLE cannot add CHECK constraints
- Notes that "downloading_data" status requires fresh DB or manual migration
3. Add comprehensive migration tests
- test_migration_adds_warnings_column: Verifies warnings column migration
- test_migration_adds_simulation_run_id_column: Tests existing migration
- Both tests include cleanup to prevent cross-test contamination
4. Update test fixtures and expectations
- Updated clean_db fixture to delete from all 9 tables
- Fixed table count assertions (6 -> 9 tables)
- Updated expected columns in schema tests
All 21 database tests now pass.
Add support for:
- downloading_data job status for visibility during data prep
- warnings TEXT column for storing job-level warnings (JSON array)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add FastAPI @app.on_event("startup") handler to display warning
- Previously only appeared when running directly (not via uvicorn)
- Add DEPLOYMENT_MODE and PRESERVE_DEV_DATA to docker-compose.yml
- Update CHANGELOG.md with fix documentation
Fixes issue where dev mode banner wasn't visible in Docker logs
because uvicorn imports app without executing __main__ block.
BREAKING CHANGE: end_date is now required and cannot be null/empty
New Features:
- Resume mode: Set start_date to null to continue from last completed date per model
- Idempotent by default: Skip already-completed dates with replace_existing=false
- Per-model independence: Each model resumes from its own last completed date
- Cold start handling: If no data exists in resume mode, runs only end_date as single day
API Changes:
- start_date: Now optional (null enables resume mode)
- end_date: Now REQUIRED (cannot be null or empty string)
- replace_existing: New optional field (default: false for idempotent behavior)
Implementation:
- Added JobManager.get_last_completed_date_for_model() method
- Added JobManager.get_completed_model_dates() method
- Updated create_job() to support model_day_filter for selective task creation
- Fixed bug with start_date=None in price data checks
Documentation:
- Updated API_REFERENCE.md with complete examples and behavior matrix
- Updated QUICK_START.md with resume mode examples
- Updated docs/user-guide/using-the-api.md
- Added CHANGELOG_NEW_API.md with migration guide
- Updated all integration tests for new schema
- Updated client library examples (Python, TypeScript)
Migration:
- Old: {"start_date": "2025-01-16"}
- New: {"start_date": "2025-01-16", "end_date": "2025-01-16"}
- Resume: {"start_date": null, "end_date": "2025-01-31"}
See CHANGELOG_NEW_API.md for complete details.
Add comprehensive warning display when server starts in development mode
to ensure users are aware of simulated AI calls and data handling.
Changes:
- Add log_dev_mode_startup_warning() function in deployment_config.py
- Display warning on main.py startup when DEPLOYMENT_MODE=DEV
- Display warning on API server startup (api/main.py)
- Warning shows AI simulation status and data persistence behavior
- Provides clear instructions for switching to PROD mode
The warning is highly visible and informs users that:
- AI API calls are simulated (no costs incurred)
- Data may be reset between runs (based on PRESERVE_DEV_DATA)
- System is using isolated dev database and paths
Co-Authored-By: Claude <noreply@anthropic.com>
Add automatic schema migration to handle existing databases that don't
have the simulation_run_id column in the positions table.
Problem:
- v0.3.0-alpha.3 databases lack simulation_run_id column
- CREATE TABLE IF NOT EXISTS doesn't add new columns to existing tables
- Index creation fails with "no such column: simulation_run_id"
Solution:
- Add _migrate_schema() function to detect and migrate old schemas
- Check if positions table exists and inspect its columns
- ALTER TABLE to add simulation_run_id if missing
- Run migration before creating indexes
This allows seamless upgrades from alpha.3 to alpha.4 without manual
database deletion or migration scripts.
Fixes docker compose startup error:
sqlite3.OperationalError: no such column: simulation_run_id
Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Add 64 new tests covering date utilities, price data management, and
on-demand download workflows with 100% coverage for date_utils and 85%
coverage for price_data_manager.
New test files:
- tests/unit/test_date_utils.py (22 tests)
* Date range expansion and validation
* Max simulation days configuration
* Chronological ordering and boundary checks
* 100% coverage of api/date_utils.py
- tests/unit/test_price_data_manager.py (33 tests)
* Initialization and configuration
* Symbol date retrieval and coverage detection
* Priority-based download ordering
* Rate limit and error handling
* Data storage and coverage tracking
* 85% coverage of api/price_data_manager.py
- tests/integration/test_on_demand_downloads.py (10 tests)
* End-to-end download workflows
* Rate limit handling with graceful degradation
* Coverage tracking and gap detection
* Data validation and filtering
Code improvements:
- Add DownloadError exception class for non-rate-limit failures
- Update all ValueError raises to DownloadError for consistency
- Add API key validation at download start
- Improve response validation to check for Meta Data
Test coverage:
- 64 tests passing (54 unit + 10 integration)
- api/date_utils.py: 100% coverage
- api/price_data_manager.py: 85% coverage
- Validates priority-first download strategy
- Confirms graceful rate limit handling
- Verifies database storage and retrieval
Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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
Phase 1 of v0.3.0 date range and on-demand download implementation.
Database changes:
- Add price_data table (OHLCV data, replaces merged.jsonl)
- Add price_data_coverage table (track downloaded date ranges)
- Add simulation_runs table (soft delete support)
- Add simulation_run_id to positions table
- Add comprehensive indexes for new tables
New modules:
- api/price_data_manager.py - Priority-based download manager
- Coverage gap detection
- Smart download prioritization (maximize date completion)
- Rate limit handling with retry logic
- Alpha Vantage integration
Configuration:
- configs/nasdaq100_symbols.json - NASDAQ 100 constituent list
Next steps (not yet implemented):
- Migration script for merged.jsonl -> price_data
- Update API models (start_date/end_date)
- Update tools/price_tools.py to read from database
- Simulation run tracking implementation
- API integration
- Tests and documentation
This is work in progress for the v0.3.0 release.
Makes config_path an internal server detail rather than an API parameter.
Changes:
- Remove config_path from SimulateTriggerRequest
- Add config_path parameter to create_app() with default
- Store in app.state.config_path for internal use
- Update trigger endpoint to use internal config path
- Change missing config error from 400 to 500 (server error)
API calls now only need to specify date_range (and optionally models):
POST /simulate/trigger
{"date_range": ["2025-01-16"]}
The server uses configs/default_config.json by default.
This simplifies the API and hides implementation details from clients.
Changed the API to respect the 'enabled' field in model configurations,
rather than requiring models to be explicitly specified in API requests.
Changes:
- Make 'models' parameter optional in POST /simulate/trigger
- If models not provided, read config and use enabled models
- If models provided, use as explicit override (for testing)
- Raise error if no enabled models found and none specified
- Update response message to show model count
Behavior:
- Default: Only runs models with "enabled": true in config
- Override: Can still specify models in request for manual testing
- Safety: Prevents accidental execution of disabled/expensive models
Example before (required):
POST /simulate/trigger
{"config_path": "...", "date_range": [...], "models": ["gpt-4"]}
Example after (optional):
POST /simulate/trigger
{"config_path": "...", "date_range": [...]}
# Uses models where enabled: true
This makes the config file the source of truth for which models
should run, while still allowing ad-hoc overrides for testing.
