- Add market parameter to aggregate_daily_from_trades() for per-market L6 aggregation
- Store market-scoped keys (total_pnl_KR, win_rate_US, etc.) in L6/L5/L4 layers
- Hook aggregate_daily_from_trades() into market close detection in run()
- Update tests for market-scoped context keys
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add L7_REALTIME writes in trading_cycle() for volatility, price, rsi, volume_ratio
- Normalize key format to {metric}_{market}_{stock_code} across scanner and main
- Fix existing key mismatch between scanner writes and main reads
- Remove unused MarketScanner dead code
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
run_all_aggregations() previously used datetime.now(UTC) for weekly
through annual layers while using the trade date only for daily,
causing data misalignment on backfill. Now all layers consistently
use the latest trade timestamp. Also adds "Z" suffix handling for
fromisoformat() compatibility and strengthens test assertions to
verify L4-L2 layer values end-to-end.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Address PR #110 review findings:
1. High — Realtime mode now loads playbook from DB before calling Gemini,
preventing duplicate API calls on process restart (4/day budget).
2. Medium — Pass market-local date (via market.timezone) to
generate_playbook() and _empty_playbook() instead of date.today().
3. Medium — scan_candidates restructured from {stock_code: candidate}
to {market_code: {stock_code: candidate}} to prevent KR/US symbol
collision.
New test: test_scan_candidates_market_scoped verifies cross-market
isolation.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Remove unused imports (sys, ScenarioMatch, asyncio, StockPlaybook),
fix import ordering, and split long lines for ruff compliance.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace brain.decide() with scenario_engine.evaluate() in trading_cycle
and brain.decide_batch() with per-stock scenario evaluation in
run_daily_session. Initialize PreMarketPlanner, ScenarioEngine, and
PlaybookStore in run(). Add pre-market playbook generation on market
open (1 Gemini call per market per day), market_data enrichment from
scanner metrics (rsi, volume_ratio), portfolio_data for global rules,
scenario match notifications, and playbook lifecycle management.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Review findings addressed:
- Finding 1 (ImportError): false positive — ContextLayer is re-exported from
src.context.store, import works correctly at runtime
- Finding 2 (timezone): generate_playbook() and build_cross_market_context()
now accept optional today parameter for market-local date injection
- Finding 3 (lint): removed unused imports (UTC, datetime, PlaybookStatus),
fixed line-too-long in prompt template
- Tests simplified: replaced date patching with direct today= parameter
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add playbooks table to src/db.py with UNIQUE(date, market) constraint
- PlaybookStore: save/load/delete, status management, match_count tracking,
list_recent with market filter, stats without full deserialization
- DayPlaybook JSON serialization via Pydantic model_dump_json/model_validate_json
- 23 tests, 100% coverage on playbook_store.py
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Addresses second round of PR #102 review:
- _warn_missing_key(): logs each missing key only once per engine instance
to prevent log spam in high-frequency trading loops
- _build_match_details(): uses _safe_float() normalized values instead of
raw market_data to ensure consistent float types in logging/analysis
- Test: verify warning fires exactly once across repeated calls
- Test: verify match_details contains normalized float values
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
ScenarioEngine evaluates pre-defined playbook scenarios against real-time
market data with sub-100ms execution (zero API calls). Supports condition
AND-matching, global portfolio rules, and first-match-wins priority.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Fixed AttributeError exceptions in /status and /positions commands:
- Replaced invalid risk.calculate_pnl() with inline P&L calculation from balance dict
- Changed risk.circuit_breaker_threshold to risk._cb_threshold
- Replaced balance.stocks access with account summary from output2 dict
- Updated tests to match new account summary format
All 27 telegram command tests pass. Live bot testing confirms no errors.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Remove /start command as name doesn't match functionality, and fix
command parsing to handle @botname suffix for group chat compatibility.
Changes:
- Remove handle_start function and registration
- Remove /start from help command list
- Remove test_start_command_content test
- Strip @botname suffix from commands (e.g., /help@mybot → help)
Rationale:
- /start command name implies bot initialization, but it was just
showing help text (duplicate of /help)
- Better to have one clear /help command
- @botname suffix handling needed for group chats
Test:
- 27 tests pass (1 removed, 1 added for @botname handling)
- All existing functionality preserved
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add real-time status and portfolio monitoring via Telegram.
Changes:
- Implement /status handler (mode, markets, P&L, trading state)
- Implement /positions handler (holdings with grouping by market)
- Integrate with Broker API and RiskManager
- Add 5 comprehensive tests for status commands
Features:
- /status: Shows trading mode, enabled markets, pause state, P&L, circuit breaker
- /positions: Lists holdings grouped by market (domestic/overseas)
- Error handling: Graceful degradation on API failures
- Empty state: Handles portfolios with no positions
Integration:
- Uses broker.get_balance() for account data
- Uses risk.calculate_pnl() for P&L calculation
- Accesses pause_trading.is_set() for trading state
- Groups positions by market for better readability
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add pause/resume functionality for remote trading control via Telegram.
Changes:
- Add pause_trading Event to main.py
- Implement /stop handler (pause trading)
- Implement /resume handler (resume trading)
- Integrate pause logic into both daily and realtime trading loops
- Add 4 comprehensive tests for trading control
Features:
- /stop: Pauses all trading operations
- /resume: Resumes trading operations
- Idempotent: Handles repeated stop/resume gracefully
- Status feedback: Informs if already paused/active
- Works in both daily and realtime trading modes
Security:
- Commands verified by TelegramCommandHandler chat_id check
- Only authorized users can control trading
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add TelegramCommandHandler class with long polling, command routing,
and security features.
Changes:
- Add TelegramCommandHandler class to telegram_client.py
- Implement long polling with getUpdates API
- Add command registration and routing mechanism
- Implement chat ID verification for security
- Add comprehensive tests (16 tests)
- Coverage: 85% for telegram_client.py
Features:
- start_polling() / stop_polling() lifecycle management
- register_command() for handler registration
- Chat ID verification to prevent unauthorized access
- Error isolation (command failures don't crash system)
- Graceful handling of API errors and timeouts
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add send_message(text, parse_mode) method that can be used for both
notifications and command responses. Refactor _send_notification to
use the new method.
Changes:
- Add send_message() method with return value for success/failure
- Refactor _send_notification() to call send_message()
- Add comprehensive tests for send_message()
- Coverage: 93% for telegram_client.py
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Root cause analysis revealed 3 critical issues causing EGW00201 errors:
1. **Hash key bypass** - _get_hash_key() made API calls without rate limiting
- Every order made 2 API calls but only 1 was rate-limited
- Fixed by adding rate_limiter.acquire() to _get_hash_key()
2. **Scanner concurrent burst** - scan_market() launched all stocks via asyncio.gather
- All tasks queued simultaneously creating burst pressure
- Fixed by adding Semaphore(1) for fully serialized scanning
3. **RPS too aggressive** - 5.0 RPS exceeded KIS API's real ~2 RPS limit
- Lowered to 2.0 RPS (500ms interval) for maximum safety
Changes:
- src/broker/kis_api.py: Add rate limiter to _get_hash_key()
- src/analysis/scanner.py: Add semaphore-based concurrency control
- New max_concurrent_scans parameter (default 1, fully serialized)
- Wrap scan_stock calls with semaphore in _bounded_scan()
- Remove ineffective asyncio.sleep(0.2) from scan_stock()
- src/config.py: Lower RATE_LIMIT_RPS from 5.0 to 2.0
- tests/test_broker.py: Add 2 tests for hash key rate limiting
- tests/test_volatility.py: Add test for scanner concurrency limit
Results:
- EGW00201 errors: 10 → 0 (100% elimination)
- All 290 tests pass
- 80% code coverage maintained
- Scanner still handles unlimited stocks (just serialized for API safety)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Resolved conflict in src/main.py by using safe_float() from main
instead of float(...or '0') pattern.
Changes:
- src/main.py: Use safe_float() for consistent empty string handling
- All 16 tests pass including test_overseas_price_empty_string
Add safe_float() helper function to safely convert API response values
to float, handling empty strings, None, and invalid values that cause
ValueError: "could not convert string to float: ''".
Changes:
- Add safe_float() function in src/main.py with full docstring
- Replace all float() calls with safe_float() in trading_cycle()
- Domestic market: orderbook prices, balance amounts
- Overseas market: price data, balance info
- Add 6 comprehensive unit tests for safe_float()
The function handles:
- Empty strings ("") → default (0.0)
- None values → default (0.0)
- Invalid strings ("abc") → default (0.0)
- Valid strings ("123.45") → parsed float
- Float inputs (123.45) → pass through
This prevents crashes when KIS API returns empty strings during
market closed hours or data unavailability.
Fixes: #44
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add asyncio.Lock to prevent multiple coroutines from simultaneously
refreshing the KIS access token, which hits the 1-per-minute rate
limit (EGW00133: "접근토큰 발급 잠시 후 다시 시도하세요").
Changes:
- Add self._token_lock in KISBroker.__init__
- Wrap token refresh in async with self._token_lock
- Re-check token validity after acquiring lock (double-check pattern)
- Add concurrent token refresh test (5 parallel requests → 1 API call)
The lock ensures that when multiple coroutines detect an expired token,
only the first one refreshes while others wait and reuse the result.
Fixes: #42
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add type checking for output2 response from get_overseas_balance API.
The API can return either list format [{}] or dict format {}, causing
KeyError when accessing output2[0].
Changes:
- Check isinstance before accessing output2[0]
- Handle list, dict, and empty cases
- Add safe fallback with "or" for empty strings
- Add 3 test cases for list/dict/empty formats
Fixes: #41
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Integrate Telegram notifications throughout the main trading loop to provide
real-time alerts for critical events and trading activities.
Changes:
- Add TelegramClient initialization in run() function
- Send system startup notification on agent start
- Send market open/close notifications when markets change state
- Send trade execution notifications for BUY/SELL orders
- Send fat finger rejection notifications when orders are blocked
- Send circuit breaker notifications when loss threshold is exceeded
- Pass telegram client to trading_cycle() function
- Add tests for all notification scenarios in test_main.py
All notifications wrapped in try/except to ensure trading continues even
if Telegram API fails. Notifications are non-blocking and do not affect
core trading logic.
Test coverage: 273 tests passed, overall coverage 79%
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add objective external data sources to enhance trading decisions beyond
market prices and user input.
## New Modules
### src/data/news_api.py
- News sentiment analysis with Alpha Vantage and NewsAPI support
- Sentiment scoring (-1.0 to +1.0) per article and aggregated
- 5-minute caching to minimize API quota usage
- Graceful degradation when APIs unavailable
### src/data/economic_calendar.py
- Track major economic events (FOMC, GDP, CPI)
- Earnings calendar per stock
- Event proximity checking for high-volatility periods
- Hardcoded major events for 2026 (no API required)
### src/data/market_data.py
- Market sentiment indicators (Fear & Greed equivalent)
- Market breadth (advance/decline ratios)
- Sector performance tracking
- Fear/Greed score calculation
## Integration
Enhanced GeminiClient to seamlessly integrate external data:
- Optional news_api, economic_calendar, and market_data parameters
- Async build_prompt() includes external context when available
- Backward-compatible build_prompt_sync() for existing code
- Graceful fallback when external data unavailable
External data automatically added to AI prompts:
- News sentiment with top articles
- Upcoming high-impact economic events
- Market sentiment and breadth indicators
## Configuration
Added optional settings to config.py:
- NEWS_API_KEY: API key for news provider
- NEWS_API_PROVIDER: "alphavantage" or "newsapi"
- MARKET_DATA_API_KEY: API key for market data
## Testing
Comprehensive test suite with 38 tests:
- NewsAPI caching, sentiment parsing, API integration
- EconomicCalendar event filtering, earnings lookup
- MarketData sentiment and breadth calculations
- GeminiClient integration with external data sources
- All tests use mocks (no real API keys required)
- 81% coverage for src/data module (exceeds 80% requirement)
## Circular Import Fix
Fixed circular dependency between gemini_client.py and cache.py:
- Use TYPE_CHECKING for imports in cache.py
- String annotations for TradeDecision type hints
All 195 existing tests pass. No breaking changes to existing functionality.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Implement comprehensive multi-market trading system with automatic
market selection based on timezone and trading hours.
## New Features
- Market schedule module with 10 global markets (KR, US, JP, HK, CN, VN)
- Overseas broker for KIS API international stock trading
- Automatic market detection based on current time and timezone
- Next market open waiting logic when all markets closed
- ConnectionError retry with exponential backoff (max 3 attempts)
## Architecture Changes
- Market-aware trading cycle with domestic/overseas broker routing
- Market context in AI prompts for better decision making
- Database schema extended with market and exchange_code columns
- Config setting ENABLED_MARKETS for market selection
## Testing
- 19 new tests for market schedule (timezone, DST, lunch breaks)
- All 54 tests passing
- Lint fixes with ruff
## Files Added
- src/markets/schedule.py - Market schedule and timezone logic
- src/broker/overseas.py - KIS overseas stock API client
- tests/test_market_schedule.py - Market schedule test suite
## Files Modified
- src/main.py - Multi-market main loop with retry logic
- src/config.py - ENABLED_MARKETS setting
- src/db.py - market/exchange_code columns with migration
- src/brain/gemini_client.py - Dynamic market context in prompts
Resolves#5
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
