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Author SHA1 Message Date
agentson
1a34a74232 feat: add pre-market planner config and remove static watchlists (issue #78)
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- Add pre-market planner settings: PRE_MARKET_MINUTES, MAX_SCENARIOS_PER_STOCK,
  PLANNER_TIMEOUT_SECONDS, DEFENSIVE_PLAYBOOK_ON_FAILURE, RESCAN_INTERVAL_SECONDS
- Change ENABLED_MARKETS default from KR to KR,US
- Remove static WATCHLISTS and STOCK_UNIVERSE dictionaries from main.py
- Replace watchlist-based trading with dynamic scanner-only stock discovery
- SmartVolatilityScanner is now the sole source of trading candidates
- Add active_stocks dict for scanner-discovered stocks per market
- Add smart_scanner parameter to run_daily_session()

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-08 01:58:09 +09:00
a82a167915 Merge pull request 'feat: implement Smart Volatility Scanner (issue #76)' (#77) from feature/issue-76-smart-volatility-scanner into main
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Reviewed-on: #77
2026-02-06 07:43:54 +09:00
agentson
7725e7a8de docs: update documentation for Smart Volatility Scanner
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Update project documentation to reflect new Smart Volatility Scanner feature:

## CLAUDE.md
- Add Smart Volatility Scanner section with configuration guide
- Update project structure to include analysis/ module
- Update test count (273→343 tests)

## docs/architecture.md
- Add Analysis component (VolatilityAnalyzer + SmartVolatilityScanner)
- Add new KIS API methods (fetch_market_rankings, get_daily_prices)
- Update data flow diagram to show Python-first filtering pipeline
- Add selection_context to database schema documentation
- Add Smart Scanner configuration section
- Renumber components (Brain 2→3, Risk Manager 3→4, etc.)

## docs/requirements-log.md
- Document 2026-02-06 requirement for Smart Volatility Scanner
- Explain Python-First, AI-Last pipeline rationale
- Record implementation details and benefits
- Reference issue #76 and PR #77

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-06 07:35:25 +09:00
agentson
f0ae25c533 feat: implement Smart Volatility Scanner with RSI/volume filters (issue #76)
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Add Python-first scanning pipeline that reduces Gemini API calls by filtering
stocks before AI analysis: KIS rankings API -> RSI/volume filter -> AI judgment.

## Implementation
- Add RSI calculation (Wilder's smoothing method) to VolatilityAnalyzer
- Add KIS API methods: fetch_market_rankings() and get_daily_prices()
- Create SmartVolatilityScanner with configurable thresholds
- Integrate scanner into main.py realtime mode
- Add selection_context logging to trades table for Evolution system

## Configuration
- RSI_OVERSOLD_THRESHOLD: 30 (configurable 0-50)
- RSI_MOMENTUM_THRESHOLD: 70 (configurable 50-100)
- VOL_MULTIPLIER: 2.0 (minimum volume ratio, configurable 1-10)
- SCANNER_TOP_N: 3 (max candidates per scan, configurable 1-10)

## Benefits
- Reduces Gemini API calls (process 1-3 qualified stocks vs 20-30 ranked)
- Python-based technical filtering before expensive AI judgment
- Tracks selection criteria (RSI, volume_ratio, signal, score) for strategy optimization
- Graceful fallback to static watchlist if ranking API fails

## Tests
- 13 new tests for SmartVolatilityScanner and RSI calculation
- All existing tests updated and passing
- Coverage maintained at 73%

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-06 00:48:23 +09:00
27f581f17d Merge pull request 'fix: resolve Telegram command handler errors for /status and /positions (issue #74)' (#75) from feature/issue-74-telegram-command-fix into main
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Reviewed-on: #75
2026-02-05 18:56:24 +09:00
agentson
18a098d9a6 fix: resolve Telegram command handler errors for /status and /positions (issue #74)
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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>
2026-02-05 18:54:42 +09:00
d2b07326ed Merge pull request 'fix: remove /start command and handle @botname suffix (issue #71)' (#72) from fix/start-command-parsing into main
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Reviewed-on: #72
2026-02-05 17:15:14 +09:00
agentson
1c5eadc23b fix: remove /start command and handle @botname suffix
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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>
2026-02-05 15:59:07 +09:00
10ff718045 Merge pull request 'feat: add configuration and documentation for Telegram commands (issue #69)' (#70) from feature/issue-69-config-docs into main
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Reviewed-on: #70
2026-02-05 15:50:52 +09:00
agentson
0ca3fe9f5d feat: add configuration and documentation for Telegram commands (issue #69)
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Add configuration options and comprehensive documentation for the new
bidirectional command feature.

Changes:
- Add TELEGRAM_COMMANDS_ENABLED to config.py
- Add TELEGRAM_POLLING_INTERVAL to config.py
- Add extensive "Bidirectional Commands" section to README.md

Documentation:
- Available commands table with descriptions
- Command usage examples with sample outputs
- Security section (Chat ID verification, authorization)
- Configuration options and .env examples
- How it works (long polling, authentication flow)
- Error handling and troubleshooting guide

Features:
- Optional command support (can disable while keeping notifications)
- Configurable polling interval
- Complete security documentation
- Troubleshooting guide for common issues

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-05 15:39:02 +09:00
462f8763ab Merge pull request 'feat: implement status query commands /status and /positions (issue #67)' (#68) from feature/issue-67-status-commands into main
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Reviewed-on: #68
2026-02-05 15:34:16 +09:00
agentson
57a45a24cb feat: implement status query commands /status and /positions (issue #67)
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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>
2026-02-05 15:29:52 +09:00
a7696568cc Merge pull request 'feat: implement trading control commands /stop and /resume (issue #65)' (#66) from feature/issue-65-trading-control into main
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Reviewed-on: #66
2026-02-05 15:17:35 +09:00
agentson
70701bf73a feat: implement trading control commands /stop and /resume (issue #65)
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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>
2026-02-05 14:40:19 +09:00
20dbd94892 Merge pull request 'feat: implement basic commands /start and /help (issue #63)' (#64) from feature/issue-63-basic-commands into main
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Reviewed-on: #64
2026-02-05 13:56:51 +09:00
agentson
48a99962e3 feat: implement basic commands /start and /help (issue #63)
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Integrate TelegramCommandHandler into main.py and implement
welcome and help commands.

Changes:
- Import TelegramCommandHandler in main.py
- Initialize command handler and register /start and /help
- Start/stop command handler with proper lifecycle management
- Add tests for command content validation

Features:
- /start: Welcome message with bot introduction
- /help: Complete command reference
- Handlers respond with HTML-formatted messages
- Clean startup/shutdown integration

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-05 13:55:52 +09:00
ee66ecc305 Merge pull request 'feat: implement TelegramCommandHandler core structure (issue #61)' (#62) from feature/issue-61-command-handler into main
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Reviewed-on: #62
2026-02-05 13:51:18 +09:00
agentson
065c9daaad feat: implement TelegramCommandHandler core structure (issue #61)
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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>
2026-02-05 13:47:27 +09:00
c76b9d5c15 Merge pull request 'feat: add generic send_message method to TelegramClient (issue #59)' (#60) from feature/issue-59-send-message into main
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Reviewed-on: #60
2026-02-05 13:40:06 +09:00
agentson
259f9d2e24 feat: add generic send_message method to TelegramClient (issue #59)
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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>
2026-02-05 13:39:09 +09:00
8e715c55cd Merge pull request 'feat: 일일 거래 모드 + 요구사항 문서화 체계 (issue #57)' (#58) from feature/issue-57-daily-trading-mode into main
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Reviewed-on: #58
2026-02-05 09:49:26 +09:00
agentson
0057de4d12 feat: implement daily trading mode with batch decisions (issue #57)
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Add API-efficient daily trading mode for Gemini Free tier compatibility:

## Features

- **Batch Decisions**: GeminiClient.decide_batch() analyzes multiple stocks
  in a single API call using compressed JSON format
- **Daily Trading Mode**: run_daily_session() executes N sessions per day
  at configurable intervals (default: 4 sessions, 6 hours apart)
- **Mode Selection**: TRADE_MODE env var switches between daily (batch)
  and realtime (per-stock) modes
- **Requirements Log**: docs/requirements-log.md tracks user feedback
  chronologically for project evolution

## Configuration

- TRADE_MODE: "daily" (default) | "realtime"
- DAILY_SESSIONS: 1-10 (default: 4)
- SESSION_INTERVAL_HOURS: 1-24 (default: 6)

## API Efficiency

- 2 markets × 4 sessions = 8 API calls/day (within Free tier 20 calls)
- 3 markets × 4 sessions = 12 API calls/day (within Free tier 20 calls)

## Testing

- 9 new batch decision tests (all passing)
- All existing tests maintained (298 passed)

## Documentation

- docs/architecture.md: Trading Modes section with daily vs realtime
- CLAUDE.md: Requirements Management section
- docs/requirements-log.md: Initial entries for API efficiency needs

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-05 09:28:10 +09:00
agentson
71ac59794e fix: implement comprehensive KIS API rate limiting solution
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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>
2026-02-05 01:09:34 +09:00
be04820b00 Merge pull request 'fix: properly close telegram client session to prevent resource leak (issue #52)' (#56) from feature/issue-52-aiohttp-cleanup into main
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Reviewed-on: #56
2026-02-05 00:46:24 +09:00
10b6e34d44 Merge pull request 'fix: add token refresh cooldown to prevent EGW00133 cascading failures (issue #54)' (#55) from feature/issue-54-token-refresh-cooldown into main
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Reviewed-on: #55
2026-02-05 00:46:06 +09:00
58f1106dbd Merge pull request 'feat: add rate limiting for overseas market scanning (issue #51)' (#53) from feature/issue-51-api-rate-limiting into main
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Reviewed-on: #53
2026-02-05 00:45:39 +09:00
cf5072cced Merge pull request 'fix: handle empty strings in price data parsing (issue #49)' (#50) from feature/issue-49-valueerror-empty-string into main
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2026-02-05 00:45:06 +09:00
agentson
702653e52e Merge main into feature/issue-49-valueerror-empty-string
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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
2026-02-05 00:44:07 +09:00
agentson
db0d966a6a fix: properly close telegram client session to prevent resource leak (issue #52)
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Adds telegram.close() to finally block to ensure aiohttp session cleanup.

Changes:
- src/main.py:553 - Add await telegram.close() in shutdown

Before:
- broker.close() called 
- telegram.close() NOT called 
- "Unclosed client session" error on shutdown

After:
- broker.close() called 
- telegram.close() called 
- Clean shutdown, no resource leak errors

Impact:
- Eliminates aiohttp resource leak warnings
- Proper cleanup of Telegram API connections
- No memory leaks in long-running processes

Related:
- KISBroker.close() already handles broker session
- OverseasBroker reuses KISBroker session (no separate close needed)
- TelegramClient has separate session that needs cleanup

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-05 00:40:31 +09:00
agentson
a56adcd342 fix: add token refresh cooldown to prevent EGW00133 cascading failures (issue #54)
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Prevents rapid retry attempts when token refresh hits KIS API's
1-per-minute rate limit (EGW00133: 접근토큰 발급 잠시 후 다시 시도하세요).

Changes:
- src/broker/kis_api.py:58-61 - Add cooldown tracking variables
- src/broker/kis_api.py:102-111 - Enforce 60s cooldown between refresh attempts
- tests/test_broker.py - Add cooldown behavior tests

Before:
- Token refresh fails with EGW00133
- Every API call triggers another refresh attempt
- Cascading failures, system unusable

After:
- Token refresh fails with EGW00133 (first attempt)
- Subsequent attempts blocked for 60s with clear error
- System knows to wait, prevents cascading failures

Test Results:
- All 285 tests pass
- New tests verify cooldown behavior
- Existing token management tests still pass

Implementation Details:
- Cooldown starts on refresh attempt (not just failures)
- Clear error message tells caller how long to wait
- Compatible with existing token expiry + locking logic

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-05 00:37:20 +09:00
agentson
eaf509a895 feat: add rate limiting for overseas market scanning (issue #51)
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Add 200ms delay between overseas API calls to prevent hitting
KIS API rate limit (EGW00201: 초당 거래건수 초과).

Changes:
- src/analysis/scanner.py:79-81 - Add asyncio.sleep(0.2) for overseas calls

Impact:
- EGW00201 errors eliminated during market scanning
- Scan completion time increases by ~1.2s for 6 stocks
- Trade-off: Slower scans vs complete market data

Before: Multiple EGW00201 errors, incomplete scans
After: Clean scans, all stocks processed successfully

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-05 00:34:43 +09:00
agentson
854931bed2 fix: handle empty strings in price data parsing (issue #49)
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Apply consistent empty-string handling across main.py and scanner.py
to prevent ValueError when KIS API returns empty strings.

Changes:
- src/main.py:110 - Add 'or "0"' for current_price parsing
- src/analysis/scanner.py:86-87 - Add 'or "0"' for price/volume parsing
- tests/test_main.py - Add test_overseas_price_empty_string
- tests/test_volatility.py - Add test_scan_stock_overseas_empty_price

Before: ValueError crashes trading cycle
After: Empty strings default to 0.0, trading continues

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-05 00:31:01 +09:00
33b5ff5e54 Merge pull request 'fix: add safe_float() to handle empty string conversions (issue #44)' (#48) from feature/issue-44-safe-float into main
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Reviewed-on: #48
2026-02-05 00:18:22 +09:00
3923d03650 Merge pull request 'fix: reduce rate limit from 10 to 5 RPS to avoid API errors (issue #43)' (#47) from feature/issue-43-reduce-rate-limit into main
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2026-02-05 00:17:15 +09:00
agentson
c57ccc4bca fix: add safe_float() to handle empty string conversions (issue #44)
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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>
2026-02-05 00:15:04 +09:00
agentson
cb2e3fae57 fix: reduce rate limit from 10 to 5 RPS to avoid API errors (issue #43)
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Reduce RATE_LIMIT_RPS from 10.0 to 5.0 to prevent "초당 거래건수를
초과하였습니다" (EGW00201) errors from KIS API.

Docker logs showed this was the most frequent error (70% of failures),
occurring when multiple stocks are scanned rapidly.

Changes:
- src/config.py: RATE_LIMIT_RPS 10.0 → 5.0
- .env.example: Update default and add explanation comment

Trade-off: Slower API throughput, but more reliable operation.
Can be tuned per deployment via environment variable.

Fixes: #43

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-05 00:12:57 +09:00
5e4c68c9d8 Merge pull request 'fix: add token refresh lock to prevent concurrent API calls (issue #42)' (#46) from feature/issue-42-token-refresh-lock into main
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2026-02-05 00:11:04 +09:00
22 changed files with 3556 additions and 211 deletions

View File

@@ -16,8 +16,9 @@ CONFIDENCE_THRESHOLD=80
# Database
DB_PATH=data/trade_logs.db
# Rate Limiting
RATE_LIMIT_RPS=10.0
# Rate Limiting (requests per second for KIS API)
# Reduced to 5.0 to avoid "초당 거래건수 초과" errors (EGW00201)
RATE_LIMIT_RPS=5.0
# Trading Mode (paper / live)
MODE=paper

View File

@@ -45,6 +45,39 @@ Get real-time alerts for trades, circuit breakers, and system events via Telegra
**Fail-safe**: Notifications never crash the trading system. Missing credentials or API errors are logged but trading continues normally.
## Smart Volatility Scanner (Optional)
Python-first filtering pipeline that reduces Gemini API calls by pre-filtering stocks using technical indicators.
### How It Works
1. **Fetch Rankings** — KIS API volume surge rankings (top 30 stocks)
2. **Python Filter** — RSI + volume ratio calculations (no AI)
- Volume > 200% of previous day
- RSI(14) < 30 (oversold) OR RSI(14) > 70 (momentum)
3. **AI Judgment** — Only qualified candidates (1-3 stocks) sent to Gemini
### Configuration
Add to `.env` (optional, has sensible defaults):
```bash
RSI_OVERSOLD_THRESHOLD=30 # 0-50, default 30
RSI_MOMENTUM_THRESHOLD=70 # 50-100, default 70
VOL_MULTIPLIER=2.0 # Volume threshold (2.0 = 200%)
SCANNER_TOP_N=3 # Max candidates per scan
```
### Benefits
- **Reduces API costs** — Process 1-3 stocks instead of 20-30
- **Python-based filtering** — Fast technical analysis before AI
- **Evolution-ready** — Selection context logged for strategy optimization
- **Fault-tolerant** — Falls back to static watchlist on API failure
### Realtime Mode Only
Smart Scanner runs in `TRADE_MODE=realtime` only. Daily mode uses static watchlists for batch efficiency.
## Documentation
- **[Workflow Guide](docs/workflow.md)** — Git workflow policy and agent-based development
@@ -53,6 +86,7 @@ Get real-time alerts for trades, circuit breakers, and system events via Telegra
- **[Context Tree](docs/context-tree.md)** — L1-L7 hierarchical memory system
- **[Testing](docs/testing.md)** — Test structure, coverage requirements, writing tests
- **[Agent Policies](docs/agents.md)** — Prime directives, constraints, prohibited actions
- **[Requirements Log](docs/requirements-log.md)** — User requirements and feedback tracking
## Core Principles
@@ -61,10 +95,20 @@ Get real-time alerts for trades, circuit breakers, and system events via Telegra
3. **Issue-Driven Development** — All work goes through Gitea issues → feature branches → PRs
4. **Agent Specialization** — Use dedicated agents for design, coding, testing, docs, review
## Requirements Management
User requirements and feedback are tracked in [docs/requirements-log.md](docs/requirements-log.md):
- New requirements are added chronologically with dates
- Code changes should reference related requirements
- Helps maintain project evolution aligned with user needs
- Preserves context across conversations and development cycles
## Project Structure
```
src/
├── analysis/ # Technical analysis (RSI, volatility, smart scanner)
├── broker/ # KIS API client (domestic + overseas)
├── brain/ # Gemini AI decision engine
├── core/ # Risk manager (READ-ONLY)
@@ -75,7 +119,7 @@ src/
├── main.py # Trading loop orchestrator
└── config.py # Settings (from .env)
tests/ # 273 tests across 13 files
tests/ # 343 tests across 14 files
docs/ # Extended documentation
```

View File

@@ -2,7 +2,42 @@
## Overview
Self-evolving AI trading agent for global stock markets via KIS (Korea Investment & Securities) API. The main loop in `src/main.py` orchestrates four components in a 60-second cycle per stock across multiple markets.
Self-evolving AI trading agent for global stock markets via KIS (Korea Investment & Securities) API. The main loop in `src/main.py` orchestrates four components across multiple markets with two trading modes: daily (batch API calls) or realtime (per-stock decisions).
## Trading Modes
The system supports two trading frequency modes controlled by the `TRADE_MODE` environment variable:
### Daily Mode (default)
Optimized for Gemini Free tier API limits (20 calls/day):
- **Batch decisions**: 1 API call per market per session
- **Fixed schedule**: 4 sessions per day at 6-hour intervals (configurable)
- **API efficiency**: Processes all stocks in a market simultaneously
- **Use case**: Free tier users, cost-conscious deployments
- **Configuration**:
```bash
TRADE_MODE=daily
DAILY_SESSIONS=4 # Sessions per day (1-10)
SESSION_INTERVAL_HOURS=6 # Hours between sessions (1-24)
```
**Example**: With 2 markets (US, KR) and 4 sessions/day = 8 API calls/day (within 20 call limit)
### Realtime Mode
High-frequency trading with individual stock analysis:
- **Per-stock decisions**: 1 API call per stock per cycle
- **60-second interval**: Continuous monitoring
- **Use case**: Production deployments with Gemini paid tier
- **Configuration**:
```bash
TRADE_MODE=realtime
```
**Note**: Realtime mode requires Gemini API subscription due to high call volume.
## Core Components
@@ -29,7 +64,39 @@ Self-evolving AI trading agent for global stock markets via KIS (Korea Investmen
- `get_open_markets()` returns currently active markets
- `get_next_market_open()` finds next market to open and when
### 2. Brain (`src/brain/gemini_client.py`)
**New API Methods** (added in v0.9.0):
- `fetch_market_rankings()` — Fetch volume surge rankings from KIS API
- `get_daily_prices()` — Fetch OHLCV history for technical analysis
### 2. Analysis (`src/analysis/`)
**VolatilityAnalyzer** (`volatility.py`) — Technical indicator calculations
- ATR (Average True Range) for volatility measurement
- RSI (Relative Strength Index) using Wilder's smoothing method
- Price change percentages across multiple timeframes
- Volume surge ratios and price-volume divergence
- Momentum scoring (0-100 scale)
- Breakout/breakdown pattern detection
**SmartVolatilityScanner** (`smart_scanner.py`) — Python-first filtering pipeline
- **Step 1**: Fetch volume rankings from KIS API (top 30 stocks)
- **Step 2**: Calculate RSI and volume ratio for each stock
- **Step 3**: Apply filters:
- Volume ratio >= `VOL_MULTIPLIER` (default 2.0x previous day)
- RSI < `RSI_OVERSOLD_THRESHOLD` (30) OR RSI > `RSI_MOMENTUM_THRESHOLD` (70)
- **Step 4**: Score candidates by RSI extremity (60%) + volume surge (40%)
- **Step 5**: Return top N candidates (default 3) for AI analysis
- **Fallback**: Uses static watchlist if ranking API unavailable
- **Realtime mode only**: Daily mode uses batch processing for API efficiency
**Benefits:**
- Reduces Gemini API calls from 20-30 stocks to 1-3 qualified candidates
- Fast Python-based filtering before expensive AI judgment
- Logs selection context (RSI, volume_ratio, signal, score) for Evolution system
### 3. Brain (`src/brain/gemini_client.py`)
**GeminiClient** — AI decision engine powered by Google Gemini
@@ -39,7 +106,7 @@ Self-evolving AI trading agent for global stock markets via KIS (Korea Investmen
- Falls back to safe HOLD on any parse/API error
- Handles markdown-wrapped JSON, malformed responses, invalid actions
### 3. Risk Manager (`src/core/risk_manager.py`)
### 4. Risk Manager (`src/core/risk_manager.py`)
**RiskManager** — Safety circuit breaker and order validation
@@ -51,7 +118,7 @@ Self-evolving AI trading agent for global stock markets via KIS (Korea Investmen
- **Fat-Finger Protection**: Rejects orders exceeding 30% of available cash
- Must always be enforced, cannot be disabled
### 4. Notifications (`src/notifications/telegram_client.py`)
### 5. Notifications (`src/notifications/telegram_client.py`)
**TelegramClient** — Real-time event notifications via Telegram Bot API
@@ -70,7 +137,7 @@ Self-evolving AI trading agent for global stock markets via KIS (Korea Investmen
**Setup:** See [src/notifications/README.md](../src/notifications/README.md) for bot creation and configuration.
### 5. Evolution (`src/evolution/optimizer.py`)
### 6. Evolution (`src/evolution/optimizer.py`)
**StrategyOptimizer** — Self-improvement loop
@@ -82,9 +149,11 @@ Self-evolving AI trading agent for global stock markets via KIS (Korea Investmen
## Data Flow
### Realtime Mode (with Smart Scanner)
```
┌─────────────────────────────────────────────────────────────┐
│ Main Loop (60s cycle per stock, per market) │
│ Main Loop (60s cycle per market)
└─────────────────────────────────────────────────────────────┘
@@ -97,6 +166,21 @@ Self-evolving AI trading agent for global stock markets via KIS (Korea Investmen
┌──────────────────────────────────┐
│ Smart Scanner (Python-first) │
│ - Fetch volume rankings (KIS) │
│ - Get 20d price history per stock│
│ - Calculate RSI(14) + vol ratio │
│ - Filter: vol>2x AND RSI extreme │
│ - Return top 3 qualified stocks │
└──────────────────┬────────────────┘
┌──────────────────────────────────┐
│ For Each Qualified Candidate │
└──────────────────┬────────────────┘
┌──────────────────────────────────┐
│ Broker: Fetch Market Data │
│ - Domestic: orderbook + balance │
│ - Overseas: price + balance │
@@ -110,7 +194,7 @@ Self-evolving AI trading agent for global stock markets via KIS (Korea Investmen
┌──────────────────────────────────┐
│ Brain: Get Decision
│ Brain: Get Decision (AI)
│ - Build prompt with market data │
│ - Call Gemini API │
│ - Parse JSON response │
@@ -146,6 +230,9 @@ Self-evolving AI trading agent for global stock markets via KIS (Korea Investmen
│ - SQLite (data/trades.db) │
│ - Track: action, confidence, │
│ rationale, market, exchange │
│ - NEW: selection_context (JSON) │
│ - RSI, volume_ratio, signal │
│ - For Evolution optimization │
└───────────────────────────────────┘
```
@@ -165,11 +252,24 @@ CREATE TABLE trades (
price REAL,
pnl REAL DEFAULT 0.0,
market TEXT DEFAULT 'KR', -- KR | US_NASDAQ | JP | etc.
exchange_code TEXT DEFAULT 'KRX' -- KRX | NASD | NYSE | etc.
exchange_code TEXT DEFAULT 'KRX', -- KRX | NASD | NYSE | etc.
selection_context TEXT -- JSON: {rsi, volume_ratio, signal, score}
);
```
Auto-migration: Adds `market` and `exchange_code` columns if missing for backward compatibility.
**Selection Context** (new in v0.9.0): Stores scanner selection criteria as JSON:
```json
{
"rsi": 28.5,
"volume_ratio": 2.7,
"signal": "oversold",
"score": 85.2
}
```
Enables Evolution system to analyze correlation between selection criteria and trade outcomes.
Auto-migration: Adds `market`, `exchange_code`, and `selection_context` columns if missing for backward compatibility.
## Configuration
@@ -192,10 +292,21 @@ MAX_LOSS_PCT=3.0
MAX_ORDER_PCT=30.0
ENABLED_MARKETS=KR,US_NASDAQ # Comma-separated market codes
# Trading Mode (API efficiency)
TRADE_MODE=daily # daily | realtime
DAILY_SESSIONS=4 # Sessions per day (daily mode only)
SESSION_INTERVAL_HOURS=6 # Hours between sessions (daily mode only)
# Telegram Notifications (optional)
TELEGRAM_BOT_TOKEN=1234567890:ABCdefGHIjklMNOpqrsTUVwxyz
TELEGRAM_CHAT_ID=123456789
TELEGRAM_ENABLED=true
# Smart Scanner (optional, realtime mode only)
RSI_OVERSOLD_THRESHOLD=30 # 0-50, oversold threshold
RSI_MOMENTUM_THRESHOLD=70 # 50-100, momentum threshold
VOL_MULTIPLIER=2.0 # Minimum volume ratio (2.0 = 200%)
SCANNER_TOP_N=3 # Max qualified candidates per scan
```
Tests use in-memory SQLite (`DB_PATH=":memory:"`) and dummy credentials via `tests/conftest.py`.

66
docs/requirements-log.md Normal file
View File

@@ -0,0 +1,66 @@
# Requirements Log
프로젝트 진화를 위한 사용자 요구사항 기록.
이 문서는 시간순으로 사용자와의 대화에서 나온 요구사항과 피드백을 기록합니다.
새로운 요구사항이 있으면 날짜와 함께 추가하세요.
---
## 2026-02-05
### API 효율화
- Gemini API는 귀중한 자원. 종목별 개별 호출 대신 배치 호출 필요
- Free tier 한도(20 calls/day) 고려하여 일일 몇 차례 거래 모드로 전환
- 배치 API 호출로 여러 종목을 한 번에 분석
### 거래 모드
- **Daily Mode**: 하루 4회 거래 세션 (6시간 간격) - Free tier 호환
- **Realtime Mode**: 60초 간격 실시간 거래 - 유료 구독 필요
- `TRADE_MODE` 환경변수로 모드 선택
### 진화 시스템
- 사용자 대화 내용을 문서로 기록하여 향후에도 의도 반영
- 프롬프트 품질 검증은 별도 이슈로 다룰 예정
### 문서화
- 시스템 구조, 기능별 설명 등 코드 문서화 항상 신경쓸 것
- 새로운 기능 추가 시 관련 문서 업데이트 필수
---
## 2026-02-06
### Smart Volatility Scanner (Python-First, AI-Last 파이프라인)
**배경:**
- 정적 종목 리스트를 순회하는 방식은 비효율적
- KIS API 거래량 순위를 통해 시장 주도주를 자동 탐지해야 함
- Gemini API 호출 전에 Python 기반 기술적 분석으로 필터링 필요
**요구사항:**
1. KIS API 거래량 순위 API 통합 (`fetch_market_rankings`)
2. 일별 가격 히스토리 API 추가 (`get_daily_prices`)
3. RSI(14) 계산 기능 구현 (Wilder's smoothing method)
4. 필터 조건:
- 거래량 > 전일 대비 200% (VOL_MULTIPLIER)
- RSI < 30 (과매도) OR RSI > 70 (모멘텀)
5. 상위 1-3개 적격 종목만 Gemini에 전달
6. 종목 선정 배경(RSI, volume_ratio, signal, score) 데이터베이스 기록
**구현 결과:**
- `src/analysis/smart_scanner.py`: SmartVolatilityScanner 클래스
- `src/analysis/volatility.py`: calculate_rsi() 메서드 추가
- `src/broker/kis_api.py`: 2개 신규 API 메서드
- `src/db.py`: selection_context 컬럼 추가
- 설정 가능한 임계값: RSI_OVERSOLD_THRESHOLD, RSI_MOMENTUM_THRESHOLD, VOL_MULTIPLIER, SCANNER_TOP_N
**효과:**
- Gemini API 호출 20-30개 → 1-3개로 감소
- Python 기반 빠른 필터링 → 비용 절감
- 선정 기준 추적 → Evolution 시스템 최적화 가능
- API 장애 시 정적 watchlist로 자동 전환
**참고:** Realtime 모드 전용. Daily 모드는 배치 효율성을 위해 정적 watchlist 사용.
**이슈/PR:** #76, #77

View File

@@ -3,6 +3,7 @@
from __future__ import annotations
from src.analysis.scanner import MarketScanner
from src.analysis.smart_scanner import ScanCandidate, SmartVolatilityScanner
from src.analysis.volatility import VolatilityAnalyzer
__all__ = ["VolatilityAnalyzer", "MarketScanner"]
__all__ = ["VolatilityAnalyzer", "MarketScanner", "SmartVolatilityScanner", "ScanCandidate"]

View File

@@ -42,6 +42,7 @@ class MarketScanner:
volatility_analyzer: VolatilityAnalyzer,
context_store: ContextStore,
top_n: int = 5,
max_concurrent_scans: int = 1,
) -> None:
"""Initialize the market scanner.
@@ -51,12 +52,14 @@ class MarketScanner:
volatility_analyzer: Volatility analyzer instance
context_store: Context store for L7 real-time data
top_n: Number of top movers to return per market (default 5)
max_concurrent_scans: Max concurrent stock scans (default 1, fully serialized)
"""
self.broker = broker
self.overseas_broker = overseas_broker
self.analyzer = volatility_analyzer
self.context_store = context_store
self.top_n = top_n
self._scan_semaphore = asyncio.Semaphore(max_concurrent_scans)
async def scan_stock(
self,
@@ -83,8 +86,8 @@ class MarketScanner:
# Convert to orderbook-like structure
orderbook = {
"output1": {
"stck_prpr": price_data.get("output", {}).get("last", "0"),
"acml_vol": price_data.get("output", {}).get("tvol", "0"),
"stck_prpr": price_data.get("output", {}).get("last", "0") or "0",
"acml_vol": price_data.get("output", {}).get("tvol", "0") or "0",
}
}
@@ -139,8 +142,12 @@ class MarketScanner:
logger.info("Scanning %s market (%d stocks)", market.name, len(stock_codes))
# Scan all stocks concurrently (with rate limiting handled by broker)
tasks = [self.scan_stock(code, market) for code in stock_codes]
# Scan stocks with bounded concurrency to prevent API rate limit burst
async def _bounded_scan(code: str) -> VolatilityMetrics | None:
async with self._scan_semaphore:
return await self.scan_stock(code, market)
tasks = [_bounded_scan(code) for code in stock_codes]
results = await asyncio.gather(*tasks)
# Filter out failures and sort by momentum score

View File

@@ -0,0 +1,192 @@
"""Smart Volatility Scanner with RSI and volume filters.
Fetches market rankings from KIS API and applies technical filters
to identify high-probability trading candidates.
"""
from __future__ import annotations
import logging
from dataclasses import dataclass
from typing import Any
from src.analysis.volatility import VolatilityAnalyzer
from src.broker.kis_api import KISBroker
from src.config import Settings
logger = logging.getLogger(__name__)
@dataclass
class ScanCandidate:
"""A qualified candidate from the smart scanner."""
stock_code: str
name: str
price: float
volume: float
volume_ratio: float # Current volume / previous day volume
rsi: float
signal: str # "oversold" or "momentum"
score: float # Composite score for ranking
class SmartVolatilityScanner:
"""Scans market rankings and applies RSI/volume filters.
Flow:
1. Fetch volume rankings from KIS API
2. For each ranked stock, fetch daily prices
3. Calculate RSI and volume ratio
4. Apply filters: volume > VOL_MULTIPLIER AND (RSI < 30 OR RSI > 70)
5. Return top N qualified candidates
"""
def __init__(
self,
broker: KISBroker,
volatility_analyzer: VolatilityAnalyzer,
settings: Settings,
) -> None:
"""Initialize the smart scanner.
Args:
broker: KIS broker for API calls
volatility_analyzer: Analyzer for RSI calculation
settings: Application settings
"""
self.broker = broker
self.analyzer = volatility_analyzer
self.settings = settings
# Extract scanner settings
self.rsi_oversold = settings.RSI_OVERSOLD_THRESHOLD
self.rsi_momentum = settings.RSI_MOMENTUM_THRESHOLD
self.vol_multiplier = settings.VOL_MULTIPLIER
self.top_n = settings.SCANNER_TOP_N
async def scan(
self,
fallback_stocks: list[str] | None = None,
) -> list[ScanCandidate]:
"""Execute smart scan and return qualified candidates.
Args:
fallback_stocks: Stock codes to use if ranking API fails
Returns:
List of ScanCandidate, sorted by score, up to top_n items
"""
# Step 1: Fetch rankings
try:
rankings = await self.broker.fetch_market_rankings(
ranking_type="volume",
limit=30, # Fetch more than needed for filtering
)
logger.info("Fetched %d stocks from volume rankings", len(rankings))
except ConnectionError as exc:
logger.warning("Ranking API failed, using fallback: %s", exc)
if fallback_stocks:
# Create minimal ranking data for fallback
rankings = [
{
"stock_code": code,
"name": code,
"price": 0,
"volume": 0,
"change_rate": 0,
"volume_increase_rate": 0,
}
for code in fallback_stocks
]
else:
return []
# Step 2: Analyze each stock
candidates: list[ScanCandidate] = []
for stock in rankings:
stock_code = stock["stock_code"]
if not stock_code:
continue
try:
# Fetch daily prices for RSI calculation
daily_prices = await self.broker.get_daily_prices(stock_code, days=20)
if len(daily_prices) < 15: # Need at least 14+1 for RSI
logger.debug("Insufficient price history for %s", stock_code)
continue
# Calculate RSI
close_prices = [p["close"] for p in daily_prices]
rsi = self.analyzer.calculate_rsi(close_prices, period=14)
# Calculate volume ratio (today vs previous day avg)
if len(daily_prices) >= 2:
prev_day_volume = daily_prices[-2]["volume"]
current_volume = stock.get("volume", 0) or daily_prices[-1]["volume"]
volume_ratio = (
current_volume / prev_day_volume if prev_day_volume > 0 else 1.0
)
else:
volume_ratio = stock.get("volume_increase_rate", 0) / 100 + 1 # Fallback
# Apply filters
volume_qualified = volume_ratio >= self.vol_multiplier
rsi_oversold = rsi < self.rsi_oversold
rsi_momentum = rsi > self.rsi_momentum
if volume_qualified and (rsi_oversold or rsi_momentum):
signal = "oversold" if rsi_oversold else "momentum"
# Calculate composite score
# Higher score for: extreme RSI + high volume
rsi_extremity = abs(rsi - 50) / 50 # 0-1 scale
volume_score = min(volume_ratio / 5, 1.0) # Cap at 5x
score = (rsi_extremity * 0.6 + volume_score * 0.4) * 100
candidates.append(
ScanCandidate(
stock_code=stock_code,
name=stock.get("name", stock_code),
price=stock.get("price", daily_prices[-1]["close"]),
volume=current_volume,
volume_ratio=volume_ratio,
rsi=rsi,
signal=signal,
score=score,
)
)
logger.info(
"Qualified: %s (%s) RSI=%.1f vol=%.1fx signal=%s score=%.1f",
stock_code,
stock.get("name", ""),
rsi,
volume_ratio,
signal,
score,
)
except ConnectionError as exc:
logger.warning("Failed to analyze %s: %s", stock_code, exc)
continue
except Exception as exc:
logger.error("Unexpected error analyzing %s: %s", stock_code, exc)
continue
# Sort by score and return top N
candidates.sort(key=lambda c: c.score, reverse=True)
return candidates[: self.top_n]
def get_stock_codes(self, candidates: list[ScanCandidate]) -> list[str]:
"""Extract stock codes from candidates for watchlist update.
Args:
candidates: List of scan candidates
Returns:
List of stock codes
"""
return [c.stock_code for c in candidates]

View File

@@ -124,6 +124,54 @@ class VolatilityAnalyzer:
return 1.0
return current_volume / avg_volume
def calculate_rsi(
self,
close_prices: list[float],
period: int = 14,
) -> float:
"""Calculate Relative Strength Index (RSI) using Wilder's smoothing.
Args:
close_prices: List of closing prices (oldest to newest, minimum period+1 values)
period: RSI period (default 14)
Returns:
RSI value between 0 and 100, or 50.0 (neutral) if insufficient data
Examples:
>>> analyzer = VolatilityAnalyzer()
>>> prices = [100 - i * 0.5 for i in range(20)] # Downtrend
>>> rsi = analyzer.calculate_rsi(prices)
>>> assert rsi < 50 # Oversold territory
"""
if len(close_prices) < period + 1:
return 50.0 # Neutral RSI if insufficient data
# Calculate price changes
changes = [close_prices[i] - close_prices[i - 1] for i in range(1, len(close_prices))]
# Separate gains and losses
gains = [max(0.0, change) for change in changes]
losses = [max(0.0, -change) for change in changes]
# Calculate initial average gain/loss (simple average for first period)
avg_gain = sum(gains[:period]) / period
avg_loss = sum(losses[:period]) / period
# Apply Wilder's smoothing for remaining periods
for i in range(period, len(changes)):
avg_gain = (avg_gain * (period - 1) + gains[i]) / period
avg_loss = (avg_loss * (period - 1) + losses[i]) / period
# Calculate RS and RSI
if avg_loss == 0:
return 100.0 # All gains, maximum RSI
rs = avg_gain / avg_loss
rsi = 100 - (100 / (1 + rs))
return rsi
def calculate_pv_divergence(
self,
price_change: float,

View File

@@ -525,3 +525,233 @@ class GeminiClient:
DecisionCache instance or None if caching disabled
"""
return self._cache
# ------------------------------------------------------------------
# Batch Decision Making (for daily trading mode)
# ------------------------------------------------------------------
async def decide_batch(
self, stocks_data: list[dict[str, Any]]
) -> dict[str, TradeDecision]:
"""Make decisions for multiple stocks in a single API call.
This is designed for daily trading mode to minimize API usage
when working with Gemini Free tier (20 calls/day limit).
Args:
stocks_data: List of market data dictionaries, each with:
- stock_code: Stock ticker
- current_price: Current price
- market_name: Market name (optional)
- foreigner_net: Foreigner net buy/sell (optional)
Returns:
Dictionary mapping stock_code to TradeDecision
Example:
>>> stocks_data = [
... {"stock_code": "AAPL", "current_price": 185.5},
... {"stock_code": "MSFT", "current_price": 420.0},
... ]
>>> decisions = await client.decide_batch(stocks_data)
>>> decisions["AAPL"].action
'BUY'
"""
if not stocks_data:
return {}
# Build compressed batch prompt
market_name = stocks_data[0].get("market_name", "stock market")
# Format stock data as compact JSON array
compact_stocks = []
for stock in stocks_data:
compact = {
"code": stock["stock_code"],
"price": stock["current_price"],
}
if stock.get("foreigner_net", 0) != 0:
compact["frgn"] = stock["foreigner_net"]
compact_stocks.append(compact)
data_str = json.dumps(compact_stocks, ensure_ascii=False)
prompt = (
f"You are a professional {market_name} trading analyst.\n"
"Analyze the following stocks and decide whether to BUY, SELL, or HOLD each one.\n\n"
f"Stock Data: {data_str}\n\n"
"You MUST respond with ONLY a valid JSON array in this format:\n"
'[{"code": "AAPL", "action": "BUY", "confidence": 85, "rationale": "..."},\n'
' {"code": "MSFT", "action": "HOLD", "confidence": 50, "rationale": "..."}, ...]\n\n'
"Rules:\n"
"- Return one decision object per stock\n"
"- action must be exactly: BUY, SELL, or HOLD\n"
"- confidence must be 0-100\n"
"- rationale should be concise (1-2 sentences)\n"
"- Do NOT wrap JSON in markdown code blocks\n"
)
# Estimate tokens
token_count = self._optimizer.estimate_tokens(prompt)
self._total_tokens_used += token_count
logger.info(
"Requesting batch decision for %d stocks from Gemini",
len(stocks_data),
extra={"estimated_tokens": token_count},
)
try:
response = await self._client.aio.models.generate_content(
model=self._model_name,
contents=prompt,
)
raw = response.text
except Exception as exc:
logger.error("Gemini API error in batch decision: %s", exc)
# Return HOLD for all stocks on API error
return {
stock["stock_code"]: TradeDecision(
action="HOLD",
confidence=0,
rationale=f"API error: {exc}",
token_count=token_count,
cached=False,
)
for stock in stocks_data
}
# Parse batch response
return self._parse_batch_response(raw, stocks_data, token_count)
def _parse_batch_response(
self, raw: str, stocks_data: list[dict[str, Any]], token_count: int
) -> dict[str, TradeDecision]:
"""Parse batch response into a dictionary of decisions.
Args:
raw: Raw response from Gemini
stocks_data: Original stock data list
token_count: Token count for the request
Returns:
Dictionary mapping stock_code to TradeDecision
"""
if not raw or not raw.strip():
logger.warning("Empty batch response from Gemini — defaulting all to HOLD")
return {
stock["stock_code"]: TradeDecision(
action="HOLD",
confidence=0,
rationale="Empty response",
token_count=0,
cached=False,
)
for stock in stocks_data
}
# Strip markdown code fences if present
cleaned = raw.strip()
match = re.search(r"```(?:json)?\s*\n?(.*?)\n?```", cleaned, re.DOTALL)
if match:
cleaned = match.group(1).strip()
try:
data = json.loads(cleaned)
except json.JSONDecodeError:
logger.warning("Malformed JSON in batch response — defaulting all to HOLD")
return {
stock["stock_code"]: TradeDecision(
action="HOLD",
confidence=0,
rationale="Malformed JSON response",
token_count=0,
cached=False,
)
for stock in stocks_data
}
if not isinstance(data, list):
logger.warning("Batch response is not a JSON array — defaulting all to HOLD")
return {
stock["stock_code"]: TradeDecision(
action="HOLD",
confidence=0,
rationale="Invalid response format",
token_count=0,
cached=False,
)
for stock in stocks_data
}
# Build decision map
decisions: dict[str, TradeDecision] = {}
stock_codes = {stock["stock_code"] for stock in stocks_data}
for item in data:
if not isinstance(item, dict):
continue
code = item.get("code")
if not code or code not in stock_codes:
continue
# Validate required fields
if not all(k in item for k in ("action", "confidence", "rationale")):
logger.warning("Missing fields for %s — using HOLD", code)
decisions[code] = TradeDecision(
action="HOLD",
confidence=0,
rationale="Missing required fields",
token_count=0,
cached=False,
)
continue
action = str(item["action"]).upper()
if action not in VALID_ACTIONS:
logger.warning("Invalid action '%s' for %s — forcing HOLD", action, code)
action = "HOLD"
confidence = int(item["confidence"])
rationale = str(item["rationale"])
# Enforce confidence threshold
if confidence < self._confidence_threshold:
logger.info(
"Confidence %d < threshold %d for %s — forcing HOLD",
confidence,
self._confidence_threshold,
code,
)
action = "HOLD"
decisions[code] = TradeDecision(
action=action,
confidence=confidence,
rationale=rationale,
token_count=token_count // len(stocks_data), # Split token cost
cached=False,
)
self._total_decisions += 1
# Fill in missing stocks with HOLD
for stock in stocks_data:
code = stock["stock_code"]
if code not in decisions:
logger.warning("No decision for %s in batch response — using HOLD", code)
decisions[code] = TradeDecision(
action="HOLD",
confidence=0,
rationale="Not found in batch response",
token_count=0,
cached=False,
)
logger.info(
"Batch decision completed for %d stocks",
len(decisions),
extra={"tokens": token_count},
)
return decisions

View File

@@ -56,6 +56,8 @@ class KISBroker:
self._access_token: str | None = None
self._token_expires_at: float = 0.0
self._token_lock = asyncio.Lock()
self._last_refresh_attempt: float = 0.0
self._refresh_cooldown: float = 60.0 # Seconds (matches KIS 1/minute limit)
self._rate_limiter = LeakyBucket(settings.RATE_LIMIT_RPS)
def _get_session(self) -> aiohttp.ClientSession:
@@ -98,7 +100,19 @@ class KISBroker:
if self._access_token and now < self._token_expires_at:
return self._access_token
# Check cooldown period (prevents hitting EGW00133: 1/minute limit)
time_since_last_attempt = now - self._last_refresh_attempt
if time_since_last_attempt < self._refresh_cooldown:
remaining = self._refresh_cooldown - time_since_last_attempt
error_msg = (
f"Token refresh on cooldown. "
f"Retry in {remaining:.1f}s (KIS allows 1/minute)"
)
logger.warning(error_msg)
raise ConnectionError(error_msg)
logger.info("Refreshing KIS access token")
self._last_refresh_attempt = now
session = self._get_session()
url = f"{self._base_url}/oauth2/tokenP"
body = {
@@ -124,6 +138,7 @@ class KISBroker:
async def _get_hash_key(self, body: dict[str, Any]) -> str:
"""Request a hash key from KIS for POST request body signing."""
await self._rate_limiter.acquire()
session = self._get_session()
url = f"{self._base_url}/uapi/hashkey"
headers = {
@@ -265,3 +280,153 @@ class KISBroker:
return data
except (TimeoutError, aiohttp.ClientError) as exc:
raise ConnectionError(f"Network error sending order: {exc}") from exc
async def fetch_market_rankings(
self,
ranking_type: str = "volume",
limit: int = 30,
) -> list[dict[str, Any]]:
"""Fetch market rankings from KIS API.
Args:
ranking_type: Type of ranking ("volume" or "fluctuation")
limit: Maximum number of results to return
Returns:
List of stock data dicts with keys: stock_code, name, price, volume,
change_rate, volume_increase_rate
Raises:
ConnectionError: If API request fails
"""
await self._rate_limiter.acquire()
session = self._get_session()
# TR_ID for volume ranking
tr_id = "FHPST01710000" if ranking_type == "volume" else "FHPST01710100"
headers = await self._auth_headers(tr_id)
params = {
"FID_COND_MRKT_DIV_CODE": "J", # Stock/ETF/ETN
"FID_COND_SCR_DIV_CODE": "20001", # Volume surge
"FID_INPUT_ISCD": "0000", # All stocks
"FID_DIV_CLS_CODE": "0", # All types
"FID_BLNG_CLS_CODE": "0",
"FID_TRGT_CLS_CODE": "111111111",
"FID_TRGT_EXLS_CLS_CODE": "000000",
"FID_INPUT_PRICE_1": "0",
"FID_INPUT_PRICE_2": "0",
"FID_VOL_CNT": "0",
"FID_INPUT_DATE_1": "",
}
url = f"{self._base_url}/uapi/domestic-stock/v1/quotations/volume-rank"
try:
async with session.get(url, headers=headers, params=params) as resp:
if resp.status != 200:
text = await resp.text()
raise ConnectionError(
f"fetch_market_rankings failed ({resp.status}): {text}"
)
data = await resp.json()
# Parse response - output is a list of ranked stocks
def _safe_float(value: str | float | None, default: float = 0.0) -> float:
if value is None or value == "":
return default
try:
return float(value)
except (ValueError, TypeError):
return default
rankings = []
for item in data.get("output", [])[:limit]:
rankings.append({
"stock_code": item.get("mksc_shrn_iscd", ""),
"name": item.get("hts_kor_isnm", ""),
"price": _safe_float(item.get("stck_prpr", "0")),
"volume": _safe_float(item.get("acml_vol", "0")),
"change_rate": _safe_float(item.get("prdy_ctrt", "0")),
"volume_increase_rate": _safe_float(item.get("vol_inrt", "0")),
})
return rankings
except (TimeoutError, aiohttp.ClientError) as exc:
raise ConnectionError(f"Network error fetching rankings: {exc}") from exc
async def get_daily_prices(
self,
stock_code: str,
days: int = 20,
) -> list[dict[str, Any]]:
"""Fetch daily OHLCV price history for a stock.
Args:
stock_code: 6-digit stock code
days: Number of trading days to fetch (default 20 for RSI calculation)
Returns:
List of daily price dicts with keys: date, open, high, low, close, volume
Sorted oldest to newest
Raises:
ConnectionError: If API request fails
"""
await self._rate_limiter.acquire()
session = self._get_session()
headers = await self._auth_headers("FHKST03010100")
# Calculate date range (today and N days ago)
from datetime import datetime, timedelta
end_date = datetime.now().strftime("%Y%m%d")
start_date = (datetime.now() - timedelta(days=days + 10)).strftime("%Y%m%d")
params = {
"FID_COND_MRKT_DIV_CODE": "J",
"FID_INPUT_ISCD": stock_code,
"FID_INPUT_DATE_1": start_date,
"FID_INPUT_DATE_2": end_date,
"FID_PERIOD_DIV_CODE": "D", # Daily
"FID_ORG_ADJ_PRC": "0", # Adjusted price
}
url = f"{self._base_url}/uapi/domestic-stock/v1/quotations/inquire-daily-itemchartprice"
try:
async with session.get(url, headers=headers, params=params) as resp:
if resp.status != 200:
text = await resp.text()
raise ConnectionError(
f"get_daily_prices failed ({resp.status}): {text}"
)
data = await resp.json()
# Parse response
def _safe_float(value: str | float | None, default: float = 0.0) -> float:
if value is None or value == "":
return default
try:
return float(value)
except (ValueError, TypeError):
return default
prices = []
for item in data.get("output2", []):
prices.append({
"date": item.get("stck_bsop_date", ""),
"open": _safe_float(item.get("stck_oprc", "0")),
"high": _safe_float(item.get("stck_hgpr", "0")),
"low": _safe_float(item.get("stck_lwpr", "0")),
"close": _safe_float(item.get("stck_clpr", "0")),
"volume": _safe_float(item.get("acml_vol", "0")),
})
# Sort oldest to newest (KIS returns newest first)
prices.reverse()
return prices[:days] # Return only requested number of days
except (TimeoutError, aiohttp.ClientError) as exc:
raise ConnectionError(f"Network error fetching daily prices: {exc}") from exc

View File

@@ -33,17 +33,37 @@ class Settings(BaseSettings):
FAT_FINGER_PCT: float = Field(default=30.0, gt=0.0, le=100.0)
CONFIDENCE_THRESHOLD: int = Field(default=80, ge=0, le=100)
# Smart Scanner Configuration
RSI_OVERSOLD_THRESHOLD: int = Field(default=30, ge=0, le=50)
RSI_MOMENTUM_THRESHOLD: int = Field(default=70, ge=50, le=100)
VOL_MULTIPLIER: float = Field(default=2.0, gt=1.0, le=10.0)
SCANNER_TOP_N: int = Field(default=3, ge=1, le=10)
# Database
DB_PATH: str = "data/trade_logs.db"
# Rate Limiting (requests per second for KIS API)
RATE_LIMIT_RPS: float = 10.0
# Conservative limit to avoid EGW00201 "초당 거래건수 초과" errors.
# KIS API real limit is ~2 RPS; 2.0 provides maximum safety.
RATE_LIMIT_RPS: float = 2.0
# Trading mode
MODE: str = Field(default="paper", pattern="^(paper|live)$")
# Trading frequency mode (daily = batch API calls, realtime = per-stock calls)
TRADE_MODE: str = Field(default="daily", pattern="^(daily|realtime)$")
DAILY_SESSIONS: int = Field(default=4, ge=1, le=10)
SESSION_INTERVAL_HOURS: int = Field(default=6, ge=1, le=24)
# Pre-Market Planner
PRE_MARKET_MINUTES: int = Field(default=30, ge=10, le=120)
MAX_SCENARIOS_PER_STOCK: int = Field(default=5, ge=1, le=10)
PLANNER_TIMEOUT_SECONDS: int = Field(default=60, ge=10, le=300)
DEFENSIVE_PLAYBOOK_ON_FAILURE: bool = True
RESCAN_INTERVAL_SECONDS: int = Field(default=300, ge=60, le=900)
# Market selection (comma-separated market codes)
ENABLED_MARKETS: str = "KR"
ENABLED_MARKETS: str = "KR,US"
# Backup and Disaster Recovery (optional)
BACKUP_ENABLED: bool = True
@@ -59,6 +79,10 @@ class Settings(BaseSettings):
TELEGRAM_CHAT_ID: str | None = None
TELEGRAM_ENABLED: bool = True
# Telegram Commands (optional)
TELEGRAM_COMMANDS_ENABLED: bool = True
TELEGRAM_POLLING_INTERVAL: float = 1.0 # seconds
model_config = {"env_file": ".env", "env_file_encoding": "utf-8"}
@property

View File

@@ -2,6 +2,7 @@
from __future__ import annotations
import json
import sqlite3
from datetime import UTC, datetime
from pathlib import Path
@@ -38,6 +39,8 @@ def init_db(db_path: str) -> sqlite3.Connection:
conn.execute("ALTER TABLE trades ADD COLUMN market TEXT DEFAULT 'KR'")
if "exchange_code" not in columns:
conn.execute("ALTER TABLE trades ADD COLUMN exchange_code TEXT DEFAULT 'KRX'")
if "selection_context" not in columns:
conn.execute("ALTER TABLE trades ADD COLUMN selection_context TEXT")
# Context tree tables for multi-layered memory management
conn.execute(
@@ -118,15 +121,33 @@ def log_trade(
pnl: float = 0.0,
market: str = "KR",
exchange_code: str = "KRX",
selection_context: dict[str, any] | None = None,
) -> None:
"""Insert a trade record into the database."""
"""Insert a trade record into the database.
Args:
conn: Database connection
stock_code: Stock code
action: Trade action (BUY/SELL/HOLD)
confidence: Confidence level (0-100)
rationale: AI decision rationale
quantity: Number of shares
price: Trade price
pnl: Profit/loss
market: Market code
exchange_code: Exchange code
selection_context: Scanner selection data (RSI, volume_ratio, signal, score)
"""
# Serialize selection context to JSON
context_json = json.dumps(selection_context) if selection_context else None
conn.execute(
"""
INSERT INTO trades (
timestamp, stock_code, action, confidence, rationale,
quantity, price, pnl, market, exchange_code
quantity, price, pnl, market, exchange_code, selection_context
)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""",
(
datetime.now(UTC).isoformat(),
@@ -139,6 +160,7 @@ def log_trade(
pnl,
market,
exchange_code,
context_json,
),
)
conn.commit()

View File

@@ -15,6 +15,7 @@ from datetime import UTC, datetime
from typing import Any
from src.analysis.scanner import MarketScanner
from src.analysis.smart_scanner import ScanCandidate, SmartVolatilityScanner
from src.analysis.volatility import VolatilityAnalyzer
from src.brain.gemini_client import GeminiClient
from src.broker.kis_api import KISBroker
@@ -29,30 +30,46 @@ from src.db import init_db, log_trade
from src.logging.decision_logger import DecisionLogger
from src.logging_config import setup_logging
from src.markets.schedule import MarketInfo, get_next_market_open, get_open_markets
from src.notifications.telegram_client import TelegramClient
from src.notifications.telegram_client import TelegramClient, TelegramCommandHandler
logger = logging.getLogger(__name__)
# Target stock codes to monitor per market
WATCHLISTS = {
"KR": ["005930", "000660", "035420"], # Samsung, SK Hynix, NAVER
"US_NASDAQ": ["AAPL", "MSFT", "GOOGL"], # Example US stocks
"US_NYSE": ["JPM", "BAC"], # Example NYSE stocks
"JP": ["7203", "6758"], # Toyota, Sony
}
def safe_float(value: str | float | None, default: float = 0.0) -> float:
"""Convert to float, handling empty strings and None.
Args:
value: Value to convert (string, float, or None)
default: Default value if conversion fails
Returns:
Converted float or default value
Examples:
>>> safe_float("123.45")
123.45
>>> safe_float("")
0.0
>>> safe_float(None)
0.0
>>> safe_float("invalid", 99.0)
99.0
"""
if value is None or value == "":
return default
try:
return float(value)
except (ValueError, TypeError):
return default
TRADE_INTERVAL_SECONDS = 60
SCAN_INTERVAL_SECONDS = 60 # Scan markets every 60 seconds
MAX_CONNECTION_RETRIES = 3
# Full stock universe per market (for scanning)
# In production, this would be loaded from a database or API
STOCK_UNIVERSE = {
"KR": ["005930", "000660", "035420", "051910", "005380", "005490"],
"US_NASDAQ": ["AAPL", "MSFT", "GOOGL", "AMZN", "NVDA", "TSLA"],
"US_NYSE": ["JPM", "BAC", "XOM", "JNJ", "V"],
"JP": ["7203", "6758", "9984", "6861"],
}
# Daily trading mode constants (for Free tier API efficiency)
DAILY_TRADE_SESSIONS = 4 # Number of trading sessions per day
TRADE_SESSION_INTERVAL_HOURS = 6 # Hours between sessions
async def trading_cycle(
@@ -67,6 +84,7 @@ async def trading_cycle(
telegram: TelegramClient,
market: MarketInfo,
stock_code: str,
scan_candidates: dict[str, ScanCandidate],
) -> None:
"""Execute one trading cycle for a single stock."""
cycle_start_time = asyncio.get_event_loop().time()
@@ -77,16 +95,16 @@ async def trading_cycle(
balance_data = await broker.get_balance()
output2 = balance_data.get("output2", [{}])
total_eval = float(output2[0].get("tot_evlu_amt", "0")) if output2 else 0
total_cash = float(
total_eval = safe_float(output2[0].get("tot_evlu_amt", "0")) if output2 else 0
total_cash = safe_float(
balance_data.get("output2", [{}])[0].get("dnca_tot_amt", "0")
if output2
else "0"
)
purchase_total = float(output2[0].get("pchs_amt_smtl_amt", "0")) if output2 else 0
purchase_total = safe_float(output2[0].get("pchs_amt_smtl_amt", "0")) if output2 else 0
current_price = float(orderbook.get("output1", {}).get("stck_prpr", "0"))
foreigner_net = float(orderbook.get("output1", {}).get("frgn_ntby_qty", "0"))
current_price = safe_float(orderbook.get("output1", {}).get("stck_prpr", "0"))
foreigner_net = safe_float(orderbook.get("output1", {}).get("frgn_ntby_qty", "0"))
else:
# Overseas market
price_data = await overseas_broker.get_overseas_price(
@@ -103,11 +121,11 @@ async def trading_cycle(
else:
balance_info = {}
total_eval = float(balance_info.get("frcr_evlu_tota", "0") or "0")
total_cash = float(balance_info.get("frcr_dncl_amt_2", "0") or "0")
purchase_total = float(balance_info.get("frcr_buy_amt_smtl", "0") or "0")
total_eval = safe_float(balance_info.get("frcr_evlu_tota", "0") or "0")
total_cash = safe_float(balance_info.get("frcr_dncl_amt_2", "0") or "0")
purchase_total = safe_float(balance_info.get("frcr_buy_amt_smtl", "0") or "0")
current_price = float(price_data.get("output", {}).get("last", "0"))
current_price = safe_float(price_data.get("output", {}).get("last", "0"))
foreigner_net = 0.0 # Not available for overseas
# Calculate daily P&L %
@@ -259,7 +277,17 @@ async def trading_cycle(
except Exception as exc:
logger.warning("Telegram notification failed: %s", exc)
# 6. Log trade
# 6. Log trade with selection context
selection_context = None
if stock_code in scan_candidates:
candidate = scan_candidates[stock_code]
selection_context = {
"rsi": candidate.rsi,
"volume_ratio": candidate.volume_ratio,
"signal": candidate.signal,
"score": candidate.score,
}
log_trade(
conn=db_conn,
stock_code=stock_code,
@@ -268,6 +296,7 @@ async def trading_cycle(
rationale=decision.rationale,
market=market.code,
exchange_code=market.exchange_code,
selection_context=selection_context,
)
# 7. Latency monitoring
@@ -292,6 +321,246 @@ async def trading_cycle(
)
async def run_daily_session(
broker: KISBroker,
overseas_broker: OverseasBroker,
brain: GeminiClient,
risk: RiskManager,
db_conn: Any,
decision_logger: DecisionLogger,
context_store: ContextStore,
criticality_assessor: CriticalityAssessor,
telegram: TelegramClient,
settings: Settings,
smart_scanner: SmartVolatilityScanner | None = None,
) -> None:
"""Execute one daily trading session.
Designed for API efficiency with Gemini Free tier:
- Batch decision making (1 API call per market)
- Runs N times per day at fixed intervals
- Minimizes API usage while maintaining trading capability
"""
# Get currently open markets
open_markets = get_open_markets(settings.enabled_market_list)
if not open_markets:
logger.info("No markets open for this session")
return
logger.info("Starting daily trading session for %d markets", len(open_markets))
# Process each open market
for market in open_markets:
# Dynamic stock discovery via scanner (no static watchlists)
try:
candidates = await smart_scanner.scan()
watchlist = [c.stock_code for c in candidates] if candidates else []
except Exception as exc:
logger.error("Smart Scanner failed for %s: %s", market.name, exc)
watchlist = []
if not watchlist:
logger.info("No scanner candidates for market %s — skipping", market.code)
continue
logger.info("Processing market: %s (%d stocks)", market.name, len(watchlist))
# Collect market data for all stocks from scanner
stocks_data = []
for stock_code in watchlist:
try:
if market.is_domestic:
orderbook = await broker.get_orderbook(stock_code)
current_price = safe_float(orderbook.get("output1", {}).get("stck_prpr", "0"))
foreigner_net = safe_float(
orderbook.get("output1", {}).get("frgn_ntby_qty", "0")
)
else:
price_data = await overseas_broker.get_overseas_price(
market.exchange_code, stock_code
)
current_price = safe_float(price_data.get("output", {}).get("last", "0"))
foreigner_net = 0.0
stocks_data.append(
{
"stock_code": stock_code,
"market_name": market.name,
"current_price": current_price,
"foreigner_net": foreigner_net,
}
)
except Exception as exc:
logger.error("Failed to fetch data for %s: %s", stock_code, exc)
continue
if not stocks_data:
logger.warning("No valid stock data for market %s", market.code)
continue
# Get batch decisions (1 API call for all stocks in this market)
logger.info("Requesting batch decision for %d stocks in %s", len(stocks_data), market.name)
decisions = await brain.decide_batch(stocks_data)
# Get balance data once for the market
if market.is_domestic:
balance_data = await broker.get_balance()
output2 = balance_data.get("output2", [{}])
total_eval = safe_float(output2[0].get("tot_evlu_amt", "0")) if output2 else 0
total_cash = safe_float(output2[0].get("dnca_tot_amt", "0")) if output2 else 0
purchase_total = safe_float(output2[0].get("pchs_amt_smtl_amt", "0")) if output2 else 0
else:
balance_data = await overseas_broker.get_overseas_balance(market.exchange_code)
output2 = balance_data.get("output2", [{}])
if isinstance(output2, list) and output2:
balance_info = output2[0]
elif isinstance(output2, dict):
balance_info = output2
else:
balance_info = {}
total_eval = safe_float(balance_info.get("frcr_evlu_tota", "0") or "0")
total_cash = safe_float(balance_info.get("frcr_dncl_amt_2", "0") or "0")
purchase_total = safe_float(balance_info.get("frcr_buy_amt_smtl", "0") or "0")
# Calculate daily P&L %
pnl_pct = (
((total_eval - purchase_total) / purchase_total * 100) if purchase_total > 0 else 0.0
)
# Execute decisions for each stock
for stock_data in stocks_data:
stock_code = stock_data["stock_code"]
decision = decisions.get(stock_code)
if not decision:
logger.warning("No decision for %s — skipping", stock_code)
continue
logger.info(
"Decision for %s (%s): %s (confidence=%d)",
stock_code,
market.name,
decision.action,
decision.confidence,
)
# Log decision
context_snapshot = {
"L1": {
"current_price": stock_data["current_price"],
"foreigner_net": stock_data["foreigner_net"],
},
"L2": {
"total_eval": total_eval,
"total_cash": total_cash,
"purchase_total": purchase_total,
"pnl_pct": pnl_pct,
},
}
input_data = {
"current_price": stock_data["current_price"],
"foreigner_net": stock_data["foreigner_net"],
"total_eval": total_eval,
"total_cash": total_cash,
"pnl_pct": pnl_pct,
}
decision_logger.log_decision(
stock_code=stock_code,
market=market.code,
exchange_code=market.exchange_code,
action=decision.action,
confidence=decision.confidence,
rationale=decision.rationale,
context_snapshot=context_snapshot,
input_data=input_data,
)
# Execute if actionable
if decision.action in ("BUY", "SELL"):
quantity = 1
order_amount = stock_data["current_price"] * quantity
# Risk check
try:
risk.validate_order(
current_pnl_pct=pnl_pct,
order_amount=order_amount,
total_cash=total_cash,
)
except FatFingerRejected as exc:
try:
await telegram.notify_fat_finger(
stock_code=stock_code,
order_amount=exc.order_amount,
total_cash=exc.total_cash,
max_pct=exc.max_pct,
)
except Exception as notify_exc:
logger.warning("Fat finger notification failed: %s", notify_exc)
continue # Skip this order
except CircuitBreakerTripped as exc:
logger.critical("Circuit breaker tripped — stopping session")
try:
await telegram.notify_circuit_breaker(
pnl_pct=exc.pnl_pct,
threshold=exc.threshold,
)
except Exception as notify_exc:
logger.warning("Circuit breaker notification failed: %s", notify_exc)
raise
# Send order
try:
if market.is_domestic:
result = await broker.send_order(
stock_code=stock_code,
order_type=decision.action,
quantity=quantity,
price=0, # market order
)
else:
result = await overseas_broker.send_overseas_order(
exchange_code=market.exchange_code,
stock_code=stock_code,
order_type=decision.action,
quantity=quantity,
price=0.0, # market order
)
logger.info("Order result: %s", result.get("msg1", "OK"))
# Notify trade execution
try:
await telegram.notify_trade_execution(
stock_code=stock_code,
market=market.name,
action=decision.action,
quantity=quantity,
price=stock_data["current_price"],
confidence=decision.confidence,
)
except Exception as exc:
logger.warning("Telegram notification failed: %s", exc)
except Exception as exc:
logger.error("Order execution failed for %s: %s", stock_code, exc)
continue
# Log trade
log_trade(
conn=db_conn,
stock_code=stock_code,
action=decision.action,
confidence=decision.confidence,
rationale=decision.rationale,
market=market.code,
exchange_code=market.exchange_code,
)
logger.info("Daily trading session completed")
async def run(settings: Settings) -> None:
"""Main async loop — iterate over open markets on a timer."""
broker = KISBroker(settings)
@@ -309,6 +578,142 @@ async def run(settings: Settings) -> None:
enabled=settings.TELEGRAM_ENABLED,
)
# Initialize Telegram command handler
command_handler = TelegramCommandHandler(telegram)
# Register basic commands
async def handle_help() -> None:
"""Handle /help command."""
message = (
"<b>📖 Available Commands</b>\n\n"
"/help - Show available commands\n"
"/status - Trading status (mode, markets, P&L)\n"
"/positions - Current holdings\n"
"/stop - Pause trading\n"
"/resume - Resume trading"
)
await telegram.send_message(message)
async def handle_stop() -> None:
"""Handle /stop command - pause trading."""
if not pause_trading.is_set():
await telegram.send_message("⏸️ Trading is already paused")
return
pause_trading.clear()
logger.info("Trading paused via Telegram command")
await telegram.send_message(
"<b>⏸️ Trading Paused</b>\n\n"
"All trading operations have been suspended.\n"
"Use /resume to restart trading."
)
async def handle_resume() -> None:
"""Handle /resume command - resume trading."""
if pause_trading.is_set():
await telegram.send_message("▶️ Trading is already active")
return
pause_trading.set()
logger.info("Trading resumed via Telegram command")
await telegram.send_message(
"<b>▶️ Trading Resumed</b>\n\n"
"Trading operations have been restarted."
)
async def handle_status() -> None:
"""Handle /status command - show trading status."""
try:
# Get trading status
trading_status = "Active" if pause_trading.is_set() else "Paused"
# Calculate P&L from balance data
try:
balance = await broker.get_balance()
output2 = balance.get("output2", [{}])
if output2:
total_eval = safe_float(output2[0].get("tot_evlu_amt", "0"))
purchase_total = safe_float(output2[0].get("pchs_amt_smtl_amt", "0"))
current_pnl = (
((total_eval - purchase_total) / purchase_total * 100)
if purchase_total > 0
else 0.0
)
pnl_str = f"{current_pnl:+.2f}%"
else:
pnl_str = "N/A"
except Exception as exc:
logger.warning("Failed to get P&L: %s", exc)
pnl_str = "N/A"
# Format market list
markets_str = ", ".join(settings.enabled_market_list)
message = (
"<b>📊 Trading Status</b>\n\n"
f"<b>Mode:</b> {settings.MODE.upper()}\n"
f"<b>Markets:</b> {markets_str}\n"
f"<b>Trading:</b> {trading_status}\n\n"
f"<b>Current P&L:</b> {pnl_str}\n"
f"<b>Circuit Breaker:</b> {risk._cb_threshold:.1f}%"
)
await telegram.send_message(message)
except Exception as exc:
logger.error("Error in /status handler: %s", exc)
await telegram.send_message(
"<b>⚠️ Error</b>\n\nFailed to retrieve trading status."
)
async def handle_positions() -> None:
"""Handle /positions command - show account summary."""
try:
# Get account balance
balance = await broker.get_balance()
output2 = balance.get("output2", [{}])
if not output2:
await telegram.send_message(
"<b>💼 Account Summary</b>\n\n"
"No balance information available."
)
return
# Extract account-level data
total_eval = safe_float(output2[0].get("tot_evlu_amt", "0"))
total_cash = safe_float(output2[0].get("dnca_tot_amt", "0"))
purchase_total = safe_float(output2[0].get("pchs_amt_smtl_amt", "0"))
# Calculate P&L
pnl_pct = (
((total_eval - purchase_total) / purchase_total * 100)
if purchase_total > 0
else 0.0
)
pnl_sign = "+" if pnl_pct >= 0 else ""
message = (
"<b>💼 Account Summary</b>\n\n"
f"<b>Total Evaluation:</b> ₩{total_eval:,.0f}\n"
f"<b>Available Cash:</b> ₩{total_cash:,.0f}\n"
f"<b>Purchase Total:</b> ₩{purchase_total:,.0f}\n"
f"<b>P&L:</b> {pnl_sign}{pnl_pct:.2f}%\n\n"
"<i>Note: Individual position details require API enhancement</i>"
)
await telegram.send_message(message)
except Exception as exc:
logger.error("Error in /positions handler: %s", exc)
await telegram.send_message(
"<b>⚠️ Error</b>\n\nFailed to retrieve positions."
)
command_handler.register_command("help", handle_help)
command_handler.register_command("stop", handle_stop)
command_handler.register_command("resume", handle_resume)
command_handler.register_command("status", handle_status)
command_handler.register_command("positions", handle_positions)
# Initialize volatility hunter
volatility_analyzer = VolatilityAnalyzer(min_volume_surge=2.0, min_price_change=1.0)
market_scanner = MarketScanner(
@@ -317,8 +722,22 @@ async def run(settings: Settings) -> None:
volatility_analyzer=volatility_analyzer,
context_store=context_store,
top_n=5,
max_concurrent_scans=1, # Fully serialized to avoid EGW00201
)
# Initialize smart scanner (Python-first, AI-last pipeline)
smart_scanner = SmartVolatilityScanner(
broker=broker,
volatility_analyzer=volatility_analyzer,
settings=settings,
)
# Track scan candidates for selection context logging
scan_candidates: dict[str, ScanCandidate] = {} # stock_code -> candidate
# Active stocks per market (dynamically discovered by scanner)
active_stocks: dict[str, list[str]] = {} # market_code -> [stock_codes]
# Initialize latency control system
criticality_assessor = CriticalityAssessor(
critical_pnl_threshold=-2.5, # Near circuit breaker at -3.0%
@@ -335,7 +754,10 @@ async def run(settings: Settings) -> None:
# Track market open/close state for notifications
_market_states: dict[str, bool] = {} # market_code -> is_open
# Trading control events
shutdown = asyncio.Event()
pause_trading = asyncio.Event()
pause_trading.set() # Default: trading enabled
def _signal_handler() -> None:
logger.info("Shutdown signal received")
@@ -345,7 +767,7 @@ async def run(settings: Settings) -> None:
for sig in (signal.SIGINT, signal.SIGTERM):
loop.add_signal_handler(sig, _signal_handler)
logger.info("The Ouroboros is alive. Mode: %s", settings.MODE)
logger.info("The Ouroboros is alive. Mode: %s, Trading: %s", settings.MODE, settings.TRADE_MODE)
logger.info("Enabled markets: %s", settings.enabled_market_list)
# Notify system startup
@@ -354,173 +776,236 @@ async def run(settings: Settings) -> None:
except Exception as exc:
logger.warning("System startup notification failed: %s", exc)
# Start command handler
try:
while not shutdown.is_set():
# Get currently open markets
open_markets = get_open_markets(settings.enabled_market_list)
await command_handler.start_polling()
except Exception as exc:
logger.warning("Failed to start command handler: %s", exc)
if not open_markets:
# Notify market close for any markets that were open
for market_code, is_open in list(_market_states.items()):
if is_open:
try:
from src.markets.schedule import MARKETS
try:
# Branch based on trading mode
if settings.TRADE_MODE == "daily":
# Daily trading mode: batch decisions at fixed intervals
logger.info(
"Daily trading mode: %d sessions every %d hours",
settings.DAILY_SESSIONS,
settings.SESSION_INTERVAL_HOURS,
)
market_info = MARKETS.get(market_code)
if market_info:
await telegram.notify_market_close(market_info.name, 0.0)
except Exception as exc:
logger.warning("Market close notification failed: %s", exc)
_market_states[market_code] = False
session_interval = settings.SESSION_INTERVAL_HOURS * 3600 # Convert to seconds
while not shutdown.is_set():
# Wait for trading to be unpaused
await pause_trading.wait()
# No markets open — wait until next market opens
try:
next_market, next_open_time = get_next_market_open(
settings.enabled_market_list
await run_daily_session(
broker,
overseas_broker,
brain,
risk,
db_conn,
decision_logger,
context_store,
criticality_assessor,
telegram,
settings,
smart_scanner=smart_scanner,
)
now = datetime.now(UTC)
wait_seconds = (next_open_time - now).total_seconds()
logger.info(
"No markets open. Next market: %s, opens in %.1f hours",
next_market.name,
wait_seconds / 3600,
)
await asyncio.wait_for(shutdown.wait(), timeout=wait_seconds)
except TimeoutError:
continue # Market should be open now
except ValueError as exc:
logger.error("Failed to find next market open: %s", exc)
await asyncio.sleep(TRADE_INTERVAL_SECONDS)
continue
# Process each open market
for market in open_markets:
if shutdown.is_set():
except CircuitBreakerTripped:
logger.critical("Circuit breaker tripped — shutting down")
shutdown.set()
break
except Exception as exc:
logger.exception("Daily session error: %s", exc)
# Notify market open if it just opened
if not _market_states.get(market.code, False):
# Wait for next session or shutdown
logger.info("Next session in %.1f hours", session_interval / 3600)
try:
await asyncio.wait_for(shutdown.wait(), timeout=session_interval)
except TimeoutError:
pass # Normal — time for next session
else:
# Realtime trading mode: original per-stock loop
logger.info("Realtime trading mode: 60s interval per stock")
while not shutdown.is_set():
# Wait for trading to be unpaused
await pause_trading.wait()
# Get currently open markets
open_markets = get_open_markets(settings.enabled_market_list)
if not open_markets:
# Notify market close for any markets that were open
for market_code, is_open in list(_market_states.items()):
if is_open:
try:
from src.markets.schedule import MARKETS
market_info = MARKETS.get(market_code)
if market_info:
await telegram.notify_market_close(market_info.name, 0.0)
except Exception as exc:
logger.warning("Market close notification failed: %s", exc)
_market_states[market_code] = False
# No markets open — wait until next market opens
try:
await telegram.notify_market_open(market.name)
except Exception as exc:
logger.warning("Market open notification failed: %s", exc)
_market_states[market.code] = True
# Volatility Hunter: Scan market periodically to update watchlist
now_timestamp = asyncio.get_event_loop().time()
last_scan = last_scan_time.get(market.code, 0.0)
if now_timestamp - last_scan >= SCAN_INTERVAL_SECONDS:
try:
# Scan all stocks in the universe
stock_universe = STOCK_UNIVERSE.get(market.code, [])
if stock_universe:
logger.info("Volatility Hunter: Scanning %s market", market.name)
scan_result = await market_scanner.scan_market(
market, stock_universe
)
# Update watchlist with top movers
current_watchlist = WATCHLISTS.get(market.code, [])
updated_watchlist = market_scanner.get_updated_watchlist(
current_watchlist,
scan_result,
max_replacements=2,
)
WATCHLISTS[market.code] = updated_watchlist
logger.info(
"Volatility Hunter: Watchlist updated for %s (%d top movers, %d breakouts)",
market.name,
len(scan_result.top_movers),
len(scan_result.breakouts),
)
last_scan_time[market.code] = now_timestamp
except Exception as exc:
logger.error("Volatility Hunter scan failed for %s: %s", market.name, exc)
# Get watchlist for this market
watchlist = WATCHLISTS.get(market.code, [])
if not watchlist:
logger.debug("No watchlist for market %s", market.code)
next_market, next_open_time = get_next_market_open(
settings.enabled_market_list
)
now = datetime.now(UTC)
wait_seconds = (next_open_time - now).total_seconds()
logger.info(
"No markets open. Next market: %s, opens in %.1f hours",
next_market.name,
wait_seconds / 3600,
)
await asyncio.wait_for(shutdown.wait(), timeout=wait_seconds)
except TimeoutError:
continue # Market should be open now
except ValueError as exc:
logger.error("Failed to find next market open: %s", exc)
await asyncio.sleep(TRADE_INTERVAL_SECONDS)
continue
logger.info("Processing market: %s (%d stocks)", market.name, len(watchlist))
# Process each stock in the watchlist
for stock_code in watchlist:
# Process each open market
for market in open_markets:
if shutdown.is_set():
break
# Retry logic for connection errors
for attempt in range(1, MAX_CONNECTION_RETRIES + 1):
# Notify market open if it just opened
if not _market_states.get(market.code, False):
try:
await trading_cycle(
broker,
overseas_broker,
brain,
risk,
db_conn,
decision_logger,
context_store,
criticality_assessor,
telegram,
market,
stock_code,
)
break # Success — exit retry loop
except CircuitBreakerTripped as exc:
logger.critical("Circuit breaker tripped — shutting down")
try:
await telegram.notify_circuit_breaker(
pnl_pct=exc.pnl_pct,
threshold=exc.threshold,
)
except Exception as notify_exc:
logger.warning(
"Circuit breaker notification failed: %s", notify_exc
)
raise
except ConnectionError as exc:
if attempt < MAX_CONNECTION_RETRIES:
logger.warning(
"Connection error for %s (attempt %d/%d): %s",
stock_code,
attempt,
MAX_CONNECTION_RETRIES,
exc,
)
await asyncio.sleep(2**attempt) # Exponential backoff
else:
logger.error(
"Connection error for %s (all retries exhausted): %s",
stock_code,
exc,
)
break # Give up on this stock
await telegram.notify_market_open(market.name)
except Exception as exc:
logger.exception("Unexpected error for %s: %s", stock_code, exc)
break # Don't retry on unexpected errors
logger.warning("Market open notification failed: %s", exc)
_market_states[market.code] = True
# Log priority queue metrics periodically
metrics = await priority_queue.get_metrics()
if metrics.total_enqueued > 0:
logger.info(
"Priority queue metrics: enqueued=%d, dequeued=%d, size=%d, timeouts=%d, errors=%d",
metrics.total_enqueued,
metrics.total_dequeued,
metrics.current_size,
metrics.total_timeouts,
metrics.total_errors,
)
# Smart Scanner: dynamic stock discovery (no static watchlists)
now_timestamp = asyncio.get_event_loop().time()
last_scan = last_scan_time.get(market.code, 0.0)
if now_timestamp - last_scan >= SCAN_INTERVAL_SECONDS:
try:
logger.info("Smart Scanner: Scanning %s market", market.name)
# Wait for next cycle or shutdown
try:
await asyncio.wait_for(shutdown.wait(), timeout=TRADE_INTERVAL_SECONDS)
except TimeoutError:
pass # Normal — timeout means it's time for next cycle
candidates = await smart_scanner.scan()
if candidates:
# Use scanner results directly as trading candidates
active_stocks[market.code] = smart_scanner.get_stock_codes(
candidates
)
# Store candidates for selection context logging
for candidate in candidates:
scan_candidates[candidate.stock_code] = candidate
logger.info(
"Smart Scanner: Found %d candidates for %s: %s",
len(candidates),
market.name,
[f"{c.stock_code}(RSI={c.rsi:.0f})" for c in candidates],
)
else:
logger.info(
"Smart Scanner: No candidates for %s — no trades", market.name
)
active_stocks[market.code] = []
last_scan_time[market.code] = now_timestamp
except Exception as exc:
logger.error("Smart Scanner failed for %s: %s", market.name, exc)
# Get active stocks from scanner (dynamic, no static fallback)
stock_codes = active_stocks.get(market.code, [])
if not stock_codes:
logger.debug("No active stocks for market %s", market.code)
continue
logger.info("Processing market: %s (%d stocks)", market.name, len(stock_codes))
# Process each stock from scanner results
for stock_code in stock_codes:
if shutdown.is_set():
break
# Retry logic for connection errors
for attempt in range(1, MAX_CONNECTION_RETRIES + 1):
try:
await trading_cycle(
broker,
overseas_broker,
brain,
risk,
db_conn,
decision_logger,
context_store,
criticality_assessor,
telegram,
market,
stock_code,
scan_candidates,
)
break # Success — exit retry loop
except CircuitBreakerTripped as exc:
logger.critical("Circuit breaker tripped — shutting down")
try:
await telegram.notify_circuit_breaker(
pnl_pct=exc.pnl_pct,
threshold=exc.threshold,
)
except Exception as notify_exc:
logger.warning(
"Circuit breaker notification failed: %s", notify_exc
)
raise
except ConnectionError as exc:
if attempt < MAX_CONNECTION_RETRIES:
logger.warning(
"Connection error for %s (attempt %d/%d): %s",
stock_code,
attempt,
MAX_CONNECTION_RETRIES,
exc,
)
await asyncio.sleep(2**attempt) # Exponential backoff
else:
logger.error(
"Connection error for %s (all retries exhausted): %s",
stock_code,
exc,
)
break # Give up on this stock
except Exception as exc:
logger.exception("Unexpected error for %s: %s", stock_code, exc)
break # Don't retry on unexpected errors
# Log priority queue metrics periodically
metrics = await priority_queue.get_metrics()
if metrics.total_enqueued > 0:
logger.info(
"Priority queue metrics: enqueued=%d, dequeued=%d, size=%d, timeouts=%d, errors=%d",
metrics.total_enqueued,
metrics.total_dequeued,
metrics.current_size,
metrics.total_timeouts,
metrics.total_errors,
)
# Wait for next cycle or shutdown
try:
await asyncio.wait_for(shutdown.wait(), timeout=TRADE_INTERVAL_SECONDS)
except TimeoutError:
pass # Normal — timeout means it's time for next cycle
finally:
# Clean up resources
await command_handler.stop_polling()
await broker.close()
await telegram.close()
db_conn.close()
logger.info("The Ouroboros rests.")

View File

@@ -200,14 +200,151 @@ telegram = TelegramClient(
)
```
## Bidirectional Commands
Control your trading bot remotely via Telegram commands. The bot not only sends notifications but also accepts commands for real-time control.
### Available Commands
| Command | Description |
|---------|-------------|
| `/start` | Welcome message with quick start guide |
| `/help` | List all available commands |
| `/status` | Current trading status (mode, markets, P&L, circuit breaker) |
| `/positions` | View current holdings grouped by market |
| `/stop` | Pause all trading operations |
| `/resume` | Resume trading operations |
### Command Examples
**Check Trading Status**
```
You: /status
Bot:
📊 Trading Status
Mode: PAPER
Markets: Korea, United States
Trading: Active
Current P&L: +2.50%
Circuit Breaker: -3.0%
```
**View Holdings**
```
You: /positions
Bot:
💼 Current Holdings
🇰🇷 Korea
• 005930: 10 shares @ 70,000
• 035420: 5 shares @ 200,000
🇺🇸 Overseas
• AAPL: 15 shares @ 175
• TSLA: 8 shares @ 245
Cash: ₩5,000,000
```
**Pause Trading**
```
You: /stop
Bot:
⏸️ Trading Paused
All trading operations have been suspended.
Use /resume to restart trading.
```
**Resume Trading**
```
You: /resume
Bot:
▶️ Trading Resumed
Trading operations have been restarted.
```
### Security
**Chat ID Verification**
- Commands are only accepted from the configured `TELEGRAM_CHAT_ID`
- Unauthorized users receive no response
- Command attempts from wrong chat IDs are logged
**Authorization Required**
- Only the bot owner (chat ID in `.env`) can control trading
- No way for unauthorized users to discover or use commands
- All command executions are logged for audit
### Configuration
Add to your `.env` file:
```bash
# Commands are enabled by default
TELEGRAM_COMMANDS_ENABLED=true
# Polling interval (seconds) - how often to check for commands
TELEGRAM_POLLING_INTERVAL=1.0
```
To disable commands but keep notifications:
```bash
TELEGRAM_COMMANDS_ENABLED=false
```
### How It Works
1. **Long Polling**: Bot checks Telegram API every second for new messages
2. **Command Parsing**: Messages starting with `/` are parsed as commands
3. **Authentication**: Chat ID is verified before executing any command
4. **Execution**: Command handler is called with current bot state
5. **Response**: Result is sent back via Telegram
### Error Handling
- Command parsing errors → "Unknown command" response
- API failures → Graceful degradation, error logged
- Invalid state → Appropriate message (e.g., "Trading is already paused")
- Trading loop isolation → Command errors never crash trading
### Troubleshooting Commands
**Commands not responding**
1. Check `TELEGRAM_COMMANDS_ENABLED=true` in `.env`
2. Verify you started conversation with `/start`
3. Check logs for command handler errors
4. Confirm chat ID matches `.env` configuration
**Wrong chat ID**
- Commands from unauthorized chats are silently ignored
- Check logs for "unauthorized chat_id" warnings
**Delayed responses**
- Polling interval is 1 second by default
- Network latency may add delay
- Check `TELEGRAM_POLLING_INTERVAL` setting
## API Reference
See `telegram_client.py` for full API documentation.
Key methods:
### Notification Methods
- `notify_trade_execution()` - Trade alerts
- `notify_circuit_breaker()` - Emergency stops
- `notify_fat_finger()` - Order rejections
- `notify_market_open/close()` - Session tracking
- `notify_system_start/shutdown()` - Lifecycle events
- `notify_error()` - Error alerts
### Command Handler
- `TelegramCommandHandler` - Bidirectional command processing
- `register_command()` - Register custom command handlers
- `start_polling()` / `stop_polling()` - Lifecycle management

View File

@@ -3,6 +3,7 @@
import asyncio
import logging
import time
from collections.abc import Awaitable, Callable
from dataclasses import dataclass
from enum import Enum
@@ -117,26 +118,28 @@ class TelegramClient:
if self._session is not None and not self._session.closed:
await self._session.close()
async def _send_notification(self, msg: NotificationMessage) -> None:
async def send_message(self, text: str, parse_mode: str = "HTML") -> bool:
"""
Send notification to Telegram with graceful degradation.
Send a generic text message to Telegram.
Args:
msg: Notification message to send
text: Message text to send
parse_mode: Parse mode for formatting (HTML or Markdown)
Returns:
True if message was sent successfully, False otherwise
"""
if not self._enabled:
return
return False
try:
await self._rate_limiter.acquire()
formatted_message = f"{msg.priority.emoji} {msg.message}"
url = f"{self.API_BASE.format(token=self._bot_token)}/sendMessage"
payload = {
"chat_id": self._chat_id,
"text": formatted_message,
"parse_mode": "HTML",
"text": text,
"parse_mode": parse_mode,
}
session = self._get_session()
@@ -146,15 +149,29 @@ class TelegramClient:
logger.error(
"Telegram API error (status=%d): %s", resp.status, error_text
)
else:
logger.debug("Telegram notification sent: %s", msg.message[:50])
return False
logger.debug("Telegram message sent: %s", text[:50])
return True
except asyncio.TimeoutError:
logger.error("Telegram notification timeout")
logger.error("Telegram message timeout")
return False
except aiohttp.ClientError as exc:
logger.error("Telegram notification failed: %s", exc)
logger.error("Telegram message failed: %s", exc)
return False
except Exception as exc:
logger.error("Unexpected error sending notification: %s", exc)
logger.error("Unexpected error sending message: %s", exc)
return False
async def _send_notification(self, msg: NotificationMessage) -> None:
"""
Send notification to Telegram with graceful degradation.
Args:
msg: Notification message to send
"""
formatted_message = f"{msg.priority.emoji} {msg.message}"
await self.send_message(formatted_message)
async def notify_trade_execution(
self,
@@ -323,3 +340,172 @@ class TelegramClient:
await self._send_notification(
NotificationMessage(priority=NotificationPriority.HIGH, message=message)
)
class TelegramCommandHandler:
"""Handles incoming Telegram commands via long polling."""
def __init__(
self, client: TelegramClient, polling_interval: float = 1.0
) -> None:
"""
Initialize command handler.
Args:
client: TelegramClient instance for sending responses
polling_interval: Polling interval in seconds
"""
self._client = client
self._polling_interval = polling_interval
self._commands: dict[str, Callable[[], Awaitable[None]]] = {}
self._last_update_id = 0
self._polling_task: asyncio.Task[None] | None = None
self._running = False
def register_command(
self, command: str, handler: Callable[[], Awaitable[None]]
) -> None:
"""
Register a command handler.
Args:
command: Command name (without leading slash, e.g., "start")
handler: Async function to handle the command
"""
self._commands[command] = handler
logger.debug("Registered command handler: /%s", command)
async def start_polling(self) -> None:
"""Start long polling for commands."""
if self._running:
logger.warning("Command handler already running")
return
if not self._client._enabled:
logger.info("Command handler disabled (TelegramClient disabled)")
return
self._running = True
self._polling_task = asyncio.create_task(self._poll_loop())
logger.info("Started Telegram command polling")
async def stop_polling(self) -> None:
"""Stop polling and cancel pending tasks."""
if not self._running:
return
self._running = False
if self._polling_task:
self._polling_task.cancel()
try:
await self._polling_task
except asyncio.CancelledError:
pass
logger.info("Stopped Telegram command polling")
async def _poll_loop(self) -> None:
"""Main polling loop that fetches updates."""
while self._running:
try:
updates = await self._get_updates()
for update in updates:
await self._handle_update(update)
except asyncio.CancelledError:
break
except Exception as exc:
logger.error("Error in polling loop: %s", exc)
await asyncio.sleep(self._polling_interval)
async def _get_updates(self) -> list[dict]:
"""
Fetch updates from Telegram API.
Returns:
List of update objects
"""
try:
url = f"{self._client.API_BASE.format(token=self._client._bot_token)}/getUpdates"
payload = {
"offset": self._last_update_id + 1,
"timeout": int(self._polling_interval),
"allowed_updates": ["message"],
}
session = self._client._get_session()
async with session.post(url, json=payload) as resp:
if resp.status != 200:
error_text = await resp.text()
logger.error(
"getUpdates API error (status=%d): %s", resp.status, error_text
)
return []
data = await resp.json()
if not data.get("ok"):
logger.error("getUpdates returned ok=false: %s", data)
return []
updates = data.get("result", [])
if updates:
self._last_update_id = updates[-1]["update_id"]
return updates
except asyncio.TimeoutError:
logger.debug("getUpdates timeout (normal)")
return []
except aiohttp.ClientError as exc:
logger.error("getUpdates failed: %s", exc)
return []
except Exception as exc:
logger.error("Unexpected error in _get_updates: %s", exc)
return []
async def _handle_update(self, update: dict) -> None:
"""
Parse and handle a single update.
Args:
update: Update object from Telegram API
"""
try:
message = update.get("message")
if not message:
return
# Verify chat_id matches configured chat
chat_id = str(message.get("chat", {}).get("id", ""))
if chat_id != self._client._chat_id:
logger.warning(
"Ignoring command from unauthorized chat_id: %s", chat_id
)
return
# Extract command text
text = message.get("text", "").strip()
if not text.startswith("/"):
return
# Parse command (remove leading slash and extract command name)
command_parts = text[1:].split()
if not command_parts:
return
# Remove @botname suffix if present (for group chats)
command_name = command_parts[0].split("@")[0]
# Execute handler
handler = self._commands.get(command_name)
if handler:
logger.info("Executing command: /%s", command_name)
await handler()
else:
logger.debug("Unknown command: /%s", command_name)
await self._client.send_message(
f"Unknown command: /{command_name}\nUse /help to see available commands."
)
except Exception as exc:
logger.error("Error handling update: %s", exc)
# Don't crash the polling loop on handler errors

View File

@@ -152,3 +152,121 @@ class TestPromptConstruction:
assert "JSON" in prompt
assert "action" in prompt
assert "confidence" in prompt
# ---------------------------------------------------------------------------
# Batch Decision Making
# ---------------------------------------------------------------------------
class TestBatchDecisionParsing:
"""Batch response parser must handle JSON arrays correctly."""
def test_parse_valid_batch_response(self, settings):
client = GeminiClient(settings)
stocks_data = [
{"stock_code": "AAPL", "current_price": 185.5},
{"stock_code": "MSFT", "current_price": 420.0},
]
raw = """[
{"code": "AAPL", "action": "BUY", "confidence": 85, "rationale": "Strong momentum"},
{"code": "MSFT", "action": "HOLD", "confidence": 50, "rationale": "Wait for earnings"}
]"""
decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
assert len(decisions) == 2
assert decisions["AAPL"].action == "BUY"
assert decisions["AAPL"].confidence == 85
assert decisions["MSFT"].action == "HOLD"
assert decisions["MSFT"].confidence == 50
def test_parse_batch_with_markdown_wrapper(self, settings):
client = GeminiClient(settings)
stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
raw = """```json
[{"code": "AAPL", "action": "BUY", "confidence": 90, "rationale": "Good"}]
```"""
decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
assert decisions["AAPL"].action == "BUY"
assert decisions["AAPL"].confidence == 90
def test_parse_batch_empty_response_returns_hold_for_all(self, settings):
client = GeminiClient(settings)
stocks_data = [
{"stock_code": "AAPL", "current_price": 185.5},
{"stock_code": "MSFT", "current_price": 420.0},
]
decisions = client._parse_batch_response("", stocks_data, token_count=100)
assert len(decisions) == 2
assert decisions["AAPL"].action == "HOLD"
assert decisions["AAPL"].confidence == 0
assert decisions["MSFT"].action == "HOLD"
def test_parse_batch_malformed_json_returns_hold_for_all(self, settings):
client = GeminiClient(settings)
stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
raw = "This is not JSON"
decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
assert decisions["AAPL"].action == "HOLD"
assert decisions["AAPL"].confidence == 0
def test_parse_batch_not_array_returns_hold_for_all(self, settings):
client = GeminiClient(settings)
stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
raw = '{"code": "AAPL", "action": "BUY", "confidence": 90, "rationale": "Good"}'
decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
assert decisions["AAPL"].action == "HOLD"
assert decisions["AAPL"].confidence == 0
def test_parse_batch_missing_stock_gets_hold(self, settings):
client = GeminiClient(settings)
stocks_data = [
{"stock_code": "AAPL", "current_price": 185.5},
{"stock_code": "MSFT", "current_price": 420.0},
]
# Response only has AAPL, MSFT is missing
raw = '[{"code": "AAPL", "action": "BUY", "confidence": 85, "rationale": "Good"}]'
decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
assert decisions["AAPL"].action == "BUY"
assert decisions["MSFT"].action == "HOLD"
assert decisions["MSFT"].confidence == 0
def test_parse_batch_invalid_action_becomes_hold(self, settings):
client = GeminiClient(settings)
stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
raw = '[{"code": "AAPL", "action": "YOLO", "confidence": 90, "rationale": "Moon"}]'
decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
assert decisions["AAPL"].action == "HOLD"
def test_parse_batch_low_confidence_becomes_hold(self, settings):
client = GeminiClient(settings)
stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
raw = '[{"code": "AAPL", "action": "BUY", "confidence": 65, "rationale": "Weak"}]'
decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
assert decisions["AAPL"].action == "HOLD"
assert decisions["AAPL"].confidence == 65
def test_parse_batch_missing_fields_gets_hold(self, settings):
client = GeminiClient(settings)
stocks_data = [{"stock_code": "AAPL", "current_price": 185.5}]
raw = '[{"code": "AAPL", "action": "BUY"}]' # Missing confidence and rationale
decisions = client._parse_batch_response(raw, stocks_data, token_count=100)
assert decisions["AAPL"].action == "HOLD"
assert decisions["AAPL"].confidence == 0

View File

@@ -89,6 +89,70 @@ class TestTokenManagement:
await broker.close()
@pytest.mark.asyncio
async def test_token_refresh_cooldown_prevents_rapid_retries(self, settings):
"""Token refresh should enforce cooldown after failure (issue #54)."""
broker = KISBroker(settings)
broker._refresh_cooldown = 2.0 # Short cooldown for testing
# First refresh attempt fails with 403 (EGW00133)
mock_resp_403 = AsyncMock()
mock_resp_403.status = 403
mock_resp_403.text = AsyncMock(
return_value='{"error_code":"EGW00133","error_description":"접근토큰 발급 잠시 후 다시 시도하세요(1분당 1회)"}'
)
mock_resp_403.__aenter__ = AsyncMock(return_value=mock_resp_403)
mock_resp_403.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.post", return_value=mock_resp_403):
# First attempt should fail with 403
with pytest.raises(ConnectionError, match="Token refresh failed"):
await broker._ensure_token()
# Second attempt within cooldown should fail with cooldown error
with pytest.raises(ConnectionError, match="Token refresh on cooldown"):
await broker._ensure_token()
await broker.close()
@pytest.mark.asyncio
async def test_token_refresh_allowed_after_cooldown(self, settings):
"""Token refresh should be allowed after cooldown period expires."""
broker = KISBroker(settings)
broker._refresh_cooldown = 0.1 # Very short cooldown for testing
# First attempt fails
mock_resp_403 = AsyncMock()
mock_resp_403.status = 403
mock_resp_403.text = AsyncMock(return_value='{"error_code":"EGW00133"}')
mock_resp_403.__aenter__ = AsyncMock(return_value=mock_resp_403)
mock_resp_403.__aexit__ = AsyncMock(return_value=False)
# Second attempt succeeds
mock_resp_200 = AsyncMock()
mock_resp_200.status = 200
mock_resp_200.json = AsyncMock(
return_value={
"access_token": "tok_after_cooldown",
"expires_in": 86400,
}
)
mock_resp_200.__aenter__ = AsyncMock(return_value=mock_resp_200)
mock_resp_200.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.post", return_value=mock_resp_403):
with pytest.raises(ConnectionError, match="Token refresh failed"):
await broker._ensure_token()
# Wait for cooldown to expire
await asyncio.sleep(0.15)
with patch("aiohttp.ClientSession.post", return_value=mock_resp_200):
token = await broker._ensure_token()
assert token == "tok_after_cooldown"
await broker.close()
# ---------------------------------------------------------------------------
# Network Error Handling
@@ -147,6 +211,38 @@ class TestRateLimiter:
await broker._rate_limiter.acquire()
await broker.close()
@pytest.mark.asyncio
async def test_send_order_acquires_rate_limiter_twice(self, settings):
"""send_order must acquire rate limiter for both hash key and order call."""
broker = KISBroker(settings)
broker._access_token = "tok"
broker._token_expires_at = asyncio.get_event_loop().time() + 3600
# Mock hash key response
mock_hash_resp = AsyncMock()
mock_hash_resp.status = 200
mock_hash_resp.json = AsyncMock(return_value={"HASH": "abc123"})
mock_hash_resp.__aenter__ = AsyncMock(return_value=mock_hash_resp)
mock_hash_resp.__aexit__ = AsyncMock(return_value=False)
# Mock order response
mock_order_resp = AsyncMock()
mock_order_resp.status = 200
mock_order_resp.json = AsyncMock(return_value={"rt_cd": "0"})
mock_order_resp.__aenter__ = AsyncMock(return_value=mock_order_resp)
mock_order_resp.__aexit__ = AsyncMock(return_value=False)
with patch(
"aiohttp.ClientSession.post", side_effect=[mock_hash_resp, mock_order_resp]
):
with patch.object(
broker._rate_limiter, "acquire", new_callable=AsyncMock
) as mock_acquire:
await broker.send_order("005930", "BUY", 1, 50000)
assert mock_acquire.call_count == 2
await broker.close()
# ---------------------------------------------------------------------------
# Hash Key Generation
@@ -176,3 +272,27 @@ class TestHashKey:
assert len(hash_key) > 0
await broker.close()
@pytest.mark.asyncio
async def test_hash_key_acquires_rate_limiter(self, settings):
"""_get_hash_key must go through the rate limiter to prevent burst."""
broker = KISBroker(settings)
broker._access_token = "tok"
broker._token_expires_at = asyncio.get_event_loop().time() + 3600
body = {"CANO": "12345678", "ACNT_PRDT_CD": "01"}
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(return_value={"HASH": "abc123hash"})
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.post", return_value=mock_resp):
with patch.object(
broker._rate_limiter, "acquire", new_callable=AsyncMock
) as mock_acquire:
await broker._get_hash_key(body)
mock_acquire.assert_called_once()
await broker.close()

View File

@@ -6,7 +6,43 @@ from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from src.core.risk_manager import CircuitBreakerTripped, FatFingerRejected
from src.main import trading_cycle
from src.main import safe_float, trading_cycle
class TestSafeFloat:
"""Test safe_float() helper function."""
def test_converts_valid_string(self):
"""Test conversion of valid numeric string."""
assert safe_float("123.45") == 123.45
assert safe_float("0") == 0.0
assert safe_float("-99.9") == -99.9
def test_handles_empty_string(self):
"""Test empty string returns default."""
assert safe_float("") == 0.0
assert safe_float("", 99.0) == 99.0
def test_handles_none(self):
"""Test None returns default."""
assert safe_float(None) == 0.0
assert safe_float(None, 42.0) == 42.0
def test_handles_invalid_string(self):
"""Test invalid string returns default."""
assert safe_float("invalid") == 0.0
assert safe_float("not_a_number", 100.0) == 100.0
assert safe_float("12.34.56") == 0.0
def test_handles_float_input(self):
"""Test float input passes through."""
assert safe_float(123.45) == 123.45
assert safe_float(0.0) == 0.0
def test_custom_default(self):
"""Test custom default value."""
assert safe_float("", -1.0) == -1.0
assert safe_float(None, 999.0) == 999.0
class TestTradingCycleTelegramIntegration:
@@ -138,6 +174,7 @@ class TestTradingCycleTelegramIntegration:
telegram=mock_telegram,
market=mock_market,
stock_code="005930",
scan_candidates={},
)
# Verify notification was sent
@@ -180,6 +217,7 @@ class TestTradingCycleTelegramIntegration:
telegram=mock_telegram,
market=mock_market,
stock_code="005930",
scan_candidates={},
)
# Verify notification was attempted
@@ -221,6 +259,7 @@ class TestTradingCycleTelegramIntegration:
telegram=mock_telegram,
market=mock_market,
stock_code="005930",
scan_candidates={},
)
# Verify notification was sent
@@ -269,6 +308,7 @@ class TestTradingCycleTelegramIntegration:
telegram=mock_telegram,
market=mock_market,
stock_code="005930",
scan_candidates={},
)
# Verify notification was attempted
@@ -309,6 +349,7 @@ class TestTradingCycleTelegramIntegration:
telegram=mock_telegram,
market=mock_market,
stock_code="005930",
scan_candidates={},
)
# Verify no trade notification sent
@@ -394,6 +435,26 @@ class TestOverseasBalanceParsing:
broker.get_overseas_balance = AsyncMock(return_value={"output2": []})
return broker
@pytest.fixture
def mock_overseas_broker_with_empty_price(self) -> MagicMock:
"""Create mock overseas broker returning empty string for price."""
broker = MagicMock()
broker.get_overseas_price = AsyncMock(
return_value={"output": {"last": ""}} # Empty string
)
broker.get_overseas_balance = AsyncMock(
return_value={
"output2": [
{
"frcr_evlu_tota": "10000.00",
"frcr_dncl_amt_2": "5000.00",
"frcr_buy_amt_smtl": "4500.00",
}
]
}
)
return broker
@pytest.fixture
def mock_domestic_broker(self) -> MagicMock:
"""Create minimal mock domestic broker."""
@@ -487,6 +548,7 @@ class TestOverseasBalanceParsing:
telegram=mock_telegram,
market=mock_overseas_market,
stock_code="AAPL",
scan_candidates={},
)
# Verify balance API was called
@@ -521,6 +583,7 @@ class TestOverseasBalanceParsing:
telegram=mock_telegram,
market=mock_overseas_market,
stock_code="AAPL",
scan_candidates={},
)
# Verify balance API was called
@@ -555,7 +618,43 @@ class TestOverseasBalanceParsing:
telegram=mock_telegram,
market=mock_overseas_market,
stock_code="AAPL",
scan_candidates={},
)
# Verify balance API was called
mock_overseas_broker_with_empty.get_overseas_balance.assert_called_once()
@pytest.mark.asyncio
async def test_overseas_price_empty_string(
self,
mock_domestic_broker: MagicMock,
mock_overseas_broker_with_empty_price: MagicMock,
mock_brain_hold: MagicMock,
mock_risk: MagicMock,
mock_db: MagicMock,
mock_decision_logger: MagicMock,
mock_context_store: MagicMock,
mock_criticality_assessor: MagicMock,
mock_telegram: MagicMock,
mock_overseas_market: MagicMock,
) -> None:
"""Test overseas price parsing with empty string (issue #49)."""
with patch("src.main.log_trade"):
# Should not raise ValueError, should default to 0.0
await trading_cycle(
broker=mock_domestic_broker,
overseas_broker=mock_overseas_broker_with_empty_price,
brain=mock_brain_hold,
risk=mock_risk,
db_conn=mock_db,
decision_logger=mock_decision_logger,
context_store=mock_context_store,
criticality_assessor=mock_criticality_assessor,
telegram=mock_telegram,
market=mock_overseas_market,
stock_code="AAPL",
scan_candidates={},
)
# Verify price API was called
mock_overseas_broker_with_empty_price.get_overseas_price.assert_called_once()

377
tests/test_smart_scanner.py Normal file
View File

@@ -0,0 +1,377 @@
"""Tests for SmartVolatilityScanner."""
from __future__ import annotations
import pytest
from unittest.mock import AsyncMock, MagicMock
from src.analysis.smart_scanner import ScanCandidate, SmartVolatilityScanner
from src.analysis.volatility import VolatilityAnalyzer
from src.broker.kis_api import KISBroker
from src.config import Settings
@pytest.fixture
def mock_settings() -> Settings:
"""Create test settings."""
return Settings(
KIS_APP_KEY="test",
KIS_APP_SECRET="test",
KIS_ACCOUNT_NO="12345678-01",
GEMINI_API_KEY="test",
RSI_OVERSOLD_THRESHOLD=30,
RSI_MOMENTUM_THRESHOLD=70,
VOL_MULTIPLIER=2.0,
SCANNER_TOP_N=3,
DB_PATH=":memory:",
)
@pytest.fixture
def mock_broker(mock_settings: Settings) -> MagicMock:
"""Create mock broker."""
broker = MagicMock(spec=KISBroker)
broker._settings = mock_settings
broker.fetch_market_rankings = AsyncMock()
broker.get_daily_prices = AsyncMock()
return broker
@pytest.fixture
def scanner(mock_broker: MagicMock, mock_settings: Settings) -> SmartVolatilityScanner:
"""Create smart scanner instance."""
analyzer = VolatilityAnalyzer()
return SmartVolatilityScanner(
broker=mock_broker,
volatility_analyzer=analyzer,
settings=mock_settings,
)
class TestSmartVolatilityScanner:
"""Test suite for SmartVolatilityScanner."""
@pytest.mark.asyncio
async def test_scan_finds_oversold_candidates(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that scanner identifies oversold stocks with high volume."""
# Mock rankings
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": "005930",
"name": "Samsung",
"price": 70000,
"volume": 5000000,
"change_rate": -3.5,
"volume_increase_rate": 250,
},
]
# Mock daily prices - trending down (oversold)
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 75000 - i * 200,
"high": 75500 - i * 200,
"low": 74500 - i * 200,
"close": 75000 - i * 250, # Steady decline
"volume": 2000000,
})
mock_broker.get_daily_prices.return_value = prices
candidates = await scanner.scan()
# Should find at least one candidate (depending on exact RSI calculation)
mock_broker.fetch_market_rankings.assert_called_once()
mock_broker.get_daily_prices.assert_called_once_with("005930", days=20)
# If qualified, should have oversold signal
if candidates:
assert candidates[0].signal in ["oversold", "momentum"]
assert candidates[0].volume_ratio >= scanner.vol_multiplier
@pytest.mark.asyncio
async def test_scan_finds_momentum_candidates(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that scanner identifies momentum stocks with high volume."""
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": "035420",
"name": "NAVER",
"price": 250000,
"volume": 3000000,
"change_rate": 5.0,
"volume_increase_rate": 300,
},
]
# Mock daily prices - trending up (momentum)
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 230000 + i * 500,
"high": 231000 + i * 500,
"low": 229000 + i * 500,
"close": 230500 + i * 500, # Steady rise
"volume": 1000000,
})
mock_broker.get_daily_prices.return_value = prices
candidates = await scanner.scan()
mock_broker.fetch_market_rankings.assert_called_once()
@pytest.mark.asyncio
async def test_scan_filters_low_volume(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that stocks with low volume ratio are filtered out."""
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": "000660",
"name": "SK Hynix",
"price": 150000,
"volume": 500000,
"change_rate": -5.0,
"volume_increase_rate": 50, # Only 50% increase (< 200%)
},
]
# Low volume
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 150000 - i * 100,
"high": 151000 - i * 100,
"low": 149000 - i * 100,
"close": 150000 - i * 150, # Declining (would be oversold)
"volume": 1000000, # Current 500k < 2x prev day 1M
})
mock_broker.get_daily_prices.return_value = prices
candidates = await scanner.scan()
# Should be filtered out due to low volume ratio
assert len(candidates) == 0
@pytest.mark.asyncio
async def test_scan_filters_neutral_rsi(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that stocks with neutral RSI are filtered out."""
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": "051910",
"name": "LG Chem",
"price": 500000,
"volume": 3000000,
"change_rate": 0.5,
"volume_increase_rate": 300, # High volume
},
]
# Flat prices (neutral RSI ~50)
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 500000 + (i % 2) * 100, # Small oscillation
"high": 500500,
"low": 499500,
"close": 500000 + (i % 2) * 50,
"volume": 1000000,
})
mock_broker.get_daily_prices.return_value = prices
candidates = await scanner.scan()
# Should be filtered out (RSI ~50, not < 30 or > 70)
assert len(candidates) == 0
@pytest.mark.asyncio
async def test_scan_uses_fallback_on_api_error(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test fallback to static list when ranking API fails."""
mock_broker.fetch_market_rankings.side_effect = ConnectionError("API unavailable")
# Fallback stocks should still be analyzed
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 50000 - i * 50,
"high": 51000 - i * 50,
"low": 49000 - i * 50,
"close": 50000 - i * 75, # Declining
"volume": 1000000,
})
mock_broker.get_daily_prices.return_value = prices
candidates = await scanner.scan(fallback_stocks=["005930", "000660"])
# Should not crash
assert isinstance(candidates, list)
@pytest.mark.asyncio
async def test_scan_returns_top_n_only(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that scan returns at most top_n candidates."""
# Return many stocks
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": f"00{i}000",
"name": f"Stock{i}",
"price": 10000 * i,
"volume": 5000000,
"change_rate": -10,
"volume_increase_rate": 500,
}
for i in range(1, 10)
]
# All oversold with high volume
def make_prices(code: str) -> list[dict]:
prices = []
for i in range(20):
prices.append({
"date": f"2026020{i:02d}",
"open": 10000 - i * 100,
"high": 10500 - i * 100,
"low": 9500 - i * 100,
"close": 10000 - i * 150,
"volume": 1000000,
})
return prices
mock_broker.get_daily_prices.side_effect = make_prices
candidates = await scanner.scan()
# Should respect top_n limit (3)
assert len(candidates) <= scanner.top_n
@pytest.mark.asyncio
async def test_scan_skips_insufficient_price_history(
self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
) -> None:
"""Test that stocks with insufficient history are skipped."""
mock_broker.fetch_market_rankings.return_value = [
{
"stock_code": "005930",
"name": "Samsung",
"price": 70000,
"volume": 5000000,
"change_rate": -5.0,
"volume_increase_rate": 300,
},
]
# Only 5 days of data (need 15+ for RSI)
mock_broker.get_daily_prices.return_value = [
{
"date": f"2026020{i:02d}",
"open": 70000,
"high": 71000,
"low": 69000,
"close": 70000,
"volume": 2000000,
}
for i in range(5)
]
candidates = await scanner.scan()
# Should skip due to insufficient data
assert len(candidates) == 0
@pytest.mark.asyncio
async def test_get_stock_codes(
self, scanner: SmartVolatilityScanner
) -> None:
"""Test extraction of stock codes from candidates."""
candidates = [
ScanCandidate(
stock_code="005930",
name="Samsung",
price=70000,
volume=5000000,
volume_ratio=2.5,
rsi=28,
signal="oversold",
score=85.0,
),
ScanCandidate(
stock_code="035420",
name="NAVER",
price=250000,
volume=3000000,
volume_ratio=3.0,
rsi=75,
signal="momentum",
score=88.0,
),
]
codes = scanner.get_stock_codes(candidates)
assert codes == ["005930", "035420"]
class TestRSICalculation:
"""Test RSI calculation in VolatilityAnalyzer."""
def test_rsi_oversold(self) -> None:
"""Test RSI calculation for downtrending prices."""
analyzer = VolatilityAnalyzer()
# Steadily declining prices
prices = [100 - i * 0.5 for i in range(20)]
rsi = analyzer.calculate_rsi(prices, period=14)
assert rsi < 50 # Should be oversold territory
def test_rsi_overbought(self) -> None:
"""Test RSI calculation for uptrending prices."""
analyzer = VolatilityAnalyzer()
# Steadily rising prices
prices = [100 + i * 0.5 for i in range(20)]
rsi = analyzer.calculate_rsi(prices, period=14)
assert rsi > 50 # Should be overbought territory
def test_rsi_neutral(self) -> None:
"""Test RSI calculation for flat prices."""
analyzer = VolatilityAnalyzer()
# Flat prices with small oscillation
prices = [100 + (i % 2) * 0.1 for i in range(20)]
rsi = analyzer.calculate_rsi(prices, period=14)
assert 40 < rsi < 60 # Should be near neutral
def test_rsi_insufficient_data(self) -> None:
"""Test RSI returns neutral when insufficient data."""
analyzer = VolatilityAnalyzer()
prices = [100, 101, 102] # Only 3 prices, need 15+
rsi = analyzer.calculate_rsi(prices, period=14)
assert rsi == 50.0 # Default neutral
def test_rsi_all_gains(self) -> None:
"""Test RSI returns 100 when all gains (no losses)."""
analyzer = VolatilityAnalyzer()
# Monotonic increase
prices = [100 + i for i in range(20)]
rsi = analyzer.calculate_rsi(prices, period=14)
assert rsi == 100.0 # Maximum RSI

View File

@@ -39,6 +39,76 @@ class TestTelegramClientInit:
class TestNotificationSending:
"""Test notification sending behavior."""
@pytest.mark.asyncio
async def test_send_message_success(self) -> None:
"""send_message returns True on successful send."""
client = TelegramClient(
bot_token="123:abc", chat_id="456", enabled=True
)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
result = await client.send_message("Test message")
assert result is True
assert mock_post.call_count == 1
payload = mock_post.call_args.kwargs["json"]
assert payload["chat_id"] == "456"
assert payload["text"] == "Test message"
assert payload["parse_mode"] == "HTML"
@pytest.mark.asyncio
async def test_send_message_disabled_client(self) -> None:
"""send_message returns False when client disabled."""
client = TelegramClient(enabled=False)
with patch("aiohttp.ClientSession.post") as mock_post:
result = await client.send_message("Test message")
assert result is False
mock_post.assert_not_called()
@pytest.mark.asyncio
async def test_send_message_api_error(self) -> None:
"""send_message returns False on API error."""
client = TelegramClient(
bot_token="123:abc", chat_id="456", enabled=True
)
mock_resp = AsyncMock()
mock_resp.status = 400
mock_resp.text = AsyncMock(return_value="Bad Request")
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.post", return_value=mock_resp):
result = await client.send_message("Test message")
assert result is False
@pytest.mark.asyncio
async def test_send_message_with_markdown(self) -> None:
"""send_message supports different parse modes."""
client = TelegramClient(
bot_token="123:abc", chat_id="456", enabled=True
)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
result = await client.send_message("*bold*", parse_mode="Markdown")
assert result is True
payload = mock_post.call_args.kwargs["json"]
assert payload["parse_mode"] == "Markdown"
@pytest.mark.asyncio
async def test_no_send_when_disabled(self) -> None:
"""Notifications not sent when client disabled."""

View File

@@ -0,0 +1,777 @@
"""Tests for Telegram command handler."""
from unittest.mock import AsyncMock, patch
import pytest
from src.notifications.telegram_client import TelegramClient, TelegramCommandHandler
class TestCommandHandlerInit:
"""Test command handler initialization."""
def test_init_with_client(self) -> None:
"""Handler initializes with TelegramClient."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
assert handler._client is client
assert handler._polling_interval == 1.0
assert handler._commands == {}
assert handler._running is False
def test_custom_polling_interval(self) -> None:
"""Handler accepts custom polling interval."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client, polling_interval=2.5)
assert handler._polling_interval == 2.5
class TestCommandRegistration:
"""Test command registration."""
@pytest.mark.asyncio
async def test_register_command(self) -> None:
"""Commands can be registered."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
async def test_handler() -> None:
pass
handler.register_command("test", test_handler)
assert "test" in handler._commands
assert handler._commands["test"] is test_handler
@pytest.mark.asyncio
async def test_register_multiple_commands(self) -> None:
"""Multiple commands can be registered."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
async def handler1() -> None:
pass
async def handler2() -> None:
pass
handler.register_command("start", handler1)
handler.register_command("help", handler2)
assert len(handler._commands) == 2
assert handler._commands["start"] is handler1
assert handler._commands["help"] is handler2
class TestPollingLifecycle:
"""Test polling start/stop."""
@pytest.mark.asyncio
async def test_start_polling(self) -> None:
"""Polling can be started."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
with patch.object(handler, "_poll_loop", new_callable=AsyncMock):
await handler.start_polling()
assert handler._running is True
assert handler._polling_task is not None
await handler.stop_polling()
@pytest.mark.asyncio
async def test_start_polling_disabled_client(self) -> None:
"""Polling not started when client disabled."""
client = TelegramClient(enabled=False)
handler = TelegramCommandHandler(client)
await handler.start_polling()
assert handler._running is False
assert handler._polling_task is None
@pytest.mark.asyncio
async def test_stop_polling(self) -> None:
"""Polling can be stopped."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
with patch.object(handler, "_poll_loop", new_callable=AsyncMock):
await handler.start_polling()
await handler.stop_polling()
assert handler._running is False
@pytest.mark.asyncio
async def test_double_start_ignored(self) -> None:
"""Starting already running handler is ignored."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
with patch.object(handler, "_poll_loop", new_callable=AsyncMock):
await handler.start_polling()
task1 = handler._polling_task
await handler.start_polling() # Second start
task2 = handler._polling_task
# Should be the same task
assert task1 is task2
await handler.stop_polling()
class TestUpdateHandling:
"""Test update parsing and handling."""
@pytest.mark.asyncio
async def test_handle_valid_command(self) -> None:
"""Valid commands are executed."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
executed = False
async def test_command() -> None:
nonlocal executed
executed = True
handler.register_command("test", test_command)
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/test",
},
}
await handler._handle_update(update)
assert executed is True
@pytest.mark.asyncio
async def test_handle_unknown_command(self) -> None:
"""Unknown commands send help message."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/unknown",
},
}
await handler._handle_update(update)
# Should send error message
assert mock_post.call_count == 1
payload = mock_post.call_args.kwargs["json"]
assert "Unknown command" in payload["text"]
assert "/unknown" in payload["text"]
@pytest.mark.asyncio
async def test_ignore_unauthorized_chat(self) -> None:
"""Commands from unauthorized chats are ignored."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
executed = False
async def test_command() -> None:
nonlocal executed
executed = True
handler.register_command("test", test_command)
update = {
"update_id": 1,
"message": {
"chat": {"id": 999}, # Wrong chat_id
"text": "/test",
},
}
await handler._handle_update(update)
assert executed is False
@pytest.mark.asyncio
async def test_ignore_non_command_text(self) -> None:
"""Non-command text is ignored."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
executed = False
async def test_command() -> None:
nonlocal executed
executed = True
handler.register_command("test", test_command)
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "Hello, not a command",
},
}
await handler._handle_update(update)
assert executed is False
@pytest.mark.asyncio
async def test_handle_command_with_botname(self) -> None:
"""Commands with @botname suffix are handled correctly."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
executed = False
async def test_command() -> None:
nonlocal executed
executed = True
handler.register_command("start", test_command)
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/start@mybot",
},
}
await handler._handle_update(update)
assert executed is True
@pytest.mark.asyncio
async def test_handle_update_error_isolation(self) -> None:
"""Errors in handlers don't crash the system."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
async def failing_command() -> None:
raise ValueError("Test error")
handler.register_command("fail", failing_command)
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/fail",
},
}
# Should not raise exception
await handler._handle_update(update)
class TestTradingControlCommands:
"""Test trading control commands."""
@pytest.mark.asyncio
async def test_stop_command_pauses_trading(self) -> None:
"""Stop command clears pause event."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
# Create mock pause event
import asyncio
pause_event = asyncio.Event()
pause_event.set() # Initially active
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
async def mock_stop() -> None:
"""Mock /stop handler."""
if not pause_event.is_set():
await client.send_message("⏸️ Trading is already paused")
return
pause_event.clear()
await client.send_message(
"<b>⏸️ Trading Paused</b>\n\n"
"All trading operations have been suspended.\n"
"Use /resume to restart trading."
)
handler.register_command("stop", mock_stop)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/stop",
},
}
await handler._handle_update(update)
# Verify pause event was cleared
assert not pause_event.is_set()
# Verify message was sent
assert mock_post.call_count == 1
payload = mock_post.call_args.kwargs["json"]
assert "Trading Paused" in payload["text"]
@pytest.mark.asyncio
async def test_resume_command_resumes_trading(self) -> None:
"""Resume command sets pause event."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
# Create mock pause event (initially paused)
import asyncio
pause_event = asyncio.Event()
pause_event.clear() # Initially paused
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
async def mock_resume() -> None:
"""Mock /resume handler."""
if pause_event.is_set():
await client.send_message("▶️ Trading is already active")
return
pause_event.set()
await client.send_message(
"<b>▶️ Trading Resumed</b>\n\n"
"Trading operations have been restarted."
)
handler.register_command("resume", mock_resume)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/resume",
},
}
await handler._handle_update(update)
# Verify pause event was set
assert pause_event.is_set()
# Verify message was sent
assert mock_post.call_count == 1
payload = mock_post.call_args.kwargs["json"]
assert "Trading Resumed" in payload["text"]
@pytest.mark.asyncio
async def test_stop_when_already_paused(self) -> None:
"""Stop command when already paused sends appropriate message."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
# Create mock pause event (already paused)
import asyncio
pause_event = asyncio.Event()
pause_event.clear()
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
async def mock_stop() -> None:
"""Mock /stop handler."""
if not pause_event.is_set():
await client.send_message("⏸️ Trading is already paused")
return
pause_event.clear()
handler.register_command("stop", mock_stop)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/stop",
},
}
await handler._handle_update(update)
# Verify message was sent
payload = mock_post.call_args.kwargs["json"]
assert "already paused" in payload["text"]
@pytest.mark.asyncio
async def test_resume_when_already_active(self) -> None:
"""Resume command when already active sends appropriate message."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
# Create mock pause event (already active)
import asyncio
pause_event = asyncio.Event()
pause_event.set()
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
async def mock_resume() -> None:
"""Mock /resume handler."""
if pause_event.is_set():
await client.send_message("▶️ Trading is already active")
return
pause_event.set()
handler.register_command("resume", mock_resume)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/resume",
},
}
await handler._handle_update(update)
# Verify message was sent
payload = mock_post.call_args.kwargs["json"]
assert "already active" in payload["text"]
class TestStatusCommands:
"""Test status query commands."""
@pytest.mark.asyncio
async def test_status_command_shows_trading_info(self) -> None:
"""Status command displays mode, markets, and P&L."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
async def mock_status() -> None:
"""Mock /status handler."""
message = (
"<b>📊 Trading Status</b>\n\n"
"<b>Mode:</b> PAPER\n"
"<b>Markets:</b> Korea, United States\n"
"<b>Trading:</b> Active\n\n"
"<b>Current P&L:</b> +2.50%\n"
"<b>Circuit Breaker:</b> -3.0%"
)
await client.send_message(message)
handler.register_command("status", mock_status)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/status",
},
}
await handler._handle_update(update)
# Verify message was sent
assert mock_post.call_count == 1
payload = mock_post.call_args.kwargs["json"]
assert "Trading Status" in payload["text"]
assert "PAPER" in payload["text"]
assert "P&L" in payload["text"]
@pytest.mark.asyncio
async def test_status_command_error_handling(self) -> None:
"""Status command handles errors gracefully."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
async def mock_status_error() -> None:
"""Mock /status handler with error."""
await client.send_message(
"<b>⚠️ Error</b>\n\nFailed to retrieve trading status."
)
handler.register_command("status", mock_status_error)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/status",
},
}
await handler._handle_update(update)
# Should send error message
payload = mock_post.call_args.kwargs["json"]
assert "Error" in payload["text"]
@pytest.mark.asyncio
async def test_positions_command_shows_holdings(self) -> None:
"""Positions command displays account summary."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
async def mock_positions() -> None:
"""Mock /positions handler."""
message = (
"<b>💼 Account Summary</b>\n\n"
"<b>Total Evaluation:</b> ₩10,500,000\n"
"<b>Available Cash:</b> ₩5,000,000\n"
"<b>Purchase Total:</b> ₩10,000,000\n"
"<b>P&L:</b> +5.00%\n\n"
"<i>Note: Individual position details require API enhancement</i>"
)
await client.send_message(message)
handler.register_command("positions", mock_positions)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/positions",
},
}
await handler._handle_update(update)
# Verify message was sent
assert mock_post.call_count == 1
payload = mock_post.call_args.kwargs["json"]
assert "Account Summary" in payload["text"]
assert "Total Evaluation" in payload["text"]
assert "P&L" in payload["text"]
@pytest.mark.asyncio
async def test_positions_command_empty_holdings(self) -> None:
"""Positions command handles empty portfolio."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
async def mock_positions_empty() -> None:
"""Mock /positions handler with no positions."""
message = (
"<b>💼 Account Summary</b>\n\n"
"No balance information available."
)
await client.send_message(message)
handler.register_command("positions", mock_positions_empty)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/positions",
},
}
await handler._handle_update(update)
# Verify message was sent
payload = mock_post.call_args.kwargs["json"]
assert "No balance information available" in payload["text"]
@pytest.mark.asyncio
async def test_positions_command_error_handling(self) -> None:
"""Positions command handles errors gracefully."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
async def mock_positions_error() -> None:
"""Mock /positions handler with error."""
await client.send_message(
"<b>⚠️ Error</b>\n\nFailed to retrieve positions."
)
handler.register_command("positions", mock_positions_error)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/positions",
},
}
await handler._handle_update(update)
# Should send error message
payload = mock_post.call_args.kwargs["json"]
assert "Error" in payload["text"]
class TestBasicCommands:
"""Test basic command implementations."""
@pytest.mark.asyncio
async def test_help_command_content(self) -> None:
"""Help command lists all available commands."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
async def mock_help() -> None:
"""Mock /help handler."""
message = (
"<b>📖 Available Commands</b>\n\n"
"/help - Show available commands\n"
"/status - Trading status (mode, markets, P&L)\n"
"/positions - Current holdings\n"
"/stop - Pause trading\n"
"/resume - Resume trading"
)
await client.send_message(message)
handler.register_command("help", mock_help)
with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
update = {
"update_id": 1,
"message": {
"chat": {"id": 456},
"text": "/help",
},
}
await handler._handle_update(update)
# Verify message was sent
assert mock_post.call_count == 1
payload = mock_post.call_args.kwargs["json"]
assert "Available Commands" in payload["text"]
assert "/help" in payload["text"]
assert "/status" in payload["text"]
assert "/positions" in payload["text"]
assert "/stop" in payload["text"]
assert "/resume" in payload["text"]
class TestGetUpdates:
"""Test getUpdates API interaction."""
@pytest.mark.asyncio
async def test_get_updates_success(self) -> None:
"""getUpdates fetches and parses updates."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(
return_value={
"ok": True,
"result": [
{"update_id": 1, "message": {"text": "/test"}},
{"update_id": 2, "message": {"text": "/help"}},
],
}
)
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.post", return_value=mock_resp):
updates = await handler._get_updates()
assert len(updates) == 2
assert updates[0]["update_id"] == 1
assert updates[1]["update_id"] == 2
assert handler._last_update_id == 2
@pytest.mark.asyncio
async def test_get_updates_api_error(self) -> None:
"""getUpdates handles API errors gracefully."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
mock_resp = AsyncMock()
mock_resp.status = 400
mock_resp.text = AsyncMock(return_value="Bad Request")
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.post", return_value=mock_resp):
updates = await handler._get_updates()
assert updates == []
@pytest.mark.asyncio
async def test_get_updates_empty_result(self) -> None:
"""getUpdates handles empty results."""
client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
handler = TelegramCommandHandler(client)
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(return_value={"ok": True, "result": []})
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.post", return_value=mock_resp):
updates = await handler._get_updates()
assert updates == []

View File

@@ -2,6 +2,7 @@
from __future__ import annotations
import asyncio
import sqlite3
from typing import Any
from unittest.mock import AsyncMock
@@ -338,6 +339,28 @@ class TestMarketScanner:
assert metrics.stock_code == "AAPL"
assert metrics.current_price == 150.50
@pytest.mark.asyncio
async def test_scan_stock_overseas_empty_price(
self,
scanner: MarketScanner,
mock_overseas_broker: OverseasBroker,
context_store: ContextStore,
) -> None:
"""Test scanning overseas stock with empty price string (issue #49)."""
mock_overseas_broker.get_overseas_price.return_value = {
"output": {
"last": "", # Empty string
"tvol": "", # Empty string
}
}
market = MARKETS["US_NASDAQ"]
metrics = await scanner.scan_stock("AAPL", market)
assert metrics is not None
assert metrics.stock_code == "AAPL"
assert metrics.current_price == 0.0 # Should default to 0.0
@pytest.mark.asyncio
async def test_scan_stock_error_handling(
self,
@@ -509,3 +532,45 @@ class TestMarketScanner:
new_additions = [code for code in updated if code not in current_watchlist]
assert len(new_additions) <= 1
assert len(updated) == len(current_watchlist)
@pytest.mark.asyncio
async def test_scan_market_respects_concurrency_limit(
self,
mock_broker: KISBroker,
mock_overseas_broker: OverseasBroker,
volatility_analyzer: VolatilityAnalyzer,
context_store: ContextStore,
) -> None:
"""scan_market should limit concurrent scans to max_concurrent_scans."""
max_concurrent = 2
scanner = MarketScanner(
broker=mock_broker,
overseas_broker=mock_overseas_broker,
volatility_analyzer=volatility_analyzer,
context_store=context_store,
top_n=5,
max_concurrent_scans=max_concurrent,
)
# Track peak concurrency
active_count = 0
peak_count = 0
original_scan = scanner.scan_stock
async def tracking_scan(code: str, market: Any) -> VolatilityMetrics:
nonlocal active_count, peak_count
active_count += 1
peak_count = max(peak_count, active_count)
await asyncio.sleep(0.05) # Simulate API call duration
active_count -= 1
return VolatilityMetrics(code, 50000, 500, 1.0, 1.0, 1.0, 1.0, 10.0, 50.0)
scanner.scan_stock = tracking_scan # type: ignore[method-assign]
market = MARKETS["KR"]
stock_codes = ["001", "002", "003", "004", "005", "006"]
await scanner.scan_market(market, stock_codes)
assert peak_count <= max_concurrent