Changed _init_db() from DROP+CREATE to CREATE IF NOT EXISTS so that
trade history, candle data, and daily PnL survive container restarts.
Previously all tables were dropped on every parser start, losing
historical data if log files had been rotated.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Parse position monitor logs (5min interval) to update current_price,
unrealized_pnl and unrealized_pnl_pct in bot_status. Position cards
now display USDT amount and percentage, colored green/red. Falls back
to entry/current price calculation if monitor data unavailable.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add [SYMBOL] prefix to all bot/user_data_stream log messages
- Rewrite log_parser.py with multi-symbol regex, per-symbol state tracking, symbol columns in DB schema
- Rewrite dashboard_api.py with /api/symbols endpoint, symbol query params on all endpoints, SQL injection fix
- Update App.jsx with symbol filter tabs, multi-position display, dynamic header
- Add tests for log parser (8 tests) and dashboard API (7 tests)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Include RSI, MACD_H, ATR in bot entry log so the log parser can
extract and store them in the trades DB for dashboard display
- Update log parser regex and _handle_entry() to persist indicator values
- Add dashboard section to README (tech stack, screens, API endpoints)
- Add dashboard/ directory to project structure in README
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Log parser: fix entry dedup to check direction instead of price tolerance,
preventing duplicate OPEN trades for the same position
- Log parser: close all OPEN trades on position close, delete stale duplicates
- Jenkinsfile: detect changed files and only build/deploy affected services,
allowing dashboard-only changes without restarting the bot
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Introduced a new trading dashboard consisting of a FastAPI backend (`dashboard-api`) for data retrieval and a React frontend (`dashboard-ui`) for visualization.
- Implemented a log parser to monitor and store bot logs in an SQLite database.
- Configured Docker setup for both API and UI, including necessary Dockerfiles and a docker-compose configuration.
- Added setup documentation for running the dashboard and accessing its features.
- Enhanced the Jenkins pipeline to build and push the new dashboard images.