mt5-trading
Comprehensive MetaTrader 5 Python algotrading knowledge base covering the official synchronous API, polling-based event systems, order execution with fill modes, historical data functions, reconnection resilience, and Windows production deployment. Includes aiomql and ZeroMQ bridge alternatives. TRIGGER WHEN: building, implementing, writing, coding, creating, optimizing, or debugging MT5 trading systems with Python. DO NOT TRIGGER WHEN: the task is outside the specific scope of this component.
What this skill does
# MetaTrader 5 Python Algotrading Knowledge base for building production-grade algorithmic trading systems with MetaTrader 5 Python API. ## When to Use - Connecting to MT5 terminal via the official Python API - Building polling-based event systems (on_tick, on_new_candle, on_position) - Executing orders with correct fill modes (FOK, IOC, Return) - Downloading historical data (copy_rates, copy_ticks) - Handling MT5 disconnections and terminal restarts - Deploying MT5 bots on Windows with process monitoring - Choosing between official API, aiomql, and ZeroMQ bridge ## Quick Start For 80% of use cases, start with: 1. **Library**: `pip install MetaTrader5` (official) or `pip install aiomql` (async wrapper) 2. **Connection**: `mt5.initialize(path=..., login=..., server=..., password=...)` 3. **Event system**: polling loop with candle/tick/position change detection 4. **Orders**: `order_check()` before `order_send()`, always detect fill mode dynamically 5. **Risk**: server-side SL/TP on every position (non-negotiable) 6. **Resilience**: health check every 30-60s, psutil process monitoring, exponential backoff Then harden incrementally: - Silent errors -- wrap every API call with None check + last_error() - Fill mode rejections (10030) -- dynamic filling_mode detection per symbol - Terminal crashes -- psutil watchdog + subprocess restart - Weekend handling -- datetime.weekday() sleep mode ## Reference Materials - `api-architecture.md` -- MT5 Python API architecture, 32 functions, named pipes IPC, MQL5 EA vs Python, library comparison - `event-system-polling.md` -- polling patterns, new candle detection, tick monitoring, position tracking, concurrency rules - `order-execution.md` -- order_send, fill modes (FOK/IOC/Return), hedging vs netting, retcodes, risk checks, magic numbers - `data-feed-historical.md` -- copy_rates, copy_ticks, depth, timezone caveats, caching, data quality, broker differences - `production-resilience.md` -- disconnection handling, reconnection, weekend management, Windows deployment, community resources ## Key Decision Points | Decision | Default | Upgrade When | |----------|---------|-------------| | Library | Official MetaTrader5 | Need async: aiomql. Need true streaming: ZeroMQ bridge | | Event model | Polling (1-5s interval) | Tick-sensitive: poll 100-250ms. True events: ZeroMQ EA bridge | | Fill mode | Detect dynamically per symbol | Never hardcode -- changes between brokers/symbols | | Account mode | Hedging (most forex brokers) | Check account_info().margin_mode at startup | | Data caching | Parquet + Zstandard | Tick data -- partition by day/month | | Concurrency | asyncio (single thread) | Multi-account -- separate processes per terminal | | Backtesting | Python framework (Backtrader, Backtesting.py) | Need MT5 tester -- MQL5 EA wrapper | | SL/TP | Server-side always | Python trailing only as supplement, never as sole protection |
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