Mt5

MetaTrader 5 Python Algotrading

Knowledge base for building production-grade algorithmic trading systems with MetaTrader 5 Python API.

What varies per broker

MetaTrader 5 is one piece of software; the broker behind a given login decides most of what an integration actually has to handle. Nothing below is restated in full here, each item is detailed in the file already named for it, because a reader chasing the symptom will already be looking there:

• Order execution parameters. Fill mode, stops level, freeze level, execution mode and volume limits are broker- and symbol-specific and must be queried at runtime rather than assumed. See order-execution.md, and the Fill mode and Account mode rows of Key Decision Points below.
• Data quality and coverage. Tick volume, tick history depth and tick fidelity differ between ECN brokers and market makers for the same instrument, which makes cross-broker comparison invalid. See data-feed-historical.md.
• Account and margin mode. Netting, hedging and exchange margin modes are a broker setting, not a code choice, read at startup from account_info().margin_mode. See the Account mode row of Key Decision Points below.

None of this is optional hardening. A value correct for one broker is routinely wrong for the next, which is the reason this plugin's scope is multi-broker-platform rather than single-broker: nothing in this skill is measured against one broker's behaviour and then offered as true of MetaTrader 5 in general.

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

Symptoms to entry points

Key Decision Points