mt5forge 1.0.2

Production-grade Python MT5 trading infrastructure library

MT5Forge

Production-grade Python trading infrastructure for MetaTrader 5.

MT5Forge is a modular framework that transforms the raw MetaTrader 5 Python API into a structured, extensible, and production-ready trading platform.

Instead of writing trading bots that directly interact with MT5, developers build strategies on top of MT5Forge while the framework handles:

• MT5 connectivity
• Session management
• Market data
• Order execution
• Risk management
• Trade lifecycle
• Notifications
• Monitoring
• Logging
• Backtesting

---

Why MT5Forge?

Most trading bots eventually become difficult to maintain because strategy logic becomes tightly coupled with:

• MT5 API calls
• Risk management
• Trade management
• Notifications
• Error handling

MT5Forge separates these concerns.

Your strategy only decides:

BUY
SELL
HOLD

Everything else is managed by the framework.

---

Features

Trading Infrastructure

• MT5 connection management
• Automatic reconnection
• Session validation
• Broker health monitoring

Market Data

• Candlestick retrieval
• Tick feeds
• Spread monitoring
• Symbol information
• Market hours detection

Order Execution

• Market orders
• Pending orders
• Order modification
• Partial close support
• Retry policies

Risk Management

• Dynamic lot sizing
• Drawdown protection
• Daily loss limits
• Exposure controls
• Margin validation

Trade Management

• Take profit management
• Stop loss management
• Trailing stops
• Breakeven automation
• Trade lifecycle tracking

Strategies

Built-in strategies:

• Moving Average Crossover
• MACD
• Hedge Recovery

Notifications

Supported channels:

• Telegram
• Discord
• Slack
• Email
• Webhooks
• Console
• File Logging

Backtesting

• Historical replay
• Slippage simulation
• Spread simulation
• Performance analytics

---

Installation

Requirements

• Python 3.11+
• Windows 10 or Windows 11
• MetaTrader 5 Terminal installed

---

Install from PyPI

pip install mt5forge

or

uv add mt5forge

---

Development Installation

git clone https://github.com/NeuroFx-Algotrading/mt5forge.git

cd mt5forge

uv sync

uv pip install -e ".[dev]"

---

Quick Start

Step 1 – Create Credentials

from mt5forge.connection import MT5Credentials

credentials = MT5Credentials(
    account=12345678,
    password="your_password",
    server="YourBroker-Demo",
)

---

Step 2 – Load Configuration

from mt5forge.config import ConfigLoader

config = ConfigLoader.from_toml(
    "mt5forge.config.toml"
)

---

Step 3 – Create Engine

from mt5forge import TradingEngine

engine = TradingEngine(config)

---

Step 4 – Login

engine.login(credentials)

---

Step 5 – Start Trading

engine.start()

---

First Strategy

from mt5forge.strategies import (
    MACrossoverStrategy,
    MACrossoverConfig,
)

strategy = MACrossoverStrategy(
    MACrossoverConfig(
        fast_ma=21,
        slow_ma=50,
        trend_ma=200,
    )
)

engine.register_strategy(strategy)
engine.start()

---

Market Data Example

from mt5forge.market import MarketDataFeed

feed = MarketDataFeed()

candles = feed.get_candles(
    symbol="EURUSD",
    timeframe="H1",
    count=500,
)

print(candles.tail())

---

Order Execution Example

from mt5forge.orders import OrderRequest
from mt5forge.enums import OrderType

request = OrderRequest(
    symbol="EURUSD",
    order_type=OrderType.BUY,
    lot=0.10,
)

result = engine.order_manager.place_market_order(
    request
)

print(result.success)

---

Custom Strategy Example

from mt5forge.strategies import (
    StrategyBase,
    Signal,
    SignalDirection,
)

class MyStrategy(StrategyBase):

    name = "my_strategy"

    def on_candle(
        self,
        symbol,
        timeframe,
        candles,
    ):
        if condition:
            return Signal(
                direction=SignalDirection.BUY,
                symbol=symbol,
            )

        return None

---

Telegram Notifications

from mt5forge.notifications.channels import (
    TelegramChannel,
)

channel = TelegramChannel(
    config.notifications.telegram
)

engine.notification_bus.register_channel(
    channel
)

---

Running a Backtest

from datetime import datetime

from mt5forge.backtest import (
    BacktestRunner,
)

runner = BacktestRunner(config)

result = runner.run(
    strategy=strategy,
    symbol="EURUSD",
    timeframe="H1",
    start=datetime(2024, 1, 1),
    end=datetime(2024, 12, 31),
)

print(result.net_profit)
print(result.win_rate)

---

Project Structure

mt5forge/
├── core/
├── connection/
├── market/
├── orders/
├── positions/
├── risk/
├── trade/
├── hedge/
├── conditions/
├── indicators/
├── strategies/
├── backtest/
├── notifications/
├── monitoring/
├── logging/
└── config/

---

Documentation

Additional documentation is available in:

docs/
├── architecture.md
├── strategy_guide.md
├── risk_management.md
├── notification_channels.md
├── backtesting_guide.md
└── api_reference.md

---

Running Tests

uv run pytest

Coverage:

uv run pytest --cov=mt5forge

---

Contributing

uv run ruff check .

uv run mypy mt5forge

uv run pytest

Please ensure all tests pass before submitting changes.

---

Security

Never commit:

• Broker passwords
• API keys
• Telegram bot tokens
• SMTP credentials

Use environment variables or secure secret storage.

---

License

MIT License

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Disclaimer

This software executes real trades and can result in financial loss.

Always test strategies in a demo environment before deploying to a live account.

Use at your own risk.