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Python Developers

For Python developers who want to manage strategy experiments with a CLI/JSON-first workflow.

Why AlphaForge Fits Python Developers

  • Strategies are JSON — declaratively manage parameters without writing boilerplate code
  • CLI supports structured output — use --json flag to pipe results into your own scripts
  • Optuna-based optimization — integrates naturally with the Python ecosystem
  • uv project structure — coexists with your existing Python code in a monorepo

Basic Usage

# Get backtest results as JSON and pipe to custom script
forge backtest run QQQ --strategy my_strategy --json | python analyze.py

# Optuna optimization (maximize Sharpe ratio)
forge optimize run QQQ --strategy my_strategy --trials 200 --objective sharpe

# Walk-forward validation
forge optimize walk-forward QQQ --strategy my_strategy --folds 5

Managing Strategies as JSON

AlphaForge strategies are defined in JSON files — easy to version-control and diff.

{
  "name": "my_strategy",
  "indicators": [
    { "id": "rsi", "period": 14 },
    { "id": "bbands", "period": 20 }
  ],
  "entry": { "rsi_lt": 30, "price_lt_lower_band": true },
  "exit": { "rsi_gt": 70 },
  "risk": { "max_position_size": 0.1 }
}