Developers
Start locally with synthetic data, evaluate safely, then experiment with paper/sandbox gateways before going live.
Quickstart
pip install -r requirements.txt python -m bot_trade.tools.gen_synth_data --symbol BTCUSDT --frame 1m --out data_ready python -m bot_trade.train_rl --algorithm PPO --symbol BTCUSDT --frame 1m --device cpu --n-envs 1 --total-steps 128 --headless --allow-synth --data-dir data_ready python -m bot_trade.tools.eval_run --symbol BTCUSDT --frame 1m --run-id latest --tearsheet # Hyperparameter sweep python -m bot_trade.tools.sweep --mode random --n-trials 4 --symbol BTCUSDT --frame 1m --algorithm SAC --continuous-env --headless --allow-synth --data-dir data_ready
The commands above produce artifacts, a tearsheet PDF and a ranked summary for sweeps.
Key CLI
python -m bot_trade.train_rl— training orchestration.python -m bot_trade.tools.eval_run— evaluation & PDF tearsheet.python -m bot_trade.tools.sweep— random/grid sweeps.python -m bot_trade.tools.dev_checks— integrity & artifact gates.python -m bot_trade.tools.panel_gui— local control panel.
Configs & Modes
Data sources: CSV/Parquet or ccxt live collectors. Modes: raw/live. Gateways: paper/sandbox. Regime controller and risk rules are configurable.
Artifacts & Logs
CSV/JSON/PNG artifacts are written periodically. Risk and decisions are exported as JSONL decision logs for audits; knowledge base snapshots track run metadata.
Safety & Promotion
Use canary → shadow → production with objective thresholds on stability and slippage. Circuit-breakers and exposure caps are enforced at runtime.