Write, register, and debug PyBroker indicators using the bundled PyBroker wiki references generated from the local docs. Use when an agent needs to write custom indicator functions with pybroker.indicator, vectorize indicator logic with NumPy and Numba @njit…
Register, train, wire, and debug machine learning models for PyBroker backtests using the bundled PyBroker wiki references generated from the local docs. Use when an agent needs to register a model with pybroker.model, write train_fn/predict_fn code for…
Build, wire, and debug multi-timeframe PyBroker strategies using the bundled PyBroker wiki references generated from the local docs. Use when an agent needs to trade a base timeframe with confirmation from coarser weekly or monthly bars, compress bars into…
Tune PyBroker strategy hyperparameters with Optuna-backed search using the bundled PyBroker wiki references generated from the local docs. Use when an agent needs to declare tunable values with pybroker.hyperparam, run Strategy.optimize with grid, TPE, or…
Build ranked-signal and rotational PyBroker strategies using the bundled PyBroker wiki references generated from the local docs. Use when an agent needs to rank symbols with ctx.long_score or ctx.short_score, cap positions with Strategy.set_max_long_positions…
Create, adapt, review, and debug PyBroker algorithmic trading strategy and backtest code using the bundled PyBroker wiki references generated from the local docs. Use when an agent needs to turn trading rules into PyBroker Strategy/ExecContext logic, add…
Rigorously triage a single Dependabot (or Renovate) dependency version-bump PR: pull the real changelog/release notes across the full old->new version range (not the PyPI summary blurb), map it against actual usage sites in this codebase, write a migration…