TiPortfolio

Backtest, simulate, or evaluate a portfolio strategy, allocation, rebalancing plan, or DCA/AIP using the tiportfolio CLI. Triggers on "backtest QQQ BIL GLD", "60/40 portfolio", "monthly DCA $1000 into SPY", "risk parity backtest", "buy and hold AAPL", "compare 1x vs 2x leverage", or tickers named with allocation ratios and a time period.

Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.