pandas-ta-classic

Paste this into your AI agent. Write the first line, or take a suggestion; the copy carries your words.

Source: https://github.com/xgboosted/pandas-ta-classic — clone it and read its README and examples before writing anything; its documented setup beats what you remember.
Stack: a pandas DataFrame extension — df.ta.sma(), df.ta.rsi(), and 280-plus more, with a Strategy object for running many indicators at once; native Python candlestick patterns need no TA-Lib.
Needs: Python and pandas; TA-Lib only if you pass talib=True for core indicators, numba only for the optional hot-loop speedups.
Start: `pip install pandas-ta-classic` (or `uv pip install pandas-ta-classic`), then df.ta.sma(length=20, append=True) and df.ta.rsi(append=True) on a DataFrame loaded from CSV.
Limit: not every TA-Lib/tulipy function has a pandas-ta-classic counterpart — check docs/indicator_support_matrix.rst for current coverage before assuming parity.
Done means: you show me my DataFrame with the new indicator columns appended, and the code you wrote.
Before you start, ask me: which indicators I want, and whether my OHLCV data is already loaded or needs fetching (e.g. via yfinance).