TA-Lib (Python)
Python bindings for TA-Lib's 150-plus technical indicators
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Overview
TA-Lib (Python) provides Cython-based Python bindings to the TA-Lib C library's 150-plus technical indicators and candlestick pattern recognition.
- ForPython developers who want the original TA-Lib indicator set on numpy arrays or pandas/Polars DataFrames.
- Needsthe TA-Lib C library installed first (via Homebrew, an installer, or Conda Forge), then the Python package.
- RunsCython bindings to the C library, with both a function API (numpy arrays) and an abstract API (DataFrames).
- Limitthe underlying C library must be installed separately before the Python package will build — most install failures are the missing C library, not the Python package.
Vibe it
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Source: https://github.com/TA-Lib/ta-lib-python — clone it and read its README and examples before writing anything; its documented setup beats what you remember. Stack: Cython bindings over the TA-Lib C library, with a function API on numpy arrays and an abstract API on Polars/pandas DataFrames. Needs: the TA-Lib C library installed first (Homebrew on Mac, the MSI installer on Windows, or build-from-source on Linux), then the Python package. Start: install the C library for my OS, then `python -m pip install TA-Lib`, then talib.RSI(close, 14) on a numpy array before moving to the abstract API. Limit: most install failures are the missing C library, not the Python package — install it first and separately. Done means: you show me the RSI (or another indicator) computed on my own price series, and the exact install steps you ran for my OS. Before you start, ask me: whether my data is a numpy array or a pandas/Polars DataFrame.
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