Numexpr: Fast numerical array expression evaluator for Python, NumPy, Pandas
NumExpr is a fast numerical expression evaluator designed for NumPy that enhances performance and reduces memory usage. It achieves this by avoiding memory allocation for intermediate results and utilizing multi-threading capabilities. Users can install NumExpr via pip or conda, with additional support for Intel's MKL for improved performance on certain operations.
- ▪NumExpr accelerates array operations and uses less memory compared to standard Python calculations.
- ▪The performance improvements can range from 0.95x to 15x depending on the complexity of the expressions.
- ▪NumExpr is available for installation via pip and conda, with specific instructions for different operating systems.
Opening excerpt (first ~120 words) tap to expand
NumExpr: Fast numerical expression evaluator for NumPy Author: David M. Cooke, Francesc Alted, and others. Maintainer:Francesc Alted Contact: [email protected] URL:https://github.com/pydata/numexpr Documentation:http://numexpr.readthedocs.io/en/latest/ GitHub Actions: PyPi: DOI: readthedocs: What is NumExpr? NumExpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like '3*a+4*b') are accelerated and use less memory than doing the same calculation in Python. In addition, its multi-threaded capabilities can make use of all your cores -- which generally results in substantial performance scaling compared to NumPy.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.