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About NumPy
Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.
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"Excellent Python math library" Posted 2022-08-03
Pros: - used for scientific computing
- huge variety of mathematical functions, random number generators, etc.
- supports a wide variety of hardware and GPU acceleration
- very fast code that runs in C, despite working with Python
- simple syntax makes it easy to learn
- good documentation
- free and open sourceCons: - there aren't many cons to using NumPy; it's a mainstay of the Python computing community for a reason
Overall: NumPy is an essential part of the Python ecosystem. It provides a huge variety of mathematical functions in a very performant library for free.
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