CVXOPT vs. NumPy vs. Python vs. tox Comparison Chart

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.

tox aims to automate and standardize testing in Python. It is part of a larger vision of easing the packaging, testing and release process of Python software. tox is a generic virtualenv management and test command-line tool you can use for checking that your package installs correctly with different Python versions and interpreters, running your tests in each of the environments, configuring your test tool of choice, and acting as a frontend to continuous integration servers, greatly reducing boilerplate and merging CI and shell-based testing. First, install tox with pip install tox. Then put basic information about your project and the test environments you want your project to run in into a tox.ini file residing right next to your setup.py file. You can also try generating a tox.ini file automatically, by running tox-quickstart and then answering a few simple questions. Install and test your project against Python2.7 and Python3.6.