CoffeeScript vs. JavaScript vs. NumPy vs. Python RPA Comparison Chart

Underneath that awkward Java-esque patina, JavaScript has always had a gorgeous heart. CoffeeScript is an attempt to expose the good parts of JavaScript in a simple way. The golden rule of CoffeeScript is: “It’s just JavaScript.” The code compiles one-to-one into the equivalent JS, and there is no interpretation at runtime. You can use any existing JavaScript library seamlessly from CoffeeScript (and vice-versa). The compiled output is readable, pretty printed, and tends to run as fast or faster than the equivalent handwritten JavaScript. Most modern JavaScript features that CoffeeScript supports can run natively in Node 7.6+, meaning that Node can run CoffeeScript’s output without any further processing required. This list may be incomplete, and excludes versions of Node that support newer features behind flags; please refer to node.green for full details. You can run the tests in your browser to see what your browser supports.

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.