Cython vs. NumPy vs. Python RPA vs. QBasic 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.

QBasic as well as QuickBasic is an easy-to-learn programming language (and therefore ideal for beginners), based on DOS operating system, but also executable on Windows. QBasic is the slimmed-down version of QuickBasic. Compared to QuickBasic, QBasic is limited as it lacks a compiler. Therefore QBasic cannot be used to produce executables (.exe files). The source code (usual files with .bas extension) can only be executed immediately by the built-in QBasic interpreter. Furthermore, QuickBasic has a more extensive command set than QBasic. The best way to learn to program is to start with a lightweight programming language and a simple compiler. Qbasic (short: QB) has great advantages for pros and beginners that other compilers can't offer. Back then, when DOS was the most widely used operating system, QB IDE enjoyed great popularity. On current Windows systems, QBasic/QuickBASIC requires a DOS emulator, e.g. DOSBox.