COBOL vs. Component Pascal vs. JavaScript vs. NumPy Comparison Chart

Component Pascal is a general-purpose language in the tradition of Pascal, Modula-2, and Oberon. Its most important features are block structure, modularity, separate compilation, static typing with strong type checking (also across module boundaries), type extension with methods, dynamic loading of modules, and garbage collection. Type extension makes Component Pascal an object-oriented language. An object is a variable of an abstract data type consisting of private data (its state) and procedures that operate on this data. Abstract data types are declared as extensible records. Component Pascal covers most terms of object-oriented languages by the established vocabulary of imperative languages in order to minimize the number of notions for similar concepts. Complete type safety and the requirement of a dynamic object model make Component Pascal a component-oriented language.

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.