Coverage.py vs. Python vs. Ring vs. TypeScript Comparison Chart

Coverage.py is a tool for measuring code coverage of Python programs. It monitors your program, noting which parts of the code have been executed, then analyzes the source to identify code that could have been executed but was not. Coverage measurement is typically used to gauge the effectiveness of tests. It can show which parts of your code are being exercised by tests, and which are not. Use coverage run to run your test suite and gather data. However you normally run your test suite, and you can run your test runner under coverage. If your test runner command starts with “python”, just replace the initial “python” with “coverage run”. To limit coverage measurement to code in the current directory, and also find files that weren’t executed at all, add the source argument to your coverage command line. By default, it will measure line (statement) coverage. It can also measure branch coverage. It can tell you what tests ran which lines.

The Ring is a practical general-purpose multi-paradigm language. The supported programming paradigms are imperative, procedural, object-oriented, declarative using nested structures, functional, meta programming and natural programming. The language is portable (Windows, Linux, macOS, Android, WebAssembly, etc.) and can be used to create Console, GUI, Web, Games and Mobile applications. The language is designed to be simple, small and flexible. The language is simple, trying to be natural, encourage organization and comes with transparent and visual implementation. It comes with compact syntax and a group of features that enable the programmer to create natural interfaces and declarative domain-specific languages in a fraction of time. It is very small, flexible and comes with smart garbage collector that puts the memory under the programmer control. It supports many programming paradigms, comes with useful and practical libraries.