Cygwin vs. NumPy vs. Python vs. SourceDebug 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.

SourceDebug is a fast powerful project-oriented programming editor, code browser, and debugger that helps you understand code while you work and plan. SourceDebug has built-in dynamic analysis for C/C++, Objective-C, and more. SourceDebug can debug application with source code in different locations. SourceDebug integrates editing, browsing, compiling and debugging functions for local and remote projects. It can be used to learn an existing code base quickly, and get up to speed on new projects. SourceDebug parses your whole project and lets you navigate and edit code like a breeze. It can jump easily to variables, functions or include files. Smart Bookmark can record the browsing location and play back when needed. Supports GDB or LLDB-MI debug over SSH, ADB, Telnet , Rlogin and Local Cygwin. GDB server debug is also supported. Show Quickwatch, Watches, Callstack, Variables, Memory, Breakpoint List, Disassemble and Thread List as needed. Sftp, Ftp and Local drives are supported.