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Spyder (software) Spyder is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language. Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software.
Xojo. The Xojo programming environment and programming language is developed and commercially marketed by Xojo, Inc. of Austin, Texas for software development targeting macOS, Microsoft Windows, Linux, iOS, Android, the Web and Raspberry Pi. Xojo uses a proprietary object-oriented language.
Anaconda is a distribution of the Python and R programming languages for scientific computing ( data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. The distribution includes data-science packages suitable for Windows, Linux, and macOS.
Mingw-w64. Mingw-w64 is a free and open-source suite of developments tools that generate Portable Executable (PE) binaries for Microsoft Windows. It was forked in 2005–2010 from MinGW ( Minimalist GNU for Windows ). Mingw-w64 includes a port of the GNU Compiler Collection (GCC), GNU Binutils for Windows ( assembler, linker, archive manager ...
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PureBasic IDE 5.10. PureBasic is a commercially distributed procedural computer programming language and integrated development environment based on BASIC and developed by Fantaisie Software for Windows, Linux, and macOS. An Amiga version is available, although it has been discontinued and some parts of it are released as open-source.
The SPYDER is a low-level, quick-reaction surface-to-air missile system capable of engaging aircraft, helicopters, unmanned air vehicles, drones, cruise missiles and precision-guided munitions. It provides air defence for fixed assets and for point and area defence for mobile forces in combat areas.
PyPy. PyPy ( / ˈpaɪpaɪ /) is an implementation of the Python programming language. [2] PyPy often runs faster than the standard implementation CPython because PyPy uses a just-in-time compiler. [3] Most Python code runs well on PyPy except for code that depends on CPython extensions, which either does not work or incurs some overhead when ...